hexsha
stringlengths 40
40
| size
int64 4
1.02M
| ext
stringclasses 8
values | lang
stringclasses 1
value | max_stars_repo_path
stringlengths 4
209
| max_stars_repo_name
stringlengths 5
121
| max_stars_repo_head_hexsha
stringlengths 40
40
| max_stars_repo_licenses
listlengths 1
10
| max_stars_count
int64 1
191k
⌀ | max_stars_repo_stars_event_min_datetime
stringlengths 24
24
⌀ | max_stars_repo_stars_event_max_datetime
stringlengths 24
24
⌀ | max_issues_repo_path
stringlengths 4
209
| max_issues_repo_name
stringlengths 5
121
| max_issues_repo_head_hexsha
stringlengths 40
40
| max_issues_repo_licenses
listlengths 1
10
| max_issues_count
int64 1
67k
⌀ | max_issues_repo_issues_event_min_datetime
stringlengths 24
24
⌀ | max_issues_repo_issues_event_max_datetime
stringlengths 24
24
⌀ | max_forks_repo_path
stringlengths 4
209
| max_forks_repo_name
stringlengths 5
121
| max_forks_repo_head_hexsha
stringlengths 40
40
| max_forks_repo_licenses
listlengths 1
10
| max_forks_count
int64 1
105k
⌀ | max_forks_repo_forks_event_min_datetime
stringlengths 24
24
⌀ | max_forks_repo_forks_event_max_datetime
stringlengths 24
24
⌀ | content
stringlengths 4
1.02M
| avg_line_length
float64 1.07
66.1k
| max_line_length
int64 4
266k
| alphanum_fraction
float64 0.01
1
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
f0ce7aaaf1a3b11fc9d159b0720225ac7679497c
| 11,667
|
py
|
Python
|
convert-2d.py
|
dcm684/lasercut
|
f459a9b9d73987e1a581728a51b031fb7aaea653
|
[
"BSD-2-Clause"
] | null | null | null |
convert-2d.py
|
dcm684/lasercut
|
f459a9b9d73987e1a581728a51b031fb7aaea653
|
[
"BSD-2-Clause"
] | null | null | null |
convert-2d.py
|
dcm684/lasercut
|
f459a9b9d73987e1a581728a51b031fb7aaea653
|
[
"BSD-2-Clause"
] | null | null | null |
"""
Process a lasercut box to enable its production on a laser cutter, 3D printer, or other comparable device
Processes a given 3D OpenSCAD scad file using the lasercut library to create a file with the sides that can be used
by a laser cutter. Or if ff a value for extrusion thickness is given, the exported file would be 3D and
could be used by a 3D printer
The OpenSCAD executable is expected to be at the default location for the current operating system
- Linux - openscad
- OSX - /Applications/OpenSCAD.app/Contents/MacOS/OpenSCAD
- Windows - "Program Files\\OpenSCAD\\openscad.exe" or "Program Files(x86)\\OpenSCAD\\openscad.exe"
The path to the executable can also be set via the "OPENSCAD_BIN" environmental variable or the --openscadbin option
"""
import os
import argparse
import subprocess
import textwrap
extensions_3d = ['.stl', '.off', '.amf', '.3mf']
extensions_2d = ['.dxf', '.svg', '.pdf']
extensions_valid = ['.scad', '.csg'] + extensions_3d + extensions_2d
def exit_with_error(error_str: str) -> None:
"""
Print the given string before exiting the script
:param error_str: String to print
:return: None
"""
print(error_str)
exit(1)
def get_openscad_path() -> str:
"""
Tries to determine the path to the openscad binary
Can determine path if OS is OSX, Windows (32-bit and 64-bit installations),
and Linux. Path is based on OS. The default installation paths are checked.
If the environmental value "OPENSCAD_BIN" is set that value will be used
without checking if the binary exists there.
:return: Expected path to openscad
"""
out_path = None
enviro_val = os.environ.get("OPENSCAD_BIN")
if enviro_val is not None:
if not os.path.isfile(enviro_val):
exit_with_error(f'Invalid environmental value for the path to '
f'OpenSCAD binary, OPENSCAD_BIN: "{enviro_val}"')
out_path = enviro_val
else:
import platform
python_platform = platform.platform()
if "Darwin" in python_platform:
# OSX
out_path = "/Applications/OpenSCAD.app/Contents/MacOS/OpenSCAD"
elif "Windows" in python_platform:
# Windows. Determine if openSCAD is 32-bit or 64-bit
prog_files_32_path = os.environ["PROGRAMFILES"]
prog_files_64_path = os.environ["ProgramW6432"]
prog_files_openscad = "OpenSCAD/openscad.exe"
openscad_32_path = os.path.join(prog_files_32_path, prog_files_openscad)
if os.path.isfile(openscad_32_path):
out_path = os.path.normpath(openscad_32_path)
elif prog_files_64_path is not None:
openscad_64_path = os.path.join(prog_files_64_path, prog_files_openscad)
if os.path.isfile(openscad_64_path):
out_path = os.path.normpath(openscad_64_path)
else:
# Assume Linux. See if the openscad exists on the path
from shutil import which
if which("openscad") is not None:
out_path = "openscad"
return out_path
def process_scad_file(in_scad_path: str, out_scad_path: str, library_path: str, extrusion_thick: float = 0) -> None:
"""
Process the input 3D OpenSCAD file to generate a file of each piece pieces
The output of OpenSCAD needs is processed in order to make it a valid .scad file.
:param in_scad_path: Path of the 3D OpenSCAD file to process
:param out_scad_path: Where to put the generated OpenSCAD file
:param library_path: Path to the lasercut.scad library. Value is placed directly in "include <XXX>" string
:param extrusion_thick: If value is greater than 0, this is the number of mm to extrude the flattened surfaces.
If value is less than or equal to 0, outputted file will be 2D.
:return: None
"""
# A file is needed for OpenSCAD to open and run the lasercut specific
# generator. It will be deleted.
temp_file_base_name = os.path.splitext(os.path.basename(out_scad_path))[0]
temp_file_base_name = f"temp_{temp_file_base_name}.csg"
temp_csg = os.path.join(os.path.dirname(out_scad_path),
temp_file_base_name)
print(f'Processing "{os.path.basename(in_scad_path)}"')
cmd_output = subprocess.run(
f'"{openscad_path}" "{in_scad_path}" -D generate=1 -o "{temp_csg}"',
capture_output=True,
)
# The CSG file was only used to get the output, delete it immediately
os.remove(temp_csg)
if cmd_output.returncode != 0:
exit_with_error(f"Failed to convert to csg file.\nError: {cmd_output.stderr}")
# Process the outputted text (rendered text via stderr)
output_file_contents = cmd_output.stderr.decode()
output_file_contents = output_file_contents.replace("\r\n", "\n")
# Strip the string 'ECHO: "[LC] ' and its closing '"' and remove warnings
import re
output_file_contents = re.sub(r'ECHO: "\[LC] ', "", output_file_contents)
output_file_contents = re.sub(r'"\n', "\n", output_file_contents)
output_file_contents = re.sub(r"WARNING.*", "", output_file_contents)
output_file_contents += ";"
# Add the library and some other basic commands to make a working scad file
scad_header = f'use <{library_path}>;\n'\
'$fn=60;\n'\
'module flat(){\n'\
'projection(cut = false)\n\n'
output_file_contents = scad_header + output_file_contents
# Close flat()
output_file_contents += "\n}\n\n"
# If a thickness was given, extrude the module
if extrusion_thick > 0:
output_file_contents += f"linear_extrude(height={extrusion_thick})\n"
output_file_contents += "flat();\n"
# Write the output file
with open(out_scad_path, "w") as outfile:
outfile.write(output_file_contents)
# Start the actual script
parser = argparse.ArgumentParser("Convert a 3D OpenSCAD lasercut box to a 2D OpenSCAD file for ready for cutting")
parser.add_argument('source',
type=str,
help='Path to the 3D OpenSCAD to convert. Must be a scad or csg file')
parser.add_argument('output',
nargs='?',
type=str,
help='Path to output file. File extension determines type. '
'Valid types are scad, svg, dxf, stl, and any other export types supported by OpenSCAD.'
'If an invalid file type is given, a scad file will be created at the given location.'
'If no path is given, the output file will be put in the same folder as the source with'
'a "2D" suffix/')
parser.add_argument('--extrude', '-x',
type=float,
default=0,
help='If 3D printing or using another system that needs thickness, this is the number of mm'
'to extrude the outputted shapes. If 0 or less this will be ignored. Output file type '
f'cannot be 2D ({", ".join(extensions_2d)}) when this is set.')
parser.add_argument('--keep', '-k',
action='store_true',
help='Keep the intermediate scad file if output type is not already scad')
parser.add_argument('--library', '-l',
default='lasercut/lasercut.scad',
help='Path to the lasercut.scad library. Value is place in the include <XXX> string.')
parser.add_argument('--openscadbin', '-b',
type=str,
help='Use the OpenSCAD executable at the given path instead of the default path for the OS')
args = parser.parse_args()
# Verify that the given file exists, and that it is a valid source file
source_abs_path = os.path.normcase(os.path.abspath(args.source))
if not os.path.isfile(source_abs_path):
exit_with_error(f"Invalid source file: {args.source}")
else:
not_ext, ext = os.path.splitext(source_abs_path)
if ext != '.scad':
exit_with_error('Source file must be a "scad" file')
# Get the path to openSCAD
if args.openscadbin is not None:
openscad_path = args.openscadbin
if not os.path.isfile(openscad_path):
exit_with_error(f'Could not find the OpenSCAD binary at the given path, "{openscad_path}"')
else:
openscad_path = get_openscad_path()
if openscad_path is None:
exit_with_error("Could not find the openscad executable")
# Generate an output file name based on the source file in case none is given
source_basename = os.path.basename(source_abs_path)
source_base_no_ext = os.path.splitext(source_basename)[0]
output_file_base = f"{source_base_no_ext}_flattened"
# Create an output path is none was given
processed_scad_path = None
output_abs_path = None
generate_non_scad_file = False
output_extension = None
if args.output is None:
# Default to a scad file in the same directory as the source
source_folder = os.path.dirname(source_abs_path)
processed_scad_path = os.path.join(source_folder, f"{output_file_base}.scad")
else:
output_dir = os.path.abspath(os.path.dirname(args.output))
if not os.path.isdir(output_dir) \
and not os.path.isdir(args.output):
# An invalid output directory was given
exit_with_error(f"Output directory does not exist: {output_dir}")
if os.path.isdir(args.output):
# The given output is only a directory, generate the output file name from the source
processed_scad_path = os.path.join(args.output, f"{output_file_base}.scad")
else:
output_abs_path = os.path.normcase(os.path.abspath(args.output))
output_no_ext, output_extension = os.path.splitext(output_abs_path)
if output_extension not in extensions_valid:
# If an invalid extension is given, default to scad
output_extension = '.scad'
elif args.extrude > 1 and output_extension in extensions_2d:
# Cannot export to a 2D format when the contents are 3D (extruded)
exit_with_error(f'Cannot export to a 2D format, "{output_extension}", '
f'when extrude, "{args.extrude}", is greater than 0')
generate_non_scad_file = output_extension != '.scad'
processed_scad_path = output_no_ext + '.scad'
processed_scad_path = os.path.normcase(processed_scad_path)
output_abs_path = os.path.normcase(output_abs_path)
# Keep the intermediate file if it already exists or the user wanted it kept
keep_intermediate_file = args.keep or os.path.isfile(processed_scad_path)
# The source file must be different than the intermediate SCAD file and the output file
# If the output file is a SCAD file it will already be equal to processed_scad_path
if source_abs_path == processed_scad_path:
exit_with_error("Source path and processed SCAD path are the same. Please change your output file name.")
# Process the input openscad file
process_scad_file(source_abs_path, processed_scad_path,
library_path=args.library, extrusion_thick=args.extrude)
# Render the file as the desired file type
if generate_non_scad_file:
print(f"Rendering and exporting as {output_extension}")
output = subprocess.run(
f'"{openscad_path}" "{processed_scad_path}" -o "{output_abs_path}"',
capture_output=True,
)
if output.returncode != 0:
exit_with_error(f"Failed to convert to {output_extension}:\n{output.stderr}")
# Delete the intermediate, processed scad file if not requested otherwise
if not keep_intermediate_file:
os.remove(processed_scad_path)
| 40.651568
| 116
| 0.676609
|
65796cc6b298ba51086fbbf338e8c60d7dfda17a
| 1,399
|
py
|
Python
|
awards/models.py
|
hugglesfox/bsc-awards
|
79ed77f9d97e5daccf31d83d850d6791ce3b86ed
|
[
"MIT"
] | null | null | null |
awards/models.py
|
hugglesfox/bsc-awards
|
79ed77f9d97e5daccf31d83d850d6791ce3b86ed
|
[
"MIT"
] | 44
|
2019-12-18T20:04:47.000Z
|
2020-11-13T01:15:45.000Z
|
awards/models.py
|
hugglesfox/bsc-awards
|
79ed77f9d97e5daccf31d83d850d6791ce3b86ed
|
[
"MIT"
] | null | null | null |
from awards import db
class AwardRecipients(db.Model):
id = db.Column(db.Integer, primary_key=True)
student_id = db.Column(db.String(7), nullable=False)
award_id = db.Column(db.Integer, nullable=False)
class Student(db.Model):
student_id = db.Column(db.String(7), primary_key=True)
first_name = db.Column(db.String(120))
last_name = db.Column(db.String(120))
preferred_name = db.Column(db.String(120))
year_level = db.Column(db.Integer)
form_group = db.Column(db.String(3))
house = db.Column(db.String(120))
gender = db.Column(db.String(120))
address = db.Column(db.String(120))
suburb = db.Column(db.String(120))
postcode = db.Column(db.String(4))
primary_parent = db.Column(db.String(120))
attending = db.Column(db.Boolean, nullable=False)
class Awards(db.Model):
award_id = db.Column(db.Integer, primary_key=True)
award_name = db.Column(db.String(120))
award_description = db.Column(db.String(120))
award_certificate_title = db.Column(db.String(120))
award_certificate_title_1 = db.Column(db.String(120))
award_certificate_title_2 = db.Column(db.String(120))
award_certificate_title_3 = db.Column(db.String(120))
award_certificate_sub_title = db.Column(db.String(120))
special_award = db.Column(db.Boolean)
number_of_awards = db.Column(db.Integer)
prize = db.Column(db.String(120))
| 36.815789
| 59
| 0.706934
|
b257084c63b859febe789175f9c7609cf1f01ae4
| 8,010
|
py
|
Python
|
openpharmacophore/algorithms/dbscan.py
|
uibcdf/openpharmacophore
|
4f563fa206f6e7c081502acab97bb795d27bdeb9
|
[
"MIT"
] | 14
|
2021-11-12T10:09:25.000Z
|
2022-03-18T08:24:16.000Z
|
openpharmacophore/algorithms/dbscan.py
|
uibcdf/openpharmacophore
|
4f563fa206f6e7c081502acab97bb795d27bdeb9
|
[
"MIT"
] | 7
|
2021-11-05T01:37:57.000Z
|
2022-01-18T06:03:39.000Z
|
openpharmacophore/algorithms/dbscan.py
|
uibcdf/openpharmacophore
|
4f563fa206f6e7c081502acab97bb795d27bdeb9
|
[
"MIT"
] | 3
|
2021-11-05T01:22:47.000Z
|
2021-12-12T03:57:09.000Z
|
from openpharmacophore import PharmacophoricPoint
from openpharmacophore.utils.align_ligands import align_set_of_ligands
from openpharmacophore.pharmacophore.chemical_features import PharmacophoricPointExtractor
import numpy as np
from sklearn.cluster import DBSCAN
from rdkit import Chem, RDConfig
from rdkit.Chem import ChemicalFeatures
import pyunitwizard as puw
import os
from typing import Optional, Sequence
def rdkit_to_point(feat_name: str, coords: np.ndarray, radius: float,
direction: Optional[Sequence] = None, atom_indices: Optional[Sequence] = None) -> PharmacophoricPoint:
""" Transform an rdkit feature point to an openpharmacophore pharmacophoric point.
Parameters
----------
feat_name : str
rdkit name of the feature point.
coords : numpy.ndarray; shape: (3, )
3D coordinates of the centroid of the feature.
radius : float
Lenght of the radius of the parmacohporic points.
direction : list, tuple, numpy.ndarray; shape:(3,)
Unit vector.
Returns
-------
openpharmacophore.PharmacophoricPoint
The pharmacophoric point.
"""
points = {
"Acceptor": "hb acceptor",
"Donor": "hb donor",
"Aromatic": "aromatic ring",
"Hydrophobe": "hydrophobicity",
"PosIonizable": "positive charge",
"NegIonizable": "negative charge",
}
return PharmacophoricPoint(
feat_type=points[feat_name],
center=puw.quantity(coords, "angstroms"),
radius=puw.quantity(radius, "angstroms"),
direction=direction,
atom_indices=atom_indices
)
def get_feature_clusters(feat_coords, eps, min_samples):
"""
Get clusters of features for a ligand based pharmacophore.
Parameters
----------
feat_coords : dict
Dictionary containing 3D coordinates for each feature type. Dictionary keys
are feature name and values are an numpy array of coordinates
eps : float
The maximum distance between two pharmacophoric points for one to be considered
as in the neighborhood of the other. (Default: 2)
min_samples : float
Percentages of ligands that must contain a pharmacophoric point to be considered as a core point.
Must be a number between 0 and 1
Returns
----------
clusters : dict
Dictionary with centroid of each cluster of features. Keys are feature name
and values is a list of coordinates
"""
clusters = {}
for feat, coords in feat_coords.items():
db_scan = DBSCAN(eps=eps, min_samples=min_samples).fit(coords)
labels = db_scan.labels_
core_samples_mask = np.zeros_like(labels, dtype=bool)
core_samples_mask[db_scan.core_sample_indices_] = True
centroids = []
unique_labels = set(labels)
for k in unique_labels:
if k == -1:
continue
class_member_mask = (labels == k)
cluster = feat_coords[feat][class_member_mask & core_samples_mask]
cluster_centroid = cluster.mean(axis=0)
centroids.append(cluster_centroid)
clusters[feat] = centroids
return clusters
def dbscan_pharmacophore(ligands, radius=1, eps=2, min_samples=0.75, feat_list=None, feat_def=None):
"""
Compute a ligand based pharmacophore from a list of ligands, using a density based
clustering algorithm.
Parameters
----------
ligands : list of rdkit.Chem.rdchem.Mol or rdkit.Chem.SmilesMolSupplier or rdkit.Chem.SDMolSupplier
List of ligands.
radius : float, optional
Lenght of the radius in angstroms of the parmacohporic points (Default: 1)
eps : float, optional
The maximum distance between two pharmacophoric points for one to be considered
as in the neighborhood of the other (default=2).
min_samples : float
Percentages of ligands that must contain a pharmacophoric point to be considered as a core point.
Must be anumber betwwen 0 and 1 (default=0.75).
feat_list : list of str, optional
List of features that will be used to compute the pharmacophore.
feat_def : dict
Definitions of the pharmacophoric points.
Dictionary which keys are SMARTS strings and values are feature names.
Returns
--------
pharmacophoric_points : list of openpharmacophore.PharmacophoricPoints
The pharmacophoric points of the common pharmacophore.
aligned_ligands: list of rdkit.Chem.Mol
A list containing the aligned ligands.
"""
if min_samples < 0 or min_samples > 1:
raise ValueError("min_samples must be a value between 0 and 1")
aligned_ligands, _ = align_set_of_ligands(ligands)
if feat_def is None: # If no feature definition is given use rdkit one
fdefName = os.path.join(RDConfig.RDDataDir,'BaseFeatures.fdef')
factory = ChemicalFeatures.BuildFeatureFactory(fdefName)
else:
reverse_feat_dict = {}
for smarts, feat_name in feat_def.items():
if feat_name not in reverse_feat_dict:
reverse_feat_dict[feat_name] = []
reverse_feat_dict[feat_name].append(smarts)
if not feat_list:
feat_list = ['Acceptor', 'Aromatic', 'Donor', 'Hydrophobe', 'PosIonizable', 'NegIonizable']
feat_coords = {}
for feature in feat_list:
feat_coords[feature] = []
for ligand in aligned_ligands:
if feat_def is None:
feats = factory.GetFeaturesForMol(ligand, includeOnly=feature)
for f in feats:
atom_idxs = f.GetAtomIds()
if len(atom_idxs) > 1: # Aromatic, hydrophobic, positive or negative feature
coords = PharmacophoricPointExtractor._feature_centroid(ligand, atom_idxs, 0)
else: # Donor or acceptor feature
position = ligand.GetConformer(0).GetAtomPosition(atom_idxs[0])
coords = np.zeros((3,))
coords[0] = position.x
coords[1] = position.y
coords[2] = position.z
feat_coords[feature].append((coords.tolist()))
else:
for f in reverse_feat_dict[feature]:
pattern = Chem.MolFromSmarts(f)
atom_idxs = ligand.GetSubstructMatch(pattern)
if len(atom_idxs) == 0:
continue
elif len(atom_idxs) == 1: # Donor or acceptor feature
position = ligand.GetConformer(0).GetAtomPosition(atom_idxs[0])
coords = np.zeros((3,))
coords[0] = position.x
coords[1] = position.y
coords[2] = position.z
elif len(atom_idxs) > 1: # Aromatic, hydrophobic, positive or negative feature
coords = PharmacophoricPointExtractor._feature_centroid(ligand, atom_idxs, 0)
feat_coords[feature].append((coords.tolist()))
feat_coords[feature] = np.array(feat_coords[feature])
feat_coords = {feature: coords for feature, coords in feat_coords.items() if len(coords) > 0} # remove features with no coordinates
min_samples = int(min_samples * len(ligands))
feature_clusters = get_feature_clusters(feat_coords, eps=eps, min_samples=min_samples)
pharmacophoric_points = []
for feature_type, coords in feature_clusters.items():
for center in coords:
point = rdkit_to_point(feature_type, center, radius=radius, direction=None)
pharmacophoric_points.append(point)
return pharmacophoric_points, aligned_ligands
| 38.695652
| 135
| 0.626966
|
a2738315e8ec1fcb3ac5c01332236e67b6fb20d5
| 1,398
|
py
|
Python
|
CreatAllFile.py
|
FAWC-bupt/Text-Classification
|
a68b639917d65778ec05ac41f0e8d2b3ac49c9fc
|
[
"MIT"
] | 4
|
2021-01-09T01:33:45.000Z
|
2021-11-11T14:03:52.000Z
|
CreatAllFile.py
|
FAWC-bupt/Text-Classification
|
a68b639917d65778ec05ac41f0e8d2b3ac49c9fc
|
[
"MIT"
] | null | null | null |
CreatAllFile.py
|
FAWC-bupt/Text-Classification
|
a68b639917d65778ec05ac41f0e8d2b3ac49c9fc
|
[
"MIT"
] | 1
|
2021-07-06T06:26:12.000Z
|
2021-07-06T06:26:12.000Z
|
"""
预处理部分3：
整合数据至一个文件all.txt，避免重复IO
"""
class_list = {'财经': 'Economics', '房产': 'House', '社会': 'Society', '时尚': 'Fashion', '教育': 'Education',
'科技': 'Technology', '时政': 'Politics', '体育': 'PE', '游戏': 'Game', '娱乐': 'Entertainment'}
if __name__ == '__main__':
all_data_test = ''
all_data_train = ''
for class_name, class_name_en in class_list.items():
string_to_write_test = ''
string_to_write_train = ''
for i in range(5000):
print(class_name + ':' + str(i))
with open('data_test/' + class_name_en + '/' + str(i) + '.txt', 'r', encoding='utf-8') as f:
string_to_write_test += (f.read() + '\n')
with open('data_train/' + class_name_en + '/' + str(i) + '.txt', 'r', encoding='utf-8') as f:
string_to_write_train += (f.read() + '\n')
with open('data_test/' + class_name_en + '/all.txt', 'w', encoding='utf-8') as f:
f.write(string_to_write_test)
with open('data_train/' + class_name_en + '/all.txt', 'w', encoding='utf-8') as f:
f.write(string_to_write_train)
all_data_test += string_to_write_test
all_data_train += string_to_write_train
with open('data_test/all.txt', 'w', encoding='utf-8') as f:
f.write(all_data_test)
with open('data_train/all.txt', 'w', encoding='utf-8') as f:
f.write(all_data_train)
| 46.6
| 105
| 0.570815
|
665f487866570e0755261286e3f1a5e8c8c9dd74
| 2,145
|
py
|
Python
|
src/oci/database_migration/models/job_collection.py
|
Manny27nyc/oci-python-sdk
|
de60b04e07a99826254f7255e992f41772902df7
|
[
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null |
src/oci/database_migration/models/job_collection.py
|
Manny27nyc/oci-python-sdk
|
de60b04e07a99826254f7255e992f41772902df7
|
[
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null |
src/oci/database_migration/models/job_collection.py
|
Manny27nyc/oci-python-sdk
|
de60b04e07a99826254f7255e992f41772902df7
|
[
"Apache-2.0",
"BSD-3-Clause"
] | null | null | null |
# coding: utf-8
# Copyright (c) 2016, 2021, Oracle and/or its affiliates. All rights reserved.
# This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license.
from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401
from oci.decorators import init_model_state_from_kwargs
@init_model_state_from_kwargs
class JobCollection(object):
"""
Note: Deprecated. Use the new resource model APIs instead.
Results of a Job search. Contains JobSummary items.
"""
def __init__(self, **kwargs):
"""
Initializes a new JobCollection object with values from keyword arguments.
The following keyword arguments are supported (corresponding to the getters/setters of this class):
:param items:
The value to assign to the items property of this JobCollection.
:type items: list[oci.database_migration.models.JobSummary]
"""
self.swagger_types = {
'items': 'list[JobSummary]'
}
self.attribute_map = {
'items': 'items'
}
self._items = None
@property
def items(self):
"""
**[Required]** Gets the items of this JobCollection.
Items in collection.
:return: The items of this JobCollection.
:rtype: list[oci.database_migration.models.JobSummary]
"""
return self._items
@items.setter
def items(self, items):
"""
Sets the items of this JobCollection.
Items in collection.
:param items: The items of this JobCollection.
:type: list[oci.database_migration.models.JobSummary]
"""
self._items = items
def __repr__(self):
return formatted_flat_dict(self)
def __eq__(self, other):
if other is None:
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
return not self == other
| 29.791667
| 245
| 0.652214
|
61ebbf8ddcb935be275478fa30e98fcc965eccce
| 1,393
|
py
|
Python
|
Fw/Python/src/fprime/common/models/serialize/i32_type.py
|
hunterpaulson/fprime
|
70560897b56dc3037dc966c99751b708b1cc8a05
|
[
"Apache-2.0"
] | null | null | null |
Fw/Python/src/fprime/common/models/serialize/i32_type.py
|
hunterpaulson/fprime
|
70560897b56dc3037dc966c99751b708b1cc8a05
|
[
"Apache-2.0"
] | 5
|
2020-07-13T16:56:33.000Z
|
2020-07-23T20:38:13.000Z
|
Fw/Python/src/fprime/common/models/serialize/i32_type.py
|
hunterpaulson/lgtm-fprime
|
9eeda383c263ecba8da8188a45e1d020107ff323
|
[
"Apache-2.0"
] | null | null | null |
"""
Created on Dec 18, 2014
@author: tcanham, reder
"""
from __future__ import print_function
from __future__ import absolute_import
import struct
from .type_exceptions import TypeMismatchException
from .type_exceptions import TypeRangeException
from . import type_base
@type_base.serialize
@type_base.deserialize
class I32Type(type_base.BaseType):
"""
Representation of the I32 type
"""
def __init__(self, val=None):
"""
Constructor
"""
self.__val = val
if val == None:
return
self._check_val(val)
def _check_val(self, val):
if not type(val) == type(int()):
raise TypeMismatchException(type(int()), type(val))
# check range
if (val < -pow(2, 31)) or (val > pow(2, 31) - 1):
raise TypeRangeException(val)
@property
def val(self):
return self.__val
@val.setter
def val(self, val):
self._check_val(val)
self.__val = val
def serialize(self):
"""
Utilize serialize decorator here...
"""
return self._serialize(">i")
def deserialize(self, data, offset):
"""
Utilize deserialized decorator here...
"""
self._deserialize(">i", data, offset)
def getSize(self):
return struct.calcsize(">i")
def __repr__(self):
return "I32"
| 21.106061
| 63
| 0.595118
|
88bff4ab4116f7f16f58ca5b7a1a0b65afbf3f16
| 787
|
py
|
Python
|
stack.py
|
FAWC-bupt/Virtual-Machine-of-Instruction-Set-Architecture
|
478d3a95150c358b41012948577db6fe3ac8483b
|
[
"MIT"
] | 3
|
2020-05-11T12:20:18.000Z
|
2020-11-14T12:31:42.000Z
|
stack.py
|
FAWC-bupt/Virtual-Machine-of-Instruction-Set-Architecture
|
478d3a95150c358b41012948577db6fe3ac8483b
|
[
"MIT"
] | null | null | null |
stack.py
|
FAWC-bupt/Virtual-Machine-of-Instruction-Set-Architecture
|
478d3a95150c358b41012948577db6fe3ac8483b
|
[
"MIT"
] | 1
|
2020-08-10T23:09:59.000Z
|
2020-08-10T23:09:59.000Z
|
from register import Register, ARegister, DRegister
from memory import Memory
def push(regA: Register, RSP: Register, AR: ARegister, DR: DRegister, memory: Memory):
"""
将指定寄存器的值压入栈中
:param regA:
:param RSP:
:param AR:
:param DR:
:param memory:
:return:
"""
RSP.data = RSP.data - 1
RSP.readData()
AR.writeData()
regA.readData()
DR.writeData()
memory.writeData(AR, DR)
def pop(regA: Register, RSP: Register, AR: ARegister, DR: DRegister, memory: Memory):
"""
将栈顶值弹出到指定寄存器
:param regA:
:param RSP:
:param AR:
:param DR:
:param memory:
:return:
"""
RSP.readData()
AR.writeData()
memory.readData(AR, DR)
DR.readData()
regA.writeData()
RSP.data = RSP.data + 1
| 17.886364
| 86
| 0.597205
|
d2f0874a452bb381303c5f55aaf2e223d2044a0b
| 266
|
py
|
Python
|
algorithms/sem_prop/inputoutput/utils.py
|
Soton-Song/valentine
|
9a47859f912540cdbe961ed3585201d3accd07be
|
[
"Apache-2.0"
] | null | null | null |
algorithms/sem_prop/inputoutput/utils.py
|
Soton-Song/valentine
|
9a47859f912540cdbe961ed3585201d3accd07be
|
[
"Apache-2.0"
] | null | null | null |
algorithms/sem_prop/inputoutput/utils.py
|
Soton-Song/valentine
|
9a47859f912540cdbe961ed3585201d3accd07be
|
[
"Apache-2.0"
] | null | null | null |
from pickle import load, dump
def serialize_object(obj, path):
f = open(path, 'wb')
dump(obj, f)
f.close()
def deserialize_object(path):
f = open(path, 'rb')
obj = load(f)
return obj
if __name__ == "__main__":
print("Input output")
| 14.777778
| 32
| 0.609023
|
fc075483ab298eff09e12415d810be7d89e4ed28
| 991
|
py
|
Python
|
main.py
|
Adeon18/Solver_Algorithms
|
54acc53d92e1234fd14dd303f5c59f818ab91f95
|
[
"MIT"
] | 4
|
2021-05-27T10:42:12.000Z
|
2022-03-23T12:51:43.000Z
|
main.py
|
Adeon18/Solver_Algorithms
|
54acc53d92e1234fd14dd303f5c59f818ab91f95
|
[
"MIT"
] | null | null | null |
main.py
|
Adeon18/Solver_Algorithms
|
54acc53d92e1234fd14dd303f5c59f818ab91f95
|
[
"MIT"
] | null | null | null |
import os
from sys import platform
# Check for user system
linux = False
bad_os = False
if platform == "linux" or platform == "linux2":
linux = True
elif platform == "win32":
bad_os = True
scripts = {
1: "maze/main.py",
2: "sudoku/main.py",
3: "crossword/main.py",
4: "graph_colorizer/main.py",
}
print("Hello! This is a script launcher. Choose a number of the script you'd like to run.")
print("Before you choose, close down the program and edit the coresponding file in data folder if you want to solve your problem\n")
print("\
1. Maze solver\n\
2. Sudoku solver\n\
3. Crossword solver\n\
4. Graph Colorer\n")
while True:
try:
choice = int(input("Enter a number: "))
command = scripts[choice]
break
except KeyError:
print("Enter a correct number")
except ValueError:
print("Enter a NUMBER")
if bad_os:
os.system("python -m " + command)
elif linux:
os.system("python " + command)
| 22.022222
| 132
| 0.638749
|
b42a0bdc611a714864e8f985dd4878727a423a0e
| 1,884
|
py
|
Python
|
homeassistant/components/remote/reproduce_state.py
|
edofullin/core
|
106dc4d28ad59cb192c60fc7a354cafa86899ea4
|
[
"Apache-2.0"
] | 1
|
2021-03-23T07:20:03.000Z
|
2021-03-23T07:20:03.000Z
|
homeassistant/components/remote/reproduce_state.py
|
edofullin/core
|
106dc4d28ad59cb192c60fc7a354cafa86899ea4
|
[
"Apache-2.0"
] | 60
|
2020-07-06T15:10:30.000Z
|
2022-03-31T06:01:46.000Z
|
homeassistant/components/remote/reproduce_state.py
|
edofullin/core
|
106dc4d28ad59cb192c60fc7a354cafa86899ea4
|
[
"Apache-2.0"
] | 4
|
2017-01-10T04:17:33.000Z
|
2021-09-02T16:37:24.000Z
|
"""Reproduce an Remote state."""
from __future__ import annotations
import asyncio
import logging
from typing import Any, Iterable
from homeassistant.const import (
ATTR_ENTITY_ID,
SERVICE_TURN_OFF,
SERVICE_TURN_ON,
STATE_OFF,
STATE_ON,
)
from homeassistant.core import Context, State
from homeassistant.helpers.typing import HomeAssistantType
from . import DOMAIN
_LOGGER = logging.getLogger(__name__)
VALID_STATES = {STATE_ON, STATE_OFF}
async def _async_reproduce_state(
hass: HomeAssistantType,
state: State,
*,
context: Context | None = None,
reproduce_options: dict[str, Any] | None = None,
) -> None:
"""Reproduce a single state."""
cur_state = hass.states.get(state.entity_id)
if cur_state is None:
_LOGGER.warning("Unable to find entity %s", state.entity_id)
return
if state.state not in VALID_STATES:
_LOGGER.warning(
"Invalid state specified for %s: %s", state.entity_id, state.state
)
return
# Return if we are already at the right state.
if cur_state.state == state.state:
return
service_data = {ATTR_ENTITY_ID: state.entity_id}
if state.state == STATE_ON:
service = SERVICE_TURN_ON
elif state.state == STATE_OFF:
service = SERVICE_TURN_OFF
await hass.services.async_call(
DOMAIN, service, service_data, context=context, blocking=True
)
async def async_reproduce_states(
hass: HomeAssistantType,
states: Iterable[State],
*,
context: Context | None = None,
reproduce_options: dict[str, Any] | None = None,
) -> None:
"""Reproduce Remote states."""
await asyncio.gather(
*(
_async_reproduce_state(
hass, state, context=context, reproduce_options=reproduce_options
)
for state in states
)
)
| 24.467532
| 81
| 0.663482
|
5e33cd996cf412f56f927a2b5fd7e324adff3a74
| 714
|
py
|
Python
|
src/python/rule.py
|
karmaresearch/glog-python
|
fdeb7f2941686ffe0692b365175452c861bfce1f
|
[
"Apache-2.0"
] | 1
|
2021-09-09T05:43:35.000Z
|
2021-09-09T05:43:35.000Z
|
src/python/rule.py
|
karmaresearch/glog-python
|
fdeb7f2941686ffe0692b365175452c861bfce1f
|
[
"Apache-2.0"
] | null | null | null |
src/python/rule.py
|
karmaresearch/glog-python
|
fdeb7f2941686ffe0692b365175452c861bfce1f
|
[
"Apache-2.0"
] | null | null | null |
import copy
class Rule:
def __init__(self, head_atoms, body_atoms):
self.head_atoms = head_atoms
self.body_atoms = body_atoms
def str(self):
out = ''
for head_atom in self.head_atoms:
out += head_atom.str() + ','
out = out[:-1] + ' :- '
for body_atom in self.body_atoms:
out += body_atom.str() + ','
out = out[:-1]
return out
def get_head(self):
return copy.deepcopy(self.head_atoms)
def get_body(self):
return copy.deepcopy(self.body_atoms)
def set_head(self, head_atoms):
self.head_atoms = head_atoms
def set_body(self, body_atoms):
self.body_atoms = body_atoms
| 24.62069
| 47
| 0.582633
|
3f1ed78b2cb6d12f6331b7b95b62fe942cfbef92
| 315
|
py
|
Python
|
packages/merlin/protocols/AssetCategory.py
|
pyre/pyre
|
0f903836f52450bf81216c5dfdfdfebb16090177
|
[
"BSD-3-Clause"
] | 25
|
2018-04-23T01:45:39.000Z
|
2021-12-10T06:01:23.000Z
|
packages/merlin/protocols/AssetCategory.py
|
pyre/pyre
|
0f903836f52450bf81216c5dfdfdfebb16090177
|
[
"BSD-3-Clause"
] | 53
|
2018-05-31T04:55:00.000Z
|
2021-10-07T21:41:32.000Z
|
packages/merlin/protocols/AssetCategory.py
|
pyre/pyre
|
0f903836f52450bf81216c5dfdfdfebb16090177
|
[
"BSD-3-Clause"
] | 12
|
2018-04-23T22:50:40.000Z
|
2022-02-20T17:27:23.000Z
|
# -*- coding: utf-8 -*-
#
# michael a.g. aïvázis <michael.aivazis@para-sim.com>
# (c) 1998-2021 all rights reserved
# support
import merlin
# class declaration
class AssetCategory(merlin.protocol, family="merlin.assets.categories"):
"""
Protocol for all project asset categories
"""
# end of file
| 16.578947
| 72
| 0.685714
|
4c014910822c141a255df77316b0bda4178ba58b
| 34,780
|
py
|
Python
|
ztfquery/query.py
|
MichaelMedford/ztfquery
|
9e3634d93338e4c753effa278d57de9142e3b791
|
[
"Apache-2.0"
] | null | null | null |
ztfquery/query.py
|
MichaelMedford/ztfquery
|
9e3634d93338e4c753effa278d57de9142e3b791
|
[
"Apache-2.0"
] | null | null | null |
ztfquery/query.py
|
MichaelMedford/ztfquery
|
9e3634d93338e4c753effa278d57de9142e3b791
|
[
"Apache-2.0"
] | null | null | null |
#! /usr/bin/env python
#
""" Combine MetaSearch and MetaURL to get data from IRSA """
import os
import numpy as np
from .metasearch import download_metadata, _test_kind_
from . import buildurl
import warnings
# This enables multiprocess downloading
from . import io
# Combining metadata with buildurl
def metatable_to_url(metatable, datakind='sci', suffix=None, source=None):
"""generic method to build the url/fullpath or the requested data.
This method is based on the `builurl.py` module of ztfquery.
Parameters
----------
suffix: [string] -optional-
What kind of data do you want?
Here is the list of available options depending the image kind:
# Science image (kind="sci"):
- sciimg.fits (primary science image) # (default)
- mskimg.fits (bit-mask image)
- psfcat.fits (PSF-fit photometry catalog)
- sexcat.fits (nested-aperture photometry catalog)
- sciimgdao.psf (spatially varying PSF estimate in DAOPhot's lookup table format)
- sciimgdaopsfcent.fits (PSF estimate at science image center as a FITS image)
- sciimlog.txt (log output from instrumental calibration pipeline)
- scimrefdiffimg.fits.fz (difference image: science minus reference; fpack-compressed)
- diffimgpsf.fits (PSF estimate for difference image as a FITS image)
- diffimlog.txt (log output from image subtraction and extraction pipeline)
- log.txt (overall system summary log from realtime pipeline)
# Reference image (kind="ref"):
-log.txt
-refcov.fits
-refimg.fits # (default)
-refimlog.txt
-refpsfcat.fits
-refsexcat.fits
-refunc.fits
# Raw images (kind="raw")
No Choice so suffix is ignored for raw data
# Calibration (kind="cal")
- None (#default) returns `caltype`.fits
- log: returns `caltype`log.txt
- unc: returns `caltype`unc.fits
// if queried metadata is for kind calibration
"""
if datakind in ['sci', "raw"]:
filtercode,imgtypecode = np.asarray(metatable[["filtercode","imgtypecode"]
].values.T, dtype="str")
paddedfield = np.asarray(["%06d"%f for f in metatable["field"].values],
dtype="str")
paddedccdid = np.asarray(["%02d"%f for f in metatable["ccdid"].values],
dtype="str")
year, month, day, fracday = np.asarray([[l[:4],l[4:6],l[6:8],l[8:]]
for l in np.asarray(metatable["filefracday"].values,
dtype="str") ]).T
if datakind in ['sci']:
qid = np.asarray(metatable["qid"], dtype="str")
# LIST of URL to download [SCIENCE]
return [buildurl.science_path(year_, month_, day_, fracday_, paddedfield_,
filtercode_, paddedccdid_, qid_,
imgtypecode=imgtypecode_, suffix=suffix, source=source)
for year_, month_, day_, fracday_, paddedfield_, filtercode_,
paddedccdid_, qid_, imgtypecode_
in zip(year, month, day, fracday, paddedfield, filtercode,
paddedccdid, qid, imgtypecode)]
else:
# LIST of URL to download [RAW]
return [buildurl.raw_path(year_, month_, day_, fracday_,
paddedfield_ if imgtypecode_ != "f" else '000000', # because sometime they do have a field, why is that ?,
filtercode_, paddedccdid_,
imgtypecode=imgtypecode_, source=source)
for year_, month_, day_, fracday_, paddedfield_, filtercode_,
paddedccdid_, imgtypecode_
in zip(year, month, day, fracday, paddedfield, filtercode,
paddedccdid, imgtypecode)]
# CALIBRATION
elif datakind in ['cal']:
year, month, day = np.asarray([[l[:4],l[4:6],l[6:]]
for l in np.asarray(metatable["nightdate"].values,
dtype="str") ]).T
paddedccdid = np.asarray(["%02d"%f for f in metatable["ccdid"].values],
dtype="str")
filtercode, qid,caltype = np.asarray(metatable[["filtercode", "qid","caltype"]].values.T,
dtype="str")
filtercode[filtercode=="0"] = "00" # such that it is what IRSA expects.
# list of url to download [CAL]
return [buildurl.calibration_path(caltype_,
year_, month_, day_,
filtercode_, paddedccdid_, qid_,
suffix=suffix, source=source)
for caltype_, year_, month_, day_, filtercode_, paddedccdid_, qid_
in zip(caltype,year, month, day,filtercode, paddedccdid, qid) ]
# PIXELS
elif datakind in ['ref']:
paddedfield = np.asarray(["%06d"%f for f in metatable["field"].values], dtype="str")
paddedccdid = np.asarray(["%02d"%f for f in metatable["ccdid"].values], dtype="str")
filtercode, qid = np.asarray(metatable[["filtercode", "qid"]].values.T, dtype="str")
return [buildurl.reference_path( paddedfield_,
filtercode_, paddedccdid_, qid_,
suffix=suffix,
fieldprefix=paddedfield_[:3], # This is how it is defined in IRSA
source=source)
for paddedfield_, filtercode_, paddedccdid_, qid_
in zip(paddedfield, filtercode, paddedccdid, qid)]
#############################
# #
# Main Query Tools #
# #
#############################
class _ZTFTableHandler_( object ):
""" """
# -------------- #
# FIELDS #
# -------------- #
def get_observed_fields(self, grid="both"):
""" get the (unique) list of field observed type. """
if "field" not in self._data.columns:
return None
all_fields = np.unique(self._data["field"])
if grid is None or grid in ["both"]:
return all_fields
from .fields import fields_in_main
if grid in ["main", "first", "primary"]:
return all_fields[fields_in_main(all_fields)]
elif grid in ["other", "secondary"]:
return all_fields[~fields_in_main(all_fields)]
else:
raise ValueError("Cannot parse the given grid %s"%grid)
def get_field_average_value(self, value, grid="both", fid=[1,2,3]):
""" """
flagfield = True if fid is None or "fid" not in self._data.columns else np.in1d(np.asarray(self._data["fid"], dtype="int"), fid)
return {f_: np.nanmean(self._data[np.in1d(self._data["field"], f_) * flagfield][value])
for f_ in self.get_observed_fields(grid=grid)}
def get_field_obsdensity(self, grid="both", fid=[1,2,3]):
""" """
flagfield = True if fid is None or "fid" not in self._data.columns \
else np.in1d(np.asarray(self._data["fid"], dtype="int"), fid)
return {f_: len(self._data[np.in1d(self._data["field"], f_) * flagfield])
for f_ in self.get_observed_fields(grid=grid)}
def show_fields(self, field_val,
ax=None,
show_ztf_fields=True,
colorbar=True, cax=None, clabel=" ",
cmap="viridis",origin=180,
vmin=None, vmax=None, **kwargs):
"""
Parameters
----------
colored_by:
"""
from .fields import show_fields
return show_fields(field_val, ax=ax,
show_ztf_fields=show_ztf_fields,
colorbar=colorbar, cax=cax, clabel=clabel,
cmap=cmap,origin=origin,
vmin=vmin, vmax=vmax, **kwargs)
def show_gri_fields(self, title=" ",
show_ztf_fields=True,
colorbar=True,
colored_by="visits", grid="main",
**kwargs):
""" """
import matplotlib.pyplot as mpl
from .fields import FIELDS_COLOR
fig = mpl.figure(figsize=[9,6])
fig.suptitle(title, fontsize="large")
# G
axg = fig.add_axes([0.03,0.52,0.43,0.48], projection="hammer")
caxg = fig.add_axes([0.03,0.54,0.43,0.015])
axg.tick_params(labelsize="x-small", labelcolor="0.3" )
# R
axr = fig.add_axes([0.54,0.52,0.43,0.48], projection="hammer")
caxr = fig.add_axes([0.54,0.54,0.43,0.015])
axr.tick_params(labelsize="x-small", labelcolor="0.3")
# I
axi = fig.add_axes([0.27,0.04,0.43,0.48], projection="hammer")
caxi = fig.add_axes([0.27,0.05,0.43,0.015])
axi.tick_params(labelsize="x-small", labelcolor="0.3", )
# python 3
# prop = {**dict(colorbar=colorbar, edgecolor="0.5", linewidth=0.5),**kwargs}
# python 2 still supported
prop = dict(colorbar=colorbar, edgecolor="0.5", linewidth=0.5)
for k,v in kwargs.items():
prop[k] = v
for i,ax_,cax_ in zip([1,2,3], [axg,axr,axi], [caxg,caxr,caxi]):
if colored_by in ["visits", "density"]:
field_val = {f:v for f,v in
self.get_field_obsdensity(grid=grid, fid=[i]).items() if v>0}
else:
field_val = colored_by[i]
self.show_fields(field_val, ax=ax_, cax=cax_, cmap=FIELDS_COLOR[i], **prop)
return fig
# =================== #
# #
# =================== #
@property
def _data(self):
""" """
return self.metatable if hasattr(self, "metatable") else self.data
class _ZTFDownloader_( object ):
""" Virtual class that enable to download consistently ZTF data.
To use it, you need to inherite this and implement get_data_path()
such that this method returns fullpath to the data given
`suffix` and `source` arguments.
"""
def get_data_path(self, suffix=None, source=""):
""" generic method to build the url/fullpath or the requested data.
This method is based on the `builurl.py` module of ztfquery.
**This is a virtual empty function ; inheriting class must implemented This**
"""
raise NotImplementedError("the get_data_path() method must be implemented. ")
# Generic that should automatically work as long as get_data_path is defined.
def download_data(self, suffix=None, source="IRSA", indexes=None,
download_dir=None,
show_progress = True, notebook=False, verbose=True,
nodl = False, overwrite=False, nprocess=None,
auth=None, **kwargs):
"""
Parameters
----------
suffix: [string] -optional-
What kind of data do you want?
Here is the list of available options depending on you image kind:
# Science image (kind="sci"):
- sciimg.fits (primary science image) # (default)
- mskimg.fits (bit-mask image)
- psfcat.fits (PSF-fit photometry catalog)
- sexcat.fits (nested-aperture photometry catalog)
- sciimgdao.psf (spatially varying PSF estimate in DAOPhot's lookup table format)
- sciimgdaopsfcent.fits (PSF estimate at science image center as a FITS image)
- sciimlog.txt (log output from instrumental calibration pipeline)
- scimrefdiffimg.fits.fz (difference image: science minus reference; fpack-compressed)
- diffimgpsf.fits (PSF estimate for difference image as a FITS image)
- diffimlog.txt (log output from image subtraction and extraction pipeline)
- log.txt (overall system summary log from realtime pipeline)
# Reference image (kind="ref"):
-log.txt
-refcov.fits
-refimg.fits # (default)
-refimlog.txt
-refpsfcat.fits
-refsexcat.fits
-refunc.fits
# Raw images (kind="raw")
No Choice. Suffix is ignored for raw data
# Calibration (kind="cal")
- None (#default) returns `caltype`.fits
- log: returns `caltype`log.txt
- unc: returns `caltype`unc.fits
download_dir: [string] -optional-
Directory where the file should be downloaded.
If th
overwrite: [bool] -optional-
Check if the requested data already exist in the target download directory.
If so, this will skip the download except if overwrite is set to True.
nprocess: [None/int] -optional-
Number of parallel downloading you want to do.
If None, it will be set to 1 and will not use multiprocess
auth: [str, str] -optional-
[username, password] of you IRSA account.
If used, information stored in ~/.ztfquery will be ignored.
"""
# login
if auth is not None:
from .io import get_cookie
cookie = get_cookie(*auth)
else:
cookie = None
# Data Structure
self._relative_data_path = self.get_data_path(suffix=suffix, source="None", indexes=indexes, **kwargs)
# The IRSA location
self.to_download_urls = [buildurl._source_to_location_(source) + d_
for d_ in self._relative_data_path]
# Where do you want them?
if download_dir is None: # Local IRSA structure
self.download_location = [buildurl._source_to_location_("local") + d_
for d_ in self._relative_data_path]
else:
self.download_location = [download_dir + "/%s"%(d_.split("/")[-1])
for d_ in self._relative_data_path]
if nodl:
return self.to_download_urls, self.download_location
# Actual Download
io.download_url(self.to_download_urls, self.download_location,
show_progress = show_progress, notebook=notebook, verbose=verbose,
overwrite=overwrite, nprocess=nprocess, cookies=cookie)
# --------- #
# GETTER #
# --------- #
def get_local_data(self, suffix=None, exists=True, indexes=None):
""" the lists of files stored in your local copy of the ztf database.
[This methods uses the get_data_path() method assuming source='local']
Parameters
----------
suffix: [string] -optional-
What kind of data do you want?
Here is the list of available options depending on you image kind:
# Science image (kind="sci"):
- sciimg.fits (primary science image) # (default)
- mskimg.fits (bit-mask image)
- psfcat.fits (PSF-fit photometry catalog)
- sexcat.fits (nested-aperture photometry catalog)
- sciimgdao.psf (spatially varying PSF estimate in DAOPhot's lookup table format)
- sciimgdaopsfcent.fits (PSF estimate at science image center as a FITS image)
- sciimlog.txt (log output from instrumental calibration pipeline)
- scimrefdiffimg.fits.fz (difference image: science minus reference; fpack-compressed)
- diffimgpsf.fits (PSF estimate for difference image as a FITS image)
- diffimlog.txt (log output from image subtraction and extraction pipeline)
- log.txt (overall system summary log from realtime pipeline)
# Reference image (kind="ref"):
-log.txt
-refcov.fits
-refimg.fits # (default)
-refimlog.txt
-refpsfcat.fits
-refsexcat.fits
-refunc.fits
# Raw images (kind="raw")
No Choice so suffix is ignored for raw data
# Calibration (kind="cal")
- None (#default) returns `caltype`.fits
- log: returns `caltype`log.txt
- unc: returns `caltype`unc.fits
exists: [bool] -optional-
returns only the file that exists in your computer.
If false, this will return the expected path of the requested data,
even though they might not exist.
Returns
-------
list
"""
files = self.get_data_path(suffix=suffix, source="local", indexes=indexes)
if not exists:
return files
return [f for f in files if os.path.isfile( f )]
class ZTFQuery( _ZTFTableHandler_, _ZTFDownloader_ ):
""" """
# ------------ #
# DOWNLOADER #
# ------------ #
def load_metadata(self, kind="sci",
radec=None, size=None, mcen=None,
caltype=None,
sql_query=None, auth=None, **kwargs):
""" Querying for the metadata information that enables to reconstruct the URL to access the data.
[This methods uses the .metasearch library, which is python wrapper of the the IRSA web API
see https://irsa.ipac.caltech.edu/docs/program_interface/ztf_api.html]
Parameters
----------
kind: [str] -optional-
What kind of data are you looking for:
- sci : Science Exposures
- raw : Raw Data
- ref : Reference Images
- cal : Bias or High Frequency Flat
any other entry will raise a ValueError
// Generic Query
sql_query: [None or string] -optional -
The where parameter can be set to a 'SQL WHERE' clause, with some restrictions.
[https://en.wikipedia.org/wiki/Where_(SQL)]
Notably, function calls and sub-queries are not supported. You can use AND, OR, NOT, IN, BETWEEN, LIKE, IS,
the usual arithmetic and comparison operators, and literal values.
Note that the where parameter is required in the absence of POS (a spatial constraint).
WHERE clauses should be URL encoded [https://en.wikipedia.org/wiki/Query_string#URL_encoding].
for instance SPACE is encoded as '+' or "%20".
If entry must be equal to a string, use `entry='str'` (with the quotes)
Examples:
get all the science field 600
```field=600```
get all the science field 600 and having an airmass greater than 2
```field=600+AND+airmass>2```
get all the science field 600 and having an airmass greater than 2 with a quadran ID been 1 or 3
```field=600+AND+airmass>2+AND+qid+IN+(1,3)```
get observation taken since the 1st of Feb 2018 (julian date 2458150.5) with an airmass > 3
```airmass>3+AND+obsjd>2458150.5```
// If not Calibration //
ra,dec: [float/str]
ICRS right ascension and declination in decimal degrees.
It identifies the point which returned images must contain, or the center of the search region.
size: [float/str/None] -optional-
It consists of one or two (comma separated) values in decimal degrees.
(With POS=ra,dec)
The first value is taken to be the full-width of the search region along the east axis at POS,
and the second is taken to be the full-height along the north axis.
Taken together, POS and SIZE define a convex spherical polygon on the sky with great circle edges - the search region.
During a query, this region is compared against the convex spherical polygons formed by connecting
the 4 corners of each image in a data-set to determine which images should be returned.
If only one size value is specified, it is used as both the full-width and full-height.
Negative sizes are illegal, and a width and height of zero indicate that the search region is a point.
mcen: [bool] -optional-
[If the size parameter is specified and non-zero, the mcen parameter is ignored]
The mcen parameter indicates that only the most centered image/image set
(with respect to POS) should be returned, rather than all images/image sets containing POS.
// If Raw //
INFO:
sql_query has a entry to select the kind of data you are looking for:
- 'imgtypecode'-
Currently, the possible values for "imgtypecode" pertaining to raw image data files are:
o = science (on-sky)
b = bias calibration image
d = dark calibration image
f = dome/screen flatfield calibration image
// If Calibration //
caltype: [strin]
which calibration type? 'bias' or 'hifreqflat'
This classification will be added to the sql_query (caltype=`caltype`)
except if the sql_query already contains it.
If None, this will be ignored
"""
_test_kind_(kind)
if auth is not None:
from .io import get_cookie
kwargs["cookies"] = get_cookie(*auth)
if kind not in ['cal']:
# python3 -> self.metaquery = download_metadata(**{**locals(),**kwargs})
self.metaquery = download_metadata(kind=kind, radec=radec, size=size, mcen=mcen, sql_query=sql_query, **kwargs)
else:
for k in ["radec", "size", "mcen"]:
if locals()[k] is not None: warnings.warn("You are querying 'calibration data', the following entry is ignored: %s"%k)
if "caltype" not in sql_query and caltype is not None and caltype:
sql_query = "caltype=%s"%caltype if sql_query is None else sql_query+"+AND+caltype='%s'"%caltype
self.metaquery = download_metadata(kind=kind, sql_query=sql_query, **kwargs)
def get_data_path(self, suffix=None, source=None, indexes=None):
""" generic method to build the url/fullpath or the requested data.
This method is based on the `builurl.py` module of ztfquery.
Parameters
----------
suffix: [string] -optional-
What kind of data do you want?
Here is the list of available options depending on you image kind:
# Science image (kind="sci"):
- sciimg.fits (primary science image) # (default)
- mskimg.fits (bit-mask image)
- psfcat.fits (PSF-fit photometry catalog)
- sexcat.fits (nested-aperture photometry catalog)
- sciimgdao.psf (spatially varying PSF estimate in DAOPhot's lookup table format)
- sciimgdaopsfcent.fits (PSF estimate at science image center as a FITS image)
- sciimlog.txt (log output from instrumental calibration pipeline)
- scimrefdiffimg.fits.fz (difference image: science minus reference; fpack-compressed)
- diffimgpsf.fits (PSF estimate for difference image as a FITS image)
- diffimlog.txt (log output from image subtraction and extraction pipeline)
- log.txt (overall system summary log from realtime pipeline)
# Reference image (kind="ref"):
-log.txt
-refcov.fits
-refimg.fits # (default)
-refimlog.txt
-refpsfcat.fits
-refsexcat.fits
-refunc.fits
# Raw images (kind="raw")
No Choice so suffix is ignored for raw data
# Calibration (kind="cal")
- None (#default) returns `caltype`.fits
- log: returns `caltype`log.txt
- unc: returns `caltype`unc.fits
// if queried metadata is for kind calibration
"""
if not hasattr(self,"metaquery"):
raise AttributeError("metaquery has not been loaded. Run load_metadata(). ")
if self.metaquery.nentries ==0:
warnings.warn("No entry associated to the query you made: metatable is empty")
return []
return metatable_to_url(self.metatable if indexes is None else self.metatable.loc[np.atleast_1d(indexes)],
datakind=self.datakind, suffix=suffix, source=source)
# =============== #
# Properties #
# =============== #
@property
def datakind(self):
""" """
if not hasattr(self, "metaquery"):
raise AttributeError("metaquery has not been loaded. Run load_metadata(). ")
return self.metaquery.datakind
@property
def metatable(self):
""" """
if not hasattr(self, "metaquery"):
raise AttributeError("metaquery has not been loaded. Run load_metadata(). ")
return self.metaquery.metatable
#############################
# #
# Addition Queries #
# #
#############################
_NIGHT_SUMMARY_URL = "http://www.astro.caltech.edu/~tb/ztfops/sky/"
def convert_summary_to_dataframe(summary):
"""
Parameters
----------
summary: [list]
Format: Result from running requests.get(URL).text.splitlines()
"""
from pandas import DataFrame
if len(summary) == 0: return None
seperator_idxs = [idx for idx,char in enumerate(summary[0]) if char=='|'][:-1]
if len(seperator_idxs) == 0: return None
columns = [summary[0][i:j] for i,j in zip(seperator_idxs, seperator_idxs[1:]+[None])]
columns = [c.replace('|','').replace(' ','') for c in columns]
data = []
for line in summary[1:]:
if line.startswith('|'): continue
_data = [line[i:j] for i,j in zip(seperator_idxs, seperator_idxs[1:]+[None])]
_data = [d.replace('|','').replace(' ','') for d in _data]
data.append(_data)
dataf = DataFrame(data=data, columns=[l if l!= "fil" else "fid" for l in columns])
dataf["fid"][dataf["fid"]=="4"] = "3"
return dataf
def download_night_summary(night, ztfops_auth = None):
"""
Parameters
----------
night: [string]
Format: YYYYMMDD like for instance 20180429
ztfops_auth: [string, string] -optional-
Provide directly the [username, password] of the ztfops page.
"""
import requests
# = Password and username
if ztfops_auth is None:
from .io import _load_id_
ztfops_auth = _load_id_("ztfops", askit=True)
summary = requests.get(_NIGHT_SUMMARY_URL+"%s/exp.%s.tbl"%(night,night),
auth=ztfops_auth).content.decode('utf-8').splitlines()
dataf = convert_summary_to_dataframe(summary)
return dataf
def download_allnight_summary(ztfops_auth = None):
"""
Parameters
----------
ztfops_auth: [string, string] -optional-
Provide directly the [username, password] of the ztfops page.
"""
import requests
# = Password and username
if ztfops_auth is None:
from .io import _load_id_
ztfops_auth = _load_id_("ztfops", askit=True)
summary = requests.get(_NIGHT_SUMMARY_URL+"allexp.tbl",
auth=ztfops_auth).content.decode('utf-8').splitlines()
dataf = convert_summary_to_dataframe(summary)
return dataf
class NightSummary( _ZTFTableHandler_, _ZTFDownloader_ ):
def __init__(self, night, ztfops_auth=None):
""" """
self.night = night
self.data_all = download_night_summary(night, ztfops_auth=ztfops_auth)
if self.data_all is None:
self.data = None
else:
self.data = self.data_all[self.data_all["type"]=="targ"]
# ================ #
# Methods #
# ================ #
# --------- #
# GETTER #
# --------- #
def get_observed_information(self, obstype="targ", columns=["field","ra","dec"]):
""" get a DataFrame (pandas) of the requested columns for the given obstype.
Parameters
----------
obstype: [string]
Type of observation.
Could be: 'bias', 'dark', 'flat', or 'targ'
columns: [string or list of]
Any field available in data (check the list by doing THIS.data.columns)
Returns
-------
DataFrame
"""
return self.data[self.data['type']==obstype][columns]
# Download Data
def set_metadata(self, kind, **kwargs):
""" Set the mate information get_data_path need
Important: Some kwargs are mandatory dependending of you given kind:
- for kind "sci": ["paddedccdid", "qid"]
- for kind "raw": ["paddedccdid"]
(other kind not implemented yet)
"""
self._metadata = {}
MANDATORY = {"sci":["paddedccdid", "qid"],
"raw":["paddedccdid"],
"ref":{},
"cal":{}
}
DEFAULT = {"sci":{"imgtypecode":"o"},
"raw":{"imgtypecode":"o"},
"ref":{},
"cal":{}}
if kind not in ["raw","sci"]:
raise NotImplementedError("Only Science ('sci') or Raw ('raw') kinds ready (%s given)."%kind)
# Requested input
for k in MANDATORY[kind]:
if k not in kwargs.keys():
raise ValueError("%s should be provided for kind: %s"%(k,kind))
# -> python3 self._metadata = **{DEFAULT[kind], **kwargs}
self._metadata = DEFAULT[kind]
self._metadata["kind"] = kind
for k,v in kwargs.items():
self._metadata[k] = v
# -> python3 self._metadata = **{DEFAULT[kind], **kwargs}; self._metadata["kind"] = kind
# WRONG SO FAR
def get_data_path(self, mask=None, suffix=None, source=None, verbose=False, ):
""" generic method to build the url/fullpath or the requested data.
This method is based on the `builurl.py` module of ztfquery.
Parameters
----------
mask: [None / list of int / boolean array] -optional-
only use the data entry for the given mask:
```
fileroots = np.asarray(self.data["fileroot"])
if mask is not None:
fileroots = fileroots[mask]
```
suffix: [string] -optional-
What kind of data do you want?
Here is the list of available options depending on you image kind:
# Science image (kind="sci"):
- sciimg.fits (primary science image) # (default)
- mskimg.fits (bit-mask image)
- psfcat.fits (PSF-fit photometry catalog)
- sexcat.fits (nested-aperture photometry catalog)
- sciimgdao.psf (spatially varying PSF estimate in DAOPhot's lookup table format)
- sciimgdaopsfcent.fits (PSF estimate at science image center as a FITS image)
- sciimlog.txt (log output from instrumental calibration pipeline)
- scimrefdiffimg.fits.fz (difference image: science minus reference; fpack-compressed)
- diffimgpsf.fits (PSF estimate for difference image as a FITS image)
- diffimlog.txt (log output from image subtraction and extraction pipeline)
- log.txt (overall system summary log from realtime pipeline)
# Reference image (kind="ref"):
-log.txt
-refcov.fits
-refimg.fits # (default)
-refimlog.txt
-refpsfcat.fits
-refsexcat.fits
-refunc.fits
# Raw images (kind="raw")
No Choice so suffix is ignored for raw data
# Calibration (kind="cal")
- None (#default) returns `caltype`.fits
- log: returns `caltype`log.txt
- unc: returns `caltype`unc.fits
// if queried metadata is for kind calibration
"""
if not hasattr(self,"_metadata"):
raise AttributeError("you did not set the metadata, you must (see self.set_metadata()) ")
fileroots = np.asarray(self.data["fileroot"])
if mask is not None:
fileroots = fileroots[mask]
# Science Products
if self._metadata["kind"] in ['sci']:
from .buildurl import fileroot_to_science_url
if suffix is None:
suffix = "sciimg.fits"
return [fileroot_to_science_url(fileroot, self._metadata["paddedccdid"], self._metadata["qid"],
imgtypecode=self._metadata["imgtypecode"],
suffix=suffix, source=source,
verbose=verbose)
for fileroot in fileroots]
# Raw Data
elif self._metadata["kind"] in ["raw"]:
from .buildurl import fileroot_to_raw_url
return [fileroot_to_raw_url(fileroot, self._metadata["paddedccdid"],
imgtypecode=self._metadata["imgtypecode"],
source=source, verbose=verbose)
for fileroot in fileroots]
else:
raise NotImplementedError("Only Science ('sci') or Raw ('raw') kinds ready (%s given)."%kind)
| 43.529412
| 150
| 0.551294
|
7a6dcdce1f7488f07a954b1ee715a793d8d97935
| 87
|
py
|
Python
|
Renter/apps.py
|
Hyped-247/rp
|
9e3c6287ec2a183998f6ddadc20153736bbefaf3
|
[
"MIT"
] | null | null | null |
Renter/apps.py
|
Hyped-247/rp
|
9e3c6287ec2a183998f6ddadc20153736bbefaf3
|
[
"MIT"
] | null | null | null |
Renter/apps.py
|
Hyped-247/rp
|
9e3c6287ec2a183998f6ddadc20153736bbefaf3
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class RenterConfig(AppConfig):
name = 'Renter'
| 14.5
| 33
| 0.747126
|
ab14b5ab963b249674cefb4bb706c5511c93b30f
| 8,406
|
py
|
Python
|
TTS/vocoder/utils/generic_utils.py
|
mightmay/Mien-TTS
|
8a22ff0a79558b3cf4981ce1b63f4d1485ea6338
|
[
"MIT"
] | null | null | null |
TTS/vocoder/utils/generic_utils.py
|
mightmay/Mien-TTS
|
8a22ff0a79558b3cf4981ce1b63f4d1485ea6338
|
[
"MIT"
] | null | null | null |
TTS/vocoder/utils/generic_utils.py
|
mightmay/Mien-TTS
|
8a22ff0a79558b3cf4981ce1b63f4d1485ea6338
|
[
"MIT"
] | 1
|
2021-04-28T17:30:03.000Z
|
2021-04-28T17:30:03.000Z
|
import re
import torch
import importlib
import numpy as np
#from matplotlib import pyplot as plt
#from TTS.tts.utils.visual import plot_spectrogram
def interpolate_vocoder_input(scale_factor, spec):
"""Interpolate spectrogram by the scale factor.
It is mainly used to match the sampling rates of
the tts and vocoder models.
Args:
scale_factor (float): scale factor to interpolate the spectrogram
spec (np.array): spectrogram to be interpolated
Returns:
torch.tensor: interpolated spectrogram.
"""
print(" > before interpolation :", spec.shape)
spec = torch.tensor(spec).unsqueeze(0).unsqueeze(0) # pylint: disable=not-callable
spec = torch.nn.functional.interpolate(spec,
scale_factor=scale_factor,
recompute_scale_factor=True,
mode='bilinear',
align_corners=False).squeeze(0)
print(" > after interpolation :", spec.shape)
return spec
def plot_results(y_hat, y, ap, global_step, name_prefix):
""" Plot vocoder model results """
# select an instance from batch
y_hat = y_hat[0].squeeze(0).detach().cpu().numpy()
y = y[0].squeeze(0).detach().cpu().numpy()
spec_fake = ap.melspectrogram(y_hat).T
spec_real = ap.melspectrogram(y).T
spec_diff = np.abs(spec_fake - spec_real)
# plot figure and save it
# fig_wave = plt.figure()
# plt.subplot(2, 1, 1)
# plt.plot(y)
# plt.title("groundtruth speech")
# plt.subplot(2, 1, 2)
# plt.plot(y_hat)
# plt.title(f"generated speech @ {global_step} steps")
# plt.tight_layout()
# plt.close()
# figures = {
# name_prefix + "spectrogram/fake": plot_spectrogram(spec_fake),
# name_prefix + "spectrogram/real": plot_spectrogram(spec_real),
# name_prefix + "spectrogram/diff": plot_spectrogram(spec_diff),
# name_prefix + "speech_comparison": fig_wave,
# }
# return figures
def to_camel(text):
text = text.capitalize()
return re.sub(r'(?!^)_([a-zA-Z])', lambda m: m.group(1).upper(), text)
def setup_wavernn(c):
print(" > Model: WaveRNN")
MyModel = importlib.import_module("TTS.vocoder.models.wavernn")
MyModel = getattr(MyModel, "WaveRNN")
model = MyModel(
rnn_dims=c.wavernn_model_params['rnn_dims'],
fc_dims=c.wavernn_model_params['fc_dims'],
mode=c.mode,
mulaw=c.mulaw,
pad=c.padding,
use_aux_net=c.wavernn_model_params['use_aux_net'],
use_upsample_net=c.wavernn_model_params['use_upsample_net'],
upsample_factors=c.wavernn_model_params['upsample_factors'],
feat_dims=c.audio['num_mels'],
compute_dims=c.wavernn_model_params['compute_dims'],
res_out_dims=c.wavernn_model_params['res_out_dims'],
num_res_blocks=c.wavernn_model_params['num_res_blocks'],
hop_length=c.audio["hop_length"],
sample_rate=c.audio["sample_rate"],
)
return model
def setup_generator(c):
print(" > Generator Model: {}".format(c.generator_model))
MyModel = importlib.import_module('TTS.vocoder.models.' +
c.generator_model.lower())
MyModel = getattr(MyModel, to_camel(c.generator_model))
if c.generator_model.lower() in 'melgan_generator':
model = MyModel(
in_channels=c.audio['num_mels'],
out_channels=1,
proj_kernel=7,
base_channels=512,
upsample_factors=c.generator_model_params['upsample_factors'],
res_kernel=3,
num_res_blocks=c.generator_model_params['num_res_blocks'])
if c.generator_model in 'melgan_fb_generator':
pass
if c.generator_model.lower() in 'multiband_melgan_generator':
model = MyModel(
in_channels=c.audio['num_mels'],
out_channels=4,
proj_kernel=7,
base_channels=384,
upsample_factors=c.generator_model_params['upsample_factors'],
res_kernel=3,
num_res_blocks=c.generator_model_params['num_res_blocks'])
if c.generator_model.lower() in 'fullband_melgan_generator':
model = MyModel(
in_channels=c.audio['num_mels'],
out_channels=1,
proj_kernel=7,
base_channels=512,
upsample_factors=c.generator_model_params['upsample_factors'],
res_kernel=3,
num_res_blocks=c.generator_model_params['num_res_blocks'])
if c.generator_model.lower() in 'parallel_wavegan_generator':
model = MyModel(
in_channels=1,
out_channels=1,
kernel_size=3,
num_res_blocks=c.generator_model_params['num_res_blocks'],
stacks=c.generator_model_params['stacks'],
res_channels=64,
gate_channels=128,
skip_channels=64,
aux_channels=c.audio['num_mels'],
dropout=0.0,
bias=True,
use_weight_norm=True,
upsample_factors=c.generator_model_params['upsample_factors'])
if c.generator_model.lower() in 'wavegrad':
model = MyModel(
in_channels=c['audio']['num_mels'],
out_channels=1,
use_weight_norm=c['model_params']['use_weight_norm'],
x_conv_channels=c['model_params']['x_conv_channels'],
y_conv_channels=c['model_params']['y_conv_channels'],
dblock_out_channels=c['model_params']['dblock_out_channels'],
ublock_out_channels=c['model_params']['ublock_out_channels'],
upsample_factors=c['model_params']['upsample_factors'],
upsample_dilations=c['model_params']['upsample_dilations'])
return model
def setup_discriminator(c):
print(" > Discriminator Model: {}".format(c.discriminator_model))
if 'parallel_wavegan' in c.discriminator_model:
MyModel = importlib.import_module(
'TTS.vocoder.models.parallel_wavegan_discriminator')
else:
MyModel = importlib.import_module('TTS.vocoder.models.' +
c.discriminator_model.lower())
MyModel = getattr(MyModel, to_camel(c.discriminator_model.lower()))
if c.discriminator_model in 'random_window_discriminator':
model = MyModel(
cond_channels=c.audio['num_mels'],
hop_length=c.audio['hop_length'],
uncond_disc_donwsample_factors=c.
discriminator_model_params['uncond_disc_donwsample_factors'],
cond_disc_downsample_factors=c.
discriminator_model_params['cond_disc_downsample_factors'],
cond_disc_out_channels=c.
discriminator_model_params['cond_disc_out_channels'],
window_sizes=c.discriminator_model_params['window_sizes'])
if c.discriminator_model in 'melgan_multiscale_discriminator':
model = MyModel(
in_channels=1,
out_channels=1,
kernel_sizes=(5, 3),
base_channels=c.discriminator_model_params['base_channels'],
max_channels=c.discriminator_model_params['max_channels'],
downsample_factors=c.
discriminator_model_params['downsample_factors'])
if c.discriminator_model == 'residual_parallel_wavegan_discriminator':
model = MyModel(
in_channels=1,
out_channels=1,
kernel_size=3,
num_layers=c.discriminator_model_params['num_layers'],
stacks=c.discriminator_model_params['stacks'],
res_channels=64,
gate_channels=128,
skip_channels=64,
dropout=0.0,
bias=True,
nonlinear_activation="LeakyReLU",
nonlinear_activation_params={"negative_slope": 0.2},
)
if c.discriminator_model == 'parallel_wavegan_discriminator':
model = MyModel(
in_channels=1,
out_channels=1,
kernel_size=3,
num_layers=c.discriminator_model_params['num_layers'],
conv_channels=64,
dilation_factor=1,
nonlinear_activation="LeakyReLU",
nonlinear_activation_params={"negative_slope": 0.2},
bias=True
)
return model
# def check_config(c):
# c = None
# pass
| 38.737327
| 87
| 0.629669
|
74124ba4f7c25ec6be3d92cf6d4af888810f3930
| 742
|
py
|
Python
|
setup.py
|
kaapstorm/openhim-mediator-utils-py
|
7ad8dd44e9e97b5d3f44ce742241e72f748f2527
|
[
"MIT"
] | null | null | null |
setup.py
|
kaapstorm/openhim-mediator-utils-py
|
7ad8dd44e9e97b5d3f44ce742241e72f748f2527
|
[
"MIT"
] | null | null | null |
setup.py
|
kaapstorm/openhim-mediator-utils-py
|
7ad8dd44e9e97b5d3f44ce742241e72f748f2527
|
[
"MIT"
] | null | null | null |
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="openhim_mediator_utils",
version="0.0.2",
author="Lazola Sifuba",
author_email="sifubalazola@gmail.com",
description="A utility library for build openHIM mediators",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/de-laz/openhim-mediator-utils-py",
packages=setuptools.find_packages(),
classifiers=(
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
"Natural Language :: English",
"Intended Audience :: Developers"
)
)
| 30.916667
| 64
| 0.672507
|
1531bcc2d525378cece1b2f5f36171125215ff19
| 40
|
py
|
Python
|
label_studio/__init__.py
|
zoumt1633/label-studio
|
324d542b49b42cac5c9a3e23373b9febaf9a426e
|
[
"Apache-2.0"
] | null | null | null |
label_studio/__init__.py
|
zoumt1633/label-studio
|
324d542b49b42cac5c9a3e23373b9febaf9a426e
|
[
"Apache-2.0"
] | 7
|
2021-06-02T02:57:44.000Z
|
2022-03-12T00:48:20.000Z
|
__init__.py
|
JamesXChang/label_tool
|
f62470a2bf677a2dd1d18054baf2d651d69c83a9
|
[
"Apache-2.0"
] | null | null | null |
# Package version
__version__ = '0.7.2'
| 13.333333
| 21
| 0.7
|
0329ef5ebc67212c458f768eb1b608364a2ee9d0
| 11,543
|
py
|
Python
|
test/test_configuration.py
|
dakshinai/unit
|
fa4d4b61200b6f465edbe24ebcdce1a7a8675d39
|
[
"Apache-2.0"
] | null | null | null |
test/test_configuration.py
|
dakshinai/unit
|
fa4d4b61200b6f465edbe24ebcdce1a7a8675d39
|
[
"Apache-2.0"
] | null | null | null |
test/test_configuration.py
|
dakshinai/unit
|
fa4d4b61200b6f465edbe24ebcdce1a7a8675d39
|
[
"Apache-2.0"
] | null | null | null |
import unittest
from unit.control import TestControl
class TestConfiguration(TestControl):
prerequisites = {'modules': {'python': 'any'}}
def test_json_empty(self):
self.assertIn('error', self.conf(''), 'empty')
def test_json_leading_zero(self):
self.assertIn('error', self.conf('00'), 'leading zero')
def test_json_unicode(self):
self.assertIn(
'success',
self.conf(
b"""
{
"ap\u0070": {
"type": "\u0070ython",
"processes": { "spare": 0 },
"path": "\u002Fapp",
"module": "wsgi"
}
}
""",
'applications',
),
'unicode',
)
self.assertDictEqual(
self.conf_get('applications'),
{
"app": {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
},
'unicode get',
)
def test_json_unicode_2(self):
self.assertIn(
'success',
self.conf(
{
"приложение": {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
},
'applications',
),
'unicode 2',
)
self.assertIn(
'приложение', self.conf_get('applications'), 'unicode 2 get'
)
def test_json_unicode_number(self):
self.assertIn(
'error',
self.conf(
b"""
{
"app": {
"type": "python",
"processes": { "spare": \u0030 },
"path": "/app",
"module": "wsgi"
}
}
""",
'applications',
),
'unicode number',
)
def test_json_utf8_bom(self):
self.assertIn(
'success',
self.conf(
b"""\xEF\xBB\xBF
{
"app": {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi"
}
}
""",
'applications',
),
'UTF-8 BOM',
)
def test_json_comment_single_line(self):
self.assertIn(
'success',
self.conf(
b"""
// this is bridge
{
"//app": {
"type": "python", // end line
"processes": {"spare": 0},
// inside of block
"path": "/app",
"module": "wsgi"
}
// double //
}
// end of json \xEF\t
""",
'applications',
),
'single line comments',
)
def test_json_comment_multi_line(self):
self.assertIn(
'success',
self.conf(
b"""
/* this is bridge */
{
"/*app": {
/**
* multiple lines
**/
"type": "python",
"processes": /* inline */ {"spare": 0},
"path": "/app",
"module": "wsgi"
/*
// end of block */
}
/* blah * / blah /* blah */
}
/* end of json \xEF\t\b */
""",
'applications',
),
'multi line comments',
)
def test_json_comment_invalid(self):
self.assertIn('error', self.conf(b'/{}', 'applications'), 'slash')
self.assertIn('error', self.conf(b'//{}', 'applications'), 'comment')
self.assertIn('error', self.conf(b'{} /', 'applications'), 'slash end')
self.assertIn(
'error', self.conf(b'/*{}', 'applications'), 'slash star'
)
self.assertIn(
'error', self.conf(b'{} /*', 'applications'), 'slash star end'
)
def test_applications_open_brace(self):
self.assertIn('error', self.conf('{', 'applications'), 'open brace')
def test_applications_string(self):
self.assertIn('error', self.conf('"{}"', 'applications'), 'string')
@unittest.skip('not yet, unsafe')
def test_applications_type_only(self):
self.assertIn(
'error',
self.conf({"app": {"type": "python"}}, 'applications'),
'type only',
)
def test_applications_miss_quote(self):
self.assertIn(
'error',
self.conf(
"""
{
app": {
"type": "python",
"processes": { "spare": 0 },
"path": "/app",
"module": "wsgi"
}
}
""",
'applications',
),
'miss quote',
)
def test_applications_miss_colon(self):
self.assertIn(
'error',
self.conf(
"""
{
"app" {
"type": "python",
"processes": { "spare": 0 },
"path": "/app",
"module": "wsgi"
}
}
""",
'applications',
),
'miss colon',
)
def test_applications_miss_comma(self):
self.assertIn(
'error',
self.conf(
"""
{
"app": {
"type": "python"
"processes": { "spare": 0 },
"path": "/app",
"module": "wsgi"
}
}
""",
'applications',
),
'miss comma',
)
def test_applications_skip_spaces(self):
self.assertIn(
'success', self.conf(b'{ \n\r\t}', 'applications'), 'skip spaces'
)
def test_applications_relative_path(self):
self.assertIn(
'success',
self.conf(
{
"app": {
"type": "python",
"processes": {"spare": 0},
"path": "../app",
"module": "wsgi",
}
},
'applications',
),
'relative path',
)
@unittest.skip('not yet, unsafe')
def test_listeners_empty(self):
self.assertIn(
'error', self.conf({"*:7080": {}}, 'listeners'), 'listener empty'
)
def test_listeners_no_app(self):
self.assertIn(
'error',
self.conf({"*:7080": {"pass": "applications/app"}}, 'listeners'),
'listeners no app',
)
def test_listeners_wildcard(self):
self.assertIn(
'success',
self.conf(
{
"listeners": {"*:7080": {"pass": "applications/app"}},
"applications": {
"app": {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
},
}
),
'listeners wildcard',
)
def test_listeners_explicit(self):
self.assertIn(
'success',
self.conf(
{
"listeners": {"127.0.0.1:7080": {"pass": "applications/app"}},
"applications": {
"app": {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
},
}
),
'explicit',
)
def test_listeners_explicit_ipv6(self):
self.assertIn(
'success',
self.conf(
{
"listeners": {"[::1]:7080": {"pass": "applications/app"}},
"applications": {
"app": {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
},
}
),
'explicit ipv6',
)
@unittest.skip('not yet, unsafe')
def test_listeners_no_port(self):
self.assertIn(
'error',
self.conf(
{
"listeners": {"127.0.0.1": {"pass": "applications/app"}},
"applications": {
"app": {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
},
}
),
'no port',
)
def test_json_application_name_large(self):
name = "X" * 1024 * 1024
self.assertIn(
'success',
self.conf(
{
"listeners": {"*:7080": {"pass": "applications/" + name}},
"applications": {
name: {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
},
}
),
)
@unittest.skip('not yet')
def test_json_application_many(self):
apps = 999
conf = {
"applications": {
"app-"
+ str(a): {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
for a in range(apps)
},
"listeners": {
"*:" + str(7000 + a): {"pass": "applications/app-" + str(a)}
for a in range(apps)
},
}
self.assertIn('success', self.conf(conf))
def test_json_application_many2(self):
conf = {
"applications": {
"app-"
+ str(a): {
"type": "python",
"processes": {"spare": 0},
"path": "/app",
"module": "wsgi",
}
for a in range(999)
},
"listeners": {"*:7080": {"pass": "applications/app-1"}},
}
self.assertIn('success', self.conf(conf))
if __name__ == '__main__':
TestConfiguration.main()
| 27.949153
| 82
| 0.337434
|
9ddc1e4c427fc896f59147e82a57abf479bb7b6a
| 3,024
|
py
|
Python
|
utils/check_ptc.py
|
bl0x/symbiflow-arch-defs
|
5fa5e71526e443d589971f2649d8b189df982d72
|
[
"ISC"
] | 183
|
2017-12-29T12:08:32.000Z
|
2022-02-15T03:29:07.000Z
|
utils/check_ptc.py
|
bl0x/symbiflow-arch-defs
|
5fa5e71526e443d589971f2649d8b189df982d72
|
[
"ISC"
] | 1,832
|
2017-12-29T14:47:27.000Z
|
2022-02-18T06:30:43.000Z
|
utils/check_ptc.py
|
bl0x/symbiflow-arch-defs
|
5fa5e71526e443d589971f2649d8b189df982d72
|
[
"ISC"
] | 96
|
2017-12-30T12:00:45.000Z
|
2022-02-17T09:03:46.000Z
|
#!/usr/bin/env python3
""" Tool for sanity checking rrgraph CHAN PTC's.
"""
import lxml.etree as ET
import argparse
def check_ptc(xml):
""" Checks ptc values used on CHANX and CHANY rr graph nodes are valid.
CHAN ptc numbers are an index per x/y coordinate and channel type (CHANX or
CHANY). ptc's at a particular coordinate/type must start at 0, and fill
to the max value.
"""
chan_ptcs = {}
nodes = {}
for node in xml.find('rr_nodes').iter('node'):
assert node.attrib['id'] not in nodes
nodes[node.attrib['id']] = node
node_type = node.attrib['type']
if node_type in ['CHANX', 'CHANY']:
loc_xml = node.find('loc')
assert loc_xml is not None
for x in range(int(loc_xml.attrib['xlow']),
int(loc_xml.attrib['xhigh']) + 1):
for y in range(int(loc_xml.attrib['ylow']),
int(loc_xml.attrib['yhigh']) + 1):
key = (node_type, x, y)
if key not in chan_ptcs:
chan_ptcs[key] = []
chan_ptcs[key].append(
(node.attrib['id'], int(loc_xml.attrib['ptc']))
)
for (node_type, x, y), node_ptcs in chan_ptcs.items():
nodes, ptcs = zip(*node_ptcs)
starts_at_zero = min(ptcs) == 0
ends_at_max_val = max(ptcs) == len(ptcs) - 1
all_values_present = len(ptcs) == len(set(ptcs))
if not all((starts_at_zero, ends_at_max_val, all_values_present)):
sorted_nodes = sorted(zip(ptcs, nodes), key=lambda x: x[0])
for idx, (ptc, node) in enumerate(sorted_nodes):
if idx == ptc:
continue
if idx > 1:
raise ValueError(
"""\
Gap in ptc value for type = {node_type} @ ({x}, {y})
Expect PTC = {idx}, found {ptc}
Current node is id = {cur_node}
Previous node is id = {prev_node}""".format(
x=x,
y=y,
node_type=node_type,
idx=idx,
ptc=ptc,
cur_node=node,
prev_node=sorted_nodes[idx - 1][1],
)
)
else:
raise ValueError(
"Lowest ptc is {ptc} for type = {node_type} @ ({x}, {y})"
.format(
x=x,
y=y,
node_type=node_type,
ptc=ptc,
)
)
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('input_xml')
args = parser.parse_args()
xml = ET.parse(args.input_xml, ET.XMLParser(remove_blank_text=True))
check_ptc(xml)
if __name__ == "__main__":
main()
| 32.170213
| 81
| 0.473214
|
5ece83c146b267015534c04adf7a992e3a427ab4
| 18,334
|
py
|
Python
|
src/python/pants/backend/project_info/tasks/export.py
|
sammy-1234/pants
|
889016952a248cf229c78c014d9f6c95422d98b8
|
[
"Apache-2.0"
] | 1
|
2020-08-26T03:30:31.000Z
|
2020-08-26T03:30:31.000Z
|
src/python/pants/backend/project_info/tasks/export.py
|
sammy-1234/pants
|
889016952a248cf229c78c014d9f6c95422d98b8
|
[
"Apache-2.0"
] | 1
|
2021-09-02T14:16:37.000Z
|
2021-09-02T14:16:37.000Z
|
src/python/pants/backend/project_info/tasks/export.py
|
sammy-1234/pants
|
889016952a248cf229c78c014d9f6c95422d98b8
|
[
"Apache-2.0"
] | null | null | null |
# Copyright 2014 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
import json
import os
from collections import defaultdict
from twitter.common.collections import OrderedSet
from pants.backend.jvm.subsystems.jvm_platform import JvmPlatform
from pants.backend.jvm.subsystems.resolve_subsystem import JvmResolveSubsystem
from pants.backend.jvm.targets.jar_library import JarLibrary
from pants.backend.jvm.targets.junit_tests import JUnitTests
from pants.backend.jvm.targets.jvm_app import JvmApp
from pants.backend.jvm.targets.jvm_target import JvmTarget
from pants.backend.jvm.targets.scala_library import ScalaLibrary
from pants.backend.jvm.tasks.classpath_products import ClasspathProducts
from pants.backend.jvm.tasks.coursier_resolve import CoursierMixin
from pants.backend.jvm.tasks.ivy_task_mixin import IvyTaskMixin
from pants.backend.python.interpreter_cache import PythonInterpreterCache
from pants.backend.python.subsystems.pex_build_util import has_python_requirements
from pants.backend.python.targets.python_requirement_library import PythonRequirementLibrary
from pants.backend.python.targets.python_target import PythonTarget
from pants.backend.python.targets.python_tests import PythonTests
from pants.backend.python.tasks.resolve_requirements_task_base import ResolveRequirementsTaskBase
from pants.base.build_environment import get_buildroot
from pants.base.exceptions import TaskError
from pants.build_graph.resources import Resources
from pants.build_graph.target import Target
from pants.invalidation.cache_manager import VersionedTargetSet
from pants.java.distribution.distribution import DistributionLocator
from pants.java.executor import SubprocessExecutor
from pants.java.jar.jar_dependency_utils import M2Coordinate
from pants.task.console_task import ConsoleTask
from pants.util.memo import memoized_property
# Changing the behavior of this task may affect the IntelliJ Pants plugin.
# Please add @yic to reviews for this file.
class ExportTask(ResolveRequirementsTaskBase, IvyTaskMixin, CoursierMixin):
"""Base class for generating a json-formattable blob of data about the target graph.
Subclasses can invoke the generate_targets_map method to get a dictionary of plain datastructures
(dicts, lists, strings) that can be easily read and exported to various formats.
"""
# FORMAT_VERSION_NUMBER: Version number for identifying the export file format output. This
# version number should change when there is a change to the output format.
#
# Major Version 1.x.x : Increment this field when there is a major format change
# Minor Version x.1.x : Increment this field when there is a minor change that breaks backward
# compatibility for an existing field or a field is removed.
# Patch version x.x.1 : Increment this field when a minor format change that just adds information
# that an application can safely ignore.
#
# Note format changes in src/docs/export.md and update the Changelog section.
#
DEFAULT_EXPORT_VERSION = '1.0.10'
@classmethod
def subsystem_dependencies(cls):
return super().subsystem_dependencies() + (
DistributionLocator, JvmPlatform, PythonInterpreterCache
)
class SourceRootTypes:
"""Defines SourceRoot Types Constants"""
SOURCE = 'SOURCE' # Source Target
TEST = 'TEST' # Test Target
SOURCE_GENERATED = 'SOURCE_GENERATED' # Code Gen Source Targets
EXCLUDED = 'EXCLUDED' # Excluded Target
RESOURCE = 'RESOURCE' # Resource belonging to Source Target
TEST_RESOURCE = 'TEST_RESOURCE' # Resource belonging to Test Target
@staticmethod
def _is_jvm(dep):
return isinstance(dep, (JarLibrary, JvmTarget, JvmApp))
@staticmethod
def _jar_id(jar):
"""Create a string identifier for the IvyModuleRef key.
:param IvyModuleRef jar: key for a resolved jar
:returns: String representing the key as a maven coordinate
"""
if jar.rev:
return '{0}:{1}:{2}'.format(jar.org, jar.name, jar.rev)
else:
return '{0}:{1}'.format(jar.org, jar.name)
@staticmethod
def _exclude_id(jar):
"""Create a string identifier for the Exclude key.
:param Exclude jar: key for an excluded jar
:returns: String representing the key as a maven coordinate
"""
return '{0}:{1}'.format(jar.org, jar.name) if jar.name else jar.org
@classmethod
def register_options(cls, register):
super().register_options(register)
register('--libraries', default=True, type=bool,
help='Causes libraries to be output.')
register('--libraries-sources', type=bool,
help='Causes libraries with sources to be output.')
register('--libraries-javadocs', type=bool,
help='Causes libraries with javadocs to be output.')
register('--sources', type=bool,
help='Causes sources to be output.')
register('--formatted', type=bool, implicit_value=False,
help='Causes output to be a single line of JSON.')
register('--jvm-options', type=list, metavar='<option>...',
help='Run the JVM 3rdparty resolver with these jvm options.')
@classmethod
def prepare(cls, options, round_manager):
super().prepare(options, round_manager)
if options.libraries or options.libraries_sources or options.libraries_javadocs:
round_manager.optional_data('java')
round_manager.optional_data('scala')
@memoized_property
def _interpreter_cache(self):
return PythonInterpreterCache.global_instance()
def check_artifact_cache_for(self, invalidation_check):
# Export is an output dependent on the entire target set, and is not divisible
# by target. So we can only cache it keyed by the entire target set.
global_vts = VersionedTargetSet.from_versioned_targets(invalidation_check.all_vts)
return [global_vts]
def resolve_jars(self, targets):
# TODO: Why is this computed directly here instead of taking from the actual product
# computed by the {Ivy,Coursier}Resolve task?
executor = SubprocessExecutor(DistributionLocator.cached())
confs = []
if self.get_options().libraries:
confs.append('default')
if self.get_options().libraries_sources:
confs.append('sources')
if self.get_options().libraries_javadocs:
confs.append('javadoc')
compile_classpath = None
if confs:
compile_classpath = ClasspathProducts(self.get_options().pants_workdir)
if JvmResolveSubsystem.global_instance().get_options().resolver == 'ivy':
IvyTaskMixin.resolve(self, executor=executor,
targets=targets,
classpath_products=compile_classpath,
confs=confs)
else:
CoursierMixin.resolve(self, targets, compile_classpath,
sources=self.get_options().libraries_sources,
javadoc=self.get_options().libraries_javadocs,
executor=executor)
return compile_classpath
def generate_targets_map(self, targets, classpath_products=None):
"""Generates a dictionary containing all pertinent information about the target graph.
The return dictionary is suitable for serialization by json.dumps.
:param targets: The list of targets to generate the map for.
:param classpath_products: Optional classpath_products. If not provided when the --libraries
option is `True`, this task will perform its own jar resolution.
"""
targets_map = {}
resource_target_map = {}
python_interpreter_targets_mapping = defaultdict(list)
if self.get_options().libraries:
# NB(gmalmquist): This supports mocking the classpath_products in tests.
if classpath_products is None:
classpath_products = self.resolve_jars(targets)
else:
classpath_products = None
target_roots_set = set(self.context.target_roots)
def process_target(current_target):
"""
:type current_target:pants.build_graph.target.Target
"""
def get_target_type(tgt):
def is_test(t):
return isinstance(t, JUnitTests) or isinstance(t, PythonTests)
if is_test(tgt):
return ExportTask.SourceRootTypes.TEST
else:
if (isinstance(tgt, Resources) and
tgt in resource_target_map and
is_test(resource_target_map[tgt])):
return ExportTask.SourceRootTypes.TEST_RESOURCE
elif isinstance(tgt, Resources):
return ExportTask.SourceRootTypes.RESOURCE
else:
return ExportTask.SourceRootTypes.SOURCE
info = {
'targets': [],
'libraries': [],
'roots': [],
'id': current_target.id,
'target_type': get_target_type(current_target),
# NB: is_code_gen should be removed when export format advances to 1.1.0 or higher
'is_code_gen': current_target.is_synthetic,
'is_synthetic': current_target.is_synthetic,
'pants_target_type': self._get_pants_target_alias(type(current_target)),
}
if not current_target.is_synthetic:
info['globs'] = current_target.globs_relative_to_buildroot()
if self.get_options().sources:
info['sources'] = list(current_target.sources_relative_to_buildroot())
info['transitive'] = current_target.transitive
info['scope'] = str(current_target.scope)
info['is_target_root'] = current_target in target_roots_set
if isinstance(current_target, PythonRequirementLibrary):
reqs = current_target.payload.get_field_value('requirements', set())
""":type : set[pants.backend.python.python_requirement.PythonRequirement]"""
info['requirements'] = [req.key for req in reqs]
if isinstance(current_target, PythonTarget):
interpreter_for_target = self._interpreter_cache.select_interpreter_for_targets(
[current_target])
if interpreter_for_target is None:
raise TaskError('Unable to find suitable interpreter for {}'
.format(current_target.address))
python_interpreter_targets_mapping[interpreter_for_target].append(current_target)
info['python_interpreter'] = str(interpreter_for_target.identity)
def iter_transitive_jars(jar_lib):
"""
:type jar_lib: :class:`pants.backend.jvm.targets.jar_library.JarLibrary`
:rtype: :class:`collections.Iterator` of
:class:`pants.java.jar.M2Coordinate`
"""
if classpath_products:
jar_products = classpath_products.get_artifact_classpath_entries_for_targets((jar_lib,))
for _, jar_entry in jar_products:
coordinate = jar_entry.coordinate
# We drop classifier and type_ since those fields are represented in the global
# libraries dict and here we just want the key into that dict (see `_jar_id`).
yield M2Coordinate(org=coordinate.org, name=coordinate.name, rev=coordinate.rev)
target_libraries = OrderedSet()
if isinstance(current_target, JarLibrary):
target_libraries = OrderedSet(iter_transitive_jars(current_target))
for dep in current_target.dependencies:
info['targets'].append(dep.address.spec)
if isinstance(dep, JarLibrary):
for jar in dep.jar_dependencies:
target_libraries.add(M2Coordinate(jar.org, jar.name, jar.rev))
# Add all the jars pulled in by this jar_library
target_libraries.update(iter_transitive_jars(dep))
if isinstance(dep, Resources):
resource_target_map[dep] = current_target
if isinstance(current_target, ScalaLibrary):
for dep in current_target.java_sources:
info['targets'].append(dep.address.spec)
process_target(dep)
if isinstance(current_target, JvmTarget):
info['excludes'] = [self._exclude_id(exclude) for exclude in current_target.excludes]
info['platform'] = current_target.platform.name
if hasattr(current_target, 'test_platform'):
info['test_platform'] = current_target.test_platform.name
info['roots'] = [{
'source_root': source_root_package_prefix[0],
'package_prefix': source_root_package_prefix[1]
} for source_root_package_prefix in self._source_roots_for_target(current_target)]
if classpath_products:
info['libraries'] = [self._jar_id(lib) for lib in target_libraries]
targets_map[current_target.address.spec] = info
for target in targets:
process_target(target)
jvm_platforms_map = {
'default_platform' : JvmPlatform.global_instance().default_platform.name,
'platforms': {
str(platform_name): {
'target_level' : str(platform.target_level),
'source_level' : str(platform.source_level),
'args' : platform.args,
} for platform_name, platform in JvmPlatform.global_instance().platforms_by_name.items() },
}
graph_info = {
'version': self.DEFAULT_EXPORT_VERSION,
'targets': targets_map,
'jvm_platforms': jvm_platforms_map,
# `jvm_distributions` are static distribution settings from config,
# `preferred_jvm_distributions` are distributions that pants actually uses for the
# given platform setting.
'preferred_jvm_distributions': {}
}
for platform_name, platform in JvmPlatform.global_instance().platforms_by_name.items():
preferred_distributions = {}
for strict, strict_key in [(True, 'strict'), (False, 'non_strict')]:
try:
dist = JvmPlatform.preferred_jvm_distribution([platform], strict=strict)
preferred_distributions[strict_key] = dist.home
except DistributionLocator.Error:
pass
if preferred_distributions:
graph_info['preferred_jvm_distributions'][platform_name] = preferred_distributions
if classpath_products:
graph_info['libraries'] = self._resolve_jars_info(targets, classpath_products)
if python_interpreter_targets_mapping:
# NB: We've selected a python interpreter compatible with each python target individually into
# the `python_interpreter_targets_mapping`. These python targets may not be compatible, ie: we
# could have a python target requiring 'CPython>=2.7<3' (ie: CPython-2.7.x) and another
# requiring 'CPython>=3.6'. To pick a default interpreter then from among these two choices
# is arbitrary and not to be relied on to work as a default interpreter if ever needed by the
# export consumer.
#
# TODO(John Sirois): consider either eliminating the 'default_interpreter' field and pressing
# export consumers to make their own choice of a default (if needed) or else use
# `select.select_interpreter_for_targets` and fail fast if there is no interpreter compatible
# across all the python targets in-play.
#
# For now, make our arbitrary historical choice of a default interpreter explicit and use the
# lowest version.
default_interpreter = min(python_interpreter_targets_mapping.keys())
interpreters_info = {}
for interpreter, targets in python_interpreter_targets_mapping.items():
req_libs = [target for target in Target.closure_for_targets(targets)
if has_python_requirements(target)]
chroot = self.resolve_requirements(interpreter, req_libs)
interpreters_info[str(interpreter.identity)] = {
'binary': interpreter.binary,
'chroot': chroot.path()
}
graph_info['python_setup'] = {
'default_interpreter': str(default_interpreter.identity),
'interpreters': interpreters_info
}
return graph_info
def _resolve_jars_info(self, targets, classpath_products):
"""Consults ivy_jar_products to export the external libraries.
:return: mapping of jar_id -> { 'default' : <jar_file>,
'sources' : <jar_file>,
'javadoc' : <jar_file>,
<other_confs> : <jar_file>,
}
"""
mapping = defaultdict(dict)
jar_products = classpath_products.get_artifact_classpath_entries_for_targets(
targets, respect_excludes=False)
for conf, jar_entry in jar_products:
conf = jar_entry.coordinate.classifier or 'default'
mapping[self._jar_id(jar_entry.coordinate)][conf] = jar_entry.cache_path
return mapping
@memoized_property
def target_aliases_map(self):
registered_aliases = self.context.build_configuration.registered_aliases()
mapping = {}
for alias, target_types in registered_aliases.target_types_by_alias.items():
# If a target class is registered under multiple aliases returns the last one.
for target_type in target_types:
mapping[target_type] = alias
return mapping
def _get_pants_target_alias(self, pants_target_type):
"""Returns the pants target alias for the given target"""
if pants_target_type in self.target_aliases_map:
return self.target_aliases_map.get(pants_target_type)
else:
return "{}.{}".format(pants_target_type.__module__, pants_target_type.__name__)
@staticmethod
def _source_roots_for_target(target):
"""
:type target:pants.build_graph.target.Target
"""
def root_package_prefix(source_file):
source = os.path.dirname(source_file)
return os.path.join(get_buildroot(), target.target_base, source), source.replace(os.sep, '.')
return {root_package_prefix(source) for source in target.sources_relative_to_source_root()}
class Export(ExportTask, ConsoleTask):
"""Export project information in JSON format.
Intended for exporting project information for IDE, such as the IntelliJ Pants plugin.
"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def console_output(self, targets, classpath_products=None):
graph_info = self.generate_targets_map(targets, classpath_products=classpath_products)
if self.get_options().formatted:
return json.dumps(graph_info, indent=4, separators=(',', ': ')).splitlines()
else:
return [json.dumps(graph_info)]
| 44.285024
| 100
| 0.709392
|
4830965a20d0892745d93688393110ab2193b038
| 18,094
|
py
|
Python
|
weewx/bin/weewx/drivers/ws1.py
|
tony-rasskazov/meteo
|
1cb41cb4f219ff4e13a3ffb377f9ebf228711b96
|
[
"MIT"
] | null | null | null |
weewx/bin/weewx/drivers/ws1.py
|
tony-rasskazov/meteo
|
1cb41cb4f219ff4e13a3ffb377f9ebf228711b96
|
[
"MIT"
] | null | null | null |
weewx/bin/weewx/drivers/ws1.py
|
tony-rasskazov/meteo
|
1cb41cb4f219ff4e13a3ffb377f9ebf228711b96
|
[
"MIT"
] | 1
|
2020-07-15T16:38:03.000Z
|
2020-07-15T16:38:03.000Z
|
#!/usr/bin/env python
#
# Copyright 2014 Matthew Wall
# See the file LICENSE.txt for your rights.
"""Driver for ADS WS1 weather stations.
Thanks to Kevin and Paul Caccamo for adding the serial-to-tcp capability.
Thanks to Steve (sesykes71) for the testing that made this driver possible.
Thanks to Jay Nugent (WB8TKL) and KRK6 for weather-2.kr6k-V2.1
http://server1.nuge.com/~weather/
"""
from __future__ import with_statement
import syslog
import time
import weewx.drivers
DRIVER_NAME = 'WS1'
DRIVER_VERSION = '0.24'
def loader(config_dict, _):
return WS1Driver(**config_dict[DRIVER_NAME])
def confeditor_loader():
return WS1ConfEditor()
INHG_PER_MBAR = 0.0295333727
METER_PER_FOOT = 0.3048
MILE_PER_KM = 0.621371
DEFAULT_SER_PORT = '/dev/ttyS0'
DEFAULT_TCP_ADDR = '192.168.36.25'
DEFAULT_TCP_PORT = 3000
PACKET_SIZE = 50
DEBUG_READ = 0
def logmsg(level, msg):
syslog.syslog(level, 'ws1: %s' % msg)
def logdbg(msg):
logmsg(syslog.LOG_DEBUG, msg)
def loginf(msg):
logmsg(syslog.LOG_INFO, msg)
def logerr(msg):
logmsg(syslog.LOG_ERR, msg)
class WS1Driver(weewx.drivers.AbstractDevice):
"""weewx driver that communicates with an ADS-WS1 station
mode - Communication mode - TCP, UDP, or Serial.
[Required. Default is serial]
port - Serial port or network address.
[Required. Default is /dev/ttyS0 for serial, and 192.168.36.25:3000 for TCP]
max_tries - how often to retry serial communication before giving up.
[Optional. Default is 5]
retry_wait - how long to wait, in seconds, before retrying after a failure.
[Optional. Default is 10]
timeout - The amount of time, in seconds, before the connection fails if
there is no response.
[Optional. Default is 3]
debug_read - The level of message logging. The higher this number, the more
information is logged.
[Optional. Default is 0]
"""
def __init__(self, **stn_dict):
loginf('driver version is %s' % DRIVER_VERSION)
con_mode = stn_dict.get('mode', 'serial').lower()
if con_mode == 'tcp' or con_mode == 'udp':
self.port = stn_dict.get(
'port', '%s:%d' % (DEFAULT_TCP_ADDR, DEFAULT_TCP_PORT))
else:
self.port = stn_dict.get('port', DEFAULT_SER_PORT)
self.max_tries = int(stn_dict.get('max_tries', 5))
self.retry_wait = int(stn_dict.get('retry_wait', 10))
self.last_rain = None
timeout = int(stn_dict.get('timeout', 3))
loginf('using %s port %s' % (con_mode, self.port))
global DEBUG_READ
DEBUG_READ = int(stn_dict.get('debug_read', DEBUG_READ))
if con_mode == 'tcp' or con_mode == 'udp':
self.station = StationInet(self.port, con_mode, timeout=timeout)
else:
self.station = StationSerial(self.port, timeout=timeout)
self.station.open()
def closePort(self):
if self.station is not None:
self.station.close()
self.station = None
@property
def hardware_name(self):
return "WS1"
def genLoopPackets(self):
while True:
packet = {'dateTime': int(time.time() + 0.5),
'usUnits': weewx.US}
readings = self.station.get_readings_with_retry(self.max_tries,
self.retry_wait)
data = StationData.parse_readings(readings)
packet.update(data)
self._augment_packet(packet)
yield packet
def _augment_packet(self, packet):
# calculate the rain delta from rain total
if self.last_rain is not None:
packet['rain'] = packet['long_term_rain'] - self.last_rain
else:
packet['rain'] = None
self.last_rain = packet['long_term_rain']
# =========================================================================== #
# Station data class - parses and validates data from the device #
# =========================================================================== #
class StationData(object):
def __init__(self):
pass
@staticmethod
def validate_string(buf):
if len(buf) != PACKET_SIZE:
raise weewx.WeeWxIOError("Unexpected buffer length %d" % len(buf))
if buf[0:2] != '!!':
raise weewx.WeeWxIOError("Unexpected header bytes '%s'" % buf[0:2])
return buf
@staticmethod
def parse_readings(raw):
"""WS1 station emits data in PeetBros format:
http://www.peetbros.com/shop/custom.aspx?recid=29
Each line has 50 characters - 2 header bytes and 48 data bytes:
!!000000BE02EB000027700000023A023A0025005800000000
SSSSXXDDTTTTLLLLPPPPttttHHHHhhhhddddmmmmRRRRWWWW
SSSS - wind speed (0.1 kph)
XX - wind direction calibration
DD - wind direction (0-255)
TTTT - outdoor temperature (0.1 F)
LLLL - long term rain (0.01 in)
PPPP - pressure (0.1 mbar)
tttt - indoor temperature (0.1 F)
HHHH - outdoor humidity (0.1 %)
hhhh - indoor humidity (0.1 %)
dddd - date (day of year)
mmmm - time (minute of day)
RRRR - daily rain (0.01 in)
WWWW - one minute wind average (0.1 kph)
"""
# FIXME: peetbros could be 40 bytes or 44 bytes, what about ws1?
# FIXME: peetbros uses two's complement for temp, what about ws1?
# FIXME: for ws1 is the pressure reading 'pressure' or 'barometer'?
buf = raw[2:]
data = dict()
data['windSpeed'] = StationData._decode(buf[0:4], 0.1 * MILE_PER_KM) # mph
data['windDir'] = StationData._decode(buf[6:8], 1.411764) # compass deg
data['outTemp'] = StationData._decode(buf[8:12], 0.1, True) # degree_F
data['long_term_rain'] = StationData._decode(buf[12:16], 0.01) # inch
data['pressure'] = StationData._decode(buf[16:20], 0.1 * INHG_PER_MBAR) # inHg
data['inTemp'] = StationData._decode(buf[20:24], 0.1, True) # degree_F
data['outHumidity'] = StationData._decode(buf[24:28], 0.1) # percent
data['inHumidity'] = StationData._decode(buf[28:32], 0.1) # percent
data['day_of_year'] = StationData._decode(buf[32:36])
data['minute_of_day'] = StationData._decode(buf[36:40])
data['daily_rain'] = StationData._decode(buf[40:44], 0.01) # inch
data['wind_average'] = StationData._decode(buf[44:48], 0.1 * MILE_PER_KM) # mph
return data
@staticmethod
def _decode(s, multiplier=None, neg=False):
v = None
try:
v = int(s, 16)
if neg:
bits = 4 * len(s)
if v & (1 << (bits - 1)) != 0:
v -= (1 << bits)
if multiplier is not None:
v *= multiplier
except ValueError, e:
if s != '----':
logdbg("decode failed for '%s': %s" % (s, e))
return v
# =========================================================================== #
# Station Serial class - Gets data through a serial port #
# =========================================================================== #
class StationSerial(object):
def __init__(self, port, timeout=3):
self.port = port
self.baudrate = 2400
self.timeout = timeout
self.serial_port = None
def __enter__(self):
self.open()
return self
def __exit__(self, _, value, traceback):
self.close()
def open(self):
import serial
logdbg("open serial port %s" % self.port)
self.serial_port = serial.Serial(self.port, self.baudrate,
timeout=self.timeout)
def close(self):
if self.serial_port is not None:
logdbg("close serial port %s" % self.port)
self.serial_port.close()
self.serial_port = None
# FIXME: use either CR or LF as line terminator. apparently some ws1
# hardware occasionally ends a line with only CR instead of the standard
# CR-LF, resulting in a line that is too long.
def get_readings(self):
buf = self.serial_port.readline()
if DEBUG_READ >= 2:
logdbg("bytes: '%s'" % ' '.join(["%0.2X" % ord(c) for c in buf]))
buf = buf.strip()
return buf
def get_readings_with_retry(self, max_tries=5, retry_wait=10):
import serial
for ntries in range(0, max_tries):
try:
buf = self.get_readings()
StationData.validate_string(buf)
return buf
except (serial.serialutil.SerialException, weewx.WeeWxIOError), e:
loginf("Failed attempt %d of %d to get readings: %s" %
(ntries + 1, max_tries, e))
time.sleep(retry_wait)
else:
msg = "Max retries (%d) exceeded for readings" % max_tries
logerr(msg)
raise weewx.RetriesExceeded(msg)
# =========================================================================== #
# Station TCP class - Gets data through a TCP/IP connection #
# For those users with a serial->TCP adapter #
# =========================================================================== #
class StationInet(object):
def __init__(self, addr, protocol='tcp', timeout=3):
import socket
ip_addr = None
ip_port = None
self.protocol = protocol
if addr.find(':') != -1:
self.conn_info = addr.split(':')
try:
self.conn_info[1] = int(self.conn_info[1], 10)
except TypeError, e:
self.conn_info[1] = DEFAULT_TCP_PORT
self.conn_info = tuple(self.conn_info)
else:
ip_addr = addr
ip_port = DEFAULT_TCP_PORT
self.conn_info = (ip_addr, ip_port)
try:
if self.protocol == 'tcp':
self.net_socket = socket.socket(
socket.AF_INET, socket.SOCK_STREAM)
elif self.protocol == 'udp':
self.net_socket = socket.socket(
socket.AF_INET, socket.SOCK_DGRAM)
except (socket.error, socket.herror), ex:
logerr("Cannot create socket for some reason: %s" % ex)
raise weewx.WeeWxIOError(ex)
self.net_socket.settimeout(timeout)
self.rec_start = False
def open(self):
import socket
logdbg("Connecting to %s:%d." % (self.conn_info[0], self.conn_info[1]))
try:
self.net_socket.connect(self.conn_info)
except (socket.error, socket.timeout, socket.herror), ex:
logerr("Cannot connect to %s:%d for some reason: %s" % (
self.conn_info[0], self.conn_info[1], ex))
raise weewx.WeeWxIOError(ex)
def close(self):
import socket
logdbg("Closing connection to %s:%d." %
(self.conn_info[0], self.conn_info[1]))
try:
self.net_socket.close()
except (socket.error, socket.herror, socket.timeout), ex:
logerr("Cannot close connection to %s:%d for some reason: %s" % (
self.conn_info[0], self.conn_info[1], ex))
raise weewx.WeeWxIOError(ex)
def get_readings(self):
import socket
if self.rec_start is not True:
# Find the record start
if DEBUG_READ >= 1:
logdbg("Attempting to find record start..")
buf = ''
while True:
try:
buf += self.net_socket.recv(8, socket.MSG_WAITALL)
except (socket.error, socket.timeout), ex:
raise weewx.WeeWxIOError(ex)
if DEBUG_READ >= 1:
logdbg("(searching...) buf: %s" % buf)
if '!!' in buf:
self.rec_start = True
if DEBUG_READ >= 1:
logdbg("Record start found!")
# Cut to the record start
buf = buf[buf.find('!!'):]
if DEBUG_READ >= 1:
logdbg("(found!) buf: %s" % buf)
break
# Add the rest of the record
try:
buf += self.net_socket.recv(
PACKET_SIZE - len(buf), socket.MSG_WAITALL)
except (socket.error, socket.timeout), ex:
raise weewx.WeeWxIOError(ex)
else:
# Keep receiving data until we find an exclamation point or two
try:
buf = self.net_socket.recv(2, socket.MSG_WAITALL)
except (socket.error, socket.timeout), ex:
raise weewx.WeeWxIOError(ex)
while True:
if buf == '\r\n':
# CRLF is expected
if DEBUG_READ >= 2:
logdbg("buf is CRLF")
buf = ''
break
elif '!' in buf:
excmks = buf.count('!')
# Assuming exclamation points are at the end of the buffer
buf = buf[len(buf) - excmks:]
if DEBUG_READ >= 2:
logdbg("buf has %d exclamation points." % (excmks))
break
else:
try:
buf = self.net_socket.recv(2, socket.MSG_WAITALL)
except (socket.error, socket.timeout), ex:
raise weewx.WeeWxIOError(ex)
if DEBUG_READ >= 2:
logdbg("buf: %s" % ' '.join(
['%02X' % ord(bc) for bc in buf]))
try:
buf += self.net_socket.recv(
PACKET_SIZE - len(buf), socket.MSG_WAITALL)
except (socket.error, socket.timeout), ex:
raise weewx.WeeWxIOError(ex)
if DEBUG_READ >= 2:
logdbg("buf: %s" % buf)
# This code assumes CRLF will be transmitted at the end of each record,
# which may not always be the case. See Matthew Wall's comment on
# GitHub here:
# https://github.com/weewx/weewx/pull/86#issuecomment-166716509
# try:
# self.net_socket.recv(2, socket.MSG_WAITALL) # CRLF
# except (socket.error, socket.timeout), ex:
# raise weewx.WeeWxIOError(ex)
buf.strip()
return buf
def get_readings_with_retry(self, max_tries=5, retry_wait=10):
for ntries in range(0, max_tries):
buf = ''
try:
buf = self.get_readings()
StationData.validate_string(buf)
return buf
except (weewx.WeeWxIOError), e:
loginf("Failed to get data for some reason: %s" % e)
self.rec_start = False
# NOTE: WeeWx IO Errors may not always occur because of
# invalid data. These kinds of errors are also caused by socket
# errors and timeouts.
if DEBUG_READ >= 1:
logdbg("buf: %s (%d bytes), rec_start: %r" %
(buf, len(buf), self.rec_start))
time.sleep(retry_wait)
else:
msg = "Max retries (%d) exceeded for readings" % max_tries
logerr(msg)
raise weewx.RetriesExceeded(msg)
class WS1ConfEditor(weewx.drivers.AbstractConfEditor):
@property
def default_stanza(self):
return """
[WS1]
# This section is for the ADS WS1 series of weather stations.
# Driver mode - tcp, udp, or serial
mode = serial
# If serial, specify the serial port device. (ex. /dev/ttyS0, /dev/ttyUSB0,
# or /dev/cuaU0)
# If TCP, specify the IP address and port number. (ex. 192.168.36.25:3000)
port = /dev/ttyUSB0
# The amount of time, in seconds, before the connection fails if there is
# no response
timeout = 3
# The driver to use:
driver = weewx.drivers.ws1
"""
def prompt_for_settings(self):
print "How is the station connected? tcp, udp, or serial."
con_mode = self._prompt('mode', 'serial')
con_mode = con_mode.lower()
if con_mode == 'serial':
print "Specify the serial port on which the station is connected, "
"for example: /dev/ttyUSB0 or /dev/ttyS0."
port = self._prompt('port', '/dev/ttyUSB0')
elif con_mode == 'tcp' or con_mode == 'udp':
print "Specify the IP address and port of the station. For "
"example: 192.168.36.40:3000."
port = self._prompt('port', '192.168.36.40:3000')
print "Specify how long to wait for a response, in seconds."
timeout = self._prompt('timeout', 3)
return {'mode': con_mode, 'port': port, 'timeout': timeout}
# define a main entry point for basic testing of the station without weewx
# engine and service overhead. invoke this as follows from the weewx root dir:
#
# PYTHONPATH=bin python bin/weewx/drivers/ws1.py
if __name__ == '__main__':
import optparse
usage = """%prog [options] [--help]"""
syslog.openlog('ws1', syslog.LOG_PID | syslog.LOG_CONS)
syslog.setlogmask(syslog.LOG_UPTO(syslog.LOG_DEBUG))
parser = optparse.OptionParser(usage=usage)
parser.add_option('--version', dest='version', action='store_true',
help='display driver version')
parser.add_option('--port', dest='port', metavar='PORT',
help='serial port to which the station is connected',
default=DEFAULT_PORT)
(options, args) = parser.parse_args()
if options.version:
print "ADS WS1 driver version %s" % DRIVER_VERSION
exit(0)
with Station(options.port) as s:
while True:
print time.time(), s.get_readings()
| 36.406439
| 88
| 0.549851
|
c709d8826838878bf90f056bbf3aeebfa3310839
| 2,094
|
py
|
Python
|
apps/04_journal/you_try/program.py
|
robbyrenz/python-jumpstart-course-demos
|
d14f30e23cbb0349ef1f22559475e4a8157613f0
|
[
"MIT"
] | null | null | null |
apps/04_journal/you_try/program.py
|
robbyrenz/python-jumpstart-course-demos
|
d14f30e23cbb0349ef1f22559475e4a8157613f0
|
[
"MIT"
] | null | null | null |
apps/04_journal/you_try/program.py
|
robbyrenz/python-jumpstart-course-demos
|
d14f30e23cbb0349ef1f22559475e4a8157613f0
|
[
"MIT"
] | null | null | null |
def main(): # defining a main method; high level code up here
print_header()
run_event_loop()
# main() can't be defined here as Python would not know the definition of the functions in the main method
def print_header():
print('-------------------------------')
print(' JOURNAL APP')
print('-------------------------------')
def run_event_loop():
print('What do you want to do with your journal?')
cmd = None # just initialize cmd to nothing just to get the while loop to work!
journal_data = [] # initializes an empty list
# you can also make a list with the list() function
while cmd != 'x':
cmd = input('[L]ist entries, [A]dd an entry, E[x]it: ')
cmd = cmd.lower().strip()
if cmd == 'l':
list_entries(journal_data)
elif cmd == 'a':
add_entries(journal_data)
elif cmd == '': # if the user doesn't enter anything
# print('Please don\'t enter a newline character!') <enter> probably doesn't result in \n, I think
print('Please enter something at least!')
elif cmd != 'x':
print('Sorry, we don\'t understand \'{}\'.'.format(cmd))
print('Done, goodbye.')
def list_entries(data):
print('Your journal entries: ')
entries = reversed(data) # the reversed() function...check if its permanent
for idx, entry in enumerate(entries): # enumerate function makes a tuple out of the items with its indexes
print('* [{}] {}'.format(idx + 1, entry))
# the below block of code is my very own twist to this app
# def list_entries(data):
# # print(data)
# if len(data) == 0: # if the length of the list is 0...
# print('You have no saved messages!')
# else:
# i = 1
# for message in data:
# print(f'{i}. {message}')
# # OR: print(str(i) + '. ' + message)
# i = i + 1
def add_entries(data):
text = input('Type your entry, <enter> to exit: ')
data.append(text)
main() # invoke the main method so that at least something happens!
| 32.215385
| 111
| 0.575454
|
3bbf109435c6dc48312104c0a78ab9500a46a4ce
| 19,405
|
py
|
Python
|
course/views.py
|
ArnedyNavi/studymate
|
55e6a2c6717dd478a311ea8bf839a26ca3ef2b40
|
[
"MIT"
] | 4
|
2021-12-31T17:25:00.000Z
|
2022-02-08T17:05:46.000Z
|
course/views.py
|
ArnedyNavi/studymate
|
55e6a2c6717dd478a311ea8bf839a26ca3ef2b40
|
[
"MIT"
] | null | null | null |
course/views.py
|
ArnedyNavi/studymate
|
55e6a2c6717dd478a311ea8bf839a26ca3ef2b40
|
[
"MIT"
] | null | null | null |
from django.http.response import JsonResponse
from django.http import Http404
from django.core.exceptions import PermissionDenied, BadRequest
from django.shortcuts import render
from django.views.decorators.csrf import csrf_exempt
from django.contrib.auth.decorators import login_required
from django.http import HttpResponseRedirect, HttpResponse, HttpResponseNotFound
from django.forms.models import model_to_dict
from django.core import serializers
from django.db.models import Q, Value
from django.template import loader
import json
from django.urls import reverse
from .models import *
import markdown as md
from PIL import Image
import os
import uuid
from studymate.settings import MEDIA_ROOT as media
import datetime
def preview(request, id):
course = Course.objects.filter(id=id).first()
if course == None:
raise Http404("Course Not Found")
else:
instructors = course.instructors.all()
categories = course.categories.all()
contents = []
content_groups = []
content_groupsDB = CourseContentGroup.objects.filter(course=course).order_by("order")
for content_group in content_groupsDB:
content = CourseContent.objects.filter(content_group = content_group).order_by("order")
content_group = {"title": content_group.title, "contents": content}
content_groups.append(content_group)
usercourseDB = UserCourse.objects.filter(user=request.user, course__id=id).first()
if usercourseDB == None:
enrolled = False
else:
enrolled = True
context = {
"course": course,
"instructors": instructors,
"categories": categories,
"content_groups": content_groups,
"enrolled": enrolled
}
return render(request, "course/preview.html", context)
def enroll(request, course_id):
if request.method == "POST":
userCourseDB = UserCourse.objects.filter(user=request.user, course__id=course_id).first()
if userCourseDB == None:
course = Course.objects.filter(id=course_id).first()
usercourseDB = UserCourse(user=request.user, course=course)
usercourseDB.save()
firstContentGroup = CourseContentGroup.objects.filter(course=course).order_by("order").first()
firstContent = CourseContent.objects.filter(content_group=firstContentGroup).order_by("order").first()
userProgress = CourseUserProgress(info=usercourseDB, last_content=firstContent.id)
contents = CourseContent.objects.filter(content_group__course=course)
for content in contents:
userContentProgress = ContentUserProgress(content=content, user=request.user)
userContentProgress.save()
contentgroups = CourseContentGroup.objects.filter(course=course)
for group in contentgroups:
userContentGroupProgress = ContentGroupUserProgress(content_group=group, user=request.user)
userContentGroupProgress.save()
output = {
"status": "success"
}
return JsonResponse(output)
else:
raise PermissionDenied()
def unenroll(request):
if request.method == "POST":
data = request.POST
course_id = data.get("id", -1)
userCourseDB = UserCourse.objects.filter(user=request.user, course__id=course_id).first()
if userCourseDB != None:
course = Course.objects.filter(id=course_id).first()
userCourseProgress = CourseUserProgress.objects.filter(info=userCourseDB)
userCourseProgress.delete()
userCourseDB.delete()
userContentsProgress = ContentUserProgress.objects.filter(content__content_group__course=course, user=request.user)
for userContent in userContentsProgress:
userContent.delete()
userContentGroupProgress = ContentGroupUserProgress.objects.filter(content_group__course=course, user=request.user)
for group in userContentGroupProgress:
group.delete()
output = {
"status": "success"
}
return JsonResponse(output)
def resetLastContent(userprogress, course_id):
firstContentGroup = CourseContentGroup.objects.filter(course__id=course_id).order_by("order").first()
firstContent = CourseContent.objects.filter(content_group=firstContentGroup).order_by("order").first()
userprogress.last_content = firstContent.id
userprogress.save()
return firstContent
def learn(request, course_id):
usercourseDB = UserCourse.objects.filter(course__id=course_id, user=request.user).first()
if usercourseDB == None:
return HttpResponseRedirect(reverse("course_preview", args=[course_id]))
else:
userprogress = CourseUserProgress.objects.filter(info=usercourseDB).first()
if userprogress == None:
userprogress = CourseUserProgress(info=usercourseDB)
userprogress.save()
course = Course.objects.filter(id=course_id).first()
last_group = CourseContent.objects.filter(id=userprogress.last_content).first()
if last_group == None:
last_group = resetLastContent(userprogress, course_id)
last_group = last_group.content_group.id
context = {
"user_data": usercourseDB,
"progress": userprogress,
"course": course,
"last_content_group": last_group
}
return render(request, "course/learn.html", context)
def search(request):
return render(request, "course/search.html")
def search_info(request):
query = request.GET["query"]
courses = Course.objects.filter(Q(name__icontains = query) | Q(description__icontains = query)).order_by('-overall_ratings').distinct()
html_response = loader.render_to_string("course/search_card_temp.html", {"courses": courses})
html_response = html_response.strip()
output = {
"status": "success",
"html": html_response
}
return JsonResponse(output)
def my_course(request):
course_inprogress = UserCourse.objects.filter(user=request.user, completed=False).order_by("-start_date")
course_completed = UserCourse.objects.filter(user=request.user, completed=True).order_by("-complete_date")
course_byuser = Course.objects.filter(maker=request.user)
context = {
"course_inprogress": course_inprogress,
"course_completed": course_completed,
"course_byuser": course_byuser
}
return render(request, "course/mycourse.html", context)
@csrf_exempt
def make_course(request):
if request.method == "POST":
data = request.POST
files = request.FILES
name = data["name"]
desc = data["desc"]
categories = json.loads(data["categories"])
contents = json.loads(data["content"])
instructors = json.loads(data["instructors"])
thumbnail = ""
profile_instructors = {}
for file in files:
if file == "thumbnail":
thumbnail = files[file]
else:
owner = int(file.split("-")[-1])
profile_instructors[owner] = files[file]
i = 0
instructorsDB = []
for instructor in instructors:
image = profile_instructors.get(i, 0)
if image == 0:
instructorModel = CourseInstructor(name=instructor)
else:
instructorModel = CourseInstructor(name=instructor, profile_image=image)
instructorModel.save()
instructorsDB.append(instructorModel)
i += 1
categoriesDB =[]
for category in categories:
categoryDB = CourseCategory.objects.filter(name=category).first()
if categoryDB == None:
categoryDB = CourseCategory(name=category)
categoryDB.save()
categoriesDB.append(categoryDB)
if thumbnail != "":
course = Course(name=name, description=desc, banner_image=thumbnail, maker=request.user)
else:
course = Course(name=name, description=desc, banner_image=thumbnail, maker=request.user)
course.save()
for category in categoriesDB:
course.categories.add(category)
for instructor in instructorsDB:
course.instructors.add(instructor)
course.save()
for i in range(len(contents)):
content_group = CourseContentGroup(course=course, title=contents[i]["subTopicTitle"], order=i+1)
content_group.save()
for j in range(len(contents[i]["contents"])):
content_now = contents[i]["contents"][j]
title = content_now["title"]
type = content_now["type"]
if type == "text":
isVideo = False
else:
isVideo = True
video_link = content_now["video_link"]
text_content = content_now["text_content"]
content = CourseContent(content_group=content_group, title=title, is_video=isVideo, video_link=video_link, content=text_content, order=j+1)
content.save()
output = {
"status": "success",
"url": reverse("course_preview", args=[course.id])
}
return JsonResponse(output)
return render(request, "course/add.html")
@csrf_exempt
def upload_image(request):
if request.method == "POST":
file = request.FILES
data = request.POST
if len(file) != 0:
img = Image.open(file["image"])
filename_before = file["image"].name
filename = "/course/content/uploads/" + str(uuid.uuid4()) + ".jpg"
img.save(media + filename, "JPEG")
output = {
"status": "success",
"url": "/media" + filename,
"filename": filename_before
}
else:
output = {
"status": "failed"
}
return JsonResponse(output)
@csrf_exempt
def markdown(request):
if request.method == "POST":
data = request.POST
text = data["text"]
md_ext = md.Markdown(extensions=["markdown_markup_emoji.markup_emoji", 'mdx_math', 'tables', 'footnotes', 'def_list', 'abbr', 'attr_list', 'fenced_code'])
html = md_ext.convert(text)
output = {
"status": "success",
"html": html
}
return JsonResponse(output)
def markdown_func(text):
md_ext = md.Markdown(extensions=["markdown_markup_emoji.markup_emoji", 'mdx_math', 'tables', 'footnotes', 'def_list', 'abbr', 'attr_list', 'fenced_code'])
html = md_ext.convert(text)
return html
@login_required
def finishContent(request):
if request.method == "POST":
content_id = request.POST.get("id", -1)
if content_id != -1:
userContentProgress = ContentUserProgress.objects.filter(content__id=content_id, user=request.user).first()
if userContentProgress == None:
output = {
"status": "failed"
}
else:
if userContentProgress.completed == False:
userContentProgress.completed = True
userContentProgress.save()
courseContentDB = CourseContent.objects.filter(id=content_id).first()
checkFinishGroup(request, courseContentDB.content_group)
output = {
"status": "success"
}
else:
output = {
"status": "failed"
}
return JsonResponse(output)
def checkFinishGroup(request, content_group):
contentsDB = ContentUserProgress.objects.filter(content__content_group=content_group, user=request.user)
finish = True
for content in contentsDB:
if content.completed == False:
finish = False
if finish == True:
userContentGroupProgress = ContentGroupUserProgress.objects.filter(content_group=content_group, user=request.user).first()
userContentGroupProgress.completed = True
userContentGroupProgress.save()
@login_required
def completeContent(request):
status = "failed"
if request.method == "POST":
data = request.POST
content_id = data["id"]
userContentProgress = ContentUserProgress.objects.filter(content__id=content_id, user=request.user).first()
if userContentProgress != None:
userContentProgress.completed = True
userContentProgress.save()
checkFinishGroup(request, userContentProgress.content.content_group)
status = "success"
output = {
"status": status
}
return JsonResponse(output)
@login_required
def setLastViewed(request):
status = "failed"
if request.method == "POST":
data = request.POST
content_id = data["id"]
content = CourseContent.objects.filter(id=content_id).first()
if content != None:
course = content.content_group.course
userprogress = CourseUserProgress.objects.filter(info__course=course).first()
if userprogress != None:
userprogress.last_content = content_id
userprogress.save()
status = "success"
output = {
'status': status
}
return JsonResponse(output)
@login_required
def validateCompletion(request):
status = "failed"
completed = False
if request.method == "POST":
data = request.POST
course_id = data.get("id", -1)
if course_id != -1:
userGroupProgress = ContentGroupUserProgress.objects.filter(content_group__course__id=course_id, user=request.user)
completed = True
for progress in userGroupProgress:
if progress.completed == False:
completed = False
if completed:
userCourseInfo = UserCourse.objects.filter(user=request.user, course__id=course_id).first()
if userCourseInfo != None:
if userCourseInfo.completed == False:
userCourseInfo.completed = True
userCourseInfo.complete_date = datetime.datetime.now()
userCourseInfo.save()
status = "success"
output = {
"status": status,
"completed": completed
}
return JsonResponse(output)
@login_required
def getCourseInfo(request):
data = request.GET
by = data["by"]
course = data.get("course", -1)
group = data.get("group", -1)
content = data.get("content", -1)
data = {}
status = "failed"
if by != -1:
if by == "course":
if course != -1:
courseDB = Course.objects.filter(id=course)
if len(courseDB) != 0:
userCourse = UserCourse.objects.filter(user=request.user, course=courseDB.first()).first()
if userCourse != None:
status = "success"
courseDB = Course.objects.filter(id=course)
course_info = list(courseDB.values())[0]
groupDB = CourseContentGroup.objects.filter(course=courseDB.first()).order_by('order')
group_info = list(groupDB.values())
content_info = None
data["course"] = course_info
data["groups"] = group_info
elif by == "group":
if group != -1:
groupDB = CourseContentGroup.objects.filter(id=group).first()
if groupDB != None:
courseDB = groupDB.course
userCourse = UserCourse.objects.filter(user=request.user, course=courseDB).first()
if userCourse != None:
status = "success"
contentsDB = CourseContent.objects.filter(content_group=groupDB).order_by('order')
info = json.loads(serializers.serialize('json', [courseDB, groupDB]))
data["course"] = info[0]["fields"]
data["groups"] = info[1]["fields"]
data["contents"] = list(contentsDB.values('id', 'title', 'is_video'))
elif by == "content":
if content != -1:
contentDB = CourseContent.objects.filter(id=content).first()
if contentDB != None:
groupDB = contentDB.content_group
courseDB = groupDB.course
userCourse = UserCourse.objects.filter(user=request.user, course=courseDB).first()
if userCourse != None:
status = "success"
info = json.loads(serializers.serialize('json', [courseDB, groupDB, contentDB]))
data["course"] = info[0]["fields"]
data["groups"] = info[1]["fields"]
data["contents"] = info[2]["fields"]
data["contents"]["content"] = markdown_func(data["contents"]["content"])
output = {
"status": status,
"data": data
}
return JsonResponse(output)
@login_required
def getUserCourseInfo(request):
data = request.GET
by = data["by"]
course = data.get("course", -1)
group = data.get("group", -1)
data = {}
status = "failed"
if by != -1:
if by == "course":
if course != -1:
courseDB = Course.objects.filter(id=course)
if len(courseDB) != 0:
userCourse = UserCourse.objects.filter(user=request.user, course=courseDB.first()).first()
if userCourse != None:
status = "success"
contentGroupProgress = ContentGroupUserProgress.objects.filter(content_group__course__id=course, user=request.user).order_by("content_group__order")
if len(contentGroupProgress) != 0:
groupProgressInfo = list(contentGroupProgress.values())
data["group_progress"] = groupProgressInfo
elif by == "group":
if group != -1:
groupDB = CourseContentGroup.objects.filter(id=group)
if len(groupDB) != 0:
userCourse = UserCourse.objects.filter(user=request.user, course=groupDB.first().course).first()
if userCourse != None:
status = "success"
contentProgress = ContentUserProgress.objects.filter(content__content_group__id = group, user=request.user).order_by("content__order")
if len(contentProgress) != 0:
contentProgressInfo = list(contentProgress.values())
data["content_progress"] = contentProgressInfo
output = {
"status": status,
"data": data
}
return JsonResponse(output)
| 39.441057
| 172
| 0.59629
|
26f6aeab90dfd6245953ae471f11d7e36452dc3c
| 562
|
py
|
Python
|
trade_remedies_api/organisations/migrations/0002_organisation_duplicate_of.py
|
uktrade/trade-remedies-api
|
fbe2d142ef099c7244788a0f72dd1003eaa7edce
|
[
"MIT"
] | 1
|
2020-08-13T10:37:15.000Z
|
2020-08-13T10:37:15.000Z
|
trade_remedies_api/organisations/migrations/0002_organisation_duplicate_of.py
|
uktrade/trade-remedies-api
|
fbe2d142ef099c7244788a0f72dd1003eaa7edce
|
[
"MIT"
] | 4
|
2020-09-10T13:41:52.000Z
|
2020-12-16T09:00:21.000Z
|
trade_remedies_api/organisations/migrations/0002_organisation_duplicate_of.py
|
uktrade/trade-remedies-api
|
fbe2d142ef099c7244788a0f72dd1003eaa7edce
|
[
"MIT"
] | null | null | null |
# Generated by Django 2.0.1 on 2018-10-24 13:24
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
("organisations", "0001_initial"),
]
operations = [
migrations.AddField(
model_name="organisation",
name="duplicate_of",
field=models.ForeignKey(
null=True,
on_delete=django.db.models.deletion.PROTECT,
to="organisations.Organisation",
),
),
]
| 23.416667
| 60
| 0.580071
|
2ed403e95cb9222d6a37a2fbc8647e211c774a4b
| 33,020
|
py
|
Python
|
torchvision/transforms/functional_tensor.py
|
mhhabdelwahab/vision
|
21790df9a4f77bd9ec4db44de04594cb539457a7
|
[
"BSD-3-Clause"
] | null | null | null |
torchvision/transforms/functional_tensor.py
|
mhhabdelwahab/vision
|
21790df9a4f77bd9ec4db44de04594cb539457a7
|
[
"BSD-3-Clause"
] | null | null | null |
torchvision/transforms/functional_tensor.py
|
mhhabdelwahab/vision
|
21790df9a4f77bd9ec4db44de04594cb539457a7
|
[
"BSD-3-Clause"
] | null | null | null |
import warnings
from typing import Optional, Tuple, List
import torch
from torch import Tensor
from torch.nn.functional import grid_sample, conv2d, interpolate, pad as torch_pad
def _is_tensor_a_torch_image(x: Tensor) -> bool:
return x.ndim >= 2
def _assert_image_tensor(img: Tensor) -> None:
if not _is_tensor_a_torch_image(img):
raise TypeError("Tensor is not a torch image.")
def _assert_threshold(img: Tensor, threshold: float) -> None:
bound = 1 if img.is_floating_point() else 255
if threshold > bound:
raise TypeError("Threshold should be less than bound of img.")
def get_image_size(img: Tensor) -> List[int]:
# Returns (w, h) of tensor image
_assert_image_tensor(img)
return [img.shape[-1], img.shape[-2]]
def get_image_num_channels(img: Tensor) -> int:
if img.ndim == 2:
return 1
elif img.ndim > 2:
return img.shape[-3]
raise TypeError(f"Input ndim should be 2 or more. Got {img.ndim}")
def _max_value(dtype: torch.dtype) -> float:
# TODO: replace this method with torch.iinfo when it gets torchscript support.
# https://github.com/pytorch/pytorch/issues/41492
a = torch.tensor(2, dtype=dtype)
signed = 1 if torch.tensor(0, dtype=dtype).is_signed() else 0
bits = 1
max_value = torch.tensor(-signed, dtype=torch.long)
while True:
next_value = a.pow(bits - signed).sub(1)
if next_value > max_value:
max_value = next_value
bits *= 2
else:
break
return max_value.item()
def _assert_channels(img: Tensor, permitted: List[int]) -> None:
c = get_image_num_channels(img)
if c not in permitted:
raise TypeError(f"Input image tensor permitted channel values are {permitted}, but found {c}")
def convert_image_dtype(image: torch.Tensor, dtype: torch.dtype = torch.float) -> torch.Tensor:
if image.dtype == dtype:
return image
if image.is_floating_point():
# TODO: replace with dtype.is_floating_point when torchscript supports it
if torch.tensor(0, dtype=dtype).is_floating_point():
return image.to(dtype)
# float to int
if (image.dtype == torch.float32 and dtype in (torch.int32, torch.int64)) or (
image.dtype == torch.float64 and dtype == torch.int64
):
msg = f"The cast from {image.dtype} to {dtype} cannot be performed safely."
raise RuntimeError(msg)
# https://github.com/pytorch/vision/pull/2078#issuecomment-612045321
# For data in the range 0-1, (float * 255).to(uint) is only 255
# when float is exactly 1.0.
# `max + 1 - epsilon` provides more evenly distributed mapping of
# ranges of floats to ints.
eps = 1e-3
max_val = _max_value(dtype)
result = image.mul(max_val + 1.0 - eps)
return result.to(dtype)
else:
input_max = _max_value(image.dtype)
# int to float
# TODO: replace with dtype.is_floating_point when torchscript supports it
if torch.tensor(0, dtype=dtype).is_floating_point():
image = image.to(dtype)
return image / input_max
output_max = _max_value(dtype)
# int to int
if input_max > output_max:
# factor should be forced to int for torch jit script
# otherwise factor is a float and image // factor can produce different results
factor = int((input_max + 1) // (output_max + 1))
image = torch.div(image, factor, rounding_mode="floor")
return image.to(dtype)
else:
# factor should be forced to int for torch jit script
# otherwise factor is a float and image * factor can produce different results
factor = int((output_max + 1) // (input_max + 1))
image = image.to(dtype)
return image * factor
def vflip(img: Tensor) -> Tensor:
_assert_image_tensor(img)
return img.flip(-2)
def hflip(img: Tensor) -> Tensor:
_assert_image_tensor(img)
return img.flip(-1)
def crop(img: Tensor, top: int, left: int, height: int, width: int) -> Tensor:
_assert_image_tensor(img)
w, h = get_image_size(img)
right = left + width
bottom = top + height
if left < 0 or top < 0 or right > w or bottom > h:
padding_ltrb = [max(-left, 0), max(-top, 0), max(right - w, 0), max(bottom - h, 0)]
return pad(img[..., max(top, 0) : bottom, max(left, 0) : right], padding_ltrb, fill=0)
return img[..., top:bottom, left:right]
def rgb_to_grayscale(img: Tensor, num_output_channels: int = 1) -> Tensor:
if img.ndim < 3:
raise TypeError(f"Input image tensor should have at least 3 dimensions, but found {img.ndim}")
_assert_channels(img, [3])
if num_output_channels not in (1, 3):
raise ValueError("num_output_channels should be either 1 or 3")
r, g, b = img.unbind(dim=-3)
# This implementation closely follows the TF one:
# https://github.com/tensorflow/tensorflow/blob/v2.3.0/tensorflow/python/ops/image_ops_impl.py#L2105-L2138
l_img = (0.2989 * r + 0.587 * g + 0.114 * b).to(img.dtype)
l_img = l_img.unsqueeze(dim=-3)
if num_output_channels == 3:
return l_img.expand(img.shape)
return l_img
def adjust_brightness(img: Tensor, brightness_factor: float) -> Tensor:
if brightness_factor < 0:
raise ValueError(f"brightness_factor ({brightness_factor}) is not non-negative.")
_assert_image_tensor(img)
_assert_channels(img, [1, 3])
return _blend(img, torch.zeros_like(img), brightness_factor)
def adjust_contrast(img: Tensor, contrast_factor: float) -> Tensor:
if contrast_factor < 0:
raise ValueError(f"contrast_factor ({contrast_factor}) is not non-negative.")
_assert_image_tensor(img)
_assert_channels(img, [3, 1])
c = get_image_num_channels(img)
dtype = img.dtype if torch.is_floating_point(img) else torch.float32
if c == 3:
mean = torch.mean(rgb_to_grayscale(img).to(dtype), dim=(-3, -2, -1), keepdim=True)
else:
mean = torch.mean(img.to(dtype), dim=(-3, -2, -1), keepdim=True)
return _blend(img, mean, contrast_factor)
def adjust_hue(img: Tensor, hue_factor: float) -> Tensor:
if not (-0.5 <= hue_factor <= 0.5):
raise ValueError(f"hue_factor ({hue_factor}) is not in [-0.5, 0.5].")
if not (isinstance(img, torch.Tensor)):
raise TypeError("Input img should be Tensor image")
_assert_image_tensor(img)
_assert_channels(img, [1, 3])
if get_image_num_channels(img) == 1: # Match PIL behaviour
return img
orig_dtype = img.dtype
if img.dtype == torch.uint8:
img = img.to(dtype=torch.float32) / 255.0
img = _rgb2hsv(img)
h, s, v = img.unbind(dim=-3)
h = (h + hue_factor) % 1.0
img = torch.stack((h, s, v), dim=-3)
img_hue_adj = _hsv2rgb(img)
if orig_dtype == torch.uint8:
img_hue_adj = (img_hue_adj * 255.0).to(dtype=orig_dtype)
return img_hue_adj
def adjust_saturation(img: Tensor, saturation_factor: float) -> Tensor:
if saturation_factor < 0:
raise ValueError(f"saturation_factor ({saturation_factor}) is not non-negative.")
_assert_image_tensor(img)
_assert_channels(img, [1, 3])
if get_image_num_channels(img) == 1: # Match PIL behaviour
return img
return _blend(img, rgb_to_grayscale(img), saturation_factor)
def adjust_gamma(img: Tensor, gamma: float, gain: float = 1) -> Tensor:
if not isinstance(img, torch.Tensor):
raise TypeError("Input img should be a Tensor.")
_assert_channels(img, [1, 3])
if gamma < 0:
raise ValueError("Gamma should be a non-negative real number")
result = img
dtype = img.dtype
if not torch.is_floating_point(img):
result = convert_image_dtype(result, torch.float32)
result = (gain * result ** gamma).clamp(0, 1)
result = convert_image_dtype(result, dtype)
return result
def _blend(img1: Tensor, img2: Tensor, ratio: float) -> Tensor:
ratio = float(ratio)
bound = 1.0 if img1.is_floating_point() else 255.0
return (ratio * img1 + (1.0 - ratio) * img2).clamp(0, bound).to(img1.dtype)
def _rgb2hsv(img: Tensor) -> Tensor:
r, g, b = img.unbind(dim=-3)
# Implementation is based on https://github.com/python-pillow/Pillow/blob/4174d4267616897df3746d315d5a2d0f82c656ee/
# src/libImaging/Convert.c#L330
maxc = torch.max(img, dim=-3).values
minc = torch.min(img, dim=-3).values
# The algorithm erases S and H channel where `maxc = minc`. This avoids NaN
# from happening in the results, because
# + S channel has division by `maxc`, which is zero only if `maxc = minc`
# + H channel has division by `(maxc - minc)`.
#
# Instead of overwriting NaN afterwards, we just prevent it from occuring so
# we don't need to deal with it in case we save the NaN in a buffer in
# backprop, if it is ever supported, but it doesn't hurt to do so.
eqc = maxc == minc
cr = maxc - minc
# Since `eqc => cr = 0`, replacing denominator with 1 when `eqc` is fine.
ones = torch.ones_like(maxc)
s = cr / torch.where(eqc, ones, maxc)
# Note that `eqc => maxc = minc = r = g = b`. So the following calculation
# of `h` would reduce to `bc - gc + 2 + rc - bc + 4 + rc - bc = 6` so it
# would not matter what values `rc`, `gc`, and `bc` have here, and thus
# replacing denominator with 1 when `eqc` is fine.
cr_divisor = torch.where(eqc, ones, cr)
rc = (maxc - r) / cr_divisor
gc = (maxc - g) / cr_divisor
bc = (maxc - b) / cr_divisor
hr = (maxc == r) * (bc - gc)
hg = ((maxc == g) & (maxc != r)) * (2.0 + rc - bc)
hb = ((maxc != g) & (maxc != r)) * (4.0 + gc - rc)
h = hr + hg + hb
h = torch.fmod((h / 6.0 + 1.0), 1.0)
return torch.stack((h, s, maxc), dim=-3)
def _hsv2rgb(img: Tensor) -> Tensor:
h, s, v = img.unbind(dim=-3)
i = torch.floor(h * 6.0)
f = (h * 6.0) - i
i = i.to(dtype=torch.int32)
p = torch.clamp((v * (1.0 - s)), 0.0, 1.0)
q = torch.clamp((v * (1.0 - s * f)), 0.0, 1.0)
t = torch.clamp((v * (1.0 - s * (1.0 - f))), 0.0, 1.0)
i = i % 6
mask = i.unsqueeze(dim=-3) == torch.arange(6, device=i.device).view(-1, 1, 1)
a1 = torch.stack((v, q, p, p, t, v), dim=-3)
a2 = torch.stack((t, v, v, q, p, p), dim=-3)
a3 = torch.stack((p, p, t, v, v, q), dim=-3)
a4 = torch.stack((a1, a2, a3), dim=-4)
return torch.einsum("...ijk, ...xijk -> ...xjk", mask.to(dtype=img.dtype), a4)
def _pad_symmetric(img: Tensor, padding: List[int]) -> Tensor:
# padding is left, right, top, bottom
# crop if needed
if padding[0] < 0 or padding[1] < 0 or padding[2] < 0 or padding[3] < 0:
neg_min_padding = [-min(x, 0) for x in padding]
crop_left, crop_right, crop_top, crop_bottom = neg_min_padding
img = img[..., crop_top : img.shape[-2] - crop_bottom, crop_left : img.shape[-1] - crop_right]
padding = [max(x, 0) for x in padding]
in_sizes = img.size()
_x_indices = [i for i in range(in_sizes[-1])] # [0, 1, 2, 3, ...]
left_indices = [i for i in range(padding[0] - 1, -1, -1)] # e.g. [3, 2, 1, 0]
right_indices = [-(i + 1) for i in range(padding[1])] # e.g. [-1, -2, -3]
x_indices = torch.tensor(left_indices + _x_indices + right_indices, device=img.device)
_y_indices = [i for i in range(in_sizes[-2])]
top_indices = [i for i in range(padding[2] - 1, -1, -1)]
bottom_indices = [-(i + 1) for i in range(padding[3])]
y_indices = torch.tensor(top_indices + _y_indices + bottom_indices, device=img.device)
ndim = img.ndim
if ndim == 3:
return img[:, y_indices[:, None], x_indices[None, :]]
elif ndim == 4:
return img[:, :, y_indices[:, None], x_indices[None, :]]
else:
raise RuntimeError("Symmetric padding of N-D tensors are not supported yet")
def pad(img: Tensor, padding: List[int], fill: int = 0, padding_mode: str = "constant") -> Tensor:
_assert_image_tensor(img)
if not isinstance(padding, (int, tuple, list)):
raise TypeError("Got inappropriate padding arg")
if not isinstance(fill, (int, float)):
raise TypeError("Got inappropriate fill arg")
if not isinstance(padding_mode, str):
raise TypeError("Got inappropriate padding_mode arg")
if isinstance(padding, tuple):
padding = list(padding)
if isinstance(padding, list) and len(padding) not in [1, 2, 4]:
raise ValueError(f"Padding must be an int or a 1, 2, or 4 element tuple, not a {len(padding)} element tuple")
if padding_mode not in ["constant", "edge", "reflect", "symmetric"]:
raise ValueError("Padding mode should be either constant, edge, reflect or symmetric")
if isinstance(padding, int):
if torch.jit.is_scripting():
# This maybe unreachable
raise ValueError("padding can't be an int while torchscripting, set it as a list [value, ]")
pad_left = pad_right = pad_top = pad_bottom = padding
elif len(padding) == 1:
pad_left = pad_right = pad_top = pad_bottom = padding[0]
elif len(padding) == 2:
pad_left = pad_right = padding[0]
pad_top = pad_bottom = padding[1]
else:
pad_left = padding[0]
pad_top = padding[1]
pad_right = padding[2]
pad_bottom = padding[3]
p = [pad_left, pad_right, pad_top, pad_bottom]
if padding_mode == "edge":
# remap padding_mode str
padding_mode = "replicate"
elif padding_mode == "symmetric":
# route to another implementation
return _pad_symmetric(img, p)
need_squeeze = False
if img.ndim < 4:
img = img.unsqueeze(dim=0)
need_squeeze = True
out_dtype = img.dtype
need_cast = False
if (padding_mode != "constant") and img.dtype not in (torch.float32, torch.float64):
# Here we temporary cast input tensor to float
# until pytorch issue is resolved :
# https://github.com/pytorch/pytorch/issues/40763
need_cast = True
img = img.to(torch.float32)
img = torch_pad(img, p, mode=padding_mode, value=float(fill))
if need_squeeze:
img = img.squeeze(dim=0)
if need_cast:
img = img.to(out_dtype)
return img
def resize(
img: Tensor,
size: List[int],
interpolation: str = "bilinear",
max_size: Optional[int] = None,
antialias: Optional[bool] = None,
) -> Tensor:
_assert_image_tensor(img)
if not isinstance(size, (int, tuple, list)):
raise TypeError("Got inappropriate size arg")
if not isinstance(interpolation, str):
raise TypeError("Got inappropriate interpolation arg")
if interpolation not in ["nearest", "bilinear", "bicubic"]:
raise ValueError("This interpolation mode is unsupported with Tensor input")
if isinstance(size, tuple):
size = list(size)
if isinstance(size, list):
if len(size) not in [1, 2]:
raise ValueError(
f"Size must be an int or a 1 or 2 element tuple/list, not a {len(size)} element tuple/list"
)
if max_size is not None and len(size) != 1:
raise ValueError(
"max_size should only be passed if size specifies the length of the smaller edge, "
"i.e. size should be an int or a sequence of length 1 in torchscript mode."
)
if antialias is None:
antialias = False
if antialias and interpolation not in ["bilinear", "bicubic"]:
raise ValueError("Antialias option is supported for bilinear and bicubic interpolation modes only")
w, h = get_image_size(img)
if isinstance(size, int) or len(size) == 1: # specified size only for the smallest edge
short, long = (w, h) if w <= h else (h, w)
requested_new_short = size if isinstance(size, int) else size[0]
if short == requested_new_short:
return img
new_short, new_long = requested_new_short, int(requested_new_short * long / short)
if max_size is not None:
if max_size <= requested_new_short:
raise ValueError(
f"max_size = {max_size} must be strictly greater than the requested "
f"size for the smaller edge size = {size}"
)
if new_long > max_size:
new_short, new_long = int(max_size * new_short / new_long), max_size
new_w, new_h = (new_short, new_long) if w <= h else (new_long, new_short)
else: # specified both h and w
new_w, new_h = size[1], size[0]
img, need_cast, need_squeeze, out_dtype = _cast_squeeze_in(img, [torch.float32, torch.float64])
# Define align_corners to avoid warnings
align_corners = False if interpolation in ["bilinear", "bicubic"] else None
if antialias:
if interpolation == "bilinear":
img = torch.ops.torchvision._interpolate_bilinear2d_aa(img, [new_h, new_w], align_corners=False)
elif interpolation == "bicubic":
img = torch.ops.torchvision._interpolate_bicubic2d_aa(img, [new_h, new_w], align_corners=False)
else:
img = interpolate(img, size=[new_h, new_w], mode=interpolation, align_corners=align_corners)
if interpolation == "bicubic" and out_dtype == torch.uint8:
img = img.clamp(min=0, max=255)
img = _cast_squeeze_out(img, need_cast=need_cast, need_squeeze=need_squeeze, out_dtype=out_dtype)
return img
def _assert_grid_transform_inputs(
img: Tensor,
matrix: Optional[List[float]],
interpolation: str,
fill: Optional[List[float]],
supported_interpolation_modes: List[str],
coeffs: Optional[List[float]] = None,
) -> None:
if not (isinstance(img, torch.Tensor)):
raise TypeError("Input img should be Tensor")
_assert_image_tensor(img)
if matrix is not None and not isinstance(matrix, list):
raise TypeError("Argument matrix should be a list")
if matrix is not None and len(matrix) != 6:
raise ValueError("Argument matrix should have 6 float values")
if coeffs is not None and len(coeffs) != 8:
raise ValueError("Argument coeffs should have 8 float values")
if fill is not None and not isinstance(fill, (int, float, tuple, list)):
warnings.warn("Argument fill should be either int, float, tuple or list")
# Check fill
num_channels = get_image_num_channels(img)
if isinstance(fill, (tuple, list)) and (len(fill) > 1 and len(fill) != num_channels):
msg = (
"The number of elements in 'fill' cannot broadcast to match the number of "
"channels of the image ({} != {})"
)
raise ValueError(msg.format(len(fill), num_channels))
if interpolation not in supported_interpolation_modes:
raise ValueError(f"Interpolation mode '{interpolation}' is unsupported with Tensor input")
def _cast_squeeze_in(img: Tensor, req_dtypes: List[torch.dtype]) -> Tuple[Tensor, bool, bool, torch.dtype]:
need_squeeze = False
# make image NCHW
if img.ndim < 4:
img = img.unsqueeze(dim=0)
need_squeeze = True
out_dtype = img.dtype
need_cast = False
if out_dtype not in req_dtypes:
need_cast = True
req_dtype = req_dtypes[0]
img = img.to(req_dtype)
return img, need_cast, need_squeeze, out_dtype
def _cast_squeeze_out(img: Tensor, need_cast: bool, need_squeeze: bool, out_dtype: torch.dtype) -> Tensor:
if need_squeeze:
img = img.squeeze(dim=0)
if need_cast:
if out_dtype in (torch.uint8, torch.int8, torch.int16, torch.int32, torch.int64):
# it is better to round before cast
img = torch.round(img)
img = img.to(out_dtype)
return img
def _apply_grid_transform(img: Tensor, grid: Tensor, mode: str, fill: Optional[List[float]]) -> Tensor:
img, need_cast, need_squeeze, out_dtype = _cast_squeeze_in(
img,
[
grid.dtype,
],
)
if img.shape[0] > 1:
# Apply same grid to a batch of images
grid = grid.expand(img.shape[0], grid.shape[1], grid.shape[2], grid.shape[3])
# Append a dummy mask for customized fill colors, should be faster than grid_sample() twice
if fill is not None:
dummy = torch.ones((img.shape[0], 1, img.shape[2], img.shape[3]), dtype=img.dtype, device=img.device)
img = torch.cat((img, dummy), dim=1)
img = grid_sample(img, grid, mode=mode, padding_mode="zeros", align_corners=False)
# Fill with required color
if fill is not None:
mask = img[:, -1:, :, :] # N * 1 * H * W
img = img[:, :-1, :, :] # N * C * H * W
mask = mask.expand_as(img)
len_fill = len(fill) if isinstance(fill, (tuple, list)) else 1
fill_img = torch.tensor(fill, dtype=img.dtype, device=img.device).view(1, len_fill, 1, 1).expand_as(img)
if mode == "nearest":
mask = mask < 0.5
img[mask] = fill_img[mask]
else: # 'bilinear'
img = img * mask + (1.0 - mask) * fill_img
img = _cast_squeeze_out(img, need_cast, need_squeeze, out_dtype)
return img
def _gen_affine_grid(
theta: Tensor,
w: int,
h: int,
ow: int,
oh: int,
) -> Tensor:
# https://github.com/pytorch/pytorch/blob/74b65c32be68b15dc7c9e8bb62459efbfbde33d8/aten/src/ATen/native/
# AffineGridGenerator.cpp#L18
# Difference with AffineGridGenerator is that:
# 1) we normalize grid values after applying theta
# 2) we can normalize by other image size, such that it covers "extend" option like in PIL.Image.rotate
d = 0.5
base_grid = torch.empty(1, oh, ow, 3, dtype=theta.dtype, device=theta.device)
x_grid = torch.linspace(-ow * 0.5 + d, ow * 0.5 + d - 1, steps=ow, device=theta.device)
base_grid[..., 0].copy_(x_grid)
y_grid = torch.linspace(-oh * 0.5 + d, oh * 0.5 + d - 1, steps=oh, device=theta.device).unsqueeze_(-1)
base_grid[..., 1].copy_(y_grid)
base_grid[..., 2].fill_(1)
rescaled_theta = theta.transpose(1, 2) / torch.tensor([0.5 * w, 0.5 * h], dtype=theta.dtype, device=theta.device)
output_grid = base_grid.view(1, oh * ow, 3).bmm(rescaled_theta)
return output_grid.view(1, oh, ow, 2)
def affine(
img: Tensor, matrix: List[float], interpolation: str = "nearest", fill: Optional[List[float]] = None
) -> Tensor:
_assert_grid_transform_inputs(img, matrix, interpolation, fill, ["nearest", "bilinear"])
dtype = img.dtype if torch.is_floating_point(img) else torch.float32
theta = torch.tensor(matrix, dtype=dtype, device=img.device).reshape(1, 2, 3)
shape = img.shape
# grid will be generated on the same device as theta and img
grid = _gen_affine_grid(theta, w=shape[-1], h=shape[-2], ow=shape[-1], oh=shape[-2])
return _apply_grid_transform(img, grid, interpolation, fill=fill)
def _compute_output_size(matrix: List[float], w: int, h: int) -> Tuple[int, int]:
# Inspired of PIL implementation:
# https://github.com/python-pillow/Pillow/blob/11de3318867e4398057373ee9f12dcb33db7335c/src/PIL/Image.py#L2054
# pts are Top-Left, Top-Right, Bottom-Left, Bottom-Right points.
pts = torch.tensor(
[
[-0.5 * w, -0.5 * h, 1.0],
[-0.5 * w, 0.5 * h, 1.0],
[0.5 * w, 0.5 * h, 1.0],
[0.5 * w, -0.5 * h, 1.0],
]
)
theta = torch.tensor(matrix, dtype=torch.float).reshape(1, 2, 3)
new_pts = pts.view(1, 4, 3).bmm(theta.transpose(1, 2)).view(4, 2)
min_vals, _ = new_pts.min(dim=0)
max_vals, _ = new_pts.max(dim=0)
# Truncate precision to 1e-4 to avoid ceil of Xe-15 to 1.0
tol = 1e-4
cmax = torch.ceil((max_vals / tol).trunc_() * tol)
cmin = torch.floor((min_vals / tol).trunc_() * tol)
size = cmax - cmin
return int(size[0]), int(size[1])
def rotate(
img: Tensor,
matrix: List[float],
interpolation: str = "nearest",
expand: bool = False,
fill: Optional[List[float]] = None,
) -> Tensor:
_assert_grid_transform_inputs(img, matrix, interpolation, fill, ["nearest", "bilinear"])
w, h = img.shape[-1], img.shape[-2]
ow, oh = _compute_output_size(matrix, w, h) if expand else (w, h)
dtype = img.dtype if torch.is_floating_point(img) else torch.float32
theta = torch.tensor(matrix, dtype=dtype, device=img.device).reshape(1, 2, 3)
# grid will be generated on the same device as theta and img
grid = _gen_affine_grid(theta, w=w, h=h, ow=ow, oh=oh)
return _apply_grid_transform(img, grid, interpolation, fill=fill)
def _perspective_grid(coeffs: List[float], ow: int, oh: int, dtype: torch.dtype, device: torch.device) -> Tensor:
# https://github.com/python-pillow/Pillow/blob/4634eafe3c695a014267eefdce830b4a825beed7/
# src/libImaging/Geometry.c#L394
#
# x_out = (coeffs[0] * x + coeffs[1] * y + coeffs[2]) / (coeffs[6] * x + coeffs[7] * y + 1)
# y_out = (coeffs[3] * x + coeffs[4] * y + coeffs[5]) / (coeffs[6] * x + coeffs[7] * y + 1)
#
theta1 = torch.tensor(
[[[coeffs[0], coeffs[1], coeffs[2]], [coeffs[3], coeffs[4], coeffs[5]]]], dtype=dtype, device=device
)
theta2 = torch.tensor([[[coeffs[6], coeffs[7], 1.0], [coeffs[6], coeffs[7], 1.0]]], dtype=dtype, device=device)
d = 0.5
base_grid = torch.empty(1, oh, ow, 3, dtype=dtype, device=device)
x_grid = torch.linspace(d, ow * 1.0 + d - 1.0, steps=ow, device=device)
base_grid[..., 0].copy_(x_grid)
y_grid = torch.linspace(d, oh * 1.0 + d - 1.0, steps=oh, device=device).unsqueeze_(-1)
base_grid[..., 1].copy_(y_grid)
base_grid[..., 2].fill_(1)
rescaled_theta1 = theta1.transpose(1, 2) / torch.tensor([0.5 * ow, 0.5 * oh], dtype=dtype, device=device)
output_grid1 = base_grid.view(1, oh * ow, 3).bmm(rescaled_theta1)
output_grid2 = base_grid.view(1, oh * ow, 3).bmm(theta2.transpose(1, 2))
output_grid = output_grid1 / output_grid2 - 1.0
return output_grid.view(1, oh, ow, 2)
def perspective(
img: Tensor, perspective_coeffs: List[float], interpolation: str = "bilinear", fill: Optional[List[float]] = None
) -> Tensor:
if not (isinstance(img, torch.Tensor)):
raise TypeError("Input img should be Tensor.")
_assert_image_tensor(img)
_assert_grid_transform_inputs(
img,
matrix=None,
interpolation=interpolation,
fill=fill,
supported_interpolation_modes=["nearest", "bilinear"],
coeffs=perspective_coeffs,
)
ow, oh = img.shape[-1], img.shape[-2]
dtype = img.dtype if torch.is_floating_point(img) else torch.float32
grid = _perspective_grid(perspective_coeffs, ow=ow, oh=oh, dtype=dtype, device=img.device)
return _apply_grid_transform(img, grid, interpolation, fill=fill)
def _get_gaussian_kernel1d(kernel_size: int, sigma: float) -> Tensor:
ksize_half = (kernel_size - 1) * 0.5
x = torch.linspace(-ksize_half, ksize_half, steps=kernel_size)
pdf = torch.exp(-0.5 * (x / sigma).pow(2))
kernel1d = pdf / pdf.sum()
return kernel1d
def _get_gaussian_kernel2d(
kernel_size: List[int], sigma: List[float], dtype: torch.dtype, device: torch.device
) -> Tensor:
kernel1d_x = _get_gaussian_kernel1d(kernel_size[0], sigma[0]).to(device, dtype=dtype)
kernel1d_y = _get_gaussian_kernel1d(kernel_size[1], sigma[1]).to(device, dtype=dtype)
kernel2d = torch.mm(kernel1d_y[:, None], kernel1d_x[None, :])
return kernel2d
def gaussian_blur(img: Tensor, kernel_size: List[int], sigma: List[float]) -> Tensor:
if not (isinstance(img, torch.Tensor)):
raise TypeError(f"img should be Tensor. Got {type(img)}")
_assert_image_tensor(img)
dtype = img.dtype if torch.is_floating_point(img) else torch.float32
kernel = _get_gaussian_kernel2d(kernel_size, sigma, dtype=dtype, device=img.device)
kernel = kernel.expand(img.shape[-3], 1, kernel.shape[0], kernel.shape[1])
img, need_cast, need_squeeze, out_dtype = _cast_squeeze_in(
img,
[
kernel.dtype,
],
)
# padding = (left, right, top, bottom)
padding = [kernel_size[0] // 2, kernel_size[0] // 2, kernel_size[1] // 2, kernel_size[1] // 2]
img = torch_pad(img, padding, mode="reflect")
img = conv2d(img, kernel, groups=img.shape[-3])
img = _cast_squeeze_out(img, need_cast, need_squeeze, out_dtype)
return img
def invert(img: Tensor) -> Tensor:
_assert_image_tensor(img)
if img.ndim < 3:
raise TypeError(f"Input image tensor should have at least 3 dimensions, but found {img.ndim}")
_assert_channels(img, [1, 3])
bound = torch.tensor(1 if img.is_floating_point() else 255, dtype=img.dtype, device=img.device)
return bound - img
def posterize(img: Tensor, bits: int) -> Tensor:
_assert_image_tensor(img)
if img.ndim < 3:
raise TypeError(f"Input image tensor should have at least 3 dimensions, but found {img.ndim}")
if img.dtype != torch.uint8:
raise TypeError(f"Only torch.uint8 image tensors are supported, but found {img.dtype}")
_assert_channels(img, [1, 3])
mask = -int(2 ** (8 - bits)) # JIT-friendly for: ~(2 ** (8 - bits) - 1)
return img & mask
def solarize(img: Tensor, threshold: float) -> Tensor:
_assert_image_tensor(img)
if img.ndim < 3:
raise TypeError(f"Input image tensor should have at least 3 dimensions, but found {img.ndim}")
_assert_channels(img, [1, 3])
_assert_threshold(img, threshold)
inverted_img = invert(img)
return torch.where(img >= threshold, inverted_img, img)
def _blurred_degenerate_image(img: Tensor) -> Tensor:
dtype = img.dtype if torch.is_floating_point(img) else torch.float32
kernel = torch.ones((3, 3), dtype=dtype, device=img.device)
kernel[1, 1] = 5.0
kernel /= kernel.sum()
kernel = kernel.expand(img.shape[-3], 1, kernel.shape[0], kernel.shape[1])
result_tmp, need_cast, need_squeeze, out_dtype = _cast_squeeze_in(
img,
[
kernel.dtype,
],
)
result_tmp = conv2d(result_tmp, kernel, groups=result_tmp.shape[-3])
result_tmp = _cast_squeeze_out(result_tmp, need_cast, need_squeeze, out_dtype)
result = img.clone()
result[..., 1:-1, 1:-1] = result_tmp
return result
def adjust_sharpness(img: Tensor, sharpness_factor: float) -> Tensor:
if sharpness_factor < 0:
raise ValueError(f"sharpness_factor ({sharpness_factor}) is not non-negative.")
_assert_image_tensor(img)
_assert_channels(img, [1, 3])
if img.size(-1) <= 2 or img.size(-2) <= 2:
return img
return _blend(img, _blurred_degenerate_image(img), sharpness_factor)
def autocontrast(img: Tensor) -> Tensor:
_assert_image_tensor(img)
if img.ndim < 3:
raise TypeError(f"Input image tensor should have at least 3 dimensions, but found {img.ndim}")
_assert_channels(img, [1, 3])
bound = 1.0 if img.is_floating_point() else 255.0
dtype = img.dtype if torch.is_floating_point(img) else torch.float32
minimum = img.amin(dim=(-2, -1), keepdim=True).to(dtype)
maximum = img.amax(dim=(-2, -1), keepdim=True).to(dtype)
scale = bound / (maximum - minimum)
eq_idxs = torch.isfinite(scale).logical_not()
minimum[eq_idxs] = 0
scale[eq_idxs] = 1
return ((img - minimum) * scale).clamp(0, bound).to(img.dtype)
def _scale_channel(img_chan: Tensor) -> Tensor:
# TODO: we should expect bincount to always be faster than histc, but this
# isn't always the case. Once
# https://github.com/pytorch/pytorch/issues/53194 is fixed, remove the if
# block and only use bincount.
if img_chan.is_cuda:
hist = torch.histc(img_chan.to(torch.float32), bins=256, min=0, max=255)
else:
hist = torch.bincount(img_chan.view(-1), minlength=256)
nonzero_hist = hist[hist != 0]
step = torch.div(nonzero_hist[:-1].sum(), 255, rounding_mode="floor")
if step == 0:
return img_chan
lut = torch.div(torch.cumsum(hist, 0) + torch.div(step, 2, rounding_mode="floor"), step, rounding_mode="floor")
lut = torch.nn.functional.pad(lut, [1, 0])[:-1].clamp(0, 255)
return lut[img_chan.to(torch.int64)].to(torch.uint8)
def _equalize_single_image(img: Tensor) -> Tensor:
return torch.stack([_scale_channel(img[c]) for c in range(img.size(0))])
def equalize(img: Tensor) -> Tensor:
_assert_image_tensor(img)
if not (3 <= img.ndim <= 4):
raise TypeError(f"Input image tensor should have 3 or 4 dimensions, but found {img.ndim}")
if img.dtype != torch.uint8:
raise TypeError(f"Only torch.uint8 image tensors are supported, but found {img.dtype}")
_assert_channels(img, [1, 3])
if img.ndim == 3:
return _equalize_single_image(img)
return torch.stack([_equalize_single_image(x) for x in img])
| 35.62028
| 119
| 0.638855
|
252803be66423b10eade3cf5f707abf8f55821b1
| 5,732
|
py
|
Python
|
test/functional/prioritise_transaction.py
|
gradinkov/pigeoncoin
|
1a4f420f344d229d37514b570e92cae358ea06d7
|
[
"MIT"
] | 49
|
2018-03-24T13:56:00.000Z
|
2021-04-15T04:29:17.000Z
|
test/functional/prioritise_transaction.py
|
gradinkov/pigeoncoin
|
1a4f420f344d229d37514b570e92cae358ea06d7
|
[
"MIT"
] | 18
|
2018-03-22T20:12:34.000Z
|
2020-05-14T03:09:37.000Z
|
test/functional/prioritise_transaction.py
|
gradinkov/pigeoncoin
|
1a4f420f344d229d37514b570e92cae358ea06d7
|
[
"MIT"
] | 64
|
2018-03-27T00:17:34.000Z
|
2021-12-02T21:41:27.000Z
|
#!/usr/bin/env python3
# Copyright (c) 2015-2016 The Bitcoin Core developers
# Copyright (c) 2017 The Pigeon Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
"""Test the prioritisetransaction mining RPC."""
from test_framework.test_framework import PigeonTestFramework
from test_framework.util import *
from test_framework.mininode import COIN, MAX_BLOCK_BASE_SIZE
class PrioritiseTransactionTest(PigeonTestFramework):
def set_test_params(self):
self.setup_clean_chain = True
self.num_nodes = 2
self.extra_args = [["-printpriority=1"], ["-printpriority=1"]]
def run_test(self):
self.txouts = gen_return_txouts()
self.relayfee = self.nodes[0].getnetworkinfo()['relayfee']
utxo_count = 90
utxos = create_confirmed_utxos(self.relayfee, self.nodes[0], utxo_count)
base_fee = self.relayfee*100 # our transactions are smaller than 100kb
txids = []
# Create 3 batches of transactions at 3 different fee rate levels
range_size = utxo_count // 3
for i in range(3):
txids.append([])
start_range = i * range_size
end_range = start_range + range_size
txids[i] = create_lots_of_big_transactions(self.nodes[0], self.txouts, utxos[start_range:end_range], end_range - start_range, (i+1)*base_fee)
# Make sure that the size of each group of transactions exceeds
# MAX_BLOCK_BASE_SIZE -- otherwise the test needs to be revised to create
# more transactions.
mempool = self.nodes[0].getrawmempool(True)
sizes = [0, 0, 0]
for i in range(3):
for j in txids[i]:
assert(j in mempool)
sizes[i] += mempool[j]['size']
assert(sizes[i] > MAX_BLOCK_BASE_SIZE) # Fail => raise utxo_count
# add a fee delta to something in the cheapest bucket and make sure it gets mined
# also check that a different entry in the cheapest bucket is NOT mined
self.nodes[0].prioritisetransaction(txid=txids[0][0], fee_delta=int(3*base_fee*COIN))
self.nodes[0].generate(1)
mempool = self.nodes[0].getrawmempool()
self.log.info("Assert that prioritised transaction was mined")
assert(txids[0][0] not in mempool)
assert(txids[0][1] in mempool)
high_fee_tx = None
for x in txids[2]:
if x not in mempool:
high_fee_tx = x
# Something high-fee should have been mined!
assert(high_fee_tx != None)
# Add a prioritisation before a tx is in the mempool (de-prioritising a
# high-fee transaction so that it's now low fee).
self.nodes[0].prioritisetransaction(txid=high_fee_tx, fee_delta=-int(2*base_fee*COIN))
# Add everything back to mempool
self.nodes[0].invalidateblock(self.nodes[0].getbestblockhash())
# Check to make sure our high fee rate tx is back in the mempool
mempool = self.nodes[0].getrawmempool()
assert(high_fee_tx in mempool)
# Now verify the modified-high feerate transaction isn't mined before
# the other high fee transactions. Keep mining until our mempool has
# decreased by all the high fee size that we calculated above.
while (self.nodes[0].getmempoolinfo()['bytes'] > sizes[0] + sizes[1]):
self.nodes[0].generate(1)
# High fee transaction should not have been mined, but other high fee rate
# transactions should have been.
mempool = self.nodes[0].getrawmempool()
self.log.info("Assert that de-prioritised transaction is still in mempool")
assert(high_fee_tx in mempool)
for x in txids[2]:
if (x != high_fee_tx):
assert(x not in mempool)
# Create a free transaction. Should be rejected.
utxo_list = self.nodes[0].listunspent()
assert(len(utxo_list) > 0)
utxo = utxo_list[0]
inputs = []
outputs = {}
inputs.append({"txid" : utxo["txid"], "vout" : utxo["vout"]})
outputs[self.nodes[0].getnewaddress()] = utxo["amount"]
raw_tx = self.nodes[0].createrawtransaction(inputs, outputs)
tx_hex = self.nodes[0].signrawtransaction(raw_tx)["hex"]
tx_id = self.nodes[0].decoderawtransaction(tx_hex)["txid"]
# This will raise an exception due to min relay fee not being met
assert_raises_rpc_error(-26, "66: min relay fee not met", self.nodes[0].sendrawtransaction, tx_hex)
assert(tx_id not in self.nodes[0].getrawmempool())
# This is a less than 1000-byte transaction, so just set the fee
# to be the minimum for a 1000 byte transaction and check that it is
# accepted.
self.nodes[0].prioritisetransaction(txid=tx_id, fee_delta=int(self.relayfee*COIN))
self.log.info("Assert that prioritised free transaction is accepted to mempool")
assert_equal(self.nodes[0].sendrawtransaction(tx_hex), tx_id)
assert(tx_id in self.nodes[0].getrawmempool())
# Test that calling prioritisetransaction is sufficient to trigger
# getblocktemplate to (eventually) return a new block.
mock_time = int(time.time())
self.nodes[0].setmocktime(mock_time)
template = self.nodes[0].getblocktemplate()
self.nodes[0].prioritisetransaction(txid=tx_id, fee_delta=-int(self.relayfee*COIN))
self.nodes[0].setmocktime(mock_time+10)
new_template = self.nodes[0].getblocktemplate()
assert(template != new_template)
if __name__ == '__main__':
PrioritiseTransactionTest().main()
| 44.092308
| 153
| 0.658234
|
d0e9f83088d8cc6c4eab82839dc1baa9255e5461
| 4,858
|
py
|
Python
|
alerta/models/heartbeat.py
|
iDemonix/alerta
|
c35c56ca246d968c0f7419af0b485e999530f792
|
[
"Apache-2.0"
] | null | null | null |
alerta/models/heartbeat.py
|
iDemonix/alerta
|
c35c56ca246d968c0f7419af0b485e999530f792
|
[
"Apache-2.0"
] | null | null | null |
alerta/models/heartbeat.py
|
iDemonix/alerta
|
c35c56ca246d968c0f7419af0b485e999530f792
|
[
"Apache-2.0"
] | null | null | null |
import os
import platform
import sys
from datetime import datetime, timedelta
from typing import Any, Dict, List, Optional, Tuple, Union
from uuid import uuid4
from flask import current_app
from alerta.app import db
from alerta.database.base import Query
from alerta.utils.format import DateTime
from alerta.utils.response import absolute_url
MAX_LATENCY = 2000 # ms
JSON = Dict[str, Any]
class Heartbeat:
def __init__(self, origin: str=None, tags: List[str]=None, create_time: datetime=None, timeout: int=None, customer: str=None, **kwargs) -> None:
self.id = kwargs.get('id', str(uuid4()))
self.origin = origin or '{}/{}'.format(os.path.basename(sys.argv[0]), platform.uname()[1])
self.tags = tags or list()
self.event_type = kwargs.get('event_type', kwargs.get('type', None)) or 'Heartbeat'
self.create_time = create_time or datetime.utcnow()
self.timeout = timeout or current_app.config['HEARTBEAT_TIMEOUT']
self.receive_time = kwargs.get('receive_time', None) or datetime.utcnow()
self.customer = customer
@property
def latency(self) -> int:
return int((self.receive_time - self.create_time).total_seconds() * 1000)
@property
def since(self) -> timedelta:
since = datetime.utcnow() - self.receive_time
return since - timedelta(microseconds=since.microseconds)
@property
def status(self) -> str:
if self.latency > MAX_LATENCY:
return 'slow'
elif self.since.total_seconds() > self.timeout:
return 'expired' # aka 'stale'
else:
return 'ok'
@classmethod
def parse(cls, json: JSON) -> 'Heartbeat':
if not isinstance(json.get('tags', []), list):
raise ValueError('tags must be a list')
if not isinstance(json.get('timeout') if json.get('timeout', None) is not None else 0, int):
raise ValueError('timeout must be an integer')
if json.get('customer', None) == '':
raise ValueError('customer must not be an empty string')
return Heartbeat(
origin=json.get('origin', None),
tags=json.get('tags', list()),
create_time=DateTime.parse(json['createTime']) if 'createTime' in json else None,
timeout=json.get('timeout', None),
customer=json.get('customer', None)
)
@property
def serialize(self) -> Dict[str, Any]:
return {
'id': self.id,
'href': absolute_url('/heartbeat/' + self.id),
'origin': self.origin,
'tags': self.tags,
'type': self.event_type,
'createTime': self.create_time,
'timeout': self.timeout,
'receiveTime': self.receive_time,
'customer': self.customer,
'latency': self.latency,
'since': self.since,
'status': self.status
}
def __repr__(self) -> str:
return 'Heartbeat(id={!r}, origin={!r}, create_time={!r}, timeout={!r}, customer={!r})'.format(
self.id, self.origin, self.create_time, self.timeout, self.customer)
@classmethod
def from_document(cls, doc: Dict[str, Any]) -> 'Heartbeat':
return Heartbeat(
id=doc.get('id', None) or doc.get('_id'),
origin=doc.get('origin', None),
tags=doc.get('tags', list()),
event_type=doc.get('type', None),
create_time=doc.get('createTime', None),
timeout=doc.get('timeout', None),
receive_time=doc.get('receiveTime', None),
customer=doc.get('customer', None)
)
@classmethod
def from_record(cls, rec) -> 'Heartbeat':
return Heartbeat(
id=rec.id,
origin=rec.origin,
tags=rec.tags,
event_type=rec.type,
create_time=rec.create_time,
timeout=rec.timeout,
receive_time=rec.receive_time,
customer=rec.customer
)
@classmethod
def from_db(cls, r: Union[Dict, Tuple]) -> 'Heartbeat':
if isinstance(r, dict):
return cls.from_document(r)
elif isinstance(r, tuple):
return cls.from_record(r)
# create/update a heartbeat
def create(self) -> 'Heartbeat':
return Heartbeat.from_db(db.upsert_heartbeat(self))
# retrieve an heartbeat
@staticmethod
def find_by_id(id: str, customers: List[str]=None) -> Optional['Heartbeat']:
return Heartbeat.from_db(db.get_heartbeat(id, customers))
# search heartbeats
@staticmethod
def find_all(query: Query=None) -> List['Heartbeat']:
return [Heartbeat.from_db(heartbeat) for heartbeat in db.get_heartbeats(query)]
# delete a heartbeat
def delete(self) -> bool:
return db.delete_heartbeat(self.id)
| 34.94964
| 148
| 0.605393
|
261cd1ed2d49f86c1d6d35e0a9170c1e0a414f71
| 13,397
|
py
|
Python
|
libraries/classification/inception/inception_distributed_train.py
|
jayant766/MIDAS-IIITD
|
9a6085bff579a5846c58bac70264a736ed9da750
|
[
"Apache-2.0"
] | 2
|
2021-05-04T11:43:20.000Z
|
2021-05-21T18:10:39.000Z
|
libraries/classification/inception/inception_distributed_train.py
|
jayant766/MIDAS-IIITD
|
9a6085bff579a5846c58bac70264a736ed9da750
|
[
"Apache-2.0"
] | null | null | null |
libraries/classification/inception/inception_distributed_train.py
|
jayant766/MIDAS-IIITD
|
9a6085bff579a5846c58bac70264a736ed9da750
|
[
"Apache-2.0"
] | null | null | null |
"""A library to train Inception using multiple replicas with synchronous update.
Please see accompanying README.md for details and instructions.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from datetime import datetime
import os.path
import time
import numpy as np
import tensorflow as tf
from inception import image_processing
from inception import inception_model as inception
from inception.slim import slim
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_string('job_name', '', 'One of "ps", "worker"')
tf.app.flags.DEFINE_string('ps_hosts', '',
"""Comma-separated list of hostname:port for the """
"""parameter server jobs. e.g. """
"""'machine1:2222,machine2:1111,machine2:2222'""")
tf.app.flags.DEFINE_string('worker_hosts', '',
"""Comma-separated list of hostname:port for the """
"""worker jobs. e.g. """
"""'machine1:2222,machine2:1111,machine2:2222'""")
tf.app.flags.DEFINE_string('protocol', 'grpc',
"""Communication protocol to use in distributed """
"""execution (default grpc) """)
tf.app.flags.DEFINE_string('train_dir', '/tmp/imagenet_train',
"""Directory where to write event logs """
"""and checkpoint.""")
tf.app.flags.DEFINE_integer('max_steps', 1000000, 'Number of batches to run.')
tf.app.flags.DEFINE_string('subset', 'train', 'Either "train" or "validation".')
tf.app.flags.DEFINE_boolean('log_device_placement', False,
'Whether to log device placement.')
# Task ID is used to select the chief and also to access the local_step for
# each replica to check staleness of the gradients in SyncReplicasOptimizer.
tf.app.flags.DEFINE_integer(
'task_id', 0, 'Task ID of the worker/replica running the training.')
# More details can be found in the SyncReplicasOptimizer class:
# tensorflow/python/training/sync_replicas_optimizer.py
tf.app.flags.DEFINE_integer('num_replicas_to_aggregate', -1,
"""Number of gradients to collect before """
"""updating the parameters.""")
tf.app.flags.DEFINE_integer('save_interval_secs', 10 * 60,
'Save interval seconds.')
tf.app.flags.DEFINE_integer('save_summaries_secs', 180,
'Save summaries interval seconds.')
# **IMPORTANT**
# Please note that this learning rate schedule is heavily dependent on the
# hardware architecture, batch size and any changes to the model architecture
# specification. Selecting a finely tuned learning rate schedule is an
# empirical process that requires some experimentation. Please see README.md
# more guidance and discussion.
#
# Learning rate decay factor selected from https://arxiv.org/abs/1604.00981
tf.app.flags.DEFINE_float('initial_learning_rate', 0.045,
'Initial learning rate.')
tf.app.flags.DEFINE_float('num_epochs_per_decay', 2.0,
'Epochs after which learning rate decays.')
tf.app.flags.DEFINE_float('learning_rate_decay_factor', 0.94,
'Learning rate decay factor.')
# Constants dictating the learning rate schedule.
RMSPROP_DECAY = 0.9 # Decay term for RMSProp.
RMSPROP_MOMENTUM = 0.9 # Momentum in RMSProp.
RMSPROP_EPSILON = 1.0 # Epsilon term for RMSProp.
def train(target, dataset, cluster_spec):
"""Train Inception on a dataset for a number of steps."""
# Number of workers and parameter servers are inferred from the workers and ps
# hosts string.
num_workers = len(cluster_spec.as_dict()['worker'])
num_parameter_servers = len(cluster_spec.as_dict()['ps'])
# If no value is given, num_replicas_to_aggregate defaults to be the number of
# workers.
if FLAGS.num_replicas_to_aggregate == -1:
num_replicas_to_aggregate = num_workers
else:
num_replicas_to_aggregate = FLAGS.num_replicas_to_aggregate
# Both should be greater than 0 in a distributed training.
assert num_workers > 0 and num_parameter_servers > 0, (' num_workers and '
'num_parameter_servers'
' must be > 0.')
# Choose worker 0 as the chief. Note that any worker could be the chief
# but there should be only one chief.
is_chief = (FLAGS.task_id == 0)
# Ops are assigned to worker by default.
with tf.device('/job:worker/task:%d' % FLAGS.task_id):
# Variables and its related init/assign ops are assigned to ps.
with slim.scopes.arg_scope(
[slim.variables.variable, slim.variables.global_step],
device=slim.variables.VariableDeviceChooser(num_parameter_servers)):
# Create a variable to count the number of train() calls. This equals the
# number of updates applied to the variables.
global_step = slim.variables.global_step()
# Calculate the learning rate schedule.
num_batches_per_epoch = (dataset.num_examples_per_epoch() /
FLAGS.batch_size)
# Decay steps need to be divided by the number of replicas to aggregate.
decay_steps = int(num_batches_per_epoch * FLAGS.num_epochs_per_decay /
num_replicas_to_aggregate)
# Decay the learning rate exponentially based on the number of steps.
lr = tf.train.exponential_decay(FLAGS.initial_learning_rate,
global_step,
decay_steps,
FLAGS.learning_rate_decay_factor,
staircase=True)
# Add a summary to track the learning rate.
tf.summary.scalar('learning_rate', lr)
# Create an optimizer that performs gradient descent.
opt = tf.train.RMSPropOptimizer(lr,
RMSPROP_DECAY,
momentum=RMSPROP_MOMENTUM,
epsilon=RMSPROP_EPSILON)
images, labels = image_processing.distorted_inputs(
dataset,
batch_size=FLAGS.batch_size,
num_preprocess_threads=FLAGS.num_preprocess_threads)
# Number of classes in the Dataset label set plus 1.
# Label 0 is reserved for an (unused) background class.
num_classes = dataset.num_classes() + 1
logits = inception.inference(images, num_classes, for_training=True)
# Add classification loss.
inception.loss(logits, labels)
# Gather all of the losses including regularization losses.
losses = tf.get_collection(slim.losses.LOSSES_COLLECTION)
losses += tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)
total_loss = tf.add_n(losses, name='total_loss')
if is_chief:
# Compute the moving average of all individual losses and the
# total loss.
loss_averages = tf.train.ExponentialMovingAverage(0.9, name='avg')
loss_averages_op = loss_averages.apply(losses + [total_loss])
# Attach a scalar summmary to all individual losses and the total loss;
# do the same for the averaged version of the losses.
for l in losses + [total_loss]:
loss_name = l.op.name
# Name each loss as '(raw)' and name the moving average version of the
# loss as the original loss name.
tf.summary.scalar(loss_name + ' (raw)', l)
tf.summary.scalar(loss_name, loss_averages.average(l))
# Add dependency to compute loss_averages.
with tf.control_dependencies([loss_averages_op]):
total_loss = tf.identity(total_loss)
# Track the moving averages of all trainable variables.
# Note that we maintain a 'double-average' of the BatchNormalization
# global statistics.
# This is not needed when the number of replicas are small but important
# for synchronous distributed training with tens of workers/replicas.
exp_moving_averager = tf.train.ExponentialMovingAverage(
inception.MOVING_AVERAGE_DECAY, global_step)
variables_to_average = (
tf.trainable_variables() + tf.moving_average_variables())
# Add histograms for model variables.
for var in variables_to_average:
tf.summary.histogram(var.op.name, var)
# Create synchronous replica optimizer.
opt = tf.train.SyncReplicasOptimizer(
opt,
replicas_to_aggregate=num_replicas_to_aggregate,
total_num_replicas=num_workers,
variable_averages=exp_moving_averager,
variables_to_average=variables_to_average)
batchnorm_updates = tf.get_collection(slim.ops.UPDATE_OPS_COLLECTION)
assert batchnorm_updates, 'Batchnorm updates are missing'
batchnorm_updates_op = tf.group(*batchnorm_updates)
# Add dependency to compute batchnorm_updates.
with tf.control_dependencies([batchnorm_updates_op]):
total_loss = tf.identity(total_loss)
# Compute gradients with respect to the loss.
grads = opt.compute_gradients(total_loss)
# Add histograms for gradients.
for grad, var in grads:
if grad is not None:
tf.summary.histogram(var.op.name + '/gradients', grad)
apply_gradients_op = opt.apply_gradients(grads, global_step=global_step)
with tf.control_dependencies([apply_gradients_op]):
train_op = tf.identity(total_loss, name='train_op')
# Get chief queue_runners and init_tokens, which is used to synchronize
# replicas. More details can be found in SyncReplicasOptimizer.
chief_queue_runners = [opt.get_chief_queue_runner()]
init_tokens_op = opt.get_init_tokens_op()
# Create a saver.
saver = tf.train.Saver()
# Build the summary operation based on the TF collection of Summaries.
summary_op = tf.summary.merge_all()
# Build an initialization operation to run below.
init_op = tf.global_variables_initializer()
# We run the summaries in the same thread as the training operations by
# passing in None for summary_op to avoid a summary_thread being started.
# Running summaries and training operations in parallel could run out of
# GPU memory.
sv = tf.train.Supervisor(is_chief=is_chief,
logdir=FLAGS.train_dir,
init_op=init_op,
summary_op=None,
global_step=global_step,
saver=saver,
save_model_secs=FLAGS.save_interval_secs)
tf.logging.info('%s Supervisor' % datetime.now())
sess_config = tf.ConfigProto(
allow_soft_placement=True,
log_device_placement=FLAGS.log_device_placement)
# Get a session.
sess = sv.prepare_or_wait_for_session(target, config=sess_config)
# Start the queue runners.
queue_runners = tf.get_collection(tf.GraphKeys.QUEUE_RUNNERS)
sv.start_queue_runners(sess, queue_runners)
tf.logging.info('Started %d queues for processing input data.',
len(queue_runners))
if is_chief:
sv.start_queue_runners(sess, chief_queue_runners)
sess.run(init_tokens_op)
# Train, checking for Nans. Concurrently run the summary operation at a
# specified interval. Note that the summary_op and train_op never run
# simultaneously in order to prevent running out of GPU memory.
next_summary_time = time.time() + FLAGS.save_summaries_secs
while not sv.should_stop():
try:
start_time = time.time()
loss_value, step = sess.run([train_op, global_step])
assert not np.isnan(loss_value), 'Model diverged with loss = NaN'
if step > FLAGS.max_steps:
break
duration = time.time() - start_time
if step % 30 == 0:
examples_per_sec = FLAGS.batch_size / float(duration)
format_str = ('Worker %d: %s: step %d, loss = %.2f'
'(%.1f examples/sec; %.3f sec/batch)')
tf.logging.info(format_str %
(FLAGS.task_id, datetime.now(), step, loss_value,
examples_per_sec, duration))
# Determine if the summary_op should be run on the chief worker.
if is_chief and next_summary_time < time.time():
tf.logging.info('Running Summary operation on the chief.')
summary_str = sess.run(summary_op)
sv.summary_computed(sess, summary_str)
tf.logging.info('Finished running Summary operation.')
# Determine the next time for running the summary.
next_summary_time += FLAGS.save_summaries_secs
except:
if is_chief:
tf.logging.info('Chief got exception while running!')
raise
# Stop the supervisor. This also waits for service threads to finish.
sv.stop()
# Save after the training ends.
if is_chief:
saver.save(sess,
os.path.join(FLAGS.train_dir, 'model.ckpt'),
global_step=global_step)
| 44.508306
| 80
| 0.646787
|
fbb94e2221ca749fa555274a352cd37691ad49a0
| 1,056
|
py
|
Python
|
pymatflow/cp2k/post/scripts/post-geo-opt-cp2k.py
|
DeqiTang/pymatflow
|
bd8776feb40ecef0e6704ee898d9f42ded3b0186
|
[
"MIT"
] | 6
|
2020-03-06T16:13:08.000Z
|
2022-03-09T07:53:34.000Z
|
pymatflow/cp2k/post/scripts/post-geo-opt-cp2k.py
|
DeqiTang/pymatflow
|
bd8776feb40ecef0e6704ee898d9f42ded3b0186
|
[
"MIT"
] | 1
|
2021-10-02T02:23:08.000Z
|
2021-11-08T13:29:37.000Z
|
pymatflow/cp2k/post/scripts/post-geo-opt-cp2k.py
|
DeqiTang/pymatflow
|
bd8776feb40ecef0e6704ee898d9f42ded3b0186
|
[
"MIT"
] | 1
|
2021-07-10T16:28:14.000Z
|
2021-07-10T16:28:14.000Z
|
#!/usr/bin/env python
# _*_ coding: utf-8 _*_
import os
import sys
import matplotlib.pyplot as plt
"""
usage:
post-geo-opt-cp2k.py xxx
xxx is the output file of the GEO_OPT run
"""
os.system("cat %s | grep 'ENERGY| Total FORCE_EVAL' > energy-per-geo-step.data" % (sys.argv[1]))
os.system("cat %s | grep '*** SCF run converged in' > scf-steps.data" % (sys.argv[1]))
energies = []
with open("energy-per-geo-step.data", 'r') as fin:
for line in fin:
energies.append(float(line.split()[8]))
scf_steps = []
with open("scf-steps.data", 'r') as fin:
for line in fin:
scf_steps.append(int(line.split()[5]))
ion_steps = [i for i in range(len(energies))]
#plt.plot(ion_steps, energies)
plt.scatter(ion_steps, energies)
for a, b in zip(ion_steps, energies):
#plt.text(a+0.001, b+0.001, 'scf steps: %d' % scf_steps[a], ha='center', va='bottom', fontsize=7)
plt.annotate(s="scf steps: %d" % scf_steps[a], xy=(a, b), xytext=(a+0.01, b+0.01), arrowprops={'arrowstyle':'->'})
plt.show()
| 28.540541
| 119
| 0.618371
|
4166d787a8cae126853bb3d514ec578ee8f9a3a9
| 2,157
|
py
|
Python
|
sitetree/management/commands/sitetreedump.py
|
mrog70/django-sitetree2
|
5dd56c9a7823f67a2988be1238b3d46860a6a426
|
[
"BSD-3-Clause"
] | null | null | null |
sitetree/management/commands/sitetreedump.py
|
mrog70/django-sitetree2
|
5dd56c9a7823f67a2988be1238b3d46860a6a426
|
[
"BSD-3-Clause"
] | null | null | null |
sitetree/management/commands/sitetreedump.py
|
mrog70/django-sitetree2
|
5dd56c9a7823f67a2988be1238b3d46860a6a426
|
[
"BSD-3-Clause"
] | null | null | null |
from django.core import serializers
from django.core.management.base import BaseCommand, CommandError
from django.db import DEFAULT_DB_ALIAS
from sitetree.utils import get_tree_model, get_tree_item_model
from sitetree.compat import CommandOption, options_getter, VERSION
MODEL_TREE_CLASS = get_tree_model()
MODEL_TREE_ITEM_CLASS = get_tree_item_model()
get_options = options_getter((
CommandOption(
'--indent', default=None, dest='indent', type=int,
help='Specifies the indent level to use when pretty-printing output.'),
CommandOption('--items_only', action='store_true', dest='items_only', default=False,
help='Export tree items only.'),
CommandOption('--database', action='store', dest='database', default=DEFAULT_DB_ALIAS,
help='Nominates a specific database to export fixtures from. Defaults to the "default" database.'),
))
class Command(BaseCommand):
option_list = get_options()
help = 'Output sitetrees from database as a fixture in JSON format.'
args = '[tree_alias tree_alias ...]'
def add_arguments(self, parser):
if VERSION >= (1, 10):
# Before that args already set with nargs='*'.
parser.add_argument('args', metavar='tree', nargs='?', help='Tree aliases.', default=[])
get_options(parser.add_argument)
def handle(self, *aliases, **options):
indent = options.get('indent', None)
using = options.get('database', DEFAULT_DB_ALIAS)
items_only = options.get('items_only', False)
objects = []
if aliases:
trees = MODEL_TREE_CLASS._default_manager.using(using).filter(alias__in=aliases)
else:
trees = MODEL_TREE_CLASS._default_manager.using(using).all()
if not items_only:
objects.extend(trees)
for tree in trees:
objects.extend(MODEL_TREE_ITEM_CLASS._default_manager.using(using).filter(tree=tree).order_by('parent'))
try:
return serializers.serialize('json', objects, indent=indent)
except Exception as e:
raise CommandError('Unable to serialize sitetree(s): %s' % e)
| 33.703125
| 116
| 0.679184
|
86f5387e001bf28a4c073b4e75316b8ac138845d
| 1,289
|
py
|
Python
|
Lib/tkinter/commondialog.py
|
dignissimus/cpython
|
17357108732c731d6ed4f2bd123ee6ba1ff6891b
|
[
"0BSD"
] | null | null | null |
Lib/tkinter/commondialog.py
|
dignissimus/cpython
|
17357108732c731d6ed4f2bd123ee6ba1ff6891b
|
[
"0BSD"
] | 2
|
2022-01-01T11:08:44.000Z
|
2022-03-01T19:01:02.000Z
|
Lib/tkinter/commondialog.py
|
dignissimus/cpython
|
17357108732c731d6ed4f2bd123ee6ba1ff6891b
|
[
"0BSD"
] | null | null | null |
# base class for tk common dialogues
#
# this module provides a base class for accessing the common
# dialogues available in Tk 4.2 and newer. use filedialog,
# colorchooser, and messagebox to access the individual
# dialogs.
#
# written by Fredrik Lundh, May 1997
#
__all__ = ["Dialog"]
from tkinter import _get_temp_root, _destroy_temp_root
class Dialog:
command = None
def __init__(self, master=None, **options):
if master is None:
master = options.get('parent')
self.master = master
self.options = options
def _fixoptions(self):
pass # hook
def _fixresult(self, widget, result):
return result # hook
def show(self, **options):
# update instance options
for k, v in options.items():
self.options[k] = v
self._fixoptions()
master = self.master
if master is None:
master = _get_temp_root()
try:
self._test_callback(master) # The function below is replaced for some tests.
s = master.tk.call(self.command, *master._options(self.options))
s = self._fixresult(master, s)
finally:
_destroy_temp_root(master)
return s
def _test_callback(self, master):
pass
| 23.87037
| 89
| 0.622188
|
0f6c04bcf5f85d41f194d32b94a8592447c298d4
| 26,649
|
py
|
Python
|
image_generation/render_images.py
|
BScarleth/clevr-dataset-generation-mask
|
efa11d69b2fc21a2007205cac6a4b0122149af7d
|
[
"BSD-3-Clause"
] | null | null | null |
image_generation/render_images.py
|
BScarleth/clevr-dataset-generation-mask
|
efa11d69b2fc21a2007205cac6a4b0122149af7d
|
[
"BSD-3-Clause"
] | null | null | null |
image_generation/render_images.py
|
BScarleth/clevr-dataset-generation-mask
|
efa11d69b2fc21a2007205cac6a4b0122149af7d
|
[
"BSD-3-Clause"
] | null | null | null |
# Copyright 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree. An additional grant
# of patent rights can be found in the PATENTS file in the same directory.
from __future__ import print_function
import math, sys, random, argparse, json, os, tempfile
from datetime import datetime as dt
from collections import Counter
"""
Renders random scenes using Blender, each with with a random number of objects;
each object has a random size, position, color, and shape. Objects will be
nonintersecting but may partially occlude each other. Output images will be
written to disk as PNGs, and we will also write a JSON file for each image with
ground-truth scene information.
This file expects to be run from Blender like this:
blender --background --python render_images.py -- [arguments to this script]
"""
INSIDE_BLENDER = True
try:
import bpy, bpy_extras
from mathutils import Vector
except ImportError as e:
INSIDE_BLENDER = False
if INSIDE_BLENDER:
try:
import utils
except ImportError as e:
print("\nERROR")
print("Running render_images.py from Blender and cannot import utils.py.")
print("You may need to add a .pth file to the site-packages of Blender's")
print("bundled python with a command like this:\n")
print("echo $PWD >> $BLENDER/$VERSION/python/lib/python3.5/site-packages/clevr.pth")
print("\nWhere $BLENDER is the directory where Blender is installed, and")
print("$VERSION is your Blender version (such as 2.78).")
sys.exit(1)
parser = argparse.ArgumentParser()
# Input options
parser.add_argument('--base_scene_blendfile', default='data/base_scene.blend',
help="Base blender file on which all scenes are based; includes " +
"ground plane, lights, and camera.")
parser.add_argument('--properties_json', default='data/properties.json',
help="JSON file defining objects, materials, sizes, and colors. " +
"The \"colors\" field maps from CLEVR color names to RGB values; " +
"The \"sizes\" field maps from CLEVR size names to scalars used to " +
"rescale object models; the \"materials\" and \"shapes\" fields map " +
"from CLEVR material and shape names to .blend files in the " +
"--object_material_dir and --shape_dir directories respectively.")
parser.add_argument('--shape_dir', default='data/shapes',
help="Directory where .blend files for object models are stored")
parser.add_argument('--material_dir', default='data/materials',
help="Directory where .blend files for materials are stored")
parser.add_argument('--shape_color_combos_json', default=None,
help="Optional path to a JSON file mapping shape names to a list of " +
"allowed color names for that shape. This allows rendering images " +
"for CLEVR-CoGenT.")
# Settings for objects
parser.add_argument('--min_objects', default=5, type=int,
help="The minimum number of objects to place in each scene")
parser.add_argument('--max_objects', default=5, type=int,
help="The maximum number of objects to place in each scene")
parser.add_argument('--min_dist', default=0.25, type=float,
help="The minimum allowed distance between object centers")
parser.add_argument('--margin', default=0.4, type=float,
help="Along all cardinal directions (left, right, front, back), all " +
"objects will be at least this distance apart. This makes resolving " +
"spatial relationships slightly less ambiguous.")
parser.add_argument('--min_pixels_per_object', default=800, type=int,
help="All objects will have at least this many visible pixels in the " +
"final rendered images; this ensures that no objects are fully " +
"occluded by other objects.")
parser.add_argument('--max_retries', default=50, type=int,
help="The number of times to try placing an object before giving up and " +
"re-placing all objects in the scene.")
# Output settings
parser.add_argument('--start_idx', default=130, type=int,
help="The index at which to start for numbering rendered images. Setting " +
"this to non-zero values allows you to distribute rendering across " +
"multiple machines and recombine the results later.")
parser.add_argument('--num_images', default=5, type=int,
help="The number of images to render")
parser.add_argument('--filename_prefix', default='CLEVR',
help="This prefix will be prepended to the rendered images and JSON scenes")
parser.add_argument('--split', default='new',
help="Name of the split for which we are rendering. This will be added to " +
"the names of rendered images, and will also be stored in the JSON " +
"scene structure for each image.")
parser.add_argument('--output_image_dir', default='../output/images/',
help="The directory where output images will be stored. It will be " +
"created if it does not exist.")
parser.add_argument('--output_scene_dir', default='../output/scenes/',
help="The directory where output JSON scene structures will be stored. " +
"It will be created if it does not exist.")
parser.add_argument('--output_scene_file', default='../output/CLEVR_scenes.json',
help="Path to write a single JSON file containing all scene information")
parser.add_argument('--output_blend_dir', default='output/blendfiles',
help="The directory where blender scene files will be stored, if the " +
"user requested that these files be saved using the " +
"--save_blendfiles flag; in this case it will be created if it does " +
"not already exist.")
parser.add_argument('--save_blendfiles', type=int, default=0,
help="Setting --save_blendfiles 1 will cause the blender scene file for " +
"each generated image to be stored in the directory specified by " +
"the --output_blend_dir flag. These files are not saved by default " +
"because they take up ~5-10MB each.")
parser.add_argument('--version', default='1.0',
help="String to store in the \"version\" field of the generated JSON file")
parser.add_argument('--license',
default="Creative Commons Attribution (CC-BY 4.0)",
help="String to store in the \"license\" field of the generated JSON file")
parser.add_argument('--date', default=dt.today().strftime("%m/%d/%Y"),
help="String to store in the \"date\" field of the generated JSON file; " +
"defaults to today's date")
# Rendering options
parser.add_argument('--use_gpu', default=0, type=int,
help="Setting --use_gpu 1 enables GPU-accelerated rendering using CUDA. " +
"You must have an NVIDIA GPU with the CUDA toolkit installed for " +
"to work.")
parser.add_argument('--width', default=520, type=int,
help="The width (in pixels) for the rendered images")
parser.add_argument('--height', default=440, type=int,
help="The height (in pixels) for the rendered images")
parser.add_argument('--key_light_jitter', default=1.0, type=float,
help="The magnitude of random jitter to add to the key light position.")
parser.add_argument('--fill_light_jitter', default=1.0, type=float,
help="The magnitude of random jitter to add to the fill light position.")
parser.add_argument('--back_light_jitter', default=1.0, type=float,
help="The magnitude of random jitter to add to the back light position.")
parser.add_argument('--camera_jitter', default=0.5, type=float,
help="The magnitude of random jitter to add to the camera position")
parser.add_argument('--render_num_samples', default=512, type=int,
help="The number of samples to use when rendering. Larger values will " +
"result in nicer images but will cause rendering to take longer.")
parser.add_argument('--render_min_bounces', default=8, type=int,
help="The minimum number of bounces to use for rendering.")
parser.add_argument('--render_max_bounces', default=8, type=int,
help="The maximum number of bounces to use for rendering.")
parser.add_argument('--render_tile_size', default=256, type=int,
help="The tile size to use for rendering. This should not affect the " +
"quality of the rendered image but may affect the speed; CPU-based " +
"rendering may achieve better performance using smaller tile sizes " +
"while larger tile sizes may be optimal for GPU-based rendering.")
def main(args):
num_digits = 6
prefix = '%s_%s_' % (args.filename_prefix, args.split)
img_template = '%s%%0%dd.png' % (prefix, num_digits)
scene_template = '%s%%0%dd.json' % (prefix, num_digits)
blend_template = '%s%%0%dd.blend' % (prefix, num_digits)
img_template = os.path.join(args.output_image_dir, img_template)
scene_template = os.path.join(args.output_scene_dir, scene_template)
blend_template = os.path.join(args.output_blend_dir, blend_template)
if not os.path.isdir(args.output_image_dir):
os.makedirs(args.output_image_dir)
if not os.path.isdir(args.output_scene_dir):
os.makedirs(args.output_scene_dir)
if args.save_blendfiles == 1 and not os.path.isdir(args.output_blend_dir):
os.makedirs(args.output_blend_dir)
all_scene_paths = []
for i in range(args.num_images):
img_path = img_template % (i + args.start_idx)
scene_path = scene_template % (i + args.start_idx)
all_scene_paths.append(scene_path)
blend_path = None
if args.save_blendfiles == 1:
blend_path = blend_template % (i + args.start_idx)
num_objects = random.randint(args.min_objects, args.max_objects)
render_scene(args,
num_objects=num_objects,
output_index=(i + args.start_idx),
output_split=args.split,
output_image=img_path,
output_scene=scene_path,
output_blendfile=blend_path,
)
# After rendering all images, combine the JSON files for each scene into a
# single JSON file.
all_scenes = []
for scene_path in all_scene_paths:
with open(scene_path, 'r') as f:
all_scenes.append(json.load(f))
output = {
'info': {
'date': args.date,
'version': args.version,
'split': args.split,
'license': args.license,
},
'scenes': all_scenes
}
with open(args.output_scene_file, 'w') as f:
json.dump(output, f)
def render_scene(args,
num_objects=5,
output_index=0,
output_split='none',
output_image='render.png',
output_scene='render_json',
output_blendfile=None,
):
# Load the main blendfile
bpy.ops.wm.open_mainfile(filepath=args.base_scene_blendfile)
# Load materials
utils.load_materials(args.material_dir)
# Set render arguments so we can get pixel coordinates later.
# We use functionality specific to the CYCLES renderer so BLENDER_RENDER
# cannot be used.
render_args = bpy.context.scene.render
render_args.engine = "CYCLES"
render_args.filepath = output_image
render_args.resolution_x = args.width
render_args.resolution_y = args.height
render_args.resolution_percentage = 100
render_args.tile_x = args.render_tile_size
render_args.tile_y = args.render_tile_size
if args.use_gpu == 1:
# Blender changed the API for enabling CUDA at some point
if bpy.app.version < (2, 78, 0):
bpy.context.user_preferences.system.compute_device_type = 'CUDA'
bpy.context.user_preferences.system.compute_device = 'CUDA_0'
else:
cycles_prefs = bpy.context.user_preferences.addons['cycles'].preferences
cycles_prefs.compute_device_type = 'CUDA'
# Some CYCLES-specific stuff
bpy.data.worlds['World'].cycles.sample_as_light = True
bpy.context.scene.cycles.blur_glossy = 2.0
bpy.context.scene.cycles.samples = args.render_num_samples
bpy.context.scene.cycles.transparent_min_bounces = args.render_min_bounces
bpy.context.scene.cycles.transparent_max_bounces = args.render_max_bounces
if args.use_gpu == 1:
bpy.context.scene.cycles.device = 'GPU'
# This will give ground-truth information about the scene and its objects
scene_struct = {
'split': output_split,
'image_index': output_index,
'image_filename': os.path.basename(output_image),
'objects': [],
'directions': {},
}
# Put a plane on the ground so we can compute cardinal directions
bpy.ops.mesh.primitive_plane_add(radius=5)
plane = bpy.context.object
def rand(L):
return 2.0 * L * (random.random() - 0.5)
# Add random jitter to camera position
if args.camera_jitter > 0:
for i in range(3):
bpy.data.objects['Camera'].location[i] += rand(args.camera_jitter)
# Figure out the left, up, and behind directions along the plane and record
# them in the scene structure
camera = bpy.data.objects['Camera']
plane_normal = plane.data.vertices[0].normal
cam_behind = camera.matrix_world.to_quaternion() * Vector((0, 0, -1))
cam_left = camera.matrix_world.to_quaternion() * Vector((-1, 0, 0))
cam_up = camera.matrix_world.to_quaternion() * Vector((0, 1, 0))
plane_behind = (cam_behind - cam_behind.project(plane_normal)).normalized()
plane_left = (cam_left - cam_left.project(plane_normal)).normalized()
plane_up = cam_up.project(plane_normal).normalized()
# Delete the plane; we only used it for normals anyway. The base scene file
# contains the actual ground plane.
utils.delete_object(plane)
# Save all six axis-aligned directions in the scene struct
scene_struct['directions']['behind'] = tuple(plane_behind)
scene_struct['directions']['front'] = tuple(-plane_behind)
scene_struct['directions']['left'] = tuple(plane_left)
scene_struct['directions']['right'] = tuple(-plane_left)
scene_struct['directions']['above'] = tuple(plane_up)
scene_struct['directions']['below'] = tuple(-plane_up)
# Add random jitter to lamp positions
if args.key_light_jitter > 0:
for i in range(3):
bpy.data.objects['Lamp_Key'].location[i] += rand(args.key_light_jitter)
if args.back_light_jitter > 0:
for i in range(3):
bpy.data.objects['Lamp_Back'].location[i] += rand(args.back_light_jitter)
if args.fill_light_jitter > 0:
for i in range(3):
bpy.data.objects['Lamp_Fill'].location[i] += rand(args.fill_light_jitter)
# Now make some random objects
objects, blender_objects = add_random_objects(scene_struct, num_objects, args, camera)
# Render the scene and dump the scene data structure
scene_struct['objects'] = objects
scene_struct['relationships'], scene_struct['relationships_modified'] = compute_all_relationships(scene_struct)
while True:
try:
bpy.ops.render.render(write_still=True)
break
except Exception as e:
print(e)
with open(output_scene, 'w') as f:
json.dump(scene_struct, f, indent=2)
if output_blendfile is not None:
bpy.ops.wm.save_as_mainfile(filepath=output_blendfile)
def assign_mask_to_object(objects, mask_by_color):
for obj in objects:
coordinates = [obj["pixel_coords"][1] , obj["pixel_coords"][0]]
for color in mask_by_color:
if coordinates in mask_by_color[color]:
obj["pixel_mask"] = mask_by_color[color]
extracted_pixels= {}
pixel_colors = sorted(mask_by_color[color], key=lambda x: x[0])
for px in pixel_colors:
if px[0] in extracted_pixels:
if extracted_pixels[px[0]][1] < px[1] or extracted_pixels[px[0]][1] == -1:
extracted_pixels[px[0]][1] = px[1]
else:
extracted_pixels[px[0]] = [px[1], -1]
final_pixels = []
final_pixels_l = []
final_pixels_r = []
prev = -1
prev_r = -1
for ep in extracted_pixels.items():
if ep[1][0] != prev and ep[1][0] + 1 != prev and ep[1][0] - 1 != prev:
final_pixels_l.append([ep[0], ep[1][0]])
prev = ep[1][0]
if ep[1][1] != prev_r and ep[1][1] + 1 != prev_r and ep[1][1] - 1 != prev_r:
if ep[1][1] != -1:
final_pixels_r.append([ep[0], ep[1][1]])
prev_r = ep[1][1]
final_pixels_l = sorted(final_pixels_l, key=lambda x: x[0])
final_pixels_r = sorted(final_pixels_r, key=lambda x: x[0])
final_pixels.extend(final_pixels_l)
final_pixels_r.reverse()
final_pixels.extend(final_pixels_r)
obj["segmentation"] = final_pixels
print("new: ", obj["segmentation"] )
def add_random_objects(scene_struct, num_objects, args, camera):
"""
Add random objects to the current blender scene
"""
# Load the property file
with open(args.properties_json, 'r') as f:
properties = json.load(f)
color_name_to_rgba = {}
for name, rgb in properties['colors'].items():
rgba = [float(c) / 255.0 for c in rgb] + [1.0]
color_name_to_rgba[name] = rgba
material_mapping = [(v, k) for k, v in properties['materials'].items()]
object_mapping = [(v, k) for k, v in properties['shapes'].items()]
size_mapping = list(properties['sizes'].items())
shape_color_combos = None
if args.shape_color_combos_json is not None:
with open(args.shape_color_combos_json, 'r') as f:
shape_color_combos = list(json.load(f).items())
positions = []
objects = []
blender_objects = []
for i in range(num_objects):
# Choose a random size
size_name, r = random.choice(size_mapping)
# Try to place the object, ensuring that we don't intersect any existing
# objects and that we are more than the desired margin away from all existing
# objects along all cardinal directions.
num_tries = 0
while True:
# If we try and fail to place an object too many times, then delete all
# the objects in the scene and start over.
num_tries += 1
if num_tries > args.max_retries:
for obj in blender_objects:
utils.delete_object(obj)
return add_random_objects(scene_struct, num_objects, args, camera)
x = random.uniform(-3, 3)
y = random.uniform(-3, 3)
# Check to make sure the new object is further than min_dist from all
# other objects, and further than margin along the four cardinal directions
dists_good = True
margins_good = True
for (xx, yy, rr) in positions:
dx, dy = x - xx, y - yy
dist = math.sqrt(dx * dx + dy * dy)
if dist - r - rr < args.min_dist:
dists_good = False
break
for direction_name in ['left', 'right', 'front', 'behind']:
direction_vec = scene_struct['directions'][direction_name]
assert direction_vec[2] == 0
margin = dx * direction_vec[0] + dy * direction_vec[1]
if 0 < margin < args.margin:
print(margin, args.margin, direction_name)
print('BROKEN MARGIN!')
margins_good = False
break
if not margins_good:
break
if dists_good and margins_good:
break
# Choose random color and shape
if shape_color_combos is None:
obj_name, obj_name_out = random.choice(object_mapping)
color_name, rgba = random.choice(list(color_name_to_rgba.items()))
else:
obj_name_out, color_choices = random.choice(shape_color_combos)
color_name = random.choice(color_choices)
obj_name = [k for k, v in object_mapping if v == obj_name_out][0]
rgba = color_name_to_rgba[color_name]
# For cube, adjust the size a bit
if obj_name == 'Cube':
r /= math.sqrt(2)
# Choose random orientation for the object.
theta = 360.0 * random.random()
# Actually add the object to the scene
utils.add_object(args.shape_dir, obj_name, r, (x, y), theta=theta)
obj = bpy.context.object
blender_objects.append(obj)
positions.append((x, y, r))
# Attach a random material
mat_name, mat_name_out = random.choice(material_mapping)
utils.add_material(mat_name, Color=rgba)
# Record data about the object in the scene data structure
pixel_coords = utils.get_camera_coords(camera, obj.location)
objects.append({
'shape': obj_name_out,
'size': size_name,
'material': mat_name_out,
'3d_coords': tuple(obj.location),
'rotation': theta,
'pixel_coords': pixel_coords,
'color': color_name,
'segmentation': [], #pixels are stored after looking for visibility
'pixel_mask': [] # pixels are stored after looking for visibility
})
# Check that all objects are at least partially visible in the rendered image
all_visible, pixels_by_color = check_visibility(blender_objects, args.min_pixels_per_object, args)
assign_mask_to_object(objects, pixels_by_color)
if not all_visible:
# If any of the objects are fully occluded then start over; delete all
# objects from the scene and place them all again.
print('Some objects are occluded; replacing objects')
for obj in blender_objects:
utils.delete_object(obj)
return add_random_objects(scene_struct, num_objects, args, camera)
return objects, blender_objects
def compute_all_relationships(scene_struct, eps=0.2):
"""
Computes relationships between all pairs of objects in the scene.
Returns a dictionary mapping string relationship names to lists of lists of
integers, where output[rel][i] gives a list of object indices that have the
relationship rel with object i. For example if j is in output['left'][i] then
object j is left of object i.
"""
#edges (0,1) = [left, behind], (0,2) = [right, front]
objs_relations = {
"left": 0,
"right": 1,
"behind": 2,
"front": 3,
}
all_relationships = {}
all_relationships_original = {}
for name, direction_vec in scene_struct['directions'].items():
if name == 'above' or name == 'below': continue
all_relationships_original[name] = []
for i, obj1 in enumerate(scene_struct['objects']):
coords1 = obj1['3d_coords']
related = set()
for j, obj2 in enumerate(scene_struct['objects']):
if obj1 == obj2: continue
name_relation = str(i) + "-" + str(j)
if name_relation not in all_relationships:
all_relationships[name_relation] = []
coords2 = obj2['3d_coords']
diff = [coords2[k] - coords1[k] for k in [0, 1, 2]]
dot = sum(diff[k] * direction_vec[k] for k in [0, 1, 2])
if dot > eps:
related.add(j)
all_relationships[name_relation].append(objs_relations[name])
all_relationships_original[name].append(sorted(list(related)))
return all_relationships_original, all_relationships
def check_visibility(blender_objects, min_pixels_per_object, args):
"""
Check whether all objects in the scene have some minimum number of visible
pixels; to accomplish this we assign random (but distinct) colors to all
objects, and render using no lighting or shading or antialiasing; this
ensures that each object is just a solid uniform color. We can then count
the number of pixels of each color in the output image to check the visibility
of each object.
Returns True if all objects are visible and False otherwise.
"""
f, path = tempfile.mkstemp(suffix='.png')
object_colors = render_shadeless(blender_objects, path=path)
img = bpy.data.images.load(path)
p = list(img.pixels)
pixel_list = []
mask_by_color = {}
column = 0
row = args.height - 1
for i in range(0, len(p), 4):
temp = (p[i], p[i+1], p[i+2], p[i+3])
if column >= args.width:
row -= 1
column = 0
pixel_list.append(temp)
if temp in mask_by_color:
mask_by_color[temp].append([row, column])
else:
mask_by_color[temp] = [[row, column]]
column += 1
color_count = Counter(pixel_list)
os.remove(path)
if len(color_count) != len(blender_objects) + 1:
return False, mask_by_color
for _, count in color_count.most_common():
if count < min_pixels_per_object:
return False, mask_by_color
return True, mask_by_color
def render_shadeless(blender_objects, path='flat.png'):
"""
Render a version of the scene with shading disabled and unique materials
assigned to all objects, and return a set of all colors that should be in the
rendered image. The image itself is written to path. This is used to ensure
that all objects will be visible in the final rendered scene.
"""
render_args = bpy.context.scene.render
# Cache the render args we are about to clobber
old_filepath = render_args.filepath
old_engine = render_args.engine
old_use_antialiasing = render_args.use_antialiasing
# Override some render settings to have flat shading
render_args.filepath = path
render_args.engine = 'BLENDER_RENDER'
render_args.use_antialiasing = False
# Move the lights and ground to layer 2 so they don't render
utils.set_layer(bpy.data.objects['Lamp_Key'], 2)
utils.set_layer(bpy.data.objects['Lamp_Fill'], 2)
utils.set_layer(bpy.data.objects['Lamp_Back'], 2)
utils.set_layer(bpy.data.objects['Ground'], 2)
# Add random shadeless materials to all objects
object_colors = set()
old_materials = []
for i, obj in enumerate(blender_objects):
old_materials.append(obj.data.materials[0])
bpy.ops.material.new()
mat = bpy.data.materials['Material']
mat.name = 'Material_%d' % i
while True:
r, g, b = [random.random() for _ in range(3)]
if (r, g, b) not in object_colors: break
object_colors.add((r, g, b))
mat.diffuse_color = [r, g, b]
mat.use_shadeless = True
obj.data.materials[0] = mat
# Render the scene
bpy.ops.render.render(write_still=True)
# Undo the above; first restore the materials to objects
for mat, obj in zip(old_materials, blender_objects):
obj.data.materials[0] = mat
# Move the lights and ground back to layer 0
utils.set_layer(bpy.data.objects['Lamp_Key'], 0)
utils.set_layer(bpy.data.objects['Lamp_Fill'], 0)
utils.set_layer(bpy.data.objects['Lamp_Back'], 0)
utils.set_layer(bpy.data.objects['Ground'], 0)
# Set the render settings back to what they were
render_args.filepath = old_filepath
render_args.engine = old_engine
render_args.use_antialiasing = old_use_antialiasing
return object_colors
if __name__ == '__main__':
if INSIDE_BLENDER:
# Run normally
argv = utils.extract_args()
args = parser.parse_args(argv)
main(args)
elif '--help' in sys.argv or '-h' in sys.argv:
parser.print_help()
else:
print('This script is intended to be called from blender like this:')
print()
print('blender --background --python render_images.py -- [args]')
print()
print('You can also run as a standalone python script to view all')
print('arguments like this:')
print()
print('python render_images.py --help')
| 40.377273
| 113
| 0.693647
|
deb449183523148b00bdabf18e21714bbe3551c8
| 467
|
py
|
Python
|
src/courses/migrations/0006_auto_20200521_2038.py
|
GiomarOsorio/another-e-learning-platform
|
5cfc76420eb3466691f5187c915c179afb13199a
|
[
"MIT"
] | null | null | null |
src/courses/migrations/0006_auto_20200521_2038.py
|
GiomarOsorio/another-e-learning-platform
|
5cfc76420eb3466691f5187c915c179afb13199a
|
[
"MIT"
] | 8
|
2020-06-25T22:16:20.000Z
|
2022-03-12T00:39:27.000Z
|
src/courses/migrations/0006_auto_20200521_2038.py
|
GiomarOsorio/another-e-learning-platform
|
5cfc76420eb3466691f5187c915c179afb13199a
|
[
"MIT"
] | null | null | null |
# Generated by Django 3.0.6 on 2020-05-21 20:38
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('courses', '0005_auto_20200521_2038'),
]
operations = [
migrations.AlterField(
model_name='module',
name='segments',
field=models.IntegerField(help_text='number of segments in a module', verbose_name='number of segments in a module'),
),
]
| 24.578947
| 129
| 0.631692
|
53f8d8f0a03c0ae367fc673431366935c0bf9f32
| 5,360
|
py
|
Python
|
AIFP/mae_toPdbqt.py
|
jeah-z/IFP-RNN
|
83cb3f0f75907227d682e8980b335b17db2c2ab1
|
[
"MIT"
] | null | null | null |
AIFP/mae_toPdbqt.py
|
jeah-z/IFP-RNN
|
83cb3f0f75907227d682e8980b335b17db2c2ab1
|
[
"MIT"
] | null | null | null |
AIFP/mae_toPdbqt.py
|
jeah-z/IFP-RNN
|
83cb3f0f75907227d682e8980b335b17db2c2ab1
|
[
"MIT"
] | null | null | null |
try:
from openbabel import pybel
except:
import pybel
import pandas as pd
import argparse
from functools import partial
from multiprocessing import Pool
from tqdm.auto import tqdm
import os
from pathlib import Path
import rdkit
from rdkit import Chem
from pebble import concurrent, ProcessPool
from concurrent.futures import TimeoutError
import glob
glide = "/mnt/home/zhangjie/Bin/Schrodinger2017/glide"
structconvert = "/mnt/home/zhangjie/Bin/Schrodinger2017/utilities/structconvert"
prepwizard = "/mnt/home/zhangjie/Bin/Schrodinger2017/utilities/prepwizard"
glide_sort = "/mnt/home/zhangjie/Bin/Schrodinger2017/utilities/glide_sort"
mol2convert = "/mnt/home/zhangjie/Bin/Schrodinger2017/utilities/mol2convert"
prepare_ligand4 = '/mnt/home/zhangjie/Bin/MGLTools-1.5.7/MGLToolsPckgs/AutoDockTools/Utilities24/prepare_ligand4.py'
def find_files(suffix):
'''find all the files with specific suffix.
'''
files = os.listdir('./')
file_list = []
for file in files:
file_sp = file.split('_')
if len(file_sp) < 2:
print(file+'\t was omitted!')
continue
elif file_sp[-1] == suffix:
file_list.append(file)
print(f"{len(file_list)} files have been detected!")
return file_list
def combine_pdbqtReport(pdbqt_file, report_file):
'''This script fetch docking score from the report file and write the dockind score to the specific pose of the pdbqt file.
'''
with open(report_file, 'r') as report_file_f:
parse_mark = 0
dockScore_list = []
for line in report_file_f.readlines():
line_sp = line.strip().split()
if parse_mark > 0 and len(line_sp) == 0:
break
if len(line_sp) > 0:
if line_sp[0] == '====':
parse_mark += 1
continue
if len(line_sp) == 19 and parse_mark > 0:
dockScore_list.append([line_sp[0], line_sp[3], line_sp[1]])
pdbqt_newFile = pdbqt_file.replace(".pdbqt", "_out.pdbqt")
pdbqt_newFile_f = open(pdbqt_newFile, 'w')
with open(pdbqt_file, 'r') as pdbqt_file_f:
if len(dockScore_list) == 1:
glide_score = dockScore_list.pop(0)
pdbqt_newFile_f.write(
f'REMARK VINA RESULT: {glide_score[1]} 0.000 0.000\n')
for line in pdbqt_file_f.readlines():
pdbqt_newFile_f.write(line)
else:
for line in pdbqt_file_f.readlines():
line_sp = line.strip().split()
if len(line_sp) > 0:
if line_sp[0] == 'MODEL' and len(line_sp) == 2:
pdbqt_newFile_f.write(line)
glide_score = dockScore_list.pop(0)
assert int(glide_score[0]) == int(line_sp[1])
pdbqt_newFile_f.write(
f'REMARK VINA RESULT: {glide_score[1]} 0.000 0.000\n')
else:
pdbqt_newFile_f.write(line)
assert len(
dockScore_list) == 0 # '''This is to make sure no glide score was left! '''
pdbqt_newFile_f.close()
def mae_toPdbqt(imaegz, pdbqt_dir):
isimple_name = imaegz.replace('_pv.maegz', '')
if os.path.exists(f'../{pdbqt_dir}/{isimple_name}_out.pdbqt'):
print(f"{imaegz} have been processed before!")
return 0
# if maegz_files.index(imaegz) > 10: # This is to accelerate the test speed!
# break
os.system(
f'{glide_sort} -r ../{pdbqt_dir}/{isimple_name}.rept {imaegz} -o ../{pdbqt_dir}/{isimple_name}.mae')
os.system(
f'{mol2convert} -n 2: -imae ../{pdbqt_dir}/{isimple_name}.mae -omol2 ../{pdbqt_dir}/{isimple_name}.mol2')
os.system(
f'babel -imol2 ../{pdbqt_dir}/{isimple_name}.mol2 -opdbqt ../{pdbqt_dir}/{isimple_name}.pdbqt')
combine_pdbqtReport(
f'../{pdbqt_dir}/{isimple_name}.pdbqt', f'../{pdbqt_dir}/{isimple_name}.rept')
# clean the unnecessary files
for isufix in ['rept', 'mol2', 'mae', 'pdbqt']:
os.system(
f"rm ../{pdbqt_dir}/{isimple_name}.{isufix}")
def main(args):
os.chdir(f"{args.path}")
maegz_files = find_files('pv.maegz')
pdbqt_dir = args.path.split("/")[-1]+'_pdbqt'
os.system(f"mkdir ../{pdbqt_dir}")
with ProcessPool(max_workers=args.n_jobs) as pool:
print("RUNING POOL!!!!")
for imaegz in maegz_files:
future = pool.schedule(
mae_toPdbqt, args=[imaegz, pdbqt_dir], timeout=600)
'''Further clean the pdbqt folder, some files cannot be removed for a unkown reason!'''
os.chdir(f"../{pdbqt_dir}")
files = os.listdir('./')
for ifile in files:
ifile_sp = ifile.split(".")
if "_" not in ifile and ifile_sp[-1] in ['rept', 'mol2', 'mae', 'pdbqt']:
os.system(f'rm {ifile}')
def get_parser():
parser = argparse.ArgumentParser()
parser.add_argument("--path", help="The directory of the docking results (maegz format).", type=str,
default='')
parser.add_argument("--n_jobs", type=int,
help="cpu cores", default=1)
args = parser.parse_args()
return args
if __name__ == "__main__":
# test section
args = get_parser()
main(args)
| 37.746479
| 127
| 0.604291
|
65ef20c3cd8fa5aeb228287be92b16208bfaf4c2
| 8,462
|
py
|
Python
|
tests/brownfield/separate_file_example/test_brownfield_app.py
|
nutanixdev/calm-dsl
|
90e1c583d7b9ac905cdfb3e2ad27f9f930e69831
|
[
"Apache-2.0"
] | null | null | null |
tests/brownfield/separate_file_example/test_brownfield_app.py
|
nutanixdev/calm-dsl
|
90e1c583d7b9ac905cdfb3e2ad27f9f930e69831
|
[
"Apache-2.0"
] | null | null | null |
tests/brownfield/separate_file_example/test_brownfield_app.py
|
nutanixdev/calm-dsl
|
90e1c583d7b9ac905cdfb3e2ad27f9f930e69831
|
[
"Apache-2.0"
] | null | null | null |
import uuid
import time
import json
import traceback
import pytest
import sys
from click.testing import CliRunner
from calm.dsl.cli import main as cli
from calm.dsl.cli.constants import APPLICATION
from calm.dsl.tools import make_file_dir
from calm.dsl.log import get_logging_handle
LOG = get_logging_handle(__name__)
DSL_BP_FILEPATH = "tests/brownfield/separate_file_example/blueprint.py"
DSL_BP_BD_FILEPATH = "tests/brownfield/separate_file_example/brownfield.py"
LOCAL_VM_IP_PATH = "tests/brownfield/separate_file_example/.local/vm_ip"
NON_BUSY_APP_STATES = [
APPLICATION.STATES.STOPPED,
APPLICATION.STATES.RUNNING,
APPLICATION.STATES.ERROR,
]
NON_BUSY_APP_DELETE_STATES = [APPLICATION.STATES.ERROR, APPLICATION.STATES.DELETED]
@pytest.mark.slow
class TestBrownFieldCommands:
def setup_method(self):
"""Method to instantiate to created_bp_list and created_app_list"""
self.created_bp_list = []
self.created_app_list = []
def teardown_method(self):
"""Method to delete creates bps and apps during tests"""
for bp_name in self.created_bp_list:
LOG.info("Deleting Blueprint {}".format(bp_name))
runner = CliRunner()
result = runner.invoke(cli, ["delete", "bp", bp_name])
assert result.exit_code == 0
for app_name in self.created_app_list:
LOG.info("Deleting app {}".format(app_name))
self._delete_app(app_name)
self.created_app_list = []
self.created_bp_list = []
def _wait_for_non_busy_state(self, app_name):
runner = CliRunner()
non_busy_statuses = [
"Status: {}".format(state) for state in NON_BUSY_APP_STATES
]
result = runner.invoke(cli, ["describe", "app", app_name])
while not any([state_str in result.output for state_str in non_busy_statuses]):
time.sleep(5)
result = runner.invoke(cli, ["describe", "app", app_name])
def _wait_for_app_delete_busy_state(self, app_name):
runner = CliRunner()
non_busy_statuses = [
"Status: {}".format(state) for state in NON_BUSY_APP_DELETE_STATES
]
result = runner.invoke(cli, ["describe", "app", app_name])
while not any([state_str in result.output for state_str in non_busy_statuses]):
time.sleep(5)
result = runner.invoke(cli, ["describe", "app", app_name])
def _delete_app(self, app_name):
runner = CliRunner()
self._wait_for_non_busy_state(app_name)
LOG.info("Deleting App {} ".format(app_name))
result = runner.invoke(cli, ["delete", "app", app_name])
assert result.exit_code == 0
self._wait_for_app_delete_busy_state(app_name=app_name)
LOG.info("App {} deleted successfully".format(app_name))
def _create_bp(self, name):
runner = CliRunner()
LOG.info("Creating Bp {}".format(name))
result = runner.invoke(
cli,
[
"create",
"bp",
"--file={}".format(DSL_BP_FILEPATH),
"--name={}".format(name),
"--description='Test DSL Blueprint; to delete'",
],
)
LOG.debug("Response: {}".format(result.output))
assert result.exit_code == 0
def test_app_vm_in_brownfield_bp(self):
"""
Steps:
1. Create Blueprint
2. Create App
3. Soft Delete app and extract vm-ip from it
4. Create Brownfield Application using that vm-ip
5. Delete brownfield application
"""
runner = CliRunner()
# Create blueprint
bp_name = "Blueprint{}".format(str(uuid.uuid4())[:10])
self._create_bp(bp_name)
self.created_bp_list.append(bp_name)
# Create application
app_name = "App{}".format(str(uuid.uuid4())[:10])
LOG.info("Creating App {}".format(app_name))
result = runner.invoke(
cli,
[
"launch",
"bp",
bp_name,
"--app_name={}".format(app_name),
"--ignore_runtime_variables",
],
)
if result.exit_code:
LOG.error(result.output)
pytest.fail("Creation of app {} failed".format(app_name))
# Wait for app creation completion
self._wait_for_non_busy_state(app_name)
LOG.info("Application {} created successfully".format(app_name))
LOG.info("Extracting vm ip from the app")
result = runner.invoke(cli, ["describe", "app", app_name, "--out=json"])
if result.exit_code:
LOG.error(result.output)
pytest.fail("Describe of app {} failed".format(app_name))
# Extracting vm+ip from the app_json
app_json = json.loads(result.output)
app_state = app_json["status"]["state"]
if app_state != APPLICATION.STATES.RUNNING:
LOG.error("App went to {} state".format(app_state))
sys.exit(-1)
vm_ip = app_json["status"]["resources"]["deployment_list"][0][
"substrate_configuration"
]["element_list"][0]["address"]
LOG.info("Soft deleting the app {}".format(app_name))
result = runner.invoke(cli, ["delete", "app", app_name, "--soft"])
if result.exit_code:
LOG.error(result.output)
pytest.fail("Deletion of app {} failed".format(app_name))
# Wait for app deletion completion
self._wait_for_app_delete_busy_state(app_name)
LOG.info("Soft Delete of app {} completed".format(app_name))
# Writing vm_ip to local directory file
LOG.info("Writing vm_ip {} to file '{}'".format(vm_ip, LOCAL_VM_IP_PATH))
make_file_dir(LOCAL_VM_IP_PATH)
with open(LOCAL_VM_IP_PATH, "w") as f:
f.write(vm_ip)
# Creating brownfield blueprint
app_name = "BrownfieldApplication{}".format(str(uuid.uuid4())[:10])
LOG.info("Creating Brownfield Application {}".format(app_name))
result = runner.invoke(
cli,
[
"create",
"app",
"--file={}".format(DSL_BP_FILEPATH),
"--brownfield_deployments={}".format(DSL_BP_BD_FILEPATH),
"--name={}".format(app_name),
],
)
if result.exit_code:
cli_res_dict = {"Output": result.output, "Exception": str(result.exception)}
LOG.debug(
"Cli Response: {}".format(
json.dumps(cli_res_dict, indent=4, separators=(",", ": "))
)
)
LOG.debug(
"Traceback: \n{}".format(
"".join(traceback.format_tb(result.exc_info[2]))
)
)
pytest.fail("Brownfield App creation failed")
self._wait_for_non_busy_state(app_name)
LOG.info("Brownfield App {} created successfully".format(app_name))
self.created_app_list.append(app_name)
@pytest.mark.parametrize(
"vm_type", ["AHV_VM", "AWS_VM", "AZURE_VM", "GCP_VM", "VMWARE_VM"]
)
@pytest.mark.parametrize("project", ["default"])
def test_get_brownfield_vms(self, vm_type, project):
"""
Test get command on brownfield vms
Note: Test will fail for provider = VMWARE_VM for version less than 2.9.8.1 and 3.0.0 (https://jira.nutanix.com/browse/CALM-18635)
"""
runner = CliRunner()
LOG.info("Testing 'calm get brownfield vms --type {}' command".format(vm_type))
result = runner.invoke(
cli,
[
"get",
"brownfield",
"vms",
"--project={}".format(project),
"--type={}".format(vm_type),
],
)
if result.exit_code:
cli_res_dict = {"Output": result.output, "Exception": str(result.exception)}
LOG.debug(
"Cli Response: {}".format(
json.dumps(cli_res_dict, indent=4, separators=(",", ": "))
)
)
LOG.debug(
"Traceback: \n{}".format(
"".join(traceback.format_tb(result.exc_info[2]))
)
)
pytest.fail("Brownfield Vm Get failed")
LOG.info("Success")
| 34.966942
| 138
| 0.578468
|
128656cc124500c88ac1af8a83d29668f6abc791
| 275
|
py
|
Python
|
lib/plugins/create/templates/kubeless-python/handler.py
|
ajesse11x/serverless
|
15333c223563e36d66469950c57c4f9ae68866a4
|
[
"MIT"
] | 39,871
|
2015-12-08T08:23:40.000Z
|
2022-03-31T23:42:35.000Z
|
lib/plugins/create/templates/kubeless-python/handler.py
|
ajesse11x/serverless
|
15333c223563e36d66469950c57c4f9ae68866a4
|
[
"MIT"
] | 8,862
|
2015-12-08T07:59:58.000Z
|
2022-03-31T23:22:49.000Z
|
lib/plugins/create/templates/kubeless-python/handler.py
|
ajesse11x/serverless
|
15333c223563e36d66469950c57c4f9ae68866a4
|
[
"MIT"
] | 6,151
|
2015-12-08T09:17:10.000Z
|
2022-03-31T06:58:23.000Z
|
import json
def hello(event, context):
body = {
"message": "Go Serverless v1.0! Your function executed successfully!",
"input": event['data']
}
response = {
"statusCode": 200,
"body": json.dumps(body)
}
return response
| 17.1875
| 78
| 0.56
|
7c3c045fdd4cc364310ac9cf38876c99f3c85b4c
| 909
|
py
|
Python
|
traffic/map_test.py
|
markraemer/mH-PriSe
|
1555c4c7e6457c3bb5bce3b6dae9c514ed7fc3d3
|
[
"MIT"
] | 1
|
2016-12-02T06:50:44.000Z
|
2016-12-02T06:50:44.000Z
|
traffic/map_test.py
|
markraemer/mH-PriSe
|
1555c4c7e6457c3bb5bce3b6dae9c514ed7fc3d3
|
[
"MIT"
] | null | null | null |
traffic/map_test.py
|
markraemer/mH-PriSe
|
1555c4c7e6457c3bb5bce3b6dae9c514ed7fc3d3
|
[
"MIT"
] | null | null | null |
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt
# create new figure, axes instances.
fig=plt.figure()
ax=fig.add_axes([0.1,0.1,0.8,0.8])
# setup mercator map projection.
m = Basemap(llcrnrlon=-100.,llcrnrlat=20.,urcrnrlon=20.,urcrnrlat=60.,\
rsphere=(6378137.00,6356752.3142),\
resolution='l',projection='merc',\
lat_0=40.,lon_0=-20.,lat_ts=20.)
# nylat, nylon are lat/lon of New York
nylat = 40.78; nylon = -73.98
# lonlat, lonlon are lat/lon of London.
lonlat = 51.53; lonlon = 0.08
# draw great circle route between NY and London
m.drawgreatcircle(nylon,nylat,lonlon,lonlat,linewidth=2,color='b')
m.drawcoastlines()
m.fillcontinents()
# draw parallels
m.drawparallels(np.arange(10,90,20))
# draw meridians
m.drawmeridians(np.arange(-180,180,30),labels=[1,1,0,1])
ax.set_title('Great Circle from New York to London')
plt.show()
| 36.36
| 71
| 0.715072
|
d0c5f685dcaac9b50ce4b0e4e26f497bbfd8a66f
| 4,756
|
py
|
Python
|
tests/python/gaia-ui-tests/gaiatest/apps/fmradio/app.py
|
NickProgramm/gaia
|
975a35c0f5010df341e96d6c5ec60217f5347412
|
[
"Apache-2.0"
] | 3
|
2016-08-17T08:52:51.000Z
|
2020-03-29T04:56:45.000Z
|
tests/python/gaia-ui-tests/gaiatest/apps/fmradio/app.py
|
NickProgramm/gaia
|
975a35c0f5010df341e96d6c5ec60217f5347412
|
[
"Apache-2.0"
] | 1
|
2017-02-21T21:36:12.000Z
|
2017-02-21T21:36:30.000Z
|
tests/python/gaia-ui-tests/gaiatest/apps/fmradio/app.py
|
NickProgramm/gaia
|
975a35c0f5010df341e96d6c5ec60217f5347412
|
[
"Apache-2.0"
] | 1
|
2019-03-03T01:31:58.000Z
|
2019-03-03T01:31:58.000Z
|
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
import re
from marionette_driver import expected, By, Wait
from marionette_driver.marionette import Actions
from gaiatest.apps.base import Base
from gaiatest.apps.base import PageRegion
class FmRadio(Base):
name = 'FM Radio'
manifest_url = '{}fm{}/manifest.webapp'.format(Base.DEFAULT_PROTOCOL,Base.DEFAULT_APP_HOSTNAME)
_power_button_locator = (By.ID, 'power-switch')
_favorite_list_locator = (By.CSS_SELECTOR, 'div.fav-list-item')
_frequency_display_locator = (By.ID, 'frequency')
_frequency_dialer_locator = (By.ID, 'dialer-bar')
_favorite_button_locator = (By.ID, 'bookmark-button')
_next_button_locator = (By.ID, 'frequency-op-seekup')
_prev_button_locator = (By.ID, 'frequency-op-seekdown')
_airplane_mode_title_locator = (By.CSS_SELECTOR, 'div[data-l10n-id="airplaneModeHeader"]')
_airplane_mode_text_locator = (By.CSS_SELECTOR, 'div[data-l10n-id="airplaneModeMsg"]')
def launch(self, airplane_mode=False):
Base.launch(self)
power = Wait(self.marionette).until(
expected.element_present(*self._power_button_locator))
if not airplane_mode:
Wait(self.marionette).until(lambda m: power.get_attribute('data-enabled') == 'true')
@property
def airplane_warning_title(self):
return self.marionette.find_element(*self._airplane_mode_title_locator).text
@property
def airplane_warning_text(self):
return self.marionette.find_element(*self._airplane_mode_text_locator).text
def flick_frequency_dialer_up(self):
dialer = self.marionette.find_element(*self._frequency_dialer_locator)
dialer_x_center = int(dialer.size['width'] / 2)
dialer_y_center = int(dialer.size['height'] / 2)
Actions(self.marionette).flick(dialer, dialer_x_center, dialer_y_center, 0, 800, 800).perform()
def tap_next(self):
frequency = Wait(self.marionette).until(
expected.element_present(*self._frequency_display_locator))
current = frequency.text
self.marionette.find_element(*self._next_button_locator).tap()
Wait(self.marionette).until(lambda m: frequency.text != current)
def tap_previous(self):
frequency = Wait(self.marionette).until(
expected.element_present(*self._frequency_display_locator))
current = frequency.text
self.marionette.find_element(*self._prev_button_locator).tap()
Wait(self.marionette).until(lambda m: frequency.text != current)
def tap_power_button(self):
self.marionette.find_element(*self._power_button_locator).tap()
def wait_for_radio_off(self):
power = Wait(self.marionette).until(
expected.element_present(*self._power_button_locator))
Wait(self.marionette).until(
lambda m: not power.get_attribute('data-enabled') == 'true')
def tap_add_favorite(self):
current = len(self.favorite_channels)
self.marionette.find_element(*self._favorite_button_locator).tap()
Wait(self.marionette).until(
lambda m: len(self.favorite_channels) == current + 1)
@property
def is_power_button_on(self):
return self.marionette.find_element(*self._power_button_locator).get_attribute('data-enabled') == 'true'
@property
def frequency(self):
raw_frequency = self.marionette.find_element(*self._frequency_display_locator).text
return float(self._crop_trailing_mhz_and_invisible_characters(raw_frequency))
@staticmethod
def _crop_trailing_mhz_and_invisible_characters(raw_frequency):
match = re.search(r'\d+\.\d', raw_frequency)
frequency = match.group()
return frequency
@property
def favorite_channels(self):
return [self.FavoriteChannel(self.marionette, channel) for channel in self.marionette.find_elements(*self._favorite_list_locator)]
class FavoriteChannel(PageRegion):
_remove_locator = (By.CSS_SELECTOR, 'div.fav-list-remove-button')
_frequency_locator = (By.CSS_SELECTOR, 'div.fav-list-frequency')
@property
def text(self):
raw_frequency = self.root_element.find_element(*self._frequency_locator).text
return float(FmRadio._crop_trailing_mhz_and_invisible_characters(raw_frequency))
def remove(self):
frequency = self.marionette.find_element(*self._frequency_locator)
self.root_element.find_element(*self._remove_locator).tap()
Wait(self.marionette).until(expected.element_not_displayed(frequency))
| 42.464286
| 138
| 0.712994
|
c49109e855bff388a92b443d8e55515a32857be0
| 13,160
|
py
|
Python
|
app/config.py
|
THIS-IS-NOT-A-BACKUP/app
|
0f5e722a3510b9163bc50d1b457ac2580ffedd1a
|
[
"MIT"
] | null | null | null |
app/config.py
|
THIS-IS-NOT-A-BACKUP/app
|
0f5e722a3510b9163bc50d1b457ac2580ffedd1a
|
[
"MIT"
] | null | null | null |
app/config.py
|
THIS-IS-NOT-A-BACKUP/app
|
0f5e722a3510b9163bc50d1b457ac2580ffedd1a
|
[
"MIT"
] | null | null | null |
import os
import random
import socket
import string
import subprocess
from ast import literal_eval
from typing import Callable
from urllib.parse import urlparse
from dotenv import load_dotenv
SHA1 = subprocess.getoutput("git rev-parse HEAD")
ROOT_DIR = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
def get_abs_path(file_path: str):
"""append ROOT_DIR for relative path"""
# Already absolute path
if file_path.startswith("/"):
return file_path
else:
return os.path.join(ROOT_DIR, file_path)
def sl_getenv(env_var: str, default_factory: Callable = None):
"""
Get env value, convert into Python object
Args:
env_var (str): env var, example: SL_DB
default_factory: returns value if this env var is not set.
"""
value = os.getenv(env_var)
if value is None:
return default_factory()
return literal_eval(value)
config_file = os.environ.get("CONFIG")
if config_file:
config_file = get_abs_path(config_file)
print("load config file", config_file)
load_dotenv(get_abs_path(config_file))
else:
load_dotenv()
COLOR_LOG = "COLOR_LOG" in os.environ
# Allow user to have 1 year of premium: set the expiration_date to 1 year more
PROMO_CODE = "SIMPLEISBETTER"
# Server url
URL = os.environ["URL"]
print(">>> URL:", URL)
# Calculate RP_ID for WebAuthn
RP_ID = urlparse(URL).hostname
SENTRY_DSN = os.environ.get("SENTRY_DSN")
# can use another sentry project for the front-end to avoid noises
SENTRY_FRONT_END_DSN = os.environ.get("SENTRY_FRONT_END_DSN") or SENTRY_DSN
# Email related settings
NOT_SEND_EMAIL = "NOT_SEND_EMAIL" in os.environ
EMAIL_DOMAIN = os.environ["EMAIL_DOMAIN"].lower()
SUPPORT_EMAIL = os.environ["SUPPORT_EMAIL"]
SUPPORT_NAME = os.environ.get("SUPPORT_NAME", "Son from SimpleLogin")
ADMIN_EMAIL = os.environ.get("ADMIN_EMAIL")
# VERP: mail_from set to BOUNCE_PREFIX + email_log.id + BOUNCE_SUFFIX
BOUNCE_PREFIX = os.environ.get("BOUNCE_PREFIX") or "bounce+"
BOUNCE_SUFFIX = os.environ.get("BOUNCE_SUFFIX") or f"+@{EMAIL_DOMAIN}"
BOUNCE_EMAIL = BOUNCE_PREFIX + "{}" + BOUNCE_SUFFIX
# Used for VERP during reply phase. It's similar to BOUNCE_PREFIX.
# It's needed when sending emails from custom domain to respect DMARC.
# BOUNCE_PREFIX_FOR_REPLY_PHASE should never be used in any existing alias
# and can't be used for creating a new alias on custom domain
# Note BOUNCE_PREFIX_FOR_REPLY_PHASE doesn't have the trailing plus sign (+) as BOUNCE_PREFIX
BOUNCE_PREFIX_FOR_REPLY_PHASE = (
os.environ.get("BOUNCE_PREFIX_FOR_REPLY_PHASE") or "bounce_reply"
)
# VERP for transactional email: mail_from set to BOUNCE_PREFIX + email_log.id + BOUNCE_SUFFIX
TRANSACTIONAL_BOUNCE_PREFIX = (
os.environ.get("TRANSACTIONAL_BOUNCE_PREFIX") or "transactional+"
)
TRANSACTIONAL_BOUNCE_SUFFIX = (
os.environ.get("TRANSACTIONAL_BOUNCE_SUFFIX") or f"+@{EMAIL_DOMAIN}"
)
TRANSACTIONAL_BOUNCE_EMAIL = (
TRANSACTIONAL_BOUNCE_PREFIX + "{}" + TRANSACTIONAL_BOUNCE_SUFFIX
)
try:
MAX_NB_EMAIL_FREE_PLAN = int(os.environ["MAX_NB_EMAIL_FREE_PLAN"])
except Exception:
print("MAX_NB_EMAIL_FREE_PLAN is not set, use 5 as default value")
MAX_NB_EMAIL_FREE_PLAN = 5
# maximum number of directory a premium user can create
MAX_NB_DIRECTORY = 50
ENFORCE_SPF = "ENFORCE_SPF" in os.environ
# allow to override postfix server locally
POSTFIX_SERVER = os.environ.get("POSTFIX_SERVER", "240.0.0.1")
DISABLE_REGISTRATION = "DISABLE_REGISTRATION" in os.environ
# allow using a different postfix port, useful when developing locally
POSTFIX_PORT = 25
if "POSTFIX_PORT" in os.environ:
POSTFIX_PORT = int(os.environ["POSTFIX_PORT"])
# postfix port to use during the forward phase
POSTFIX_PORT_FORWARD = POSTFIX_PORT
if "POSTFIX_PORT_FORWARD" in os.environ:
POSTFIX_PORT_FORWARD = int(os.environ["POSTFIX_PORT_FORWARD"])
# Use port 587 instead of 25 when sending emails through Postfix
# Useful when calling Postfix from an external network
POSTFIX_SUBMISSION_TLS = "POSTFIX_SUBMISSION_TLS" in os.environ
# ["domain1.com", "domain2.com"]
OTHER_ALIAS_DOMAINS = sl_getenv("OTHER_ALIAS_DOMAINS", list)
OTHER_ALIAS_DOMAINS = [d.lower().strip() for d in OTHER_ALIAS_DOMAINS]
# List of domains user can use to create alias
if "ALIAS_DOMAINS" in os.environ:
ALIAS_DOMAINS = sl_getenv("ALIAS_DOMAINS") # ["domain1.com", "domain2.com"]
else:
ALIAS_DOMAINS = OTHER_ALIAS_DOMAINS + [EMAIL_DOMAIN]
ALIAS_DOMAINS = [d.lower().strip() for d in ALIAS_DOMAINS]
# ["domain1.com", "domain2.com"]
PREMIUM_ALIAS_DOMAINS = sl_getenv("PREMIUM_ALIAS_DOMAINS", list)
PREMIUM_ALIAS_DOMAINS = [d.lower().strip() for d in PREMIUM_ALIAS_DOMAINS]
# the alias domain used when creating the first alias for user
FIRST_ALIAS_DOMAIN = os.environ.get("FIRST_ALIAS_DOMAIN") or EMAIL_DOMAIN
# list of (priority, email server)
# e.g. [(10, "mx1.hostname."), (10, "mx2.hostname.")]
EMAIL_SERVERS_WITH_PRIORITY = sl_getenv("EMAIL_SERVERS_WITH_PRIORITY")
# these emails are ignored when computing stats
IGNORED_EMAILS = sl_getenv("IGNORED_EMAILS", list)
# disable the alias suffix, i.e. the ".random_word" part
DISABLE_ALIAS_SUFFIX = "DISABLE_ALIAS_SUFFIX" in os.environ
# the email address that receives all unsubscription request
UNSUBSCRIBER = os.environ.get("UNSUBSCRIBER")
DKIM_SELECTOR = b"dkim"
DKIM_HEADERS = [b"from", b"to"]
DKIM_PRIVATE_KEY = None
if "DKIM_PRIVATE_KEY_PATH" in os.environ:
DKIM_PRIVATE_KEY_PATH = get_abs_path(os.environ["DKIM_PRIVATE_KEY_PATH"])
with open(DKIM_PRIVATE_KEY_PATH) as f:
DKIM_PRIVATE_KEY = f.read()
# Database
DB_URI = os.environ["DB_URI"]
# Flask secret
FLASK_SECRET = os.environ["FLASK_SECRET"]
SESSION_COOKIE_NAME = "slapp"
MAILBOX_SECRET = FLASK_SECRET + "mailbox"
CUSTOM_ALIAS_SECRET = FLASK_SECRET + "custom_alias"
# AWS
AWS_REGION = os.environ.get("AWS_REGION") or "eu-west-3"
BUCKET = os.environ.get("BUCKET")
AWS_ACCESS_KEY_ID = os.environ.get("AWS_ACCESS_KEY_ID")
AWS_SECRET_ACCESS_KEY = os.environ.get("AWS_SECRET_ACCESS_KEY")
# Paddle
try:
PADDLE_VENDOR_ID = int(os.environ["PADDLE_VENDOR_ID"])
PADDLE_MONTHLY_PRODUCT_ID = int(os.environ["PADDLE_MONTHLY_PRODUCT_ID"])
PADDLE_YEARLY_PRODUCT_ID = int(os.environ["PADDLE_YEARLY_PRODUCT_ID"])
except (KeyError, ValueError):
print("Paddle param not set")
PADDLE_VENDOR_ID = -1
PADDLE_MONTHLY_PRODUCT_ID = -1
PADDLE_YEARLY_PRODUCT_ID = -1
# Other Paddle product IDS
PADDLE_MONTHLY_PRODUCT_IDS = sl_getenv("PADDLE_MONTHLY_PRODUCT_IDS", list)
PADDLE_MONTHLY_PRODUCT_IDS.append(PADDLE_MONTHLY_PRODUCT_ID)
PADDLE_YEARLY_PRODUCT_IDS = sl_getenv("PADDLE_YEARLY_PRODUCT_IDS", list)
PADDLE_YEARLY_PRODUCT_IDS.append(PADDLE_YEARLY_PRODUCT_ID)
PADDLE_PUBLIC_KEY_PATH = get_abs_path(
os.environ.get("PADDLE_PUBLIC_KEY_PATH", "local_data/paddle.key.pub")
)
PADDLE_AUTH_CODE = os.environ.get("PADDLE_AUTH_CODE")
# OpenID keys, used to sign id_token
OPENID_PRIVATE_KEY_PATH = get_abs_path(
os.environ.get("OPENID_PRIVATE_KEY_PATH", "local_data/jwtRS256.key")
)
OPENID_PUBLIC_KEY_PATH = get_abs_path(
os.environ.get("OPENID_PUBLIC_KEY_PATH", "local_data/jwtRS256.key.pub")
)
# Used to generate random email
WORDS_FILE_PATH = get_abs_path(
os.environ.get("WORDS_FILE_PATH", "local_data/words_alpha.txt")
)
# Used to generate random email
if os.environ.get("GNUPGHOME"):
GNUPGHOME = get_abs_path(os.environ.get("GNUPGHOME"))
else:
letters = string.ascii_lowercase
random_dir_name = "".join(random.choice(letters) for _ in range(20))
GNUPGHOME = f"/tmp/{random_dir_name}"
if not os.path.exists(GNUPGHOME):
os.mkdir(GNUPGHOME, mode=0o700)
print("WARNING: Use a temp directory for GNUPGHOME", GNUPGHOME)
# Github, Google, Facebook client id and secrets
GITHUB_CLIENT_ID = os.environ.get("GITHUB_CLIENT_ID")
GITHUB_CLIENT_SECRET = os.environ.get("GITHUB_CLIENT_SECRET")
GOOGLE_CLIENT_ID = os.environ.get("GOOGLE_CLIENT_ID")
GOOGLE_CLIENT_SECRET = os.environ.get("GOOGLE_CLIENT_SECRET")
FACEBOOK_CLIENT_ID = os.environ.get("FACEBOOK_CLIENT_ID")
FACEBOOK_CLIENT_SECRET = os.environ.get("FACEBOOK_CLIENT_SECRET")
# in seconds
AVATAR_URL_EXPIRATION = 3600 * 24 * 7 # 1h*24h/d*7d=1week
# session key
MFA_USER_ID = "mfa_user_id"
FLASK_PROFILER_PATH = os.environ.get("FLASK_PROFILER_PATH")
FLASK_PROFILER_PASSWORD = os.environ.get("FLASK_PROFILER_PASSWORD")
# Job names
JOB_ONBOARDING_1 = "onboarding-1"
JOB_ONBOARDING_2 = "onboarding-2"
JOB_ONBOARDING_3 = "onboarding-3"
JOB_ONBOARDING_4 = "onboarding-4"
JOB_BATCH_IMPORT = "batch-import"
JOB_DELETE_ACCOUNT = "delete-account"
# for pagination
PAGE_LIMIT = 20
# Upload to static/upload instead of s3
LOCAL_FILE_UPLOAD = "LOCAL_FILE_UPLOAD" in os.environ
UPLOAD_DIR = None
# Rate Limiting
# nb max of activity (forward/reply) an alias can have during 1 min
MAX_ACTIVITY_DURING_MINUTE_PER_ALIAS = 10
# nb max of activity (forward/reply) a mailbox can have during 1 min
MAX_ACTIVITY_DURING_MINUTE_PER_MAILBOX = 15
if LOCAL_FILE_UPLOAD:
print("Upload files to local dir")
UPLOAD_DIR = os.path.join(ROOT_DIR, "static/upload")
if not os.path.exists(UPLOAD_DIR):
print("Create upload dir")
os.makedirs(UPLOAD_DIR)
LANDING_PAGE_URL = os.environ.get("LANDING_PAGE_URL") or "https://simplelogin.io"
STATUS_PAGE_URL = os.environ.get("STATUS_PAGE_URL") or "https://status.simplelogin.io"
# Loading PGP keys when mail_handler runs. To be used locally when init_app is not called.
LOAD_PGP_EMAIL_HANDLER = "LOAD_PGP_EMAIL_HANDLER" in os.environ
DISPOSABLE_FILE_PATH = get_abs_path(
os.environ.get("DISPOSABLE_FILE_PATH", "local_data/local_disposable_domains.txt")
)
with open(get_abs_path(DISPOSABLE_FILE_PATH), "r") as f:
DISPOSABLE_EMAIL_DOMAINS = f.readlines()
DISPOSABLE_EMAIL_DOMAINS = [d.strip().lower() for d in DISPOSABLE_EMAIL_DOMAINS]
DISPOSABLE_EMAIL_DOMAINS = [
d for d in DISPOSABLE_EMAIL_DOMAINS if not d.startswith("#")
]
# Used when querying info on Apple API
# for iOS App
APPLE_API_SECRET = os.environ.get("APPLE_API_SECRET")
# for Mac App
MACAPP_APPLE_API_SECRET = os.environ.get("MACAPP_APPLE_API_SECRET")
# <<<<< ALERT EMAIL >>>>
# maximal number of alerts that can be sent to the same email in 24h
MAX_ALERT_24H = 4
# When a reverse-alias receives emails from un unknown mailbox
ALERT_REVERSE_ALIAS_UNKNOWN_MAILBOX = "reverse_alias_unknown_mailbox"
# When a forwarding email is bounced
ALERT_BOUNCE_EMAIL = "bounce"
ALERT_BOUNCE_EMAIL_REPLY_PHASE = "bounce-when-reply"
# When a forwarding email is detected as spam
ALERT_SPAM_EMAIL = "spam"
# When an email is sent from a mailbox to an alias - a cycle
ALERT_SEND_EMAIL_CYCLE = "cycle"
ALERT_SPF = "spf"
# when a mailbox is also an alias
# happens when user adds a mailbox with their domain
# then later adds this domain into SimpleLogin
ALERT_MAILBOX_IS_ALIAS = "mailbox_is_alias"
AlERT_WRONG_MX_RECORD_CUSTOM_DOMAIN = "custom_domain_mx_record_issue"
# alert when a new alias is about to be created on a disabled directory
ALERT_DIRECTORY_DISABLED_ALIAS_CREATION = "alert_directory_disabled_alias_creation"
# <<<<< END ALERT EMAIL >>>>
# Disable onboarding emails
DISABLE_ONBOARDING = "DISABLE_ONBOARDING" in os.environ
HCAPTCHA_SECRET = os.environ.get("HCAPTCHA_SECRET")
HCAPTCHA_SITEKEY = os.environ.get("HCAPTCHA_SITEKEY")
PLAUSIBLE_HOST = os.environ.get("PLAUSIBLE_HOST")
PLAUSIBLE_DOMAIN = os.environ.get("PLAUSIBLE_DOMAIN")
# server host
HOST = socket.gethostname()
SPAMASSASSIN_HOST = os.environ.get("SPAMASSASSIN_HOST")
# by default use a tolerant score
if "MAX_SPAM_SCORE" in os.environ:
MAX_SPAM_SCORE = float(os.environ["MAX_SPAM_SCORE"])
else:
MAX_SPAM_SCORE = 5.5
# use a more restrictive score when replying
if "MAX_REPLY_PHASE_SPAM_SCORE" in os.environ:
MAX_REPLY_PHASE_SPAM_SCORE = float(os.environ["MAX_REPLY_PHASE_SPAM_SCORE"])
else:
MAX_REPLY_PHASE_SPAM_SCORE = 5
PGP_SENDER_PRIVATE_KEY = None
PGP_SENDER_PRIVATE_KEY_PATH = os.environ.get("PGP_SENDER_PRIVATE_KEY_PATH")
if PGP_SENDER_PRIVATE_KEY_PATH:
with open(get_abs_path(PGP_SENDER_PRIVATE_KEY_PATH)) as f:
PGP_SENDER_PRIVATE_KEY = f.read()
# the signer address that signs outgoing encrypted emails
PGP_SIGNER = os.environ.get("PGP_SIGNER")
# emails that have empty From address is sent from this special reverse-alias
NOREPLY = os.environ.get("NOREPLY", f"noreply@{EMAIL_DOMAIN}")
COINBASE_WEBHOOK_SECRET = os.environ.get("COINBASE_WEBHOOK_SECRET")
COINBASE_CHECKOUT_ID = os.environ.get("COINBASE_CHECKOUT_ID")
COINBASE_API_KEY = os.environ.get("COINBASE_API_KEY")
try:
COINBASE_YEARLY_PRICE = float(os.environ["COINBASE_YEARLY_PRICE"])
except Exception:
COINBASE_YEARLY_PRICE = 30.00
ALIAS_LIMIT = os.environ.get("ALIAS_LIMIT") or "100/day;50/hour;5/minute"
ENABLE_SPAM_ASSASSIN = "ENABLE_SPAM_ASSASSIN" in os.environ
ALIAS_RANDOM_SUFFIX_LENGTH = int(os.environ.get("ALIAS_RAND_SUFFIX_LENGTH", 5))
try:
HIBP_SCAN_INTERVAL_DAYS = int(os.environ.get("HIBP_SCAN_INTERVAL_DAYS"))
except Exception:
HIBP_SCAN_INTERVAL_DAYS = 7
HIBP_API_KEYS = sl_getenv("HIBP_API_KEYS", list) or []
NEWRELIC_CONFIG_PATH = os.environ.get("NEWRELIC_CONFIG_PATH")
| 33.232323
| 93
| 0.771657
|
7e8b568001a30c3f17599b6738d0bbd60c7cb807
| 8,068
|
py
|
Python
|
mayan/apps/quotas/quota_backends.py
|
PatrickMugayaJoel/Mayan-EDMS
|
1a2b4d4fa784a68498f82e0735958dc116b60d46
|
[
"Apache-2.0"
] | null | null | null |
mayan/apps/quotas/quota_backends.py
|
PatrickMugayaJoel/Mayan-EDMS
|
1a2b4d4fa784a68498f82e0735958dc116b60d46
|
[
"Apache-2.0"
] | null | null | null |
mayan/apps/quotas/quota_backends.py
|
PatrickMugayaJoel/Mayan-EDMS
|
1a2b4d4fa784a68498f82e0735958dc116b60d46
|
[
"Apache-2.0"
] | 1
|
2021-09-01T14:07:47.000Z
|
2021-09-01T14:07:47.000Z
|
import types
from django.contrib.auth import get_user_model
from django.contrib.contenttypes.models import ContentType
from django.db.models import IntegerField
from django.db.models.functions import Cast
from django.template.defaultfilters import filesizeformat
from django.utils.translation import ugettext_lazy as _
from actstream.models import Action
from mayan.apps.common.signals import signal_mayan_pre_save
from mayan.apps.documents.events import event_document_created
from mayan.apps.documents.models import Document, DocumentFile
from mayan.apps.user_management.querysets import get_user_queryset
from .classes import QuotaBackend
from .exceptions import QuotaExceeded
from .mixins import DocumentTypesQuotaMixin, GroupsUsersQuotaMixin
def hook_factory_document_check_quota(klass):
def hook_check_quota(**kwargs):
# Fake Document to be able to reuse the .process() method
# for pre check.
fake_document_instance = types.SimpleNamespace(pk=None)
final_kwargs = kwargs['kwargs'].copy()
final_kwargs['instance'] = fake_document_instance
for quota in klass.get_instances().filter(enabled=True):
backend_instance = quota.get_backend_instance()
backend_instance.process(**final_kwargs)
return hook_check_quota
def hook_factory_document_file_check_quota(klass):
def hook_check_quota(**kwargs):
# Pass the real parent document or create a fake one.
if 'document' in kwargs['kwargs']:
document = kwargs['kwargs']['document']
else:
document = types.SimpleNamespace(
document_type=kwargs['kwargs']['document_type']
)
# Fake DocumentFile to be able to reuse the
# .process() method for pre check.
shared_uploaded_file = kwargs['kwargs']['shared_uploaded_file']
if shared_uploaded_file:
fake_document_instance = types.SimpleNamespace(
file=kwargs['kwargs']['shared_uploaded_file'].file,
document=document,
pk=None
)
final_kwargs = kwargs['kwargs'].copy()
final_kwargs['instance'] = fake_document_instance
for quota in klass.get_instances().filter(enabled=True):
backend_instance = quota.get_backend_instance()
backend_instance.process(**final_kwargs)
return hook_check_quota
class DocumentCountQuota(
GroupsUsersQuotaMixin, DocumentTypesQuotaMixin, QuotaBackend
):
error_message = _('Document count quota exceeded.')
field_order = ('documents_limit',)
fields = {
'documents_limit': {
'label': _('Documents limit'),
'class': 'django.forms.IntegerField',
'help_text': _(
'Maximum number of documents.'
)
},
}
label = _('Document count limit')
sender = Document
signal = signal_mayan_pre_save
@classmethod
def _initialize(cls):
Document.register_pre_create_hook(
func=hook_factory_document_check_quota(klass=cls)
)
def __init__(
self, document_type_all, document_type_ids, documents_limit,
group_ids, user_all, user_ids
):
self.document_type_all = document_type_all
self.document_type_ids = document_type_ids
self.documents_limit = documents_limit
self.group_ids = group_ids
self.user_all = user_all
self.user_ids = user_ids
def _allowed(self):
return self.documents_limit
def _allowed_filter_display(self):
return _('document count: %(document_count)s') % {
'document_count': self._allowed()
}
def _get_user_document_count(self, user):
action_queryset = Action.objects.annotate(
target_object_id_int=Cast(
'target_object_id', output_field=IntegerField()
),
)
action_filter_kwargs = {
'verb': event_document_created.id
}
document_filter_kwargs = {}
if not self.document_type_all:
document_filter_kwargs.update(
{
'document_type_id__in': self._get_document_types().values(
'pk'
),
}
)
if user:
# Admins are always excluded.
if user.is_superuser or user.is_staff:
return 0
if not self.user_all:
users = self._get_users() | get_user_queryset().filter(
groups__in=self._get_groups()
)
if not users.filter(pk=user.pk).exists():
# User is not in the restricted list of users and groups.
return 0
else:
content_type = ContentType.objects.get_for_model(
model=get_user_model()
)
action_filter_kwargs.update(
{
'actor_object_id': user.pk,
'actor_content_type': content_type,
}
)
action_queryset = action_queryset.filter(**action_filter_kwargs)
document_filter_kwargs.update(
{
'pk__in': action_queryset.values('target_object_id_int')
}
)
return Document.objects.filter(**document_filter_kwargs).count()
def process(self, **kwargs):
# Only for new documents.
if not kwargs['instance'].pk:
if self._get_user_document_count(user=kwargs.get('user')) >= self._allowed():
raise QuotaExceeded(
_('Document count quota exceeded.')
)
class DocumentSizeQuota(
GroupsUsersQuotaMixin, DocumentTypesQuotaMixin, QuotaBackend
):
field_order = ('document_size_limit',)
fields = {
'document_size_limit': {
'label': _('Document size limit'),
'class': 'django.forms.FloatField',
'help_text': _('Maximum document size in megabytes (MB).')
}
}
label = _('Document size limit')
sender = DocumentFile
signal = signal_mayan_pre_save
@classmethod
def _initialize(cls):
DocumentFile.register_pre_create_hook(
func=hook_factory_document_file_check_quota(klass=cls)
)
def __init__(
self, document_size_limit, document_type_all, document_type_ids,
group_ids, user_all, user_ids
):
self.document_size_limit = document_size_limit
self.document_type_all = document_type_all
self.document_type_ids = document_type_ids
self.group_ids = group_ids
self.user_all = user_all
self.user_ids = user_ids
def _allowed(self):
return self.document_size_limit * 1024 * 1024
def _allowed_filter_display(self):
return _('document size: %(formatted_file_size)s') % {
'formatted_file_size': filesizeformat(self._allowed())
}
def process(self, **kwargs):
if not kwargs['instance'].pk:
if kwargs['instance'].file.size >= self._allowed():
if self.document_type_all or self._get_document_types().filter(pk=kwargs['instance'].document.document_type.pk).exists():
# Don't asume there is always a user in the signal.
# Non interactive uploads might not include a user.
if kwargs['user']:
if kwargs['user'].is_superuser or kwargs['user'].is_staff:
return
users = self._get_users() | get_user_queryset().filter(
groups__in=self._get_groups()
)
if self.user_all or kwargs['user'] and users.filter(pk=kwargs['user'].pk).exists():
raise QuotaExceeded(
_('Document size quota exceeded.')
)
| 34.775862
| 137
| 0.606718
|
59dae854bdabb689b85af13f3c0de6705ef8786a
| 22,836
|
py
|
Python
|
src/external/simplexml.py
|
ojimary/titus
|
ac53bcde5e0f32ab1f8b982b5c2bb7d89c9917a4
|
[
"Condor-1.1"
] | 108
|
2015-05-29T07:50:26.000Z
|
2022-03-04T06:10:55.000Z
|
src/external/simplexml.py
|
ROBERT-MCDOWELL/p2p-sip
|
3ba6d39327694f662c3e4c9c943f9bfb4abb9a29
|
[
"Condor-1.1"
] | 5
|
2015-07-16T16:33:21.000Z
|
2020-05-30T23:13:20.000Z
|
src/external/simplexml.py
|
ROBERT-MCDOWELL/p2p-sip
|
3ba6d39327694f662c3e4c9c943f9bfb4abb9a29
|
[
"Condor-1.1"
] | 69
|
2015-07-20T16:05:04.000Z
|
2022-03-31T15:41:03.000Z
|
# Copyright (c) 2008, Kundan Singh. All rights reserved. See LICENSING for details.
'''
Simple XML handling. The existing xml.dom.minidom is too Java'ish, so simplexml is used to allow easier syntax
when processing XML. The basic API ideas are inspired from ActionScript's XML and XMLList data types.
XML is the main class which can be used as follows:
An XML string can be parsed using the constructor.
>>> a1 = XML(u'<people xmlns="private" type="contacts">start<contact>Kundan Singh</contact>end</people>')
>>> print a1
<people xmlns="private" type="contacts">start<contact>Kundan Singh</contact>end</people>
The XML element has attributes such as xmlns, tag and children. The XML attributes can be accessed using the
special attribute named '_' in the XML object. The XML attribute can also be read-accessed as a regular
Python attribute on the XML element assuming there is no conflict and the attribute name is simple.
>>> print a1.xmlns, a1.tag
private people
>>> print a1.type
contacts
>>> print a1.type == a1._['type'] == a1._.type == 'contacts'
True
>>> a1._.source='yahoo'; print a1
<people xmlns="private" source="yahoo" type="contacts">start<contact>Kundan Singh</contact>end</people>
>>> del a1._['source']; print a1
<people xmlns="private" type="contacts">start<contact>Kundan Singh</contact>end</people>
The children can be accessed using various ways. The children attribute returns the XMLList of children
which includes both elements and data objects.
>>> x1 = a1.children
>>> print len(x1)
3
An XMLList is derived from list, and each element contains individual XML element or data item.
>>> print x1
start<contact>Kundan Singh</contact>end
>>> print list(x1)
[u'start', <contact>Kundan Singh</contact>, u'end']
>>> print ', '.join(map(unicode, x1))
start, <contact>Kundan Singh</contact>, end
>>> print XML('<contact>Kundan Singh</contact>') in x1, u'start' in x1
True False
You can use the list semantics to access the children. The list methods such as append, extend,
insert, pop, reverse, and operators such as del, slicing and indexing. The only catch is that
the slicing operation returns a regular list, instead of XMLList.
>>> x1.append(XML('<contact/>')); print x1
start<contact>Kundan Singh</contact>end<contact />
>>> x1.extend(['final']); print x1
start<contact>Kundan Singh</contact>end<contact />final
>>> x1.insert(1, 'begin'); print x1
startbegin<contact>Kundan Singh</contact>end<contact />final
>>> y = x1.pop(); print y, x1
final startbegin<contact>Kundan Singh</contact>end<contact />
>>> x1.reverse(); print x1
<contact />end<contact>Kundan Singh</contact>beginstart
>>> del x1[3]; print x1
<contact />end<contact>Kundan Singh</contact>start
>>> x1[1], x1[3] = x1[3], x1[1]; print x1
<contact />start<contact>Kundan Singh</contact>end
>>> print x1[0], isinstance(x1[0], XML), type(x1[1])
<contact /> True <type 'unicode'>
>>> print x1[0:2], type(x1) == XMLList, type(x1[0:2])
[<contact />, u'start'] True <type 'list'>
>>> print x1[:]
[<contact />, u'start', <contact>Kundan Singh</contact>, u'end']
You can also use the mapping semantics to access the children. It allows various filtering and
search method as well. There are some special index defined such as x1['*'] to return all the
elements with no data items of this XMLList, and x1('name') to return all the children elements
of the elements in XMLList with tag as 'name', and x1() to return all the children elements
of the elements in XMLList. Additionally the cdata and elems attributes fetch only the concatenated
CDATA string or list of elements, respectively.
>>> type(x1.contact) == XMLList
True
>>> print x1.contact
<contact /><contact>Kundan Singh</contact>
>>> print x1.contact == x1["contact"]
True
>>> print x1.contact == x1[lambda x: x.tag == 'contact']
True
>>> x = XML('<first><second><third a="1"/><third a="2"/><third2/></second></first>')
>>> x2 = x.children
>>> print x2("third")
<third a="1" /><third a="2" />
>>> print x2(lambda x: x.tag == 'third') == x2('third')
True
>>> print x2()
<third a="1" /><third a="2" /><third2 />
>>> print x2['*']
<second><third a="1" /><third a="2" /><third2 /></second>
>>> print x()('third')
<third a="1" /><third a="2" />
>>> print x() == x.children["*"]
True
>>> print 'contact' in x1, 'info' in x1
True False
>>> x1['info'] = XML('<info>contact list</info>'); print x1
<contact />start<contact>Kundan Singh</contact>end<info>contact list</info>
>>> del x1['info']; print x1
<contact />start<contact>Kundan Singh</contact>end
>>> x1['info'] = 'contact list'; print x1 # has same effect as earlier explict XML assignment
<contact />start<contact>Kundan Singh</contact>end<info>contact list</info>
>>> x1['info'] = None; print x1; # same effect as del x1['info']
<contact />start<contact>Kundan Singh</contact>end
>>> x1['contact'] = XMLList([XML('<contact>Kundan Singh</contact>'), XML('<contact>Mamta Singh</contact>')]); print x1
<contact>Kundan Singh</contact><contact>Mamta Singh</contact>startend
>>> x1['info'] = XMLList([XML('<info>contact list</info>')]); print x1
<contact>Kundan Singh</contact><contact>Mamta Singh</contact>startend<info>contact list</info>
>>> print x1.keys()
set([u'info', u'contact'])
>>> print map(unicode, x1.iterkeys())
[u'info', u'contact']
>>> print x1.values()
[<contact>Kundan Singh</contact>, <contact>Mamta Singh</contact>, u'start', u'end', <info>contact list</info>]
>>> print map(unicode, x1.itervalues())
[u'<contact>Kundan Singh</contact>', u'<contact>Mamta Singh</contact>', u'start', u'end', u'<info>contact list</info>']
>>> print x1.items()
[(u'contact', <contact>Kundan Singh</contact>), (u'contact', <contact>Mamta Singh</contact>), ('#text', u'start'), ('#text', u'end'), (u'info', <info>contact list</info>)]
>>> print map(unicode, x1.iteritems())
[u"(u'contact', <contact>Kundan Singh</contact>)", u"(u'contact', <contact>Mamta Singh</contact>)", u"('#text', u'start')", u"('#text', u'end')", u"(u'info', <info>contact list</info>)"]
>>> x2 = x1.copy(); print type(x2) == XMLList, x2 == x1
True True
>>> x2.clear(); print len(x2), len(x1)
0 5
>>> print x1.cdata
Kundan SinghMamta Singhstartendcontact list
>>> print x1.elems
[<contact>Kundan Singh</contact>, <contact>Mamta Singh</contact>, <info>contact list</info>]
>>> del x1[1:]; print x1
<contact>Kundan Singh</contact>
Additionally, the XMLList defines certain arithmetic style operations to manipulate the
data or list.
>>> print x1 + XML('<desc/>')
<contact>Kundan Singh</contact><desc />
>>> print x1 + x1
<contact>Kundan Singh</contact><contact>Kundan Singh</contact>
>>> print x1 + 'something'
<contact>Kundan Singh</contact>something
>>> x1 += XML('<desc/>'); print x1 # append tag
<contact>Kundan Singh</contact><desc />
>>> x1 |= XML('<desc/>'); x1 |= XML('<desc type="1"/>'); x1 |= XML('<info/>'); print x1 # overwrite or append tag
<contact>Kundan Singh</contact><desc type="1" /><info />
>>> x1 -= XML('<info/>'); print x1 # remove if tag is present
<contact>Kundan Singh</contact><desc type="1" />
>>> x1 ^= XML('<desc/>'); x1 ^= XML('<info/>'); print x1; # append if tag not already present, else don't overwrite
<contact>Kundan Singh</contact><desc type="1" /><info />
>>> x1 &= XML('<desc/>'); x1 &= XML('<info2/>'); print x1 # overwrite if tag already present, else don't append
<contact>Kundan Singh</contact><info /><desc />
The XML namespaces are handled using the xmlns property. The namespaces attribute of the top-level XML element
contains the list of namespace URI and their prefixes. The xmlns attribute is just the namespace URI. The namespace
declaration might get moved from parent to child or vice-versa during various XML operations.
>>> x2 = XML('<a:node xmlns:a="private" xmlns:b="public"><a:child/><b:child/></a:node>'); print x2
<node xmlns="private"><child /><child xmlns="public" /></node>
'''
from xml.parsers import expat
escape =lambda x: x.replace('&', '&').replace('<', '<').replace('>', '>').replace('"', '"') # escape & < > " with appropriate XML entities
def ustr(value):
'''Converts 'value' to utf-8 string using value's __str__ or unicode.
>>> print type (ustr(u'kundan')) == unicode, ustr(u'kundan') == ustr('kundan')
True True
'''
if isinstance(value, unicode): return value
try: r = value.__str__()
except AttributeError: r = str(value)
return r if isinstance(r, unicode) else unicode(r, 'utf-8')
class parser(object):
'''A parser using expat to parse XML string into XML object. Use the xml attribute to extract the parsed XML.'''
def __init__(self, value=None, node=None):
self._parser = expat.ParserCreate(namespace_separator=' ')
for n in ('StartElementHandler', 'EndElementHandler', 'CharacterDataHandler', 'StartNamespaceDeclHandler'):
exec 'self._parser.%s = self._%s'%(n, n) # TODO: should avoid calling exec
self._current, self._depth, self._root = None, 0, node
self.namespaces={'http://www.w3.org/XML/1998/namespace': 'xml:'}
self.xmlns='http://www.w3.org/XML/1998/namespace'
if value:
self._parser.Parse(value, 1)
if self._depth != 0: raise ValueError, 'Invalid XML value ' + value
def update(self, value): self._parser.Parse(value, 0) # add more data to be parsed
@property
def xml(self): return self._root # return the root XML node after parsing
def _StartElementHandler(self, tag, attrs):
xmlns, tag = tag.split(' ') if tag.find(' ') >= 0 else ('', tag)
for n, v in filter(lambda x: x[0].rfind(' ') >= 0, attrs.items()):
uri,ignore,prefix = n.partition(' ')
attrs[self.namespaces[uri]+prefix] = v; del attrs[n]
if self._depth == 0 and self._root is None: self._root = XML(tag=tag, xmlns=xmlns, attrs=attrs) # create new root element
elif self._depth == 0: XML.__init__(self._root, tag=tag, xmlns=xmlns, attrs=attrs) # re-invoke the constructor
else: self._current.children.append(XML(tag=tag, xmlns=xmlns, parent=self._current, attrs=attrs)) # append child element
self._current = self._root if self._depth == 0 else self._current.children[-1] # current node is root or last child
self._depth += 1
def _EndElementHandler(self, tag):
self._depth -= 1
if self._depth > 0: self._current = self._current.parent
def _CharacterDataHandler(self, data):
if not self._current: return
if self._current.children and isinstance(self._current.children[-1], XML): self._current.children.append(data)
elif self._current.children: self._current.children[-1] += data
else: self._current.children.append(data)
def _StartNamespaceDeclHandler(self, prefix, uri):
if prefix: self.namespaces[uri] = prefix + ':'
else: self.xmlns = uri
class XMLList(list):
'''List of XML or CDATA elements. Used for children in XML.'''
def __init__(self, values=[]): list.__init__(self, values)
def __repr__(self): return u''.join([str(x) for x in self])
# private functions
def _filter(self, func, recurse=False): # filter the elements in the sub-tree
if recurse:
result = XMLList()
for x in filter(lambda y: isinstance(y, XML), self):
if func(x): result.append(x)
res = x.children._filter(func, recurse)
if res: result.extend(res)
return result
else: return XMLList(filter(lambda x: isinstance(x, XML) and func(x), self))
def _delete(self, func, recurse=False): # delete the elements in the sub-tree
result = XMLList()
remove = list()
for x in filter(lambda y: isinstance(y, XML), self):
if func(x): result.append(x); remove.append(x)
elif recurse:
res = x.children._delete(func, recurse)
if res: result.extend(res)
for x in remove: self.remove(x)
return result
def _update(self, tag, values):
remove = list()
pos = -1
for i in xrange(0, len(self)):
x = self[i] if isinstance(self[i], XML) and self[i].tag == tag else None
if x is not None:
if pos < 0: pos = i
remove.append(x)
for x in remove: self.remove(x)
if pos < 0: pos = len(self)
if isinstance(values, XMLList): self[pos:pos] = values[:]
elif isinstance(values, XML): self[pos:pos] = [values]
elif isinstance(values, (str, unicode)): self[pos:pos] = [XML('<%s>%s</%s>'%(tag, values, tag))]
elif values is None or not values: pass # do nothing, already deleted
else: raise ValueError, 'Invalid argument in XMLList._update ' + str(type(values))
# attribute access for elements, and call semantics for accessing or filtering child elements
def __getattr__(self, name): return self._filter(lambda x: x.tag == name)
def __call__(self, name=None):
f = (lambda x: x.tag == name or not name) if not callable(name) else name
return XMLList(sum([[y for y in x.children._filter(f)] for x in self["*"]], []))
# container access for elements as well as filtering elements
def __contains__(self, item): # item is either XML, or tag name, or lambda function to test
if isinstance(item, XML): return list.__contains__(self, item)
elif isinstance(item, (str, unicode)): return self._filter(lambda x: x.tag == item)
elif callable(item): return self._filter(item)
else: return False
def __getitem__(self, key): # key is either int, or "*", or tag name, or lambda function to test
if isinstance(key, int): return list.__getitem__(self, key)
elif key == u'*': return self._filter(lambda x: True)
elif isinstance(key, (str, unicode)): return self._filter(lambda x: x.tag == key)
elif callable(key): return self._filter(key)
else: return None
def __setitem__(self, key, value): # key is either int, or tag name.
if isinstance(key, int): list.__setitem__(self, key, value); result = value
elif key == u'*': self[:] = value if isinstance(value, XMLList) else [value]; result = self
elif isinstance(key, (str, unicode)): self._update(key, value); result = value
return result
def __delitem__(self, key): # key is same as that in __getitem__
if isinstance(key, int): list.__delitem__(self, key); return None
elif key == u'*': result, self[:] = self[:], []; return result # make it empty
elif isinstance(key, (str, unicode)): return self._delete(lambda x: x.tag == key)
elif callable(key): return self._delete(key)
else: return None
# mapping related methods similar to container access for elements
def keys(self): return set([x.tag for x in filter(lambda y: isinstance(y, XML), self)]) # returns a set of all tags
def values(self): return self[:] # return all the XML and data elements in this list
def items(self): return [(x.tag, x) if isinstance(x, XML) else ('#text', x) for x in self] # return list of tuples of (tag, XML)
def has_key(self, key): # return true if the tag exists
for y in filter(lambda x: isinstance(x, XML), self):
if y.tag == key: return True
return False
def get(self, key, default=None): return self._filter(lambda x: x.tag == key) or default # return the value for the key, or default
def clear(self): self[:] = [] # clear the list
def iterkeys(self): return iter(self.keys()) # iterator for keys
def itervalues(self): return iter(self) # iterator for values
def iteritems(self): # iterator for items
for x in self: yield (x.tag if isinstance(x, XML) else '#text', x)
def copy(self): return XMLList(self[:])
def update(self, arg): self[:] = arg # update self with the given list of XML
#not implemented: setdefault(), pop(), popitem()
@property
def cdata(self): return u''.join([(x.cdata if isinstance(x, XML) else x) for x in self])
@property
def elems(self): return filter(lambda x: isinstance(x, XML), self)
# arithmetic manipulation or operations
def __add__(self, other): # XMLList + XML, XMLList + XMLList, XMLList + list, XMLList + object
if isinstance(other, list): return XMLList(self[:] + other)
else: return XMLList(self[:] + [other if isinstance(other, XML) else unicode(other)])
def __radd__(self, other):
if isinstance(other, list): return XMLList(other + self[:])
else: return XMLList([other if isinstance(other, XML) else unicode(other)] + self[:])
def __iadd__(self, other): # XMLList += XML, XMLList += XMLList, XMLList += list, XMLList += object
if isinstance(other, list): self.extend(other)
else: self.append(other if isinstance(other, XML) else unicode(other))
return self
def __isub__(self, other): # XMLList -= XML, XMLList -= XMLList, XMLList -= list, XMLList -= object
if not isinstance(other, list): other = [other]
self[:] = filter(lambda x: x not in other, self)
return self
def __ixor__(self, other): # XMLList ^= XML, XMLList ^= XMLList (add only if tag is not found, else don't overwrite)
if not isinstance(other, list): other = [other]
self.extend(filter(lambda x: x.tag not in self.keys(), other))
return self
def __ior__(self, other): # XMLList |= XML, XMLList |= XMLList (overwrite if tag is found else append)
if not isinstance(other, list): other = [other]
overwrite = filter(lambda x: x.tag in self.keys(), other) # that needs to be overwritten
overtags = map(lambda x: x.tag, overwrite)
add = filter(lambda x: x.tag not in self.keys(), other) # that needs to be added
self[:] = filter(lambda x: x.tag not in overtags, self) # remove these for overwritting
self.extend(overwrite + add) # append the overwritten and added elements
return self
def __iand__(self, other): # XMLList &= XML, XMLList &= XMLList (overwrite only if tag is found, else don't append)
if not isinstance(other, list): other = [other]
overwrite = filter(lambda x: x.tag in self.keys(), other) # that needs to be overwritten
overtags = map(lambda x: x.tag, overwrite)
self[:] = filter(lambda x: x.tag not in overtags, self) # remove these for overwriting
self.extend(overwrite) # append the overwritten elements
return self
class XML(object):
'''A single XML element. Can be constructed either using raw string or individual fields.'''
def __init__(self, value=None, tag='element', xmlns='', attrs={}, children=None, parent=None):
if value and value[0] == '<': p = parser(value, self); return
self.tag, self.xmlns, self.attrs, self.children, self.parent = tag, xmlns, attrs.copy() if attrs else {}, children if isinstance(children, XMLList) else XMLList(children) if children else XMLList(), parent
if self.parent and not self.xmlns: self.xmlns = self.parent.xmlns
if isinstance(self.children, (str, unicode)): self.children = [self.children]
def __repr__(self):
ns = [u'xmlns="%s"'%(self.xmlns,)] if self.xmlns and (not self.parent or self.xmlns != self.parent.xmlns) else []
attrs = [u'%s="%s"'%(k, escape(ustr(v))) for k,v in self.attrs.iteritems()]
intag = u' '.join([self.tag] + ns + attrs)
inner = u''.join([unicode(x) if isinstance(x, XML) else escape(x) for x in self.children])
return u'<%s>%s</%s>'%(intag, inner, self.tag) if inner else u'<%s />'%(intag)
def toprettyxml(self, encoding='UTF-8', indent=' ', count=0): # similar but not same as xml.dom.minidom's toprettyxml
ns = [u'xmlns="%s"'%(self.xmlns,)] if self.xmlns and (not self.parent or self.xmlns != self.parent.xmlns) else []
attrs = [u'%s="%s"'%(k, escape(ustr(v))) for k,v in self.attrs.iteritems()]
intag = u' '.join([self.tag] + ns + attrs)
inner = (u'\n' + indent*(count+1)).join([x.toprettyxml(encoding=None, indent=indent, count=count+1) if isinstance(x, XML) else escape(x.strip()) for x in self.children if not isinstance(x, basestring) or x.strip()])
return ('' if encoding is None else u'<?xml version="1.0"?>\n' if not encoding else u'<?xml version="1.0" encoding="%s"?>\n'%(encoding,)) + \
(u'<%s>\n'%(intag,) + indent*(count+1) + inner + '\n' + indent*count + u'</%s>'%(self.tag,) if len(self.elems) \
else (u'<%s>%s</%s>'%(intag, inner, self.tag) if inner else u'<%s />'%(intag,)))
def __cmp__(self, other): return cmp(unicode(self), unicode(other))
# XML attributes can be accessed using Python container semantics. Doesn't throw exception.
def __getitem__(self, item): return self.attrs.get(item, None)
def __setitem__(self, item, value): self.attrs[item] = value
def __delitem__(self, item): del self.attrs[item]
def __contains__(self, item): return item in self.attrs
def __call__(self, name=None): return self.children[name if name else "*"]
def __getattr__(self, name): # if Python attribute not found, then check XML attribute. Never throws exception for attribute error
if name == '_':
if name not in self.__dict__: self.__dict__[name] = _(self)
return self.__dict__[name]
elif name in self.__dict__['attrs']:
return self.__dict__['attrs'].get(name)
raise AttributeError, 'Invalid attribute access ' + name
def clear(self): self.children.clear(); self.attrs.clear() # clear all children and attributes
def copy(self): return XML(str(self)) # copy into another XML
@property
def cdata(self): return self.children.cdata
@property
def elems(self): return self.children.elems
class _(object):
'''Allows accessing XML attributes by name using Python attribute semantics.'''
def __init__(self, node): self.__dict__['_node'] = node
def __getattr__(self, name): return self._node.attrs.get(name, None)
def __setattr__(self, name, value): self._node.attrs[name] = value
def __delattr__(self, name): del self._node.attrs[name]
def __contains__(self, name): return name in self._node.attrs
def __setitem__(self, name, value): self._node.attrs[name] = value
def __getitem__(self, name): return self._node.attrs.get(name, None)
def __delitem__(self, name): del self._node.attrs[name]
def __call__(self, name): return self._node.attrs.get(name, None)
# unit testing of this module
if __name__ == '__main__':
import doctest
doctest.testmod()
| 53.230769
| 223
| 0.652566
|
bcd67e851a8bd49122613e6df435a6c9dcb87bb9
| 34,990
|
py
|
Python
|
.history/neuroformer/model_perceiver_20220121144355.py
|
woanderer/neuroformer
|
df3462d55977b6c9adcb6753e7c474b8b76e8021
|
[
"MIT"
] | null | null | null |
.history/neuroformer/model_perceiver_20220121144355.py
|
woanderer/neuroformer
|
df3462d55977b6c9adcb6753e7c474b8b76e8021
|
[
"MIT"
] | null | null | null |
.history/neuroformer/model_perceiver_20220121144355.py
|
woanderer/neuroformer
|
df3462d55977b6c9adcb6753e7c474b8b76e8021
|
[
"MIT"
] | null | null | null |
# from code.transformer_vid.utils import convert_weights
# import rotary_embedding_torch
from torch.nn.modules.activation import GELU, ReLU
# from data.OneCombo3.trainer import TrainerConfig
import math
import numpy as np
import itertools
import logging
import torch
import torch.nn as nn
from torch.nn import functional as F
from torch.autograd import Variable
from torchvision.models.video import r3d_18
# from ResNet3D import r3d_18
from scipy.optimize import linear_sum_assignment
# from rotary_embedding_torch import apply_rotary_emb, RotaryEmbedding
from einops.layers.torch import Rearrange
logger = logging.getLogger(__name__)
def convert_weights(model: nn.Module):
"""Convert applicable model parameters to fp16"""
def _convert_weights_to_fp16(l):
if isinstance(l, (nn.Conv1d, nn.Conv2d, nn.Linear)): # nn.Conv3d,
l.weight.data = l.weight.data.half()
if l.bias is not None:
l.bias.data = l.bias.data.half()
if isinstance(l, nn.MultiheadAttention):
for attr in [*[f"{s}_proj_weight" for s in ["in", "q", "k", "v"]], "in_proj_bias", "bias_k", "bias_v"]:
tensor = getattr(l, attr)
if tensor is not None:
tensor.data = tensor.data.half()
for name in ["text_projection", "proj"]:
if hasattr(l, name):
attr = getattr(l, name)
if attr is not None:
attr.data = attr.data.half()
model.apply(_convert_weights_to_fp16)
class GPTConfig:
""" base GPT config, params common to all GPT versions """
embd_pdrop = 0.2
resid_pdrop = 0.2
attn_pdrop = 0.2
pos_pdrop = 0.2
temp_pdrop = 0.2
pos_emb = True
temp_emb = True
start_prune = 30
epoch = 0
def __init__(self, vocab_size, block_size, **kwargs):
self.vocab_size = vocab_size
self.block_size = block_size
for k, v in kwargs.items():
setattr(self, k, v)
class neuralGPTConfig:
""" base GPT config, params common to all GPT versions """
n = 0.4
im_drop = 0.2
id_drop = n
embd_pdrop = n
resid_pdrop = n
attn_pdrop = n
pos_pdrop = n
temp_pdrop = n
pos_emb = True
temp_emb = True
def __init__(self, vocab_size, block_size, **kwargs):
self.vocab_size = vocab_size
self.block_size = block_size
for k, v in kwargs.items():
setattr(self, k, v)
class GPT1Config(GPTConfig):
""" GPT-1 like network roughly 125M params """
n_layer = 12
n_head = 12
n_embd = 768
class VideoFeaturesExtractor(nn.Module):
"""
R3D: (3 x T x H x W)
H, W = 112
"""
def __init__(self):
super().__init__()
self.backbone = torch.nn.Sequential(*(list(r3d_18(pretrained=True).children())[:-2]))
convert_weights(self.backbone)
# # freeze backbone
# for k, v in self.backbone.named_parameters():
# v.requires_grad = False
def forward(self, x):
# B = Batch, T, C, Fm, H, W
features = self.backbone(x) # (B, C, T, H, W)
B, C, T, H, W = features.shape
features = features.permute(0, 2, 3, 4, 1)
features = features.view(B, -1, C)
return features
class VideoEncoder(nn.Module):
def __init__(self, n_embd):
super().__init__()
p1, p2 = 16
assert n_embd % (p1 * p2) == 0 "n_embd must be divisible by p1 * p2 "
c = n_embd /
self.to_patch_embedding = nn.Sequential(
Rearrange(f'b c t (h p1) (w p2) -> b (t h w) (p1 p2 c)', p1=16, p2=16)
)
def forward(self, x):
return self.to_patch_embedding(x)
class CausalSelfAttention(nn.Module):
"""
A vanilla multi-head masked self-attention layer with a projection at the end.
"""
def __init__(self, config):
super().__init__()
assert config.n_embd % config.n_head == 0
self.config = config
# key, query, value projections for all heads
self.key = nn.Linear(config.n_embd, config.n_embd)
self.query = nn.Linear(config.n_embd, config.n_embd)
self.value = nn.Linear(config.n_embd, config.n_embd)
# regularization
self.attn_drop = nn.Dropout(config.attn_pdrop)
self.resid_drop = nn.Dropout(config.resid_pdrop)
# output projection
self.proj = nn.Linear(config.n_embd, config.n_embd)
self.register_buffer("mask", self.build_mask(config.block_size))
self.n_head = config.n_head
self.att = None
self.T = config.block_size
# self.rotary_embedding = RotarySpatioTemporalEmbedding(config)
def build_mask(self, block_size):
mask = torch.tril(torch.ones((block_size, block_size)),
).view(1, 1, block_size, block_size)
return mask
def generate_sparse_mask(self, att, p, config):
"""
Generate a sparse mask according to p.
"""
assert p >= 0 and p <= 1, "p should be in [0, 1]"
T = config.block_size
mask = torch.rand((1, T)) < p
mask = mask.repeat(T, 1)
mask[0, 0] = False # don't mask 1st step
# check if any step is fully masked and umask it
idx_all_true = (True == torch.all(mask, dim=0)).nonzero()
for step in idx_all_true:
sampler = torch.distributions.Uniform(low=0, high=step.item()+1)
idx_false = sampler.sample((1,1)).long()
mask[step, idx_false] = False
# mask = mask.repeat(T, 1)
mask = mask.view(1, 1, T, T).cuda() if att.is_cuda else mask.view(1, 1, T, T)
att = att.masked_fill(mask, float('-inf'))
return att
def forward(self, x, pad=None, dtx=None):
# B = Batch, T = Sequence, C = n_embed
B, T, C = x.size()
# calculate query, key, values for all head in batch and move head forward to the batch dim
k = self.key(x).view(B, T, self.n_head, C // self.n_head).transpose(1, 2) # (B, nh, T, hs)
q = self.query(x).view(B, T, self.n_head, C // self.n_head).transpose(1, 2) # (B, nh, T, hs)
v = self.value(x).view(B, T, self.n_head, C // self.n_head).transpose(1, 2) # (B, nh, T, hs)
# # apply rotary embeddings
# if dtx is not None:
# q, k = self.rotary_embedding(q, k, dtx)
# causal self-attention; Self-attend: (B, nh, T, hs) x (B, nh, hs, T) -> (B, nh, T, T)
att = (q @ k.transpose(-2, -1)) * (1.0 / math.sqrt(k.size(-1)))
att = att.masked_fill(self.mask[:,:,:T,:T] == 0, float('-inf'))
if self.training:
att = self.generate_sparse_mask(att, 0.25, self.config)
if pad is not None:
for idx, i in enumerate(pad):
att[idx, :, :, self.T - i:] = float('-inf') # only able to see first padding token
att = F.softmax(att, dim=-1)
att = self.attn_drop(att)
self.att = att
y = att @ v # (B, nh, T, T) x (B, nh, T, hs) -> (B, nh, T, hs)
y = y.transpose(1, 2).contiguous().view(B, T, C) # re-assemble all head outputs side by side
# output projection
y = self.resid_drop(self.proj(y))
return y
class PositionalEmbedding(nn.Module):
""" Implement the PE function. """
def __init__(self, n_embd, p_drop, max_len=1500):
super().__init__()
self.dropout = nn.Dropout(p=p_drop)
# Compute the positional encodings once in log space.
pe = torch.zeros(max_len, n_embd)
position = torch.arange(0, max_len).unsqueeze(1)
div_term = torch.exp(torch.arange(0, n_embd, 2) *
-(math.log(10000.0) / n_embd))
pe[:, 0::2] = torch.sin(position * div_term)
pe[:, 1::2] = torch.cos(position * div_term)
pe = pe.unsqueeze(0)
self.register_buffer('pe', pe)
def forward(self, x):
x = Variable(self.pe[:, :x.size(1)],
requires_grad=False)
return self.dropout(x)
# class RotarySpatioTemporalEmbedding(nn.Module):
# """ Rotary temporal embeddings - block_size = id_blk_sz """
# def __init__(self, config):
# super().__init__()
# self.frame_block_size = config.frame_block_size
# self.id_block_size = config.id_block_size
# self.emb = RotaryEmbedding(dim=32)
# def forward(self, q, k, t):
# b = t.shape[0]
# tf = self.frame_block_size
# queries = []
# keys = []
# for B in range(b):
# im_temp_emb = torch.tensor([-0.5] * (tf//2) + [0.5] * (tf//2))
# im_pos_emb = torch.arange(self.frame_block_size)
# im_emb = torch.stack([im_temp_emb, im_pos_emb], dim=0)
# id_temp_emb = self.temp_emb(t[B], cache_key=self.block_size)
# freqs = self.emb(torch.cat(im_emb, id_temp_emb))
# queries.append(apply_rotary_emb(freqs, q[B][None, ...]))
# keys.append(apply_rotary_emb(freqs, k[B][None, ...]))
# q, k = torch.cat(queries), torch.cat(keys)
# return q, k
class TemporalEmbedding(nn.Module):
""" encoding temporal information using fourrier signals """
def __init__(self, n_embd, p_drop, max_len=1500):
super().__init__()
self.dropout = nn.Dropout(p=p_drop)
# Compute the positional encodings once in log space.
pe = torch.zeros(max_len, n_embd)
position = torch.arange(0, max_len).unsqueeze(1)
div_term = torch.exp(torch.arange(0, n_embd, 2) *
-(math.log(10000.0) / n_embd))
pe[:, 0::2] = torch.sin(position * div_term)
pe[:, 1::2] = torch.cos(position * div_term)
pe = pe.unsqueeze(0)
self.register_buffer('pe', pe)
def forward(self, x):
x = Variable(self.pe[:, :x.size(1)],
requires_grad=False)
return self.dropout(x)
class LearntTemporalEmbedding(nn.Module):
"""
Project B x T x 1 time sequence to
B x T x C
"""
def __init__(self, block_sz, n_embd, p_drop=0.2):
super().__init__()
self.temp_emb = nn.Sequential(
nn.Linear(1, n_embd // 2),
nn.GELU(),
nn.Linear(n_embd // 2, n_embd),
nn.Dropout(p_drop)
)
def forward(self, x):
return self.temp_emb(x.unsqueeze(-1))
class Decoder(nn.Module):
def __init__(self, config):
super().__init__()
# decoder_layer = nn.TransformerDecoderLayer(config.n_embd, config.n_head,
# activation='gelu', dropout=0.2, batch_first=True)
# self.decoder = nn.TransformerDecoder(decoder_layer, config.n_layer)
self.decoder = nn.Transformer(d_model=config.n_embd, nhead=config.n_head,
num_encoder_layers=3, num_decoder_layers=config.n_layer,
activation="gelu", dropout=0.4, batch_first=True)
self.register_buffer("tgt_mask", self.generate_square_subsequent_mask(config.id_block_size))
# self.register_buffer("tgt_pad_mask", self.generate_padding_mask(config.ids_block_size))
self.T = config.id_block_size
def generate_square_subsequent_mask(self, sz: int, pad=None):
r"""Generate a square mask for the sequence. The masked positions are filled with float('-inf').
Unmasked positions are filled with float(0.0).
"""
mask = (torch.triu(torch.ones(sz, sz), diagonal=0) == 1).transpose(0, 1)
mask = mask.float().masked_fill(mask == 0, float('-inf')).masked_fill(mask == 1, float(0.0))
return mask
def generate_padding_mask(self, sz: int, pad=None):
r"""Build a (B x T) mask that resides on the GPU and can be
manipulated by build_padding_mask according to padded sequence
"""
mask = torch.zeros(1, sz, dtype=torch.bool)
return mask
def generate_sparse_mask(self, sz: int, pad=None):
r""" Build a square mask that employs
teacher forcing according to P
"""
rand_mat = torch.rand(1, sz)
k = round(0.75 * sz)
k_th_quant = torch.topk(rand_mat, k, largest = False)[0][:,-1:]
bool_tensor = rand_mat <= k_th_quant
mask = torch.where(bool_tensor, torch.tensor(1), torch.tensor(0)).repeat(sz, 1)
mask = mask.float().masked_fill(mask == 0, float('-inf')).masked_fill(mask == 1, float(0.0))
return mask.cuda(self.tgt_mask.get_device()) if self.tgt_mask.is_cuda else mask
def build_padding_mask(self, tgt, pad):
# mask = self.tgt_pad_mask.repeat(tgt.shape[0], 1)
mask = torch.zeros(tgt.shape[0], self.T, dtype=torch.bool)
for B, P in enumerate(pad):
mask[B, self.T - P:] = True
return mask # .to(torch.cuda.current_device())
def forward(self, tgt, memory, pad):
# padding_mask = self.build_padding_mask(tgt, pad)
# tgt_mask = self.generate_sparse_mask(self.T) if self.training else self.tgt_mask
return self.decoder(src=memory, tgt=tgt, tgt_mask=self.tgt_mask,
tgt_key_padding_mask=None)
class ProjectNorm(nn.Module):
def __init__(self, feat_size, target_size):
super().__init__()
self.ln = nn.LayerNorm(feat_size)
self.mlp = nn.Sequential(
nn.Linear(feat_size, math.floor(2 * feat_size), bias=False),
nn.GELU(),
nn.Linear(math.floor(2 * feat_size), target_size, bias=False),
)
def forward(self, x):
return self.mlp(self.ln(x))
class TimeProjection(nn.Module):
def __init__(self, seq_size, id_seq_size, feat_size, target_size):
super().__init__()
self.mlp_seq = nn.Sequential(
nn.Linear(seq_size, id_seq_size),
nn.ReLU(),
nn.Dropout(p=0.3),
nn.Linear(id_seq_size, id_seq_size)
)
self.mlp_t = nn.Sequential(
nn.Linear(feat_size, feat_size // 2),
nn.ReLU(),
nn.Dropout(p=0.3),
nn.Linear(feat_size // 2, target_size)
)
def forward(self, x):
x = x.permute(0, 2, 1) # B, T, C -> B, C, T
x = self.mlp_seq(x) # B, C, T / 2
x = x.permute(0, 2, 1) # B, T / 2, C
return self.mlp_t(x) # B, T / 2, 1
class PSTHProjection(nn.Module):
"""Takes Last Output of Block -> (B, C)
Builds PSTH table
"""
def __init__(self, config):
super().__init__()
self.mlp = nn.Sequential(
nn.Linear(config.n_embd, 4 * config.n_embd, bias=False),
nn.Dropout(p=0.2),
nn.GELU(),
nn.Linear(config.n_embd * 4, config.id_vocab_size, bias=False)
)
def forward(self, x):
return self.mlp(x)
# class PSTHProjection(nn.Module):
# def __init__(self, config):
# super().__init__()
# self.mlp_seq = nn.Sequential(
# nn.Linear(config.id_block_size, config.id_block_size // 2, bias=False),
# nn.GELU(),
# nn.Dropout(p=0.2),
# nn.Linear(config.id_block_size // 2, 1, bias=False)
# )
# self.mlp_t = nn.Sequential(
# nn.Linear(config.n_embd, config.n_embd * 4, bias=False),
# nn.GELU(),
# nn.Dropout(p=0.2),
# nn.Linear(config.n_embd * 4, config.id_vocab_size, bias=False)
# )
# def forward(self, x):
# x = x.transpose(-1, -2) # B, T, C -> B, C, T
# x = self.mlp_seq(x) # B, C, 1
# x = x.transpose(-2, -1) # B, 1, Vocab_id
# return self.mlp_t(x)
class TimeRNN(nn.Module):
def __init__(self, feat_size, target_size):
super().__init__()
class Block(nn.Module):
""" an unassuming Transformer block """
def __init__(self, config):
super().__init__()
self.ln1 = nn.LayerNorm(config.n_embd)
self.ln2 = nn.LayerNorm(config.n_embd)
self.attn = CausalSelfAttention(config)
self.mlp = nn.Sequential(
nn.Linear(config.n_embd, 4 * config.n_embd),
nn.GELU(),
nn.Linear(4 * config.n_embd, config.n_embd),
nn.Dropout(config.resid_pdrop),
)
def forward(self, x, pad=None, dtx=None):
x = x + self.attn(self.ln1(x), pad)
x = x + self.mlp(self.ln2(x))
return x
class BlockSequential(nn.Sequential):
def forward(self, x, pad=None, dtx=None):
for module in self._modules.values():
x = module(x, pad, dtx)
return x
class DiceLossPSTH(nn.Module):
def __init__(self, size_average=True, smooth=1):
super().__init__()
def cross_entropy(self, input, target):
return torch.mean(-torch.sum(target * torch.log(input), 1))
def forward(self, logits, targets, smooth=1, class_weights=None):
total_logits = F.layer_norm(torch.sum(logits, dim=-2), [logits.size()[-1]])
# probs = F.log_softmax(logits, dim=-1)
probs = F.softmax(total_logits, dim=-1)
# logits = F.gelu(logits)
# probs = logits / (logits.max(dim=-1).values.unsqueeze(-1))
# flatten label and prediction tensors
outputs = probs.contiguous().view(-1)
targets = targets.contiguous().view(-1)
labels = torch.zeros_like(outputs)
labels[targets] = 1 / len(targets)
# intersection = (outputs * labels).sum()
# dice = (2. * intersection + smooth) / (outputs.sum() + labels.sum() + smooth)
return self.cross_entropy(outputs[None, ...], labels[None, ...])
class SetLoss(nn.Module):
def __init__(self):
super().__init__()
def cross_entropy(self, input, target):
return torch.mean(-torch.sum(target * torch.log(input), 1))
def forward(self, logits, targets):
targets = targets.contiguous().view(-1)
loss = 0
for n_step, n_logits in enumerate(logits):
n_logits = F.softmax(n_logits, dim=-1)
n_target = targets[n_step:]
n_target_dist = torch.zeros_like(n_logits)
if len(n_target) != 0:
n_target_dist[n_target] = 1 / len(n_target)
loss += self.cross_entropy(n_logits[None,...], n_target_dist[None, ...])
return loss / len(logits)
class TruncatedLoss(nn.Module):
def __init__(self, q=0.8, k=0.2, trainset_size=50000):
super(TruncatedLoss, self).__init__()
self.q = q
self.k = k
self.weight = torch.nn.Parameter(data=torch.ones(trainset_size, 1), requires_grad=False)
def forward(self, logits, targets, indexes):
p = F.softmax(logits, dim=-1)
Yg = torch.gather(p, 2, targets.unsqueeze(2))
loss = ((1-(Yg**self.q))/self.q)*self.weight[indexes] - ((1-(self.k**self.q))/self.q)*self.weight[indexes]
loss = torch.mean(loss)
return loss
def update_weight(self, logits, targets, indexes):
p = F.softmax(logits, dim=-1)
Yg = torch.gather(p, 2, targets.unsqueeze(2))
Lq = ((1-(Yg**self.q))/self.q)
Lqk = np.repeat(((1-(self.k**self.q))/self.q), targets.size(0))
Lqk = torch.from_numpy(Lqk).type(torch.cuda.FloatTensor)
Lqk = torch.unsqueeze(Lqk, 1)
condition = torch.gt(Lqk, Lq)
self.weight[indexes] = condition.type(torch.cuda.FloatTensor)
# class PSTHLOSS(nn.Module):
# def __init__(self):
# super().__init__()
# def forward(self, logits, targets):
# total_logits = torch.sum(logits, dim=-2) # sum over sequence dimension
# probs = F.softmax(total_logits, dim=-1)
# outptu
class HungarianMatcher(nn.Module):
def __init__(self):
super().__init__()
@torch.no_grad()
def forward(self, logits, targets):
T, C = logits.size()
probs = F.softmax(logits, dim=-1)
cost_id = (1 - probs[:, targets]).cpu().view(T, -1).unsqueeze(0)
indices = [linear_sum_assignment(c[i]) for i, c in enumerate(cost_id.split(len(targets), -1))]
return [(torch.as_tensor(i, dtype=torch.int64), torch.as_tensor(j, dtype=torch.int64)) for i, j in indices]
class KLDivLoss(nn.Module):
def __init__(self):
super().__init__()
self.log_softmax = nn.LogSoftmax(dim=-1)
self.KLdiv = nn.KLDivLoss()
def forward(self, logits, targets):
log_probs = self.log_softmax(logits)
return self.KLdiv(log_probs.long(), targets)
class PoissonCrossEntropyLoss(nn.Module):
def __init__(self):
super().__init__()
self.log_softmax = nn.LogSoftmax(dim=-1)
# self.softmax = nn.Softmax(dim=-1)
self.nll_poisson = nn.PoissonNLLLoss()
# self.nll_poisson = nn.NLLLoss()
def forward(self, logits, targets):
log_probs = self.log_softmax(logits)
return self.nll_poisson(log_probs, targets)
class GPT(nn.Module):
""" the full GPT language model, with a context size of block_size """
def __init__(self, config):
super().__init__()
self.device = 'cpu'
if torch.cuda.is_available():
self.device = torch.cuda.current_device()
self.config = config
# input embedding stem
self.n_embd = config.n_embd
self.tok_emb = nn.Embedding(config.id_vocab_size, config.n_embd)
self.pos_emb = PositionalEmbedding(config.n_embd, p_drop=0.2)
# self.pos_emb_id = nn.Parameter(torch.zeros(1, config.id_block_size, config.n_embd))
self.pos_emb_frames = nn.Parameter(torch.zeros(1, config.frame_block_size, config.n_embd))
# self.temp_emb = TemporalEmbedding(config.n_embd, p_drop=0.2)
# self.temp_emb = RotaryTemporalEmbedding(config.id_block_size)
self.temp_emb = LearntTemporalEmbedding(config.id_block_size, config.n_embd)
self.frame_temp_emb = LearntTemporalEmbedding(config.frame_block_size, config.n_embd)
self.id_drop = nn.Dropout(config.id_drop)
self.im_drop = nn.Dropout(config.im_drop)
self.drop = nn.Dropout(config.embd_pdrop)
# -- Visual Backbone -- #
# self.visual_backbone = VideoFeaturesExtractor()
self.video_encoder = VideoEncoder()
frame_temp_emb = torch.tensor(list(itertools.chain(*[[n * 0.05] * (config.frame_block_size//20) for n in range(20)]))).unsqueeze(0)
self.register_buffer("frame_temp_emb_seq", frame_temp_emb)
# -- Contrastive Loss -- ##
# self.proj_id = ProjectNorm(config.n_embd, config.n_embd)
# self.proj_vid = VidProjectNorm(config.n_embd, config.n_embd) # im_shape
## -- IM_Decoder -- ##
# self.blocks_id = BlockSequential(*[Block(config) for _ in range(2)])
# self.blocks_im = BlockSequential(*[Block(config) for _ in range(2)])
# self.ln_f_id = nn.LayerNorm(config.n_embd)
# self.ln_f_im = nn.LayerNorm(config.n_embd)
## -- Decoder -- ##
# self.ln_f = nn.LayerNorm(config.n_embd)
## GPT
# self.blocks = BlockSequential(*[Block(config) for _ in range(config.n_layer)])
# self.ln_f = nn.LayerNorm(config.n_embd)
## enc_dec
self.state_decoder = Decoder(config)
self.ln_f_state_dec = nn.LayerNorm(config.n_embd)
self.stimulus_decoder = Decoder(config)
self.ln_f_stimulus_dec = nn.LayerNorm(config.n_embd)
self.head = nn.Linear(config.n_embd, config.vocab_size, bias=False)
## -- Time -- ##
# self.proj_time = TimeProjection(config.block_size, config.id_block_size, config.n_embd, config.n_dt)
self.proj_time = ProjectNorm(config.n_embd, config.n_dt)
# self.proj_time = ProjectNorm(config.n_embd, 1)
## -- PSTH -- ##
# self.proj_psth = PSTHProjection(config)
# Loss
# self.dice_loss = DiceLossPSTH()
# self.poisson_loss = PoissonCrossEntropyLoss()
# self.hungarian_matcher = HungarianMatcher()
# self.kldiv_loss = KLDivLoss()
# self.truncated_loss = TruncatedLoss(trainset_size=config.data_size)
# self.set_loss = SetLoss()
# self.a = torch.tensor(0.5, requires_grad=True)
self.block_size = config.block_size
self.apply(self._init_weights)
if config.class_weights is not None:
for key in config.class_weights.keys():
self.register_buffer(f"class_weights_{key}", config.class_weights[key])
logger.info("number of parameters: %e", sum(p.numel() for p in self.parameters()))
def get_block_size(self):
return self.block_size
def _init_weights(self, module):
if isinstance(module, (nn.Linear, nn.Embedding)):
module.weight.data.normal_(mean=0.0, std=0.02)
if isinstance(module, nn.Linear) and module.bias is not None:
module.bias.data.zero_()
elif isinstance(module, nn.LayerNorm):
module.bias.data.zero_()
module.weight.data.fill_(1.0)
def configure_optimizers(self, train_config):
"""
Separates parameters into those who will experience weight decay and those that will not
"""
if train_config.decay_weights:
decay = set()
no_decay = set()
whitelist_weight_modules = (torch.nn.Linear, )
blacklist_weight_modules = (torch.nn.LayerNorm, torch.nn.Embedding)
for mn, m in self.named_modules():
for pn, p in m.named_parameters():
fpn = '%s.%s' % (mn, pn) if mn else pn # full param name
if pn.endswith('bias'):
# all biases will not be decayed
no_decay.add(fpn)
elif pn.endswith('weight') and isinstance(m, whitelist_weight_modules):
# weights of whitelist modules will be weight decayed
decay.add(fpn)
elif pn.endswith('weight') and isinstance(m, blacklist_weight_modules):
# weights of blacklist modules will NOT be weight decayed
no_decay.add(fpn)
else: no_decay.add(fpn)
# special case the position embedding parameter in the root GPT module as not decayed
black_list_mods = ['pos_emb', 'temp_emb']
for mods in black_list_mods:
for name, param in self.named_parameters():
if mods in name:
no_decay.add(name) # also pos_emb
# validate that we considered every parameter
param_dict = {pn: p for pn, p in self.named_parameters()}
no_decay -= decay & no_decay
inter_params = decay & no_decay
union_params = decay | no_decay
assert len(inter_params) == 0, "parameters %s made it into both decay/no_decay sets!" % (str(inter_params), )
assert len(param_dict.keys() - union_params) == 0, "parameters %s were not separated into either decay/no_decay set!" \
% (str(param_dict.keys() - union_params), )
# create the pytorch optimizer object
optim_groups = [
{"params": [param_dict[pn] for pn in sorted(list(decay))], "weight_decay": train_config.weight_decay},
{"params": [param_dict[pn] for pn in sorted(list(no_decay))], "weight_decay": 0.0},
]
optimizer = torch.optim.AdamW(optim_groups, lr=train_config.learning_rate, betas=train_config.betas)
else:
parameters = self.parameters()
optimizer = torch.optim.Adam(parameters, lr=train_config.learning_rate)
return optimizer
def process_features(self, x):
# batch, block_size, feature
p_idx = x['id_prev']
idx = x['id']
dtx = x['dt']
dtx_prev = x['dt_prev']
frames = self.video_encoder(x['frames'])
pad = x['pad']
b, t = idx.size()
# b_p, t_p = p_idx.size()
bf, tf = frames.size()[0:2]
# forward the GPT model
'''
positional and temporal embeddings implemented in multiple ways, learnt,
fourrier decomposition and in the case of time, just passed as is.
'''
# # Embeddings
prev_id_position_embeddings = self.pos_emb(p_idx)
prev_id_temporal_embeddings = self.temp_emb(dtx_prev.float())
id_position_embeddings = self.pos_emb(idx)
im_position_embeddings = self.pos_emb_frames
temporal_embeddings = self.temp_emb(dtx.float())
# Extract ID features
prev_token_embeddings = self.id_drop(self.tok_emb(p_idx) + prev_id_temporal_embeddings + prev_id_position_embeddings)
token_embeddings = self.tok_emb(idx) # each index maps to a (learnable) vector
token_embeddings = token_embeddings + temporal_embeddings + id_position_embeddings
token_embeddings = self.id_drop(token_embeddings)
# Extract image features and add time embeddings
im_temporal_embeddings = self.frame_temp_emb(self.frame_temp_emb_seq)
im_embeddings = frames # self.tok_emb(frames)
im_embeddings = im_embeddings + im_position_embeddings + im_temporal_embeddings
im_embeddings = self.im_drop(im_embeddings) # separate pos emb?
# Tidy up
features = dict()
features['id_prev'] = prev_token_embeddings
features['id'] = token_embeddings
features['frames'] = im_embeddings
return features, pad
def perceiver(self, features, pad):
x = self.state_decoder(tgt=features['id'], memory=features['id_prev'], pad=pad)
x = self.ln_f_state_dec(x)
x = self.stimulus_decoder(tgt=features['id'], memory=features['frames'], pad=pad)
x = self.ln_f_stimulus_dec(x)
logits = self.head(x)
return logits, x
def enc_dec(self, features, pad):
x = self.stimulus_decoder(tgt=features['id'], memory=features['frames'], pad=pad)
x = self.ln_f_stimulus_dec(x)
logits = self.head(x)
return logits, x
def GPTdecoder(self, features, pad, dtx=None):
# image + neural features
x = torch.cat((features['frames'], features['id']), dim=1)
# Decoder
x = self.blocks(x, pad, dtx) # (B, T, C)
x = self.ln_f(x)
logits = self.head(x)
# print(logits.shape) # (B, T, Vocab)
# logits_psth = x[:, -1] # (B, C)
return logits, x
def forward(self, x, targets=None):
idx = x['id']
dtx = x['dt']
frames = x['frames']
pad = x['pad']
b, t = idx.size()
# b, t = x['id'].shape[0], x['id'].shape[1] + x['id_prev'].shape[1]
bf, tf = frames.size()[0:2]
tf = self.config.frame_block_size
# assert t + tf == self.config.block_size, f"{tf} {t}"
# assert t <= self.block_size, "Cannot forward, model block size is exhausted"
features, pad = self.process_features(x)
logits, x = self.perceiver(features, pad)
# logits, x = self.enc_dec(features, pad)
# logits, x = self.GPTdecoder(features, pad)
time = self.proj_time(x) # (B, T_id, 1)
# print(x[:, 0].shape)
# psth = self.proj_psth(x) # (B, Vocab_id)
# if targets, calculate loss
# calculate loss on logits up to padding token for each batch
loss = None
loss_frames = 0
loss_id = []
loss_time = []
loss_dice = []
loss_psth = []
loss_hungarian = []
if targets is not None:
# loss_psth = self.dice_loss(psth, targets['modes'][:, tf:])
for B, P in enumerate(pad):
tf = 0
# im_logits = logits[B, :tf]
# im_targets = targets['frames'][B, :tf]
# loss_frames += F.cross_entropy(im_logits.view(-1, im_logits.size(-1)), im_targets.view(-1))
id_logits = logits[B, tf:tf + t - P]
id_targets = targets['id'][B, :t - P]
loss_id_ = F.cross_entropy(id_logits.view(-1, id_logits.size(-1)), id_targets.view(-1), weight=self.class_weights_id)
# if self.config.epoch >= 15:
# self.truncated_loss.update_weight(id_logits[None, ...], id_targets[None, ...], id_indexes[None, ...])
# loss_id_ = self.truncated_loss(id_logits[None, ...], id_targets[None, ...], id_indexes[None, ...])
time_preds = time[B, :t - P]
time_targets = targets['dt'][B, :t - P]
loss_time_ = F.cross_entropy(time_preds.view(-1, time_preds.size(-1)), time_targets.view(-1), weight=self.class_weights_dt)
# loss_time_ = F.mse_loss(time_preds.squeeze(-1), time_targets)
# loss_id_ = self.poisson_loss(id_logits.view(-1, id_logits.size(-1)), F.one_hot(id_targets, self.config.vocab_size))
# if len(id_targets) > 0:
# indices = self.hungarian_matcher(id_logits, id_targets)
# probs_matching, targets_matching = id_logits[indices[0][0]], id_targets[indices[0][1]]
# loss_hungarian_ = F.cross_entropy(probs_matching, targets_matching, weight=self.class_weights).to(self.device)
# loss_hungarian.append(loss_hungarian_)
# # psth = self.proj_psth(x[B, -1]) # from the EOS position
# loss_psth.append(torch.nan_to_num(self.set_loss(id_logits, id_targets)))
# loss_psth_ = self.dice_loss(id_logits, id_targets)
# loss_psth.append(torch.nan_to_num(loss_psth_))
loss_time.append(torch.nan_to_num(loss_time_))
loss_id.append(torch.nan_to_num(loss_id_))
loss = dict()
# loss['frames'] = loss_frames / (b / 3)
loss['id'] = sum(loss_id) / (b * 2) # sum(loss_id) / (b * 2) # / len(loss_id)
loss['time'] = sum(loss_time) / (b * 2)
# loss['dice'] = sum(loss_dice) / len(loss_dice)
# loss['dt'] = loss_time / (b * 50)
# loss['hungarian'] = sum(loss_hungarian) / (b * 2)
# loss['psth'] = sum(loss_psth) / (b * 2)
for key in list(loss):
if isinstance(loss[key], float):
del loss[key]
preds = dict()
preds['id'] = logits # [:, tf:] # only id logits
preds['dt'] = time
return preds, features, loss
| 39.270483
| 139
| 0.582223
|
1584291f3a7e50975c197a8ee5207917531ee96e
| 5,030
|
py
|
Python
|
groups/models.py
|
qsic/qsic3
|
b45dfcc76c80001b0c35c6a887a0cfcdf8d1c1e2
|
[
"BSD-3-Clause"
] | null | null | null |
groups/models.py
|
qsic/qsic3
|
b45dfcc76c80001b0c35c6a887a0cfcdf8d1c1e2
|
[
"BSD-3-Clause"
] | 1
|
2015-01-12T05:54:20.000Z
|
2015-01-12T05:55:23.000Z
|
groups/models.py
|
qsic/qsic3
|
b45dfcc76c80001b0c35c6a887a0cfcdf8d1c1e2
|
[
"BSD-3-Clause"
] | null | null | null |
import os
import string
import urllib.parse
import urllib.request
from django.core.urlresolvers import reverse
from django.db import models
from django.db.models import Q
from django.template.defaultfilters import slugify
from django.utils import timezone
from image_cropping.fields import ImageRatioField
from py3s3.files import S3ContentFile
from parsers.improvteams.parser import ItTeamParser
class Group(models.Model):
"""
Represents a Team or other Performance Group.
"""
name = models.CharField(max_length=64)
slug = models.SlugField(blank=True, default='')
# 'it' is short for Imrpovteams / Improvteams.com
it_url = models.URLField(null=True, blank=True)
photo = models.ImageField(upload_to='groups/photos', null=True, blank=True)
detail_crop = ImageRatioField('photo', '970x500', size_warning=True)
banner_crop = ImageRatioField('photo', '960x300', size_warning=True)
bio = models.TextField(null=True, blank=True)
create_dt = models.DateTimeField(auto_now_add=True, null=True)
is_house_team = models.BooleanField(default=True)
is_active = models.BooleanField(default=True)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.performer_offset = 0
def __str__(self):
return self.name
def __iter__(self):
return self
def type(self):
return self.__class__.__name__
def __next__(self):
qs = self.groupperformerrelation_set.all()
qs = qs.filter(
Q(start_dt__lte=timezone.now()),
Q(end_dt__gte=timezone.now()) | Q(end_dt=None)
)
if self.performer_offset < qs.count():
gpr = qs[self.performer_offset]
self.performer_offset += 1
return gpr.performer
else:
raise StopIteration
@property
def is_current(self):
return self.is_active
def save(self, **kwargs):
self.slug = slugify(self.name)
super().save()
@property
def url(self):
url = reverse('groups:group_detail_view_add_slug', kwargs={'pk': self.id})
url = ''.join((url, '/', self.slug))
return url
def save_it_content_from_parsed_it_url(self):
"""Save Group info parsed from Improvteams.com
Return True on successful completion
"""
from performers.models import Performer
# Return False if URL passed does not save to model
# eg. invalid URL
if not self.it_url:
return {'success': False, 'msg': 'It url is not set.'}
# Parse performer info from URL
try:
group_info = ItTeamParser(self.it_url)
except:
return {'success': False, 'msg': 'Unable to parse team info.'}
self.name = group_info.team_name
self.bio = group_info.team_bio
uri = urllib.parse.urljoin(self.it_url, group_info.team_photo_uri)
file_name = os.path.basename(uri)
with urllib.request.urlopen(uri) as imgp:
# make sure resource has a content-length
if not 'Content-Length' in imgp.headers:
return None
content_length = int(imgp.headers['Content-Length'])
content = imgp.read(content_length)
# make sure imgp is a jpeg
mimetype = 'image/jpeg'
if imgp.info().get_content_type() == mimetype:
s3file = S3ContentFile(content, name=file_name, mimetype=mimetype)
self.photo.save(file_name, s3file, save=True)
self.save()
if group_info.performer_uri_list:
for performer_uri in group_info.performer_uri_list:
p = Performer.objects.create(first_name='', last_name='', it_url=performer_uri)
p.load_from_it()
GroupPerformerRelation.objects.create(group=self,
performer=p,
start_dt=timezone.now())
return {'success': True}
def load_from_it(self):
self.save_it_content_from_parsed_it_url()
# save default dims of photo
if self.photo:
self.detail_crop = ','.join(('0', '0', str(self.photo.width), str(500)))
self.banner_crop = ','.join(('0', '0', str(self.photo.width), str(300)))
self.save()
return True
class GroupPerformerRelation(models.Model):
"""
This model represents the relationship between a performer and a
performance group. A performer is always part of a group. Whether the
performer appears on a team's current roster depends on if the peroformer
has a ``GroupPerfromerRelation`` for the group.
"""
group = models.ForeignKey('groups.Group')
performer = models.ForeignKey('performers.Performer')
start_dt = models.DateTimeField()
end_dt = models.DateTimeField(null=True, blank=True)
def __str__(self):
return '{} in {}'.format(self.performer, self.group)
| 33.986486
| 95
| 0.631014
|
b8443b6b72fabe5c427c905e0851cc7ded70722e
| 912
|
py
|
Python
|
hw2/support.py
|
ixlan/Deep-learning
|
246e5285b6fb6508814762fddfd00d54515ccf79
|
[
"MIT"
] | null | null | null |
hw2/support.py
|
ixlan/Deep-learning
|
246e5285b6fb6508814762fddfd00d54515ccf79
|
[
"MIT"
] | null | null | null |
hw2/support.py
|
ixlan/Deep-learning
|
246e5285b6fb6508814762fddfd00d54515ccf79
|
[
"MIT"
] | null | null | null |
import matplotlib.pyplot as plt
from glob import glob
import os
def accuracy_loss_curve(train_acc, test_acc, train_loss, test_loss, iter_steps):
plt.subplot(2, 1, 1)
plt.plot(iter_steps, train_loss, '-o', label ='train')
plt.plot(iter_steps, test_loss, '-o', label = 'test')
plt.xlabel('Iteration')
plt.ylabel('Loss')
plt.legend(loc='upper right')
plt.subplot(2, 1, 2)
plt.plot(iter_steps, train_acc, '-o', label='train')
plt.plot(iter_steps, test_acc, '-o', label='test')
plt.xlabel('Iteration')
plt.ylabel('Accuracy')
plt.legend(loc='lower right')
plt.gcf().set_size_inches(15, 12)
plt.show()
def get_run_var(dir):
subdirectories = get_immediate_subdirectories(dir)
return len(subdirectories)
def get_immediate_subdirectories(a_dir):
return [name for name in os.listdir(a_dir)
if os.path.isdir(os.path.join(a_dir, name))]
| 27.636364
| 80
| 0.680921
|
4bfdddd569923d16c7edbded917eaf53d848ffe3
| 656
|
py
|
Python
|
src/genie/libs/parser/bigip/get_wom_profile.py
|
nujo/genieparser
|
083b01efc46afc32abe1a1858729578beab50cd3
|
[
"Apache-2.0"
] | 204
|
2018-06-27T00:55:27.000Z
|
2022-03-06T21:12:18.000Z
|
src/genie/libs/parser/bigip/get_wom_profile.py
|
nujo/genieparser
|
083b01efc46afc32abe1a1858729578beab50cd3
|
[
"Apache-2.0"
] | 468
|
2018-06-19T00:33:18.000Z
|
2022-03-31T23:23:35.000Z
|
src/genie/libs/parser/bigip/get_wom_profile.py
|
nujo/genieparser
|
083b01efc46afc32abe1a1858729578beab50cd3
|
[
"Apache-2.0"
] | 309
|
2019-01-16T20:21:07.000Z
|
2022-03-30T12:56:41.000Z
|
# Global Imports
import json
from collections import defaultdict
# Metaparser
from genie.metaparser import MetaParser
# =============================================
# Collection for '/mgmt/tm/wom/profile' resources
# =============================================
class WomProfileSchema(MetaParser):
schema = {}
class WomProfile(WomProfileSchema):
""" To F5 resource for /mgmt/tm/wom/profile
"""
cli_command = "/mgmt/tm/wom/profile"
def rest(self):
response = self.device.get(self.cli_command)
response_json = response.json()
if not response_json:
return {}
return response_json
| 19.294118
| 52
| 0.577744
|
1b9ef6398acadcef2e849943f43501841e125121
| 7,524
|
py
|
Python
|
scripts/elia_daily_graph.py
|
sophiano/cusvm
|
7bba8a216b02a7c5607b4b5127c245c74d8f8514
|
[
"MIT"
] | null | null | null |
scripts/elia_daily_graph.py
|
sophiano/cusvm
|
7bba8a216b02a7c5607b4b5127c245c74d8f8514
|
[
"MIT"
] | null | null | null |
scripts/elia_daily_graph.py
|
sophiano/cusvm
|
7bba8a216b02a7c5607b4b5127c245c74d8f8514
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 2 08:44:14 2021
@author: sopmathieu
"""
import pickle
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.size'] = 14
import pkg_resources as pkg
from cusvm import preprocessing as pre
from cusvm import autocorrelations as acf
### load data (loaded automatically with package)
data_path = pkg.resource_filename(pkg.Requirement.parse("cusvm"), 'data')
#df = pd.read_csv (r'../data/PVdaily.csv') #local path
df = pd.read_csv(data_path + '\PVdaily.csv') #global path
data = np.array(df)[:,1:]
data = data.astype('float')
data = data/96
names = list(df.columns)[1:]
(n_obs, n_series) = data.shape
### plot raw data
# plt.hist(data[~np.isnan(data)], bins='auto', density=True, facecolor='b')
# plt.title("Elia data (day)")
# plt.grid(True)
# plt.ylabel('Density')
# plt.xlabel('load factor')
# plt.savefig('hist_day.pdf') #save figures
# plt.show()
### load time
#with open('../data/time_daily', 'rb') as file: #local path
with open(data_path + '/time_daily', 'rb') as file: #global path
my_depickler = pickle.Unpickler(file)
time = my_depickler.load() #data every day
### remove year 2015 with unusual deviations
# start = np.where(time >= 2016)[0][0]
# data = data[start:,:]
# time = time[start:]
### plot the data
def multiplot(data, time, start_time=2015, stop_time=2021, ind=[3,4,14,20,21], same_ax=False):
start = np.where(time >= start_time)[0][0]
stop = np.where(time >= stop_time)[0][0]
if stop-start < 1000:
ind_ticks = np.arange(start, stop, 60) #two months
x_ticks = np.round(time[ind_ticks],2)
else :
ind_ticks = np.arange(start, stop, 365) #one year
x_ticks = np.round(time[ind_ticks])
count = 1
fig = plt.figure(figsize=(10.0, 12.0))
max_val = np.max(data[start:stop, ind])*1.1
for i in ind:
f = fig.add_subplot(len(ind), 1, count)
plt.ylabel(names[i])
#plt.plot(data[start:stop, i])
plt.plot(time[start:stop], data[start:stop, i])
if same_ax:
f.set_ylim([0, max_val])
if count < len(ind):
f.axes.get_xaxis().set_ticklabels([])
plt.xticks(x_ticks)
count += 1
plt.show()
return fig
def plot_single(data, time, start_time=2015, stop_time=2021, ind=3, same_ax=False):
start = np.where(time >= start_time)[0][0]
stop = np.where(time >= stop_time)[0][0]
if stop-start < 1000:
ind_ticks = np.arange(start, stop, 60) #two months
x_ticks = np.round(time[ind_ticks],2)
else :
ind_ticks = np.arange(start, stop, 365) #one year
x_ticks = np.round(time[ind_ticks])
fig = plt.figure(figsize=(8.0, 4.5))
plt.title(names[ind])
plt.xlabel('year')
plt.plot(time[start:stop], data[start:stop, ind])
plt.xticks(x_ticks)
return fig
################################################
multiplot(data, time, 2016, 2017) #RESA, IVEG, IMEA 2015
multiplot(data, time, 2019, 2020) #14 September, IMEA (pic)
multiplot(data, time, 2017, 2017.8) #8march-21May (par 1/4H, changements brusques, avec 0)
# plot_single(data, time, 2016, 2018, ind=5)
# plt.ylabel('$P(i,t)$')
# plt.savefig('mult.pdf') #save figures
region = [i for i in range(len(names)) if names[i] == 'IMEA'][0]
fig = plot_single(data, time, ind=region)
plt.ylabel('$P(i,t)$ ')
#plt.savefig('flow_1_el.pdf') #save figure
plt.show()
plt.hist(data[:,region], bins='auto', density=True, facecolor='b')
plt.text(40, 0.04, 'mean: ' '%.3f' %np.nanmean(data[:,region]))
plt.text(40, 0.03, 'std: ' '%.3f' %np.nanstd(data[:,region]))
plt.xlabel('$P(i,t)$')
plt.title(names[region])
plt.ylabel('Density')
plt.grid(True)
#plt.savefig('hist_1_el.pdf') #save figure
plt.show()
#=====================================================================
### Histograms and graphs for the preprocessing
#======================================================================
### rescaling
data_rescaled, k_factors = pre.rescaling(data, period_rescaling=365)
multiplot(data_rescaled, time)
### median
med = pre.median(data_rescaled)
fig = plt.figure(figsize=(10.0, 6.0))
plt.plot(time, med) ; plt.show()
### remove common signal
ratio = pre.remove_signal(data, ref=med) #mean = 1
multiplot(ratio, time)
fig = plot_single(ratio, time, ind=region)
plt.ylabel('$P(i,t)/\hat c(t)$ ')
#plt.savefig('flow_2_el.pdf')
plt.show()
plt.hist(ratio[:,region], bins='auto', density=True, facecolor='b')
plt.text(1.5, 4, 'mean: ' '%.3f' %np.nanmean(ratio[:,region]))
plt.text(1.5, 3, 'std: ' '%.3f' %np.nanstd(ratio[:,region]))
#plt.axis([0,150, 0, 0.08])
#plt.yticks(np.arange(0, 0.02, 0.005))
plt.xlabel('$P(i,t)/\hat c(t)$')
plt.title(names[region])
plt.ylabel('Density')
plt.grid(True)
#plt.savefig('hist_2_el.pdf')
plt.show()
### rescale the ratio
ratio, k_factors = pre.rescaling(ratio, period_rescaling=365)
multiplot(ratio, time)
fig = plot_single(ratio, time, ind=region)
plt.ylabel('$\hat \mu_{\eta}(i,t)$ ')
#plt.savefig('flow_3_el.pdf')
plt.show()
plt.hist(ratio[:,region], bins='auto', density=True, facecolor='b')
plt.text(1.5, 3, 'mean: ' '%.3f' %np.nanmean(ratio[:,region]))
plt.text(1.5, 2, 'std: ' '%.3f' %np.nanstd(ratio[:,region]))
#plt.axis([0,150, 0, 0.08])
#plt.yticks(np.arange(0, 0.02, 0.005))
plt.xlabel('$\hat \mu_{\eta}(i,t)$')
plt.title(names[region])
plt.ylabel('Density')
plt.grid(True)
#plt.savefig('hist_3_el.pdf')
plt.show()
### select an IC pool
pool = pre.pool_clustering(ratio) #10
names_IC = [names[i] for i in range(n_series) if i in pool]
names_OC = [names[i] for i in range(n_series) if i not in pool]
multiplot(ratio, time)
multiplot(ratio, time, ind=[2,7,12,14,17], same_ax=True) #OC
multiplot(ratio, time, ind=[9,11,18,19,21], same_ax=True) #IC
multiplot(ratio, time, ind=[1,21,2,8,15], same_ax=True) #IC and OC
ratioIC = ratio[:, pool]
### standardise the data
#K_knee = pre.choice_K(ratio, ratioIC, start=50, stop=2000, step=50)
K = 400
data_stn, dataIC_stn = pre.standardisation(ratio, ratioIC, K)
multiplot(data_stn, time)
fig = plot_single(data_stn, time, ind=region)
plt.ylabel('$\hat \epsilon_{\eta}(i,t)$ ')
#plt.savefig('flow_4_el.pdf')
plt.show()
plt.hist(data_stn[:,region], bins='auto', density=True, facecolor='b')
plt.text(7.5, 0.3, 'mean: ' '%.3f' %np.nanmean(data_stn[:,region]))
plt.text(7.5, 0.2, 'std: ' '%.3f' %np.nanstd(data_stn[:,region]))
#plt.axis([0,150, 0, 0.08])
#plt.yticks(np.arange(0, 0.02, 0.005))
plt.xlabel('$\hat \epsilon_{\eta}(i,t)$')
plt.title(names[region])
plt.ylabel('Density')
plt.grid(True)
#plt.savefig('hist_4_el.pdf')
plt.show()
### plot the (IC) data
# plt.hist(dataIC_stn[~np.isnan(dataIC_stn)], range=[-4,4], bins='auto', density=True, facecolor='b')
# plt.title("Data IC")
# plt.text(2, 1, 'mean:' '%4f' %np.nanmean(dataIC_stn))
# plt.text(2, 0.8, 'std:' '%4f' %np.nanstd(dataIC_stn))
# plt.axis([-4, 4, 0, 1.5])
# plt.grid(True)
# plt.show()
### plot all data
# plt.hist(data_stn[~np.isnan(data_stn)], range=[-4,4], bins='auto', density=True, facecolor='b')
# plt.title("All Data (IC and OC)")
# plt.text(2, 1, 'mean:' '%4f' %np.nanmean(data_stn))
# plt.text(2, 0.8, 'std:' '%4f' %np.nanstd(data_stn))
# plt.axis([-4, 4, 0, 1.5])
# plt.grid(True)
# plt.show()
### autocorrelation
acf.acf_pacf_plot(data_stn, which_display=3, max_cov=50)
acf.acf_pacf_plot(data_stn, which_display=2, max_cov=50)
acf.acf_pacf_plot(data_stn, which_display=21, max_cov=50)
| 30.33871
| 103
| 0.630649
|
6b96f562dd2288fbae2fcae077aa7114c47aeed7
| 2,161
|
py
|
Python
|
src/azure-cli/azure/cli/command_modules/interactive/__init__.py
|
WCollins3/azure-cli
|
1639f71f25e926376e3af7014325329702e028ec
|
[
"MIT"
] | 1
|
2020-03-20T06:01:04.000Z
|
2020-03-20T06:01:04.000Z
|
src/azure-cli/azure/cli/command_modules/interactive/__init__.py
|
WCollins3/azure-cli
|
1639f71f25e926376e3af7014325329702e028ec
|
[
"MIT"
] | null | null | null |
src/azure-cli/azure/cli/command_modules/interactive/__init__.py
|
WCollins3/azure-cli
|
1639f71f25e926376e3af7014325329702e028ec
|
[
"MIT"
] | 1
|
2019-09-30T22:27:10.000Z
|
2019-09-30T22:27:10.000Z
|
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# --------------------------------------------------------------------------------------------
from knack.help_files import helps
from azure.cli.core import AzCommandsLoader
helps['interactive'] = """
type: command
short-summary: Start interactive mode. Installs the Interactive extension if not installed already.
long-summary: >
For more information on interactive mode, see: https://azure.microsoft.com/en-us/blog/welcome-to-azure-cli-shell/
"""
class InteractiveCommandsLoader(AzCommandsLoader):
def __init__(self, cli_ctx=None):
from azure.cli.core import ModExtensionSuppress
super(InteractiveCommandsLoader, self).__init__(
cli_ctx=cli_ctx,
suppress_extension=ModExtensionSuppress(
__name__, 'alias', '0.5.1',
reason='Your version of the extension is not compatible with this version of the CLI.',
recommend_update=True))
def load_command_table(self, _):
with self.command_group('', operations_tmpl='azure.cli.command_modules.interactive.custom#{}') as g:
g.command('interactive', 'start_shell', is_preview=True)
return self.command_table
def load_arguments(self, _):
with self.argument_context('interactive') as c:
style_options = ['quiet', 'purple', 'default', 'none', 'contrast', 'pastel',
'halloween', 'grey', 'br', 'bg', 'primary', 'neon']
c.argument('style', options_list=['--style', '-s'], help='The colors of the shell.',
choices=style_options)
c.argument('update', help='Update the Interactive extension to the latest available.',
action='store_true')
c.ignore('_subscription') # hide global subscription param
COMMAND_LOADER_CLS = InteractiveCommandsLoader
| 44.102041
| 129
| 0.589542
|
8448d5c2d7af31e5441265104aedcae98887bb22
| 1,721
|
py
|
Python
|
PythonExercicios/ex073 - Tuplas com Times de Futebol.py
|
caique-santana/CursoEmVideo-Curso_Python3
|
86bb67bbbf348544e1135d8657672d4e33fa70e2
|
[
"MIT"
] | 1
|
2020-04-15T00:49:02.000Z
|
2020-04-15T00:49:02.000Z
|
PythonExercicios/ex073 - Tuplas com Times de Futebol.py
|
caique-santana/CursoEmVideo-Curso_Python3
|
86bb67bbbf348544e1135d8657672d4e33fa70e2
|
[
"MIT"
] | null | null | null |
PythonExercicios/ex073 - Tuplas com Times de Futebol.py
|
caique-santana/CursoEmVideo-Curso_Python3
|
86bb67bbbf348544e1135d8657672d4e33fa70e2
|
[
"MIT"
] | null | null | null |
""" Crie uma tupla preenchida com os 20 primeiros colocados da Tableda do Campeonato Brasileiro de Futebol,
a ordem de colocação. Depois mostre:
A) Apenas os 5 primeiros colocados.
B) Os últimos 4 colocados da tabela.
C) Uma lista com os times em ordem alfabética.
D) Em que posição na tabela está o time da Chapecoense."""
# Caique Santana
colocacao = ('Corinthians', 'Palmeiras', 'Santos', 'Grêmio', 'Cruzeiro', 'Flamengo', 'Vasco', 'Chapecoense',
'Atlético-MG', 'Botafogo', 'Atlético-PR', 'Bahia', 'São Paulo', 'Fluminense', 'Sport',
'Vitória', 'Coritiba', 'Avaí', 'Ponte Preta', 'Atlético-GO')
print('{:^60}'.format('Campeonato Brasileiro 2017'))
print(f'Classificação Geral: \n{colocacao}')
print('*' * 60)
print(f'Os 5 primeiros colocados são: \n{colocacao[0:5]}')
print('*' * 60)
print(f'Os 4 últimos colocados são: \n{colocacao[-4:]}')
print('*' * 60)
print(f'Os times em ordem alfabética fica: \n{sorted(colocacao)}')
print('*' * 60)
print(f'A Chapecoense está na {colocacao.index("Chapecoense")+1}ª posição.')
# Gustavo Guanabara
times = ('Corinthians', 'Palmeiras', 'Santos', 'Grêmio',
'Cruzeiro', 'Flamengo', 'Vasco', 'Chapecoense',
'Atlético-MG', 'Botafogo', 'Atlético-PR', 'Bahia',
'São Paulo', 'Fluminense', 'Sport Recife',
'EC Vitória', 'Coritiba', 'Avaí', 'Ponte Preta',
'Atlético-GO')
print('-=' * 15)
print(f'Lista de times do Brasileirão: {times}')
print('-=' * 15)
print(f'Os 5 primeiros são {times[0:5]}')
print('-=' * 15)
print(f'Os 4 últimos são: {times[-4:]}')
print('-=' * 15)
print(f'Times em ordem alfabética: {sorted(times)}')
print('-=' * 15)
print(f'O Chapecoense está na {times.index("Chapecoense")+1}ª posição')
| 43.025
| 108
| 0.65369
|
77db8f745d7ea33a4a7409fba8a48c636a2351ea
| 12,150
|
py
|
Python
|
lldb/packages/Python/lldbsuite/test/functionalities/breakpoint/breakpoint_command/TestBreakpointCommand.py
|
medismailben/llvm-project
|
e334a839032fe500c3bba22bf976ab7af13ce1c1
|
[
"Apache-2.0"
] | 34
|
2020-01-31T17:50:00.000Z
|
2022-02-16T20:19:29.000Z
|
lldb/packages/Python/lldbsuite/test/functionalities/breakpoint/breakpoint_command/TestBreakpointCommand.py
|
medismailben/llvm-project
|
e334a839032fe500c3bba22bf976ab7af13ce1c1
|
[
"Apache-2.0"
] | 14
|
2020-02-03T23:39:51.000Z
|
2021-07-20T16:24:25.000Z
|
lldb/packages/Python/lldbsuite/test/functionalities/breakpoint/breakpoint_command/TestBreakpointCommand.py
|
medismailben/llvm-project
|
e334a839032fe500c3bba22bf976ab7af13ce1c1
|
[
"Apache-2.0"
] | 7
|
2020-04-14T09:12:18.000Z
|
2021-09-20T10:31:12.000Z
|
"""
Test lldb breakpoint command add/list/delete.
"""
import lldb
from lldbsuite.test.decorators import *
from lldbsuite.test.lldbtest import *
from lldbsuite.test import lldbutil
import side_effect
class BreakpointCommandTestCase(TestBase):
NO_DEBUG_INFO_TESTCASE = True
mydir = TestBase.compute_mydir(__file__)
@expectedFailureAll(oslist=["windows"], bugnumber="llvm.org/pr24528")
def not_test_breakpoint_command_sequence(self):
"""Test a sequence of breakpoint command add, list, and delete."""
self.build()
self.breakpoint_command_sequence()
@skipIf(oslist=["windows"], bugnumber="llvm.org/pr44431")
def test_script_parameters(self):
"""Test a sequence of breakpoint command add, list, and delete."""
self.build()
self.breakpoint_command_script_parameters()
def test_commands_on_creation(self):
self.build()
self.breakpoint_commands_on_creation()
def setUp(self):
# Call super's setUp().
TestBase.setUp(self)
# Find the line number to break inside main().
self.line = line_number('main.c', '// Set break point at this line.')
# disable "There is a running process, kill it and restart?" prompt
self.runCmd("settings set auto-confirm true")
self.addTearDownHook(
lambda: self.runCmd("settings clear auto-confirm"))
def test_delete_all_breakpoints(self):
"""Test that deleting all breakpoints works."""
self.build()
exe = self.getBuildArtifact("a.out")
self.runCmd("file " + exe, CURRENT_EXECUTABLE_SET)
lldbutil.run_break_set_by_symbol(self, "main")
lldbutil.run_break_set_by_file_and_line(
self, "main.c", self.line, num_expected_locations=1, loc_exact=True)
self.runCmd("run", RUN_SUCCEEDED)
self.runCmd("breakpoint delete")
self.runCmd("process continue")
self.expect("process status", PROCESS_STOPPED,
patterns=['Process .* exited with status = 0'])
def breakpoint_command_sequence(self):
"""Test a sequence of breakpoint command add, list, and delete."""
exe = self.getBuildArtifact("a.out")
self.runCmd("file " + exe, CURRENT_EXECUTABLE_SET)
# Add three breakpoints on the same line. The first time we don't specify the file,
# since the default file is the one containing main:
lldbutil.run_break_set_by_file_and_line(
self, None, self.line, num_expected_locations=1, loc_exact=True)
lldbutil.run_break_set_by_file_and_line(
self, "main.c", self.line, num_expected_locations=1, loc_exact=True)
lldbutil.run_break_set_by_file_and_line(
self, "main.c", self.line, num_expected_locations=1, loc_exact=True)
# Breakpoint 4 - set at the same location as breakpoint 1 to test
# setting breakpoint commands on two breakpoints at a time
lldbutil.run_break_set_by_file_and_line(
self, None, self.line, num_expected_locations=1, loc_exact=True)
# Make sure relative path source breakpoints work as expected. We test
# with partial paths with and without "./" prefixes.
lldbutil.run_break_set_by_file_and_line(
self, "./main.c", self.line,
num_expected_locations=1, loc_exact=True)
lldbutil.run_break_set_by_file_and_line(
self, "breakpoint_command/main.c", self.line,
num_expected_locations=1, loc_exact=True)
lldbutil.run_break_set_by_file_and_line(
self, "./breakpoint_command/main.c", self.line,
num_expected_locations=1, loc_exact=True)
lldbutil.run_break_set_by_file_and_line(
self, "breakpoint/breakpoint_command/main.c", self.line,
num_expected_locations=1, loc_exact=True)
lldbutil.run_break_set_by_file_and_line(
self, "./breakpoint/breakpoint_command/main.c", self.line,
num_expected_locations=1, loc_exact=True)
# Test relative breakpoints with incorrect paths and make sure we get
# no breakpoint locations
lldbutil.run_break_set_by_file_and_line(
self, "invalid/main.c", self.line,
num_expected_locations=0, loc_exact=True)
lldbutil.run_break_set_by_file_and_line(
self, "./invalid/main.c", self.line,
num_expected_locations=0, loc_exact=True)
# Now add callbacks for the breakpoints just created.
self.runCmd(
"breakpoint command add -s command -o 'frame variable --show-types --scope' 1 4")
self.runCmd(
"breakpoint command add -s python -o 'import side_effect; side_effect.one_liner = \"one liner was here\"' 2")
import side_effect
self.runCmd("command script import --allow-reload ./bktptcmd.py")
self.runCmd(
"breakpoint command add --python-function bktptcmd.function 3")
# Check that the breakpoint commands are correctly set.
# The breakpoint list now only contains breakpoint 1.
self.expect(
"breakpoint list", "Breakpoints 1 & 2 created", substrs=[
"2: file = 'main.c', line = %d, exact_match = 0, locations = 1" %
self.line], patterns=[
"1: file = '.*main.c', line = %d, exact_match = 0, locations = 1" %
self.line])
self.expect(
"breakpoint list -f",
"Breakpoints 1 & 2 created",
substrs=[
"2: file = 'main.c', line = %d, exact_match = 0, locations = 1" %
self.line],
patterns=[
"1: file = '.*main.c', line = %d, exact_match = 0, locations = 1" %
self.line,
"1.1: .+at main.c:%d:?[0-9]*, .+unresolved, hit count = 0" %
self.line,
"2.1: .+at main.c:%d:?[0-9]*, .+unresolved, hit count = 0" %
self.line])
self.expect("breakpoint command list 1", "Breakpoint 1 command ok",
substrs=["Breakpoint commands:",
"frame variable --show-types --scope"])
self.expect("breakpoint command list 2", "Breakpoint 2 command ok",
substrs=["Breakpoint commands (Python):",
"import side_effect",
"side_effect.one_liner"])
self.expect("breakpoint command list 3", "Breakpoint 3 command ok",
substrs=["Breakpoint commands (Python):",
"bktptcmd.function(frame, bp_loc, internal_dict)"])
self.expect("breakpoint command list 4", "Breakpoint 4 command ok",
substrs=["Breakpoint commands:",
"frame variable --show-types --scope"])
self.runCmd("breakpoint delete 4")
# Next lets try some other breakpoint kinds. First break with a regular expression
# and then specify only one file. The first time we should get two locations,
# the second time only one:
lldbutil.run_break_set_by_regexp(
self, r"._MyFunction", num_expected_locations=2)
lldbutil.run_break_set_by_regexp(
self,
r"._MyFunction",
extra_options="-f a.c",
num_expected_locations=1)
lldbutil.run_break_set_by_regexp(
self,
r"._MyFunction",
extra_options="-f a.c -f b.c",
num_expected_locations=2)
# Now try a source regex breakpoint:
lldbutil.run_break_set_by_source_regexp(
self,
r"is about to return [12]0",
extra_options="-f a.c -f b.c",
num_expected_locations=2)
lldbutil.run_break_set_by_source_regexp(
self,
r"is about to return [12]0",
extra_options="-f a.c",
num_expected_locations=1)
# Reset our canary variables and run the program.
side_effect.one_liner = None
side_effect.bktptcmd = None
self.runCmd("run", RUN_SUCCEEDED)
# Check the value of canary variables.
self.assertEquals("one liner was here", side_effect.one_liner)
self.assertEquals("function was here", side_effect.bktptcmd)
# Finish the program.
self.runCmd("process continue")
# Remove the breakpoint command associated with breakpoint 1.
self.runCmd("breakpoint command delete 1")
# Remove breakpoint 2.
self.runCmd("breakpoint delete 2")
self.expect(
"breakpoint command list 1",
startstr="Breakpoint 1 does not have an associated command.")
self.expect(
"breakpoint command list 2",
error=True,
startstr="error: '2' is not a currently valid breakpoint ID.")
# The breakpoint list now only contains breakpoint 1.
self.expect(
"breakpoint list -f",
"Breakpoint 1 exists",
patterns=[
"1: file = '.*main.c', line = %d, exact_match = 0, locations = 1, resolved = 1" %
self.line,
"hit count = 1"])
# Not breakpoint 2.
self.expect(
"breakpoint list -f",
"No more breakpoint 2",
matching=False,
substrs=[
"2: file = 'main.c', line = %d, exact_match = 0, locations = 1, resolved = 1" %
self.line])
# Run the program again, with breakpoint 1 remaining.
self.runCmd("run", RUN_SUCCEEDED)
# We should be stopped again due to breakpoint 1.
# The stop reason of the thread should be breakpoint.
self.expect("thread list", STOPPED_DUE_TO_BREAKPOINT,
substrs=['stopped',
'stop reason = breakpoint'])
# The breakpoint should have a hit count of 2.
self.expect("breakpoint list -f", BREAKPOINT_HIT_TWICE,
substrs=['resolved, hit count = 2'])
def breakpoint_command_script_parameters(self):
"""Test that the frame and breakpoint location are being properly passed to the script breakpoint command function."""
exe = self.getBuildArtifact("a.out")
self.runCmd("file " + exe, CURRENT_EXECUTABLE_SET)
# Add a breakpoint.
lldbutil.run_break_set_by_file_and_line(
self, "main.c", self.line, num_expected_locations=1, loc_exact=True)
# Now add callbacks for the breakpoints just created.
self.runCmd("breakpoint command add -s python -o 'import side_effect; side_effect.frame = str(frame); side_effect.bp_loc = str(bp_loc)' 1")
# Reset canary variables and run.
side_effect.frame = None
side_effect.bp_loc = None
self.runCmd("run", RUN_SUCCEEDED)
self.expect(side_effect.frame, exe=False, startstr="frame #0:")
self.expect(side_effect.bp_loc, exe=False,
patterns=["1.* where = .*main .* resolved, hit count = 1"])
def breakpoint_commands_on_creation(self):
"""Test that setting breakpoint commands when creating the breakpoint works"""
exe = self.getBuildArtifact("a.out")
target = self.dbg.CreateTarget(exe)
self.assertTrue(target.IsValid(), "Created an invalid target.")
# Add a breakpoint.
lldbutil.run_break_set_by_file_and_line(
self, "main.c", self.line, num_expected_locations=1, loc_exact=True,
extra_options='-C bt -C "thread list" -C continue')
bkpt = target.FindBreakpointByID(1)
self.assertTrue(bkpt.IsValid(), "Couldn't find breakpoint 1")
com_list = lldb.SBStringList()
bkpt.GetCommandLineCommands(com_list)
self.assertEqual(com_list.GetSize(), 3, "Got the wrong number of commands")
self.assertEqual(com_list.GetStringAtIndex(0), "bt", "First bt")
self.assertEqual(com_list.GetStringAtIndex(1), "thread list", "Next thread list")
self.assertEqual(com_list.GetStringAtIndex(2), "continue", "Last continue")
| 42.1875
| 147
| 0.615802
|
ead8a3cca4941f438d5af80676d62dfe8d8ddea1
| 3,280
|
py
|
Python
|
antlr4_vba_parser/vba_listener.py
|
Liam-Deacon/antlr4-vba-parser
|
af273e6d7c4efd7660d647ad5b6e338a4ff46bd3
|
[
"BSD-3-Clause"
] | 1
|
2021-07-23T19:28:59.000Z
|
2021-07-23T19:28:59.000Z
|
antlr4_vba_parser/vba_listener.py
|
Liam-Deacon/antlr4-vba-parser
|
af273e6d7c4efd7660d647ad5b6e338a4ff46bd3
|
[
"BSD-3-Clause"
] | null | null | null |
antlr4_vba_parser/vba_listener.py
|
Liam-Deacon/antlr4-vba-parser
|
af273e6d7c4efd7660d647ad5b6e338a4ff46bd3
|
[
"BSD-3-Clause"
] | null | null | null |
"""Implements the ANTLR listener pattern for the VBA parser"""
from .vbaListener import vbaListener
from .vbaParser import vbaParser
class VBADictListener(vbaListener):
"""Custom VBA listener which produces a dictionary of VBA output"""
def __init__(self) -> None:
super().__init__()
self.data = {
'modules': {}
}
# Enter a parse tree produced by vbaParser#module.
def enterModule(self, ctx: vbaParser.ModuleContext):
self.data['modules'][ctx] = {
'name': ctx.getText(),
'attributes': {},
'declarations': {},
'comments': {},
'functions': {},
'subroutines': {}
}
self._module = ctx
# Exit a parse tree produced by vbaParser#module.
def exitModule(self, ctx: vbaParser.ModuleContext):
self._module = None
# Enter a parse tree produced by vbaParser#moduleHeader.
def enterModuleHeader(self, ctx: vbaParser.ModuleHeaderContext):
self._module_header = ctx
# Exit a parse tree produced by vbaParser#moduleHeader.
def exitModuleHeader(self, ctx: vbaParser.ModuleHeaderContext):
self._module_header = None
# Enter a parse tree produced by vbaParser#subStmt.
def enterSubStmt(self, ctx:vbaParser.SubStmtContext):
self._sub = ctx
# Exit a parse tree produced by vbaParser#subStmt.
def exitSubStmt(self, ctx:vbaParser.SubStmtContext):
self._sub = None
# Enter a parse tree produced by vbaParser#ambiguousIdentifier.
def enterAmbiguousIdentifier(self, ctx:vbaParser.AmbiguousIdentifierContext):
self._identifier = ctx
# Exit a parse tree produced by vbaParser#ambiguousIdentifier.
def exitAmbiguousIdentifier(self, ctx:vbaParser.AmbiguousIdentifierContext):
self._identifier = None
# Enter a parse tree produced by vbaParser#certainIdentifier.
def enterCertainIdentifier(self, ctx:vbaParser.CertainIdentifierContext):
self._identifier = ctx
# Exit a parse tree produced by vbaParser#certainIdentifier.
def exitCertainIdentifier(self, ctx:vbaParser.CertainIdentifierContext):
self._identifier = None
# Enter a parse tree produced by vbaParser#remComment.
def enterRemComment(self, ctx:vbaParser.RemCommentContext):
pass
# Exit a parse tree produced by vbaParser#remComment.
def exitRemComment(self, ctx:vbaParser.RemCommentContext):
pass
# Enter a parse tree produced by vbaParser#comment.
def enterComment(self, ctx:vbaParser.CommentContext):
pass
# Exit a parse tree produced by vbaParser#comment.
def exitComment(self, ctx:vbaParser.CommentContext):
pass
# Enter a parse tree produced by vbaParser#endOfLine.
def enterEndOfLine(self, ctx:vbaParser.EndOfLineContext):
pass
# Exit a parse tree produced by vbaParser#endOfLine.
def exitEndOfLine(self, ctx:vbaParser.EndOfLineContext):
pass
# Enter a parse tree produced by vbaParser#endOfStatement.
def enterEndOfStatement(self, ctx:vbaParser.EndOfStatementContext):
pass
# Exit a parse tree produced by vbaParser#endOfStatement.
def exitEndOfStatement(self, ctx:vbaParser.EndOfStatementContext):
pass
| 34.526316
| 81
| 0.694817
|
bcaa83106caec5ce19f7b056605ed98b280304bc
| 11,116
|
py
|
Python
|
MAIN/Basics.py
|
xtuyaowu/Pair-Trading-Reinforcement-Learning
|
24b744224457efa2dfee23ed0c44ec393b37449a
|
[
"MIT"
] | 4
|
2021-01-17T17:18:07.000Z
|
2022-01-05T10:52:01.000Z
|
MAIN/Basics.py
|
xtuyaowu/Pair-Trading-Reinforcement-Learning
|
24b744224457efa2dfee23ed0c44ec393b37449a
|
[
"MIT"
] | null | null | null |
MAIN/Basics.py
|
xtuyaowu/Pair-Trading-Reinforcement-Learning
|
24b744224457efa2dfee23ed0c44ec393b37449a
|
[
"MIT"
] | null | null | null |
import tensorflow as tf
import itertools
import random
random.seed(0)
import numpy as np
import abc
from os import path
class Agent(metaclass=abc.ABCMeta):
def __init__(self, network, config):
self.session = None
self.network = network
self.config = config
self.data = dict()
self.feed_dict = dict()
self.saver = tf.train.Saver()
self.counters = dict()
self.input_layer = None
self.output_layer = None
self.get_counter()
self.docking()
def docking(self):
self.input_layer = getattr(self.network, list(self.network.__dict__.keys())[0])
self.output_layer = getattr(self.network, list(self.network.__dict__.keys())[-1])
def assign_network(self, network):
self.network = network
self.docking()
def set_session(self, session):
self.session = session
def initialize_global(self):
init = tf.global_variables_initializer()
self.session.run(init)
def get_counter(self):
for key in self.config['Counter'].keys():
self.counters[key] = StepCounter(**self.config['Counter'][key])
def save_model(self, folder=None, name=None, session=None):
folder_path = self.config['AgentModelSaverSavePath'] if folder is None else folder
name = self.config['AgentModelSaverSaveName'] if name is None else name
file_path = path.join(folder_path, name + '.ckpt').replace('\\', '/')
session = self.session if session is None else session
self.saver.save(session, file_path)
def restore_model(self, folder=None, name=None, session=None):
folder_path = self.config['AgentModelSaverRestorePath'] if folder is None else folder
name = self.config['AgentModelSaverRestoreName'] if name is None else name
file_path = path.join(folder_path, name + '.ckpt').replace('\\', '/')
session = self.session if session is None else session
self.saver.restore(session, file_path)
def close(self):
self.session.close()
@abc.abstractmethod
def process(self, **kwargs):
pass
class Processor(metaclass=abc.ABCMeta):
@abc.abstractmethod
def process(self, **kwargs):
pass
class Strategy(metaclass=abc.ABCMeta):
@abc.abstractmethod
def process(self, **kwargs):
pass
@property
@abc.abstractmethod
def reward(self):
return
@property
@abc.abstractmethod
def record(self):
return
@reward.setter
@abc.abstractmethod
def reward(self, value):
return
@record.setter
@abc.abstractmethod
def record(self, value):
return
class Network(object):
def __init__(self, input_layer):
self.input_layer = input_layer
@property
def num_layer(self):
return self.layer_names
@property
def layer_names(self):
return list(self.__dict__.keys())
def build_layers(self, layer_dict):
layer_names = list(layer_dict.keys())
for name in layer_names:
current_name = list(self.__dict__.keys())
assert name not in current_name, 'Error: Duplicated layer names.'
func_name = layer_dict[name]['func_name']
input_arg = layer_dict[name]['input_arg']
input_name = current_name[-1]
layer_para = layer_dict[name]['layer_para']
layer_para[input_arg] = getattr(self, input_name)
layer_func = TFLayer.get_func(func_name)
setattr(self, name, layer_func()(**layer_para))
def add_layer_duplicates(self, layer_dict, n_copy):
num_layer = 0
layer_names = list(layer_dict.keys())
for i in range(n_copy):
num_layer += 1
for name in layer_names:
current_names = list(self.__dict__.keys())
input_name = current_names[-1]
new_name = name + '_' + str(num_layer)
assert new_name not in current_names, 'Error: Duplicated layer names.'
new_layer_dict = {new_name: layer_dict[name]}
new_layer_dict[new_name]['input_name'] = input_name
self.build_layers(new_layer_dict)
class TFLayer(object):
@classmethod
def get_func(cls, method):
return getattr(cls, method)
@staticmethod
def fully_connected():
return tf.contrib.layers.fully_connected
@staticmethod
def dense():
return tf.layers.dense
@staticmethod
def flatten():
return tf.layers.flatten
@staticmethod
def dropout():
return tf.layers.dropout
@staticmethod
def softmax():
return tf.contrib.layers.softmax
@staticmethod
def one_hot():
return tf.one_hot
class Space(object):
def __init__(self, space):
self.check_space(space)
self.space = space
self.n_combination, self.indices, self.multipliers = Space.get_attribute(space)
self.idx_range = range(len(self.indices))
@classmethod
def check_space(cls, space):
assert isinstance(space, dict), 'Error:Input space should be a dictionary.'
for value in space.values():
assert isinstance(value, list), 'Error:Space value should be a list.'
@classmethod
def get_attribute(cls, space):
n_element = [len(space[key]) for key in space.keys()]
multiplier = [1]
for i in range(-1, -len(n_element), -1):
prod = multiplier[-1] * n_element[i]
multiplier.append(prod)
multiplier.reverse()
multiplier = tuple(multiplier)
space_index = tuple([list(range(n)) for n in n_element])
n_comb = np.product(n_element)
return n_comb, space_index, multiplier
def get_combinations(self):
space_keys = list(self.space.keys())
space_sets = list(map(list, self.space.values()))
combinations = list(itertools.product(*space_sets))
comb_list = [dict(zip(space_keys, element)) for element in combinations]
return comb_list
def get_random_sample(self, method):
indices = [random.choice(idx) for idx in self.indices]
if method == 'indices':
return indices
elif method == 'index':
return self._indices_to_index(indices)
elif method == 'one_hot':
return self._indices_to_one_hot(indices)
elif method == 'dict':
return self._indices_to_dict(indices)
else:
raise ValueError('Error: Method should be indices/index/one_hot/dict.')
def convert(self, sample, method):
method = '_' + method
return getattr(self, method)(sample)
def _indices_to_index(self, indices):
index = sum([indices[i] * self.multipliers[i] for i in self.idx_range])
return index
def _indices_to_one_hot(self, indices):
index = self._indices_to_index(indices)
output = self._index_to_one_hot(index)
return output
def _indices_to_dict(self, indices):
output = dict()
keys = list(self.space.keys())
for i in self.idx_range:
output[keys[i]] = self.space[keys[i]][indices[i]]
return output
def _index_to_indices(self, index):
mod = index
output = list(np.zeros(self.idx_range[-1] + 1, dtype=int))
for i in self.idx_range:
div, mod = divmod(mod, self.multipliers[i])
output[i] = div
if mod == 0:
break
return output
def _index_to_one_hot(self, index):
output = np.zeros((1, self.n_combination), dtype=int)
output[0][index] = 1
return output
def _index_to_dict(self, index):
indices = self._index_to_indices(index)
output = self._indices_to_dict(indices)
return output
def _one_hot_to_index(self, one_hot, axis=None):
index = np.argmax(one_hot, axis=axis)
return index
def _one_hot_to_indices(self, one_hot):
index = self._one_hot_to_index(one_hot)
output = self._index_to_indices(index)
return output
def _one_hot_to_dict(self, one_hot):
index = self._one_hot_to_index(one_hot)
output = self._index_to_dict(index)
return output
def _dict_to_indices(self, dict_in):
output = [self.space[key].index(value) for key, value in dict_in.items()]
return output
def _dict_to_index(self, dict_in):
indices = self._dict_to_indices(dict_in)
index = self._indices_to_index(indices)
return index
def _dict_to_one_hot(self, dict_in):
index = self._dict_to_index(dict_in)
output = self._index_to_one_hot(index)
return output
def _no_conversion(self, sample_in):
return sample_in
class StepCounter(object):
def __init__(self, name, start_num, end_num, step_size, n_buffer=0, is_descend=True, print_freq=0):
self.name = name
self.start_num = start_num
self.end_num = end_num
self.step_size = abs(step_size)
self.n_buffer = n_buffer
self.is_descend = is_descend
self.print_freq = print_freq
self.value = start_num
self.n_step = 0
self.is_buffered = False
self.is_ended = True if start_num == end_num else False
def reset(self, reset_buffer=False, reset_n_step=False):
self.value = self.start_num
if reset_n_step is True: self.n_step = 0
if reset_buffer is True: self.is_buffered = False
self.is_ended = True if self.start_num == self.end_num else False
def step(self):
if self.is_ended is False:
self.n_step += 1
self._check_is_buffered()
if self.print_freq is not None:
if self.n_step % self.print_freq == 0:
print('Counter [{name}]: {n_step} steps processed...'.format(name=self.name, n_step=self.n_step))
if (self.value != self.end_num) & (self.is_buffered is True):
if self.is_descend is True:
self._step_down()
elif self.is_descend is False:
self._step_up()
else:
raise ValueError("Error: Boolean value required for input is_descend.")
def _check_is_buffered(self):
if (self.is_buffered is False) & (self.n_step > self.n_buffer):
self.is_buffered = True
def _step_down(self):
self.value -= self.step_size
if self.value <= self.end_num:
self.value = self.end_num
self.is_ended = True
print('Counter [{name}]: Process completed.'.format(name=self.name))
def _step_up(self):
self.value += self.step_size
if self.value == self.end_num:
self.value = self.end_num
self.is_ended = True
print('Counter [{name}]: Process completed.'.format(name=self.name))
| 31.851003
| 117
| 0.61407
|
7ebe71b8d3e931455b2a39b8c047cb3db9d642e4
| 21,693
|
py
|
Python
|
webinterface/src/plugin.py
|
FoxyRabbit67/enigma2-plugins
|
f6b94012726931fdf28e80a26226aec612b350de
|
[
"Linux-OpenIB"
] | 41
|
2016-01-21T17:54:44.000Z
|
2021-06-26T05:54:41.000Z
|
webinterface/src/plugin.py
|
FoxyRabbit67/enigma2-plugins
|
f6b94012726931fdf28e80a26226aec612b350de
|
[
"Linux-OpenIB"
] | 22
|
2016-11-16T11:25:26.000Z
|
2021-12-13T09:13:06.000Z
|
webinterface/src/plugin.py
|
FoxyRabbit67/enigma2-plugins
|
f6b94012726931fdf28e80a26226aec612b350de
|
[
"Linux-OpenIB"
] | 62
|
2016-02-05T22:55:48.000Z
|
2022-03-12T21:48:22.000Z
|
Version = '$Header$';
from enigma import eConsoleAppContainer
from Plugins.Plugin import PluginDescriptor
from Components.config import config, ConfigBoolean, ConfigSubsection, ConfigInteger, ConfigYesNo, ConfigText, ConfigOnOff
from Components.Network import iNetworkInfo
from Screens.MessageBox import MessageBox
from WebIfConfig import WebIfConfigScreen
from WebChilds.Toplevel import getToplevel
from Tools.HardwareInfo import HardwareInfo
from Tools.Directories import copyfile, resolveFilename, SCOPE_PLUGINS, SCOPE_CONFIG
from Tools.IO import saveFile
from Tools.Log import Log
from twisted.internet import reactor, ssl
from twisted.internet.error import CannotListenError
from twisted.web import server, http, util, static, resource
from zope.interface import Interface, implements
from socket import gethostname as socket_gethostname
from OpenSSL import SSL, crypto
from time import gmtime
from os.path import isfile as os_isfile, exists as os_exists
from __init__ import __version__
import random, uuid, time, hashlib
from netaddr import IPNetwork
hw = HardwareInfo()
#CONFIG INIT
#init the config
config.plugins.Webinterface = ConfigSubsection()
config.plugins.Webinterface.enabled = ConfigYesNo(default=True)
config.plugins.Webinterface.show_in_extensionsmenu = ConfigYesNo(default = False)
config.plugins.Webinterface.allowzapping = ConfigYesNo(default=True)
config.plugins.Webinterface.includemedia = ConfigYesNo(default=False)
config.plugins.Webinterface.autowritetimer = ConfigYesNo(default=False)
config.plugins.Webinterface.loadmovielength = ConfigYesNo(default=True)
config.plugins.Webinterface.version = ConfigText(__version__) # used to make the versioninfo accessible enigma2-wide, not confgurable in GUI.
config.plugins.Webinterface.http = ConfigSubsection()
config.plugins.Webinterface.http.enabled = ConfigYesNo(default=True)
config.plugins.Webinterface.http.port = ConfigInteger(default = 80, limits=(1, 65535) )
config.plugins.Webinterface.http.auth = ConfigYesNo(default=True)
config.plugins.Webinterface.https = ConfigSubsection()
config.plugins.Webinterface.https.enabled = ConfigYesNo(default=True)
config.plugins.Webinterface.https.port = ConfigInteger(default = 443, limits=(1, 65535) )
config.plugins.Webinterface.https.auth = ConfigYesNo(default=True)
config.plugins.Webinterface.streamauth = ConfigYesNo(default=False)
config.plugins.Webinterface.localauth = ConfigOnOff(default=False)
config.plugins.Webinterface.anti_hijack = ConfigOnOff(default=True)
config.plugins.Webinterface.extended_security = ConfigOnOff(default=True)
global running_defered, waiting_shutdown, toplevel
running_defered = []
waiting_shutdown = 0
toplevel = None
server.VERSION = "Enigma2 WebInterface Server $Revision$".replace("$Revi", "").replace("sion: ", "").replace("$", "")
KEY_FILE = resolveFilename(SCOPE_CONFIG, "key.pem")
CERT_FILE = resolveFilename(SCOPE_CONFIG, "cert.pem")
#===============================================================================
# Helperclass to close running Instances of the Webinterface
#===============================================================================
class Closer:
counter = 0
def __init__(self, session, callback=None):
self.callback = callback
self.session = session
#===============================================================================
# Closes all running Instances of the Webinterface
#===============================================================================
def stop(self):
global running_defered
for d in running_defered:
print "[Webinterface] stopping interface on ", d.interface, " with port", d.port
x = d.stopListening()
try:
x.addCallback(self.isDown)
self.counter += 1
except AttributeError:
pass
running_defered = []
if self.counter < 1:
if self.callback is not None:
self.callback(self.session)
#===============================================================================
# #Is it already down?
#===============================================================================
def isDown(self, s):
self.counter -= 1
if self.counter < 1:
if self.callback is not None:
self.callback(self.session)
def installCertificates(session):
if not os_exists(CERT_FILE) \
or not os_exists(KEY_FILE):
print "[Webinterface].installCertificates :: Generating SSL key pair and CACert"
# create a key pair
k = crypto.PKey()
k.generate_key(crypto.TYPE_RSA, 2048)
# create a self-signed cert
cert = crypto.X509()
cert.get_subject().C = "DE"
cert.get_subject().ST = "Home"
cert.get_subject().L = "Home"
cert.get_subject().O = "Dreambox"
cert.get_subject().OU = "STB"
cert.get_subject().CN = socket_gethostname()
cert.set_serial_number(random.randint(1000000,1000000000))
cert.set_notBefore("20120101000000Z");
cert.set_notAfter("20301231235900Z")
cert.set_issuer(cert.get_subject())
cert.set_pubkey(k)
print "[Webinterface].installCertificates :: Signing SSL key pair with new CACert"
cert.sign(k, 'sha256')
try:
print "[Webinterface].installCertificates :: Installing newly generated certificate and key pair"
saveFile(CERT_FILE, crypto.dump_certificate(crypto.FILETYPE_PEM, cert))
saveFile(KEY_FILE, crypto.dump_privatekey(crypto.FILETYPE_PEM, k))
except IOError, e:
#Disable https
config.plugins.Webinterface.https.enabled.value = False
config.plugins.Webinterface.https.enabled.save()
#Inform the user
session.open(MessageBox, "Couldn't install generated SSL-Certifactes for https access\nHttps access is disabled!", MessageBox.TYPE_ERROR)
#===============================================================================
# restart the Webinterface for all configured Interfaces
#===============================================================================
def restartWebserver(session):
try:
del session.mediaplayer
del session.messageboxanswer
except NameError:
pass
except AttributeError:
pass
global running_defered
if len(running_defered) > 0:
Closer(session, startWebserver).stop()
else:
startWebserver(session)
#===============================================================================
# start the Webinterface for all configured Interfaces
#===============================================================================
def startWebserver(session):
global running_defered
global toplevel
session.mediaplayer = None
session.messageboxanswer = None
if toplevel is None:
toplevel = getToplevel(session)
errors = ""
if config.plugins.Webinterface.enabled.value is not True:
print "[Webinterface] is disabled!"
else:
# IF SSL is enabled we need to check for the certs first
# If they're not there we'll exit via return here
# and get called after Certificates are installed properly
if config.plugins.Webinterface.https.enabled.value:
installCertificates(session)
# Listen on all Interfaces
#HTTP
port = config.plugins.Webinterface.http.port.value
auth = config.plugins.Webinterface.http.auth.value
if config.plugins.Webinterface.http.enabled.value is True:
ret = startServerInstance(session, port, useauth=auth)
if not ret:
errors = "%s port %i\n" %(errors, port)
else:
registerBonjourService('http', port)
#Streaming requires listening on localhost:80 no matter what, ensure it its available
if config.plugins.Webinterface.http.port.value != 80 or not config.plugins.Webinterface.http.enabled.value:
#LOCAL HTTP Connections (Streamproxy)
local4 = "127.0.0.1"
local4mapped = "::ffff:127.0.0.1"
local6 = "::1"
ret = startServerInstance(session, 80, useauth=auth, ipaddress=local4)
if not ret:
errors = "%s%s:%i\n" %(errors, local4, 80)
ret = startServerInstance(session, 80, useauth=auth, ipaddress=local4mapped, ipaddress2=local6)
#ip6 is optional
# if not ret:
# errors = "%s%s/%s:%i\n" %(errors, local4mapped, local6, 80)
#HTTPS
if config.plugins.Webinterface.https.enabled.value is True:
sport = config.plugins.Webinterface.https.port.value
sauth = config.plugins.Webinterface.https.auth.value
ret = startServerInstance(session, sport, useauth=sauth, usessl=True)
if not ret:
errors = "%s%s:%i\n" %(errors, "0.0.0.0 / ::", sport)
else:
registerBonjourService('https', sport)
if errors:
session.open(MessageBox, "Webinterface - Couldn't listen on:\n %s" % (errors), type=MessageBox.TYPE_ERROR, timeout=30)
#===============================================================================
# stop the Webinterface for all configured Interfaces
#===============================================================================
def stopWebserver(session):
try:
del session.mediaplayer
del session.messageboxanswer
except NameError:
pass
except AttributeError:
pass
global running_defered
if len(running_defered) > 0:
Closer(session).stop()
#===============================================================================
# startServerInstance
# Starts an Instance of the Webinterface
# on given ipaddress, port, w/o auth, w/o ssl
#===============================================================================
def startServerInstance(session, port, useauth=False, usessl=False, ipaddress="::", ipaddress2=None):
if useauth:
# HTTPAuthResource handles the authentication for every Resource you want it to
root = HTTPAuthResource(toplevel, "Enigma2 WebInterface")
site = server.Site(root)
else:
root = HTTPRootResource(toplevel)
site = server.Site(root)
result = False
def logFail(addr, exception=None):
print "[Webinterface] FAILED to listen on %s:%i auth=%s ssl=%s" % (addr, port, useauth, usessl)
if exception:
print exception
if usessl:
ctx = ChainedOpenSSLContextFactory(KEY_FILE, CERT_FILE)
try:
d = reactor.listenSSL(port, site, ctx, interface=ipaddress)
result = True
running_defered.append(d)
except CannotListenError as e:
logFail(ipaddress, e)
if ipaddress2:
try:
d = reactor.listenSSL(port, site, ctx, interface=ipaddress2)
result = True
running_defered.append(d)
except CannotListenError as e:
logFail(ipaddress2, e)
else:
try:
d = reactor.listenTCP(port, site, interface=ipaddress)
result = True
running_defered.append(d)
except CannotListenError as e:
logFail(ipaddress, e)
if ipaddress2:
try:
d = reactor.listenTCP(port, site, interface=ipaddress2)
result = True
running_defered.append(d)
except CannotListenError as e:
logFail(ipaddress2, e)
print "[Webinterface] started on %s:%i auth=%s ssl=%s" % (ipaddress, port, useauth, usessl)
return result
#except Exception, e:
#print "[Webinterface] starting FAILED on %s:%i!" % (ipaddress, port), e
#return False
class ChainedOpenSSLContextFactory(ssl.DefaultOpenSSLContextFactory):
def __init__(self, privateKeyFileName, certificateChainFileName, sslmethod=SSL.SSLv23_METHOD):
self.privateKeyFileName = privateKeyFileName
self.certificateChainFileName = certificateChainFileName
self.sslmethod = sslmethod
self.cacheContext()
def cacheContext(self):
ctx = SSL.Context(self.sslmethod)
ctx.set_options(SSL.OP_NO_SSLv3|SSL.OP_NO_SSLv2)
ctx.use_certificate_chain_file(self.certificateChainFileName)
ctx.use_privatekey_file(self.privateKeyFileName)
self._context = ctx
class SimpleSession(object):
def __init__(self, expires=0):
self._id = "0"
self._expires = time.time() + expires if expires > 0 else 0
def _generateId(self):
if config.plugins.Webinterface.extended_security.value:
self._id = str ( uuid.uuid4() )
else:
self._id = "0"
def _getId(self):
if self.expired():
self._generateId()
return self._id
def expired(self):
expired = False
if config.plugins.Webinterface.extended_security.value:
expired = self._expires > 0 and self._expires < time.time()
expired = expired or self._id == "0"
else:
expired = self._id != "0"
return expired
id = property(_getId)
#Every request made will pass this Resource (as it is the root resource)
#Any "global" checks should be done here
class HTTPRootResource(resource.Resource):
SESSION_PROTECTED_PATHS = ['/web/', '/opkg', '/ipkg']
SESSION_EXCEPTIONS = [
'/web/epgsearch.rss', '/web/movielist.m3u', '/web/movielist.rss', '/web/services.m3u', '/web/session',
'/web/stream.m3u', '/web/stream', '/web/streamcurrent.m3u', '/web/strings.js', '/web/ts.m3u']
def __init__(self, res):
print "[HTTPRootResource}.__init__"
resource.Resource.__init__(self)
self.resource = res
self.sessionInvalidResource = resource.ErrorPage(http.PRECONDITION_FAILED, "Precondition failed!", "sessionid is missing, invalid or expired!")
self._sessions = {}
def getClientToken(self, request):
ip = request.getClientIP()
ua = request.getHeader("User-Agent") or "Default UA"
return hashlib.sha1("%s/%s" %(ip, ua)).hexdigest()
def isSessionValid(self, request):
session = self._sessions.get( self.getClientToken(request), None )
if session is None or session.expired():
session = SimpleSession()
key = self.getClientToken(request)
print "[HTTPRootResource].isSessionValid :: created session with id '%s' for client with token '%s'" %(session.id, key)
self._sessions[ key ] = session
request.enigma2_session = session
if config.plugins.Webinterface.extended_security.value and not request.path in self.SESSION_EXCEPTIONS:
protected = False
for path in self.SESSION_PROTECTED_PATHS:
if request.path.startswith(path):
protected = True
if protected:
rsid = request.args.get('sessionid', None)
if rsid:
rsid = rsid[0]
return session and session.id == rsid
return True
def render(self, request):
#enable SAMEORIGIN policy for iframes
if config.plugins.Webinterface.anti_hijack.value:
request.setHeader("X-Frame-Options", "SAMEORIGIN")
if self.isSessionValid(request):
return self.resource.render(request)
else:
return self.sessionInvalidResource.render(request)
def getChildWithDefault(self, path, request):
#enable SAMEORIGIN policy for iframes
if config.plugins.Webinterface.anti_hijack.value:
request.setHeader("X-Frame-Options", "SAMEORIGIN")
if self.isSessionValid(request):
return self.resource.getChildWithDefault(path, request)
else:
print "[Webinterface.HTTPRootResource.render] !!! session invalid !!!"
return self.sessionInvalidResource
#===============================================================================
# HTTPAuthResource
# Handles HTTP Authorization for a given Resource
#===============================================================================
class HTTPAuthResource(HTTPRootResource):
LOCALHOSTS = (IPNetwork("127.0.0.1"), IPNetwork("::1"))
def __init__(self, res, realm):
HTTPRootResource.__init__(self, res)
self.realm = realm
self.authorized = False
self.unauthorizedResource = resource.ErrorPage(http.UNAUTHORIZED, "Access denied", "Authentication credentials invalid!")
self._localNetworks = []
def _assignLocalNetworks(self, ifaces):
if self._localNetworks:
return
self._localNetworks = []
#LAN
for key, iface in ifaces.iteritems():
if iface.ipv4.address != "0.0.0.0":
v4net = IPNetwork("%s/%s" %(iface.ipv4.address, iface.ipv4.netmask))
self._localNetworks.append(v4net)
if iface.ipv6.address != "::":
v6net = IPNetwork("%s/%s" %(iface.ipv6.address, iface.ipv6.netmask))
self._localNetworks.append(v6net)
Log.w(self._localNetworks)
def unauthorized(self, request):
request.setHeader('WWW-authenticate', 'Basic realm="%s"' % self.realm)
request.setResponseCode(http.UNAUTHORIZED)
return self.unauthorizedResource
def _isLocalClient(self, clientip):
if self._isLocalHost(clientip):
return True
for lnw in self._localNetworks:
if self._networkContains(lnw, clientip):
return True
return False
def _isLocalHost(self, clientip):
for host in self.LOCALHOSTS:
if self._networkContains(host, clientip):
return True
return False
def _networkContains(self, network, ip):
if network.__contains__(ip):
return True
try:
# You may get an ipv6 noted ipv4 address like "::ffff:192.168.0.2"
# In that case it won't match the ipv4 local network so we have to try converting it to plain ipv4
if network.__contains__(ip.ipv4()):
return True
except:
pass
return False
def isAuthenticated(self, request):
self._assignLocalNetworks(iNetworkInfo.getConfiguredInterfaces())
if request.transport:
host = IPNetwork(request.transport.getPeer().host)
#If streamauth is disabled allow all acces from localhost
if not config.plugins.Webinterface.streamauth.value:
if self._isLocalHost(host.ip):
Log.d("Streaming auth is disabled - Bypassing Authcheck because host '%s' is local!" %host)
return True
if not config.plugins.Webinterface.localauth.value:
if self._isLocalClient(host.ip):
Log.d("Local auth is disabled - Bypassing Authcheck because host '%s' is local!" %host)
return True
# get the Session from the Request
http_session = request.getSession().sessionNamespaces
# if the auth-information has not yet been stored to the http_session
if not http_session.has_key('authenticated'):
if request.getUser() and request.getPassword():
http_session['authenticated'] = check_passwd(request.getUser(), request.getPassword())
else:
http_session['authenticated'] = False
#if the auth-information already is in the http_session
else:
if http_session['authenticated'] is False:
http_session['authenticated'] = check_passwd(request.getUser(), request.getPassword() )
#return the current authentication status
return http_session['authenticated']
#===============================================================================
# Call render of self.resource (if authenticated)
#===============================================================================
def render(self, request):
if self.isAuthenticated(request) is True:
return HTTPRootResource.render(self, request)
else:
print "[Webinterface.HTTPAuthResource.render] !!! unauthorized !!!"
return self.unauthorized(request).render(request)
#===============================================================================
# Override to call getChildWithDefault of self.resource (if authenticated)
#===============================================================================
def getChildWithDefault(self, path, request):
if self.isAuthenticated(request) is True:
return HTTPRootResource.getChildWithDefault(self, path, request)
else:
print "[Webinterface.HTTPAuthResource.getChildWithDefault] !!! unauthorized !!!"
return self.unauthorized(request)
from auth import check_passwd
global_session = None
#===============================================================================
# sessionstart
# Actions to take place on Session start
#===============================================================================
def sessionstart(reason, session):
global global_session
global_session = session
networkstart(True, session)
def registerBonjourService(protocol, port):
try:
from Plugins.Extensions.Bonjour.Bonjour import bonjour
service = bonjour.buildService(protocol, port)
bonjour.registerService(service, True)
print "[WebInterface.registerBonjourService] Service for protocol '%s' with port '%i' registered!" %(protocol, port)
return True
except ImportError, e:
print "[WebInterface.registerBonjourService] %s" %e
return False
def unregisterBonjourService(protocol):
try:
from Plugins.Extensions.Bonjour.Bonjour import bonjour
bonjour.unregisterService(protocol)
print "[WebInterface.unregisterBonjourService] Service for protocol '%s' unregistered!" %(protocol)
return True
except ImportError, e:
print "[WebInterface.unregisterBonjourService] %s" %e
return False
def checkBonjour():
if ( not config.plugins.Webinterface.http.enabled.value ) or ( not config.plugins.Webinterface.enabled.value ):
unregisterBonjourService('http')
if ( not config.plugins.Webinterface.https.enabled.value ) or ( not config.plugins.Webinterface.enabled.value ):
unregisterBonjourService('https')
#===============================================================================
# networkstart
# Actions to take place after Network is up (startup the Webserver)
#===============================================================================
#def networkstart(reason, **kwargs):
def networkstart(reason, session):
if reason is True:
startWebserver(session)
checkBonjour()
elif reason is False:
stopWebserver(session)
checkBonjour()
def openconfig(session, **kwargs):
session.openWithCallback(configCB, WebIfConfigScreen)
def menu_config(menuid, **kwargs):
if menuid == "network":
return [(_("Webinterface"), openconfig, "webif", 60)]
else:
return []
def configCB(result, session):
if result:
print "[WebIf] config changed"
restartWebserver(session)
checkBonjour()
else:
print "[WebIf] config not changed"
def Plugins(**kwargs):
p = PluginDescriptor(where=[PluginDescriptor.WHERE_SESSIONSTART], fnc=sessionstart)
p.weight = 100 #webif should start as last plugin
list = [p,
# PluginDescriptor(where=[PluginDescriptor.WHERE_NETWORKCONFIG_READ], fnc=networkstart),
PluginDescriptor(name=_("Webinterface"), description=_("Configuration for the Webinterface"),
where=PluginDescriptor.WHERE_MENU, icon="plugin.png", fnc=menu_config)]
if config.plugins.Webinterface.show_in_extensionsmenu.value:
list.append(PluginDescriptor(name="Webinterface", description=_("Configuration for the Webinterface"),
where=PluginDescriptor.WHERE_EXTENSIONSMENU, icon="plugin.png", fnc=openconfig))
return list
| 35.856198
| 145
| 0.685797
|
b7c34ea86c77de4a0625f6b121568d1e673c902e
| 364
|
py
|
Python
|
src/content_style_layers.py
|
d4rk6h05t/neural-style-art
|
f2fb3586e8a039e04238e0eb2dc4c8af96cd85d6
|
[
"Apache-2.0"
] | 6
|
2020-07-20T01:21:17.000Z
|
2022-01-13T02:27:40.000Z
|
src/content_style_layers.py
|
d4rk6h05t/neural-style-art
|
f2fb3586e8a039e04238e0eb2dc4c8af96cd85d6
|
[
"Apache-2.0"
] | null | null | null |
src/content_style_layers.py
|
d4rk6h05t/neural-style-art
|
f2fb3586e8a039e04238e0eb2dc4c8af96cd85d6
|
[
"Apache-2.0"
] | null | null | null |
# Content layer where will pull our feature maps
content_layers = ['block5_conv2']
# Style layer we are interested in
style_layers = ['block1_conv1',
'block2_conv1',
'block3_conv1',
'block4_conv1',
'block5_conv1'
]
num_content_layers = len(content_layers)
num_style_layers = len(style_layers)
| 26
| 48
| 0.631868
|
5d43c06e5d540a18d7e890c0eb0122234361e906
| 340
|
py
|
Python
|
am/__main__.py
|
ove/ove-asset-manager
|
34b20ba8b436a5fe5c1561e0c5d98f171a37193f
|
[
"MIT"
] | null | null | null |
am/__main__.py
|
ove/ove-asset-manager
|
34b20ba8b436a5fe5c1561e0c5d98f171a37193f
|
[
"MIT"
] | 191
|
2019-03-01T14:00:57.000Z
|
2021-06-06T23:01:57.000Z
|
am/__main__.py
|
ove/ove-asset-manager
|
34b20ba8b436a5fe5c1561e0c5d98f171a37193f
|
[
"MIT"
] | 1
|
2020-01-13T13:07:49.000Z
|
2020-01-13T13:07:49.000Z
|
from wsgiref import simple_server
from am import setup_app
# do not use this in production
# this is a dev only method provided for convenience
def main():
simple_server.make_server('0.0.0.0', 6080, setup_app()).serve_forever() # nosec
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
pass
| 20
| 84
| 0.691176
|
9cf45c76d24b239727c43b60b69bbdd534ad05c8
| 1,483
|
py
|
Python
|
src/sqlfluff/rules/L021.py
|
tdstark/sqlfluff
|
873263465c879a4061d7613078da9e6050fb66ff
|
[
"MIT"
] | null | null | null |
src/sqlfluff/rules/L021.py
|
tdstark/sqlfluff
|
873263465c879a4061d7613078da9e6050fb66ff
|
[
"MIT"
] | 8
|
2022-01-26T21:43:03.000Z
|
2022-01-31T10:22:02.000Z
|
src/sqlfluff/rules/L021.py
|
tdstark/sqlfluff
|
873263465c879a4061d7613078da9e6050fb66ff
|
[
"MIT"
] | 1
|
2022-01-24T10:10:43.000Z
|
2022-01-24T10:10:43.000Z
|
"""Implementation of Rule L021."""
from typing import Optional
from sqlfluff.core.rules.base import BaseRule, LintResult, RuleContext
import sqlfluff.core.rules.functional.segment_predicates as sp
class Rule_L021(BaseRule):
"""Ambiguous use of ``DISTINCT`` in select statement with ``GROUP BY``.
| **Anti-pattern**
| ``DISTINCT`` and ``GROUP BY`` are conflicting.
.. code-block:: sql
SELECT DISTINCT
a
FROM foo
GROUP BY a
| **Best practice**
| Remove ``DISTINCT`` or ``GROUP BY``. In our case, removing GROUP BY is better.
.. code-block:: sql
SELECT DISTINCT
a
FROM foo
"""
def _eval(self, context: RuleContext) -> Optional[LintResult]:
"""Ambiguous use of DISTINCT in select statement with GROUP BY."""
segment = context.functional.segment
if (
segment.all(sp.is_type("select_statement"))
# Do we have a group by clause
and segment.children(sp.is_type("groupby_clause"))
):
# Do we have the "DISTINCT" keyword in the select clause
distinct = (
segment.children(sp.is_type("select_clause"))
.children(sp.is_type("select_clause_modifier"))
.children(sp.is_type("keyword"))
.select(sp.is_name("distinct"))
)
if distinct:
return LintResult(anchor=distinct[0])
return None
| 30.265306
| 84
| 0.59002
|
71ac6798465f3c6a9c48f99cfd9cf63511ab9a9b
| 2,382
|
py
|
Python
|
common/src/stack/command/stack/commands/load/json/plugin_api.py
|
shivanshs9/stacki
|
258740748281dfe89b0f566261eaf23102f91aa4
|
[
"BSD-3-Clause"
] | null | null | null |
common/src/stack/command/stack/commands/load/json/plugin_api.py
|
shivanshs9/stacki
|
258740748281dfe89b0f566261eaf23102f91aa4
|
[
"BSD-3-Clause"
] | null | null | null |
common/src/stack/command/stack/commands/load/json/plugin_api.py
|
shivanshs9/stacki
|
258740748281dfe89b0f566261eaf23102f91aa4
|
[
"BSD-3-Clause"
] | null | null | null |
# @copyright@
# Copyright (c) 2006 - 2018 Teradata
# All rights reserved. Stacki(r) v5.x stacki.com
# https://github.com/Teradata/stacki/blob/master/LICENSE.txt
# @copyright@
import stack.commands
import json
from stack.exception import CommandError
class Plugin(stack.commands.Plugin, stack.commands.Command):
notifications = True
def provides(self):
return 'api'
def requires(self):
return [ 'software', 'environment', 'group', 'network', 'appliance', 'os', 'global', 'bootaction', 'host' ]
def run(self, args):
# check if the user would like to import api data
if args and 'api' not in args:
return
# self.owner.data contains the data from the json file defined in init
if 'api' in self.owner.data:
import_data = self.owner.data['api']
else:
self.owner.log.info('no api data in json file')
return
self.notify('\n\tLoading api\n')
# load the api group information
for group, data in import_data['group'].items():
self.owner.try_command('add.api.group', [ group ], f'adding api group {group}', 'already')
for permission in data['permissions']:
self.owner.try_command('add.api.group.perms', [ group, f'perm={permission}' ], f'adding api group permission {permission}', 'already')
# load the api user information
for user in import_data['user']:
parameters = [
user['username'],
f'admin={user["admin"]}',
# just add the first group for now, we will add the others later
f'group={user["groups"][0]}'
]
self.owner.try_command('add.api.user', parameters, f'adding api user {user["username"]}', 'already')
# now we iterate through each users groups
for group in user['groups']:
parameters = [
user['username'],
f'group={group}',
]
self.owner.try_command('add.api.user.group', parameters, f'adding api user group {group}', 'already')
# now we add user level permissions
for permission in user['permissions']:
parameters = [
user['username'],
f'perm={permission}',
]
self.owner.try_command('add.api.user.perms', parameters, f'adding permission {permission} to user {user["username"]}', 'already')
# load the blacklisted commands
for blacklist_command in import_data['blacklist commands']:
self.owner.try_command('add.api.blacklist.command', [ f'command={blacklist_command}' ], f'adding blacklist command {blacklist_command}', 'already')
| 34.521739
| 150
| 0.688077
|
97ac16530430a7e2b118e76c6a8b82d5c18a290f
| 356
|
py
|
Python
|
Aula 08/Ex3.py
|
diegorafaelvieira/Programacao-1
|
657a974f1215cec4aed68603e738d9a135131545
|
[
"MIT"
] | null | null | null |
Aula 08/Ex3.py
|
diegorafaelvieira/Programacao-1
|
657a974f1215cec4aed68603e738d9a135131545
|
[
"MIT"
] | null | null | null |
Aula 08/Ex3.py
|
diegorafaelvieira/Programacao-1
|
657a974f1215cec4aed68603e738d9a135131545
|
[
"MIT"
] | null | null | null |
qtd10_100=0
soma=0
qtdPares_100=0
for x in range(0,1000):
valor = int(input("Informe o valor:"))
if valor>10 and valor<100:
qtd10_100+=1
soma+=valor
if valor>100 and valor%2==0:
qtdPares_100+=1
print("Números pares e maiores do que 100:",qtdPares_100)
print("Números maiores que 10 e menores que 100:",(soma/qtd10_100))
| 27.384615
| 67
| 0.668539
|
1503620cf769424b5e5d422a1d22901bbaaa1f50
| 2,237
|
py
|
Python
|
HLTrigger/Configuration/python/HLT_75e33/sequences/HLTDiphoton3023IsoCaloIdUnseededSequence_cfi.py
|
PKUfudawei/cmssw
|
8fbb5ce74398269c8a32956d7c7943766770c093
|
[
"Apache-2.0"
] | 1
|
2021-11-30T16:24:46.000Z
|
2021-11-30T16:24:46.000Z
|
HLTrigger/Configuration/python/HLT_75e33/sequences/HLTDiphoton3023IsoCaloIdUnseededSequence_cfi.py
|
PKUfudawei/cmssw
|
8fbb5ce74398269c8a32956d7c7943766770c093
|
[
"Apache-2.0"
] | 4
|
2021-11-29T13:57:56.000Z
|
2022-03-29T06:28:36.000Z
|
HLTrigger/Configuration/python/HLT_75e33/sequences/HLTDiphoton3023IsoCaloIdUnseededSequence_cfi.py
|
PKUfudawei/cmssw
|
8fbb5ce74398269c8a32956d7c7943766770c093
|
[
"Apache-2.0"
] | 1
|
2021-11-30T16:16:05.000Z
|
2021-11-30T16:16:05.000Z
|
import FWCore.ParameterSet.Config as cms
from ..modules.hltDiEG23EtUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdClusterShapeSigmavvUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdClusterShapeSigmawwUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdClusterShapeUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdEcalIsoUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdHcalIsoUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdHEUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdHgcalHEUnseededFilter_cfi import *
from ..modules.hltDiEG3023IsoCaloIdHgcalIsoUnseededFilter_cfi import *
from ..modules.hltEG30EtUnseededFilter_cfi import *
from ..modules.hltEgammaCandidatesWrapperUnseeded_cfi import *
from ..modules.hltEGL1SeedsForDoublePhotonIsolatedFilter_cfi import *
from ..sequences.HLTDoFullUnpackingEgammaEcalSequence_cfi import *
from ..sequences.HLTDoLocalHcalSequence_cfi import *
from ..sequences.HLTFastJetForEgamma_cfi import *
from ..sequences.HLTHgcalTiclPFClusteringForEgammaUnseeded_cfi import *
from ..sequences.HLTL1Sequence_cfi import *
from ..sequences.HLTPFClusteringForEgammaUnseeded_cfi import *
from ..sequences.HLTPFHcalClusteringForEgamma_cfi import *
from ..tasks.HLTDiphoton3023IsoCaloIdUnseededTask_cfi import *
HLTDiphoton3023IsoCaloIdUnseededSequence = cms.Sequence(
HLTL1Sequence +
hltEGL1SeedsForDoublePhotonIsolatedFilter +
HLTDoFullUnpackingEgammaEcalSequence +
HLTPFClusteringForEgammaUnseeded +
HLTHgcalTiclPFClusteringForEgammaUnseeded +
hltEgammaCandidatesWrapperUnseeded +
hltEG30EtUnseededFilter +
hltDiEG23EtUnseededFilter +
hltDiEG3023IsoCaloIdClusterShapeUnseededFilter +
hltDiEG3023IsoCaloIdClusterShapeSigmavvUnseededFilter +
hltDiEG3023IsoCaloIdClusterShapeSigmawwUnseededFilter +
hltDiEG3023IsoCaloIdHgcalHEUnseededFilter +
HLTDoLocalHcalSequence +
HLTFastJetForEgamma +
hltDiEG3023IsoCaloIdHEUnseededFilter +
hltDiEG3023IsoCaloIdEcalIsoUnseededFilter +
hltDiEG3023IsoCaloIdHgcalIsoUnseededFilter +
HLTPFHcalClusteringForEgamma +
hltDiEG3023IsoCaloIdHcalIsoUnseededFilter,
HLTDiphoton3023IsoCaloIdUnseededTask
)
| 48.630435
| 81
| 0.86008
|
86f026e35fcc3d887549d6b70c4fce7518acccfc
| 503
|
py
|
Python
|
local_groups/migrations/0057_auto_20170829_2137.py
|
JoshZero87/site
|
c8024b805ff5ff0e16f54dce7bf05097fd2f08e0
|
[
"MIT"
] | 4
|
2017-01-29T00:38:41.000Z
|
2019-09-04T14:30:24.000Z
|
local_groups/migrations/0057_auto_20170829_2137.py
|
JoshZero87/site
|
c8024b805ff5ff0e16f54dce7bf05097fd2f08e0
|
[
"MIT"
] | 74
|
2017-10-02T04:42:54.000Z
|
2022-01-13T00:44:16.000Z
|
local_groups/migrations/0057_auto_20170829_2137.py
|
JoshZero87/site
|
c8024b805ff5ff0e16f54dce7bf05097fd2f08e0
|
[
"MIT"
] | 3
|
2017-03-24T23:26:46.000Z
|
2019-10-21T01:16:03.000Z
|
# -*- coding: utf-8 -*-
# Generated by Django 1.10.2 on 2017-08-29 21:37
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('local_groups', '0056_auto_20170829_1818'),
]
operations = [
migrations.AlterField(
model_name='group',
name='mou_url',
field=models.URLField(blank=True, max_length=255, null=True, verbose_name='MOU URL'),
),
]
| 23.952381
| 97
| 0.632207
|
ff9f07d9604147f7e4977699d5f95acc43408809
| 2,995
|
py
|
Python
|
experiments/exp_adult_10_OLHPGRR.py
|
Leaflowave/PrivCQ
|
8acc6ad0888793fb7fa190a1bd5b4f9eb1140514
|
[
"MIT"
] | null | null | null |
experiments/exp_adult_10_OLHPGRR.py
|
Leaflowave/PrivCQ
|
8acc6ad0888793fb7fa190a1bd5b4f9eb1140514
|
[
"MIT"
] | null | null | null |
experiments/exp_adult_10_OLHPGRR.py
|
Leaflowave/PrivCQ
|
8acc6ad0888793fb7fa190a1bd5b4f9eb1140514
|
[
"MIT"
] | null | null | null |
import frequency_oracle_3dim as freq
import linecache
import random
def query_on_adult_dim3(oraclePath,oracleInterval,queryPath,trueOraclePath,aggregation="count"):
# adult_3 range 10
queriesStr = linecache.getline(queryPath, 1)
queries = eval(queriesStr)
answer = [0]*500
trueOracleStr = linecache.getline(trueOraclePath, 1)
trueOracle = eval(trueOracleStr)
n = sum([sum(trueOracle[k].values()) for k in trueOracle.keys()])
TrueAnswer = [0]*500
relativeError = 0
averageError = 0
for i in range(1, 501):
for _ in range(10):
kthoracle = random.randint(1, 500)
oracleWithoutGroup = freq.frequency_oracle(oraclePath, oracleInterval, k_th_oracle=kthoracle)
oracle = {}
for oraclekey in oracleWithoutGroup.keys():
if oraclekey[2] not in oracle.keys():
oracle[oraclekey[2]] = {}
if (oraclekey[0], oraclekey[1]) not in oracle[oraclekey[2]].keys():
oracle[oraclekey[2]][(oraclekey[0], oraclekey[1])] = 0
oracle[oraclekey[2]][(oraclekey[0], oraclekey[1])] += oracleWithoutGroup[oraclekey]
sum_value = 0
true_sum_value = 0
for k1 in range(queries[i - 1][0][0], queries[i - 1][0][1] + 1):
for k2 in range(queries[i - 1][1][0], queries[i - 1][1][1] + 1):
for j in oracle.keys():
sum_value += j * oracle[j][(k1,k2)]
true_sum_value += j * trueOracle[j][(k1,k2)]
answer[i - 1] += sum_value
TrueAnswer[i - 1] += true_sum_value
answer[i - 1] /= 10.0
TrueAnswer[i - 1] /= 10.0
relativeError += (answer[i - 1] - TrueAnswer[i - 1]) / max(0.001 * n, float(TrueAnswer[i - 1]))
averageError += answer[i - 1] - TrueAnswer[i - 1]
# averageError += sum_value - true_sum_value
# relativeError += (abs(sum_value - true_sum_value)) / max(0.001 * n, float(true_sum_value))
return answer,TrueAnswer, relativeError / 500, averageError / 500
if __name__ == '__main__':
oraclePath = "experiments//adult_3_OLHPGRR_results.txt"
oracleInterval = 5
queryPath = "experiments//adult_query_6_8_10.txt"
trueOraclePath = "adult//adult5.txt"
ans,trueans, relativeError, averageError = query_on_adult_dim3(oraclePath, oracleInterval,
queryPath,
trueOraclePath,
aggregation="sum")
print(relativeError)
with open("experiments//final_adult_3_sum_range_OLHPGRR.txt", "w+") as f:
f.write(str(ans) + "\n")
f.write("true ans"+str(trueans)+"\n")
f.write("relativeError:" + str(relativeError) + "\n")
f.write("averageError:" + str(averageError) + "\n")
| 45.378788
| 106
| 0.55793
|
399f7a275c2d21e47c659bdc1b39ef535eeeb5bb
| 917
|
py
|
Python
|
filelist_excel.py
|
exomachine/filelist_excel
|
73347a49b990ed6e8e609c9cc53bbd68fcdce2ad
|
[
"MIT"
] | null | null | null |
filelist_excel.py
|
exomachine/filelist_excel
|
73347a49b990ed6e8e609c9cc53bbd68fcdce2ad
|
[
"MIT"
] | null | null | null |
filelist_excel.py
|
exomachine/filelist_excel
|
73347a49b990ed6e8e609c9cc53bbd68fcdce2ad
|
[
"MIT"
] | null | null | null |
# Export a list of all files from a target path to an Excel Spreadsheet
# @exomachine 2019
import glob
import xlwt
import ntpath
from tempfile import TemporaryFile
path = 'U:\\' #Input path
savePath = "Q:\\Folder Content.xls" #Output path
rawData = []
book1 = xlwt.Workbook()
sheet1 = book1.add_sheet('sheet1')
rawData.append('List of folders')
for d in glob.glob(path + "**/", recursive=False):
rawData.append (d)
rawData.append('List of Folder and Files')
for f in glob.glob(path + "*", recursive=False):
rawData.append (f)
#for f in rawData:
# print(f)
def path_leaf(path): #trim path for filename or folder name
head, tail = ntpath.split(path)
return tail or ntpath.basename(head)
for i, e in enumerate(rawData):
sheet1.write(i,0,path_leaf(e))
sheet1.write(i,1,e)
book1.save(savePath)
book1.save(TemporaryFile())
print("done")
| 23.512821
| 72
| 0.665213
|
25e4e66486e71405c13378b7ff5abefc75bf9075
| 6,985
|
py
|
Python
|
app/dataprocessing.py
|
sean-ashley/Stroke-Prediction-App
|
8abb6f7c1217291f5f5a52e9f422314d85dd0fae
|
[
"Apache-2.0"
] | 7
|
2021-03-21T23:19:28.000Z
|
2021-12-27T18:51:45.000Z
|
app/dataprocessing.py
|
sean-ashley/Stroke-Prediction-App
|
8abb6f7c1217291f5f5a52e9f422314d85dd0fae
|
[
"Apache-2.0"
] | null | null | null |
app/dataprocessing.py
|
sean-ashley/Stroke-Prediction-App
|
8abb6f7c1217291f5f5a52e9f422314d85dd0fae
|
[
"Apache-2.0"
] | null | null | null |
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import MultiLabelBinarizer
def is_user_diabetic(avg_glucose_level):
"""
desc: converts avg_glucose_level to category based on ADA Guidelines https://www.diabetes.org/a1c/diagnosis
args:
avg_glucose_level (float) : glucose level in blood based on mg/dL
returns:
blood_cat (string) : blood sugar category
"""
if avg_glucose_level >= 200:
return 1
else:
return 0
def add_diabetes(df,add_col = True):
"""
desc : creates and adds a diabetes column to the dataframe
args:
df (pd.DataFrame) : stroke dataframe
return:
df (pd.DataFrame) : stroke dataframe with diabetes column added
"""
if add_col:
stroke_data = df.copy()
stroke_data["is_user_diabetic"] = stroke_data["avg_glucose_level"].apply(is_user_diabetic)
return stroke_data
#if we dont want to add the col return the same def
return df
def bmi_to_bodytype(bmi):
"""
desc : converts bmi to a category body type based on CDC guidelines https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html
args:
bmi (float) : the users bmi
returns:
bodytype (string) : The users bodytype
"""
if bmi < 18.5:
return "Underweight"
elif 18.5 <= bmi < 24.9:
return "Normal"
elif 24.9 <= bmi < 29.9:
return "Overweight"
else:
return "Obese"
def add_bodytype(df, add_col = True):
"""
desc : converts bmi to a category body type based on CDC guidelines https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html
args:
df (pd.DataFrame) : stroke dataframe
returns:
df (pd.DataFrame) : stroke dataframe with bodytype column
"""
if add_col:
stroke_data = df.copy()
num_cols = stroke_data.select_dtypes(exclude= ["object"])
num_cols_names = num_cols.columns
#impute missing values again to take into account new columns
imputer = SimpleImputer()
imputed_cols = imputer.fit_transform(num_cols)
imputed_cols = pd.DataFrame(data = imputed_cols,columns = num_cols.columns,index = num_cols.index)
#apply function
stroke_data["body_type"] = imputed_cols["bmi"].apply(bmi_to_bodytype)
return stroke_data
#if we dont want to add the col the same df
return df
def impute(df):
"""
desc : imputes
args:
df (pd.DataFrame) : stroke dataframe
returns:
df (pd.DataFrame) : stroke dataframe imputed
"""
stroke_data = df.copy()
num_cols = stroke_data.select_dtypes(exclude= ["object"])
num_cols_names = num_cols.columns
#impute missing values again to take into account new columns
imputer = SimpleImputer()
imputed_cols = imputer.fit_transform(num_cols)
imputed_cols = pd.DataFrame(data = imputed_cols,columns = num_cols.columns,index = num_cols.index)
#drop numeric columns
stroke_data.drop(columns = num_cols_names, axis = 1, inplace = True)
stroke_data = pd.concat([stroke_data,imputed_cols],axis = 1)
return stroke_data
def one_hot_encode(df):
"""
desc : one hot encodes categorical cols
args:
df (pd.DataFrame) : stroke dataframe
returns:
df (pd.DataFrame) : stroke dataframe with one_hot_encoded columns
"""
# extract categorical columns
stroke_data = df.copy()
cat_cols = stroke_data.select_dtypes(include = ["object"])
cat_vals = cat_cols.values
cat_cols_names = cat_cols.columns
binarizer = MultiLabelBinarizer()
encoded_cols = pd.DataFrame(binarizer.fit_transform(cat_vals),columns = binarizer.classes_,index = cat_cols.index)
#drop non one hot encoded cols
stroke_data.drop(columns = cat_cols_names, axis = 1, inplace = True)
#add encoded columns
stroke_data = pd.concat([stroke_data,encoded_cols], axis = 1)
#print(stroke_data.shape)
return stroke_data
def add_preexisting(df):
"""
desc : denotes whether or not a user has a pre-existing heart condition (high blood pressure or heart disease)
args:
df (pd.DataFrame) : stroke dataframe
returns:
df (pd.DataFrame) : stroke dataframe with pre_existing column
"""
stroke_data = df.copy()
stroke_data["pre_existing"] = (stroke_data['hypertension'] + stroke_data['heart_disease']).astype("bool")
return stroke_data
def get_all_tags(df):
"""
desc : get all possible tags for the df
args:
df (pd.DataFrame) : stroke dataframe
return:
all_tags (list) : full list of tags
"""
#add feature columns
diabetes_df = add_diabetes(df)
body_type_df = add_bodytype(diabetes_df)
pre_existing_df = add_preexisting(body_type_df)
#impute and onehotencode
imputed_df = impute(pre_existing_df)
encoded_df = one_hot_encode(imputed_df)
return encoded_df.columns
def add_missing_cols(df, total_tags):
"""
desc : add any missing columns and fill with 0's to make sure we can use gridsearchcv
args:
df (pd.DataFrame) : stroke dataframe
all_tags (list) : full list of tags
return:
df (pd.DataFrame) : stroke dataframe with all columns added
"""
#convert to set so we can perform set operations
df_cols = set(df.columns)
total_tags = set(total_tags)
cols_to_add = list(total_tags.difference(df_cols))
cols = sorted(list(total_tags))
if cols_to_add:
#make an array of zeros for all of the columns we are going to add
zeros = np.zeros(shape = (df.shape[0],len(cols_to_add)))
#add the cols
df[cols_to_add] = zeros
#maintain same order no matter what
df = df[cols]
return df
df = df[cols]
return df
def load_data(data_path,test_size = 0.1):
"""
desc : read in data, one hot encode, and seperate into training and test data
args:
data (string) : path to data
test_size (float) : portion of the data set reserved for testing
random_state (int) : Seed to use to randomely select
return:
X_train (pd.DataFrame) : training data
X_test (pd.DataFrame) : testing data
y_train (pd.DataFrame) : training target
y_test (pd.DataFrame) : testing target
"""
stroke_data = pd.read_csv(data_path,index_col = "id")
#print(one_hot_encode(stroke_data).columns)
#drop smoking status, 30% missing
#stroke_data = stroke_data.drop(columns = ["smoking_status"],axis = 1)
y = stroke_data["stroke"]
X = stroke_data.drop(columns=["stroke"], axis=1)
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = test_size, random_state=1)
return X_train, X_test, y_train, y_test
| 29.723404
| 140
| 0.661704
|
26d9d0b467b0d72d0888084969c5d2aee9ad8c6c
| 4,378
|
py
|
Python
|
umetnine/account/views.py
|
jaanos/OPB-umetnine
|
f1fedd62e750317548510c412793d80c60b9e392
|
[
"MIT"
] | null | null | null |
umetnine/account/views.py
|
jaanos/OPB-umetnine
|
f1fedd62e750317548510c412793d80c60b9e392
|
[
"MIT"
] | null | null | null |
umetnine/account/views.py
|
jaanos/OPB-umetnine
|
f1fedd62e750317548510c412793d80c60b9e392
|
[
"MIT"
] | null | null | null |
from django.contrib.auth import authenticate, login
from django.contrib.auth.models import User
from django.shortcuts import render, redirect, get_object_or_404
from django.http import HttpResponse
# from django.views.generic import CreateView, TemplateView
from datetime import datetime
from artists.forms import NewArtForm, TagForm, UserDescriptionForm
from artists.models import ArtworksTags, Tags, Arts, UserDescription
from .forms import RegisterForm, EditProfileFrom, AddArtForm
# Create your views here.
from .models import UserArtwork
def register(request):
if request.method == "POST":
form = RegisterForm(request.POST)
if form.is_valid():
form.save()
new_user = authenticate(username=form.cleaned_data['username'],
password=form.cleaned_data['password1'],
)
login(request, new_user)
return redirect('/user/profile/')
else:
form = RegisterForm()
return render(request, 'account/register.html', {'form': form})
def user_list(request):
queryset = User.objects.all() # list of objects
return render(request, 'account/userList.html', {'object_list': queryset})
def all_user_works(request):
queryset = Arts.objects.filter(user_id=request.user.id).order_by('-timestamp') # list of objects
context = {'object_list': queryset, 'user': request.user}
return render(request, 'account/all_user_works.html', context)
def art_delete(request, pk):
art_to_delete = get_object_or_404(Arts, id=pk)
try:
art_to_delete.delete()
finally:
return redirect("/user/myworks")
def profile_view(request):
if not request.user.is_authenticated:
html = "<h1>You are not logged in.</h1><a href='/login'>Log in.</a>"
return HttpResponse(html)
# za vpisane uporabnike pripravim pravi view
if request.method == "POST":
form = NewArtForm(request.POST)
form2 = TagForm(request.POST)
if form.is_valid() and form2.is_valid():
new_art = form.save(commit=False)
new_art.user_id = request.user
new_art.timestamp = datetime.now()
new_art.save()
tags_input = form2.cleaned_data['tag']
all_tags = set(tags_input.split(", "))
for tg in all_tags:
new_tag = Tags.objects.create(tag=tg)
ArtworksTags.objects.create(tag_id=new_tag, artwork_id=new_art)
context = {'form': NewArtForm(), 'new_art': new_art, "form2": form2}
return redirect('/user/myworks/')
else:
return render(request, 'account/profile.html', {'form': NewArtForm(), "form2": TagForm()})
else: # request je get
form = NewArtForm()
form2 = TagForm()
context = {'form': form, "form2": form2}
return render(request, 'account/profile.html', context)
def edit_profile(request):
if not request.user.is_authenticated:
html = "<h1>You are not logged in.</h1><a href='/login'>Log in.</a>"
return HttpResponse(html)
# za vpisane uporabnike pripravim pravi view
if request.method == 'POST':
form = EditProfileFrom(request.POST, instance=request.user)
form2 = UserDescriptionForm(request.POST)
if form.is_valid() and form2.is_valid():
# dobro je izpolnjeno, posodobim bazo
obj, created = UserDescription.objects.update_or_create(
user_id_id=request.user.id,
defaults={'description': form2.cleaned_data['description']}
)
form.save()
return redirect('/user/profile')
else:
# ce formi niso dobro izpolnjeni
form = EditProfileFrom()
form2 = UserDescriptionForm()
else:
try:
old_description = UserDescription.objects.get(user_id_id=request.user.id)
form2 = UserDescriptionForm(instance=old_description)
except Exception:
form2 = UserDescriptionForm()
form = EditProfileFrom(instance=request.user)
context = {'form': form, 'form2': form2}
return render(request, 'account/edit_profile.html', context)
return render(request, 'account/edit_profile.html', {})
def logout(request):
return render(request, 'account/logout.html', {})
| 37.741379
| 102
| 0.640247
|
b1eec386b7239e221374f6f2dc5021d6c2d0cc67
| 837
|
py
|
Python
|
sana/api/middleware/echo/urls.py
|
satvikdhandhania/vit-11
|
e599f2b82a9194658c67bbd5c7e45f3b50d016da
|
[
"BSD-3-Clause"
] | 1
|
2016-09-20T20:36:53.000Z
|
2016-09-20T20:36:53.000Z
|
sana/api/middleware/echo/urls.py
|
satvikdhandhania/vit-11
|
e599f2b82a9194658c67bbd5c7e45f3b50d016da
|
[
"BSD-3-Clause"
] | null | null | null |
sana/api/middleware/echo/urls.py
|
satvikdhandhania/vit-11
|
e599f2b82a9194658c67bbd5c7e45f3b50d016da
|
[
"BSD-3-Clause"
] | null | null | null |
'''
@author: Sana Dev Team
Created on May 18, 2011
'''
from django.conf.urls.defaults import patterns
import handlers
urlpatterns = patterns(
'',
(r'^binary/$',
handlers.binary_resource,
{},
'binary'),
(r'^client/',
handlers.client_resource,
{},
'client'),
(r'^encounter/$',
handlers.encounter_resource,
{},
'encounter'),
(r'^notification/$',
handlers.notification_resource,
{},
'notification'),
(r'^procedure/$',
handlers.procedure_resource,
{},
'procedure'),
(r'^status/$',
handlers.status_resource,
{},
'status'),
(r'^subject/$',
handlers.subject_resource,
{},
'subject'),
)
| 18.195652
| 46
| 0.476703
|
c3674877e97a6605e7d7eef510113b30704b7799
| 14,714
|
py
|
Python
|
Practise_1_Olympic Hero/Python_Olympic Hero.py
|
csk1908/ga-learner-dsmp-repo
|
ea841db0d534e6b45176b6b316fa7f2a3ca87a4a
|
[
"MIT"
] | null | null | null |
Practise_1_Olympic Hero/Python_Olympic Hero.py
|
csk1908/ga-learner-dsmp-repo
|
ea841db0d534e6b45176b6b316fa7f2a3ca87a4a
|
[
"MIT"
] | null | null | null |
Practise_1_Olympic Hero/Python_Olympic Hero.py
|
csk1908/ga-learner-dsmp-repo
|
ea841db0d534e6b45176b6b316fa7f2a3ca87a4a
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# coding: utf-8
# Problem Statement
# The Olympic Games, considered to be the world's foremost sports competition has more than 200 nations participating across the Summer and Winter Games alternating by occurring every four years but two years apart.
#
# Throughout this project, we will explore the Olympics dataset(scraped from https://en.wikipedia.org/wiki/All-time_Olympic_Games_medal_table) , look at some interesting statistics and then try to find out which country is the King of Olympic Games.
#
# About the dataset
# The snapshot of the data, you will be working on:
#
# The dataset has details of 146 countries with following 16 features
#
# Feature Description
# Country_Name Name of the country
# # Summer No. of games played in Summer Olympics
# Gold_Summer No. of gold medals won in Summer Olympics
# Silver_Summer No. of silver medals won in Summer Olympics
# Bronze_Summer No. of bronze medals won in Summer Olympics
# Total_Summer Total no. of all the medals won in Summer Olympics
# # Winter No. of games played in Winter Olympics
# Gold_Winter No. of gold medals won in Winter Olympics
# Silver_Winter No. of silver medals won in Winter Olympics
# Bronze_Winter No. of bronze medals won in Winter Olympics
# Total_Winter Total no. of all the medals won in Winter Olympics
# # Games Total no. of games played in both Summer and Winter Olympics
# Gold_Total Total no. of gold medals won in both Summer and Winter Olympics
# Silver_Total Total no. of silver medals won in both Summer and Winter Olympics
# Bronze_Total Total no. of bronze medals won in both Summer and Winter Olympics
# Total Total no. of all the medals won in both Summer and Winter Olympics
# Why solve this project?
# After completing this project, you will have a better understanding of data handling with python(pandas). In this project, you will be applying the following concepts :
#
# Dataframe operations
#
# Conditional statement and loops
#
# List operations
#
# Bar Plotting
#
# Mathematical operations
# In[2]:
import csv
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# 1. Data Loading
# Let's start with the simple task of loading the data and do a little bit of renaming.
#
# Instructions :
# Load the dataframe from the path using pd.read_csv() and store the dataframe in a variable called 'data'.
#
# In the dataframe, rename the column Total to Total_Medals
#
# Display first 10 records using "head()" function to take a look at the dataframe.
# In[3]:
data = pd.read_csv("E:\\GreyAtom_Online_04.04.2020\\Python_Olympic Hero.csv")
data.head()
data.rename(columns = {'Total':'Total_Medals'}, inplace = True)
print(data.head(10))
# In[4]:
data.info()
# 2. Summer or Winter
# Some Countries love Summer, some Winter. We think it has to do something with their Olympic performance.
#
# For this task we will try to figure out which olympic event does a country perform better in.
#
# Instructions :
# Create a new column Better_Event that stores 'Summer','Winter' or 'Both' based on the comparision between the total medals won in Summer event and Winter event (i.e. comparision between the Total_Summer and Total_Winter columns) using "np.where()"function.
# Example of np.where() function:
# data = {'name': ['A', 'B', 'C', 'D', 'E'],
# 'age': [12, 66, 22, 80, 7],
# 'gender': ['M', 'F', 'F', 'M', 'M'],
# }
# df = pd.DataFrame(data, columns = ['name', 'age', 'gender'])
#
# print("dataframe before: \n",df)
#
# """
# Creating a new column called senior_citizen where the value is yes
# if df.age is greater than 60 and no if not
# """
# df['senior_citizen'] = np.where(df['age']>=60, 'yes', 'no')
# print("dataframe after:\n",df)
# Output
#
# dataframe before:
#
# name age gender
# 0 A 12 M
# 1 B 66 F
# 2 C 22 F
# 3 D 80 M
# 4 E 7 M
#
# dataframe after:
# name age gender senior_citizen
# 0 A 12 M no
# 1 B 66 F yes
# 2 C 22 F no
# 3 D 80 M yes
# 4 E 7 M no
# Find out which has been a better event with respect to all the performing countries by using value_counts() function and store it in a new variable called 'better_event'.
# In[5]:
data['Better_Event'] = np.where(data['Total_Summer']>data['Total_Winter'],'Summer', 'Winter')
data['Better_Event'] =np.where(data['Total_Summer'] ==data['Total_Winter'],'Both',data['Better_Event'])
#print(data)
better_event = data['Better_Event'].value_counts().index.values[0]
print(better_event)
# 3. Top 10
# So we figured out which is a better event for each country. Let's move on to finding out the best performing countries across all events
#
# In this task we will try to find
#
# Which are the top 10 performing teams at summer event (with respect to total medals), winter event and overall?
# How many teams are present in all of the three lists above?
# Instructions :
# Create a new dataframe subset called 'top_countries' with the columns ['Country_Name','Total_Summer', 'Total_Winter','Total_Medals'] only
#
# Drop the last row from 'top_countries'(The last row contains the sum of the medals)
#
# Create a function called 'top_ten' that:
#
# Takes the dataframe 'top_countries' and a column name as parameters.
#
# Creates a new empty list called 'country_list'
#
# Find the top 10 values for that particular column(for e.g. 'Total_Summer') using "nlargest()" function
#
# From the dataframe returned by nlargest function, slices the Country_Name column and stores it in the 'country_list' list
#
# Returns the 'country_list'
#
# Example of 'nlargest()' function :
# df = pd.DataFrame({'ID': [1, 2, 3, 4, 5],
# 'Score': [33, 92, 26, 75, 80]})
#
# print("The dataframe:\n",df)
# # Filtering the 3 largest scores and getting the IDs associated with it
# top_3=df.nlargest(3, 'Score')
# print("df having top 3 scores:")
# print(top_3)
# print("IDs associated to top 3:")
# print(list(top_3['ID']))
# Output
#
# The dataframe:
# ID Score
# 0 1 33
# 1 2 92
# 2 3 26
# 3 4 75
# 4 5 80
# df having top 3 scores:
# ID Score
# 1 2 92
# 4 5 80
# 3 4 75
# IDs associated to top 3:
# [2, 5, 4]
# Parameters :
#
# parameter dtype Argument Type default value description
# variable1 pandas.DataFrame compulsory dataframe to be loaded
# variable2 string compulsory column name
# Returns:
#
# returns dtype description
# variable1 list list containing countries names
# Call the 'top_ten()' function for the three columns :Total_Summer,Total_Winter and Total_Medals and store their respective results in lists called 'top_10_summer', 'top_10_winter' and 'top_10'
#
# Create a new list 'common' that stores the common elements between the three lists('top_10_summer', 'top_10_winter' and 'top_10')
# In[ ]:
# In[6]:
top_countries = data[['Country_Name','Total_Summer', 'Total_Winter','Total_Medals']]
print(top_countries.tail())
top_countries.drop(index=146,axis=0,inplace=True)
print(top_countries.tail())
# In[ ]:
# In[7]:
def top_ten(v1,v2):
country_list = []
#x = v1.nlargest(10,v2)
#country_list = x['Country_Name']
country_list = v1.nlargest(10,v2)['Country_Name']
country_list = list(country_list)
return(country_list)
top_10_summer = top_ten(top_countries,'Total_Summer')
print('Top 10 countries for SUMMER are \n',top_10_summer)
top_10_winter = top_ten(top_countries,'Total_Winter')
print('Top 10 countries for WINTER are \n',top_10_winter)
top_10 = top_ten(top_countries,'Total_Medals')
print('Top 10 countries who got TOTAL MEDALS are \n',top_10)
type(top_10)
common = [value for value in top_10_summer if value in top_10_winter and value in top_10]
print('Countries common in all the three ist are \n ',common)
"""
def intersection(l1,l2,l3):
l4 = [value for value in l1 if value in l2 and value in l3]
return l4
common = intersection (top_10_summer,top_10_winter,top_10)
print(common)
"""
# 4. Plotting Top 10
# From the lists that you have created from the previous task, let's plot the medal count of the top 10 countries for better visualisation
#
# Instructions :
# Take the three previously created lists(top_10_summer, top_10_winter, top_10)
#
# Subset the dataframe 'data' based on the country names present in the list top_10_summer using "isin()" function on the column Country_Name. Store the new subsetted dataframes in 'summer_df'. Do the similar operation using top_10_winter and top_10 and store the subset dataframes in 'winter_df' & 'top_df' respectively.
#
# Example of isin() function:
# df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': ['Alpha', 'Beta', 'Gamma','Delta','Epsilon'], 'C':[1, 4, 9, 16, 25]})
# #List
# List= ['Beta','Epsilon']
#
# #Usage of isin() function
# subset_df=df[df['B'].isin(List)]
#
# print(subset_df)
# Output
#
# A B C
# 1 2 Beta 4
# 4 5 Epsilon 25
# Take each subsetted dataframe and plot a bar graph between the country name and total medal count according to the event (For e.g. for 'summer_df' plot a bar graph between Country_Name and Total_Summer)
#
# Modify the axes info accordingly
# In[8]:
#Code starts here
summer_df = data[data['Country_Name'].isin(top_10_summer)]
print('Summer_dataframe is \n', summer_df.head())
winter_df = data[data['Country_Name'].isin(top_10_winter)]
print('Winter_dataframe is\n',winter_df.head())
top_df = data[data['Country_Name'].isin(top_10)]
print('Total_dataframe is\n',top_df.head())
#type_2.plot(kind='bar')
#Summer_df
plt.figure(figsize=[14,8])
plt.title("Total Medals won in Summer by top 10 countries")
plt.xlabel("Name of the Country")
plt.ylabel("Total Medals")
plt.bar(summer_df['Country_Name'],summer_df['Total_Summer'])
plt.show()
#Winter_df
plt.figure(figsize=[14,8])
plt.title("Total Medals won in Winter by top 10 countries")
plt.xlabel("Name of the Country")
plt.ylabel("Total Medals")
plt.bar(summer_df['Country_Name'],summer_df['Total_Winter'])
plt.show()
#Total_df
plt.figure(figsize=[14,8])
plt.title("Total Medals won in Summer and Winter by top 10 countries")
plt.xlabel("Name of the Country")
plt.ylabel("Total Medals")
plt.bar(summer_df['Country_Name'],summer_df['Total_Medals'])
plt.show()
# 6. Top performing country(Gold)
# Winning silver or bronze medals is a big achievement but winning gold is bigger.
#
# Using the above created dataframe subsets, in this task let's find out which country has had the best performance with respect to the ratio between gold medals won and total medals won.
#
# Instructions :
# In the dataframe 'summer_df'(created in the previous function) , create a new column Golden_Ratio which is the quotient after dividing the two columns Gold_Summer and Total_Summer.
#
# Find the max value of Golden_Ratio and the country associated with it and store them in summer_max_ratio and summer_country_gold respectively.
#
# In the dataframe 'winter_df'(created in the previous function) , create a new column Golden_Ratio which is the quotient after dividing the two columns Gold_Winter and Total_Winter.
#
# Find the max value of Golden_Ratio and the country associated with it and store them in 'winter_max_ratio' and 'winter_country_gold' respectively.
#
# In the dataframe top_df'(created in the previous function) , create a new column Golden_Ratio which is the quotient after dividing the two columns Gold_Total and Total_Medals.
#
# Find the max value of Golden_Ratio and the country associated with it and store them in top_max_ratio' and 'top_country_gold' respectively.
# In[9]:
#Code starts here
summer_df['Golden_Ratio'] = round(summer_df['Gold_Summer']/summer_df['Total_Summer'],2)
print(summer_df.head())
summer_max_ratio = summer_df['Golden_Ratio'].max()
print(summer_max_ratio)
summer_country_gold = summer_df.loc[summer_df['Golden_Ratio'].idxmax(),'Country_Name']
print(summer_country_gold)
winter_df['Golden_Ratio'] = round(winter_df['Gold_Winter']/summer_df['Total_Winter'],2)
print(winter_df.head())
winter_max_ratio = winter_df['Golden_Ratio'].max()
print(winter_max_ratio)
winter_country_gold = winter_df.loc[winter_df['Golden_Ratio'].idxmax(),'Country_Name']
print(winter_country_gold)
top_df['Golden_Ratio'] = round(top_df['Gold_Total']/top_df['Total_Medals'],2)
print(winter_df.head())
top_max_ratio = top_df['Golden_Ratio'].max()
print(top_max_ratio)
top_country_gold = top_df.loc[top_df['Golden_Ratio'].idxmax(),'Country_Name']
print(top_country_gold)
# 7. Best in the world
# Winning Gold is great but is winning most gold equivalent to being the best overall perfomer? Let's find out.
#
# Instructions :
# Drop the last row from the dataframe(The last row contains the total of all the values calculated vertically) and save the result in 'data_1'
#
# Update the dataframe 'data_1' to include a new column called Total_Points which is a weighted value where each gold medal counts for 3 points, silver medals for 2 points, and bronze medals for 1 point.(i.e. You need to take weighted value of Gold_Total, Silver_Total and Bronze_Total)
#
# Find the max value of Total_Points in 'data_1' and the country assosciated with it and store it in variables 'most_points' and 'best_country' respectively.
# In[10]:
data_1=data[:-1]
data_1['Total_Points']= data_1['Gold_Total']*3 + data_1['Silver_Total']*2 + data_1['Bronze_Total']*1
print(data_1.head())
most_points = data_1['Total_Points'].max()
print(most_points)
best_country = data_1.loc[data_1['Total_Points'].idxmax(),'Country_Name']
print(best_country)
# Plot for the best
# We know which country is best when it comes to winning the most points in Olympic Games. Let's plot the medal count to visualise their success better.
#
# Instructions
# Create a single row dataframe called 'best' from 'data' where value of column Country_Name is equal to 'best_country'(The variable you created in the previous task)
#
# Subset 'best' even further by only including the columns : ['Gold_Total','Silver_Total','Bronze_Total']
#
# Create a stacked bar plot of 'best' using "DataFrame.plot.bar()" function
#
# Name the x-axis as United States using "plt.xlabel()"
#
# Name the y-axis as Medals Tally using "plt.ylabel()"
#
# Rotate the labels of x-axis by 45o using "plt.xticks()"
# In[12]:
best = data[data['Country_Name'] == best_country]
print(best)
print(type(best))
best = best[['Gold_Total','Silver_Total','Bronze_Total']]
print(best)
best.plot(kind='bar', stacked=True)
plt.xlabel("United States")
plt.ylabel("Medals Tally")
plt.xticks(rotation = 45)
plt.show()
# In[25]:
# In[ ]:
| 32.84375
| 321
| 0.722441
|
9fa768b4e784735bb1f6b6d19c1458f5e29d73b9
| 11,809
|
py
|
Python
|
bin/Python27/Lib/site-packages/sympy/combinatorics/prufer.py
|
lefevre-fraser/openmeta-mms
|
08f3115e76498df1f8d70641d71f5c52cab4ce5f
|
[
"MIT"
] | null | null | null |
bin/Python27/Lib/site-packages/sympy/combinatorics/prufer.py
|
lefevre-fraser/openmeta-mms
|
08f3115e76498df1f8d70641d71f5c52cab4ce5f
|
[
"MIT"
] | null | null | null |
bin/Python27/Lib/site-packages/sympy/combinatorics/prufer.py
|
lefevre-fraser/openmeta-mms
|
08f3115e76498df1f8d70641d71f5c52cab4ce5f
|
[
"MIT"
] | null | null | null |
from sympy.core import Basic
from sympy.core.compatibility import iterable, as_int
from sympy.utilities.iterables import flatten
from collections import defaultdict
class Prufer(Basic):
"""
The Prufer correspondence is an algorithm that describes the
bijection between labeled trees and the Prufer code. A Prufer
code of a labeled tree is unique up to isomorphism and has
a length of n - 2.
Prufer sequences were first used by Heinz Prufer to give a
proof of Cayley's formula.
References
==========
.. [1] http://mathworld.wolfram.com/LabeledTree.html
"""
_prufer_repr = None
_tree_repr = None
_nodes = None
_rank = None
@property
def prufer_repr(self):
"""Returns Prufer sequence for the Prufer object.
This sequence is found by removing the highest numbered vertex,
recording the node it was attached to, and continuuing until only
two verices remain. The Prufer sequence is the list of recorded nodes.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]).prufer_repr
[3, 3, 3, 4]
>>> Prufer([1, 0, 0]).prufer_repr
[1, 0, 0]
See Also
========
to_prufer
"""
if self._prufer_repr is None:
self._prufer_repr = self.to_prufer(self._tree_repr[:], self.nodes)
return self._prufer_repr
@property
def tree_repr(self):
"""Returns the tree representation of the Prufer object.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]).tree_repr
[[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]
>>> Prufer([1, 0, 0]).tree_repr
[[1, 2], [0, 1], [0, 3], [0, 4]]
See Also
========
to_tree
"""
if self._tree_repr is None:
self._tree_repr = self.to_tree(self._prufer_repr[:])
return self._tree_repr
@property
def nodes(self):
"""Returns the number of nodes in the tree.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]]).nodes
6
>>> Prufer([1, 0, 0]).nodes
5
"""
return self._nodes
@property
def rank(self):
"""Returns the rank of the Prufer sequence.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> p = Prufer([[0, 3], [1, 3], [2, 3], [3, 4], [4, 5]])
>>> p.rank
778
>>> p.next(1).rank
779
>>> p.prev().rank
777
See Also
========
prufer_rank, next, prev, size
"""
if self._rank is None:
self._rank = self.prufer_rank()
return self._rank
@property
def size(self):
"""Return the number of possible trees of this Prufer object.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> Prufer([0]*4).size == Prufer([6]*4).size == 1296
True
See Also
========
prufer_rank, rank, next, prev
"""
return self.prev(self.rank).prev().rank + 1
@staticmethod
def to_prufer(tree, n):
"""Return the Prufer sequence for a tree given as a list of edges where
``n`` is the number of nodes in the tree.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> a = Prufer([[0, 1], [0, 2], [0, 3]])
>>> a.prufer_repr
[0, 0]
>>> Prufer.to_prufer([[0, 1], [0, 2], [0, 3]], 4)
[0, 0]
See Also
========
prufer_repr: returns Prufer sequence of a Prufer object.
"""
d = defaultdict(int)
L = []
for edge in tree:
# Increment the value of the corresponding
# node in the degree list as we encounter an
# edge involving it.
d[edge[0]] += 1
d[edge[1]] += 1
for i in xrange(n - 2):
# find the smallest leaf
for x in xrange(n):
if d[x] == 1:
break
# find the node it was connected to
y = None
for edge in tree:
if x == edge[0]:
y = edge[1]
elif x == edge[1]:
y = edge[0]
if y is not None:
break
# record and update
L.append(y)
for j in (x, y):
d[j] -= 1
if not d[j]:
d.pop(j)
tree.remove(edge)
return L
@staticmethod
def to_tree(prufer):
"""Return the tree (as a list of edges) of the given Prufer sequence.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> a = Prufer([0, 2], 4)
>>> a.tree_repr
[[0, 1], [0, 2], [2, 3]]
>>> Prufer.to_tree([0, 2])
[[0, 1], [0, 2], [2, 3]]
References
==========
- http://hamberg.no/erlend/2010/11/06/prufer-sequence/
See Also
========
tree_repr: returns tree representation of a Prufer object.
"""
tree = []
last = []
n = len(prufer) + 2
d = defaultdict(lambda: 1)
for p in prufer:
d[p] += 1
for i in prufer:
for j in xrange(n):
# find the smallest leaf (degree = 1)
if d[j] == 1:
break
# (i, j) is the new edge that we append to the tree
# and remove from the degree dictionary
d[i] -= 1
d[j] -= 1
tree.append(sorted([i, j]))
last = [i for i in xrange(n) if d[i] == 1] or [0, 1]
tree.append(last)
return tree
@staticmethod
def edges(*runs):
"""Return a list of edges and the number of nodes from the given runs
that connect nodes in an integer-labelled tree.
All node numbers will be shifted so that the minimum node is 0. It is
not a problem if edges are repeated in the runs; only unique edges are
returned. There is no assumption made about what the range of the node
labels should be, but all nodes from the smallest through the largest
must be present.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> Prufer.edges([1, 2, 3], [2, 4, 5]) # a T
([[0, 1], [3, 4], [1, 2], [1, 3]], 5)
Duplicate edges are removed:
>>> Prufer.edges([0, 1, 2, 3], [1, 4, 5], [1, 4, 6]) # a K
([[0, 1], [1, 2], [4, 6], [4, 5], [1, 4], [2, 3]], 7)
"""
e = set()
nmin = runs[0][0]
for r in runs:
for i in range(len(r)-1):
a, b = r[i: i + 2]
if b < a:
a, b = b, a
e.add((a, b))
rv = []
got = set()
nmin = nmax = None
while e:
ei = e.pop()
for i in ei:
got.add(i)
nmin = min(ei[0], nmin) if nmin != None else ei[0]
nmax = max(ei[1], nmax) if nmax != None else ei[1]
rv.append(list(ei))
missing = set(range(nmin, nmax + 1)) - got
if missing:
missing = [i + nmin for i in missing]
if len(missing) == 1:
msg = 'Node %s is missing.' % missing.pop()
else:
msg = 'Nodes %s are missing.' % list(sorted(missing))
raise ValueError(msg)
if nmin != 0:
for i, ei in enumerate(rv):
rv[i] = [n - nmin for n in ei]
nmax -= nmin
return rv, nmax + 1
def prufer_rank(self):
"""Computes the rank of a Prufer sequence.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> a = Prufer([[0, 1], [0, 2], [0, 3]])
>>> a.prufer_rank()
0
See Also
========
rank, next, prev, size
"""
r = 0
p = 1
for i in xrange(self.nodes - 3, -1, -1):
r += p*self.prufer_repr[i]
p *= self.nodes
return r
@classmethod
def unrank(self, rank, n):
"""Finds the unranked Prufer sequence.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> Prufer.unrank(0, 4)
Prufer([0, 0])
"""
n, rank = as_int(n), as_int(rank)
L = defaultdict(int)
for i in xrange(n - 3, -1, -1):
L[i] = rank % n
rank = (rank - L[i])//n
return Prufer([L[i] for i in xrange(len(L))])
def __new__(cls, *args, **kw_args):
"""The constructor for the Prufer object.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
A Prufer object can be constructed from a list of edges:
>>> a = Prufer([[0, 1], [0, 2], [0, 3]])
>>> a.prufer_repr
[0, 0]
If the number of nodes is given, no checking of the nodes will
be performed; it will be assumed that nodes 0 through n - 1 are
present:
>>> Prufer([[0, 1], [0, 2], [0, 3]], 4)
Prufer([[0, 1], [0, 2], [0, 3]], 4)
A Prufer object can be constructed from a Prufer sequence:
>>> b = Prufer([1, 3])
>>> b.tree_repr
[[0, 1], [1, 3], [2, 3]]
"""
ret_obj = Basic.__new__(cls, *args, **kw_args)
args = [list(args[0])]
if args[0] and iterable(args[0][0]):
if not args[0][0]:
raise ValueError('Prufer expects at least one edge in the tree.')
if len(args) > 1:
nnodes = args[1]
else:
nodes = set(flatten(args[0]))
nnodes = max(nodes) + 1
if nnodes != len(nodes):
missing = set(range(nnodes)) - nodes
if len(missing) == 1:
msg = 'Node %s is missing.' % missing.pop()
else:
msg = 'Nodes %s are missing.' % list(sorted(missing))
raise ValueError(msg)
ret_obj._tree_repr = [list(i) for i in args[0]]
ret_obj._nodes = nnodes
else:
ret_obj._prufer_repr = args[0]
ret_obj._nodes = len(ret_obj._prufer_repr) + 2
return ret_obj
def next(self, delta=1):
"""Generates the Prufer sequence that is delta beyond the current one.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> a = Prufer([[0, 1], [0, 2], [0, 3]])
>>> b = a.next(1) # == a.next()
>>> b.tree_repr
[[0, 2], [0, 1], [1, 3]]
>>> b.rank
1
See Also
========
prufer_rank, rank, prev, size
"""
return Prufer.unrank(self.rank + delta, self.nodes)
def prev(self, delta=1):
"""Generates the Prufer sequence that is -delta before the current one.
Examples
========
>>> from sympy.combinatorics.prufer import Prufer
>>> a = Prufer([[0, 1], [1, 2], [2, 3], [1, 4]])
>>> a.rank
36
>>> b = a.prev()
>>> b
Prufer([1, 2, 0])
>>> b.rank
35
See Also
========
prufer_rank, rank, next, size
"""
return Prufer.unrank(self.rank - delta, self.nodes)
| 27.399072
| 81
| 0.473791
|
2fcd2959ad9fc1c976eba5a80209d279b3d87709
| 3,068
|
py
|
Python
|
braille_experience/braille_translators/mapAlphaToBraille.py
|
firekim2/testserver
|
0ebd7be0e254fa825dad8be314fbfcb7b03f7a30
|
[
"MIT"
] | null | null | null |
braille_experience/braille_translators/mapAlphaToBraille.py
|
firekim2/testserver
|
0ebd7be0e254fa825dad8be314fbfcb7b03f7a30
|
[
"MIT"
] | null | null | null |
braille_experience/braille_translators/mapAlphaToBraille.py
|
firekim2/testserver
|
0ebd7be0e254fa825dad8be314fbfcb7b03f7a30
|
[
"MIT"
] | null | null | null |
# Contains dictionaries that map English letters to braille.
letters = {'a': chr(10241),
'b': chr(10243),
'c': chr(10249),
'd': chr(10265),
'e': chr(10257),
'f': chr(10251),
'g': chr(10267),
'h': chr(10259),
'i': chr(10250),
'j': chr(10266),
'k': chr(10245),
'l': chr(10247),
'm': chr(10253),
'n': chr(10269),
'o': chr(10261),
'p': chr(10255),
'q': chr(10271),
'r': chr(10263),
's': chr(10254),
't': chr(10270),
'u': chr(10277),
'v': chr(10279),
'w': chr(10298),
'x': chr(10285),
'y': chr(10301),
'z': chr(10293)}
contractions = {'but': chr(10243),
'can': chr(10249),
'do': chr(10265),
'every': chr(10257),
'from': chr(10251),
'go': chr(10267),
'have': chr(10259),
'just': chr(10266),
'knowledge': chr(10280),
'like': chr(10296),
'more': chr(10253),
'not': chr(10269),
'people': chr(10255),
'quite': chr(10271),
'rather': chr(10263),
'so': chr(10254),
'that': chr(10270),
'us': chr(10277),
'very': chr(10279),
'it': chr(10285),
'you': chr(10301),
'as': chr(10293),
'and': chr(10287),
'for': chr(10303),
'of': chr(10295),
'the': chr(10286),
'with': chr(10302),
'will': chr(10298),
'his': chr(10278),
'in': chr(10260),
'was': chr(10292),
'to': chr(10262)}
punctuation = {',': chr(10242),
';': chr(10246),
':': chr(10258),
'.': chr(10290),
'!': chr(10262),
'(': chr(10294),
')': chr(10294),
'“': chr(10278),
'”': chr(10292),
'?': chr(10278),
'/': chr(10252),
'#': chr(10300),
'\'': chr(10244),
'…': chr(10290) + chr(10290) + chr(10290),
'’': chr(10244),
'': chr(10276),
'-': chr(10276),
'‐': chr(10276),
'‑': chr(10276),
'‒': chr(10276),
'–': chr(10276),
'—': chr(10276),
'―': chr(10276)}
numbers = {'1': chr(10241),
'2': chr(10243),
'3': chr(10249),
'4': chr(10265),
'5': chr(10257),
'6': chr(10251),
'7': chr(10267),
'8': chr(10259),
'9': chr(10250),
'0': chr(10266)}
| 31.628866
| 61
| 0.3191
|
0bf92279ccb15fcd06d5b4abcacf6f23dc7bb1aa
| 16,309
|
py
|
Python
|
sfs/mono/source.py
|
vishwesh-vishwesh/HiWi-job
|
8953eb744f6e03191b94869e833b44efe74f7bd8
|
[
"MIT"
] | null | null | null |
sfs/mono/source.py
|
vishwesh-vishwesh/HiWi-job
|
8953eb744f6e03191b94869e833b44efe74f7bd8
|
[
"MIT"
] | null | null | null |
sfs/mono/source.py
|
vishwesh-vishwesh/HiWi-job
|
8953eb744f6e03191b94869e833b44efe74f7bd8
|
[
"MIT"
] | null | null | null |
"""Compute the sound field generated by a sound source.
.. plot::
:context: reset
import sfs
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = 8, 4.5 # inch
x0 = 1.5, 1, 0
f = 500 # Hz
omega = 2 * np.pi * f
normalization_point = 4 * np.pi
normalization_line = \\
np.sqrt(8 * np.pi * omega / sfs.defs.c) * np.exp(1j * np.pi / 4)
grid = sfs.util.xyz_grid([-2, 3], [-1, 2], 0, spacing=0.02)
# Grid for vector fields:
vgrid = sfs.util.xyz_grid([-2, 3], [-1, 2], 0, spacing=0.1)
"""
import itertools
import numpy as np
from scipy import special
from .. import util
from .. import defs
def point(omega, x0, n0, grid, c=None):
"""Point source.
Notes
-----
::
1 e^(-j w/c |x-x0|)
G(x-x0, w) = --- -----------------
4pi |x-x0|
Examples
--------
.. plot::
:context: close-figs
p = sfs.mono.source.point(omega, x0, None, grid)
sfs.plot.soundfield(p, grid)
plt.title("Point Source at {} m".format(x0))
Normalization ...
.. plot::
:context: close-figs
sfs.plot.soundfield(p * normalization_point, grid,
colorbar_kwargs=dict(label="p / Pa"))
plt.title("Point Source at {} m (normalized)".format(x0))
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)
grid = util.as_xyz_components(grid)
r = np.linalg.norm(grid - x0)
return 1 / (4*np.pi) * np.exp(-1j * k * r) / r
def point_velocity(omega, x0, n0, grid, c=None):
"""Velocity of a point source.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
Examples
--------
The particle velocity can be plotted on top of the sound pressure:
.. plot::
:context: close-figs
v = sfs.mono.source.point_velocity(omega, x0, None, vgrid)
sfs.plot.soundfield(p * normalization_point, grid)
sfs.plot.vectors(v * normalization_point, vgrid)
plt.title("Sound Pressure and Particle Velocity")
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)
grid = util.as_xyz_components(grid)
offset = grid - x0
r = np.linalg.norm(offset)
v = point(omega, x0, n0, grid, c=c)
v *= (1+1j*k*r) / (defs.rho0 * defs.c * 1j*k*r)
return util.XyzComponents([v * o / r for o in offset])
def point_dipole(omega, x0, n0, grid, c=None):
"""Point source with dipole characteristics.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
n0 : (3,) array_like
Normal vector (direction) of dipole.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
Notes
-----
::
d 1 / iw 1 \ (x-x0) n0
---- G(x-x0,w) = --- | ----- + ------- | ----------- e^(-i w/c |x-x0|)
d ns 4pi \ c |x-x0| / |x-x0|^2
Examples
--------
.. plot::
:context: close-figs
n0 = 0, 1, 0
p = sfs.mono.source.point_dipole(omega, x0, n0, grid)
sfs.plot.soundfield(p, grid)
plt.title("Dipole Point Source at {} m".format(x0))
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)
n0 = util.asarray_1d(n0)
grid = util.as_xyz_components(grid)
offset = grid - x0
r = np.linalg.norm(offset)
return 1 / (4*np.pi) * (1j * k + 1 / r) * np.inner(offset, n0) / \
np.power(r, 2) * np.exp(-1j * k * r)
def point_modal(omega, x0, n0, grid, L, N=None, deltan=0, c=None):
"""Point source in a rectangular room using a modal room model.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
n0 : (3,) array_like
Normal vector (direction) of source (only required for
compatibility).
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
L : (3,) array_like
Dimensionons of the rectangular room.
N : (3,) array_like or int, optional
For all three spatial dimensions per dimension maximum order or
list of orders. A scalar applies to all three dimensions. If no
order is provided it is approximately determined.
deltan : float, optional
Absorption coefficient of the walls.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)
x, y, z = util.as_xyz_components(grid)
if np.isscalar(N):
N = N * np.ones(3, dtype=int)
if N is None:
N = [None, None, None]
orders = [0, 0, 0]
for i in range(3):
if N[i] is None:
# compute max order
orders[i] = range(int(np.ceil(L[i]/np.pi * k) + 1))
elif np.isscalar(N[i]):
# use given max order
orders[i] = range(N[i] + 1)
else:
# use given orders
orders[i] = N[i]
kmp0 = [((kx + 1j * deltan)**2, np.cos(kx * x) * np.cos(kx * x0[0]))
for kx in [m * np.pi / L[0] for m in orders[0]]]
kmp1 = [((ky + 1j * deltan)**2, np.cos(ky * y) * np.cos(ky * x0[1]))
for ky in [n * np.pi / L[1] for n in orders[1]]]
kmp2 = [((kz + 1j * deltan)**2, np.cos(kz * z) * np.cos(kz * x0[2]))
for kz in [l * np.pi / L[2] for l in orders[2]]]
ksquared = k**2
p = 0
for (km0, p0), (km1, p1), (km2, p2) in itertools.product(kmp0, kmp1, kmp2):
km = km0 + km1 + km2
p = p + 8 / (ksquared - km) * p0 * p1 * p2
return p
def point_modal_velocity(omega, x0, n0, grid, L, N=None, deltan=0, c=None):
"""Velocity of point source in a rectangular room using a modal room model.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
n0 : (3,) array_like
Normal vector (direction) of source (only required for
compatibility).
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
L : (3,) array_like
Dimensionons of the rectangular room.
N : (3,) array_like or int, optional
Combination of modal orders in the three-spatial dimensions to
calculate the sound field for or maximum order for all
dimensions. If not given, the maximum modal order is
approximately determined and the sound field is computed up to
this maximum order.
deltan : float, optional
Absorption coefficient of the walls.
c : float, optional
Speed of sound.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)
x, y, z = util.as_xyz_components(grid)
if N is None:
# determine maximum modal order per dimension
Nx = int(np.ceil(L[0]/np.pi * k))
Ny = int(np.ceil(L[1]/np.pi * k))
Nz = int(np.ceil(L[2]/np.pi * k))
mm = range(Nx)
nn = range(Ny)
ll = range(Nz)
elif np.isscalar(N):
# compute up to a given order
mm = range(N)
nn = range(N)
ll = range(N)
else:
# compute field for one order combination only
mm = [N[0]]
nn = [N[1]]
ll = [N[2]]
kmp0 = [((kx + 1j * deltan)**2, np.sin(kx * x) * np.cos(kx * x0[0]))
for kx in [m * np.pi / L[0] for m in mm]]
kmp1 = [((ky + 1j * deltan)**2, np.sin(ky * y) * np.cos(ky * x0[1]))
for ky in [n * np.pi / L[1] for n in nn]]
kmp2 = [((kz + 1j * deltan)**2, np.sin(kz * z) * np.cos(kz * x0[2]))
for kz in [l * np.pi / L[2] for l in ll]]
ksquared = k**2
vx = 0+0j
vy = 0+0j
vz = 0+0j
for (km0, p0), (km1, p1), (km2, p2) in itertools.product(kmp0, kmp1, kmp2):
km = km0 + km1 + km2
vx = vx - 8*1j / (ksquared - km) * p0
vy = vy - 8*1j / (ksquared - km) * p1
vz = vz - 8*1j / (ksquared - km) * p2
return util.XyzComponents([vx, vy, vz])
def point_image_sources(omega, x0, n0, grid, L, max_order, coeffs=None,
c=None):
"""Point source in a rectangular room using the mirror image source model.
Parameters
----------
omega : float
Frequency of source.
x0 : (3,) array_like
Position of source.
n0 : (3,) array_like
Normal vector (direction) of source (only required for
compatibility).
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
L : (3,) array_like
Dimensions of the rectangular room.
max_order : int
Maximum number of reflections for each image source.
coeffs : (6,) array_like, optional
Reflection coeffecients of the walls.
If not given, the reflection coefficients are set to one.
c : float, optional
Speed of sound.
Returns
-------
numpy.ndarray
Sound pressure at positions given by *grid*.
"""
if coeffs is None:
coeffs = np.ones(6)
xs, order = util.image_sources_for_box(x0, L, max_order)
source_strengths = np.prod(coeffs**order, axis=1)
p = 0
for position, strength in zip(xs, source_strengths):
if strength != 0:
p += strength * point(omega, position, n0, grid, c)
return p
def line(omega, x0, n0, grid, c=None):
"""Line source parallel to the z-axis.
Note: third component of x0 is ignored.
Notes
-----
::
(2)
G(x-x0, w) = -j/4 H0 (w/c |x-x0|)
Examples
--------
.. plot::
:context: close-figs
p = sfs.mono.source.line(omega, x0, None, grid)
sfs.plot.soundfield(p, grid)
plt.title("Line Source at {} m".format(x0[:2]))
Normalization ...
.. plot::
:context: close-figs
sfs.plot.soundfield(p * normalization_line, grid,
colorbar_kwargs=dict(label="p / Pa"))
plt.title("Line Source at {} m (normalized)".format(x0[:2]))
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)[:2] # ignore z-component
grid = util.as_xyz_components(grid)
r = np.linalg.norm(grid[:2] - x0)
p = -1j/4 * _hankel2_0(k * r)
return _duplicate_zdirection(p, grid)
def line_velocity(omega, x0, n0, grid, c=None):
"""Velocity of line source parallel to the z-axis.
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
Examples
--------
The particle velocity can be plotted on top of the sound pressure:
.. plot::
:context: close-figs
v = sfs.mono.source.line_velocity(omega, x0, None, vgrid)
sfs.plot.soundfield(p * normalization_line, grid)
sfs.plot.vectors(v * normalization_line, vgrid)
plt.title("Sound Pressure and Particle Velocity")
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)[:2] # ignore z-component
grid = util.as_xyz_components(grid)
offset = grid[:2] - x0
r = np.linalg.norm(offset)
v = -1/(4*defs.c*defs.rho0) * special.hankel2(1, k * r)
v = [v * o / r for o in offset]
assert v[0].shape == v[1].shape
if len(grid) > 2:
v.append(np.zeros_like(v[0]))
return util.XyzComponents([_duplicate_zdirection(vi, grid) for vi in v])
def line_dipole(omega, x0, n0, grid, c=None):
"""Line source with dipole characteristics parallel to the z-axis.
Note: third component of x0 is ignored.
Notes
-----
::
(2)
G(x-x0, w) = jk/4 H1 (w/c |x-x0|) cos(phi)
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)[:2] # ignore z-components
n0 = util.asarray_1d(n0)[:2]
grid = util.as_xyz_components(grid)
dx = grid[:2] - x0
r = np.linalg.norm(dx)
p = 1j*k/4 * special.hankel2(1, k * r) * np.inner(dx, n0) / r
return _duplicate_zdirection(p, grid)
def line_dirichlet_edge(omega, x0, grid, alpha=3/2*np.pi, Nc=None, c=None):
"""Line source scattered at an edge with Dirichlet boundary conditions.
:cite:`Moser2012`, eq.(10.18/19)
Parameters
----------
omega : float
Angular frequency.
x0 : (3,) array_like
Position of line source.
grid : triple of array_like
The grid that is used for the sound field calculations.
See `sfs.util.xyz_grid()`.
alpha : float, optional
Outer angle of edge.
Nc : int, optional
Number of elements for series expansion of driving function.
Estimated if not given.
c : float, optional
Speed of sound
Returns
-------
numpy.ndarray
Complex pressure at grid positions.
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)
phi_s = np.arctan2(x0[1], x0[0])
if phi_s < 0:
phi_s = phi_s + 2*np.pi
r_s = np.linalg.norm(x0)
grid = util.XyzComponents(grid)
r = np.linalg.norm(grid[:2])
phi = np.arctan2(grid[1], grid[0])
phi = np.where(phi < 0, phi+2*np.pi, phi)
if Nc is None:
Nc = np.ceil(2 * k * np.max(r) * alpha/np.pi)
epsilon = np.ones(Nc) # weights for series expansion
epsilon[0] = 2
p = np.zeros((grid[0].shape[1], grid[1].shape[0]), dtype=complex)
idxr = (r <= r_s)
idxa = (phi <= alpha)
for m in np.arange(Nc):
nu = m*np.pi/alpha
f = 1/epsilon[m] * np.sin(nu*phi_s) * np.sin(nu*phi)
p[idxr & idxa] = p[idxr & idxa] + f[idxr & idxa] * \
special.jn(nu, k*r[idxr & idxa]) * special.hankel2(nu, k*r_s)
p[~idxr & idxa] = p[~idxr & idxa] + f[~idxr & idxa] * \
special.jn(nu, k*r_s) * special.hankel2(nu, k*r[~idxr & idxa])
p = p * -1j*np.pi/alpha
pl = line(omega, x0, None, grid, c=c)
p[~idxa] = pl[~idxa]
return p
def plane(omega, x0, n0, grid, c=None):
"""Plane wave.
Notes
-----
::
G(x, w) = e^(-i w/c n x)
Examples
--------
.. plot::
:context: close-figs
direction = 45 # degree
n0 = sfs.util.direction_vector(np.radians(direction))
p = sfs.mono.source.plane(omega, x0, n0, grid)
sfs.plot.soundfield(p, grid, colorbar_kwargs=dict(label="p / Pa"))
plt.title("Plane wave with direction {} degree".format(direction))
"""
k = util.wavenumber(omega, c)
x0 = util.asarray_1d(x0)
n0 = util.normalize_vector(n0)
grid = util.as_xyz_components(grid)
return np.exp(-1j * k * np.inner(grid - x0, n0))
def plane_velocity(omega, x0, n0, grid, c=None):
"""Velocity of a plane wave.
Notes
-----
::
V(x, w) = 1/(rho c) e^(-i w/c n x) n
Returns
-------
`XyzComponents`
Particle velocity at positions given by *grid*.
Examples
--------
The particle velocity can be plotted on top of the sound pressure:
.. plot::
:context: close-figs
v = sfs.mono.source.plane_velocity(omega, x0, n0, vgrid)
sfs.plot.soundfield(p, grid)
sfs.plot.vectors(v, vgrid)
plt.title("Sound Pressure and Particle Velocity")
"""
v = plane(omega, x0, n0, grid, c=c) / (defs.rho0 * defs.c)
return util.XyzComponents([v * n for n in n0])
def _duplicate_zdirection(p, grid):
"""If necessary, duplicate field in z-direction."""
gridshape = np.broadcast(*grid).shape
if len(gridshape) > 2:
return np.tile(p, [1, 1, gridshape[2]])
else:
return p
def _hankel2_0(x):
"""Wrapper for Hankel function of the second type using fast versions
of the Bessel functions of first/second kind in scipy"""
return special.j0(x)-1j*special.y0(x)
| 27.974271
| 79
| 0.559384
|
adff23053e45aaca10579c0b0de3a70d1d48c88d
| 1,646
|
py
|
Python
|
src/models/fft.py
|
charlesxjyang/DeepGeyser
|
59f54c67667800f091d7af1805c04bbc36c7624b
|
[
"Apache-2.0"
] | null | null | null |
src/models/fft.py
|
charlesxjyang/DeepGeyser
|
59f54c67667800f091d7af1805c04bbc36c7624b
|
[
"Apache-2.0"
] | null | null | null |
src/models/fft.py
|
charlesxjyang/DeepGeyser
|
59f54c67667800f091d7af1805c04bbc36c7624b
|
[
"Apache-2.0"
] | null | null | null |
#misc
import sys
#data processing
import numpy as np
import pandas as pd
from scipy.fftpack import rfft
from scipy import optimize
#plotting
import matplotlib.pyplot as plt
#home-made
sys.path.append('../../utils')
from preprocessing import temp_forecasting_shape_processing,test_train_split
from error_reporting import error_reporting_regression,error_histogram,error_time_series,keras_training_loss_curve
from helpers import save_model,load_tsv
sys.path.append('../data_cleaning')
from grand import process_grand,clean_grand
def curve_func(x, a, b, c, d, e, f, g, h):
return a * np.sin(b * x) + c * np.cos(d * x) + e * np.sin(f * x) + g * np.cos(h * x)
def curve_func_2(x, a, b):
return a * np.sin(b * x)
def scipy_curve_fit(data,func):
data = data.flatten()
x_data = np.array(range(len(data)))
y_data = data
params, params_covariance = optimize.curve_fit(func, x_data, y_data,
p0=[2, 2])
pred = func(data,params[0],params[1]).flatten()
error_reporting_regression(data,pred)
return params,pred
def just_trying_fft(n=100):
df = clean_grand()
temp = df['temp'].values
spectra = np.fft.rfft(temp,n=n)
plt.plot(spectra)
def fft_to_pred(theta,cn_vec):
n = len(cn_vec)
total = 0
for i in range(n):
ea = np.exp(n*theta*np.array([0+1j]))
total = cn_vec[i] *ea + total
return total
def fft_model(lookbacklength,lookforwardlength,test_split):
df = clean_grand()
X_train,X_test,y_train,y_test = process_grand(df,lookbacklength=lookbacklength,lookforwardlength=lookforwardlength,test_split=test_split)
| 32.27451
| 141
| 0.693196
|
67e538e42011db37d2919725f0d26babbf747145
| 205
|
py
|
Python
|
test123.py
|
andreroche/Test-Scripts
|
3d2b93900b8cd4e234fe909fc41ae0e4e2a43263
|
[
"Apache-2.0"
] | null | null | null |
test123.py
|
andreroche/Test-Scripts
|
3d2b93900b8cd4e234fe909fc41ae0e4e2a43263
|
[
"Apache-2.0"
] | null | null | null |
test123.py
|
andreroche/Test-Scripts
|
3d2b93900b8cd4e234fe909fc41ae0e4e2a43263
|
[
"Apache-2.0"
] | null | null | null |
result = False
x = 2520
while not True:
x+=2520
for y in range(2,21):
if x%y != 0:
break
print (result)
else:
print (result)
| 14.642857
| 27
| 0.404878
|
98cc60de4bad6988d47425e36293a46f0df95984
| 2,912
|
py
|
Python
|
infoblox_netmri/api/remote/models/scan_interface_remote.py
|
IngmarVG-IB/infoblox-netmri
|
b0c725fd64aee1890d83917d911b89236207e564
|
[
"Apache-2.0"
] | null | null | null |
infoblox_netmri/api/remote/models/scan_interface_remote.py
|
IngmarVG-IB/infoblox-netmri
|
b0c725fd64aee1890d83917d911b89236207e564
|
[
"Apache-2.0"
] | null | null | null |
infoblox_netmri/api/remote/models/scan_interface_remote.py
|
IngmarVG-IB/infoblox-netmri
|
b0c725fd64aee1890d83917d911b89236207e564
|
[
"Apache-2.0"
] | null | null | null |
from ..remote import RemoteModel
from infoblox_netmri.utils.utils import check_api_availability
class ScanInterfaceRemote(RemoteModel):
"""
A NetMRI interface that can do discovery and other interaction with licensed devices
| ``unit_id:`` The internal identifier for the collector on which the scan interface exists.
| ``attribute type:`` number
| ``virtual_network_id:`` The internal NetMRI identifier of the Virtual Network in which the scan interface is present.
| ``attribute type:`` number
| ``if_dev:`` The system device name of the scan interface.
| ``attribute type:`` string
| ``name:`` The name of the scan interface.
| ``attribute type:`` string
| ``physical_if_id:`` The scan interface identifier of the physical interface, if this is a sub-interface.
| ``attribute type:`` string
| ``encap_tag:`` The 802.1Q encapsulation tag of traffic to be forwarded from the physical interface to the scan interface.
| ``attribute type:`` number
| ``ipv4_address:`` The IP address of the scan interface in dotted format.
| ``attribute type:`` string
| ``ipv4_mask:`` The network mask of the scan interface in dotted format.
| ``attribute type:`` string
| ``ipv4_gateway:`` The gateway of the scan interface in dotted format.
| ``attribute type:`` string
| ``ipv6_address:`` The IPv6 address of the scan interface in colon-delimited format.
| ``attribute type:`` string
| ``ipv6_prefix:`` The IPv6 mask of the scan interface.
| ``attribute type:`` string
| ``ipv6_gateway:`` The gateway of the scan interface in colon-delimited format IPv6.
| ``attribute type:`` string
| ``primary_dns_server:`` The IP address of the scan interface primary dns server in dotted format.
| ``attribute type:`` string
| ``secondary_dns_server:`` The IP address of the scan interface secondary dns server in dotted format.
| ``attribute type:`` string
| ``id:`` The internal NetMRI identifier of the Scan Interface.
| ``attribute type:`` number
| ``search_domains:`` Search domains for DNS resolving.
| ``attribute type:`` string
"""
properties = ("unit_id",
"virtual_network_id",
"if_dev",
"name",
"physical_if_id",
"encap_tag",
"ipv4_address",
"ipv4_mask",
"ipv4_gateway",
"ipv6_address",
"ipv6_prefix",
"ipv6_gateway",
"primary_dns_server",
"secondary_dns_server",
"id",
"search_domains",
)
| 30.978723
| 128
| 0.580701
|
2f5caa259e269f889ae53cf284cd9d0abcd33507
| 19,572
|
py
|
Python
|
cobra/utils.py
|
sherppard/cobra
|
5e2b9bf7418490a901d5d7cdc48f622717655f39
|
[
"MIT"
] | 1
|
2018-06-12T11:20:55.000Z
|
2018-06-12T11:20:55.000Z
|
cobra/utils.py
|
PCanyi/cobra
|
0a80aa81a340c9d0f6ca68ef36980c5348cb5396
|
[
"MIT"
] | null | null | null |
cobra/utils.py
|
PCanyi/cobra
|
0a80aa81a340c9d0f6ca68ef36980c5348cb5396
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
utils
~~~~~
Implements utils
:author: Feei <feei@feei.cn>
:homepage: https://github.com/WhaleShark-Team/cobra
:license: MIT, see LICENSE for more details.
:copyright: Copyright (c) 2018 Feei. All rights reserved
"""
import shutil
import hashlib
import json
import base64
import os
import random
import re
import string
import sys
import time
import urllib
import requests
import json
import pipes
from .log import logger
from .config import Config, issue_history_path
from .__version__ import __version__, __python_version__, __platform__, __url__
from .exceptions import PickupException, NotExistException, AuthFailedException
from .pickup import Git, NotExistError, AuthError, Decompress
from .const import access_token
TARGET_MODE_GIT = 'git'
TARGET_MODE_FILE = 'file'
TARGET_MODE_FOLDER = 'folder'
TARGET_MODE_COMPRESS = 'compress'
OUTPUT_MODE_MAIL = 'mail'
OUTPUT_MODE_API = 'api'
OUTPUT_MODE_FILE = 'file'
OUTPUT_MODE_STREAM = 'stream'
PY2 = sys.version_info[0] == 2
class ParseArgs(object):
def __init__(self, target, formatter, output, special_rules=None, a_sid=None):
self.target = target
self.formatter = formatter
self.output = output
if special_rules is not None and special_rules is not '':
self.special_rules = []
extension = '.xml'
if ',' in special_rules:
# check rule name
s_rules = special_rules.split(',')
for sr in s_rules:
if self._check_rule_name(sr):
if extension not in sr:
sr += extension
self.special_rules.append(sr)
else:
logger.critical('[PARSE-ARGS] Exception rule name: {sr}'.format(sr=sr))
else:
if self._check_rule_name(special_rules):
if extension not in special_rules:
special_rules += extension
self.special_rules = [special_rules]
else:
logger.critical(
'[PARSE-ARGS] Exception special rule name(e.g: CVI-110001): {sr}'.format(sr=special_rules))
else:
self.special_rules = None
self.sid = a_sid
@staticmethod
def _check_rule_name(name):
return re.match(r'^(cvi|CVI)-\d{6}(\.xml)?', name.strip()) is not None
@property
def target_mode(self):
"""
Parse target mode (git/file/folder/compress)
:return: str
"""
target_mode = None
target_git_cases = ['http://', 'https://', 'ssh://']
for tgc in target_git_cases:
if self.target[0:len(tgc)] == tgc:
target_mode = TARGET_MODE_GIT
if os.path.isfile(self.target):
target_mode = TARGET_MODE_FILE
try:
if self.target.split('.')[-1] in Config('upload', 'extensions').value.split('|'):
target_mode = TARGET_MODE_COMPRESS
except AttributeError as e:
logger.critical('Please config the config file copy from the config.template file')
if os.path.isdir(self.target):
target_mode = TARGET_MODE_FOLDER
if target_mode is None:
logger.critical('[PARSE-ARGS] [-t <target>] can\'t empty!')
exit()
logger.debug('[PARSE-ARGS] Target Mode: {mode}'.format(mode=target_mode))
return target_mode
@property
def output_mode(self):
"""
Parse output mode (api/mail/file/stream)
:return: str
"""
output_mode = None
output_mode_api = ['http', 'https']
output_mode_mail = r"(^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$)"
if re.match(output_mode_mail, self.output) is not None:
output_mode = OUTPUT_MODE_MAIL
for oma in output_mode_api:
if self.output[0:len(oma)] == oma:
output_mode = OUTPUT_MODE_API
if os.path.isdir(os.path.dirname(self.output)):
output_mode = OUTPUT_MODE_FILE
if output_mode is None:
output_mode = OUTPUT_MODE_STREAM
logger.debug('[PARSE-ARGS] Output Mode: {mode}'.format(mode=output_mode))
return output_mode
def target_directory(self, target_mode):
reg = '^((ht|f)tps?):\/\/[\w\-]+(\.[\w\-]+)+([\w\-\.,@?^=%&:\/~\+#]*[\w\-\@?^=%&\/~\+#])?$'
target_directory = None
if target_mode == TARGET_MODE_GIT:
logger.debug('GIT Project')
# branch or tag
split_target = self.target.split(':')
if len(split_target) == 3:
target, branch = '{p}:{u}'.format(p=split_target[0], u=split_target[1]), split_target[-1]
if re.match(reg, target) is None:
logger.critical('Please enter a valid URL')
exit()
branch = pipes.quote(branch)
elif len(split_target) == 2:
target, branch = self.target, 'master'
if re.match(reg, target) is None:
logger.critical('Please enter a valid URL')
exit()
branch = pipes.quote(branch)
else:
logger.critical('Target url exception: {u}'.format(u=self.target))
if 'gitlab' in target:
username = Config('git', 'username').value
password = Config('git', 'password').value
else:
username = None
password = None
gg = Git(repo_address=target, branch=branch, username=username, password=password)
# Git Clone Error
try:
clone_ret, clone_err = gg.clone()
if clone_ret is False:
raise PickupException('Clone Failed ({0})'.format(clone_err), gg)
except NotExistError:
raise NotExistException(4001, 'Repository or Branch Does not exist!', gg)
except AuthError:
raise AuthFailedException('Git Authentication Failed')
target_directory = gg.repo_directory
elif target_mode == TARGET_MODE_COMPRESS:
ret, target_directory = Decompress(self.target).decompress()
elif target_mode == TARGET_MODE_FOLDER:
target_directory = self.target
elif target_mode == TARGET_MODE_FILE:
target_directory = self.target
else:
logger.critical('[PARSE-ARGS] exception target mode ({mode})'.format(mode=target_mode))
exit()
logger.debug('[PARSE-ARGS] target directory: {directory}'.format(directory=target_directory))
target_directory = os.path.abspath(target_directory)
if target_directory[-1] == '/':
return target_directory
else:
return u'{t}/'.format(t=target_directory)
def to_bool(value):
"""Converts 'something' to boolean. Raises exception for invalid formats"""
if str(value).lower() in ("on", "yes", "y", "true", "t", "1"):
return True
if str(value).lower() in ("off", "no", "n", "false", "f", "0", "0.0", "", "none", "[]", "{}"):
return False
raise Exception('Invalid value for boolean conversion: ' + str(value))
def convert_time(seconds):
"""
Seconds to minute/second
Ex: 61 -> 1'1"
:param seconds:
:return:
:link: https://en.wikipedia.org/wiki/Prime_(symbol)
"""
one_minute = 60
minute = seconds / one_minute
if minute == 0:
return str(seconds % one_minute) + "\""
else:
return str(int(minute)) + "'" + str(seconds % one_minute) + "\""
def convert_number(n):
"""
Convert number to , split
Ex: 123456 -> 123,456
:param n:
:return:
"""
if n is None:
return '0'
n = str(n)
if '.' in n:
dollars, cents = n.split('.')
else:
dollars, cents = n, None
r = []
for i, c in enumerate(str(dollars)[::-1]):
if i and (not (i % 3)):
r.insert(0, ',')
r.insert(0, c)
out = ''.join(r)
if cents:
out += '.' + cents
return out
def md5(content):
"""
MD5 Hash
:param content:
:return:
"""
content = content.encode('utf8')
return hashlib.md5(content).hexdigest()
def allowed_file(filename):
"""
Allowed upload file
Config Path: ./config [upload]
:param filename:
:return:
"""
config_extension = Config('upload', 'extensions').value
if config_extension == '':
logger.critical('Please set config file upload->directory')
sys.exit(0)
allowed_extensions = config_extension.split('|')
return '.' in filename and filename.rsplit('.', 1)[1] in allowed_extensions
def path_to_short(path, max_length=36):
"""
/impl/src/main/java/com/mogujie/service/mgs/digitalcert/utils/CertUtil.java
/impl/src/.../utils/CertUtil.java
:param path:
:param max_length:
:return:
"""
if len(path) < max_length:
return path
paths = path.split('/')
paths = filter(None, paths)
paths = list(paths)
tmp_path = ''
for i in range(0, len(paths)):
logger.debug((i, str(paths[i]), str(paths[len(paths) - i - 1])))
tmp_path = tmp_path + str(paths[i]) + '/' + str(paths[len(paths) - i - 1])
if len(tmp_path) > max_length:
tmp_path = ''
for j in range(0, i):
tmp_path = tmp_path + '/' + str(paths[j])
tmp_path += '/...'
for k in range(i, 0, -1):
tmp_path = tmp_path + '/' + str(paths[len(paths) - k])
if tmp_path == '/...':
return '.../{0}'.format(paths[len(paths) - 1])
elif tmp_path[0] == '/':
return tmp_path[1:]
else:
return tmp_path
def path_to_file(path):
"""
Path to file
/impl/src/main/java/com/mogujie/service/mgs/digitalcert/utils/CertUtil.java
.../CertUtil.java
:param path:
:return:
"""
paths = path.split('/')
paths = list(filter(None, paths))
length = len(paths)
return '.../{0}'.format(paths[length - 1])
def percent(part, whole, need_per=True):
"""
Percent
:param part:
:param whole:
:param need_per:
:return:
"""
if need_per:
per = '%'
else:
per = ''
if part == 0 and whole == 0:
return 0
return '{0}{1}'.format(100 * float(part) / float(whole), per)
def timestamp():
"""Get timestamp"""
return int(time.time())
def format_gmt(time_gmt, time_format=None):
"""
Format GMT time
Ex: Wed, 14 Sep 2016 17:57:41 GMT to 2016-09-14 17:57:41
:param time_gmt:
:param time_format:
:return:
"""
if time_format is None:
time_format = '%Y-%m-%d %X'
t = time.strptime(time_gmt, "%a, %d %b %Y %H:%M:%S GMT")
return time.strftime(time_format, t)
def random_generator(size=6, chars=string.ascii_uppercase + string.digits):
return ''.join(random.choice(chars) for _ in range(size))
def is_list(value):
"""
Returns True if the given value is a list-like instance
>>> is_list([1, 2, 3])
True
>>> is_list(u'2')
False
"""
return isinstance(value, (list, tuple, set))
def get_unicode(value, encoding=None, none_to_null=False):
"""
Return the unicode representation of the supplied value:
>>> get_unicode(u'test')
u'test'
>>> get_unicode('test')
u'test'
>>> get_unicode(1)
u'1'
"""
if none_to_null and value is None:
return None
if str(type(value)) == "<class 'bytes'>":
value = value.encode('utf8')
return value
elif str(type(value)) == "<type 'unicode'>":
return value
elif is_list(value):
value = list(get_unicode(_, encoding, none_to_null) for _ in value)
return value
else:
try:
return value.encode('utf8')
except UnicodeDecodeError:
return value.encode('utf8', errors="ignore")
def get_safe_ex_string(ex, encoding=None):
"""
Safe way how to get the proper exception represtation as a string
(Note: errors to be avoided: 1) "%s" % Exception(u'\u0161') and 2) "%s" % str(Exception(u'\u0161'))
>>> get_safe_ex_string(Exception('foobar'))
u'foobar'
"""
ret = ex
if getattr(ex, "message", None):
ret = ex.message
elif getattr(ex, "msg", None):
ret = ex.msg
return get_unicode(ret or "", encoding=encoding).strip()
class Tool:
def __init__(self):
# `grep` (`ggrep` on Mac)
if os.path.isfile('/bin/grep'):
self.grep = '/bin/grep'
elif os.path.isfile('/usr/bin/grep'):
self.grep = '/usr/bin/grep'
elif os.path.isfile('/usr/local/bin/grep'):
self.grep = '/usr/local/bin/grep'
else:
self.grep = 'grep'
# `find` (`gfind` on Mac)
if os.path.isfile('/bin/find'):
self.find = '/bin/find'
elif os.path.isfile('/usr/bin/find'):
self.find = '/usr/bin/find'
elif os.path.isfile('/usr/local/bin/find'):
self.find = '/usr/local/bin/find'
else:
self.find = 'find'
if 'darwin' == sys.platform:
ggrep = ''
gfind = ''
for root, dir_names, file_names in os.walk('/usr/local/Cellar/grep'):
for filename in file_names:
if 'ggrep' == filename or 'grep' == filename:
ggrep = os.path.join(root, filename)
for root, dir_names, file_names in os.walk('/usr/local/Cellar/findutils'):
for filename in file_names:
if 'gfind' == filename:
gfind = os.path.join(root, filename)
if ggrep == '':
logger.critical("brew install grep pleases!")
sys.exit(0)
else:
self.grep = ggrep
if gfind == '':
logger.critical("brew install findutils pleases!")
sys.exit(0)
else:
self.find = gfind
def secure_filename(filename):
_filename_utf8_strip_re = re.compile(u"[^\u4e00-\u9fa5A-Za-z0-9_.\-\+]")
_windows_device_files = ('CON', 'AUX', 'COM1', 'COM2', 'COM3', 'COM4', 'LPT1', 'LPT2', 'LPT3', 'PRN', 'NUL')
try:
text_type = unicode # Python 2
except NameError:
text_type = str # Python 3
if isinstance(filename, text_type):
from unicodedata import normalize
filename = normalize('NFKD', filename).encode('utf-8', 'ignore')
if not PY2:
filename = filename.decode('utf-8')
if filename in (os.path.sep, os.path.altsep, os.path.pardir):
return ""
if PY2:
filename = filename.decode('utf-8')
filename = _filename_utf8_strip_re.sub('', '_'.join(filename.split()))
# on nt a couple of special files are present in each folder. We
# have to ensure that the target file is not such a filename. In
# this case we prepend an underline
if os.name == 'nt' and filename and filename.split('.')[0].upper() in _windows_device_files:
filename = '_' + filename
return filename
def split_branch(target_str):
split_target = target_str.split(':')
if len(split_target) == 3:
target, branch = '{p}:{u}'.format(p=split_target[0], u=split_target[1]), split_target[-1]
elif len(split_target) == 2:
target, branch = target_str, 'master'
else:
target, branch = target_str, 'master'
return target, branch
def unhandled_exception_unicode_message(root, dirs, filenames):
err_msg = unhandled_exception_message()
dirs = ','.join(dirs)
filenames = ','.join(filenames)
err_msg_unicode = err_msg + """\nRoot path: {rp}\nDirs: {di}\nFilenames: {fn}""".format(
rp=root,
di=dirs,
fn=filenames
)
return err_msg_unicode
def unhandled_exception_message():
"""
Returns detailed message about occurred unhandled exception
"""
err_msg = """Cobra version: {cv}\nPython version: {pv}\nOperating system: {os}\nCommand line: {cl}""".format(
cv=__version__,
pv=__python_version__,
os=__platform__,
cl=re.sub(r".+?\bcobra.py\b", "cobra.py", " ".join(sys.argv).encode('utf-8'))
)
return err_msg
def create_github_issue(err_msg, exc_msg):
"""
Automatically create a Github issue with unhandled exception information
"""
issues = []
try:
with open(issue_history_path, 'r') as f:
for line in f.readlines():
issues.append(line.strip())
except:
pass
finally:
# unique
issues = set(issues)
_ = re.sub(r"'[^']+'", "''", exc_msg)
_ = re.sub(r"\s+line \d+", "", _)
_ = re.sub(r'File ".+?/(\w+\.py)', "\g<1>", _)
_ = re.sub(r".+\Z", "", _)
key = hashlib.md5(_).hexdigest()[:8]
if key in issues:
logger.warning('issue already reported!')
return
ex = None
try:
url = "https://api.github.com/search/issues?q={q}".format(q=urllib.quote("repo:WhaleShark-Team/cobra [AUTO] Unhandled exception (#{k})".format(k=key)))
logger.debug(url)
resp = requests.get(url=url)
content = resp.json()
_ = content
duplicate = _["total_count"] > 0
closed = duplicate and _["items"][0]["state"] == "closed"
if duplicate:
warn_msg = "issue seems to be already reported"
if closed:
warn_msg += " and resolved. Please update to the latest version from official GitHub repository at '{u}'".format(u=__url__)
logger.warning(warn_msg)
return
except:
logger.warning('search github issue failed')
pass
try:
url = "https://api.github.com/repos/WhaleShark-Team/cobra/issues"
data = {
"title": "[AUTO] Unhandled exception (#{k})".format(k=key),
"body": "## Environment\n```\n{err}\n```\n## Traceback\n```\n{exc}\n```\n".format(err=err_msg, exc=exc_msg)
}
headers = {"Authorization": "token {t}".format(t=base64.b64decode(access_token))}
resp = requests.post(url=url, data=json.dumps(data), headers=headers)
content = resp.text
except Exception as ex:
content = None
issue_url = re.search(r"https://github.com/WhaleShark-Team/cobra/issues/\d+", content or "")
if issue_url:
info_msg = "created Github issue can been found at the address '{u}'".format(u=issue_url.group(0))
logger.info(info_msg)
try:
with open(issue_history_path, "a+b") as f:
f.write("{k}\n".format(k=key))
except:
pass
else:
warn_msg = "something went wrong while creating a Github issue"
if ex:
warn_msg += " ('{m}')".format(m=get_safe_ex_string(ex))
if "Unauthorized" in warn_msg:
warn_msg += ". Please update to the latest revision"
logger.warning(warn_msg)
def clean_dir(filepath):
if os.path.isdir(filepath):
if os.path.isfile(filepath):
try:
os.remove(filepath)
except OSError:
logger.warning('[RM] remove {} fail'.format(filepath))
elif os.path.isdir(filepath):
shutil.rmtree(filepath, True)
return True
| 32.137931
| 159
| 0.566166
|
9d703529daec585e5994a10a2f7270992957741f
| 1,027
|
py
|
Python
|
config/cifar100_200.py
|
XuZhengzhuo/Prior-LT
|
60720b519f4f4b56316e589702b58fa1374059d7
|
[
"MIT"
] | 9
|
2021-11-17T09:21:20.000Z
|
2022-02-23T03:40:31.000Z
|
config/cifar100_200.py
|
XuZhengzhuo/Prior-LT
|
60720b519f4f4b56316e589702b58fa1374059d7
|
[
"MIT"
] | 1
|
2021-12-21T07:58:23.000Z
|
2021-12-21T08:06:55.000Z
|
config/cifar100_200.py
|
XuZhengzhuo/Prior-LT
|
60720b519f4f4b56316e589702b58fa1374059d7
|
[
"MIT"
] | 1
|
2022-01-04T07:58:42.000Z
|
2022-01-04T07:58:42.000Z
|
# model
arch = 'resnet32'
# dataset
dataset = 'cifar100' # or 'cifar10'
imb_type = 'exp' # or 'step'
num_classes = int(dataset[5:])
imb_factor = 0.005
train_cls_num_list = None
inf_label_distribution = None
if dataset == 'cifar10':
h_class_idx = [0, 3]
m_class_idx = [3, 7]
t_class_idx = [7, 10]
else:
h_class_idx = [0, 33]
m_class_idx = [33, 66]
t_class_idx = [66, 100]
# load setting
workers = 4
seed = 0
rand_number = 0
# gpu
gpu = 0
# train setting
epochs = 200
batch_size = 64 # will double if mix
lr = 0.1
start_epoch = 0
momentum = 0.9
weight_decay = 2e-4
# mixup manners
mix_type = 'unimix'
mix_stop_epoch = 200
# alp=1. and tau=0. equals to origin mixup
unimix_alp = 0.8
unimix_tau = -0.1
# loss
loss_type = 'Bayias' # or 'CE'
# checkpoint
resume = '' # relative path to ckpt
save_ckpt_epoch = mix_stop_epoch # save ckpt for finetune
# debug info
cfg_name = 'Final' # the main store path
debug = False # mkdir or not
note = f'bs_64_alp_0.8_tau_0.1' # for better visualization
| 18.672727
| 59
| 0.673807
|
84d5c977ff393ab701f9a0125335606377675532
| 531,138
|
py
|
Python
|
template_container_macaque/labels/slice_53.py
|
lkondratova/Brainplot
|
3c8a88c1995dedeaa5cbd88ee71499c7cf9c571d
|
[
"MIT"
] | null | null | null |
template_container_macaque/labels/slice_53.py
|
lkondratova/Brainplot
|
3c8a88c1995dedeaa5cbd88ee71499c7cf9c571d
|
[
"MIT"
] | null | null | null |
template_container_macaque/labels/slice_53.py
|
lkondratova/Brainplot
|
3c8a88c1995dedeaa5cbd88ee71499c7cf9c571d
|
[
"MIT"
] | null | null | null |
coordinates_00EBFF = ((46, 187),
(46, 189), (47, 186), (47, 191), (48, 184), (48, 187), (48, 188), (48, 189), (48, 192), (49, 183), (49, 186), (49, 187), (49, 188), (49, 189), (49, 190), (49, 191), (49, 193), (50, 181), (50, 184), (50, 185), (50, 186), (50, 187), (50, 188), (50, 189), (50, 190), (50, 191), (50, 192), (50, 194), (51, 180), (51, 183), (51, 184), (51, 185), (51, 186), (51, 187), (51, 188), (51, 189), (51, 190), (51, 191), (51, 192), (51, 194), (52, 178), (52, 181), (52, 182), (52, 183), (52, 184), (52, 185), (52, 186), (52, 187), (52, 188), (52, 189), (52, 190), (52, 191), (52, 192), (52, 194), (53, 176), (53, 180), (53, 181), (53, 182), (53, 183), (53, 184), (53, 185), (53, 186), (53, 187), (53, 188), (53, 189), (53, 190), (53, 191), (53, 193), (54, 174), (54, 178), (54, 179), (54, 180), (54, 181),
(54, 182), (54, 183), (54, 184), (54, 185), (54, 186), (54, 187), (54, 188), (54, 189), (54, 190), (54, 192), (55, 172), (55, 176), (55, 177), (55, 178), (55, 179), (55, 180), (55, 181), (55, 182), (55, 183), (55, 184), (55, 185), (55, 186), (55, 187), (55, 188), (55, 189), (55, 191), (56, 170), (56, 174), (56, 175), (56, 176), (56, 177), (56, 178), (56, 179), (56, 180), (56, 181), (56, 182), (56, 183), (56, 184), (56, 185), (56, 186), (56, 187), (56, 188), (56, 190), (57, 168), (57, 172), (57, 173), (57, 174), (57, 175), (57, 176), (57, 177), (57, 178), (57, 179), (57, 180), (57, 181), (57, 182), (57, 183), (57, 184), (57, 185), (57, 186), (57, 187), (57, 190), (58, 166), (58, 170), (58, 171), (58, 172), (58, 173), (58, 174), (58, 175), (58, 176), (58, 177), (58, 178), (58, 179),
(58, 180), (58, 181), (58, 182), (58, 183), (58, 189), (59, 163), (59, 164), (59, 168), (59, 169), (59, 170), (59, 171), (59, 172), (59, 173), (59, 174), (59, 175), (59, 176), (59, 177), (59, 178), (59, 179), (59, 180), (59, 184), (59, 185), (59, 186), (59, 187), (59, 189), (60, 161), (60, 162), (60, 165), (60, 166), (60, 167), (60, 168), (60, 169), (60, 170), (60, 171), (60, 172), (60, 173), (60, 174), (60, 175), (60, 176), (60, 177), (60, 178), (60, 181), (60, 182), (61, 159), (61, 163), (61, 164), (61, 165), (61, 166), (61, 167), (61, 168), (61, 169), (61, 170), (61, 171), (61, 172), (61, 173), (61, 174), (61, 175), (61, 176), (61, 180), (62, 157), (62, 161), (62, 162), (62, 163), (62, 164), (62, 165), (62, 166), (62, 167), (62, 168), (62, 169), (62, 170), (62, 171), (62, 172),
(62, 173), (62, 174), (62, 175), (62, 178), (63, 156), (63, 159), (63, 160), (63, 161), (63, 162), (63, 163), (63, 164), (63, 165), (63, 166), (63, 167), (63, 168), (63, 169), (63, 170), (63, 171), (63, 172), (63, 173), (63, 174), (64, 155), (64, 157), (64, 158), (64, 159), (64, 160), (64, 161), (64, 162), (64, 163), (64, 164), (64, 165), (64, 166), (64, 167), (64, 168), (64, 169), (64, 170), (64, 171), (64, 172), (64, 173), (64, 175), (65, 154), (65, 156), (65, 157), (65, 158), (65, 159), (65, 160), (65, 161), (65, 162), (65, 163), (65, 164), (65, 165), (65, 166), (65, 167), (65, 168), (65, 169), (65, 170), (65, 171), (65, 172), (65, 174), (66, 153), (66, 155), (66, 156), (66, 157), (66, 158), (66, 159), (66, 160), (66, 161), (66, 162), (66, 163), (66, 164), (66, 165), (66, 166),
(66, 167), (66, 168), (66, 169), (66, 170), (66, 171), (66, 173), (67, 152), (67, 154), (67, 155), (67, 156), (67, 157), (67, 158), (67, 159), (67, 160), (67, 161), (67, 162), (67, 163), (67, 164), (67, 165), (67, 166), (67, 167), (67, 168), (67, 169), (67, 170), (67, 172), (68, 151), (68, 153), (68, 154), (68, 155), (68, 156), (68, 157), (68, 158), (68, 159), (68, 160), (68, 161), (68, 162), (68, 163), (68, 164), (68, 165), (68, 166), (68, 167), (68, 168), (68, 169), (68, 171), (69, 151), (69, 152), (69, 153), (69, 154), (69, 155), (69, 156), (69, 157), (69, 158), (69, 159), (69, 160), (69, 161), (69, 162), (69, 163), (69, 164), (69, 165), (69, 166), (69, 167), (69, 168), (69, 170), (70, 152), (70, 154), (70, 155), (70, 156), (70, 157), (70, 158), (70, 159), (70, 160), (70, 161),
(70, 162), (70, 163), (70, 164), (70, 165), (70, 166), (70, 167), (70, 168), (70, 170), (70, 239), (71, 152), (71, 154), (71, 155), (71, 156), (71, 157), (71, 158), (71, 159), (71, 160), (71, 161), (71, 162), (71, 163), (71, 164), (71, 165), (71, 166), (71, 167), (71, 169), (71, 239), (71, 240), (72, 153), (72, 155), (72, 156), (72, 157), (72, 158), (72, 159), (72, 160), (72, 161), (72, 162), (72, 163), (72, 164), (72, 165), (72, 166), (72, 168), (72, 239), (72, 241), (73, 153), (73, 155), (73, 156), (73, 157), (73, 158), (73, 159), (73, 160), (73, 161), (73, 162), (73, 163), (73, 164), (73, 165), (73, 166), (73, 168), (73, 240), (73, 242), (74, 154), (74, 156), (74, 157), (74, 158), (74, 159), (74, 160), (74, 161), (74, 162), (74, 163), (74, 164), (74, 165), (74, 167), (74, 240),
(74, 243), (75, 154), (75, 156), (75, 157), (75, 158), (75, 159), (75, 160), (75, 161), (75, 162), (75, 163), (75, 164), (75, 165), (75, 167), (75, 241), (75, 245), (76, 154), (76, 156), (76, 157), (76, 158), (76, 159), (76, 160), (76, 161), (76, 162), (76, 163), (76, 164), (76, 166), (76, 241), (76, 243), (76, 247), (77, 155), (77, 157), (77, 158), (77, 159), (77, 160), (77, 161), (77, 162), (77, 163), (77, 164), (77, 166), (77, 242), (77, 244), (77, 245), (77, 248), (77, 249), (77, 251), (78, 155), (78, 157), (78, 158), (78, 159), (78, 160), (78, 161), (78, 162), (78, 163), (78, 164), (78, 166), (78, 243), (78, 245), (78, 246), (78, 247), (78, 251), (79, 156), (79, 158), (79, 159), (79, 160), (79, 161), (79, 162), (79, 163), (79, 164), (79, 166), (79, 244), (79, 246), (79, 247),
(79, 248), (79, 249), (79, 250), (79, 252), (80, 156), (80, 158), (80, 159), (80, 160), (80, 161), (80, 162), (80, 163), (80, 164), (80, 166), (80, 245), (80, 247), (80, 248), (80, 249), (80, 250), (80, 251), (80, 253), (81, 156), (81, 158), (81, 159), (81, 160), (81, 161), (81, 162), (81, 163), (81, 164), (81, 166), (81, 246), (81, 248), (81, 249), (81, 250), (81, 251), (81, 252), (81, 255), (82, 157), (82, 159), (82, 160), (82, 161), (82, 162), (82, 163), (82, 164), (82, 166), (82, 247), (82, 249), (82, 250), (82, 251), (82, 252), (82, 253), (82, 256), (82, 257), (83, 157), (83, 159), (83, 160), (83, 161), (83, 162), (83, 163), (83, 164), (83, 166), (83, 248), (83, 250), (83, 251), (83, 252), (83, 253), (83, 254), (83, 255), (83, 258), (83, 259), (83, 260), (84, 157), (84, 159),
(84, 160), (84, 161), (84, 162), (84, 163), (84, 164), (84, 165), (84, 167), (84, 249), (84, 251), (84, 252), (84, 253), (84, 254), (84, 255), (84, 256), (84, 257), (84, 262), (84, 263), (85, 157), (85, 159), (85, 160), (85, 161), (85, 162), (85, 163), (85, 164), (85, 165), (85, 167), (85, 250), (85, 252), (85, 253), (85, 254), (85, 255), (85, 256), (85, 257), (85, 258), (85, 259), (85, 260), (85, 261), (85, 265), (86, 157), (86, 159), (86, 160), (86, 161), (86, 162), (86, 163), (86, 164), (86, 165), (86, 167), (86, 251), (86, 253), (86, 254), (86, 255), (86, 256), (86, 257), (86, 258), (86, 259), (86, 260), (86, 261), (86, 262), (86, 263), (86, 264), (86, 267), (87, 157), (87, 159), (87, 160), (87, 161), (87, 162), (87, 163), (87, 164), (87, 165), (87, 166), (87, 168), (87, 252),
(87, 254), (87, 255), (87, 256), (87, 257), (87, 258), (87, 259), (87, 260), (87, 261), (87, 262), (87, 263), (87, 264), (87, 265), (87, 268), (88, 158), (88, 160), (88, 161), (88, 162), (88, 163), (88, 164), (88, 165), (88, 166), (88, 167), (88, 169), (88, 253), (88, 255), (88, 256), (88, 257), (88, 258), (88, 259), (88, 260), (88, 261), (88, 262), (88, 263), (88, 264), (88, 265), (88, 266), (88, 267), (88, 270), (89, 158), (89, 160), (89, 161), (89, 162), (89, 163), (89, 164), (89, 165), (89, 166), (89, 167), (89, 168), (89, 170), (89, 253), (89, 256), (89, 257), (89, 258), (89, 259), (89, 260), (89, 261), (89, 262), (89, 263), (89, 264), (89, 265), (89, 266), (89, 267), (89, 268), (89, 271), (90, 158), (90, 160), (90, 161), (90, 162), (90, 163), (90, 164), (90, 165), (90, 166),
(90, 167), (90, 168), (90, 169), (90, 171), (90, 254), (90, 256), (90, 257), (90, 258), (90, 259), (90, 260), (90, 261), (90, 262), (90, 263), (90, 264), (90, 265), (90, 266), (90, 267), (90, 268), (90, 269), (90, 270), (90, 273), (91, 159), (91, 161), (91, 162), (91, 163), (91, 164), (91, 165), (91, 166), (91, 167), (91, 168), (91, 169), (91, 170), (91, 172), (91, 174), (91, 255), (91, 258), (91, 259), (91, 260), (91, 261), (91, 262), (91, 263), (91, 264), (91, 265), (91, 266), (91, 267), (91, 268), (91, 269), (91, 270), (91, 271), (91, 274), (92, 159), (92, 161), (92, 162), (92, 163), (92, 164), (92, 165), (92, 166), (92, 167), (92, 168), (92, 169), (92, 170), (92, 171), (92, 174), (92, 256), (92, 259), (92, 260), (92, 261), (92, 262), (92, 263), (92, 264), (92, 265), (92, 266),
(92, 267), (92, 268), (92, 269), (92, 270), (92, 271), (92, 272), (92, 273), (92, 275), (93, 159), (93, 161), (93, 162), (93, 163), (93, 164), (93, 165), (93, 166), (93, 167), (93, 168), (93, 169), (93, 170), (93, 171), (93, 172), (93, 175), (93, 258), (93, 260), (93, 261), (93, 262), (93, 263), (93, 264), (93, 265), (93, 266), (93, 267), (93, 268), (93, 269), (93, 270), (93, 271), (93, 272), (93, 273), (93, 274), (93, 276), (94, 159), (94, 161), (94, 162), (94, 163), (94, 164), (94, 165), (94, 166), (94, 167), (94, 168), (94, 169), (94, 170), (94, 171), (94, 172), (94, 173), (94, 174), (94, 176), (94, 259), (94, 261), (94, 262), (94, 263), (94, 264), (94, 265), (94, 266), (94, 267), (94, 268), (94, 269), (94, 270), (94, 271), (94, 272), (94, 273), (94, 274), (94, 275), (94, 277),
(95, 159), (95, 161), (95, 162), (95, 163), (95, 164), (95, 165), (95, 166), (95, 167), (95, 168), (95, 169), (95, 170), (95, 171), (95, 172), (95, 173), (95, 174), (95, 177), (95, 178), (95, 260), (95, 262), (95, 263), (95, 264), (95, 265), (95, 266), (95, 267), (95, 268), (95, 269), (95, 270), (95, 271), (95, 272), (95, 273), (95, 274), (95, 275), (95, 276), (95, 278), (96, 159), (96, 161), (96, 162), (96, 163), (96, 164), (96, 165), (96, 166), (96, 167), (96, 168), (96, 169), (96, 170), (96, 171), (96, 172), (96, 173), (96, 174), (96, 175), (96, 176), (96, 179), (96, 180), (96, 181), (96, 182), (96, 183), (96, 184), (96, 185), (96, 186), (96, 187), (96, 188), (96, 189), (96, 190), (96, 191), (96, 192), (96, 193), (96, 194), (96, 262), (96, 263), (96, 264), (96, 265), (96, 266),
(96, 267), (96, 268), (96, 269), (96, 270), (96, 271), (96, 272), (96, 273), (96, 274), (96, 275), (96, 276), (96, 277), (96, 279), (97, 159), (97, 161), (97, 162), (97, 163), (97, 164), (97, 165), (97, 166), (97, 167), (97, 168), (97, 169), (97, 170), (97, 171), (97, 172), (97, 173), (97, 174), (97, 175), (97, 176), (97, 177), (97, 178), (97, 196), (97, 261), (97, 263), (97, 264), (97, 265), (97, 266), (97, 267), (97, 268), (97, 269), (97, 270), (97, 271), (97, 272), (97, 273), (97, 274), (97, 275), (97, 276), (97, 277), (97, 278), (97, 280), (98, 159), (98, 161), (98, 162), (98, 163), (98, 164), (98, 165), (98, 166), (98, 167), (98, 168), (98, 169), (98, 170), (98, 171), (98, 172), (98, 173), (98, 174), (98, 175), (98, 176), (98, 177), (98, 178), (98, 179), (98, 180), (98, 181),
(98, 182), (98, 183), (98, 184), (98, 185), (98, 186), (98, 187), (98, 188), (98, 189), (98, 190), (98, 191), (98, 192), (98, 193), (98, 194), (98, 198), (98, 199), (98, 262), (98, 264), (98, 265), (98, 266), (98, 267), (98, 268), (98, 269), (98, 270), (98, 271), (98, 272), (98, 273), (98, 274), (98, 275), (98, 276), (98, 277), (98, 278), (98, 279), (98, 281), (99, 158), (99, 159), (99, 160), (99, 161), (99, 162), (99, 163), (99, 164), (99, 165), (99, 166), (99, 167), (99, 168), (99, 169), (99, 170), (99, 171), (99, 172), (99, 173), (99, 174), (99, 175), (99, 176), (99, 177), (99, 178), (99, 179), (99, 180), (99, 181), (99, 182), (99, 183), (99, 184), (99, 185), (99, 186), (99, 187), (99, 188), (99, 189), (99, 190), (99, 191), (99, 192), (99, 193), (99, 194), (99, 195), (99, 196),
(99, 197), (99, 200), (99, 201), (99, 202), (99, 203), (99, 263), (99, 265), (99, 266), (99, 267), (99, 268), (99, 269), (99, 270), (99, 271), (99, 272), (99, 273), (99, 274), (99, 275), (99, 276), (99, 277), (99, 278), (99, 279), (99, 280), (99, 282), (100, 158), (100, 160), (100, 161), (100, 162), (100, 163), (100, 164), (100, 165), (100, 166), (100, 167), (100, 168), (100, 169), (100, 170), (100, 171), (100, 172), (100, 173), (100, 174), (100, 175), (100, 176), (100, 177), (100, 178), (100, 179), (100, 180), (100, 181), (100, 182), (100, 183), (100, 184), (100, 185), (100, 186), (100, 187), (100, 188), (100, 189), (100, 190), (100, 191), (100, 192), (100, 193), (100, 194), (100, 195), (100, 196), (100, 197), (100, 198), (100, 199), (100, 204), (100, 205), (100, 206), (100, 208), (100, 263), (100, 265), (100, 266), (100, 267),
(100, 268), (100, 269), (100, 270), (100, 271), (100, 272), (100, 273), (100, 274), (100, 275), (100, 276), (100, 277), (100, 278), (100, 279), (100, 280), (100, 282), (101, 158), (101, 160), (101, 161), (101, 162), (101, 163), (101, 164), (101, 165), (101, 166), (101, 167), (101, 168), (101, 169), (101, 170), (101, 171), (101, 172), (101, 173), (101, 174), (101, 175), (101, 176), (101, 177), (101, 178), (101, 179), (101, 180), (101, 181), (101, 182), (101, 183), (101, 184), (101, 185), (101, 186), (101, 187), (101, 188), (101, 189), (101, 190), (101, 191), (101, 192), (101, 193), (101, 194), (101, 195), (101, 196), (101, 197), (101, 198), (101, 199), (101, 200), (101, 201), (101, 202), (101, 203), (101, 210), (101, 264), (101, 270), (101, 271), (101, 272), (101, 273), (101, 274), (101, 275), (101, 276), (101, 277), (101, 278), (101, 279), (101, 280),
(101, 281), (102, 158), (102, 160), (102, 161), (102, 162), (102, 163), (102, 164), (102, 165), (102, 166), (102, 167), (102, 168), (102, 169), (102, 170), (102, 171), (102, 172), (102, 173), (102, 174), (102, 175), (102, 176), (102, 177), (102, 178), (102, 179), (102, 180), (102, 181), (102, 182), (102, 183), (102, 184), (102, 185), (102, 186), (102, 187), (102, 188), (102, 189), (102, 190), (102, 191), (102, 192), (102, 193), (102, 194), (102, 195), (102, 196), (102, 197), (102, 198), (102, 199), (102, 200), (102, 201), (102, 202), (102, 203), (102, 204), (102, 205), (102, 206), (102, 207), (102, 208), (102, 211), (102, 265), (102, 267), (102, 268), (102, 269), (102, 272), (102, 273), (102, 274), (102, 275), (102, 276), (102, 277), (102, 278), (102, 279), (102, 280), (102, 283), (103, 157), (103, 158), (103, 159), (103, 160), (103, 161), (103, 162),
(103, 163), (103, 164), (103, 165), (103, 166), (103, 167), (103, 168), (103, 169), (103, 170), (103, 171), (103, 172), (103, 173), (103, 174), (103, 175), (103, 176), (103, 177), (103, 178), (103, 184), (103, 185), (103, 186), (103, 187), (103, 188), (103, 189), (103, 190), (103, 191), (103, 192), (103, 193), (103, 194), (103, 195), (103, 196), (103, 197), (103, 198), (103, 199), (103, 200), (103, 201), (103, 202), (103, 203), (103, 204), (103, 205), (103, 206), (103, 207), (103, 208), (103, 209), (103, 210), (103, 213), (103, 270), (103, 271), (103, 274), (103, 275), (103, 276), (103, 277), (103, 278), (103, 279), (103, 281), (104, 157), (104, 159), (104, 160), (104, 161), (104, 162), (104, 163), (104, 164), (104, 165), (104, 166), (104, 167), (104, 168), (104, 169), (104, 170), (104, 171), (104, 172), (104, 173), (104, 174), (104, 175), (104, 179),
(104, 180), (104, 181), (104, 182), (104, 183), (104, 190), (104, 191), (104, 192), (104, 193), (104, 194), (104, 195), (104, 196), (104, 197), (104, 198), (104, 199), (104, 200), (104, 201), (104, 202), (104, 203), (104, 204), (104, 205), (104, 206), (104, 207), (104, 208), (104, 209), (104, 210), (104, 211), (104, 214), (104, 272), (104, 276), (104, 277), (104, 278), (104, 280), (105, 157), (105, 159), (105, 160), (105, 161), (105, 162), (105, 163), (105, 164), (105, 165), (105, 166), (105, 167), (105, 168), (105, 169), (105, 170), (105, 171), (105, 172), (105, 176), (105, 177), (105, 178), (105, 184), (105, 186), (105, 187), (105, 188), (105, 189), (105, 194), (105, 195), (105, 196), (105, 197), (105, 198), (105, 199), (105, 200), (105, 201), (105, 202), (105, 203), (105, 204), (105, 205), (105, 206), (105, 207), (105, 208), (105, 209), (105, 210),
(105, 211), (105, 212), (105, 213), (105, 216), (105, 274), (105, 278), (105, 280), (106, 156), (106, 158), (106, 159), (106, 160), (106, 161), (106, 162), (106, 163), (106, 164), (106, 165), (106, 166), (106, 167), (106, 168), (106, 169), (106, 173), (106, 174), (106, 175), (106, 190), (106, 191), (106, 192), (106, 193), (106, 196), (106, 197), (106, 198), (106, 199), (106, 200), (106, 201), (106, 202), (106, 203), (106, 204), (106, 205), (106, 206), (106, 207), (106, 208), (106, 209), (106, 210), (106, 211), (106, 212), (106, 213), (106, 214), (106, 217), (106, 218), (106, 220), (106, 276), (106, 280), (107, 156), (107, 158), (107, 159), (107, 160), (107, 161), (107, 162), (107, 163), (107, 164), (107, 165), (107, 166), (107, 167), (107, 170), (107, 171), (107, 172), (107, 194), (107, 198), (107, 199), (107, 200), (107, 201), (107, 202), (107, 203),
(107, 204), (107, 205), (107, 206), (107, 207), (107, 208), (107, 209), (107, 210), (107, 211), (107, 212), (107, 213), (107, 214), (107, 215), (107, 216), (107, 221), (107, 278), (107, 280), (108, 155), (108, 157), (108, 158), (108, 159), (108, 160), (108, 161), (108, 162), (108, 163), (108, 164), (108, 165), (108, 168), (108, 196), (108, 200), (108, 201), (108, 202), (108, 203), (108, 204), (108, 205), (108, 206), (108, 207), (108, 208), (108, 209), (108, 210), (108, 211), (108, 212), (108, 213), (108, 214), (108, 215), (108, 216), (108, 217), (108, 218), (108, 219), (108, 279), (109, 155), (109, 157), (109, 158), (109, 159), (109, 160), (109, 161), (109, 162), (109, 163), (109, 164), (109, 167), (109, 198), (109, 202), (109, 203), (109, 204), (109, 205), (109, 206), (109, 207), (109, 208), (109, 209), (109, 210), (109, 211), (109, 212), (109, 213),
(109, 214), (109, 215), (109, 216), (109, 217), (109, 218), (109, 219), (109, 220), (109, 222), (110, 154), (110, 156), (110, 157), (110, 158), (110, 159), (110, 160), (110, 161), (110, 162), (110, 163), (110, 165), (110, 200), (110, 204), (110, 205), (110, 206), (110, 207), (110, 208), (110, 209), (110, 210), (110, 211), (110, 212), (110, 213), (110, 214), (110, 215), (110, 216), (110, 217), (110, 218), (110, 219), (110, 220), (110, 221), (110, 223), (111, 154), (111, 156), (111, 157), (111, 158), (111, 159), (111, 160), (111, 161), (111, 162), (111, 164), (111, 202), (111, 206), (111, 207), (111, 208), (111, 209), (111, 210), (111, 211), (111, 212), (111, 213), (111, 214), (111, 215), (111, 216), (111, 217), (111, 218), (111, 219), (111, 220), (111, 221), (111, 223), (112, 153), (112, 155), (112, 156), (112, 157), (112, 158), (112, 159), (112, 160),
(112, 161), (112, 163), (112, 204), (112, 208), (112, 209), (112, 210), (112, 211), (112, 212), (112, 213), (112, 214), (112, 215), (112, 216), (112, 217), (112, 218), (112, 219), (112, 220), (112, 221), (112, 223), (113, 152), (113, 154), (113, 155), (113, 156), (113, 157), (113, 158), (113, 159), (113, 160), (113, 162), (113, 206), (113, 209), (113, 210), (113, 211), (113, 212), (113, 213), (113, 214), (113, 215), (113, 216), (113, 217), (113, 218), (113, 219), (113, 220), (113, 221), (113, 223), (114, 152), (114, 154), (114, 155), (114, 156), (114, 157), (114, 158), (114, 159), (114, 161), (114, 208), (114, 210), (114, 211), (114, 212), (114, 213), (114, 214), (114, 215), (114, 216), (114, 217), (114, 218), (114, 219), (114, 220), (114, 221), (114, 223), (115, 151), (115, 153), (115, 154), (115, 155), (115, 156), (115, 157), (115, 158), (115, 159),
(115, 161), (115, 209), (115, 211), (115, 212), (115, 213), (115, 214), (115, 215), (115, 216), (115, 217), (115, 218), (115, 219), (115, 220), (115, 221), (115, 223), (116, 150), (116, 152), (116, 153), (116, 154), (116, 155), (116, 156), (116, 157), (116, 158), (116, 160), (116, 210), (116, 212), (116, 213), (116, 214), (116, 215), (116, 216), (116, 217), (116, 218), (116, 219), (116, 220), (116, 221), (116, 223), (117, 149), (117, 151), (117, 152), (117, 153), (117, 154), (117, 155), (117, 156), (117, 157), (117, 159), (117, 210), (117, 212), (117, 213), (117, 214), (117, 215), (117, 216), (117, 217), (117, 218), (117, 219), (117, 220), (117, 221), (117, 223), (118, 149), (118, 151), (118, 152), (118, 153), (118, 154), (118, 155), (118, 156), (118, 157), (118, 159), (118, 211), (118, 213), (118, 214), (118, 215), (118, 216), (118, 217), (118, 218),
(118, 219), (118, 220), (118, 221), (118, 223), (119, 148), (119, 150), (119, 151), (119, 152), (119, 153), (119, 154), (119, 155), (119, 156), (119, 158), (119, 212), (119, 214), (119, 215), (119, 216), (119, 217), (119, 218), (119, 219), (119, 220), (119, 222), (120, 147), (120, 149), (120, 150), (120, 151), (120, 152), (120, 153), (120, 154), (120, 155), (120, 156), (120, 158), (120, 212), (120, 214), (120, 215), (120, 216), (120, 217), (120, 218), (120, 219), (120, 220), (120, 222), (121, 146), (121, 148), (121, 149), (121, 150), (121, 151), (121, 152), (121, 153), (121, 154), (121, 155), (121, 156), (121, 158), (121, 213), (121, 215), (121, 216), (121, 217), (121, 218), (121, 219), (121, 220), (121, 222), (122, 145), (122, 147), (122, 148), (122, 149), (122, 150), (122, 151), (122, 152), (122, 153), (122, 154), (122, 155), (122, 157), (122, 213),
(122, 215), (122, 216), (122, 217), (122, 218), (122, 219), (122, 221), (123, 144), (123, 146), (123, 147), (123, 148), (123, 149), (123, 150), (123, 151), (123, 152), (123, 153), (123, 154), (123, 155), (123, 157), (123, 214), (123, 216), (123, 217), (123, 218), (123, 219), (123, 221), (124, 142), (124, 145), (124, 146), (124, 147), (124, 148), (124, 149), (124, 150), (124, 151), (124, 152), (124, 153), (124, 154), (124, 155), (124, 157), (124, 215), (124, 217), (124, 218), (124, 219), (124, 221), (125, 141), (125, 144), (125, 145), (125, 146), (125, 147), (125, 148), (125, 149), (125, 150), (125, 151), (125, 152), (125, 153), (125, 154), (125, 155), (125, 157), (125, 218), (125, 220), (126, 140), (126, 143), (126, 144), (126, 145), (126, 146), (126, 147), (126, 148), (126, 149), (126, 150), (126, 151), (126, 152), (126, 153), (126, 154), (126, 155),
(126, 157), (126, 216), (126, 217), (126, 220), (127, 141), (127, 142), (127, 143), (127, 144), (127, 145), (127, 146), (127, 147), (127, 148), (127, 149), (127, 150), (127, 151), (127, 152), (127, 153), (127, 154), (127, 155), (127, 157), (127, 218), (127, 220), (128, 137), (128, 140), (128, 141), (128, 142), (128, 143), (128, 144), (128, 145), (128, 146), (128, 147), (128, 148), (128, 149), (128, 150), (128, 151), (128, 152), (128, 153), (128, 154), (128, 155), (128, 156), (128, 157), (129, 135), (129, 138), (129, 139), (129, 140), (129, 141), (129, 142), (129, 143), (129, 144), (129, 145), (129, 146), (129, 147), (129, 148), (129, 149), (129, 150), (129, 151), (129, 152), (129, 153), (129, 154), (129, 155), (129, 157), (130, 88), (130, 91), (130, 133), (130, 134), (130, 137), (130, 138), (130, 139), (130, 140), (130, 141), (130, 142), (130, 143),
(130, 144), (130, 145), (130, 146), (130, 147), (130, 148), (130, 149), (130, 150), (130, 151), (130, 152), (130, 153), (130, 154), (130, 155), (130, 157), (131, 86), (131, 93), (131, 132), (131, 135), (131, 136), (131, 137), (131, 138), (131, 139), (131, 140), (131, 141), (131, 142), (131, 143), (131, 144), (131, 145), (131, 146), (131, 147), (131, 148), (131, 149), (131, 150), (131, 151), (131, 152), (131, 153), (131, 154), (131, 155), (131, 157), (132, 85), (132, 88), (132, 89), (132, 90), (132, 91), (132, 94), (132, 134), (132, 135), (132, 136), (132, 137), (132, 138), (132, 139), (132, 140), (132, 141), (132, 142), (132, 143), (132, 144), (132, 145), (132, 146), (132, 147), (132, 148), (132, 149), (132, 150), (132, 151), (132, 152), (132, 153), (132, 154), (132, 155), (132, 157), (133, 84), (133, 87), (133, 88), (133, 89), (133, 90),
(133, 91), (133, 92), (133, 93), (133, 96), (133, 131), (133, 133), (133, 134), (133, 135), (133, 136), (133, 137), (133, 138), (133, 139), (133, 140), (133, 141), (133, 142), (133, 143), (133, 144), (133, 145), (133, 146), (133, 147), (133, 148), (133, 149), (133, 150), (133, 151), (133, 152), (133, 153), (133, 154), (133, 155), (133, 157), (134, 84), (134, 86), (134, 87), (134, 88), (134, 89), (134, 90), (134, 91), (134, 92), (134, 93), (134, 94), (134, 97), (134, 130), (134, 132), (134, 133), (134, 134), (134, 135), (134, 136), (134, 137), (134, 138), (134, 139), (134, 140), (134, 141), (134, 142), (134, 143), (134, 144), (134, 145), (134, 146), (134, 147), (134, 148), (134, 149), (134, 150), (134, 151), (134, 152), (134, 153), (134, 154), (134, 155), (134, 157), (135, 83), (135, 85), (135, 86), (135, 87), (135, 88), (135, 89),
(135, 90), (135, 91), (135, 92), (135, 93), (135, 94), (135, 95), (135, 98), (135, 129), (135, 131), (135, 132), (135, 133), (135, 134), (135, 135), (135, 136), (135, 137), (135, 138), (135, 139), (135, 140), (135, 141), (135, 142), (135, 143), (135, 144), (135, 145), (135, 146), (135, 147), (135, 148), (135, 149), (135, 150), (135, 151), (135, 152), (135, 153), (135, 154), (135, 155), (135, 156), (135, 158), (136, 83), (136, 85), (136, 86), (136, 87), (136, 88), (136, 89), (136, 90), (136, 91), (136, 92), (136, 93), (136, 94), (136, 95), (136, 96), (136, 99), (136, 129), (136, 131), (136, 132), (136, 133), (136, 134), (136, 135), (136, 136), (136, 137), (136, 138), (136, 139), (136, 140), (136, 141), (136, 142), (136, 143), (136, 144), (136, 145), (136, 146), (136, 147), (136, 148), (136, 149), (136, 150), (136, 151), (136, 152),
(136, 153), (136, 154), (136, 155), (136, 156), (136, 158), (137, 83), (137, 85), (137, 86), (137, 87), (137, 88), (137, 89), (137, 90), (137, 91), (137, 92), (137, 93), (137, 94), (137, 95), (137, 96), (137, 97), (137, 100), (137, 128), (137, 130), (137, 131), (137, 132), (137, 133), (137, 134), (137, 135), (137, 136), (137, 137), (137, 138), (137, 139), (137, 140), (137, 141), (137, 142), (137, 143), (137, 144), (137, 145), (137, 146), (137, 147), (137, 148), (137, 149), (137, 150), (137, 151), (137, 152), (137, 153), (137, 154), (137, 155), (137, 156), (137, 157), (137, 159), (138, 82), (138, 84), (138, 85), (138, 86), (138, 87), (138, 88), (138, 89), (138, 90), (138, 91), (138, 92), (138, 93), (138, 94), (138, 95), (138, 96), (138, 97), (138, 98), (138, 101), (138, 127), (138, 129), (138, 130), (138, 131), (138, 132),
(138, 133), (138, 134), (138, 135), (138, 136), (138, 137), (138, 138), (138, 139), (138, 140), (138, 141), (138, 142), (138, 143), (138, 144), (138, 145), (138, 146), (138, 147), (138, 148), (138, 149), (138, 150), (138, 151), (138, 152), (138, 153), (138, 154), (138, 155), (138, 156), (138, 157), (138, 159), (139, 82), (139, 84), (139, 85), (139, 86), (139, 87), (139, 88), (139, 89), (139, 90), (139, 91), (139, 92), (139, 93), (139, 94), (139, 95), (139, 96), (139, 97), (139, 98), (139, 99), (139, 102), (139, 126), (139, 128), (139, 129), (139, 130), (139, 131), (139, 132), (139, 133), (139, 134), (139, 135), (139, 136), (139, 137), (139, 138), (139, 139), (139, 140), (139, 141), (139, 142), (139, 143), (139, 144), (139, 145), (139, 146), (139, 147), (139, 148), (139, 149), (139, 150), (139, 151), (139, 152), (139, 153), (139, 154),
(139, 155), (139, 156), (139, 157), (139, 158), (139, 160), (140, 82), (140, 84), (140, 85), (140, 86), (140, 87), (140, 88), (140, 89), (140, 90), (140, 91), (140, 92), (140, 93), (140, 94), (140, 95), (140, 96), (140, 97), (140, 98), (140, 99), (140, 100), (140, 103), (140, 125), (140, 127), (140, 128), (140, 129), (140, 130), (140, 131), (140, 132), (140, 133), (140, 134), (140, 135), (140, 136), (140, 137), (140, 138), (140, 139), (140, 140), (140, 141), (140, 145), (140, 146), (140, 151), (140, 152), (140, 153), (140, 154), (140, 155), (140, 156), (140, 157), (140, 158), (140, 159), (140, 161), (141, 82), (141, 84), (141, 85), (141, 86), (141, 87), (141, 88), (141, 89), (141, 90), (141, 91), (141, 92), (141, 93), (141, 94), (141, 95), (141, 96), (141, 97), (141, 98), (141, 99), (141, 100), (141, 101), (141, 104),
(141, 123), (141, 126), (141, 127), (141, 128), (141, 129), (141, 130), (141, 131), (141, 132), (141, 133), (141, 134), (141, 135), (141, 136), (141, 137), (141, 138), (141, 139), (141, 142), (141, 143), (141, 144), (141, 145), (141, 146), (141, 147), (141, 148), (141, 149), (141, 150), (141, 153), (141, 154), (141, 155), (141, 156), (141, 157), (141, 158), (141, 159), (141, 160), (141, 163), (142, 81), (142, 83), (142, 84), (142, 85), (142, 86), (142, 87), (142, 88), (142, 89), (142, 90), (142, 91), (142, 92), (142, 93), (142, 94), (142, 95), (142, 96), (142, 97), (142, 98), (142, 99), (142, 100), (142, 101), (142, 102), (142, 105), (142, 118), (142, 119), (142, 120), (142, 121), (142, 125), (142, 126), (142, 127), (142, 128), (142, 129), (142, 130), (142, 131), (142, 132), (142, 133), (142, 134), (142, 135), (142, 136), (142, 137),
(142, 140), (142, 151), (142, 155), (142, 156), (142, 157), (142, 158), (142, 159), (142, 160), (142, 161), (142, 164), (143, 81), (143, 83), (143, 84), (143, 85), (143, 86), (143, 87), (143, 88), (143, 89), (143, 90), (143, 91), (143, 92), (143, 93), (143, 94), (143, 95), (143, 96), (143, 97), (143, 98), (143, 99), (143, 100), (143, 101), (143, 102), (143, 103), (143, 106), (143, 116), (143, 117), (143, 122), (143, 123), (143, 124), (143, 125), (143, 126), (143, 127), (143, 128), (143, 129), (143, 130), (143, 131), (143, 132), (143, 133), (143, 134), (143, 135), (143, 136), (143, 139), (143, 153), (143, 156), (143, 157), (143, 158), (143, 159), (143, 160), (143, 161), (143, 162), (143, 163), (143, 166), (144, 81), (144, 83), (144, 84), (144, 85), (144, 86), (144, 87), (144, 88), (144, 89), (144, 90), (144, 91), (144, 92),
(144, 93), (144, 94), (144, 95), (144, 96), (144, 97), (144, 98), (144, 99), (144, 100), (144, 101), (144, 102), (144, 103), (144, 104), (144, 105), (144, 107), (144, 114), (144, 115), (144, 118), (144, 119), (144, 120), (144, 121), (144, 122), (144, 123), (144, 124), (144, 125), (144, 126), (144, 127), (144, 128), (144, 129), (144, 130), (144, 131), (144, 132), (144, 133), (144, 134), (144, 135), (144, 137), (144, 155), (144, 157), (144, 158), (144, 159), (144, 160), (144, 161), (144, 162), (144, 163), (144, 164), (144, 168), (145, 81), (145, 83), (145, 84), (145, 85), (145, 86), (145, 87), (145, 88), (145, 89), (145, 90), (145, 91), (145, 92), (145, 93), (145, 94), (145, 95), (145, 96), (145, 97), (145, 98), (145, 99), (145, 100), (145, 101), (145, 102), (145, 103), (145, 104), (145, 105), (145, 106), (145, 109), (145, 110),
(145, 111), (145, 112), (145, 113), (145, 116), (145, 117), (145, 118), (145, 119), (145, 120), (145, 121), (145, 122), (145, 123), (145, 124), (145, 125), (145, 126), (145, 127), (145, 128), (145, 129), (145, 130), (145, 131), (145, 132), (145, 133), (145, 134), (145, 136), (145, 156), (145, 159), (145, 160), (145, 161), (145, 162), (145, 163), (145, 164), (145, 165), (145, 166), (145, 170), (146, 80), (146, 82), (146, 83), (146, 84), (146, 85), (146, 86), (146, 87), (146, 88), (146, 89), (146, 90), (146, 91), (146, 92), (146, 93), (146, 94), (146, 95), (146, 96), (146, 97), (146, 98), (146, 99), (146, 100), (146, 101), (146, 102), (146, 103), (146, 104), (146, 105), (146, 106), (146, 107), (146, 114), (146, 115), (146, 116), (146, 117), (146, 118), (146, 119), (146, 120), (146, 121), (146, 122), (146, 123), (146, 124), (146, 125),
(146, 126), (146, 127), (146, 128), (146, 129), (146, 130), (146, 131), (146, 132), (146, 133), (146, 135), (146, 157), (146, 160), (146, 161), (146, 162), (146, 163), (146, 164), (146, 165), (146, 166), (146, 167), (146, 168), (146, 171), (147, 80), (147, 82), (147, 83), (147, 84), (147, 85), (147, 86), (147, 87), (147, 88), (147, 89), (147, 90), (147, 91), (147, 92), (147, 93), (147, 94), (147, 95), (147, 96), (147, 97), (147, 98), (147, 99), (147, 100), (147, 101), (147, 102), (147, 103), (147, 104), (147, 105), (147, 106), (147, 107), (147, 108), (147, 109), (147, 110), (147, 111), (147, 112), (147, 113), (147, 114), (147, 115), (147, 116), (147, 117), (147, 118), (147, 119), (147, 120), (147, 121), (147, 122), (147, 123), (147, 124), (147, 125), (147, 126), (147, 127), (147, 128), (147, 129), (147, 130), (147, 131), (147, 132),
(147, 133), (147, 135), (147, 158), (147, 161), (147, 162), (147, 163), (147, 164), (147, 165), (147, 166), (147, 167), (147, 168), (147, 169), (147, 170), (147, 172), (148, 79), (148, 81), (148, 82), (148, 83), (148, 84), (148, 85), (148, 86), (148, 87), (148, 88), (148, 89), (148, 90), (148, 91), (148, 92), (148, 93), (148, 94), (148, 95), (148, 96), (148, 97), (148, 98), (148, 99), (148, 100), (148, 101), (148, 102), (148, 103), (148, 104), (148, 105), (148, 106), (148, 107), (148, 108), (148, 109), (148, 110), (148, 111), (148, 112), (148, 113), (148, 114), (148, 115), (148, 116), (148, 117), (148, 118), (148, 119), (148, 120), (148, 121), (148, 122), (148, 123), (148, 124), (148, 125), (148, 126), (148, 127), (148, 128), (148, 129), (148, 130), (148, 131), (148, 132), (148, 134), (148, 159), (148, 162), (148, 163), (148, 164),
(148, 165), (148, 166), (148, 167), (148, 168), (148, 169), (148, 170), (148, 171), (148, 173), (149, 79), (149, 81), (149, 82), (149, 83), (149, 84), (149, 85), (149, 86), (149, 87), (149, 88), (149, 89), (149, 90), (149, 91), (149, 92), (149, 93), (149, 94), (149, 95), (149, 96), (149, 97), (149, 98), (149, 99), (149, 100), (149, 101), (149, 102), (149, 103), (149, 104), (149, 105), (149, 106), (149, 107), (149, 108), (149, 109), (149, 110), (149, 111), (149, 112), (149, 113), (149, 114), (149, 115), (149, 116), (149, 117), (149, 118), (149, 119), (149, 120), (149, 121), (149, 122), (149, 123), (149, 124), (149, 125), (149, 126), (149, 127), (149, 128), (149, 129), (149, 130), (149, 131), (149, 133), (149, 160), (149, 162), (149, 163), (149, 164), (149, 165), (149, 166), (149, 167), (149, 168), (149, 169), (149, 170), (149, 171),
(149, 173), (150, 78), (150, 80), (150, 81), (150, 82), (150, 83), (150, 84), (150, 85), (150, 86), (150, 87), (150, 88), (150, 89), (150, 90), (150, 91), (150, 92), (150, 93), (150, 94), (150, 95), (150, 96), (150, 97), (150, 98), (150, 99), (150, 100), (150, 101), (150, 102), (150, 103), (150, 104), (150, 105), (150, 106), (150, 107), (150, 108), (150, 109), (150, 110), (150, 111), (150, 112), (150, 113), (150, 114), (150, 115), (150, 116), (150, 117), (150, 118), (150, 119), (150, 120), (150, 121), (150, 122), (150, 123), (150, 124), (150, 125), (150, 126), (150, 127), (150, 128), (150, 129), (150, 130), (150, 131), (150, 133), (150, 161), (150, 163), (150, 164), (150, 165), (150, 166), (150, 167), (150, 168), (150, 169), (150, 170), (150, 171), (150, 172), (150, 174), (151, 78), (151, 80), (151, 81), (151, 82), (151, 83),
(151, 84), (151, 85), (151, 86), (151, 87), (151, 88), (151, 89), (151, 90), (151, 91), (151, 92), (151, 93), (151, 94), (151, 95), (151, 96), (151, 97), (151, 98), (151, 99), (151, 100), (151, 101), (151, 102), (151, 103), (151, 104), (151, 105), (151, 106), (151, 107), (151, 108), (151, 109), (151, 110), (151, 111), (151, 112), (151, 113), (151, 114), (151, 115), (151, 116), (151, 117), (151, 118), (151, 119), (151, 120), (151, 121), (151, 122), (151, 123), (151, 124), (151, 125), (151, 126), (151, 127), (151, 128), (151, 129), (151, 130), (151, 132), (151, 162), (151, 164), (151, 165), (151, 166), (151, 167), (151, 168), (151, 169), (151, 170), (151, 171), (151, 172), (151, 173), (151, 175), (152, 77), (152, 79), (152, 80), (152, 81), (152, 82), (152, 83), (152, 84), (152, 85), (152, 86), (152, 87), (152, 88), (152, 89),
(152, 90), (152, 91), (152, 92), (152, 93), (152, 94), (152, 95), (152, 96), (152, 97), (152, 98), (152, 99), (152, 100), (152, 101), (152, 102), (152, 103), (152, 104), (152, 105), (152, 106), (152, 107), (152, 108), (152, 109), (152, 110), (152, 111), (152, 112), (152, 113), (152, 114), (152, 115), (152, 116), (152, 117), (152, 118), (152, 119), (152, 120), (152, 121), (152, 122), (152, 123), (152, 124), (152, 125), (152, 126), (152, 127), (152, 128), (152, 129), (152, 130), (152, 131), (152, 132), (152, 163), (152, 165), (152, 166), (152, 167), (152, 168), (152, 169), (152, 170), (152, 171), (152, 172), (152, 173), (152, 175), (153, 77), (153, 78), (153, 79), (153, 80), (153, 81), (153, 82), (153, 83), (153, 84), (153, 85), (153, 86), (153, 87), (153, 88), (153, 89), (153, 90), (153, 91), (153, 92), (153, 93), (153, 94),
(153, 95), (153, 96), (153, 97), (153, 98), (153, 99), (153, 100), (153, 101), (153, 102), (153, 103), (153, 104), (153, 105), (153, 106), (153, 107), (153, 108), (153, 109), (153, 110), (153, 111), (153, 112), (153, 113), (153, 114), (153, 115), (153, 116), (153, 117), (153, 118), (153, 119), (153, 120), (153, 121), (153, 122), (153, 123), (153, 124), (153, 125), (153, 126), (153, 127), (153, 128), (153, 129), (153, 131), (153, 164), (153, 166), (153, 167), (153, 168), (153, 169), (153, 170), (153, 171), (153, 172), (153, 173), (153, 174), (153, 176), (154, 76), (154, 78), (154, 79), (154, 80), (154, 81), (154, 82), (154, 83), (154, 84), (154, 85), (154, 86), (154, 87), (154, 88), (154, 89), (154, 90), (154, 91), (154, 92), (154, 93), (154, 94), (154, 95), (154, 96), (154, 97), (154, 98), (154, 99), (154, 100), (154, 101),
(154, 102), (154, 103), (154, 104), (154, 105), (154, 106), (154, 107), (154, 108), (154, 109), (154, 110), (154, 111), (154, 112), (154, 113), (154, 114), (154, 115), (154, 116), (154, 117), (154, 118), (154, 119), (154, 120), (154, 121), (154, 122), (154, 123), (154, 124), (154, 125), (154, 126), (154, 127), (154, 128), (154, 129), (154, 131), (154, 164), (154, 166), (154, 167), (154, 168), (154, 169), (154, 170), (154, 171), (154, 172), (154, 173), (154, 174), (154, 175), (154, 177), (155, 75), (155, 77), (155, 78), (155, 79), (155, 80), (155, 81), (155, 82), (155, 83), (155, 84), (155, 85), (155, 86), (155, 87), (155, 88), (155, 89), (155, 90), (155, 91), (155, 92), (155, 93), (155, 94), (155, 95), (155, 96), (155, 97), (155, 98), (155, 99), (155, 100), (155, 101), (155, 102), (155, 103), (155, 104), (155, 105), (155, 106),
(155, 107), (155, 108), (155, 109), (155, 110), (155, 111), (155, 112), (155, 113), (155, 114), (155, 115), (155, 116), (155, 117), (155, 118), (155, 119), (155, 120), (155, 121), (155, 122), (155, 123), (155, 124), (155, 125), (155, 126), (155, 127), (155, 128), (155, 129), (155, 131), (155, 165), (155, 167), (155, 168), (155, 169), (155, 170), (155, 171), (155, 172), (155, 173), (155, 174), (155, 175), (155, 176), (155, 178), (156, 75), (156, 77), (156, 78), (156, 79), (156, 80), (156, 81), (156, 82), (156, 83), (156, 84), (156, 85), (156, 86), (156, 87), (156, 88), (156, 89), (156, 90), (156, 91), (156, 92), (156, 93), (156, 94), (156, 95), (156, 96), (156, 97), (156, 98), (156, 99), (156, 100), (156, 101), (156, 102), (156, 103), (156, 104), (156, 105), (156, 106), (156, 107), (156, 108), (156, 109), (156, 110), (156, 111),
(156, 112), (156, 113), (156, 114), (156, 115), (156, 116), (156, 117), (156, 118), (156, 119), (156, 120), (156, 121), (156, 122), (156, 123), (156, 124), (156, 125), (156, 126), (156, 127), (156, 128), (156, 129), (156, 131), (156, 166), (156, 168), (156, 169), (156, 170), (156, 171), (156, 172), (156, 173), (156, 174), (156, 175), (156, 176), (156, 179), (157, 74), (157, 76), (157, 77), (157, 78), (157, 79), (157, 80), (157, 81), (157, 82), (157, 83), (157, 84), (157, 85), (157, 86), (157, 87), (157, 88), (157, 89), (157, 90), (157, 91), (157, 92), (157, 93), (157, 94), (157, 95), (157, 96), (157, 97), (157, 98), (157, 99), (157, 100), (157, 101), (157, 102), (157, 103), (157, 104), (157, 105), (157, 106), (157, 107), (157, 108), (157, 109), (157, 110), (157, 111), (157, 112), (157, 113), (157, 114), (157, 115), (157, 116),
(157, 117), (157, 118), (157, 119), (157, 120), (157, 121), (157, 122), (157, 123), (157, 124), (157, 125), (157, 126), (157, 127), (157, 128), (157, 129), (157, 131), (157, 166), (157, 168), (157, 169), (157, 170), (157, 171), (157, 172), (157, 173), (157, 174), (157, 175), (157, 176), (157, 177), (157, 180), (158, 74), (158, 76), (158, 77), (158, 78), (158, 79), (158, 80), (158, 81), (158, 82), (158, 83), (158, 84), (158, 85), (158, 86), (158, 87), (158, 88), (158, 89), (158, 90), (158, 91), (158, 92), (158, 93), (158, 94), (158, 95), (158, 96), (158, 97), (158, 98), (158, 99), (158, 100), (158, 101), (158, 102), (158, 103), (158, 104), (158, 105), (158, 106), (158, 107), (158, 108), (158, 109), (158, 110), (158, 111), (158, 112), (158, 113), (158, 114), (158, 115), (158, 116), (158, 117), (158, 118), (158, 119), (158, 120),
(158, 121), (158, 122), (158, 123), (158, 124), (158, 125), (158, 126), (158, 127), (158, 128), (158, 129), (158, 131), (158, 167), (158, 169), (158, 170), (158, 171), (158, 172), (158, 173), (158, 174), (158, 175), (158, 176), (158, 177), (158, 178), (158, 181), (159, 73), (159, 75), (159, 76), (159, 77), (159, 78), (159, 79), (159, 80), (159, 81), (159, 82), (159, 83), (159, 84), (159, 85), (159, 86), (159, 87), (159, 88), (159, 89), (159, 90), (159, 91), (159, 92), (159, 93), (159, 94), (159, 95), (159, 96), (159, 97), (159, 98), (159, 99), (159, 100), (159, 101), (159, 102), (159, 103), (159, 104), (159, 105), (159, 106), (159, 107), (159, 108), (159, 109), (159, 110), (159, 111), (159, 112), (159, 113), (159, 114), (159, 115), (159, 116), (159, 117), (159, 118), (159, 119), (159, 120), (159, 121), (159, 122), (159, 123),
(159, 124), (159, 125), (159, 126), (159, 127), (159, 128), (159, 129), (159, 131), (159, 167), (159, 169), (159, 170), (159, 171), (159, 172), (159, 173), (159, 174), (159, 175), (159, 176), (159, 177), (159, 178), (159, 179), (159, 180), (159, 182), (160, 73), (160, 75), (160, 76), (160, 77), (160, 78), (160, 79), (160, 80), (160, 81), (160, 82), (160, 83), (160, 84), (160, 85), (160, 86), (160, 87), (160, 88), (160, 89), (160, 90), (160, 91), (160, 92), (160, 93), (160, 94), (160, 95), (160, 96), (160, 97), (160, 98), (160, 99), (160, 100), (160, 101), (160, 102), (160, 108), (160, 109), (160, 110), (160, 111), (160, 112), (160, 113), (160, 114), (160, 115), (160, 116), (160, 117), (160, 118), (160, 119), (160, 120), (160, 121), (160, 122), (160, 123), (160, 124), (160, 125), (160, 126), (160, 127), (160, 128), (160, 129),
(160, 131), (160, 168), (160, 170), (160, 171), (160, 172), (160, 173), (160, 174), (160, 175), (160, 176), (160, 177), (160, 178), (160, 179), (160, 180), (160, 181), (160, 184), (160, 185), (161, 72), (161, 74), (161, 75), (161, 76), (161, 77), (161, 78), (161, 79), (161, 80), (161, 81), (161, 82), (161, 83), (161, 84), (161, 85), (161, 86), (161, 87), (161, 88), (161, 89), (161, 90), (161, 91), (161, 92), (161, 93), (161, 94), (161, 95), (161, 96), (161, 97), (161, 98), (161, 102), (161, 103), (161, 104), (161, 105), (161, 106), (161, 107), (161, 113), (161, 114), (161, 115), (161, 116), (161, 117), (161, 118), (161, 119), (161, 120), (161, 121), (161, 122), (161, 123), (161, 124), (161, 125), (161, 126), (161, 127), (161, 128), (161, 129), (161, 130), (161, 132), (161, 169), (161, 171), (161, 172), (161, 173), (161, 174),
(161, 175), (161, 176), (161, 177), (161, 178), (161, 179), (161, 180), (161, 181), (161, 182), (161, 183), (161, 186), (161, 187), (162, 71), (162, 73), (162, 74), (162, 75), (162, 76), (162, 77), (162, 78), (162, 79), (162, 80), (162, 81), (162, 82), (162, 83), (162, 84), (162, 85), (162, 86), (162, 87), (162, 88), (162, 89), (162, 90), (162, 91), (162, 92), (162, 93), (162, 94), (162, 95), (162, 96), (162, 99), (162, 100), (162, 101), (162, 108), (162, 109), (162, 110), (162, 111), (162, 112), (162, 116), (162, 117), (162, 118), (162, 119), (162, 120), (162, 121), (162, 122), (162, 123), (162, 124), (162, 125), (162, 126), (162, 127), (162, 128), (162, 129), (162, 130), (162, 132), (162, 170), (162, 173), (162, 174), (162, 175), (162, 176), (162, 177), (162, 178), (162, 179), (162, 180), (162, 181), (162, 182), (162, 183),
(162, 184), (162, 185), (162, 189), (163, 71), (163, 73), (163, 74), (163, 75), (163, 76), (163, 77), (163, 78), (163, 79), (163, 80), (163, 81), (163, 82), (163, 83), (163, 84), (163, 85), (163, 86), (163, 87), (163, 88), (163, 89), (163, 90), (163, 91), (163, 92), (163, 93), (163, 94), (163, 95), (163, 98), (163, 114), (163, 117), (163, 118), (163, 119), (163, 120), (163, 121), (163, 122), (163, 123), (163, 124), (163, 125), (163, 126), (163, 127), (163, 128), (163, 129), (163, 130), (163, 132), (163, 171), (163, 172), (163, 175), (163, 176), (163, 177), (163, 178), (163, 179), (163, 180), (163, 181), (163, 182), (163, 183), (163, 184), (163, 185), (163, 186), (163, 187), (163, 191), (164, 70), (164, 72), (164, 73), (164, 74), (164, 75), (164, 76), (164, 77), (164, 78), (164, 79), (164, 80), (164, 81), (164, 82),
(164, 83), (164, 84), (164, 85), (164, 86), (164, 87), (164, 88), (164, 89), (164, 90), (164, 91), (164, 92), (164, 93), (164, 96), (164, 116), (164, 118), (164, 119), (164, 120), (164, 121), (164, 122), (164, 123), (164, 124), (164, 125), (164, 126), (164, 127), (164, 128), (164, 129), (164, 130), (164, 131), (164, 133), (164, 173), (164, 178), (164, 179), (164, 180), (164, 181), (164, 182), (164, 183), (164, 184), (164, 185), (164, 186), (164, 187), (164, 188), (164, 189), (164, 192), (165, 70), (165, 72), (165, 73), (165, 74), (165, 75), (165, 76), (165, 77), (165, 78), (165, 79), (165, 80), (165, 81), (165, 82), (165, 83), (165, 84), (165, 85), (165, 86), (165, 87), (165, 88), (165, 89), (165, 90), (165, 91), (165, 92), (165, 95), (165, 117), (165, 119), (165, 120), (165, 121), (165, 122), (165, 123), (165, 124),
(165, 125), (165, 126), (165, 127), (165, 128), (165, 129), (165, 130), (165, 131), (165, 133), (165, 175), (165, 177), (165, 181), (165, 182), (165, 183), (165, 184), (165, 185), (165, 186), (165, 187), (165, 188), (165, 189), (165, 190), (165, 191), (165, 193), (166, 69), (166, 71), (166, 72), (166, 73), (166, 74), (166, 75), (166, 76), (166, 77), (166, 78), (166, 79), (166, 80), (166, 81), (166, 82), (166, 83), (166, 84), (166, 85), (166, 86), (166, 87), (166, 88), (166, 89), (166, 90), (166, 91), (166, 94), (166, 118), (166, 120), (166, 121), (166, 122), (166, 123), (166, 124), (166, 125), (166, 126), (166, 127), (166, 128), (166, 129), (166, 130), (166, 131), (166, 132), (166, 134), (166, 178), (166, 180), (166, 186), (166, 187), (166, 188), (166, 189), (166, 192), (167, 69), (167, 71), (167, 72), (167, 73), (167, 74),
(167, 75), (167, 76), (167, 77), (167, 78), (167, 79), (167, 80), (167, 81), (167, 82), (167, 83), (167, 84), (167, 85), (167, 86), (167, 87), (167, 88), (167, 89), (167, 90), (167, 91), (167, 93), (167, 119), (167, 121), (167, 122), (167, 123), (167, 124), (167, 125), (167, 126), (167, 127), (167, 128), (167, 129), (167, 130), (167, 131), (167, 132), (167, 134), (167, 181), (167, 182), (167, 183), (167, 184), (167, 185), (167, 190), (167, 192), (168, 68), (168, 70), (168, 71), (168, 72), (168, 73), (168, 74), (168, 75), (168, 76), (168, 77), (168, 78), (168, 79), (168, 80), (168, 81), (168, 82), (168, 83), (168, 84), (168, 85), (168, 86), (168, 87), (168, 88), (168, 89), (168, 90), (168, 92), (168, 119), (168, 121), (168, 122), (168, 123), (168, 124), (168, 125), (168, 126), (168, 127), (168, 128), (168, 129),
(168, 130), (168, 131), (168, 132), (168, 133), (168, 135), (168, 186), (168, 187), (168, 188), (168, 189), (169, 68), (169, 70), (169, 71), (169, 72), (169, 73), (169, 74), (169, 75), (169, 76), (169, 77), (169, 78), (169, 79), (169, 80), (169, 81), (169, 82), (169, 83), (169, 84), (169, 85), (169, 86), (169, 87), (169, 88), (169, 89), (169, 91), (169, 120), (169, 122), (169, 123), (169, 124), (169, 125), (169, 126), (169, 127), (169, 128), (169, 129), (169, 130), (169, 131), (169, 132), (169, 133), (169, 135), (170, 67), (170, 68), (170, 69), (170, 70), (170, 71), (170, 72), (170, 73), (170, 74), (170, 75), (170, 76), (170, 77), (170, 78), (170, 79), (170, 80), (170, 81), (170, 82), (170, 83), (170, 84), (170, 85), (170, 86), (170, 87), (170, 88), (170, 90), (170, 120), (170, 122), (170, 123), (170, 124),
(170, 125), (170, 126), (170, 127), (170, 128), (170, 129), (170, 130), (170, 131), (170, 132), (170, 133), (170, 134), (170, 136), (171, 67), (171, 69), (171, 70), (171, 71), (171, 72), (171, 73), (171, 74), (171, 75), (171, 76), (171, 77), (171, 78), (171, 79), (171, 80), (171, 81), (171, 82), (171, 83), (171, 84), (171, 85), (171, 86), (171, 87), (171, 88), (171, 90), (171, 120), (171, 122), (171, 123), (171, 124), (171, 125), (171, 126), (171, 127), (171, 128), (171, 129), (171, 130), (171, 131), (171, 132), (171, 133), (171, 134), (171, 136), (172, 67), (172, 69), (172, 70), (172, 71), (172, 72), (172, 73), (172, 74), (172, 75), (172, 76), (172, 77), (172, 78), (172, 79), (172, 80), (172, 81), (172, 82), (172, 83), (172, 84), (172, 85), (172, 86), (172, 87), (172, 89), (172, 120), (172, 122), (172, 123),
(172, 124), (172, 125), (172, 126), (172, 127), (172, 128), (172, 129), (172, 130), (172, 131), (172, 132), (172, 133), (172, 134), (172, 136), (173, 66), (173, 68), (173, 69), (173, 70), (173, 71), (173, 72), (173, 73), (173, 74), (173, 75), (173, 76), (173, 77), (173, 78), (173, 79), (173, 80), (173, 81), (173, 82), (173, 83), (173, 84), (173, 85), (173, 86), (173, 87), (173, 89), (173, 120), (173, 122), (173, 123), (173, 124), (173, 125), (173, 126), (173, 127), (173, 128), (173, 129), (173, 130), (173, 131), (173, 132), (173, 133), (173, 134), (173, 135), (173, 136), (173, 137), (174, 66), (174, 68), (174, 69), (174, 70), (174, 71), (174, 72), (174, 73), (174, 74), (174, 75), (174, 76), (174, 77), (174, 78), (174, 79), (174, 80), (174, 81), (174, 82), (174, 83), (174, 84), (174, 85), (174, 86), (174, 88),
(174, 120), (174, 122), (174, 123), (174, 124), (174, 125), (174, 126), (174, 127), (174, 128), (174, 129), (174, 130), (174, 131), (174, 132), (174, 133), (174, 134), (174, 136), (175, 66), (175, 68), (175, 69), (175, 70), (175, 71), (175, 72), (175, 73), (175, 74), (175, 75), (175, 76), (175, 77), (175, 78), (175, 79), (175, 80), (175, 81), (175, 82), (175, 83), (175, 84), (175, 85), (175, 86), (175, 88), (175, 120), (175, 122), (175, 123), (175, 124), (175, 125), (175, 126), (175, 127), (175, 128), (175, 129), (175, 130), (175, 131), (175, 132), (175, 133), (175, 134), (175, 136), (176, 65), (176, 67), (176, 68), (176, 69), (176, 70), (176, 71), (176, 72), (176, 73), (176, 74), (176, 75), (176, 76), (176, 77), (176, 78), (176, 79), (176, 80), (176, 81), (176, 82), (176, 83), (176, 84), (176, 85), (176, 86),
(176, 88), (176, 120), (176, 122), (176, 123), (176, 124), (176, 125), (176, 126), (176, 127), (176, 128), (176, 129), (176, 130), (176, 131), (176, 132), (176, 133), (176, 134), (176, 135), (176, 136), (176, 137), (177, 65), (177, 67), (177, 68), (177, 69), (177, 70), (177, 71), (177, 72), (177, 73), (177, 74), (177, 75), (177, 76), (177, 77), (177, 78), (177, 79), (177, 80), (177, 81), (177, 82), (177, 83), (177, 84), (177, 85), (177, 86), (177, 88), (177, 119), (177, 121), (177, 122), (177, 123), (177, 124), (177, 125), (177, 126), (177, 127), (177, 128), (177, 129), (177, 130), (177, 131), (177, 132), (177, 133), (177, 134), (177, 135), (177, 137), (178, 65), (178, 67), (178, 68), (178, 69), (178, 70), (178, 71), (178, 72), (178, 73), (178, 74), (178, 75), (178, 76), (178, 77), (178, 78), (178, 79), (178, 80),
(178, 81), (178, 82), (178, 83), (178, 84), (178, 85), (178, 86), (178, 88), (178, 119), (178, 121), (178, 122), (178, 123), (178, 124), (178, 125), (178, 126), (178, 127), (178, 128), (178, 129), (178, 130), (178, 131), (178, 132), (178, 133), (178, 134), (178, 135), (178, 136), (178, 138), (179, 65), (179, 67), (179, 68), (179, 69), (179, 70), (179, 71), (179, 72), (179, 73), (179, 74), (179, 75), (179, 76), (179, 77), (179, 78), (179, 79), (179, 80), (179, 81), (179, 82), (179, 83), (179, 84), (179, 85), (179, 88), (179, 119), (179, 121), (179, 122), (179, 123), (179, 124), (179, 125), (179, 126), (179, 127), (179, 128), (179, 129), (179, 130), (179, 131), (179, 132), (179, 133), (179, 134), (179, 135), (179, 136), (179, 137), (179, 139), (180, 65), (180, 67), (180, 68), (180, 69), (180, 70), (180, 71), (180, 72),
(180, 73), (180, 74), (180, 75), (180, 76), (180, 77), (180, 78), (180, 79), (180, 80), (180, 81), (180, 82), (180, 83), (180, 86), (180, 119), (180, 121), (180, 122), (180, 123), (180, 124), (180, 125), (180, 126), (180, 127), (180, 128), (180, 129), (180, 130), (180, 131), (180, 132), (180, 133), (180, 134), (180, 135), (180, 136), (180, 137), (180, 138), (180, 140), (181, 66), (181, 84), (181, 85), (181, 119), (181, 121), (181, 122), (181, 123), (181, 124), (181, 125), (181, 126), (181, 127), (181, 128), (181, 129), (181, 130), (181, 131), (181, 132), (181, 133), (181, 134), (181, 135), (181, 136), (181, 137), (181, 138), (181, 141), (182, 67), (182, 69), (182, 70), (182, 71), (182, 72), (182, 73), (182, 74), (182, 75), (182, 76), (182, 77), (182, 78), (182, 79), (182, 80), (182, 81), (182, 83), (182, 118), (182, 119),
(182, 120), (182, 121), (182, 122), (182, 123), (182, 124), (182, 125), (182, 126), (182, 127), (182, 128), (182, 129), (182, 130), (182, 131), (182, 132), (182, 133), (182, 134), (182, 135), (182, 136), (182, 137), (182, 138), (182, 139), (182, 141), (183, 118), (183, 120), (183, 121), (183, 122), (183, 123), (183, 124), (183, 125), (183, 126), (183, 127), (183, 128), (183, 129), (183, 130), (183, 131), (183, 132), (183, 133), (183, 134), (183, 135), (183, 136), (183, 137), (183, 138), (183, 139), (183, 140), (183, 142), (184, 118), (184, 120), (184, 121), (184, 122), (184, 123), (184, 124), (184, 125), (184, 126), (184, 127), (184, 128), (184, 129), (184, 130), (184, 131), (184, 132), (184, 133), (184, 134), (184, 135), (184, 136), (184, 137), (184, 138), (184, 139), (184, 140), (184, 141), (184, 143), (185, 118), (185, 120), (185, 121), (185, 122),
(185, 123), (185, 124), (185, 125), (185, 126), (185, 127), (185, 128), (185, 129), (185, 130), (185, 134), (185, 135), (185, 136), (185, 137), (185, 138), (185, 139), (185, 140), (185, 141), (185, 143), (186, 118), (186, 131), (186, 132), (186, 135), (186, 136), (186, 137), (186, 138), (186, 139), (186, 140), (186, 141), (186, 142), (186, 144), (187, 118), (187, 120), (187, 121), (187, 122), (187, 123), (187, 124), (187, 125), (187, 126), (187, 127), (187, 128), (187, 129), (187, 130), (187, 134), (187, 136), (187, 137), (187, 138), (187, 139), (187, 140), (187, 141), (187, 142), (187, 143), (187, 145), (188, 135), (188, 137), (188, 138), (188, 139), (188, 140), (188, 141), (188, 142), (188, 143), (188, 144), (188, 146), (189, 135), (189, 137), (189, 138), (189, 139), (189, 140), (189, 141), (189, 142), (189, 143), (189, 144), (189, 146), (190, 135),
(190, 136), (190, 137), (190, 138), (190, 139), (190, 140), (190, 141), (190, 142), (190, 143), (190, 144), (190, 145), (190, 147), (191, 136), (191, 138), (191, 139), (191, 140), (191, 141), (191, 142), (191, 143), (191, 144), (191, 145), (191, 146), (191, 148), (192, 136), (192, 138), (192, 139), (192, 140), (192, 141), (192, 142), (192, 143), (192, 144), (192, 145), (192, 146), (192, 148), (193, 136), (193, 138), (193, 139), (193, 140), (193, 141), (193, 142), (193, 143), (193, 144), (193, 145), (193, 146), (193, 147), (193, 149), (194, 136), (194, 138), (194, 139), (194, 140), (194, 141), (194, 142), (194, 143), (194, 144), (194, 145), (194, 146), (194, 147), (194, 148), (194, 150), (195, 136), (195, 138), (195, 139), (195, 140), (195, 141), (195, 142), (195, 143), (195, 144), (195, 145), (195, 146), (195, 147), (195, 148), (195, 149), (196, 136),
(196, 138), (196, 139), (196, 140), (196, 141), (196, 142), (196, 143), (196, 144), (196, 145), (196, 146), (196, 147), (196, 148), (196, 149), (196, 151), (197, 136), (197, 138), (197, 139), (197, 140), (197, 141), (197, 142), (197, 143), (197, 144), (197, 145), (197, 146), (197, 147), (197, 148), (197, 149), (197, 150), (197, 152), (198, 136), (198, 138), (198, 139), (198, 140), (198, 141), (198, 142), (198, 143), (198, 144), (198, 145), (198, 146), (198, 147), (198, 148), (198, 149), (198, 150), (198, 152), (199, 136), (199, 138), (199, 139), (199, 140), (199, 141), (199, 142), (199, 143), (199, 144), (199, 145), (199, 146), (199, 147), (199, 148), (199, 149), (199, 150), (199, 152), (200, 136), (200, 138), (200, 139), (200, 140), (200, 141), (200, 142), (200, 143), (200, 144), (200, 145), (200, 146), (200, 147), (200, 148), (200, 149), (200, 150),
(200, 152), (201, 136), (201, 138), (201, 139), (201, 140), (201, 141), (201, 142), (201, 143), (201, 144), (201, 145), (201, 146), (201, 147), (201, 148), (201, 149), (201, 150), (201, 152), (202, 136), (202, 138), (202, 139), (202, 140), (202, 141), (202, 142), (202, 143), (202, 144), (202, 145), (202, 146), (202, 147), (202, 148), (202, 149), (202, 150), (202, 152), (203, 136), (203, 138), (203, 139), (203, 140), (203, 141), (203, 142), (203, 143), (203, 144), (203, 145), (203, 146), (203, 147), (203, 148), (203, 149), (203, 151), (204, 136), (204, 138), (204, 139), (204, 140), (204, 141), (204, 142), (204, 143), (204, 144), (204, 145), (204, 146), (204, 147), (204, 148), (204, 150), (205, 136), (205, 138), (205, 139), (205, 140), (205, 141), (205, 142), (205, 143), (205, 144), (205, 145), (205, 146), (205, 147), (205, 148), (205, 150), (206, 136),
(206, 138), (206, 139), (206, 140), (206, 141), (206, 142), (206, 143), (206, 144), (206, 145), (206, 146), (206, 147), (206, 149), (207, 136), (207, 138), (207, 139), (207, 140), (207, 141), (207, 142), (207, 143), (207, 144), (207, 145), (207, 146), (207, 148), (208, 136), (208, 138), (208, 139), (208, 140), (208, 141), (208, 142), (208, 143), (208, 144), (208, 145), (208, 146), (208, 148), (209, 135), (209, 137), (209, 138), (209, 139), (209, 140), (209, 141), (209, 142), (209, 143), (209, 144), (209, 145), (209, 147), (210, 135), (210, 137), (210, 138), (210, 139), (210, 140), (210, 141), (210, 142), (210, 143), (210, 144), (210, 146), (211, 135), (211, 137), (211, 138), (211, 139), (211, 140), (211, 141), (211, 142), (211, 143), (211, 145), (212, 118), (212, 120), (212, 121), (212, 122), (212, 123), (212, 124), (212, 125), (212, 126), (212, 127),
(212, 128), (212, 129), (212, 130), (212, 134), (212, 135), (212, 136), (212, 137), (212, 138), (212, 139), (212, 140), (212, 141), (212, 142), (212, 143), (212, 145), (213, 118), (213, 131), (213, 132), (213, 135), (213, 136), (213, 137), (213, 138), (213, 139), (213, 140), (213, 141), (213, 142), (213, 144), (214, 118), (214, 120), (214, 121), (214, 122), (214, 123), (214, 124), (214, 125), (214, 126), (214, 127), (214, 128), (214, 129), (214, 130), (214, 134), (214, 135), (214, 136), (214, 137), (214, 138), (214, 139), (214, 140), (214, 141), (214, 143), (215, 118), (215, 120), (215, 121), (215, 122), (215, 123), (215, 124), (215, 125), (215, 126), (215, 127), (215, 128), (215, 129), (215, 130), (215, 131), (215, 132), (215, 133), (215, 134), (215, 135), (215, 136), (215, 137), (215, 138), (215, 139), (215, 140), (215, 141), (215, 143), (216, 118),
(216, 120), (216, 121), (216, 122), (216, 123), (216, 124), (216, 125), (216, 126), (216, 127), (216, 128), (216, 129), (216, 130), (216, 131), (216, 132), (216, 133), (216, 134), (216, 135), (216, 136), (216, 137), (216, 138), (216, 139), (216, 140), (216, 142), (217, 67), (217, 69), (217, 70), (217, 71), (217, 72), (217, 73), (217, 74), (217, 75), (217, 76), (217, 77), (217, 78), (217, 79), (217, 80), (217, 81), (217, 83), (217, 118), (217, 119), (217, 120), (217, 121), (217, 122), (217, 123), (217, 124), (217, 125), (217, 126), (217, 127), (217, 128), (217, 129), (217, 130), (217, 131), (217, 132), (217, 133), (217, 134), (217, 135), (217, 136), (217, 137), (217, 138), (217, 139), (217, 141), (218, 66), (218, 85), (218, 119), (218, 121), (218, 122), (218, 123), (218, 124), (218, 125), (218, 126), (218, 127), (218, 128), (218, 129),
(218, 130), (218, 131), (218, 132), (218, 133), (218, 134), (218, 135), (218, 136), (218, 137), (218, 138), (219, 65), (219, 67), (219, 68), (219, 69), (219, 70), (219, 71), (219, 72), (219, 73), (219, 74), (219, 75), (219, 76), (219, 77), (219, 78), (219, 79), (219, 80), (219, 81), (219, 82), (219, 83), (219, 86), (219, 119), (219, 121), (219, 122), (219, 123), (219, 124), (219, 125), (219, 126), (219, 127), (219, 128), (219, 129), (219, 130), (219, 131), (219, 132), (219, 133), (219, 134), (219, 135), (219, 136), (219, 137), (219, 138), (219, 140), (220, 65), (220, 67), (220, 68), (220, 69), (220, 70), (220, 71), (220, 72), (220, 73), (220, 74), (220, 75), (220, 76), (220, 77), (220, 78), (220, 79), (220, 80), (220, 81), (220, 82), (220, 83), (220, 84), (220, 85), (220, 88), (220, 119), (220, 121), (220, 122),
(220, 123), (220, 124), (220, 125), (220, 126), (220, 127), (220, 128), (220, 129), (220, 130), (220, 131), (220, 132), (220, 133), (220, 134), (220, 135), (220, 136), (220, 137), (220, 139), (221, 65), (221, 67), (221, 68), (221, 69), (221, 70), (221, 71), (221, 72), (221, 73), (221, 74), (221, 75), (221, 76), (221, 77), (221, 78), (221, 79), (221, 80), (221, 81), (221, 82), (221, 83), (221, 84), (221, 85), (221, 86), (221, 88), (221, 119), (221, 121), (221, 122), (221, 123), (221, 124), (221, 125), (221, 126), (221, 127), (221, 128), (221, 129), (221, 130), (221, 131), (221, 132), (221, 133), (221, 134), (221, 135), (221, 136), (221, 138), (222, 65), (222, 67), (222, 68), (222, 69), (222, 70), (222, 71), (222, 72), (222, 73), (222, 74), (222, 75), (222, 76), (222, 77), (222, 78), (222, 79), (222, 80), (222, 81),
(222, 82), (222, 83), (222, 84), (222, 85), (222, 86), (222, 88), (222, 119), (222, 121), (222, 122), (222, 123), (222, 124), (222, 125), (222, 126), (222, 127), (222, 128), (222, 129), (222, 130), (222, 131), (222, 132), (222, 133), (222, 134), (222, 135), (222, 137), (223, 65), (223, 67), (223, 68), (223, 69), (223, 70), (223, 71), (223, 72), (223, 73), (223, 74), (223, 75), (223, 76), (223, 77), (223, 78), (223, 79), (223, 80), (223, 81), (223, 82), (223, 83), (223, 84), (223, 85), (223, 86), (223, 88), (223, 120), (223, 122), (223, 123), (223, 124), (223, 125), (223, 126), (223, 127), (223, 128), (223, 129), (223, 130), (223, 131), (223, 132), (223, 133), (223, 134), (223, 136), (224, 66), (224, 68), (224, 69), (224, 70), (224, 71), (224, 72), (224, 73), (224, 74), (224, 75), (224, 76), (224, 77), (224, 78),
(224, 79), (224, 80), (224, 81), (224, 82), (224, 83), (224, 84), (224, 85), (224, 86), (224, 88), (224, 120), (224, 122), (224, 123), (224, 124), (224, 125), (224, 126), (224, 127), (224, 128), (224, 129), (224, 130), (224, 131), (224, 132), (224, 133), (224, 134), (224, 136), (225, 66), (225, 68), (225, 69), (225, 70), (225, 71), (225, 72), (225, 73), (225, 74), (225, 75), (225, 76), (225, 77), (225, 78), (225, 79), (225, 80), (225, 81), (225, 82), (225, 83), (225, 84), (225, 85), (225, 86), (225, 88), (225, 120), (225, 122), (225, 123), (225, 124), (225, 125), (225, 126), (225, 127), (225, 128), (225, 129), (225, 130), (225, 131), (225, 132), (225, 133), (225, 134), (225, 136), (226, 66), (226, 68), (226, 69), (226, 70), (226, 71), (226, 72), (226, 73), (226, 74), (226, 75), (226, 76), (226, 77), (226, 78),
(226, 79), (226, 80), (226, 81), (226, 82), (226, 83), (226, 84), (226, 85), (226, 86), (226, 87), (226, 89), (226, 120), (226, 122), (226, 123), (226, 124), (226, 125), (226, 126), (226, 127), (226, 128), (226, 129), (226, 130), (226, 131), (226, 132), (226, 133), (226, 134), (226, 135), (226, 137), (227, 67), (227, 69), (227, 70), (227, 71), (227, 72), (227, 73), (227, 74), (227, 75), (227, 76), (227, 77), (227, 78), (227, 79), (227, 80), (227, 81), (227, 82), (227, 83), (227, 84), (227, 85), (227, 86), (227, 87), (227, 89), (227, 120), (227, 122), (227, 123), (227, 124), (227, 125), (227, 126), (227, 127), (227, 128), (227, 129), (227, 130), (227, 131), (227, 132), (227, 133), (227, 134), (227, 136), (228, 67), (228, 69), (228, 70), (228, 71), (228, 72), (228, 73), (228, 74), (228, 75), (228, 76), (228, 77),
(228, 78), (228, 79), (228, 80), (228, 81), (228, 82), (228, 83), (228, 84), (228, 85), (228, 86), (228, 87), (228, 88), (228, 90), (228, 120), (228, 122), (228, 123), (228, 124), (228, 125), (228, 126), (228, 127), (228, 128), (228, 129), (228, 130), (228, 131), (228, 132), (228, 133), (228, 134), (228, 136), (229, 68), (229, 69), (229, 70), (229, 71), (229, 72), (229, 73), (229, 74), (229, 75), (229, 76), (229, 77), (229, 78), (229, 79), (229, 80), (229, 81), (229, 82), (229, 83), (229, 84), (229, 85), (229, 86), (229, 87), (229, 88), (229, 90), (229, 120), (229, 122), (229, 123), (229, 124), (229, 125), (229, 126), (229, 127), (229, 128), (229, 129), (229, 130), (229, 131), (229, 132), (229, 133), (229, 134), (229, 136), (230, 68), (230, 70), (230, 71), (230, 72), (230, 73), (230, 74), (230, 75), (230, 76),
(230, 77), (230, 78), (230, 79), (230, 80), (230, 81), (230, 82), (230, 83), (230, 84), (230, 85), (230, 86), (230, 87), (230, 88), (230, 89), (230, 91), (230, 120), (230, 122), (230, 123), (230, 124), (230, 125), (230, 126), (230, 127), (230, 128), (230, 129), (230, 130), (230, 131), (230, 132), (230, 133), (230, 135), (231, 68), (231, 70), (231, 71), (231, 72), (231, 73), (231, 74), (231, 75), (231, 76), (231, 77), (231, 78), (231, 79), (231, 80), (231, 81), (231, 82), (231, 83), (231, 84), (231, 85), (231, 86), (231, 87), (231, 88), (231, 89), (231, 90), (231, 92), (231, 119), (231, 121), (231, 122), (231, 123), (231, 124), (231, 125), (231, 126), (231, 127), (231, 128), (231, 129), (231, 130), (231, 131), (231, 132), (231, 133), (231, 135), (231, 185), (231, 186), (231, 187), (231, 188), (231, 189), (232, 69),
(232, 71), (232, 72), (232, 73), (232, 74), (232, 75), (232, 76), (232, 77), (232, 78), (232, 79), (232, 80), (232, 81), (232, 82), (232, 83), (232, 84), (232, 85), (232, 86), (232, 87), (232, 88), (232, 89), (232, 90), (232, 91), (232, 93), (232, 119), (232, 121), (232, 122), (232, 123), (232, 124), (232, 125), (232, 126), (232, 127), (232, 128), (232, 129), (232, 130), (232, 131), (232, 132), (232, 134), (232, 181), (232, 182), (232, 183), (232, 184), (232, 190), (232, 192), (233, 69), (233, 71), (233, 72), (233, 73), (233, 74), (233, 75), (233, 76), (233, 77), (233, 78), (233, 79), (233, 80), (233, 81), (233, 82), (233, 83), (233, 84), (233, 85), (233, 86), (233, 87), (233, 88), (233, 89), (233, 90), (233, 91), (233, 94), (233, 118), (233, 120), (233, 121), (233, 122), (233, 123), (233, 124), (233, 125),
(233, 126), (233, 127), (233, 128), (233, 129), (233, 130), (233, 131), (233, 132), (233, 134), (233, 178), (233, 179), (233, 185), (233, 186), (233, 187), (233, 188), (233, 189), (233, 190), (233, 192), (234, 70), (234, 72), (234, 73), (234, 74), (234, 75), (234, 76), (234, 77), (234, 78), (234, 79), (234, 80), (234, 81), (234, 82), (234, 83), (234, 84), (234, 85), (234, 86), (234, 87), (234, 88), (234, 89), (234, 90), (234, 91), (234, 92), (234, 95), (234, 117), (234, 119), (234, 120), (234, 121), (234, 122), (234, 123), (234, 124), (234, 125), (234, 126), (234, 127), (234, 128), (234, 129), (234, 130), (234, 131), (234, 133), (234, 175), (234, 180), (234, 181), (234, 182), (234, 183), (234, 184), (234, 185), (234, 186), (234, 187), (234, 188), (234, 189), (234, 190), (234, 191), (234, 193), (235, 70), (235, 72), (235, 73),
(235, 74), (235, 75), (235, 76), (235, 77), (235, 78), (235, 79), (235, 80), (235, 81), (235, 82), (235, 83), (235, 84), (235, 85), (235, 86), (235, 87), (235, 88), (235, 89), (235, 90), (235, 91), (235, 92), (235, 93), (235, 96), (235, 116), (235, 118), (235, 119), (235, 120), (235, 121), (235, 122), (235, 123), (235, 124), (235, 125), (235, 126), (235, 127), (235, 128), (235, 129), (235, 130), (235, 131), (235, 133), (235, 173), (235, 177), (235, 178), (235, 179), (235, 180), (235, 181), (235, 182), (235, 183), (235, 184), (235, 185), (235, 186), (235, 187), (235, 188), (235, 189), (235, 192), (236, 71), (236, 73), (236, 74), (236, 75), (236, 76), (236, 77), (236, 78), (236, 79), (236, 80), (236, 81), (236, 82), (236, 83), (236, 84), (236, 85), (236, 86), (236, 87), (236, 88), (236, 89), (236, 90), (236, 91),
(236, 92), (236, 93), (236, 94), (236, 95), (236, 98), (236, 113), (236, 114), (236, 117), (236, 118), (236, 119), (236, 120), (236, 121), (236, 122), (236, 123), (236, 124), (236, 125), (236, 126), (236, 127), (236, 128), (236, 129), (236, 130), (236, 132), (236, 171), (236, 175), (236, 176), (236, 177), (236, 178), (236, 179), (236, 180), (236, 181), (236, 182), (236, 183), (236, 184), (236, 185), (236, 186), (236, 187), (236, 191), (237, 72), (237, 73), (237, 74), (237, 75), (237, 76), (237, 77), (237, 78), (237, 79), (237, 80), (237, 81), (237, 82), (237, 83), (237, 84), (237, 85), (237, 86), (237, 87), (237, 88), (237, 89), (237, 90), (237, 91), (237, 92), (237, 93), (237, 94), (237, 95), (237, 96), (237, 99), (237, 100), (237, 101), (237, 102), (237, 107), (237, 108), (237, 109), (237, 110), (237, 111), (237, 112),
(237, 116), (237, 117), (237, 118), (237, 119), (237, 120), (237, 121), (237, 122), (237, 123), (237, 124), (237, 125), (237, 126), (237, 127), (237, 128), (237, 129), (237, 130), (237, 132), (237, 170), (237, 173), (237, 174), (237, 175), (237, 176), (237, 177), (237, 178), (237, 179), (237, 180), (237, 181), (237, 182), (237, 183), (237, 184), (237, 185), (237, 189), (238, 72), (238, 74), (238, 75), (238, 76), (238, 77), (238, 78), (238, 79), (238, 80), (238, 81), (238, 82), (238, 83), (238, 84), (238, 85), (238, 86), (238, 87), (238, 88), (238, 89), (238, 90), (238, 91), (238, 92), (238, 93), (238, 94), (238, 95), (238, 96), (238, 97), (238, 98), (238, 103), (238, 104), (238, 105), (238, 106), (238, 107), (238, 113), (238, 114), (238, 115), (238, 116), (238, 117), (238, 118), (238, 119), (238, 120), (238, 121), (238, 122),
(238, 123), (238, 124), (238, 125), (238, 126), (238, 127), (238, 128), (238, 129), (238, 130), (238, 132), (238, 169), (238, 171), (238, 172), (238, 173), (238, 174), (238, 175), (238, 176), (238, 177), (238, 178), (238, 179), (238, 180), (238, 181), (238, 182), (238, 187), (239, 73), (239, 75), (239, 76), (239, 77), (239, 78), (239, 79), (239, 80), (239, 81), (239, 82), (239, 83), (239, 84), (239, 85), (239, 86), (239, 87), (239, 88), (239, 89), (239, 90), (239, 91), (239, 92), (239, 93), (239, 94), (239, 95), (239, 96), (239, 97), (239, 98), (239, 99), (239, 100), (239, 101), (239, 102), (239, 107), (239, 108), (239, 109), (239, 110), (239, 111), (239, 112), (239, 113), (239, 114), (239, 115), (239, 116), (239, 117), (239, 118), (239, 119), (239, 120), (239, 121), (239, 122), (239, 123), (239, 124), (239, 125), (239, 126),
(239, 127), (239, 128), (239, 129), (239, 131), (239, 168), (239, 170), (239, 171), (239, 172), (239, 173), (239, 174), (239, 175), (239, 176), (239, 177), (239, 178), (239, 179), (239, 180), (239, 181), (239, 184), (239, 185), (240, 73), (240, 75), (240, 76), (240, 77), (240, 78), (240, 79), (240, 80), (240, 81), (240, 82), (240, 83), (240, 84), (240, 85), (240, 86), (240, 87), (240, 88), (240, 89), (240, 90), (240, 91), (240, 92), (240, 93), (240, 94), (240, 95), (240, 96), (240, 97), (240, 98), (240, 99), (240, 100), (240, 101), (240, 102), (240, 103), (240, 104), (240, 105), (240, 106), (240, 107), (240, 108), (240, 109), (240, 110), (240, 111), (240, 112), (240, 113), (240, 114), (240, 115), (240, 116), (240, 117), (240, 118), (240, 119), (240, 120), (240, 121), (240, 122), (240, 123), (240, 124), (240, 125), (240, 126),
(240, 127), (240, 128), (240, 129), (240, 131), (240, 167), (240, 169), (240, 170), (240, 171), (240, 172), (240, 173), (240, 174), (240, 175), (240, 176), (240, 177), (240, 178), (240, 179), (240, 182), (241, 74), (241, 76), (241, 77), (241, 78), (241, 79), (241, 80), (241, 81), (241, 82), (241, 83), (241, 84), (241, 85), (241, 86), (241, 87), (241, 88), (241, 89), (241, 90), (241, 91), (241, 92), (241, 93), (241, 94), (241, 95), (241, 96), (241, 97), (241, 98), (241, 99), (241, 100), (241, 101), (241, 102), (241, 103), (241, 104), (241, 105), (241, 106), (241, 107), (241, 108), (241, 109), (241, 110), (241, 111), (241, 112), (241, 113), (241, 114), (241, 115), (241, 116), (241, 117), (241, 118), (241, 119), (241, 120), (241, 121), (241, 122), (241, 123), (241, 124), (241, 125), (241, 126), (241, 127), (241, 128), (241, 129),
(241, 131), (241, 167), (241, 169), (241, 170), (241, 171), (241, 172), (241, 173), (241, 174), (241, 175), (241, 176), (241, 177), (241, 178), (241, 181), (242, 74), (242, 76), (242, 77), (242, 78), (242, 79), (242, 80), (242, 81), (242, 82), (242, 83), (242, 84), (242, 85), (242, 86), (242, 87), (242, 88), (242, 89), (242, 90), (242, 91), (242, 92), (242, 93), (242, 94), (242, 95), (242, 96), (242, 97), (242, 98), (242, 99), (242, 100), (242, 101), (242, 102), (242, 103), (242, 104), (242, 105), (242, 106), (242, 107), (242, 108), (242, 109), (242, 110), (242, 111), (242, 112), (242, 113), (242, 114), (242, 115), (242, 116), (242, 117), (242, 118), (242, 119), (242, 120), (242, 121), (242, 122), (242, 123), (242, 124), (242, 125), (242, 126), (242, 127), (242, 128), (242, 129), (242, 131), (242, 166), (242, 168), (242, 169),
(242, 170), (242, 171), (242, 172), (242, 173), (242, 174), (242, 175), (242, 176), (242, 177), (243, 75), (243, 77), (243, 78), (243, 79), (243, 80), (243, 81), (243, 82), (243, 83), (243, 84), (243, 85), (243, 86), (243, 87), (243, 88), (243, 89), (243, 90), (243, 91), (243, 92), (243, 93), (243, 94), (243, 95), (243, 96), (243, 97), (243, 98), (243, 99), (243, 100), (243, 101), (243, 102), (243, 103), (243, 104), (243, 105), (243, 106), (243, 107), (243, 108), (243, 109), (243, 110), (243, 111), (243, 112), (243, 113), (243, 114), (243, 115), (243, 116), (243, 117), (243, 118), (243, 119), (243, 120), (243, 121), (243, 122), (243, 123), (243, 124), (243, 125), (243, 126), (243, 127), (243, 128), (243, 129), (243, 131), (243, 166), (243, 168), (243, 169), (243, 170), (243, 171), (243, 172), (243, 173), (243, 174), (243, 175),
(243, 176), (244, 75), (244, 77), (244, 78), (244, 79), (244, 80), (244, 81), (244, 82), (244, 83), (244, 84), (244, 85), (244, 86), (244, 87), (244, 88), (244, 89), (244, 90), (244, 91), (244, 92), (244, 93), (244, 94), (244, 95), (244, 96), (244, 97), (244, 98), (244, 99), (244, 100), (244, 101), (244, 102), (244, 103), (244, 104), (244, 105), (244, 106), (244, 107), (244, 108), (244, 109), (244, 110), (244, 111), (244, 112), (244, 113), (244, 114), (244, 115), (244, 116), (244, 117), (244, 118), (244, 119), (244, 120), (244, 121), (244, 122), (244, 123), (244, 124), (244, 125), (244, 126), (244, 127), (244, 128), (244, 129), (244, 131), (244, 165), (244, 167), (244, 168), (244, 169), (244, 170), (244, 171), (244, 172), (244, 173), (244, 174), (244, 175), (244, 176), (244, 178), (245, 76), (245, 78), (245, 79), (245, 80),
(245, 81), (245, 82), (245, 83), (245, 84), (245, 85), (245, 86), (245, 87), (245, 88), (245, 89), (245, 90), (245, 91), (245, 92), (245, 93), (245, 94), (245, 95), (245, 96), (245, 97), (245, 98), (245, 99), (245, 100), (245, 101), (245, 102), (245, 103), (245, 104), (245, 105), (245, 106), (245, 107), (245, 108), (245, 109), (245, 110), (245, 111), (245, 112), (245, 113), (245, 114), (245, 115), (245, 116), (245, 117), (245, 118), (245, 119), (245, 120), (245, 121), (245, 122), (245, 123), (245, 124), (245, 125), (245, 126), (245, 127), (245, 128), (245, 129), (245, 131), (245, 164), (245, 166), (245, 167), (245, 168), (245, 169), (245, 170), (245, 171), (245, 172), (245, 173), (245, 174), (245, 175), (245, 177), (246, 77), (246, 79), (246, 80), (246, 81), (246, 82), (246, 83), (246, 84), (246, 85), (246, 86), (246, 87),
(246, 88), (246, 89), (246, 90), (246, 91), (246, 92), (246, 93), (246, 94), (246, 95), (246, 96), (246, 97), (246, 98), (246, 99), (246, 100), (246, 101), (246, 102), (246, 103), (246, 104), (246, 105), (246, 106), (246, 107), (246, 108), (246, 109), (246, 110), (246, 111), (246, 112), (246, 113), (246, 114), (246, 115), (246, 116), (246, 117), (246, 118), (246, 119), (246, 120), (246, 121), (246, 122), (246, 123), (246, 124), (246, 125), (246, 126), (246, 127), (246, 128), (246, 129), (246, 131), (246, 164), (246, 166), (246, 167), (246, 168), (246, 169), (246, 170), (246, 171), (246, 172), (246, 173), (246, 174), (246, 176), (247, 77), (247, 79), (247, 80), (247, 81), (247, 82), (247, 83), (247, 84), (247, 85), (247, 86), (247, 87), (247, 88), (247, 89), (247, 90), (247, 91), (247, 92), (247, 93), (247, 94), (247, 95),
(247, 96), (247, 97), (247, 98), (247, 99), (247, 100), (247, 101), (247, 102), (247, 103), (247, 104), (247, 105), (247, 106), (247, 107), (247, 108), (247, 109), (247, 110), (247, 111), (247, 112), (247, 113), (247, 114), (247, 115), (247, 116), (247, 117), (247, 118), (247, 119), (247, 120), (247, 121), (247, 122), (247, 123), (247, 124), (247, 125), (247, 126), (247, 127), (247, 128), (247, 129), (247, 130), (247, 132), (247, 163), (247, 165), (247, 166), (247, 167), (247, 168), (247, 169), (247, 170), (247, 171), (247, 172), (247, 173), (247, 175), (248, 78), (248, 80), (248, 81), (248, 82), (248, 83), (248, 84), (248, 85), (248, 86), (248, 87), (248, 88), (248, 89), (248, 90), (248, 91), (248, 92), (248, 93), (248, 94), (248, 95), (248, 96), (248, 97), (248, 98), (248, 99), (248, 100), (248, 101), (248, 102), (248, 103),
(248, 104), (248, 105), (248, 106), (248, 107), (248, 108), (248, 109), (248, 110), (248, 111), (248, 112), (248, 113), (248, 114), (248, 115), (248, 116), (248, 117), (248, 118), (248, 119), (248, 120), (248, 121), (248, 122), (248, 123), (248, 124), (248, 125), (248, 126), (248, 127), (248, 128), (248, 129), (248, 130), (248, 132), (248, 162), (248, 164), (248, 165), (248, 166), (248, 167), (248, 168), (248, 169), (248, 170), (248, 171), (248, 172), (248, 173), (248, 175), (249, 78), (249, 80), (249, 81), (249, 82), (249, 83), (249, 84), (249, 85), (249, 86), (249, 87), (249, 88), (249, 89), (249, 90), (249, 91), (249, 92), (249, 93), (249, 94), (249, 95), (249, 96), (249, 97), (249, 98), (249, 99), (249, 100), (249, 101), (249, 102), (249, 103), (249, 104), (249, 105), (249, 106), (249, 107), (249, 108), (249, 109), (249, 110),
(249, 111), (249, 112), (249, 113), (249, 114), (249, 115), (249, 116), (249, 117), (249, 118), (249, 119), (249, 120), (249, 121), (249, 122), (249, 123), (249, 124), (249, 125), (249, 126), (249, 127), (249, 128), (249, 129), (249, 130), (249, 131), (249, 133), (249, 161), (249, 163), (249, 164), (249, 165), (249, 166), (249, 167), (249, 168), (249, 169), (249, 170), (249, 171), (249, 172), (249, 174), (250, 79), (250, 81), (250, 82), (250, 83), (250, 84), (250, 85), (250, 86), (250, 87), (250, 88), (250, 89), (250, 90), (250, 91), (250, 92), (250, 93), (250, 94), (250, 95), (250, 96), (250, 97), (250, 98), (250, 99), (250, 100), (250, 101), (250, 102), (250, 103), (250, 104), (250, 105), (250, 106), (250, 107), (250, 108), (250, 109), (250, 110), (250, 111), (250, 112), (250, 113), (250, 114), (250, 115), (250, 116), (250, 117),
(250, 118), (250, 119), (250, 120), (250, 121), (250, 122), (250, 123), (250, 124), (250, 125), (250, 126), (250, 127), (250, 128), (250, 129), (250, 130), (250, 131), (250, 133), (250, 160), (250, 162), (250, 163), (250, 164), (250, 165), (250, 166), (250, 167), (250, 168), (250, 169), (250, 170), (250, 171), (250, 173), (251, 79), (251, 81), (251, 82), (251, 83), (251, 84), (251, 85), (251, 86), (251, 87), (251, 88), (251, 89), (251, 90), (251, 91), (251, 92), (251, 93), (251, 94), (251, 95), (251, 96), (251, 97), (251, 98), (251, 99), (251, 100), (251, 101), (251, 102), (251, 103), (251, 104), (251, 105), (251, 106), (251, 107), (251, 108), (251, 109), (251, 110), (251, 111), (251, 112), (251, 113), (251, 114), (251, 115), (251, 116), (251, 117), (251, 118), (251, 119), (251, 120), (251, 121), (251, 122), (251, 123), (251, 124),
(251, 125), (251, 126), (251, 127), (251, 128), (251, 129), (251, 130), (251, 131), (251, 132), (251, 134), (251, 159), (251, 161), (251, 162), (251, 163), (251, 164), (251, 165), (251, 166), (251, 167), (251, 168), (251, 169), (251, 170), (251, 171), (251, 173), (252, 80), (252, 82), (252, 83), (252, 84), (252, 85), (252, 86), (252, 87), (252, 88), (252, 89), (252, 90), (252, 91), (252, 92), (252, 93), (252, 94), (252, 95), (252, 96), (252, 97), (252, 98), (252, 99), (252, 100), (252, 101), (252, 102), (252, 103), (252, 104), (252, 105), (252, 106), (252, 107), (252, 108), (252, 109), (252, 110), (252, 111), (252, 112), (252, 113), (252, 114), (252, 115), (252, 116), (252, 117), (252, 118), (252, 119), (252, 120), (252, 121), (252, 122), (252, 123), (252, 124), (252, 125), (252, 126), (252, 127), (252, 128), (252, 129), (252, 130),
(252, 131), (252, 132), (252, 133), (252, 135), (252, 158), (252, 161), (252, 162), (252, 163), (252, 164), (252, 165), (252, 166), (252, 167), (252, 168), (252, 169), (252, 170), (252, 172), (253, 80), (253, 82), (253, 83), (253, 84), (253, 85), (253, 86), (253, 87), (253, 88), (253, 89), (253, 90), (253, 91), (253, 92), (253, 93), (253, 94), (253, 95), (253, 96), (253, 97), (253, 98), (253, 99), (253, 100), (253, 101), (253, 102), (253, 103), (253, 104), (253, 105), (253, 106), (253, 107), (253, 114), (253, 115), (253, 116), (253, 117), (253, 118), (253, 119), (253, 120), (253, 121), (253, 122), (253, 123), (253, 124), (253, 125), (253, 126), (253, 127), (253, 128), (253, 129), (253, 130), (253, 131), (253, 132), (253, 133), (253, 157), (253, 160), (253, 161), (253, 162), (253, 163), (253, 164), (253, 165), (253, 166), (253, 167),
(253, 168), (253, 171), (254, 81), (254, 83), (254, 84), (254, 85), (254, 86), (254, 87), (254, 88), (254, 89), (254, 90), (254, 91), (254, 92), (254, 93), (254, 94), (254, 95), (254, 96), (254, 97), (254, 98), (254, 99), (254, 100), (254, 101), (254, 102), (254, 103), (254, 104), (254, 105), (254, 106), (254, 109), (254, 110), (254, 111), (254, 112), (254, 113), (254, 116), (254, 117), (254, 118), (254, 119), (254, 120), (254, 121), (254, 122), (254, 123), (254, 124), (254, 125), (254, 126), (254, 127), (254, 128), (254, 129), (254, 130), (254, 131), (254, 132), (254, 133), (254, 134), (254, 156), (254, 158), (254, 159), (254, 160), (254, 161), (254, 162), (254, 163), (254, 164), (254, 165), (254, 166), (254, 170), (255, 81), (255, 83), (255, 84), (255, 85), (255, 86), (255, 87), (255, 88), (255, 89), (255, 90), (255, 91),
(255, 92), (255, 93), (255, 94), (255, 95), (255, 96), (255, 97), (255, 98), (255, 99), (255, 100), (255, 101), (255, 102), (255, 103), (255, 104), (255, 107), (255, 114), (255, 115), (255, 118), (255, 119), (255, 120), (255, 121), (255, 122), (255, 123), (255, 124), (255, 125), (255, 126), (255, 127), (255, 128), (255, 129), (255, 130), (255, 131), (255, 132), (255, 133), (255, 134), (255, 135), (255, 138), (255, 155), (255, 157), (255, 158), (255, 159), (255, 160), (255, 161), (255, 162), (255, 163), (255, 164), (255, 168), (256, 81), (256, 83), (256, 84), (256, 85), (256, 86), (256, 87), (256, 88), (256, 89), (256, 90), (256, 91), (256, 92), (256, 93), (256, 94), (256, 95), (256, 96), (256, 97), (256, 98), (256, 99), (256, 100), (256, 101), (256, 102), (256, 103), (256, 106), (256, 117), (256, 123), (256, 124), (256, 125),
(256, 126), (256, 127), (256, 128), (256, 129), (256, 130), (256, 131), (256, 132), (256, 133), (256, 134), (256, 135), (256, 136), (256, 139), (256, 153), (256, 156), (256, 157), (256, 158), (256, 159), (256, 160), (256, 161), (256, 162), (256, 166), (257, 81), (257, 83), (257, 84), (257, 85), (257, 86), (257, 87), (257, 88), (257, 89), (257, 90), (257, 91), (257, 92), (257, 93), (257, 94), (257, 95), (257, 96), (257, 97), (257, 98), (257, 99), (257, 100), (257, 101), (257, 102), (257, 105), (257, 119), (257, 120), (257, 121), (257, 122), (257, 125), (257, 126), (257, 127), (257, 128), (257, 129), (257, 130), (257, 131), (257, 132), (257, 133), (257, 134), (257, 135), (257, 136), (257, 137), (257, 140), (257, 141), (257, 151), (257, 155), (257, 156), (257, 157), (257, 158), (257, 159), (257, 160), (257, 161), (257, 164), (258, 82),
(258, 84), (258, 85), (258, 86), (258, 87), (258, 88), (258, 89), (258, 90), (258, 91), (258, 92), (258, 93), (258, 94), (258, 95), (258, 96), (258, 97), (258, 98), (258, 99), (258, 100), (258, 101), (258, 104), (258, 123), (258, 126), (258, 127), (258, 128), (258, 129), (258, 130), (258, 131), (258, 132), (258, 133), (258, 134), (258, 135), (258, 136), (258, 137), (258, 138), (258, 139), (258, 142), (258, 143), (258, 144), (258, 145), (258, 146), (258, 147), (258, 148), (258, 149), (258, 153), (258, 154), (258, 155), (258, 156), (258, 157), (258, 158), (258, 159), (258, 160), (258, 162), (259, 82), (259, 84), (259, 85), (259, 86), (259, 87), (259, 88), (259, 89), (259, 90), (259, 91), (259, 92), (259, 93), (259, 94), (259, 95), (259, 96), (259, 97), (259, 98), (259, 99), (259, 100), (259, 103), (259, 125), (259, 127),
(259, 128), (259, 129), (259, 130), (259, 131), (259, 132), (259, 133), (259, 134), (259, 135), (259, 136), (259, 137), (259, 138), (259, 139), (259, 140), (259, 141), (259, 151), (259, 152), (259, 153), (259, 154), (259, 155), (259, 156), (259, 157), (259, 158), (259, 159), (259, 161), (260, 82), (260, 84), (260, 85), (260, 86), (260, 87), (260, 88), (260, 89), (260, 90), (260, 91), (260, 92), (260, 93), (260, 94), (260, 95), (260, 96), (260, 97), (260, 98), (260, 99), (260, 102), (260, 126), (260, 128), (260, 129), (260, 130), (260, 131), (260, 132), (260, 133), (260, 134), (260, 135), (260, 136), (260, 137), (260, 138), (260, 139), (260, 140), (260, 141), (260, 142), (260, 143), (260, 144), (260, 145), (260, 146), (260, 147), (260, 148), (260, 149), (260, 150), (260, 151), (260, 152), (260, 153), (260, 154), (260, 155), (260, 156),
(260, 157), (260, 158), (260, 160), (261, 82), (261, 84), (261, 85), (261, 86), (261, 87), (261, 88), (261, 89), (261, 90), (261, 91), (261, 92), (261, 93), (261, 94), (261, 95), (261, 96), (261, 97), (261, 98), (261, 101), (261, 127), (261, 129), (261, 130), (261, 131), (261, 132), (261, 133), (261, 134), (261, 135), (261, 136), (261, 137), (261, 138), (261, 139), (261, 140), (261, 141), (261, 142), (261, 143), (261, 144), (261, 145), (261, 146), (261, 147), (261, 148), (261, 149), (261, 150), (261, 151), (261, 152), (261, 153), (261, 154), (261, 155), (261, 156), (261, 157), (261, 159), (262, 83), (262, 85), (262, 86), (262, 87), (262, 88), (262, 89), (262, 90), (262, 91), (262, 92), (262, 93), (262, 94), (262, 95), (262, 96), (262, 97), (262, 100), (262, 128), (262, 130), (262, 131), (262, 132), (262, 133), (262, 134),
(262, 135), (262, 136), (262, 137), (262, 138), (262, 139), (262, 140), (262, 141), (262, 142), (262, 143), (262, 144), (262, 145), (262, 146), (262, 147), (262, 148), (262, 149), (262, 150), (262, 151), (262, 152), (262, 153), (262, 154), (262, 155), (262, 156), (262, 157), (262, 159), (263, 83), (263, 85), (263, 86), (263, 87), (263, 88), (263, 89), (263, 90), (263, 91), (263, 92), (263, 93), (263, 94), (263, 95), (263, 96), (263, 99), (263, 129), (263, 131), (263, 132), (263, 133), (263, 134), (263, 135), (263, 136), (263, 137), (263, 138), (263, 139), (263, 140), (263, 141), (263, 142), (263, 143), (263, 144), (263, 145), (263, 146), (263, 147), (263, 148), (263, 149), (263, 150), (263, 151), (263, 152), (263, 153), (263, 154), (263, 155), (263, 156), (263, 158), (264, 83), (264, 85), (264, 86), (264, 87), (264, 88), (264, 89),
(264, 90), (264, 91), (264, 92), (264, 93), (264, 94), (264, 95), (264, 98), (264, 129), (264, 131), (264, 132), (264, 133), (264, 134), (264, 135), (264, 136), (264, 137), (264, 138), (264, 139), (264, 140), (264, 141), (264, 142), (264, 143), (264, 144), (264, 145), (264, 146), (264, 147), (264, 148), (264, 149), (264, 150), (264, 151), (264, 152), (264, 153), (264, 154), (264, 155), (264, 156), (264, 158), (265, 84), (265, 86), (265, 87), (265, 88), (265, 89), (265, 90), (265, 91), (265, 92), (265, 93), (265, 94), (265, 97), (265, 130), (265, 132), (265, 133), (265, 134), (265, 135), (265, 136), (265, 137), (265, 138), (265, 139), (265, 140), (265, 141), (265, 142), (265, 143), (265, 144), (265, 145), (265, 146), (265, 147), (265, 148), (265, 149), (265, 150), (265, 151), (265, 152), (265, 153), (265, 154), (265, 155), (265, 157),
(266, 84), (266, 87), (266, 88), (266, 89), (266, 90), (266, 91), (266, 92), (266, 93), (266, 131), (266, 133), (266, 134), (266, 135), (266, 136), (266, 137), (266, 138), (266, 139), (266, 140), (266, 141), (266, 142), (266, 143), (266, 144), (266, 145), (266, 146), (266, 147), (266, 148), (266, 149), (266, 150), (266, 151), (266, 152), (266, 153), (266, 154), (266, 155), (266, 157), (267, 85), (267, 88), (267, 89), (267, 90), (267, 91), (267, 94), (267, 132), (267, 134), (267, 135), (267, 136), (267, 137), (267, 138), (267, 139), (267, 140), (267, 141), (267, 142), (267, 143), (267, 144), (267, 145), (267, 146), (267, 147), (267, 148), (267, 149), (267, 150), (267, 151), (267, 152), (267, 153), (267, 154), (267, 155), (267, 157), (268, 86), (268, 93), (268, 132), (268, 135), (268, 136), (268, 137), (268, 138), (268, 139), (268, 140),
(268, 141), (268, 142), (268, 143), (268, 144), (268, 145), (268, 146), (268, 147), (268, 148), (268, 149), (268, 150), (268, 151), (268, 152), (268, 153), (268, 154), (268, 155), (268, 157), (269, 88), (269, 91), (269, 134), (269, 137), (269, 138), (269, 139), (269, 140), (269, 141), (269, 142), (269, 143), (269, 144), (269, 145), (269, 146), (269, 147), (269, 148), (269, 149), (269, 150), (269, 151), (269, 152), (269, 153), (269, 154), (269, 155), (269, 157), (270, 135), (270, 139), (270, 140), (270, 141), (270, 142), (270, 143), (270, 144), (270, 145), (270, 146), (270, 147), (270, 148), (270, 149), (270, 150), (270, 151), (270, 152), (270, 153), (270, 154), (270, 155), (270, 157), (271, 137), (271, 140), (271, 141), (271, 142), (271, 143), (271, 144), (271, 145), (271, 146), (271, 147), (271, 148), (271, 149), (271, 150), (271, 151), (271, 152),
(271, 153), (271, 154), (271, 155), (271, 156), (271, 157), (271, 220), (272, 139), (272, 141), (272, 142), (272, 143), (272, 144), (272, 145), (272, 146), (272, 147), (272, 148), (272, 149), (272, 150), (272, 151), (272, 152), (272, 153), (272, 154), (272, 155), (272, 157), (272, 218), (272, 220), (273, 140), (273, 143), (273, 144), (273, 145), (273, 146), (273, 147), (273, 148), (273, 149), (273, 150), (273, 151), (273, 152), (273, 153), (273, 154), (273, 155), (273, 157), (273, 216), (273, 220), (274, 141), (274, 144), (274, 145), (274, 146), (274, 147), (274, 148), (274, 149), (274, 150), (274, 151), (274, 152), (274, 153), (274, 154), (274, 155), (274, 157), (274, 215), (274, 218), (274, 220), (275, 145), (275, 146), (275, 147), (275, 148), (275, 149), (275, 150), (275, 151), (275, 152), (275, 153), (275, 154), (275, 155), (275, 157), (275, 215),
(275, 217), (275, 218), (275, 219), (275, 221), (276, 144), (276, 146), (276, 147), (276, 148), (276, 149), (276, 150), (276, 151), (276, 152), (276, 153), (276, 154), (276, 155), (276, 157), (276, 214), (276, 216), (276, 217), (276, 218), (276, 219), (276, 221), (277, 145), (277, 147), (277, 148), (277, 149), (277, 150), (277, 151), (277, 152), (277, 153), (277, 154), (277, 155), (277, 157), (277, 213), (277, 215), (277, 216), (277, 217), (277, 218), (277, 219), (277, 221), (278, 146), (278, 148), (278, 149), (278, 150), (278, 151), (278, 152), (278, 153), (278, 154), (278, 155), (278, 156), (278, 158), (278, 213), (278, 215), (278, 216), (278, 217), (278, 218), (278, 219), (278, 220), (278, 222), (279, 147), (279, 149), (279, 150), (279, 151), (279, 152), (279, 153), (279, 154), (279, 155), (279, 156), (279, 158), (279, 212), (279, 214), (279, 215),
(279, 216), (279, 217), (279, 218), (279, 219), (279, 220), (279, 222), (280, 148), (280, 150), (280, 151), (280, 152), (280, 153), (280, 154), (280, 155), (280, 156), (280, 158), (280, 212), (280, 214), (280, 215), (280, 216), (280, 217), (280, 218), (280, 219), (280, 220), (280, 222), (281, 149), (281, 151), (281, 152), (281, 153), (281, 154), (281, 155), (281, 156), (281, 157), (281, 159), (281, 211), (281, 213), (281, 214), (281, 215), (281, 216), (281, 217), (281, 218), (281, 219), (281, 220), (281, 221), (281, 223), (282, 149), (282, 151), (282, 152), (282, 153), (282, 154), (282, 155), (282, 156), (282, 157), (282, 159), (282, 210), (282, 212), (282, 213), (282, 214), (282, 215), (282, 216), (282, 217), (282, 218), (282, 219), (282, 220), (282, 221), (282, 223), (283, 150), (283, 152), (283, 153), (283, 154), (283, 155), (283, 156), (283, 157),
(283, 158), (283, 160), (283, 209), (283, 211), (283, 212), (283, 213), (283, 214), (283, 215), (283, 216), (283, 217), (283, 218), (283, 219), (283, 220), (283, 221), (283, 223), (284, 151), (284, 153), (284, 154), (284, 155), (284, 156), (284, 157), (284, 158), (284, 159), (284, 161), (284, 209), (284, 211), (284, 212), (284, 213), (284, 214), (284, 215), (284, 216), (284, 217), (284, 218), (284, 219), (284, 220), (284, 221), (284, 223), (285, 152), (285, 154), (285, 155), (285, 156), (285, 157), (285, 158), (285, 159), (285, 161), (285, 210), (285, 211), (285, 212), (285, 213), (285, 214), (285, 215), (285, 216), (285, 217), (285, 218), (285, 219), (285, 220), (285, 221), (285, 223), (286, 152), (286, 154), (286, 155), (286, 156), (286, 157), (286, 158), (286, 159), (286, 160), (286, 162), (286, 206), (286, 209), (286, 210), (286, 211), (286, 212),
(286, 213), (286, 214), (286, 215), (286, 216), (286, 217), (286, 218), (286, 219), (286, 220), (286, 221), (286, 223), (287, 153), (287, 155), (287, 156), (287, 157), (287, 158), (287, 159), (287, 160), (287, 161), (287, 163), (287, 204), (287, 208), (287, 209), (287, 210), (287, 211), (287, 212), (287, 213), (287, 214), (287, 215), (287, 216), (287, 217), (287, 218), (287, 219), (287, 220), (287, 221), (287, 223), (288, 154), (288, 156), (288, 157), (288, 158), (288, 159), (288, 160), (288, 161), (288, 162), (288, 164), (288, 202), (288, 206), (288, 207), (288, 208), (288, 209), (288, 210), (288, 211), (288, 212), (288, 213), (288, 214), (288, 215), (288, 216), (288, 217), (288, 218), (288, 219), (288, 220), (288, 221), (288, 223), (289, 154), (289, 156), (289, 157), (289, 158), (289, 159), (289, 160), (289, 161), (289, 162), (289, 163), (289, 165),
(289, 200), (289, 204), (289, 205), (289, 206), (289, 207), (289, 208), (289, 209), (289, 210), (289, 211), (289, 212), (289, 213), (289, 214), (289, 215), (289, 216), (289, 217), (289, 218), (289, 219), (289, 220), (289, 221), (289, 223), (290, 155), (290, 157), (290, 158), (290, 159), (290, 160), (290, 161), (290, 162), (290, 163), (290, 164), (290, 167), (290, 198), (290, 202), (290, 203), (290, 204), (290, 205), (290, 206), (290, 207), (290, 208), (290, 209), (290, 210), (290, 211), (290, 212), (290, 213), (290, 214), (290, 215), (290, 216), (290, 217), (290, 218), (290, 219), (290, 220), (290, 222), (291, 155), (291, 157), (291, 158), (291, 159), (291, 160), (291, 161), (291, 162), (291, 163), (291, 164), (291, 165), (291, 168), (291, 169), (291, 196), (291, 200), (291, 201), (291, 202), (291, 203), (291, 204), (291, 205), (291, 206), (291, 207),
(291, 208), (291, 209), (291, 210), (291, 211), (291, 212), (291, 213), (291, 214), (291, 215), (291, 216), (291, 217), (291, 218), (291, 219), (291, 221), (291, 279), (292, 156), (292, 158), (292, 159), (292, 160), (292, 161), (292, 162), (292, 163), (292, 164), (292, 165), (292, 166), (292, 167), (292, 170), (292, 171), (292, 172), (292, 194), (292, 198), (292, 199), (292, 200), (292, 201), (292, 202), (292, 203), (292, 204), (292, 205), (292, 206), (292, 207), (292, 208), (292, 209), (292, 210), (292, 211), (292, 212), (292, 213), (292, 214), (292, 215), (292, 216), (292, 221), (292, 277), (292, 278), (292, 280), (293, 156), (293, 158), (293, 159), (293, 160), (293, 161), (293, 162), (293, 163), (293, 164), (293, 165), (293, 166), (293, 167), (293, 168), (293, 169), (293, 173), (293, 174), (293, 175), (293, 176), (293, 189), (293, 190), (293, 191),
(293, 192), (293, 193), (293, 196), (293, 197), (293, 198), (293, 199), (293, 200), (293, 201), (293, 202), (293, 203), (293, 204), (293, 205), (293, 206), (293, 207), (293, 208), (293, 209), (293, 210), (293, 211), (293, 212), (293, 213), (293, 214), (293, 217), (293, 218), (293, 276), (293, 280), (294, 157), (294, 159), (294, 160), (294, 161), (294, 162), (294, 163), (294, 164), (294, 165), (294, 166), (294, 167), (294, 168), (294, 169), (294, 170), (294, 171), (294, 172), (294, 177), (294, 178), (294, 184), (294, 186), (294, 187), (294, 188), (294, 194), (294, 195), (294, 196), (294, 197), (294, 198), (294, 199), (294, 200), (294, 201), (294, 202), (294, 203), (294, 204), (294, 205), (294, 206), (294, 207), (294, 208), (294, 209), (294, 210), (294, 211), (294, 212), (294, 213), (294, 216), (294, 274), (294, 277), (294, 278), (294, 280), (295, 157),
(295, 159), (295, 160), (295, 161), (295, 162), (295, 163), (295, 164), (295, 165), (295, 166), (295, 167), (295, 168), (295, 169), (295, 170), (295, 171), (295, 172), (295, 173), (295, 174), (295, 175), (295, 176), (295, 179), (295, 180), (295, 181), (295, 182), (295, 183), (295, 189), (295, 190), (295, 191), (295, 192), (295, 193), (295, 194), (295, 195), (295, 196), (295, 197), (295, 198), (295, 199), (295, 200), (295, 201), (295, 202), (295, 203), (295, 204), (295, 205), (295, 206), (295, 207), (295, 208), (295, 209), (295, 210), (295, 211), (295, 214), (295, 272), (295, 276), (295, 277), (295, 278), (295, 280), (296, 157), (296, 158), (296, 159), (296, 160), (296, 161), (296, 162), (296, 163), (296, 164), (296, 165), (296, 166), (296, 167), (296, 168), (296, 169), (296, 170), (296, 171), (296, 172), (296, 173), (296, 174), (296, 175), (296, 176),
(296, 177), (296, 178), (296, 179), (296, 184), (296, 185), (296, 186), (296, 187), (296, 188), (296, 189), (296, 190), (296, 191), (296, 192), (296, 193), (296, 194), (296, 195), (296, 196), (296, 197), (296, 198), (296, 199), (296, 200), (296, 201), (296, 202), (296, 203), (296, 204), (296, 205), (296, 206), (296, 207), (296, 208), (296, 209), (296, 210), (296, 213), (296, 270), (296, 274), (296, 275), (296, 276), (296, 277), (296, 278), (296, 279), (296, 281), (297, 158), (297, 160), (297, 161), (297, 162), (297, 163), (297, 164), (297, 165), (297, 166), (297, 167), (297, 168), (297, 169), (297, 170), (297, 171), (297, 172), (297, 173), (297, 174), (297, 175), (297, 176), (297, 177), (297, 178), (297, 179), (297, 180), (297, 181), (297, 182), (297, 183), (297, 184), (297, 185), (297, 186), (297, 187), (297, 188), (297, 189), (297, 190), (297, 191),
(297, 192), (297, 193), (297, 194), (297, 195), (297, 196), (297, 197), (297, 198), (297, 199), (297, 200), (297, 201), (297, 202), (297, 203), (297, 204), (297, 205), (297, 206), (297, 207), (297, 208), (297, 211), (297, 265), (297, 267), (297, 268), (297, 269), (297, 272), (297, 273), (297, 274), (297, 275), (297, 276), (297, 277), (297, 278), (297, 279), (297, 280), (297, 283), (298, 158), (298, 160), (298, 161), (298, 162), (298, 163), (298, 164), (298, 165), (298, 166), (298, 167), (298, 168), (298, 169), (298, 170), (298, 171), (298, 172), (298, 173), (298, 174), (298, 175), (298, 176), (298, 177), (298, 178), (298, 179), (298, 180), (298, 181), (298, 182), (298, 183), (298, 184), (298, 185), (298, 186), (298, 187), (298, 188), (298, 189), (298, 190), (298, 191), (298, 192), (298, 193), (298, 194), (298, 195), (298, 196), (298, 197), (298, 198),
(298, 199), (298, 200), (298, 201), (298, 202), (298, 203), (298, 210), (298, 264), (298, 270), (298, 271), (298, 272), (298, 273), (298, 274), (298, 275), (298, 276), (298, 277), (298, 278), (298, 279), (298, 280), (298, 281), (299, 158), (299, 160), (299, 161), (299, 162), (299, 163), (299, 164), (299, 165), (299, 166), (299, 167), (299, 168), (299, 169), (299, 170), (299, 171), (299, 172), (299, 173), (299, 174), (299, 175), (299, 176), (299, 177), (299, 178), (299, 179), (299, 180), (299, 181), (299, 182), (299, 183), (299, 184), (299, 185), (299, 186), (299, 187), (299, 188), (299, 189), (299, 190), (299, 191), (299, 192), (299, 193), (299, 194), (299, 195), (299, 196), (299, 197), (299, 198), (299, 199), (299, 204), (299, 205), (299, 206), (299, 208), (299, 263), (299, 265), (299, 266), (299, 267), (299, 268), (299, 269), (299, 270), (299, 271),
(299, 272), (299, 273), (299, 274), (299, 275), (299, 276), (299, 277), (299, 278), (299, 279), (299, 280), (299, 282), (300, 158), (300, 159), (300, 160), (300, 161), (300, 162), (300, 163), (300, 164), (300, 165), (300, 166), (300, 167), (300, 168), (300, 169), (300, 170), (300, 171), (300, 172), (300, 173), (300, 174), (300, 175), (300, 176), (300, 177), (300, 178), (300, 179), (300, 180), (300, 181), (300, 182), (300, 183), (300, 184), (300, 185), (300, 186), (300, 187), (300, 188), (300, 189), (300, 190), (300, 191), (300, 192), (300, 193), (300, 194), (300, 195), (300, 196), (300, 197), (300, 200), (300, 201), (300, 202), (300, 203), (300, 265), (300, 266), (300, 267), (300, 268), (300, 269), (300, 270), (300, 271), (300, 272), (300, 273), (300, 274), (300, 275), (300, 276), (300, 277), (300, 278), (300, 279), (301, 159), (301, 161), (301, 162),
(301, 163), (301, 164), (301, 165), (301, 166), (301, 167), (301, 168), (301, 169), (301, 170), (301, 171), (301, 172), (301, 173), (301, 174), (301, 175), (301, 176), (301, 177), (301, 178), (301, 179), (301, 180), (301, 181), (301, 182), (301, 183), (301, 184), (301, 185), (301, 186), (301, 187), (301, 188), (301, 189), (301, 190), (301, 191), (301, 192), (301, 193), (301, 194), (301, 198), (301, 199), (301, 262), (301, 264), (301, 265), (301, 266), (301, 267), (301, 268), (301, 269), (301, 270), (301, 271), (301, 272), (301, 273), (301, 274), (301, 275), (301, 276), (301, 277), (301, 278), (301, 279), (301, 281), (302, 159), (302, 161), (302, 162), (302, 163), (302, 164), (302, 165), (302, 166), (302, 167), (302, 168), (302, 169), (302, 170), (302, 171), (302, 172), (302, 173), (302, 174), (302, 175), (302, 176), (302, 177), (302, 178), (302, 196),
(302, 261), (302, 263), (302, 264), (302, 265), (302, 266), (302, 267), (302, 268), (302, 269), (302, 270), (302, 271), (302, 272), (302, 273), (302, 274), (302, 275), (302, 276), (302, 277), (302, 278), (302, 280), (303, 159), (303, 161), (303, 162), (303, 163), (303, 164), (303, 165), (303, 166), (303, 167), (303, 168), (303, 169), (303, 170), (303, 171), (303, 172), (303, 173), (303, 174), (303, 175), (303, 176), (303, 179), (303, 180), (303, 181), (303, 182), (303, 183), (303, 184), (303, 185), (303, 186), (303, 187), (303, 188), (303, 189), (303, 190), (303, 191), (303, 192), (303, 194), (303, 260), (303, 262), (303, 263), (303, 264), (303, 265), (303, 266), (303, 267), (303, 268), (303, 269), (303, 270), (303, 271), (303, 272), (303, 273), (303, 274), (303, 275), (303, 276), (303, 277), (303, 279), (304, 159), (304, 161), (304, 162), (304, 163),
(304, 164), (304, 165), (304, 166), (304, 167), (304, 168), (304, 169), (304, 170), (304, 171), (304, 172), (304, 173), (304, 174), (304, 177), (304, 178), (304, 260), (304, 262), (304, 263), (304, 264), (304, 265), (304, 266), (304, 267), (304, 268), (304, 269), (304, 270), (304, 271), (304, 272), (304, 273), (304, 274), (304, 275), (304, 276), (304, 278), (305, 159), (305, 161), (305, 162), (305, 163), (305, 164), (305, 165), (305, 166), (305, 167), (305, 168), (305, 169), (305, 170), (305, 171), (305, 172), (305, 173), (305, 174), (305, 259), (305, 261), (305, 262), (305, 263), (305, 264), (305, 265), (305, 266), (305, 267), (305, 268), (305, 269), (305, 270), (305, 271), (305, 272), (305, 273), (305, 274), (305, 275), (305, 277), (306, 159), (306, 161), (306, 162), (306, 163), (306, 164), (306, 165), (306, 166), (306, 167), (306, 168), (306, 169),
(306, 170), (306, 171), (306, 172), (306, 174), (306, 258), (306, 260), (306, 261), (306, 262), (306, 263), (306, 264), (306, 265), (306, 266), (306, 267), (306, 268), (306, 269), (306, 270), (306, 271), (306, 272), (306, 273), (306, 274), (306, 276), (307, 159), (307, 161), (307, 162), (307, 163), (307, 164), (307, 165), (307, 166), (307, 167), (307, 168), (307, 169), (307, 170), (307, 171), (307, 174), (307, 256), (307, 259), (307, 260), (307, 261), (307, 262), (307, 263), (307, 264), (307, 265), (307, 266), (307, 267), (307, 268), (307, 269), (307, 270), (307, 271), (307, 272), (307, 275), (308, 159), (308, 161), (308, 162), (308, 163), (308, 164), (308, 165), (308, 166), (308, 167), (308, 168), (308, 169), (308, 170), (308, 172), (308, 255), (308, 258), (308, 259), (308, 260), (308, 261), (308, 262), (308, 263), (308, 264), (308, 265), (308, 266),
(308, 267), (308, 268), (308, 269), (308, 270), (308, 271), (308, 274), (309, 158), (309, 160), (309, 161), (309, 162), (309, 163), (309, 164), (309, 165), (309, 166), (309, 167), (309, 168), (309, 169), (309, 171), (309, 254), (309, 256), (309, 257), (309, 258), (309, 259), (309, 260), (309, 261), (309, 262), (309, 263), (309, 264), (309, 265), (309, 266), (309, 267), (309, 268), (309, 269), (309, 270), (309, 273), (310, 158), (310, 160), (310, 161), (310, 162), (310, 163), (310, 164), (310, 165), (310, 166), (310, 167), (310, 168), (310, 170), (310, 253), (310, 255), (310, 256), (310, 257), (310, 258), (310, 259), (310, 260), (310, 261), (310, 262), (310, 263), (310, 264), (310, 265), (310, 266), (310, 267), (310, 268), (310, 271), (311, 158), (311, 160), (311, 161), (311, 162), (311, 163), (311, 164), (311, 165), (311, 166), (311, 167), (311, 169),
(311, 255), (311, 256), (311, 257), (311, 258), (311, 259), (311, 260), (311, 261), (311, 262), (311, 263), (311, 264), (311, 265), (311, 266), (311, 267), (311, 270), (312, 157), (312, 159), (312, 160), (312, 161), (312, 162), (312, 163), (312, 164), (312, 165), (312, 166), (312, 168), (312, 252), (312, 254), (312, 255), (312, 256), (312, 257), (312, 258), (312, 259), (312, 260), (312, 261), (312, 262), (312, 263), (312, 264), (312, 265), (312, 268), (313, 157), (313, 159), (313, 160), (313, 161), (313, 162), (313, 163), (313, 164), (313, 165), (313, 167), (313, 251), (313, 253), (313, 254), (313, 255), (313, 256), (313, 257), (313, 258), (313, 259), (313, 260), (313, 261), (313, 262), (313, 263), (313, 267), (314, 157), (314, 159), (314, 160), (314, 161), (314, 162), (314, 163), (314, 164), (314, 165), (314, 167), (314, 250), (314, 252), (314, 253),
(314, 254), (314, 255), (314, 256), (314, 257), (314, 258), (314, 259), (314, 260), (314, 265), (315, 157), (315, 159), (315, 160), (315, 161), (315, 162), (315, 163), (315, 164), (315, 165), (315, 167), (315, 249), (315, 251), (315, 252), (315, 253), (315, 254), (315, 255), (315, 256), (315, 257), (315, 261), (315, 262), (315, 263), (316, 157), (316, 159), (316, 160), (316, 161), (316, 162), (316, 163), (316, 164), (316, 166), (316, 248), (316, 250), (316, 251), (316, 252), (316, 253), (316, 254), (316, 255), (316, 258), (316, 259), (316, 260), (317, 157), (317, 159), (317, 160), (317, 161), (317, 162), (317, 163), (317, 164), (317, 166), (317, 247), (317, 249), (317, 250), (317, 251), (317, 252), (317, 253), (317, 256), (317, 257), (318, 156), (318, 158), (318, 159), (318, 160), (318, 161), (318, 162), (318, 163), (318, 164), (318, 166), (318, 246),
(318, 248), (318, 249), (318, 250), (318, 251), (318, 252), (318, 254), (319, 156), (319, 158), (319, 159), (319, 160), (319, 161), (319, 162), (319, 163), (319, 164), (319, 166), (319, 245), (319, 247), (319, 248), (319, 249), (319, 250), (319, 251), (319, 253), (320, 156), (320, 158), (320, 159), (320, 160), (320, 161), (320, 162), (320, 163), (320, 164), (320, 166), (320, 244), (320, 246), (320, 247), (320, 248), (320, 249), (320, 250), (320, 252), (321, 155), (321, 157), (321, 158), (321, 159), (321, 160), (321, 161), (321, 162), (321, 163), (321, 164), (321, 166), (321, 243), (321, 245), (321, 246), (321, 247), (321, 251), (322, 155), (322, 157), (322, 158), (322, 159), (322, 160), (322, 161), (322, 162), (322, 163), (322, 164), (322, 166), (322, 242), (322, 244), (322, 245), (322, 248), (322, 249), (322, 251), (323, 154), (323, 156), (323, 157),
(323, 158), (323, 159), (323, 160), (323, 161), (323, 162), (323, 163), (323, 164), (323, 166), (323, 241), (323, 243), (323, 247), (324, 154), (324, 156), (324, 157), (324, 158), (324, 159), (324, 160), (324, 161), (324, 162), (324, 163), (324, 164), (324, 165), (324, 167), (324, 241), (324, 245), (325, 154), (325, 156), (325, 157), (325, 158), (325, 159), (325, 160), (325, 161), (325, 162), (325, 163), (325, 164), (325, 165), (325, 167), (325, 240), (325, 243), (326, 153), (326, 155), (326, 156), (326, 157), (326, 158), (326, 159), (326, 160), (326, 161), (326, 162), (326, 163), (326, 164), (326, 165), (326, 166), (326, 168), (326, 240), (326, 242), (327, 153), (327, 155), (327, 156), (327, 157), (327, 158), (327, 159), (327, 160), (327, 161), (327, 162), (327, 163), (327, 164), (327, 165), (327, 166), (327, 168), (327, 239), (327, 241), (328, 152),
(328, 154), (328, 155), (328, 156), (328, 157), (328, 158), (328, 159), (328, 160), (328, 161), (328, 162), (328, 163), (328, 164), (328, 165), (328, 166), (328, 167), (328, 169), (328, 239), (328, 240), (329, 152), (329, 154), (329, 155), (329, 156), (329, 157), (329, 158), (329, 159), (329, 160), (329, 161), (329, 162), (329, 163), (329, 164), (329, 165), (329, 166), (329, 167), (329, 168), (329, 170), (329, 239), (330, 151), (330, 153), (330, 154), (330, 155), (330, 156), (330, 157), (330, 158), (330, 159), (330, 160), (330, 161), (330, 162), (330, 163), (330, 164), (330, 165), (330, 166), (330, 167), (330, 168), (330, 170), (331, 151), (331, 153), (331, 154), (331, 155), (331, 156), (331, 157), (331, 158), (331, 159), (331, 160), (331, 161), (331, 162), (331, 163), (331, 164), (331, 165), (331, 166), (331, 167), (331, 168), (331, 169), (331, 171),
(332, 152), (332, 154), (332, 155), (332, 156), (332, 157), (332, 158), (332, 159), (332, 160), (332, 161), (332, 162), (332, 163), (332, 164), (332, 165), (332, 166), (332, 167), (332, 168), (332, 169), (332, 170), (332, 172), (333, 153), (333, 155), (333, 156), (333, 157), (333, 158), (333, 159), (333, 160), (333, 161), (333, 162), (333, 163), (333, 164), (333, 165), (333, 166), (333, 167), (333, 168), (333, 169), (333, 170), (333, 171), (333, 173), (334, 154), (334, 156), (334, 157), (334, 158), (334, 159), (334, 160), (334, 161), (334, 162), (334, 163), (334, 164), (334, 165), (334, 166), (334, 167), (334, 168), (334, 169), (334, 170), (334, 171), (334, 172), (334, 174), (335, 155), (335, 157), (335, 158), (335, 159), (335, 160), (335, 161), (335, 162), (335, 163), (335, 164), (335, 165), (335, 166), (335, 167), (335, 168), (335, 169), (335, 170),
(335, 171), (335, 172), (335, 173), (335, 175), (336, 156), (336, 159), (336, 160), (336, 161), (336, 162), (336, 163), (336, 164), (336, 165), (336, 166), (336, 167), (336, 168), (336, 169), (336, 170), (336, 171), (336, 172), (336, 173), (336, 174), (336, 177), (337, 157), (337, 161), (337, 162), (337, 163), (337, 164), (337, 165), (337, 166), (337, 167), (337, 168), (337, 169), (337, 170), (337, 171), (337, 172), (337, 173), (337, 174), (337, 175), (337, 178), (338, 159), (338, 160), (338, 163), (338, 164), (338, 165), (338, 166), (338, 167), (338, 168), (338, 169), (338, 170), (338, 171), (338, 172), (338, 173), (338, 174), (338, 175), (338, 176), (338, 177), (338, 180), (339, 161), (339, 162), (339, 165), (339, 166), (339, 167), (339, 168), (339, 169), (339, 170), (339, 171), (339, 172), (339, 173), (339, 174), (339, 175), (339, 176), (339, 177),
(339, 178), (339, 181), (339, 182), (340, 164), (340, 168), (340, 169), (340, 170), (340, 171), (340, 172), (340, 173), (340, 174), (340, 175), (340, 176), (340, 177), (340, 178), (340, 179), (340, 180), (340, 184), (340, 185), (340, 186), (340, 187), (340, 189), (341, 166), (341, 170), (341, 171), (341, 172), (341, 173), (341, 174), (341, 175), (341, 176), (341, 177), (341, 178), (341, 179), (341, 180), (341, 181), (341, 182), (341, 183), (341, 189), (342, 168), (342, 172), (342, 173), (342, 174), (342, 175), (342, 176), (342, 177), (342, 178), (342, 179), (342, 180), (342, 181), (342, 182), (342, 183), (342, 184), (342, 185), (342, 186), (342, 187), (342, 188), (342, 190), (343, 170), (343, 174), (343, 175), (343, 176), (343, 177), (343, 178), (343, 179), (343, 180), (343, 181), (343, 182), (343, 183), (343, 184), (343, 185), (343, 186), (343, 187),
(343, 188), (343, 190), (344, 172), (344, 176), (344, 177), (344, 178), (344, 179), (344, 180), (344, 181), (344, 182), (344, 183), (344, 184), (344, 185), (344, 186), (344, 187), (344, 188), (344, 189), (344, 191), (345, 174), (345, 178), (345, 179), (345, 180), (345, 181), (345, 182), (345, 183), (345, 184), (345, 185), (345, 186), (345, 187), (345, 188), (345, 189), (345, 190), (345, 192), (346, 176), (346, 180), (346, 181), (346, 182), (346, 183), (346, 184), (346, 185), (346, 186), (346, 187), (346, 188), (346, 189), (346, 190), (346, 191), (346, 193), (347, 178), (347, 181), (347, 182), (347, 183), (347, 184), (347, 185), (347, 186), (347, 187), (347, 188), (347, 189), (347, 190), (347, 191), (347, 192), (347, 194), (348, 180), (348, 183), (348, 184), (348, 185), (348, 186), (348, 187), (348, 188), (348, 189), (348, 190), (348, 191), (348, 192),
(348, 194), (349, 181), (349, 184), (349, 185), (349, 186), (349, 187), (349, 188), (349, 189), (349, 190), (349, 191), (349, 192), (349, 194), (350, 183), (350, 186), (350, 187), (350, 188), (350, 189), (350, 190), (350, 193), (351, 184), (351, 187), (351, 188), (351, 189), (351, 192), (352, 186), (352, 191), (353, 187), (353, 189), )
coordinates_FF00A6 = ((189, 124),
(190, 115), (190, 117), (190, 118), (190, 119), (190, 120), (190, 121), (190, 122), (190, 124), (191, 114), (191, 124), (192, 113), (192, 115), (192, 116), (192, 117), (192, 118), (192, 119), (192, 120), (192, 121), (192, 122), (192, 124), (193, 112), (193, 114), (193, 115), (193, 116), (193, 117), (193, 118), (193, 119), (193, 120), (193, 121), (193, 122), (193, 124), (194, 111), (194, 113), (194, 114), (194, 115), (194, 116), (194, 117), (194, 118), (194, 119), (194, 120), (194, 121), (194, 122), (194, 123), (194, 125), (195, 110), (195, 112), (195, 113), (195, 114), (195, 115), (195, 116), (195, 117), (195, 118), (195, 119), (195, 120), (195, 121), (195, 122), (195, 123), (195, 125), (196, 109), (196, 111), (196, 112), (196, 113), (196, 114), (196, 115), (196, 116), (196, 117), (196, 118), (196, 119), (196, 120), (196, 121), (196, 122), (196, 123),
(196, 125), (197, 108), (197, 110), (197, 111), (197, 112), (197, 113), (197, 114), (197, 115), (197, 116), (197, 117), (197, 118), (197, 119), (197, 120), (197, 121), (197, 125), (198, 108), (198, 110), (198, 111), (198, 112), (198, 113), (198, 114), (198, 115), (198, 116), (198, 117), (198, 118), (198, 119), (198, 120), (198, 121), (198, 122), (198, 123), (199, 109), (199, 111), (199, 112), (199, 113), (199, 114), (199, 115), (199, 116), (199, 117), (199, 118), (199, 119), (199, 121), (200, 109), (200, 111), (200, 112), (200, 113), (200, 114), (200, 115), (200, 116), (200, 117), (200, 118), (200, 119), (200, 121), (201, 108), (201, 110), (201, 111), (201, 112), (201, 113), (201, 114), (201, 115), (201, 116), (201, 117), (201, 118), (201, 119), (201, 120), (201, 121), (201, 122), (201, 123), (201, 125), (202, 111), (202, 112), (202, 113), (202, 114),
(202, 115), (202, 116), (202, 117), (202, 118), (202, 119), (202, 120), (202, 121), (202, 122), (202, 125), (203, 109), (203, 111), (203, 112), (203, 113), (203, 114), (203, 115), (203, 116), (203, 117), (203, 118), (203, 119), (203, 120), (203, 121), (203, 122), (203, 123), (203, 125), (204, 110), (204, 112), (204, 113), (204, 114), (204, 115), (204, 116), (204, 117), (204, 118), (204, 119), (204, 120), (204, 121), (204, 122), (204, 123), (204, 125), (205, 111), (205, 113), (205, 114), (205, 115), (205, 116), (205, 117), (205, 118), (205, 119), (205, 120), (205, 121), (205, 122), (205, 123), (205, 125), (206, 112), (206, 114), (206, 115), (206, 116), (206, 117), (206, 118), (206, 119), (206, 120), (206, 121), (206, 122), (206, 124), (207, 113), (207, 116), (207, 117), (207, 118), (207, 119), (207, 120), (207, 121), (207, 122), (207, 124), (208, 114),
(208, 124), (209, 115), (209, 116), (209, 117), (209, 118), (209, 119), (209, 120), (209, 121), (209, 122), (209, 124), )
coordinates_7F0053 = ((164, 105),
(164, 107), (164, 108), (164, 109), (164, 110), (164, 111), (165, 105), (165, 114), (166, 105), (166, 107), (166, 108), (166, 109), (166, 110), (166, 111), (166, 112), (166, 116), (167, 106), (167, 108), (167, 109), (167, 110), (167, 111), (167, 112), (167, 113), (167, 114), (168, 106), (168, 108), (168, 109), (168, 110), (168, 111), (168, 112), (168, 113), (168, 114), (168, 115), (168, 117), (169, 107), (169, 109), (169, 110), (169, 111), (169, 112), (169, 113), (169, 114), (169, 115), (169, 117), (170, 107), (170, 109), (170, 110), (170, 111), (170, 112), (170, 113), (170, 114), (170, 115), (170, 116), (170, 118), (171, 107), (171, 109), (171, 110), (171, 111), (171, 112), (171, 113), (171, 114), (171, 115), (171, 116), (171, 118), (172, 108), (172, 110), (172, 111), (172, 112), (172, 113), (172, 114), (172, 115), (172, 116), (172, 118), (173, 108),
(173, 110), (173, 111), (173, 112), (173, 113), (173, 114), (173, 115), (173, 116), (173, 118), (174, 108), (174, 110), (174, 111), (174, 112), (174, 113), (174, 114), (174, 115), (174, 116), (174, 118), (175, 108), (175, 110), (175, 111), (175, 112), (175, 113), (175, 114), (175, 115), (175, 117), (176, 108), (176, 110), (176, 111), (176, 112), (176, 113), (176, 114), (176, 115), (176, 117), (177, 108), (177, 110), (177, 111), (177, 112), (177, 113), (177, 114), (177, 115), (177, 117), (178, 108), (178, 110), (178, 111), (178, 112), (178, 113), (178, 114), (178, 115), (178, 117), (179, 108), (179, 110), (179, 111), (179, 112), (179, 113), (179, 114), (179, 115), (179, 117), (180, 107), (180, 109), (180, 110), (180, 111), (180, 112), (180, 113), (180, 114), (180, 115), (180, 117), (181, 107), (181, 109), (181, 110), (181, 111), (181, 112), (181, 113),
(181, 114), (181, 116), (182, 106), (182, 108), (182, 109), (182, 110), (182, 111), (182, 112), (182, 113), (182, 114), (182, 116), (183, 106), (183, 108), (183, 109), (183, 110), (183, 111), (183, 112), (183, 113), (183, 114), (183, 116), (184, 105), (184, 107), (184, 108), (184, 109), (184, 110), (184, 111), (184, 112), (184, 113), (184, 114), (184, 116), (185, 105), (185, 107), (185, 108), (185, 109), (185, 110), (185, 111), (185, 112), (185, 113), (185, 114), (185, 116), (186, 104), (186, 106), (186, 107), (186, 108), (186, 109), (186, 110), (186, 111), (186, 112), (186, 113), (186, 114), (186, 116), (187, 104), (187, 106), (187, 107), (187, 108), (187, 109), (187, 110), (187, 111), (187, 112), (187, 113), (187, 114), (187, 116), (188, 103), (188, 105), (188, 106), (188, 107), (188, 108), (188, 109), (188, 110), (188, 111), (188, 112), (188, 115),
(189, 103), (189, 105), (189, 106), (189, 107), (189, 108), (189, 109), (189, 110), (189, 111), (189, 114), (190, 102), (190, 104), (190, 105), (190, 106), (190, 107), (190, 108), (190, 109), (190, 110), (190, 113), (191, 102), (191, 104), (191, 105), (191, 106), (191, 107), (191, 108), (191, 109), (191, 111), (192, 102), (192, 104), (192, 105), (192, 106), (192, 107), (192, 108), (192, 110), (193, 102), (193, 104), (193, 105), (193, 106), (193, 107), (193, 109), (194, 102), (194, 104), (194, 105), (194, 106), (195, 105), (195, 106), (195, 108), (196, 103), (196, 107), (197, 104), (197, 106), (201, 106), (202, 104), (202, 106), (203, 103), (203, 107), (204, 102), (204, 104), (204, 105), (204, 106), (204, 108), (205, 102), (205, 104), (205, 105), (205, 106), (205, 109), (206, 102), (206, 104), (206, 105), (206, 106), (206, 107), (207, 102), (207, 104),
(207, 105), (207, 106), (207, 107), (207, 108), (208, 102), (208, 104), (208, 105), (208, 106), (208, 107), (208, 108), (208, 109), (209, 103), (209, 104), (209, 105), (209, 106), (209, 107), (209, 108), (209, 109), (209, 110), (209, 113), (210, 103), (210, 105), (210, 106), (210, 107), (210, 108), (210, 109), (210, 110), (210, 111), (210, 114), (211, 103), (211, 105), (211, 106), (211, 107), (211, 108), (211, 109), (211, 110), (211, 111), (211, 112), (211, 113), (211, 115), (211, 116), (212, 104), (212, 106), (212, 107), (212, 108), (212, 109), (212, 110), (212, 111), (212, 112), (212, 113), (212, 114), (212, 116), (213, 104), (213, 106), (213, 107), (213, 108), (213, 109), (213, 110), (213, 111), (213, 112), (213, 113), (213, 114), (213, 116), (214, 105), (214, 107), (214, 108), (214, 109), (214, 110), (214, 111), (214, 112), (214, 113), (214, 114),
(214, 116), (215, 105), (215, 107), (215, 108), (215, 109), (215, 110), (215, 111), (215, 112), (215, 113), (215, 114), (215, 116), (216, 106), (216, 108), (216, 109), (216, 110), (216, 111), (216, 112), (216, 113), (216, 114), (216, 116), (217, 106), (217, 108), (217, 109), (217, 110), (217, 111), (217, 112), (217, 113), (217, 114), (217, 116), (218, 107), (218, 109), (218, 110), (218, 111), (218, 112), (218, 113), (218, 114), (218, 116), (219, 107), (219, 109), (219, 110), (219, 111), (219, 112), (219, 113), (219, 114), (219, 115), (219, 117), (220, 108), (220, 110), (220, 111), (220, 112), (220, 113), (220, 114), (220, 115), (220, 117), (221, 108), (221, 110), (221, 111), (221, 112), (221, 113), (221, 114), (221, 115), (221, 117), (222, 108), (222, 110), (222, 111), (222, 112), (222, 113), (222, 114), (222, 115), (222, 117), (223, 108), (223, 110),
(223, 111), (223, 112), (223, 113), (223, 114), (223, 115), (223, 117), (224, 108), (224, 110), (224, 111), (224, 112), (224, 113), (224, 114), (224, 115), (224, 117), (225, 108), (225, 110), (225, 111), (225, 112), (225, 113), (225, 114), (225, 115), (225, 116), (225, 118), (226, 108), (226, 110), (226, 111), (226, 112), (226, 113), (226, 114), (226, 115), (226, 116), (226, 118), (227, 108), (227, 110), (227, 111), (227, 112), (227, 113), (227, 114), (227, 115), (227, 116), (227, 118), (228, 107), (228, 109), (228, 110), (228, 111), (228, 112), (228, 113), (228, 114), (228, 115), (228, 116), (228, 118), (229, 107), (229, 109), (229, 110), (229, 111), (229, 112), (229, 113), (229, 114), (229, 115), (229, 116), (229, 118), (230, 106), (230, 107), (230, 108), (230, 109), (230, 110), (230, 111), (230, 112), (230, 113), (230, 114), (230, 115), (230, 117),
(231, 106), (231, 108), (231, 109), (231, 110), (231, 111), (231, 112), (231, 113), (231, 114), (231, 115), (231, 117), (232, 106), (232, 108), (232, 109), (232, 110), (232, 111), (232, 112), (232, 113), (232, 114), (232, 116), (233, 105), (233, 107), (233, 108), (233, 109), (233, 110), (233, 111), (233, 115), (234, 105), (234, 112), (234, 114), (235, 105), (235, 107), (235, 108), (235, 109), (235, 110), (235, 111), )
coordinates_7F0013 = ((188, 132),
(189, 126), (189, 128), (189, 129), (189, 130), (189, 131), (189, 133), (190, 126), (190, 133), (191, 126), (191, 128), (191, 129), (191, 130), (191, 131), (191, 133), (192, 126), (192, 127), (192, 128), (192, 129), (192, 130), (192, 131), (192, 133), (193, 127), (193, 129), (193, 130), (193, 131), (193, 133), (194, 127), (194, 129), (194, 130), (194, 131), (194, 132), (194, 133), (195, 127), (195, 129), (195, 130), (195, 134), (196, 127), (196, 131), (196, 132), (196, 133), (197, 127), (197, 128), (197, 130), (202, 127), (202, 130), (203, 127), (203, 131), (203, 132), (203, 133), (204, 127), (204, 129), (204, 130), (204, 134), (205, 127), (205, 129), (205, 130), (205, 131), (205, 133), (206, 127), (206, 129), (206, 130), (206, 131), (206, 133), (207, 126), (207, 128), (207, 129), (207, 130), (207, 131), (207, 133), (208, 126), (208, 128), (208, 129),
(208, 130), (208, 131), (208, 133), (209, 126), (209, 133), (210, 128), (210, 129), (210, 130), (210, 131), (210, 133), )
coordinates_00007F = ((175, 138),
(178, 140), (179, 141), (180, 142), (183, 144), (184, 145), (186, 146), (187, 147), (188, 148), (189, 151), (190, 149), (190, 153), (190, 154), (191, 150), (191, 152), (191, 155), (191, 156), (191, 157), (192, 151), (192, 153), (192, 154), (192, 160), (193, 151), (193, 153), (193, 154), (193, 157), (193, 158), (194, 152), (194, 156), (195, 153), (195, 154), (204, 153), (204, 154), (205, 152), (205, 156), (206, 151), (206, 153), (206, 154), (206, 158), (207, 151), (207, 153), (207, 154), (207, 158), (207, 160), (208, 150), (208, 155), (208, 156), (209, 149), (209, 153), (209, 154), (210, 151), (211, 148), (211, 149), (212, 147), (213, 146), (215, 145), (216, 144), (217, 143), (220, 141), (221, 140), (222, 139), (224, 138), )
coordinates_27007F = ((180, 49),
(180, 51), (180, 52), (180, 53), (180, 54), (180, 55), (180, 56), (180, 57), (180, 58), (180, 59), (180, 60), (180, 63), (181, 49), (181, 61), (181, 62), (181, 64), (181, 88), (182, 49), (182, 51), (182, 52), (182, 53), (182, 54), (182, 55), (182, 56), (182, 57), (182, 58), (182, 59), (182, 60), (182, 65), (182, 86), (183, 49), (183, 51), (183, 52), (183, 53), (183, 54), (183, 55), (183, 56), (183, 57), (183, 58), (183, 59), (183, 60), (183, 61), (183, 62), (183, 63), (183, 65), (183, 84), (183, 85), (183, 89), (184, 49), (184, 51), (184, 52), (184, 53), (184, 54), (184, 55), (184, 56), (184, 57), (184, 58), (184, 59), (184, 60), (184, 61), (184, 62), (184, 63), (184, 64), (184, 83), (184, 86), (184, 87), (184, 88), (185, 49), (185, 51), (185, 52), (185, 53), (185, 54), (185, 55),
(185, 56), (185, 57), (185, 58), (185, 59), (185, 60), (185, 61), (185, 62), (185, 63), (185, 64), (185, 65), (185, 68), (185, 69), (185, 70), (185, 71), (185, 72), (185, 73), (185, 74), (185, 75), (185, 76), (185, 77), (185, 78), (185, 79), (185, 80), (185, 81), (185, 84), (185, 85), (185, 86), (185, 87), (185, 88), (185, 89), (185, 92), (186, 49), (186, 51), (186, 52), (186, 53), (186, 54), (186, 55), (186, 56), (186, 57), (186, 58), (186, 59), (186, 60), (186, 61), (186, 62), (186, 63), (186, 64), (186, 65), (186, 66), (186, 67), (186, 83), (186, 84), (186, 85), (186, 86), (186, 87), (186, 88), (186, 89), (186, 90), (186, 93), (187, 49), (187, 51), (187, 52), (187, 53), (187, 54), (187, 55), (187, 56), (187, 57), (187, 58), (187, 59), (187, 60), (187, 61), (187, 62), (187, 63),
(187, 64), (187, 65), (187, 66), (187, 67), (187, 68), (187, 69), (187, 70), (187, 71), (187, 72), (187, 73), (187, 74), (187, 75), (187, 76), (187, 77), (187, 78), (187, 79), (187, 80), (187, 81), (187, 82), (187, 83), (187, 84), (187, 85), (187, 86), (187, 87), (187, 88), (187, 89), (187, 90), (187, 91), (187, 92), (187, 94), (188, 49), (188, 51), (188, 52), (188, 53), (188, 54), (188, 55), (188, 56), (188, 57), (188, 58), (188, 59), (188, 60), (188, 61), (188, 62), (188, 63), (188, 64), (188, 65), (188, 66), (188, 67), (188, 68), (188, 69), (188, 70), (188, 71), (188, 72), (188, 73), (188, 74), (188, 75), (188, 76), (188, 77), (188, 78), (188, 79), (188, 80), (188, 81), (188, 82), (188, 83), (188, 84), (188, 85), (188, 86), (188, 87), (188, 88), (188, 89), (188, 90), (188, 91),
(188, 92), (188, 93), (188, 96), (189, 50), (189, 52), (189, 53), (189, 54), (189, 55), (189, 56), (189, 57), (189, 58), (189, 59), (189, 60), (189, 61), (189, 62), (189, 63), (189, 64), (189, 65), (189, 66), (189, 67), (189, 68), (189, 69), (189, 70), (189, 71), (189, 72), (189, 73), (189, 74), (189, 75), (189, 76), (189, 77), (189, 78), (189, 79), (189, 80), (189, 81), (189, 82), (189, 83), (189, 84), (189, 85), (189, 86), (189, 87), (189, 88), (189, 89), (189, 90), (189, 91), (189, 92), (189, 93), (189, 94), (189, 97), (190, 50), (190, 52), (190, 53), (190, 54), (190, 55), (190, 56), (190, 57), (190, 58), (190, 59), (190, 60), (190, 61), (190, 62), (190, 63), (190, 64), (190, 65), (190, 66), (190, 67), (190, 68), (190, 69), (190, 70), (190, 71), (190, 72), (190, 73), (190, 74),
(190, 75), (190, 76), (190, 77), (190, 78), (190, 79), (190, 80), (190, 81), (190, 82), (190, 83), (190, 84), (190, 85), (190, 86), (190, 87), (190, 88), (190, 89), (190, 90), (190, 91), (190, 92), (190, 93), (190, 94), (190, 95), (190, 97), (191, 50), (191, 52), (191, 53), (191, 54), (191, 55), (191, 56), (191, 57), (191, 58), (191, 59), (191, 60), (191, 61), (191, 62), (191, 63), (191, 64), (191, 65), (191, 66), (191, 67), (191, 68), (191, 69), (191, 70), (191, 71), (191, 72), (191, 73), (191, 74), (191, 75), (191, 76), (191, 77), (191, 78), (191, 79), (191, 80), (191, 81), (191, 82), (191, 83), (191, 84), (191, 85), (191, 86), (191, 87), (191, 88), (191, 89), (191, 90), (191, 91), (191, 92), (191, 93), (191, 94), (191, 95), (191, 97), (192, 51), (192, 53), (192, 54), (192, 55),
(192, 56), (192, 57), (192, 58), (192, 59), (192, 60), (192, 61), (192, 62), (192, 63), (192, 64), (192, 65), (192, 66), (192, 67), (192, 68), (192, 69), (192, 70), (192, 71), (192, 72), (192, 73), (192, 74), (192, 75), (192, 76), (192, 77), (192, 78), (192, 79), (192, 80), (192, 81), (192, 82), (192, 83), (192, 84), (192, 85), (192, 86), (192, 87), (192, 88), (192, 89), (192, 90), (192, 91), (192, 92), (192, 93), (192, 94), (192, 95), (192, 97), (193, 51), (193, 54), (193, 55), (193, 56), (193, 57), (193, 58), (193, 59), (193, 60), (193, 61), (193, 62), (193, 63), (193, 64), (193, 65), (193, 66), (193, 67), (193, 68), (193, 69), (193, 70), (193, 71), (193, 72), (193, 73), (193, 74), (193, 75), (193, 76), (193, 77), (193, 78), (193, 79), (193, 80), (193, 81), (193, 82), (193, 83),
(193, 84), (193, 85), (193, 86), (193, 87), (193, 88), (193, 89), (193, 90), (193, 91), (193, 92), (193, 93), (193, 94), (193, 95), (193, 97), (194, 52), (194, 56), (194, 57), (194, 58), (194, 59), (194, 60), (194, 61), (194, 62), (194, 63), (194, 64), (194, 65), (194, 66), (194, 67), (194, 68), (194, 69), (194, 70), (194, 71), (194, 72), (194, 73), (194, 74), (194, 75), (194, 76), (194, 77), (194, 78), (194, 79), (194, 80), (194, 81), (194, 82), (194, 83), (194, 84), (194, 85), (194, 86), (194, 87), (194, 88), (194, 89), (194, 90), (194, 91), (194, 92), (194, 93), (194, 94), (194, 95), (194, 97), (195, 54), (195, 57), (195, 58), (195, 59), (195, 60), (195, 61), (195, 62), (195, 63), (195, 64), (195, 65), (195, 66), (195, 67), (195, 68), (195, 69), (195, 70), (195, 71), (195, 72),
(195, 73), (195, 74), (195, 75), (195, 76), (195, 77), (195, 78), (195, 79), (195, 80), (195, 81), (195, 82), (195, 83), (195, 84), (195, 85), (195, 86), (195, 87), (195, 88), (195, 89), (195, 90), (195, 91), (195, 92), (195, 93), (195, 94), (195, 95), (195, 97), (196, 56), (196, 65), (196, 66), (196, 67), (196, 68), (196, 69), (196, 70), (196, 71), (196, 72), (196, 73), (196, 74), (196, 75), (196, 76), (196, 77), (196, 78), (196, 79), (196, 80), (196, 81), (196, 82), (196, 83), (196, 84), (196, 85), (196, 86), (196, 87), (196, 88), (196, 89), (196, 96), (197, 57), (197, 58), (197, 59), (197, 60), (197, 61), (197, 62), (197, 63), (197, 64), (197, 67), (197, 68), (197, 69), (197, 70), (197, 71), (197, 72), (197, 73), (197, 74), (197, 75), (197, 76), (197, 77), (197, 78), (197, 79),
(197, 80), (197, 81), (197, 82), (197, 83), (197, 84), (197, 85), (197, 86), (197, 87), (197, 90), (197, 91), (197, 92), (197, 93), (197, 95), (198, 66), (198, 67), (198, 68), (198, 69), (198, 70), (198, 71), (198, 72), (198, 73), (198, 74), (198, 75), (198, 76), (198, 77), (198, 78), (198, 79), (198, 80), (198, 81), (198, 82), (198, 83), (198, 84), (198, 85), (198, 86), (198, 87), (198, 88), (199, 67), (199, 69), (199, 70), (199, 71), (199, 72), (199, 73), (199, 74), (199, 75), (199, 76), (199, 77), (199, 78), (199, 79), (199, 80), (199, 81), (199, 82), (199, 83), (199, 84), (199, 85), (199, 87), (200, 67), (200, 69), (200, 70), (200, 71), (200, 72), (200, 73), (200, 74), (200, 75), (200, 76), (200, 77), (200, 78), (200, 79), (200, 80), (200, 81), (200, 82), (200, 83), (200, 84),
(200, 85), (200, 87), (201, 63), (201, 64), (201, 65), (201, 66), (201, 67), (201, 68), (201, 69), (201, 70), (201, 71), (201, 72), (201, 73), (201, 74), (201, 75), (201, 76), (201, 77), (201, 78), (201, 79), (201, 80), (201, 81), (201, 82), (201, 83), (201, 84), (201, 85), (201, 86), (201, 87), (201, 88), (202, 57), (202, 59), (202, 60), (202, 61), (202, 62), (202, 67), (202, 68), (202, 69), (202, 70), (202, 71), (202, 72), (202, 73), (202, 74), (202, 75), (202, 76), (202, 77), (202, 78), (202, 79), (202, 80), (202, 81), (202, 82), (202, 83), (202, 84), (202, 85), (202, 86), (202, 87), (202, 90), (202, 91), (202, 92), (202, 93), (202, 95), (203, 55), (203, 63), (203, 64), (203, 65), (203, 66), (203, 67), (203, 68), (203, 69), (203, 70), (203, 71), (203, 72), (203, 73), (203, 74),
(203, 75), (203, 76), (203, 77), (203, 78), (203, 79), (203, 80), (203, 81), (203, 82), (203, 83), (203, 84), (203, 85), (203, 86), (203, 87), (203, 88), (203, 89), (203, 96), (204, 54), (204, 57), (204, 58), (204, 59), (204, 60), (204, 61), (204, 62), (204, 63), (204, 64), (204, 65), (204, 66), (204, 67), (204, 68), (204, 69), (204, 70), (204, 71), (204, 72), (204, 73), (204, 74), (204, 75), (204, 76), (204, 77), (204, 78), (204, 79), (204, 80), (204, 81), (204, 82), (204, 83), (204, 84), (204, 85), (204, 86), (204, 87), (204, 88), (204, 89), (204, 90), (204, 91), (204, 92), (204, 93), (204, 94), (204, 95), (204, 97), (205, 53), (205, 55), (205, 56), (205, 57), (205, 58), (205, 59), (205, 60), (205, 61), (205, 62), (205, 63), (205, 64), (205, 65), (205, 66), (205, 67), (205, 68),
(205, 69), (205, 70), (205, 71), (205, 72), (205, 73), (205, 74), (205, 75), (205, 76), (205, 77), (205, 78), (205, 79), (205, 80), (205, 81), (205, 82), (205, 83), (205, 84), (205, 85), (205, 86), (205, 87), (205, 88), (205, 89), (205, 90), (205, 91), (205, 92), (205, 93), (205, 94), (205, 95), (205, 97), (206, 52), (206, 54), (206, 55), (206, 56), (206, 57), (206, 58), (206, 59), (206, 60), (206, 61), (206, 62), (206, 63), (206, 64), (206, 65), (206, 66), (206, 67), (206, 68), (206, 69), (206, 70), (206, 71), (206, 72), (206, 73), (206, 74), (206, 75), (206, 76), (206, 77), (206, 78), (206, 79), (206, 80), (206, 81), (206, 82), (206, 83), (206, 84), (206, 85), (206, 86), (206, 87), (206, 88), (206, 89), (206, 90), (206, 91), (206, 92), (206, 93), (206, 94), (206, 95), (206, 97),
(207, 51), (207, 53), (207, 54), (207, 55), (207, 56), (207, 57), (207, 58), (207, 59), (207, 60), (207, 61), (207, 62), (207, 63), (207, 64), (207, 65), (207, 66), (207, 67), (207, 68), (207, 69), (207, 70), (207, 71), (207, 72), (207, 73), (207, 74), (207, 75), (207, 76), (207, 77), (207, 78), (207, 79), (207, 80), (207, 81), (207, 82), (207, 83), (207, 84), (207, 85), (207, 86), (207, 87), (207, 88), (207, 89), (207, 90), (207, 91), (207, 92), (207, 93), (207, 94), (207, 95), (207, 97), (208, 51), (208, 53), (208, 54), (208, 55), (208, 56), (208, 57), (208, 58), (208, 59), (208, 60), (208, 61), (208, 62), (208, 63), (208, 64), (208, 65), (208, 66), (208, 67), (208, 68), (208, 69), (208, 70), (208, 71), (208, 72), (208, 73), (208, 74), (208, 75), (208, 76), (208, 77), (208, 78),
(208, 79), (208, 80), (208, 81), (208, 82), (208, 83), (208, 84), (208, 85), (208, 86), (208, 87), (208, 88), (208, 89), (208, 90), (208, 91), (208, 92), (208, 93), (208, 94), (208, 95), (208, 97), (209, 50), (209, 52), (209, 53), (209, 54), (209, 55), (209, 56), (209, 57), (209, 58), (209, 59), (209, 60), (209, 61), (209, 62), (209, 63), (209, 64), (209, 65), (209, 66), (209, 67), (209, 68), (209, 69), (209, 70), (209, 71), (209, 72), (209, 73), (209, 74), (209, 75), (209, 76), (209, 77), (209, 78), (209, 79), (209, 80), (209, 81), (209, 82), (209, 83), (209, 84), (209, 85), (209, 86), (209, 87), (209, 88), (209, 89), (209, 90), (209, 91), (209, 92), (209, 93), (209, 94), (209, 95), (209, 97), (210, 50), (210, 52), (210, 53), (210, 54), (210, 55), (210, 56), (210, 57), (210, 58),
(210, 59), (210, 60), (210, 61), (210, 62), (210, 63), (210, 64), (210, 65), (210, 66), (210, 67), (210, 68), (210, 69), (210, 70), (210, 71), (210, 72), (210, 73), (210, 74), (210, 75), (210, 76), (210, 77), (210, 78), (210, 79), (210, 80), (210, 81), (210, 82), (210, 83), (210, 84), (210, 85), (210, 86), (210, 87), (210, 88), (210, 89), (210, 90), (210, 91), (210, 92), (210, 93), (210, 94), (211, 50), (211, 52), (211, 53), (211, 54), (211, 55), (211, 56), (211, 57), (211, 58), (211, 59), (211, 60), (211, 61), (211, 62), (211, 63), (211, 64), (211, 65), (211, 66), (211, 67), (211, 68), (211, 69), (211, 70), (211, 71), (211, 72), (211, 73), (211, 74), (211, 75), (211, 76), (211, 77), (211, 78), (211, 79), (211, 80), (211, 81), (211, 82), (211, 83), (211, 84), (211, 85), (211, 86),
(211, 87), (211, 88), (211, 89), (211, 90), (211, 91), (211, 92), (211, 93), (211, 96), (212, 49), (212, 51), (212, 52), (212, 53), (212, 54), (212, 55), (212, 56), (212, 57), (212, 58), (212, 59), (212, 60), (212, 61), (212, 62), (212, 63), (212, 64), (212, 65), (212, 66), (212, 67), (212, 68), (212, 69), (212, 70), (212, 71), (212, 72), (212, 73), (212, 74), (212, 75), (212, 76), (212, 77), (212, 78), (212, 79), (212, 80), (212, 81), (212, 82), (212, 83), (212, 84), (212, 85), (212, 86), (212, 87), (212, 88), (212, 89), (212, 90), (212, 91), (212, 92), (212, 94), (213, 49), (213, 51), (213, 52), (213, 53), (213, 54), (213, 55), (213, 56), (213, 57), (213, 58), (213, 59), (213, 60), (213, 61), (213, 62), (213, 63), (213, 64), (213, 65), (213, 66), (213, 83), (213, 84), (213, 85),
(213, 86), (213, 87), (213, 88), (213, 89), (213, 90), (213, 93), (214, 49), (214, 51), (214, 52), (214, 53), (214, 54), (214, 55), (214, 56), (214, 57), (214, 58), (214, 59), (214, 60), (214, 61), (214, 62), (214, 63), (214, 64), (214, 65), (214, 68), (214, 69), (214, 70), (214, 71), (214, 72), (214, 73), (214, 74), (214, 75), (214, 76), (214, 77), (214, 78), (214, 79), (214, 80), (214, 81), (214, 82), (214, 85), (214, 86), (214, 87), (214, 88), (214, 89), (214, 92), (215, 49), (215, 51), (215, 52), (215, 53), (215, 54), (215, 55), (215, 56), (215, 57), (215, 58), (215, 59), (215, 60), (215, 61), (215, 62), (215, 63), (215, 64), (215, 66), (215, 83), (215, 86), (215, 87), (215, 88), (215, 90), (216, 49), (216, 51), (216, 52), (216, 53), (216, 54), (216, 55), (216, 56), (216, 57),
(216, 58), (216, 59), (216, 60), (216, 61), (216, 62), (216, 63), (216, 65), (216, 85), (216, 89), (217, 49), (217, 51), (217, 52), (217, 53), (217, 54), (217, 55), (217, 56), (217, 57), (217, 58), (217, 59), (217, 86), (218, 49), (218, 59), (218, 60), (218, 61), (218, 62), (218, 64), (218, 88), (219, 49), (219, 51), (219, 52), (219, 53), (219, 54), (219, 55), (219, 56), (219, 57), (219, 58), (219, 59), )
coordinates_7F3500 = ((143, 142),
(143, 144), (143, 145), (143, 146), (143, 147), (143, 149), (144, 140), (144, 151), (145, 139), (145, 142), (145, 143), (145, 144), (145, 145), (145, 146), (145, 147), (145, 148), (145, 149), (145, 153), (146, 138), (146, 140), (146, 141), (146, 142), (146, 143), (146, 144), (146, 145), (146, 146), (146, 147), (146, 148), (146, 149), (146, 150), (146, 151), (146, 154), (147, 137), (147, 139), (147, 140), (147, 141), (147, 142), (147, 143), (147, 144), (147, 145), (147, 146), (147, 147), (147, 148), (147, 149), (147, 150), (147, 151), (147, 152), (147, 153), (147, 156), (148, 136), (148, 138), (148, 139), (148, 140), (148, 141), (148, 142), (148, 143), (148, 144), (148, 145), (148, 146), (148, 147), (148, 148), (148, 149), (148, 150), (148, 151), (148, 152), (148, 153), (148, 154), (148, 157), (149, 138), (149, 139), (149, 140), (149, 141), (149, 142),
(149, 143), (149, 144), (149, 145), (149, 146), (149, 147), (149, 148), (149, 149), (149, 150), (149, 151), (149, 152), (149, 153), (149, 154), (149, 155), (149, 156), (149, 158), (150, 135), (150, 137), (150, 138), (150, 139), (150, 140), (150, 141), (150, 142), (150, 143), (150, 144), (150, 145), (150, 146), (150, 147), (150, 148), (150, 149), (150, 150), (150, 151), (150, 152), (150, 153), (150, 154), (150, 155), (150, 156), (150, 157), (150, 159), (151, 134), (151, 136), (151, 137), (151, 138), (151, 139), (151, 140), (151, 141), (151, 142), (151, 143), (151, 144), (151, 145), (151, 146), (151, 147), (151, 148), (151, 149), (151, 150), (151, 151), (151, 152), (151, 153), (151, 154), (151, 155), (151, 156), (151, 157), (151, 158), (151, 160), (152, 134), (152, 136), (152, 137), (152, 138), (152, 139), (152, 140), (152, 141), (152, 142), (152, 143),
(152, 144), (152, 145), (152, 146), (152, 147), (152, 148), (152, 149), (152, 150), (152, 151), (152, 152), (152, 153), (152, 154), (152, 155), (152, 156), (152, 157), (152, 158), (153, 133), (153, 135), (153, 136), (153, 137), (153, 138), (153, 139), (153, 140), (153, 141), (153, 142), (153, 143), (153, 144), (153, 145), (153, 146), (153, 147), (153, 148), (153, 149), (153, 150), (153, 151), (153, 152), (153, 153), (153, 154), (153, 155), (153, 156), (153, 157), (153, 158), (153, 159), (153, 161), (154, 133), (154, 135), (154, 136), (154, 137), (154, 138), (154, 139), (154, 140), (154, 141), (154, 142), (154, 143), (154, 144), (154, 145), (154, 146), (154, 147), (154, 148), (154, 149), (154, 150), (154, 151), (154, 152), (154, 153), (154, 154), (154, 155), (154, 156), (154, 157), (154, 158), (154, 159), (154, 160), (154, 162), (155, 133), (155, 135),
(155, 136), (155, 137), (155, 138), (155, 139), (155, 140), (155, 141), (155, 142), (155, 143), (155, 144), (155, 145), (155, 146), (155, 147), (155, 148), (155, 149), (155, 150), (155, 151), (155, 152), (155, 153), (155, 154), (155, 155), (155, 156), (155, 157), (155, 158), (155, 159), (155, 160), (155, 161), (155, 163), (156, 133), (156, 135), (156, 136), (156, 137), (156, 138), (156, 139), (156, 140), (156, 141), (156, 142), (156, 143), (156, 144), (156, 145), (156, 146), (156, 147), (156, 148), (156, 149), (156, 150), (156, 151), (156, 152), (156, 153), (156, 154), (156, 155), (156, 156), (156, 157), (156, 158), (156, 159), (156, 160), (156, 161), (156, 163), (157, 133), (157, 135), (157, 136), (157, 137), (157, 138), (157, 139), (157, 140), (157, 141), (157, 142), (157, 143), (157, 144), (157, 145), (157, 146), (157, 147), (157, 148), (157, 149),
(157, 150), (157, 151), (157, 152), (157, 153), (157, 154), (157, 155), (157, 156), (157, 157), (157, 158), (157, 159), (157, 160), (157, 161), (157, 162), (157, 164), (158, 133), (158, 135), (158, 136), (158, 137), (158, 138), (158, 139), (158, 140), (158, 141), (158, 142), (158, 143), (158, 144), (158, 145), (158, 146), (158, 147), (158, 148), (158, 149), (158, 150), (158, 151), (158, 152), (158, 153), (158, 154), (158, 155), (158, 156), (158, 157), (158, 158), (158, 159), (158, 160), (158, 161), (158, 162), (158, 163), (159, 133), (159, 135), (159, 136), (159, 137), (159, 138), (159, 139), (159, 140), (159, 141), (159, 142), (159, 143), (159, 144), (159, 145), (159, 146), (159, 147), (159, 148), (159, 149), (159, 150), (159, 151), (159, 152), (159, 153), (159, 154), (159, 155), (159, 156), (159, 157), (159, 158), (159, 159), (159, 160), (159, 161),
(159, 162), (159, 163), (159, 165), (160, 134), (160, 135), (160, 136), (160, 137), (160, 138), (160, 139), (160, 140), (160, 141), (160, 142), (160, 143), (160, 144), (160, 145), (160, 146), (160, 147), (160, 148), (160, 149), (160, 150), (160, 151), (160, 152), (160, 153), (160, 154), (160, 155), (160, 156), (160, 157), (160, 158), (160, 159), (160, 160), (160, 161), (160, 162), (160, 163), (160, 164), (160, 166), (161, 134), (161, 136), (161, 137), (161, 138), (161, 139), (161, 140), (161, 141), (161, 142), (161, 143), (161, 144), (161, 145), (161, 146), (161, 147), (161, 148), (161, 149), (161, 150), (161, 151), (161, 152), (161, 153), (161, 154), (161, 155), (161, 156), (161, 157), (161, 158), (161, 159), (161, 160), (161, 161), (161, 162), (161, 163), (161, 164), (161, 166), (162, 134), (162, 136), (162, 137), (162, 138), (162, 139), (162, 140),
(162, 141), (162, 142), (162, 143), (162, 144), (162, 145), (162, 146), (162, 147), (162, 148), (162, 149), (162, 150), (162, 151), (162, 152), (162, 153), (162, 154), (162, 155), (162, 156), (162, 157), (162, 158), (162, 159), (162, 160), (162, 161), (162, 162), (162, 163), (162, 164), (162, 165), (162, 167), (163, 135), (163, 137), (163, 138), (163, 139), (163, 140), (163, 141), (163, 142), (163, 143), (163, 144), (163, 145), (163, 146), (163, 147), (163, 148), (163, 149), (163, 150), (163, 151), (163, 152), (163, 153), (163, 154), (163, 155), (163, 156), (163, 157), (163, 158), (163, 159), (163, 160), (163, 161), (163, 162), (163, 163), (163, 164), (163, 165), (163, 166), (163, 168), (164, 135), (164, 137), (164, 138), (164, 139), (164, 140), (164, 141), (164, 142), (164, 143), (164, 144), (164, 145), (164, 146), (164, 147), (164, 148), (164, 149),
(164, 150), (164, 151), (164, 152), (164, 153), (164, 154), (164, 155), (164, 156), (164, 157), (164, 158), (164, 159), (164, 160), (164, 161), (164, 162), (164, 163), (164, 164), (164, 165), (164, 166), (164, 167), (164, 170), (165, 136), (165, 138), (165, 139), (165, 140), (165, 141), (165, 142), (165, 143), (165, 144), (165, 145), (165, 146), (165, 147), (165, 148), (165, 149), (165, 150), (165, 151), (165, 152), (165, 153), (165, 154), (165, 155), (165, 156), (165, 157), (165, 158), (165, 159), (165, 160), (165, 161), (165, 162), (165, 163), (165, 164), (165, 165), (165, 166), (165, 167), (165, 168), (165, 171), (166, 136), (166, 138), (166, 139), (166, 140), (166, 141), (166, 142), (166, 143), (166, 144), (166, 145), (166, 146), (166, 147), (166, 148), (166, 149), (166, 150), (166, 151), (166, 152), (166, 153), (166, 154), (166, 155), (166, 156),
(166, 157), (166, 158), (166, 159), (166, 160), (166, 161), (166, 162), (166, 163), (166, 164), (166, 165), (166, 166), (166, 167), (166, 168), (166, 169), (166, 170), (166, 173), (166, 195), (166, 198), (167, 137), (167, 139), (167, 140), (167, 141), (167, 142), (167, 143), (167, 144), (167, 145), (167, 146), (167, 147), (167, 148), (167, 149), (167, 150), (167, 151), (167, 152), (167, 153), (167, 154), (167, 155), (167, 156), (167, 157), (167, 158), (167, 159), (167, 160), (167, 161), (167, 162), (167, 163), (167, 164), (167, 165), (167, 166), (167, 167), (167, 168), (167, 169), (167, 170), (167, 171), (167, 172), (167, 175), (167, 176), (167, 194), (167, 198), (168, 137), (168, 139), (168, 140), (168, 141), (168, 142), (168, 143), (168, 144), (168, 145), (168, 146), (168, 147), (168, 148), (168, 149), (168, 150), (168, 151), (168, 152), (168, 153),
(168, 154), (168, 155), (168, 156), (168, 157), (168, 158), (168, 159), (168, 160), (168, 161), (168, 162), (168, 163), (168, 164), (168, 165), (168, 166), (168, 167), (168, 168), (168, 169), (168, 170), (168, 171), (168, 172), (168, 173), (168, 174), (168, 177), (168, 178), (168, 179), (168, 193), (168, 195), (168, 197), (169, 138), (169, 140), (169, 141), (169, 142), (169, 143), (169, 144), (169, 145), (169, 146), (169, 147), (169, 148), (169, 149), (169, 150), (169, 151), (169, 152), (169, 153), (169, 154), (169, 155), (169, 156), (169, 157), (169, 158), (169, 159), (169, 160), (169, 161), (169, 162), (169, 163), (169, 164), (169, 165), (169, 166), (169, 167), (169, 168), (169, 169), (169, 170), (169, 171), (169, 172), (169, 173), (169, 174), (169, 175), (169, 176), (169, 180), (169, 181), (169, 182), (169, 183), (169, 191), (169, 194), (169, 195),
(169, 197), (170, 138), (170, 140), (170, 141), (170, 142), (170, 143), (170, 144), (170, 145), (170, 146), (170, 147), (170, 148), (170, 149), (170, 150), (170, 151), (170, 152), (170, 153), (170, 154), (170, 155), (170, 156), (170, 157), (170, 158), (170, 159), (170, 160), (170, 161), (170, 162), (170, 163), (170, 164), (170, 165), (170, 166), (170, 167), (170, 168), (170, 169), (170, 170), (170, 171), (170, 172), (170, 173), (170, 174), (170, 175), (170, 176), (170, 177), (170, 178), (170, 179), (170, 184), (170, 185), (170, 186), (170, 187), (170, 188), (170, 189), (170, 190), (170, 193), (170, 194), (170, 195), (170, 197), (171, 138), (171, 140), (171, 141), (171, 142), (171, 143), (171, 144), (171, 145), (171, 146), (171, 147), (171, 148), (171, 149), (171, 150), (171, 151), (171, 152), (171, 153), (171, 154), (171, 155), (171, 156), (171, 157),
(171, 158), (171, 159), (171, 160), (171, 161), (171, 162), (171, 163), (171, 164), (171, 165), (171, 166), (171, 167), (171, 168), (171, 169), (171, 170), (171, 171), (171, 172), (171, 173), (171, 174), (171, 175), (171, 176), (171, 177), (171, 178), (171, 179), (171, 180), (171, 181), (171, 182), (171, 183), (171, 191), (171, 192), (171, 193), (171, 194), (171, 195), (171, 197), (172, 139), (172, 141), (172, 142), (172, 143), (172, 144), (172, 145), (172, 146), (172, 147), (172, 148), (172, 149), (172, 150), (172, 151), (172, 152), (172, 153), (172, 154), (172, 155), (172, 156), (172, 157), (172, 158), (172, 159), (172, 160), (172, 161), (172, 162), (172, 163), (172, 164), (172, 165), (172, 166), (172, 167), (172, 168), (172, 169), (172, 170), (172, 171), (172, 172), (172, 173), (172, 174), (172, 175), (172, 176), (172, 177), (172, 178), (172, 179),
(172, 180), (172, 181), (172, 182), (172, 183), (172, 184), (172, 185), (172, 186), (172, 187), (172, 188), (172, 189), (172, 190), (172, 191), (172, 192), (172, 193), (172, 194), (172, 196), (173, 139), (173, 141), (173, 142), (173, 143), (173, 144), (173, 145), (173, 146), (173, 147), (173, 148), (173, 149), (173, 150), (173, 151), (173, 152), (173, 153), (173, 154), (173, 155), (173, 156), (173, 157), (173, 158), (173, 159), (173, 160), (173, 161), (173, 162), (173, 163), (173, 164), (173, 165), (173, 166), (173, 167), (173, 168), (173, 169), (173, 170), (173, 171), (173, 172), (173, 173), (173, 174), (173, 175), (173, 176), (173, 177), (173, 178), (173, 179), (173, 180), (173, 181), (173, 182), (173, 183), (173, 184), (173, 185), (173, 186), (173, 187), (173, 188), (173, 189), (173, 190), (173, 191), (173, 192), (173, 193), (173, 194), (173, 196),
(174, 139), (174, 141), (174, 142), (174, 143), (174, 144), (174, 145), (174, 146), (174, 147), (174, 148), (174, 149), (174, 150), (174, 151), (174, 152), (174, 153), (174, 154), (174, 155), (174, 156), (174, 157), (174, 158), (174, 159), (174, 160), (174, 161), (174, 162), (174, 163), (174, 164), (174, 165), (174, 166), (174, 167), (174, 168), (174, 169), (174, 170), (174, 171), (174, 172), (174, 173), (174, 174), (174, 175), (174, 176), (174, 177), (174, 178), (174, 179), (174, 180), (174, 181), (174, 182), (174, 183), (174, 184), (174, 185), (174, 186), (174, 187), (174, 188), (174, 189), (174, 190), (174, 191), (174, 192), (174, 193), (174, 195), (175, 140), (175, 142), (175, 143), (175, 144), (175, 145), (175, 146), (175, 147), (175, 148), (175, 149), (175, 150), (175, 151), (175, 152), (175, 153), (175, 154), (175, 155), (175, 156), (175, 157),
(175, 158), (175, 159), (175, 160), (175, 161), (175, 162), (175, 163), (175, 164), (175, 165), (175, 166), (175, 167), (175, 168), (175, 169), (175, 170), (175, 171), (175, 172), (175, 173), (175, 174), (175, 175), (175, 176), (175, 177), (175, 178), (175, 179), (175, 180), (175, 181), (175, 182), (175, 183), (175, 184), (175, 185), (175, 186), (175, 187), (175, 188), (175, 189), (175, 190), (175, 191), (175, 192), (175, 193), (175, 195), (176, 141), (176, 143), (176, 144), (176, 145), (176, 146), (176, 147), (176, 148), (176, 149), (176, 150), (176, 151), (176, 152), (176, 153), (176, 154), (176, 155), (176, 156), (176, 157), (176, 158), (176, 159), (176, 160), (176, 161), (176, 162), (176, 163), (176, 164), (176, 165), (176, 166), (176, 167), (176, 168), (176, 169), (176, 170), (176, 171), (176, 172), (176, 173), (176, 174), (176, 175), (176, 176),
(176, 177), (176, 178), (176, 179), (176, 180), (176, 181), (176, 182), (176, 183), (176, 184), (176, 185), (176, 186), (176, 187), (176, 188), (176, 189), (176, 190), (176, 191), (176, 192), (176, 193), (176, 195), (177, 142), (177, 144), (177, 145), (177, 146), (177, 147), (177, 148), (177, 149), (177, 150), (177, 151), (177, 152), (177, 153), (177, 154), (177, 155), (177, 156), (177, 157), (177, 158), (177, 159), (177, 160), (177, 161), (177, 162), (177, 163), (177, 164), (177, 165), (177, 166), (177, 167), (177, 168), (177, 169), (177, 170), (177, 171), (177, 172), (177, 173), (177, 174), (177, 175), (177, 176), (177, 177), (177, 178), (177, 179), (177, 180), (177, 181), (177, 182), (177, 183), (177, 184), (177, 185), (177, 186), (177, 187), (177, 188), (177, 189), (177, 190), (177, 191), (177, 192), (177, 194), (178, 142), (178, 144), (178, 145),
(178, 146), (178, 147), (178, 148), (178, 149), (178, 150), (178, 151), (178, 152), (178, 153), (178, 154), (178, 155), (178, 156), (178, 157), (178, 158), (178, 159), (178, 160), (178, 161), (178, 162), (178, 163), (178, 164), (178, 165), (178, 166), (178, 167), (178, 168), (178, 169), (178, 170), (178, 171), (178, 172), (178, 173), (178, 174), (178, 175), (178, 176), (178, 177), (178, 178), (178, 179), (178, 180), (178, 181), (178, 182), (178, 183), (178, 184), (178, 185), (178, 186), (178, 187), (178, 188), (178, 189), (178, 190), (178, 191), (178, 192), (178, 194), (179, 143), (179, 145), (179, 146), (179, 147), (179, 148), (179, 149), (179, 150), (179, 151), (179, 152), (179, 153), (179, 154), (179, 155), (179, 156), (179, 157), (179, 158), (179, 159), (179, 160), (179, 161), (179, 162), (179, 163), (179, 164), (179, 165), (179, 166), (179, 167),
(179, 168), (179, 169), (179, 170), (179, 171), (179, 172), (179, 173), (179, 174), (179, 175), (179, 176), (179, 177), (179, 178), (179, 179), (179, 180), (179, 181), (179, 182), (179, 183), (179, 184), (179, 185), (179, 186), (179, 187), (179, 188), (179, 189), (179, 190), (179, 191), (179, 192), (179, 194), (180, 144), (180, 146), (180, 147), (180, 148), (180, 149), (180, 150), (180, 151), (180, 152), (180, 153), (180, 154), (180, 155), (180, 156), (180, 157), (180, 158), (180, 159), (180, 160), (180, 161), (180, 162), (180, 163), (180, 164), (180, 165), (180, 166), (180, 167), (180, 168), (180, 169), (180, 170), (180, 171), (180, 172), (180, 173), (180, 174), (180, 175), (180, 176), (180, 177), (180, 178), (180, 179), (180, 180), (180, 181), (180, 182), (180, 183), (180, 184), (180, 185), (180, 186), (180, 187), (180, 188), (180, 189), (180, 190),
(180, 191), (180, 192), (180, 194), (181, 145), (181, 147), (181, 148), (181, 149), (181, 150), (181, 151), (181, 152), (181, 153), (181, 154), (181, 155), (181, 156), (181, 157), (181, 158), (181, 159), (181, 160), (181, 161), (181, 162), (181, 163), (181, 164), (181, 165), (181, 166), (181, 167), (181, 168), (181, 169), (181, 170), (181, 171), (181, 172), (181, 173), (181, 174), (181, 175), (181, 176), (181, 177), (181, 178), (181, 179), (181, 180), (181, 181), (181, 182), (181, 183), (181, 184), (181, 185), (181, 186), (181, 187), (181, 188), (181, 189), (181, 190), (181, 191), (181, 194), (182, 145), (182, 147), (182, 148), (182, 149), (182, 150), (182, 151), (182, 152), (182, 153), (182, 154), (182, 155), (182, 156), (182, 157), (182, 158), (182, 159), (182, 160), (182, 161), (182, 162), (182, 163), (182, 164), (182, 165), (182, 166), (182, 167),
(182, 168), (182, 169), (182, 170), (182, 171), (182, 172), (182, 173), (182, 174), (182, 175), (182, 176), (182, 177), (182, 178), (182, 179), (182, 180), (182, 181), (182, 182), (182, 183), (182, 184), (182, 185), (182, 186), (182, 187), (182, 188), (182, 189), (182, 190), (182, 192), (183, 146), (183, 148), (183, 149), (183, 150), (183, 151), (183, 152), (183, 153), (183, 154), (183, 155), (183, 156), (183, 157), (183, 158), (183, 159), (183, 160), (183, 161), (183, 162), (183, 163), (183, 164), (183, 165), (183, 166), (183, 167), (183, 168), (183, 169), (183, 170), (183, 171), (183, 172), (183, 173), (183, 174), (183, 175), (183, 176), (183, 177), (183, 178), (183, 179), (183, 180), (183, 181), (183, 182), (183, 183), (183, 184), (183, 185), (183, 186), (183, 187), (183, 188), (183, 189), (183, 191), (184, 147), (184, 149), (184, 150), (184, 151),
(184, 152), (184, 153), (184, 154), (184, 155), (184, 156), (184, 157), (184, 158), (184, 159), (184, 160), (184, 161), (184, 162), (184, 163), (184, 164), (184, 165), (184, 166), (184, 167), (184, 168), (184, 169), (184, 170), (184, 171), (184, 172), (184, 173), (184, 174), (184, 175), (184, 176), (184, 177), (184, 178), (184, 179), (184, 180), (184, 181), (184, 182), (184, 183), (184, 184), (184, 185), (184, 186), (184, 187), (184, 188), (184, 190), (185, 148), (185, 151), (185, 152), (185, 153), (185, 154), (185, 155), (185, 156), (185, 157), (185, 158), (185, 159), (185, 160), (185, 161), (185, 162), (185, 163), (185, 164), (185, 165), (185, 166), (185, 167), (185, 168), (185, 169), (185, 170), (185, 171), (185, 172), (185, 173), (185, 174), (185, 175), (185, 176), (185, 177), (185, 178), (185, 179), (185, 180), (185, 181), (185, 182), (185, 183),
(185, 184), (185, 185), (185, 186), (185, 187), (185, 190), (186, 149), (186, 153), (186, 154), (186, 155), (186, 156), (186, 157), (186, 158), (186, 159), (186, 160), (186, 161), (186, 162), (186, 163), (186, 164), (186, 165), (186, 166), (186, 167), (186, 168), (186, 169), (186, 170), (186, 171), (186, 172), (186, 173), (186, 174), (186, 175), (186, 176), (186, 177), (186, 178), (186, 179), (186, 180), (186, 187), (186, 189), (187, 151), (187, 156), (187, 157), (187, 158), (187, 159), (187, 160), (187, 161), (187, 162), (187, 163), (187, 164), (187, 165), (187, 166), (187, 167), (187, 168), (187, 169), (187, 170), (187, 171), (187, 172), (187, 173), (187, 174), (187, 175), (187, 176), (187, 181), (187, 182), (187, 183), (187, 184), (187, 185), (187, 186), (187, 187), (188, 153), (188, 159), (188, 160), (188, 161), (188, 162), (188, 163), (188, 164),
(188, 165), (188, 166), (188, 167), (188, 168), (188, 169), (188, 170), (188, 171), (188, 172), (188, 173), (188, 177), (188, 178), (188, 179), (188, 180), (189, 156), (189, 157), (189, 158), (189, 165), (189, 166), (189, 167), (189, 174), (189, 175), (189, 176), (190, 159), (190, 160), (190, 161), (190, 162), (190, 163), (190, 164), (190, 165), (190, 166), (190, 167), (190, 168), (190, 169), (190, 170), (190, 171), (190, 173), (209, 159), (209, 160), (209, 161), (209, 162), (209, 163), (209, 164), (209, 165), (209, 166), (209, 167), (209, 168), (209, 169), (209, 170), (209, 171), (209, 172), (209, 173), (210, 156), (210, 157), (210, 175), (210, 176), (211, 153), (211, 158), (211, 159), (211, 160), (211, 161), (211, 162), (211, 163), (211, 164), (211, 165), (211, 166), (211, 167), (211, 168), (211, 169), (211, 170), (211, 171), (211, 172), (211, 173),
(211, 174), (211, 177), (211, 178), (211, 179), (211, 180), (212, 151), (212, 155), (212, 156), (212, 157), (212, 158), (212, 159), (212, 160), (212, 161), (212, 162), (212, 163), (212, 164), (212, 165), (212, 166), (212, 167), (212, 168), (212, 169), (212, 170), (212, 171), (212, 172), (212, 173), (212, 174), (212, 175), (212, 176), (212, 182), (212, 183), (212, 184), (212, 185), (212, 186), (212, 187), (212, 189), (213, 149), (213, 153), (213, 154), (213, 155), (213, 156), (213, 157), (213, 158), (213, 159), (213, 160), (213, 161), (213, 162), (213, 163), (213, 164), (213, 165), (213, 166), (213, 167), (213, 168), (213, 169), (213, 170), (213, 171), (213, 172), (213, 173), (213, 174), (213, 175), (213, 176), (213, 177), (213, 178), (213, 179), (213, 180), (213, 181), (213, 189), (214, 148), (214, 151), (214, 152), (214, 153), (214, 154), (214, 155),
(214, 156), (214, 157), (214, 158), (214, 159), (214, 160), (214, 161), (214, 162), (214, 163), (214, 164), (214, 165), (214, 166), (214, 167), (214, 168), (214, 169), (214, 170), (214, 171), (214, 172), (214, 173), (214, 174), (214, 175), (214, 176), (214, 177), (214, 178), (214, 179), (214, 180), (214, 181), (214, 182), (214, 183), (214, 184), (214, 185), (214, 186), (214, 187), (214, 190), (215, 147), (215, 149), (215, 150), (215, 151), (215, 152), (215, 153), (215, 154), (215, 155), (215, 156), (215, 157), (215, 158), (215, 159), (215, 160), (215, 161), (215, 162), (215, 163), (215, 164), (215, 165), (215, 166), (215, 167), (215, 168), (215, 169), (215, 170), (215, 171), (215, 172), (215, 173), (215, 174), (215, 175), (215, 176), (215, 177), (215, 178), (215, 179), (215, 180), (215, 181), (215, 182), (215, 183), (215, 184), (215, 185), (215, 186),
(215, 187), (215, 188), (215, 190), (216, 146), (216, 148), (216, 149), (216, 150), (216, 151), (216, 152), (216, 153), (216, 154), (216, 155), (216, 156), (216, 157), (216, 158), (216, 159), (216, 160), (216, 161), (216, 162), (216, 163), (216, 164), (216, 165), (216, 166), (216, 167), (216, 168), (216, 169), (216, 170), (216, 171), (216, 172), (216, 173), (216, 174), (216, 175), (216, 176), (216, 177), (216, 178), (216, 179), (216, 180), (216, 181), (216, 182), (216, 183), (216, 184), (216, 185), (216, 186), (216, 187), (216, 188), (216, 189), (216, 191), (217, 145), (217, 147), (217, 148), (217, 149), (217, 150), (217, 151), (217, 152), (217, 153), (217, 154), (217, 155), (217, 156), (217, 157), (217, 158), (217, 159), (217, 160), (217, 161), (217, 162), (217, 163), (217, 164), (217, 165), (217, 166), (217, 167), (217, 168), (217, 169), (217, 170),
(217, 171), (217, 172), (217, 173), (217, 174), (217, 175), (217, 176), (217, 177), (217, 178), (217, 179), (217, 180), (217, 181), (217, 182), (217, 183), (217, 184), (217, 185), (217, 186), (217, 187), (217, 188), (217, 189), (217, 190), (217, 192), (218, 145), (218, 147), (218, 148), (218, 149), (218, 150), (218, 151), (218, 152), (218, 153), (218, 154), (218, 155), (218, 156), (218, 157), (218, 158), (218, 159), (218, 160), (218, 161), (218, 162), (218, 163), (218, 164), (218, 165), (218, 166), (218, 167), (218, 168), (218, 169), (218, 170), (218, 171), (218, 172), (218, 173), (218, 174), (218, 175), (218, 176), (218, 177), (218, 178), (218, 179), (218, 180), (218, 181), (218, 182), (218, 183), (218, 184), (218, 185), (218, 186), (218, 187), (218, 188), (218, 189), (218, 190), (218, 191), (218, 194), (219, 144), (219, 146), (219, 147), (219, 148),
(219, 149), (219, 150), (219, 151), (219, 152), (219, 153), (219, 154), (219, 155), (219, 156), (219, 157), (219, 158), (219, 159), (219, 160), (219, 161), (219, 162), (219, 163), (219, 164), (219, 165), (219, 166), (219, 167), (219, 168), (219, 169), (219, 170), (219, 171), (219, 172), (219, 173), (219, 174), (219, 175), (219, 176), (219, 177), (219, 178), (219, 179), (219, 180), (219, 181), (219, 182), (219, 183), (219, 184), (219, 185), (219, 186), (219, 187), (219, 188), (219, 189), (219, 190), (219, 191), (219, 192), (219, 194), (220, 143), (220, 145), (220, 146), (220, 147), (220, 148), (220, 149), (220, 150), (220, 151), (220, 152), (220, 153), (220, 154), (220, 155), (220, 156), (220, 157), (220, 158), (220, 159), (220, 160), (220, 161), (220, 162), (220, 163), (220, 164), (220, 165), (220, 166), (220, 167), (220, 168), (220, 169), (220, 170),
(220, 171), (220, 172), (220, 173), (220, 174), (220, 175), (220, 176), (220, 177), (220, 178), (220, 179), (220, 180), (220, 181), (220, 182), (220, 183), (220, 184), (220, 185), (220, 186), (220, 187), (220, 188), (220, 189), (220, 190), (220, 191), (220, 192), (220, 194), (221, 142), (221, 144), (221, 145), (221, 146), (221, 147), (221, 148), (221, 149), (221, 150), (221, 151), (221, 152), (221, 153), (221, 154), (221, 155), (221, 156), (221, 157), (221, 158), (221, 159), (221, 160), (221, 161), (221, 162), (221, 163), (221, 164), (221, 165), (221, 166), (221, 167), (221, 168), (221, 169), (221, 170), (221, 171), (221, 172), (221, 173), (221, 174), (221, 175), (221, 176), (221, 177), (221, 178), (221, 179), (221, 180), (221, 181), (221, 182), (221, 183), (221, 184), (221, 185), (221, 186), (221, 187), (221, 188), (221, 189), (221, 190), (221, 191),
(221, 192), (221, 194), (222, 144), (222, 145), (222, 146), (222, 147), (222, 148), (222, 149), (222, 150), (222, 151), (222, 152), (222, 153), (222, 154), (222, 155), (222, 156), (222, 157), (222, 158), (222, 159), (222, 160), (222, 161), (222, 162), (222, 163), (222, 164), (222, 165), (222, 166), (222, 167), (222, 168), (222, 169), (222, 170), (222, 171), (222, 172), (222, 173), (222, 174), (222, 175), (222, 176), (222, 177), (222, 178), (222, 179), (222, 180), (222, 181), (222, 182), (222, 183), (222, 184), (222, 185), (222, 186), (222, 187), (222, 188), (222, 189), (222, 190), (222, 191), (222, 192), (222, 194), (223, 141), (223, 143), (223, 144), (223, 145), (223, 146), (223, 147), (223, 148), (223, 149), (223, 150), (223, 151), (223, 152), (223, 153), (223, 154), (223, 155), (223, 156), (223, 157), (223, 158), (223, 159), (223, 160), (223, 161),
(223, 162), (223, 163), (223, 164), (223, 165), (223, 166), (223, 167), (223, 168), (223, 169), (223, 170), (223, 171), (223, 172), (223, 173), (223, 174), (223, 175), (223, 176), (223, 177), (223, 178), (223, 179), (223, 180), (223, 181), (223, 182), (223, 183), (223, 184), (223, 185), (223, 186), (223, 187), (223, 188), (223, 189), (223, 190), (223, 191), (223, 192), (223, 193), (223, 195), (224, 140), (224, 142), (224, 143), (224, 144), (224, 145), (224, 146), (224, 147), (224, 148), (224, 149), (224, 150), (224, 151), (224, 152), (224, 153), (224, 154), (224, 155), (224, 156), (224, 157), (224, 158), (224, 159), (224, 160), (224, 161), (224, 162), (224, 163), (224, 164), (224, 165), (224, 166), (224, 167), (224, 168), (224, 169), (224, 170), (224, 171), (224, 172), (224, 173), (224, 174), (224, 175), (224, 176), (224, 177), (224, 178), (224, 179),
(224, 180), (224, 181), (224, 182), (224, 183), (224, 184), (224, 185), (224, 186), (224, 187), (224, 188), (224, 189), (224, 190), (224, 191), (224, 192), (224, 193), (224, 195), (225, 139), (225, 141), (225, 142), (225, 143), (225, 144), (225, 145), (225, 146), (225, 147), (225, 148), (225, 149), (225, 150), (225, 151), (225, 152), (225, 153), (225, 154), (225, 155), (225, 156), (225, 157), (225, 158), (225, 159), (225, 160), (225, 161), (225, 162), (225, 163), (225, 164), (225, 165), (225, 166), (225, 167), (225, 168), (225, 169), (225, 170), (225, 171), (225, 172), (225, 173), (225, 174), (225, 175), (225, 176), (225, 177), (225, 178), (225, 179), (225, 180), (225, 181), (225, 182), (225, 183), (225, 184), (225, 185), (225, 186), (225, 187), (225, 188), (225, 189), (225, 190), (225, 191), (225, 192), (225, 193), (225, 195), (226, 139), (226, 141),
(226, 142), (226, 143), (226, 144), (226, 145), (226, 146), (226, 147), (226, 148), (226, 149), (226, 150), (226, 151), (226, 152), (226, 153), (226, 154), (226, 155), (226, 156), (226, 157), (226, 158), (226, 159), (226, 160), (226, 161), (226, 162), (226, 163), (226, 164), (226, 165), (226, 166), (226, 167), (226, 168), (226, 169), (226, 170), (226, 171), (226, 172), (226, 173), (226, 174), (226, 175), (226, 176), (226, 177), (226, 178), (226, 179), (226, 180), (226, 181), (226, 182), (226, 183), (226, 184), (226, 185), (226, 186), (226, 187), (226, 188), (226, 189), (226, 190), (226, 191), (226, 192), (226, 193), (226, 194), (226, 196), (227, 139), (227, 141), (227, 142), (227, 143), (227, 144), (227, 145), (227, 146), (227, 147), (227, 148), (227, 149), (227, 150), (227, 151), (227, 152), (227, 153), (227, 154), (227, 155), (227, 156), (227, 157),
(227, 158), (227, 159), (227, 160), (227, 161), (227, 162), (227, 163), (227, 164), (227, 165), (227, 166), (227, 167), (227, 168), (227, 169), (227, 170), (227, 171), (227, 172), (227, 173), (227, 174), (227, 175), (227, 176), (227, 177), (227, 178), (227, 179), (227, 180), (227, 181), (227, 182), (227, 183), (227, 184), (227, 185), (227, 186), (227, 187), (227, 188), (227, 189), (227, 190), (227, 191), (227, 192), (227, 193), (227, 194), (227, 196), (228, 138), (228, 140), (228, 141), (228, 142), (228, 143), (228, 144), (228, 145), (228, 146), (228, 147), (228, 148), (228, 149), (228, 150), (228, 151), (228, 152), (228, 153), (228, 154), (228, 155), (228, 156), (228, 157), (228, 158), (228, 159), (228, 160), (228, 161), (228, 162), (228, 163), (228, 164), (228, 165), (228, 166), (228, 167), (228, 168), (228, 169), (228, 170), (228, 171), (228, 172),
(228, 173), (228, 174), (228, 175), (228, 176), (228, 177), (228, 178), (228, 179), (228, 180), (228, 181), (228, 182), (228, 183), (228, 191), (228, 192), (228, 193), (228, 194), (228, 195), (228, 197), (229, 138), (229, 140), (229, 141), (229, 142), (229, 143), (229, 144), (229, 145), (229, 146), (229, 147), (229, 148), (229, 149), (229, 150), (229, 151), (229, 152), (229, 153), (229, 154), (229, 155), (229, 156), (229, 157), (229, 158), (229, 159), (229, 160), (229, 161), (229, 162), (229, 163), (229, 164), (229, 165), (229, 166), (229, 167), (229, 168), (229, 169), (229, 170), (229, 171), (229, 172), (229, 173), (229, 174), (229, 175), (229, 176), (229, 177), (229, 178), (229, 179), (229, 184), (229, 185), (229, 186), (229, 187), (229, 188), (229, 189), (229, 190), (229, 193), (229, 194), (229, 195), (229, 197), (230, 138), (230, 140), (230, 141),
(230, 142), (230, 143), (230, 144), (230, 145), (230, 146), (230, 147), (230, 148), (230, 149), (230, 150), (230, 151), (230, 152), (230, 153), (230, 154), (230, 155), (230, 156), (230, 157), (230, 158), (230, 159), (230, 160), (230, 161), (230, 162), (230, 163), (230, 164), (230, 165), (230, 166), (230, 167), (230, 168), (230, 169), (230, 170), (230, 171), (230, 172), (230, 173), (230, 174), (230, 175), (230, 176), (230, 180), (230, 181), (230, 182), (230, 183), (230, 191), (230, 192), (230, 194), (230, 195), (230, 197), (231, 137), (231, 139), (231, 140), (231, 141), (231, 142), (231, 143), (231, 144), (231, 145), (231, 146), (231, 147), (231, 148), (231, 149), (231, 150), (231, 151), (231, 152), (231, 153), (231, 154), (231, 155), (231, 156), (231, 157), (231, 158), (231, 159), (231, 160), (231, 161), (231, 162), (231, 163), (231, 164), (231, 165),
(231, 166), (231, 167), (231, 168), (231, 169), (231, 170), (231, 171), (231, 172), (231, 173), (231, 174), (231, 177), (231, 178), (231, 179), (231, 193), (231, 195), (231, 197), (232, 137), (232, 139), (232, 140), (232, 141), (232, 142), (232, 143), (232, 144), (232, 145), (232, 146), (232, 147), (232, 148), (232, 149), (232, 150), (232, 151), (232, 152), (232, 153), (232, 154), (232, 155), (232, 156), (232, 157), (232, 158), (232, 159), (232, 160), (232, 161), (232, 162), (232, 163), (232, 164), (232, 165), (232, 166), (232, 167), (232, 168), (232, 169), (232, 170), (232, 171), (232, 175), (232, 176), (232, 194), (232, 198), (233, 136), (233, 138), (233, 139), (233, 140), (233, 141), (233, 142), (233, 143), (233, 144), (233, 145), (233, 146), (233, 147), (233, 148), (233, 149), (233, 150), (233, 151), (233, 152), (233, 153), (233, 154), (233, 155),
(233, 156), (233, 157), (233, 158), (233, 159), (233, 160), (233, 161), (233, 162), (233, 163), (233, 164), (233, 165), (233, 166), (233, 167), (233, 168), (233, 169), (233, 170), (233, 173), (233, 195), (233, 198), (234, 136), (234, 138), (234, 139), (234, 140), (234, 141), (234, 142), (234, 143), (234, 144), (234, 145), (234, 146), (234, 147), (234, 148), (234, 149), (234, 150), (234, 151), (234, 152), (234, 153), (234, 154), (234, 155), (234, 156), (234, 157), (234, 158), (234, 159), (234, 160), (234, 161), (234, 162), (234, 163), (234, 164), (234, 165), (234, 166), (234, 167), (234, 168), (234, 171), (235, 135), (235, 137), (235, 138), (235, 139), (235, 140), (235, 141), (235, 142), (235, 143), (235, 144), (235, 145), (235, 146), (235, 147), (235, 148), (235, 149), (235, 150), (235, 151), (235, 152), (235, 153), (235, 154), (235, 155), (235, 156),
(235, 157), (235, 158), (235, 159), (235, 160), (235, 161), (235, 162), (235, 163), (235, 164), (235, 165), (235, 166), (235, 167), (235, 170), (236, 135), (236, 137), (236, 138), (236, 139), (236, 140), (236, 141), (236, 142), (236, 143), (236, 144), (236, 145), (236, 146), (236, 147), (236, 148), (236, 149), (236, 150), (236, 151), (236, 152), (236, 153), (236, 154), (236, 155), (236, 156), (236, 157), (236, 158), (236, 159), (236, 160), (236, 161), (236, 162), (236, 163), (236, 164), (236, 165), (236, 166), (236, 168), (237, 134), (237, 136), (237, 137), (237, 138), (237, 139), (237, 140), (237, 141), (237, 142), (237, 143), (237, 144), (237, 145), (237, 146), (237, 147), (237, 148), (237, 149), (237, 150), (237, 151), (237, 152), (237, 153), (237, 154), (237, 155), (237, 156), (237, 157), (237, 158), (237, 159), (237, 160), (237, 161), (237, 162),
(237, 163), (237, 164), (237, 165), (237, 167), (238, 134), (238, 136), (238, 137), (238, 138), (238, 139), (238, 140), (238, 141), (238, 142), (238, 143), (238, 144), (238, 145), (238, 146), (238, 147), (238, 148), (238, 149), (238, 150), (238, 151), (238, 152), (238, 153), (238, 154), (238, 155), (238, 156), (238, 157), (238, 158), (238, 159), (238, 160), (238, 161), (238, 162), (238, 163), (238, 164), (238, 166), (239, 133), (239, 134), (239, 135), (239, 136), (239, 137), (239, 138), (239, 139), (239, 140), (239, 141), (239, 142), (239, 143), (239, 144), (239, 145), (239, 146), (239, 147), (239, 148), (239, 149), (239, 150), (239, 151), (239, 152), (239, 153), (239, 154), (239, 155), (239, 156), (239, 157), (239, 158), (239, 159), (239, 160), (239, 161), (239, 162), (239, 163), (239, 164), (239, 166), (240, 133), (240, 135), (240, 136), (240, 137),
(240, 138), (240, 139), (240, 140), (240, 141), (240, 142), (240, 143), (240, 144), (240, 145), (240, 146), (240, 147), (240, 148), (240, 149), (240, 150), (240, 151), (240, 152), (240, 153), (240, 154), (240, 155), (240, 156), (240, 157), (240, 158), (240, 159), (240, 160), (240, 161), (240, 162), (240, 163), (240, 165), (241, 133), (241, 135), (241, 136), (241, 137), (241, 138), (241, 139), (241, 140), (241, 141), (241, 142), (241, 143), (241, 144), (241, 145), (241, 146), (241, 147), (241, 148), (241, 149), (241, 150), (241, 151), (241, 152), (241, 153), (241, 154), (241, 155), (241, 156), (241, 157), (241, 158), (241, 159), (241, 160), (241, 161), (241, 162), (241, 164), (242, 133), (242, 135), (242, 136), (242, 137), (242, 138), (242, 139), (242, 140), (242, 141), (242, 142), (242, 143), (242, 144), (242, 145), (242, 146), (242, 147), (242, 148),
(242, 149), (242, 150), (242, 151), (242, 152), (242, 153), (242, 154), (242, 155), (242, 156), (242, 157), (242, 158), (242, 159), (242, 160), (242, 161), (242, 162), (242, 164), (243, 133), (243, 135), (243, 136), (243, 137), (243, 138), (243, 139), (243, 140), (243, 141), (243, 142), (243, 143), (243, 144), (243, 145), (243, 146), (243, 147), (243, 148), (243, 149), (243, 150), (243, 151), (243, 152), (243, 153), (243, 154), (243, 155), (243, 156), (243, 157), (243, 158), (243, 159), (243, 160), (243, 161), (243, 163), (244, 133), (244, 135), (244, 136), (244, 137), (244, 138), (244, 139), (244, 140), (244, 141), (244, 142), (244, 143), (244, 144), (244, 145), (244, 146), (244, 147), (244, 148), (244, 149), (244, 150), (244, 151), (244, 152), (244, 153), (244, 154), (244, 155), (244, 156), (244, 157), (244, 158), (244, 159), (244, 160), (244, 161),
(244, 163), (245, 133), (245, 135), (245, 136), (245, 137), (245, 138), (245, 139), (245, 140), (245, 141), (245, 142), (245, 143), (245, 144), (245, 145), (245, 146), (245, 147), (245, 148), (245, 149), (245, 150), (245, 151), (245, 152), (245, 153), (245, 154), (245, 155), (245, 156), (245, 157), (245, 158), (245, 159), (245, 160), (245, 162), (246, 133), (246, 135), (246, 136), (246, 137), (246, 138), (246, 139), (246, 140), (246, 141), (246, 142), (246, 143), (246, 144), (246, 145), (246, 146), (246, 147), (246, 148), (246, 149), (246, 150), (246, 151), (246, 152), (246, 153), (246, 154), (246, 155), (246, 156), (246, 157), (246, 158), (246, 159), (246, 161), (247, 134), (247, 136), (247, 137), (247, 138), (247, 139), (247, 140), (247, 141), (247, 142), (247, 143), (247, 144), (247, 145), (247, 146), (247, 147), (247, 148), (247, 149), (247, 150),
(247, 151), (247, 152), (247, 153), (247, 154), (247, 155), (247, 156), (247, 157), (247, 158), (247, 160), (248, 134), (248, 136), (248, 137), (248, 138), (248, 139), (248, 140), (248, 141), (248, 142), (248, 143), (248, 144), (248, 145), (248, 146), (248, 147), (248, 148), (248, 149), (248, 150), (248, 151), (248, 152), (248, 153), (248, 154), (248, 155), (248, 156), (248, 157), (248, 160), (249, 135), (249, 137), (249, 138), (249, 139), (249, 140), (249, 141), (249, 142), (249, 143), (249, 144), (249, 145), (249, 146), (249, 147), (249, 148), (249, 149), (249, 150), (249, 151), (249, 152), (249, 153), (249, 154), (249, 155), (249, 156), (249, 157), (249, 159), (250, 136), (250, 138), (250, 139), (250, 140), (250, 141), (250, 142), (250, 143), (250, 144), (250, 145), (250, 146), (250, 147), (250, 148), (250, 149), (250, 150), (250, 151), (250, 152),
(250, 153), (250, 154), (250, 155), (250, 158), (251, 136), (251, 138), (251, 139), (251, 140), (251, 141), (251, 142), (251, 143), (251, 144), (251, 145), (251, 146), (251, 147), (251, 148), (251, 149), (251, 150), (251, 151), (251, 152), (251, 153), (251, 154), (251, 157), (252, 137), (252, 139), (252, 140), (252, 141), (252, 142), (252, 143), (252, 144), (252, 145), (252, 146), (252, 147), (252, 148), (252, 149), (252, 150), (252, 151), (252, 152), (252, 153), (252, 156), (253, 138), (253, 140), (253, 141), (253, 142), (253, 143), (253, 144), (253, 145), (253, 146), (253, 147), (253, 148), (253, 149), (253, 150), (253, 151), (253, 154), (254, 139), (254, 142), (254, 143), (254, 144), (254, 145), (254, 146), (254, 147), (254, 148), (254, 149), (254, 153), (255, 140), (255, 151), (256, 142), (256, 144), (256, 145), (256, 146), (256, 147), (256, 149),
)
coordinates_6BFF00 = ((36, 198),
(36, 200), (36, 201), (36, 202), (37, 198), (37, 205), (38, 196), (38, 199), (38, 200), (38, 201), (38, 202), (38, 206), (39, 195), (39, 198), (39, 199), (39, 200), (39, 201), (39, 202), (39, 203), (39, 204), (39, 205), (39, 208), (40, 193), (40, 196), (40, 197), (40, 198), (40, 199), (40, 200), (40, 201), (40, 202), (40, 203), (40, 204), (40, 205), (40, 206), (40, 209), (41, 191), (41, 194), (41, 195), (41, 196), (41, 197), (41, 198), (41, 199), (41, 200), (41, 201), (41, 202), (41, 203), (41, 204), (41, 205), (41, 206), (41, 207), (41, 208), (41, 210), (42, 193), (42, 194), (42, 195), (42, 196), (42, 197), (42, 198), (42, 199), (42, 200), (42, 201), (42, 202), (42, 203), (42, 204), (42, 205), (42, 206), (42, 207), (42, 208), (42, 209), (42, 211), (43, 190), (43, 192), (43, 193),
(43, 194), (43, 195), (43, 196), (43, 197), (43, 198), (43, 199), (43, 200), (43, 201), (43, 202), (43, 203), (43, 204), (43, 205), (43, 206), (43, 207), (43, 208), (43, 209), (43, 210), (43, 212), (44, 190), (44, 192), (44, 193), (44, 194), (44, 195), (44, 196), (44, 197), (44, 198), (44, 199), (44, 200), (44, 201), (44, 202), (44, 203), (44, 204), (44, 205), (44, 206), (44, 207), (44, 208), (44, 209), (44, 210), (44, 212), (45, 191), (45, 194), (45, 195), (45, 196), (45, 197), (45, 198), (45, 199), (45, 200), (45, 201), (45, 202), (45, 203), (45, 204), (45, 205), (45, 206), (45, 207), (45, 208), (45, 209), (45, 210), (45, 211), (45, 213), (46, 192), (46, 195), (46, 196), (46, 197), (46, 198), (46, 199), (46, 200), (46, 201), (46, 202), (46, 203), (46, 204), (46, 205), (46, 206),
(46, 207), (46, 208), (46, 209), (46, 210), (46, 211), (46, 213), (47, 194), (47, 196), (47, 197), (47, 198), (47, 199), (47, 200), (47, 201), (47, 202), (47, 203), (47, 204), (47, 205), (47, 206), (47, 207), (47, 208), (47, 209), (47, 210), (47, 211), (47, 213), (48, 195), (48, 197), (48, 198), (48, 199), (48, 200), (48, 201), (48, 202), (48, 203), (48, 204), (48, 205), (48, 206), (48, 207), (48, 208), (48, 209), (48, 210), (48, 211), (48, 212), (48, 214), (49, 196), (49, 198), (49, 199), (49, 200), (49, 201), (49, 202), (49, 203), (49, 204), (49, 205), (49, 206), (49, 207), (49, 208), (49, 209), (49, 210), (49, 211), (49, 212), (49, 214), (50, 196), (50, 198), (50, 199), (50, 200), (50, 201), (50, 202), (50, 203), (50, 204), (50, 205), (50, 206), (50, 207), (50, 208), (50, 209),
(50, 210), (50, 211), (50, 212), (50, 214), (51, 196), (51, 198), (51, 199), (51, 200), (51, 201), (51, 202), (51, 203), (51, 204), (51, 205), (51, 206), (51, 207), (51, 208), (51, 209), (51, 210), (51, 211), (51, 212), (51, 214), (52, 196), (52, 198), (52, 199), (52, 200), (52, 201), (52, 202), (52, 203), (52, 204), (52, 205), (52, 206), (52, 207), (52, 208), (52, 209), (52, 210), (52, 211), (52, 212), (52, 214), (53, 195), (53, 197), (53, 198), (53, 199), (53, 200), (53, 201), (53, 202), (53, 203), (53, 204), (53, 205), (53, 206), (53, 207), (53, 208), (53, 209), (53, 210), (53, 211), (53, 212), (53, 214), (54, 195), (54, 196), (54, 197), (54, 198), (54, 199), (54, 200), (54, 201), (54, 202), (54, 203), (54, 204), (54, 205), (54, 206), (54, 207), (54, 208), (54, 209), (54, 210),
(54, 211), (54, 212), (54, 214), (55, 194), (55, 196), (55, 197), (55, 198), (55, 199), (55, 200), (55, 201), (55, 202), (55, 203), (55, 204), (55, 205), (55, 206), (55, 207), (55, 208), (55, 209), (55, 210), (55, 211), (55, 213), (56, 193), (56, 195), (56, 196), (56, 197), (56, 198), (56, 199), (56, 200), (56, 201), (56, 202), (56, 203), (56, 204), (56, 205), (56, 206), (56, 207), (56, 208), (56, 209), (56, 210), (56, 211), (56, 213), (57, 192), (57, 194), (57, 195), (57, 196), (57, 197), (57, 198), (57, 199), (57, 200), (57, 201), (57, 202), (57, 203), (57, 204), (57, 205), (57, 206), (57, 207), (57, 208), (57, 209), (57, 210), (57, 211), (57, 213), (58, 191), (58, 193), (58, 194), (58, 195), (58, 196), (58, 197), (58, 198), (58, 199), (58, 200), (58, 201), (58, 202), (58, 203),
(58, 204), (58, 205), (58, 206), (58, 207), (58, 208), (58, 209), (58, 210), (58, 212), (59, 191), (59, 193), (59, 194), (59, 195), (59, 196), (59, 197), (59, 198), (59, 199), (59, 200), (59, 201), (59, 202), (59, 203), (59, 204), (59, 205), (59, 206), (59, 207), (59, 208), (59, 209), (59, 210), (59, 212), (60, 191), (60, 193), (60, 194), (60, 195), (60, 196), (60, 197), (60, 198), (60, 199), (60, 200), (60, 201), (60, 202), (60, 203), (60, 204), (60, 205), (60, 206), (60, 207), (60, 208), (60, 209), (60, 210), (60, 212), (61, 191), (61, 198), (61, 199), (61, 200), (61, 201), (61, 202), (61, 203), (61, 204), (61, 205), (61, 206), (61, 207), (61, 208), (61, 209), (61, 210), (61, 212), (62, 191), (62, 193), (62, 194), (62, 195), (62, 196), (62, 197), (62, 198), (62, 199), (62, 200),
(62, 201), (62, 202), (62, 203), (62, 204), (62, 205), (62, 206), (62, 207), (62, 208), (62, 209), (62, 211), (63, 198), (63, 199), (63, 200), (63, 201), (63, 203), (63, 204), (63, 205), (63, 206), (63, 207), (63, 208), (63, 209), (63, 211), (64, 199), (64, 200), (64, 205), (64, 206), (64, 207), (64, 208), (64, 209), (64, 211), (65, 199), (65, 201), (65, 204), (65, 211), (66, 199), (66, 200), (66, 205), (66, 206), (66, 207), (66, 208), (66, 210), (67, 199), (332, 199), (333, 199), (333, 200), (333, 205), (333, 207), (333, 208), (333, 210), (334, 199), (334, 204), (334, 211), (335, 198), (335, 199), (335, 200), (335, 205), (335, 206), (335, 207), (335, 208), (335, 209), (335, 211), (336, 198), (336, 199), (336, 200), (336, 201), (336, 202), (336, 203), (336, 204), (336, 205), (336, 206), (336, 207), (336, 208),
(336, 209), (336, 211), (337, 191), (337, 193), (337, 194), (337, 195), (337, 196), (337, 198), (337, 199), (337, 200), (337, 201), (337, 202), (337, 203), (337, 204), (337, 205), (337, 206), (337, 207), (337, 208), (337, 209), (337, 211), (338, 191), (338, 198), (338, 199), (338, 200), (338, 201), (338, 202), (338, 203), (338, 204), (338, 205), (338, 206), (338, 207), (338, 208), (338, 209), (338, 210), (338, 212), (339, 191), (339, 193), (339, 194), (339, 195), (339, 196), (339, 197), (339, 198), (339, 199), (339, 200), (339, 201), (339, 202), (339, 203), (339, 204), (339, 205), (339, 206), (339, 207), (339, 208), (339, 209), (339, 210), (339, 212), (340, 191), (340, 193), (340, 194), (340, 195), (340, 196), (340, 197), (340, 198), (340, 199), (340, 200), (340, 201), (340, 202), (340, 203), (340, 204), (340, 205), (340, 206), (340, 207), (340, 208),
(340, 209), (340, 210), (340, 212), (341, 191), (341, 193), (341, 194), (341, 195), (341, 196), (341, 197), (341, 198), (341, 199), (341, 200), (341, 201), (341, 202), (341, 203), (341, 204), (341, 205), (341, 206), (341, 207), (341, 208), (341, 209), (341, 210), (341, 212), (342, 192), (342, 194), (342, 195), (342, 196), (342, 197), (342, 198), (342, 199), (342, 200), (342, 201), (342, 202), (342, 203), (342, 204), (342, 205), (342, 206), (342, 207), (342, 208), (342, 209), (342, 210), (342, 211), (342, 213), (343, 193), (343, 195), (343, 196), (343, 197), (343, 198), (343, 199), (343, 200), (343, 201), (343, 202), (343, 203), (343, 204), (343, 205), (343, 206), (343, 207), (343, 208), (343, 209), (343, 210), (343, 211), (343, 213), (344, 194), (344, 196), (344, 197), (344, 198), (344, 199), (344, 200), (344, 201), (344, 202), (344, 203), (344, 204),
(344, 205), (344, 206), (344, 207), (344, 208), (344, 209), (344, 210), (344, 211), (344, 213), (345, 195), (345, 197), (345, 198), (345, 199), (345, 200), (345, 201), (345, 202), (345, 203), (345, 204), (345, 205), (345, 206), (345, 207), (345, 208), (345, 209), (345, 210), (345, 211), (345, 212), (345, 214), (346, 195), (346, 197), (346, 198), (346, 199), (346, 200), (346, 201), (346, 202), (346, 203), (346, 204), (346, 205), (346, 206), (346, 207), (346, 208), (346, 209), (346, 210), (346, 211), (346, 212), (346, 214), (347, 196), (347, 198), (347, 199), (347, 200), (347, 201), (347, 202), (347, 203), (347, 204), (347, 205), (347, 206), (347, 207), (347, 208), (347, 209), (347, 210), (347, 211), (347, 212), (347, 214), (348, 196), (348, 198), (348, 199), (348, 200), (348, 201), (348, 202), (348, 203), (348, 204), (348, 205), (348, 206), (348, 207),
(348, 208), (348, 209), (348, 210), (348, 211), (348, 212), (348, 214), (349, 196), (349, 198), (349, 199), (349, 200), (349, 201), (349, 202), (349, 203), (349, 204), (349, 205), (349, 206), (349, 207), (349, 208), (349, 209), (349, 210), (349, 211), (349, 212), (349, 214), (350, 196), (350, 198), (350, 199), (350, 200), (350, 201), (350, 202), (350, 203), (350, 204), (350, 205), (350, 206), (350, 207), (350, 208), (350, 209), (350, 210), (350, 211), (350, 212), (350, 214), (351, 195), (351, 197), (351, 198), (351, 199), (351, 200), (351, 201), (351, 202), (351, 203), (351, 204), (351, 205), (351, 206), (351, 207), (351, 208), (351, 209), (351, 210), (351, 211), (351, 212), (351, 214), (352, 193), (352, 196), (352, 197), (352, 198), (352, 199), (352, 200), (352, 201), (352, 202), (352, 203), (352, 204), (352, 205), (352, 206), (352, 207), (352, 208),
(352, 209), (352, 210), (352, 211), (352, 213), (353, 192), (353, 195), (353, 196), (353, 197), (353, 198), (353, 199), (353, 200), (353, 201), (353, 202), (353, 203), (353, 204), (353, 205), (353, 206), (353, 207), (353, 208), (353, 209), (353, 210), (353, 211), (353, 213), (354, 191), (354, 194), (354, 195), (354, 196), (354, 197), (354, 198), (354, 199), (354, 200), (354, 201), (354, 202), (354, 203), (354, 204), (354, 205), (354, 206), (354, 207), (354, 208), (354, 209), (354, 210), (354, 211), (354, 213), (355, 190), (355, 192), (355, 193), (355, 194), (355, 195), (355, 196), (355, 197), (355, 198), (355, 199), (355, 200), (355, 201), (355, 202), (355, 203), (355, 204), (355, 205), (355, 206), (355, 207), (355, 208), (355, 209), (355, 210), (355, 212), (356, 190), (356, 192), (356, 193), (356, 194), (356, 195), (356, 196), (356, 197), (356, 198),
(356, 199), (356, 200), (356, 201), (356, 202), (356, 203), (356, 204), (356, 205), (356, 206), (356, 207), (356, 208), (356, 209), (357, 191), (357, 193), (357, 194), (357, 195), (357, 196), (357, 197), (357, 198), (357, 199), (357, 200), (357, 201), (357, 202), (357, 203), (357, 204), (357, 205), (357, 206), (357, 207), (357, 208), (357, 209), (357, 211), (358, 191), (358, 195), (358, 196), (358, 197), (358, 198), (358, 199), (358, 200), (358, 201), (358, 202), (358, 203), (358, 204), (358, 205), (358, 206), (358, 207), (358, 208), (358, 210), (359, 193), (359, 196), (359, 197), (359, 198), (359, 199), (359, 200), (359, 201), (359, 202), (359, 203), (359, 204), (359, 205), (359, 206), (359, 209), (360, 195), (360, 198), (360, 199), (360, 200), (360, 201), (360, 202), (360, 203), (360, 204), (360, 205), (360, 208), (361, 196), (361, 199), (361, 200),
(361, 201), (361, 202), (361, 206), (362, 198), (362, 203), (362, 204), (363, 198), (363, 199), (363, 200), (363, 202), )
coordinates_00FF9C = ((164, 100),
(164, 101), (164, 103), (165, 98), (165, 103), (166, 96), (166, 99), (166, 100), (166, 101), (166, 103), (167, 95), (167, 98), (167, 99), (167, 100), (167, 101), (167, 103), (168, 94), (168, 96), (168, 97), (168, 98), (168, 99), (168, 100), (168, 101), (168, 102), (168, 104), (169, 93), (169, 95), (169, 96), (169, 97), (169, 98), (169, 99), (169, 100), (169, 101), (169, 102), (169, 104), (170, 93), (170, 95), (170, 96), (170, 97), (170, 98), (170, 99), (170, 100), (170, 101), (170, 102), (170, 103), (170, 105), (171, 92), (171, 94), (171, 95), (171, 96), (171, 97), (171, 98), (171, 99), (171, 100), (171, 101), (171, 102), (171, 103), (171, 105), (172, 93), (172, 94), (172, 95), (172, 96), (172, 97), (172, 98), (172, 99), (172, 100), (172, 101), (172, 102), (172, 103), (172, 105), (173, 91), (173, 93), (173, 94),
(173, 95), (173, 96), (173, 97), (173, 98), (173, 99), (173, 100), (173, 101), (173, 102), (173, 103), (173, 104), (173, 106), (174, 91), (174, 93), (174, 94), (174, 95), (174, 96), (174, 97), (174, 98), (174, 99), (174, 100), (174, 101), (174, 102), (174, 103), (174, 104), (174, 106), (175, 90), (175, 92), (175, 93), (175, 94), (175, 95), (175, 96), (175, 97), (175, 98), (175, 99), (175, 100), (175, 101), (175, 102), (175, 103), (175, 104), (175, 106), (176, 90), (176, 92), (176, 93), (176, 94), (176, 95), (176, 96), (176, 97), (176, 98), (176, 99), (176, 100), (176, 101), (176, 102), (176, 103), (176, 104), (176, 106), (177, 90), (177, 92), (177, 93), (177, 94), (177, 95), (177, 96), (177, 97), (177, 98), (177, 99), (177, 100), (177, 101), (177, 102), (177, 103), (177, 104), (177, 106), (178, 90), (178, 92),
(178, 93), (178, 94), (178, 95), (178, 96), (178, 97), (178, 98), (178, 99), (178, 100), (178, 101), (178, 102), (178, 103), (178, 104), (178, 106), (179, 90), (179, 92), (179, 93), (179, 94), (179, 95), (179, 96), (179, 97), (179, 98), (179, 99), (179, 100), (179, 101), (179, 102), (179, 103), (179, 105), (180, 90), (180, 92), (180, 93), (180, 94), (180, 95), (180, 96), (180, 97), (180, 98), (180, 99), (180, 100), (180, 101), (180, 102), (180, 103), (180, 105), (181, 90), (181, 92), (181, 93), (181, 94), (181, 95), (181, 96), (181, 97), (181, 98), (181, 99), (181, 100), (181, 101), (181, 102), (181, 104), (182, 91), (182, 93), (182, 94), (182, 95), (182, 96), (182, 97), (182, 98), (182, 99), (182, 100), (182, 101), (182, 102), (182, 104), (183, 92), (183, 95), (183, 96), (183, 97), (183, 98), (183, 99),
(183, 100), (183, 101), (183, 102), (183, 103), (183, 104), (184, 93), (184, 96), (184, 97), (184, 98), (184, 99), (184, 100), (184, 101), (184, 103), (185, 95), (185, 97), (185, 98), (185, 99), (185, 100), (185, 101), (185, 103), (186, 96), (186, 98), (186, 99), (186, 100), (186, 102), (187, 97), (187, 99), (187, 100), (187, 102), (188, 98), (188, 101), (189, 99), (189, 101), (190, 99), (190, 100), (208, 100), (209, 99), (209, 100), (210, 99), (210, 101), (211, 98), (211, 101), (212, 97), (212, 99), (212, 100), (212, 102), (213, 96), (213, 98), (213, 99), (213, 100), (213, 102), (214, 95), (214, 97), (214, 98), (214, 99), (214, 100), (214, 101), (214, 103), (215, 93), (215, 96), (215, 97), (215, 98), (215, 99), (215, 100), (215, 101), (215, 103), (216, 92), (216, 95), (216, 96), (216, 97), (216, 98), (216, 99),
(216, 100), (216, 101), (216, 102), (216, 104), (217, 91), (217, 93), (217, 94), (217, 95), (217, 96), (217, 97), (217, 98), (217, 99), (217, 100), (217, 101), (217, 102), (217, 104), (218, 90), (218, 92), (218, 93), (218, 94), (218, 95), (218, 96), (218, 97), (218, 98), (218, 99), (218, 100), (218, 101), (218, 102), (218, 103), (218, 104), (218, 105), (219, 90), (219, 92), (219, 93), (219, 94), (219, 95), (219, 96), (219, 97), (219, 98), (219, 99), (219, 100), (219, 101), (219, 102), (219, 103), (219, 105), (220, 90), (220, 92), (220, 93), (220, 94), (220, 95), (220, 96), (220, 97), (220, 98), (220, 99), (220, 100), (220, 101), (220, 102), (220, 103), (220, 105), (221, 90), (221, 92), (221, 93), (221, 94), (221, 95), (221, 96), (221, 97), (221, 98), (221, 99), (221, 100), (221, 101), (221, 102), (221, 103),
(221, 104), (221, 106), (222, 90), (222, 92), (222, 93), (222, 94), (222, 95), (222, 96), (222, 97), (222, 98), (222, 99), (222, 100), (222, 101), (222, 102), (222, 103), (222, 104), (222, 106), (223, 90), (223, 92), (223, 93), (223, 94), (223, 95), (223, 96), (223, 97), (223, 98), (223, 99), (223, 100), (223, 101), (223, 102), (223, 103), (223, 104), (223, 106), (224, 90), (224, 92), (224, 93), (224, 94), (224, 95), (224, 96), (224, 97), (224, 98), (224, 99), (224, 100), (224, 101), (224, 102), (224, 103), (224, 104), (224, 106), (225, 91), (225, 93), (225, 94), (225, 95), (225, 96), (225, 97), (225, 98), (225, 99), (225, 100), (225, 101), (225, 102), (225, 103), (225, 104), (225, 106), (226, 91), (226, 93), (226, 94), (226, 95), (226, 96), (226, 97), (226, 98), (226, 99), (226, 100), (226, 101), (226, 102),
(226, 103), (226, 104), (226, 106), (227, 92), (227, 93), (227, 94), (227, 95), (227, 96), (227, 97), (227, 98), (227, 99), (227, 100), (227, 101), (227, 102), (227, 103), (227, 105), (228, 92), (228, 94), (228, 95), (228, 96), (228, 97), (228, 98), (228, 99), (228, 100), (228, 101), (228, 102), (228, 103), (228, 105), (229, 93), (229, 95), (229, 96), (229, 97), (229, 98), (229, 99), (229, 100), (229, 101), (229, 102), (229, 103), (229, 105), (230, 93), (230, 95), (230, 96), (230, 97), (230, 98), (230, 99), (230, 100), (230, 101), (230, 102), (230, 104), (231, 94), (231, 96), (231, 97), (231, 98), (231, 99), (231, 100), (231, 101), (231, 102), (231, 104), (232, 95), (232, 98), (232, 99), (232, 100), (232, 101), (232, 103), (233, 96), (233, 100), (233, 101), (233, 103), (234, 98), (234, 103), (235, 100), (235, 103),
)
coordinates_2700FF = ((191, 213),
(191, 214), (191, 215), (191, 216), (191, 217), (191, 219), (192, 208), (192, 209), (192, 211), (192, 212), (192, 219), (193, 208), (193, 217), (194, 208), (194, 210), (194, 211), (194, 212), (194, 213), (194, 214), (205, 208), (205, 210), (205, 211), (205, 212), (205, 213), (205, 215), (206, 208), (206, 216), (206, 217), (207, 209), (207, 211), (207, 212), (207, 219), (208, 213), (208, 214), (208, 215), (208, 216), (208, 217), (208, 219), )
coordinates_7F0009 = ((106, 180),
(106, 182), (107, 177), (107, 179), (107, 184), (107, 185), (107, 186), (108, 174), (108, 175), (108, 176), (108, 180), (108, 181), (108, 182), (108, 187), (108, 188), (108, 189), (108, 190), (108, 191), (108, 192), (109, 170), (109, 172), (109, 173), (109, 177), (109, 178), (109, 179), (109, 180), (109, 181), (109, 182), (109, 183), (109, 184), (109, 185), (109, 186), (109, 194), (110, 168), (110, 174), (110, 175), (110, 176), (110, 177), (110, 178), (110, 179), (110, 180), (110, 181), (110, 182), (110, 183), (110, 184), (110, 185), (110, 186), (110, 187), (110, 188), (110, 189), (110, 190), (110, 191), (110, 192), (110, 196), (111, 167), (111, 170), (111, 171), (111, 172), (111, 173), (111, 174), (111, 175), (111, 176), (111, 177), (111, 178), (111, 179), (111, 180), (111, 181), (111, 182), (111, 183), (111, 184), (111, 185), (111, 186), (111, 187),
(111, 188), (111, 189), (111, 190), (111, 191), (111, 192), (111, 193), (111, 194), (111, 198), (112, 166), (112, 168), (112, 169), (112, 170), (112, 171), (112, 172), (112, 173), (112, 174), (112, 175), (112, 176), (112, 177), (112, 178), (112, 179), (112, 180), (112, 181), (112, 182), (112, 183), (112, 184), (112, 185), (112, 186), (112, 187), (112, 188), (112, 189), (112, 190), (112, 191), (112, 192), (112, 193), (112, 194), (112, 195), (112, 196), (112, 197), (112, 200), (113, 165), (113, 167), (113, 168), (113, 169), (113, 170), (113, 171), (113, 172), (113, 173), (113, 174), (113, 175), (113, 176), (113, 177), (113, 178), (113, 179), (113, 180), (113, 181), (113, 182), (113, 183), (113, 184), (113, 185), (113, 186), (113, 187), (113, 188), (113, 189), (113, 190), (113, 191), (113, 192), (113, 193), (113, 194), (113, 195), (113, 196), (113, 197),
(113, 198), (113, 199), (113, 202), (114, 164), (114, 166), (114, 167), (114, 168), (114, 169), (114, 170), (114, 171), (114, 172), (114, 173), (114, 174), (114, 175), (114, 176), (114, 177), (114, 178), (114, 179), (114, 180), (114, 181), (114, 182), (114, 183), (114, 184), (114, 185), (114, 186), (114, 187), (114, 188), (114, 189), (114, 190), (114, 191), (114, 192), (114, 193), (114, 194), (114, 195), (114, 196), (114, 197), (114, 198), (114, 199), (114, 200), (114, 201), (114, 204), (115, 163), (115, 165), (115, 166), (115, 167), (115, 168), (115, 169), (115, 170), (115, 171), (115, 172), (115, 173), (115, 174), (115, 175), (115, 176), (115, 177), (115, 178), (115, 179), (115, 180), (115, 181), (115, 182), (115, 183), (115, 184), (115, 185), (115, 186), (115, 187), (115, 188), (115, 189), (115, 190), (115, 191), (115, 192), (115, 193), (115, 194),
(115, 195), (115, 196), (115, 197), (115, 198), (115, 199), (115, 200), (115, 201), (115, 202), (115, 203), (115, 206), (116, 162), (116, 164), (116, 165), (116, 166), (116, 167), (116, 168), (116, 169), (116, 170), (116, 171), (116, 172), (116, 173), (116, 174), (116, 175), (116, 176), (116, 177), (116, 178), (116, 179), (116, 180), (116, 181), (116, 182), (116, 183), (116, 184), (116, 185), (116, 186), (116, 187), (116, 188), (116, 189), (116, 190), (116, 191), (116, 192), (116, 193), (116, 194), (116, 195), (116, 196), (116, 197), (116, 198), (116, 199), (116, 200), (116, 201), (116, 202), (116, 203), (116, 204), (116, 207), (117, 162), (117, 164), (117, 165), (117, 166), (117, 167), (117, 168), (117, 169), (117, 170), (117, 171), (117, 172), (117, 173), (117, 174), (117, 175), (117, 176), (117, 177), (117, 178), (117, 179), (117, 180), (117, 181),
(117, 182), (117, 183), (117, 184), (117, 185), (117, 186), (117, 187), (117, 188), (117, 189), (117, 190), (117, 191), (117, 192), (117, 193), (117, 194), (117, 195), (117, 196), (117, 197), (117, 198), (117, 199), (117, 200), (117, 201), (117, 202), (117, 203), (117, 204), (117, 205), (117, 206), (117, 208), (118, 161), (118, 163), (118, 164), (118, 165), (118, 166), (118, 167), (118, 168), (118, 169), (118, 170), (118, 171), (118, 172), (118, 173), (118, 174), (118, 175), (118, 176), (118, 177), (118, 178), (118, 179), (118, 180), (118, 181), (118, 182), (118, 183), (118, 184), (118, 185), (118, 186), (118, 187), (118, 188), (118, 189), (118, 190), (118, 191), (118, 192), (118, 193), (118, 194), (118, 195), (118, 196), (118, 197), (118, 198), (118, 199), (118, 200), (118, 201), (118, 202), (118, 203), (118, 204), (118, 205), (118, 206), (118, 207),
(118, 209), (119, 161), (119, 163), (119, 164), (119, 165), (119, 166), (119, 167), (119, 168), (119, 169), (119, 170), (119, 171), (119, 172), (119, 173), (119, 174), (119, 175), (119, 176), (119, 177), (119, 178), (119, 179), (119, 180), (119, 181), (119, 182), (119, 183), (119, 184), (119, 185), (119, 186), (119, 187), (119, 188), (119, 189), (119, 190), (119, 191), (119, 192), (119, 193), (119, 194), (119, 195), (119, 196), (119, 197), (119, 198), (119, 199), (119, 200), (119, 201), (119, 202), (119, 203), (119, 204), (119, 205), (119, 206), (119, 207), (119, 209), (120, 160), (120, 162), (120, 163), (120, 164), (120, 165), (120, 166), (120, 167), (120, 168), (120, 169), (120, 170), (120, 171), (120, 172), (120, 173), (120, 174), (120, 175), (120, 176), (120, 177), (120, 178), (120, 179), (120, 180), (120, 181), (120, 182), (120, 183), (120, 184),
(120, 185), (120, 186), (120, 187), (120, 188), (120, 189), (120, 190), (120, 191), (120, 192), (120, 193), (120, 194), (120, 195), (120, 196), (120, 197), (120, 198), (120, 199), (120, 200), (120, 201), (120, 202), (120, 203), (120, 204), (120, 205), (120, 206), (120, 207), (120, 208), (120, 210), (121, 160), (121, 162), (121, 163), (121, 164), (121, 165), (121, 166), (121, 167), (121, 168), (121, 169), (121, 170), (121, 171), (121, 172), (121, 173), (121, 174), (121, 175), (121, 176), (121, 177), (121, 178), (121, 179), (121, 180), (121, 181), (121, 182), (121, 183), (121, 184), (121, 185), (121, 186), (121, 187), (121, 188), (121, 189), (121, 190), (121, 191), (121, 192), (121, 193), (121, 194), (121, 195), (121, 196), (121, 197), (121, 198), (121, 199), (121, 200), (121, 201), (121, 202), (121, 203), (121, 204), (121, 205), (121, 206), (121, 207),
(121, 208), (121, 209), (121, 210), (122, 160), (122, 162), (122, 163), (122, 164), (122, 165), (122, 166), (122, 167), (122, 168), (122, 169), (122, 170), (122, 171), (122, 172), (122, 173), (122, 174), (122, 175), (122, 176), (122, 177), (122, 178), (122, 179), (122, 180), (122, 181), (122, 182), (122, 183), (122, 184), (122, 185), (122, 186), (122, 187), (122, 188), (122, 189), (122, 190), (122, 191), (122, 192), (122, 193), (122, 194), (122, 195), (122, 196), (122, 197), (122, 198), (122, 199), (122, 200), (122, 201), (122, 202), (122, 203), (122, 204), (122, 205), (122, 206), (122, 207), (122, 208), (122, 209), (122, 211), (123, 159), (123, 161), (123, 162), (123, 163), (123, 164), (123, 165), (123, 166), (123, 167), (123, 168), (123, 169), (123, 170), (123, 171), (123, 172), (123, 173), (123, 174), (123, 175), (123, 176), (123, 177), (123, 178),
(123, 179), (123, 180), (123, 181), (123, 182), (123, 183), (123, 184), (123, 185), (123, 186), (123, 187), (123, 188), (123, 189), (123, 190), (123, 191), (123, 192), (123, 193), (123, 194), (123, 195), (123, 196), (123, 197), (123, 198), (123, 199), (123, 200), (123, 201), (123, 202), (123, 203), (123, 204), (123, 205), (123, 206), (123, 207), (123, 208), (123, 209), (123, 210), (123, 212), (124, 159), (124, 161), (124, 162), (124, 163), (124, 164), (124, 165), (124, 166), (124, 167), (124, 168), (124, 169), (124, 170), (124, 171), (124, 172), (124, 173), (124, 174), (124, 175), (124, 176), (124, 177), (124, 178), (124, 179), (124, 180), (124, 181), (124, 182), (124, 183), (124, 184), (124, 185), (124, 186), (124, 187), (124, 188), (124, 189), (124, 190), (124, 191), (124, 192), (124, 193), (124, 194), (124, 195), (124, 196), (124, 197), (124, 198),
(124, 199), (124, 200), (124, 201), (124, 202), (124, 203), (124, 204), (124, 205), (124, 206), (124, 207), (124, 208), (124, 209), (124, 210), (124, 212), (125, 159), (125, 161), (125, 162), (125, 163), (125, 164), (125, 165), (125, 166), (125, 167), (125, 168), (125, 169), (125, 170), (125, 171), (125, 172), (125, 173), (125, 174), (125, 175), (125, 176), (125, 177), (125, 178), (125, 179), (125, 180), (125, 181), (125, 182), (125, 183), (125, 184), (125, 185), (125, 186), (125, 187), (125, 188), (125, 189), (125, 190), (125, 191), (125, 192), (125, 193), (125, 194), (125, 195), (125, 196), (125, 197), (125, 198), (125, 199), (125, 200), (125, 201), (125, 202), (125, 203), (125, 204), (125, 205), (125, 206), (125, 207), (125, 208), (125, 209), (125, 210), (125, 211), (125, 213), (126, 159), (126, 161), (126, 162), (126, 163), (126, 164), (126, 165),
(126, 166), (126, 167), (126, 168), (126, 169), (126, 170), (126, 171), (126, 172), (126, 173), (126, 174), (126, 175), (126, 176), (126, 177), (126, 178), (126, 179), (126, 180), (126, 181), (126, 182), (126, 183), (126, 184), (126, 185), (126, 186), (126, 187), (126, 188), (126, 189), (126, 190), (126, 191), (126, 192), (126, 193), (126, 194), (126, 195), (126, 196), (126, 197), (126, 198), (126, 199), (126, 200), (126, 201), (126, 202), (126, 203), (126, 204), (126, 205), (126, 206), (126, 207), (126, 208), (126, 209), (126, 210), (126, 211), (126, 212), (126, 214), (127, 159), (127, 161), (127, 162), (127, 163), (127, 164), (127, 165), (127, 166), (127, 167), (127, 168), (127, 169), (127, 170), (127, 171), (127, 172), (127, 173), (127, 174), (127, 175), (127, 176), (127, 177), (127, 178), (127, 179), (127, 180), (127, 181), (127, 182), (127, 183),
(127, 184), (127, 185), (127, 186), (127, 187), (127, 188), (127, 189), (127, 190), (127, 191), (127, 192), (127, 193), (127, 194), (127, 195), (127, 196), (127, 197), (127, 198), (127, 199), (127, 200), (127, 201), (127, 202), (127, 203), (127, 204), (127, 205), (127, 206), (127, 207), (127, 208), (127, 209), (127, 210), (127, 211), (127, 212), (127, 213), (127, 215), (128, 159), (128, 161), (128, 162), (128, 163), (128, 164), (128, 165), (128, 166), (128, 167), (128, 168), (128, 169), (128, 170), (128, 171), (128, 172), (128, 173), (128, 174), (128, 175), (128, 176), (128, 177), (128, 178), (128, 179), (128, 180), (128, 181), (128, 182), (128, 183), (128, 184), (128, 185), (128, 186), (128, 187), (128, 188), (128, 189), (128, 190), (128, 191), (128, 192), (128, 193), (128, 194), (128, 195), (128, 196), (128, 197), (128, 198), (128, 199), (128, 200),
(128, 201), (128, 202), (128, 203), (128, 204), (128, 205), (128, 206), (128, 207), (128, 208), (128, 209), (128, 210), (128, 211), (128, 212), (128, 213), (128, 214), (128, 216), (129, 159), (129, 161), (129, 162), (129, 163), (129, 164), (129, 165), (129, 166), (129, 167), (129, 168), (129, 169), (129, 170), (129, 171), (129, 172), (129, 173), (129, 174), (129, 175), (129, 176), (129, 177), (129, 178), (129, 179), (129, 180), (129, 181), (129, 182), (129, 183), (129, 184), (129, 185), (129, 186), (129, 187), (129, 188), (129, 189), (129, 190), (129, 191), (129, 192), (129, 193), (129, 194), (129, 195), (129, 196), (129, 197), (129, 198), (129, 199), (129, 200), (129, 201), (129, 202), (129, 203), (129, 204), (129, 205), (129, 206), (129, 207), (129, 208), (129, 209), (129, 210), (129, 211), (129, 212), (129, 213), (129, 214), (129, 215), (129, 218),
(129, 220), (130, 159), (130, 161), (130, 162), (130, 163), (130, 164), (130, 165), (130, 166), (130, 167), (130, 168), (130, 169), (130, 170), (130, 171), (130, 172), (130, 173), (130, 174), (130, 175), (130, 176), (130, 177), (130, 178), (130, 179), (130, 180), (130, 181), (130, 182), (130, 183), (130, 184), (130, 185), (130, 186), (130, 187), (130, 188), (130, 189), (130, 190), (130, 191), (130, 192), (130, 193), (130, 194), (130, 195), (130, 196), (130, 197), (130, 198), (130, 199), (130, 200), (130, 201), (130, 202), (130, 203), (130, 204), (130, 205), (130, 206), (130, 207), (130, 208), (130, 209), (130, 210), (130, 211), (130, 212), (130, 213), (130, 214), (130, 215), (130, 216), (130, 220), (131, 159), (131, 161), (131, 162), (131, 163), (131, 164), (131, 165), (131, 166), (131, 167), (131, 168), (131, 169), (131, 170), (131, 171), (131, 172),
(131, 173), (131, 174), (131, 175), (131, 176), (131, 177), (131, 178), (131, 179), (131, 180), (131, 181), (131, 182), (131, 183), (131, 184), (131, 185), (131, 186), (131, 187), (131, 188), (131, 189), (131, 190), (131, 191), (131, 192), (131, 193), (131, 194), (131, 195), (131, 196), (131, 197), (131, 198), (131, 199), (131, 200), (131, 201), (131, 202), (131, 203), (131, 204), (131, 205), (131, 206), (131, 207), (131, 208), (131, 209), (131, 210), (131, 211), (131, 212), (131, 213), (131, 214), (131, 215), (131, 216), (131, 217), (131, 218), (131, 220), (132, 159), (132, 161), (132, 162), (132, 163), (132, 164), (132, 165), (132, 166), (132, 167), (132, 168), (132, 169), (132, 170), (132, 171), (132, 172), (132, 173), (132, 174), (132, 175), (132, 176), (132, 177), (132, 178), (132, 179), (132, 180), (132, 181), (132, 182), (132, 183), (132, 184),
(132, 185), (132, 186), (132, 187), (132, 188), (132, 189), (132, 190), (132, 191), (132, 192), (132, 193), (132, 194), (132, 195), (132, 196), (132, 197), (132, 198), (132, 199), (132, 200), (132, 201), (132, 202), (132, 203), (132, 204), (132, 205), (132, 206), (132, 207), (132, 208), (132, 209), (132, 210), (132, 211), (132, 212), (132, 213), (132, 214), (132, 215), (132, 216), (132, 217), (132, 218), (132, 219), (132, 221), (133, 159), (133, 161), (133, 162), (133, 163), (133, 164), (133, 165), (133, 166), (133, 167), (133, 168), (133, 169), (133, 170), (133, 171), (133, 172), (133, 173), (133, 174), (133, 175), (133, 176), (133, 177), (133, 178), (133, 179), (133, 180), (133, 181), (133, 182), (133, 183), (133, 184), (133, 185), (133, 186), (133, 187), (133, 188), (133, 189), (133, 190), (133, 191), (133, 192), (133, 193), (133, 194), (133, 195),
(133, 196), (133, 197), (133, 198), (133, 199), (133, 200), (133, 201), (133, 202), (133, 203), (133, 204), (133, 205), (133, 206), (133, 207), (133, 208), (133, 209), (133, 210), (133, 211), (133, 212), (133, 213), (133, 214), (133, 215), (133, 216), (133, 217), (133, 218), (133, 219), (133, 220), (133, 222), (134, 160), (134, 162), (134, 163), (134, 164), (134, 165), (134, 166), (134, 167), (134, 168), (134, 169), (134, 170), (134, 171), (134, 172), (134, 173), (134, 174), (134, 175), (134, 176), (134, 177), (134, 178), (134, 179), (134, 180), (134, 181), (134, 182), (134, 183), (134, 184), (134, 185), (134, 186), (134, 187), (134, 188), (134, 189), (134, 190), (134, 191), (134, 192), (134, 193), (134, 194), (134, 195), (134, 196), (134, 197), (134, 198), (134, 199), (134, 200), (134, 201), (134, 202), (134, 203), (134, 204), (134, 205), (134, 206),
(134, 207), (134, 208), (134, 209), (134, 210), (134, 211), (134, 212), (134, 213), (134, 214), (134, 215), (134, 216), (134, 217), (134, 218), (134, 219), (134, 220), (134, 221), (134, 223), (135, 160), (135, 162), (135, 163), (135, 164), (135, 165), (135, 166), (135, 167), (135, 168), (135, 169), (135, 170), (135, 171), (135, 172), (135, 173), (135, 174), (135, 175), (135, 176), (135, 177), (135, 178), (135, 179), (135, 180), (135, 181), (135, 182), (135, 183), (135, 184), (135, 185), (135, 186), (135, 187), (135, 188), (135, 189), (135, 190), (135, 191), (135, 192), (135, 193), (135, 194), (135, 195), (135, 196), (135, 197), (135, 198), (135, 199), (135, 200), (135, 201), (135, 202), (135, 203), (135, 204), (135, 205), (135, 206), (135, 207), (135, 208), (135, 209), (135, 210), (135, 211), (135, 212), (135, 213), (135, 214), (135, 215), (135, 216),
(135, 217), (135, 218), (135, 219), (135, 220), (135, 221), (135, 222), (135, 224), (136, 160), (136, 162), (136, 163), (136, 164), (136, 165), (136, 166), (136, 167), (136, 168), (136, 169), (136, 170), (136, 171), (136, 172), (136, 173), (136, 174), (136, 175), (136, 176), (136, 177), (136, 178), (136, 179), (136, 180), (136, 181), (136, 182), (136, 183), (136, 184), (136, 185), (136, 186), (136, 187), (136, 188), (136, 189), (136, 190), (136, 191), (136, 192), (136, 193), (136, 194), (136, 195), (136, 196), (136, 197), (136, 198), (136, 199), (136, 200), (136, 201), (136, 202), (136, 203), (136, 204), (136, 205), (136, 206), (136, 207), (136, 208), (136, 209), (136, 210), (136, 211), (136, 212), (136, 213), (136, 214), (136, 215), (136, 216), (136, 217), (136, 218), (136, 219), (136, 220), (136, 221), (136, 222), (136, 223), (136, 226), (137, 161),
(137, 163), (137, 164), (137, 165), (137, 166), (137, 167), (137, 168), (137, 169), (137, 170), (137, 171), (137, 172), (137, 173), (137, 174), (137, 175), (137, 176), (137, 177), (137, 178), (137, 179), (137, 180), (137, 181), (137, 182), (137, 183), (137, 184), (137, 185), (137, 186), (137, 187), (137, 188), (137, 189), (137, 190), (137, 191), (137, 192), (137, 193), (137, 194), (137, 195), (137, 196), (137, 197), (137, 198), (137, 199), (137, 200), (137, 201), (137, 202), (137, 203), (137, 204), (137, 205), (137, 206), (137, 207), (137, 208), (137, 209), (137, 210), (137, 211), (137, 212), (137, 213), (137, 214), (137, 215), (137, 216), (137, 217), (137, 218), (137, 219), (137, 220), (137, 221), (137, 222), (137, 223), (137, 224), (137, 227), (138, 162), (138, 164), (138, 165), (138, 166), (138, 167), (138, 168), (138, 169), (138, 170), (138, 171),
(138, 172), (138, 173), (138, 174), (138, 175), (138, 176), (138, 177), (138, 178), (138, 179), (138, 180), (138, 181), (138, 182), (138, 183), (138, 184), (138, 185), (138, 186), (138, 187), (138, 188), (138, 189), (138, 190), (138, 191), (138, 192), (138, 193), (138, 194), (138, 195), (138, 196), (138, 197), (138, 198), (138, 199), (138, 200), (138, 201), (138, 202), (138, 203), (138, 204), (138, 205), (138, 206), (138, 207), (138, 208), (138, 209), (138, 210), (138, 211), (138, 212), (138, 213), (138, 214), (138, 215), (138, 216), (138, 217), (138, 218), (138, 219), (138, 220), (138, 221), (138, 222), (138, 223), (138, 224), (138, 225), (138, 227), (139, 163), (139, 166), (139, 167), (139, 168), (139, 169), (139, 170), (139, 171), (139, 172), (139, 173), (139, 174), (139, 175), (139, 176), (139, 177), (139, 178), (139, 179), (139, 180), (139, 181),
(139, 182), (139, 183), (139, 184), (139, 185), (139, 186), (139, 187), (139, 188), (139, 189), (139, 190), (139, 191), (139, 192), (139, 193), (139, 194), (139, 195), (139, 196), (139, 197), (139, 198), (139, 199), (139, 200), (139, 201), (139, 202), (139, 203), (139, 204), (139, 205), (139, 206), (139, 207), (139, 208), (139, 209), (139, 210), (139, 211), (139, 212), (139, 213), (139, 214), (139, 215), (139, 216), (139, 217), (139, 218), (139, 219), (139, 220), (139, 221), (139, 222), (139, 223), (139, 224), (139, 225), (139, 226), (139, 228), (140, 164), (140, 168), (140, 169), (140, 170), (140, 171), (140, 172), (140, 173), (140, 174), (140, 175), (140, 176), (140, 177), (140, 178), (140, 179), (140, 180), (140, 181), (140, 182), (140, 183), (140, 184), (140, 185), (140, 186), (140, 187), (140, 188), (140, 189), (140, 190), (140, 191), (140, 192),
(140, 193), (140, 194), (140, 195), (140, 196), (140, 197), (140, 198), (140, 199), (140, 200), (140, 201), (140, 202), (140, 203), (140, 204), (140, 205), (140, 206), (140, 207), (140, 208), (140, 209), (140, 210), (140, 211), (140, 212), (140, 213), (140, 214), (140, 215), (140, 216), (140, 217), (140, 218), (140, 219), (140, 220), (140, 221), (140, 222), (140, 223), (140, 224), (140, 225), (140, 226), (140, 228), (141, 166), (141, 170), (141, 171), (141, 172), (141, 173), (141, 174), (141, 175), (141, 176), (141, 177), (141, 178), (141, 179), (141, 180), (141, 181), (141, 182), (141, 183), (141, 184), (141, 185), (141, 186), (141, 187), (141, 188), (141, 189), (141, 190), (141, 191), (141, 192), (141, 193), (141, 194), (141, 195), (141, 196), (141, 197), (141, 198), (141, 199), (141, 200), (141, 201), (141, 202), (141, 203), (141, 204), (141, 205),
(141, 206), (141, 207), (141, 208), (141, 209), (141, 210), (141, 211), (141, 212), (141, 213), (141, 214), (141, 215), (141, 216), (141, 217), (141, 218), (141, 219), (141, 220), (141, 221), (141, 222), (141, 223), (141, 224), (141, 225), (141, 226), (141, 228), (142, 168), (142, 172), (142, 173), (142, 174), (142, 175), (142, 176), (142, 177), (142, 178), (142, 179), (142, 180), (142, 181), (142, 182), (142, 183), (142, 184), (142, 185), (142, 186), (142, 187), (142, 188), (142, 189), (142, 190), (142, 191), (142, 192), (142, 193), (142, 194), (142, 195), (142, 196), (142, 197), (142, 198), (142, 199), (142, 200), (142, 201), (142, 202), (142, 203), (142, 204), (142, 205), (142, 206), (142, 207), (142, 208), (142, 209), (142, 210), (142, 211), (142, 212), (142, 213), (142, 214), (142, 215), (142, 216), (142, 217), (142, 218), (142, 219), (142, 220),
(142, 221), (142, 222), (142, 223), (142, 224), (142, 225), (142, 226), (142, 228), (143, 170), (143, 173), (143, 174), (143, 175), (143, 176), (143, 177), (143, 178), (143, 179), (143, 180), (143, 181), (143, 182), (143, 183), (143, 184), (143, 185), (143, 186), (143, 187), (143, 188), (143, 189), (143, 190), (143, 191), (143, 192), (143, 193), (143, 194), (143, 195), (143, 196), (143, 197), (143, 198), (143, 199), (143, 200), (143, 201), (143, 202), (143, 203), (143, 204), (143, 205), (143, 206), (143, 207), (143, 208), (143, 209), (143, 210), (143, 211), (143, 212), (143, 213), (143, 214), (143, 215), (143, 216), (143, 217), (143, 218), (143, 219), (143, 220), (143, 221), (143, 222), (143, 223), (143, 224), (143, 225), (143, 226), (143, 228), (144, 172), (144, 174), (144, 175), (144, 176), (144, 177), (144, 178), (144, 179), (144, 180), (144, 181),
(144, 182), (144, 183), (144, 184), (144, 185), (144, 186), (144, 187), (144, 188), (144, 189), (144, 190), (144, 191), (144, 192), (144, 193), (144, 194), (144, 195), (144, 196), (144, 197), (144, 198), (144, 199), (144, 200), (144, 201), (144, 202), (144, 203), (144, 204), (144, 205), (144, 206), (144, 207), (144, 208), (144, 209), (144, 210), (144, 211), (144, 212), (144, 213), (144, 214), (144, 215), (144, 216), (144, 217), (144, 218), (144, 219), (144, 220), (144, 221), (144, 222), (144, 223), (144, 224), (144, 225), (144, 226), (144, 228), (145, 173), (145, 175), (145, 176), (145, 177), (145, 178), (145, 179), (145, 180), (145, 181), (145, 182), (145, 183), (145, 184), (145, 185), (145, 186), (145, 187), (145, 188), (145, 189), (145, 190), (145, 191), (145, 192), (145, 193), (145, 194), (145, 195), (145, 196), (145, 197), (145, 198), (145, 199),
(145, 200), (145, 201), (145, 202), (145, 203), (145, 204), (145, 205), (145, 206), (145, 207), (145, 208), (145, 209), (145, 210), (145, 211), (145, 212), (145, 213), (145, 214), (145, 215), (145, 216), (145, 217), (145, 218), (145, 219), (145, 220), (145, 221), (145, 222), (145, 223), (145, 224), (145, 225), (145, 226), (145, 228), (146, 174), (146, 176), (146, 177), (146, 178), (146, 179), (146, 180), (146, 181), (146, 182), (146, 183), (146, 184), (146, 185), (146, 186), (146, 187), (146, 188), (146, 189), (146, 190), (146, 191), (146, 192), (146, 193), (146, 194), (146, 195), (146, 196), (146, 197), (146, 198), (146, 199), (146, 200), (146, 201), (146, 202), (146, 203), (146, 204), (146, 205), (146, 206), (146, 207), (146, 208), (146, 209), (146, 210), (146, 211), (146, 212), (146, 213), (146, 214), (146, 215), (146, 216), (146, 217), (146, 218),
(146, 219), (146, 220), (146, 221), (146, 222), (146, 223), (146, 224), (146, 225), (146, 226), (146, 228), (147, 174), (147, 176), (147, 177), (147, 178), (147, 179), (147, 180), (147, 181), (147, 182), (147, 183), (147, 184), (147, 185), (147, 186), (147, 187), (147, 188), (147, 189), (147, 190), (147, 191), (147, 192), (147, 193), (147, 194), (147, 195), (147, 196), (147, 197), (147, 198), (147, 199), (147, 200), (147, 201), (147, 202), (147, 203), (147, 204), (147, 205), (147, 206), (147, 207), (147, 208), (147, 209), (147, 210), (147, 211), (147, 212), (147, 213), (147, 214), (147, 215), (147, 216), (147, 217), (147, 218), (147, 219), (147, 220), (147, 221), (147, 222), (147, 223), (147, 224), (147, 225), (147, 226), (147, 227), (147, 229), (148, 175), (148, 177), (148, 178), (148, 179), (148, 180), (148, 181), (148, 182), (148, 183), (148, 184),
(148, 185), (148, 186), (148, 187), (148, 188), (148, 189), (148, 190), (148, 191), (148, 192), (148, 193), (148, 194), (148, 195), (148, 196), (148, 197), (148, 198), (148, 199), (148, 200), (148, 201), (148, 202), (148, 203), (148, 204), (148, 205), (148, 206), (148, 207), (148, 208), (148, 209), (148, 210), (148, 211), (148, 212), (148, 213), (148, 214), (148, 215), (148, 216), (148, 217), (148, 218), (148, 219), (148, 220), (148, 221), (148, 222), (148, 223), (148, 224), (148, 225), (148, 226), (148, 227), (148, 229), (149, 176), (149, 178), (149, 179), (149, 180), (149, 181), (149, 182), (149, 183), (149, 184), (149, 185), (149, 186), (149, 187), (149, 188), (149, 189), (149, 190), (149, 191), (149, 192), (149, 193), (149, 194), (149, 195), (149, 196), (149, 197), (149, 198), (149, 199), (149, 200), (149, 201), (149, 202), (149, 203), (149, 204),
(149, 205), (149, 206), (149, 207), (149, 208), (149, 209), (149, 210), (149, 211), (149, 212), (149, 213), (149, 214), (149, 215), (149, 216), (149, 217), (149, 218), (149, 219), (149, 220), (149, 221), (149, 222), (149, 223), (149, 224), (149, 225), (149, 226), (149, 227), (149, 228), (149, 230), (150, 176), (150, 178), (150, 179), (150, 180), (150, 181), (150, 182), (150, 183), (150, 184), (150, 185), (150, 186), (150, 187), (150, 188), (150, 189), (150, 190), (150, 191), (150, 192), (150, 193), (150, 194), (150, 195), (150, 196), (150, 197), (150, 198), (150, 199), (150, 200), (150, 201), (150, 202), (150, 203), (150, 204), (150, 205), (150, 206), (150, 207), (150, 208), (150, 209), (150, 210), (150, 211), (150, 212), (150, 213), (150, 214), (150, 215), (150, 216), (150, 217), (150, 218), (150, 219), (150, 220), (150, 221), (150, 222), (150, 223),
(150, 224), (150, 225), (150, 226), (150, 227), (150, 228), (150, 230), (151, 177), (151, 179), (151, 180), (151, 181), (151, 182), (151, 183), (151, 184), (151, 185), (151, 186), (151, 187), (151, 188), (151, 189), (151, 190), (151, 191), (151, 192), (151, 193), (151, 194), (151, 195), (151, 196), (151, 197), (151, 198), (151, 199), (151, 200), (151, 201), (151, 202), (151, 203), (151, 204), (151, 205), (151, 206), (151, 207), (151, 208), (151, 209), (151, 210), (151, 211), (151, 212), (151, 213), (151, 214), (151, 215), (151, 216), (151, 217), (151, 218), (151, 219), (151, 220), (151, 221), (151, 222), (151, 223), (151, 224), (151, 225), (151, 226), (151, 227), (151, 228), (151, 230), (152, 178), (152, 180), (152, 181), (152, 182), (152, 183), (152, 184), (152, 185), (152, 186), (152, 187), (152, 188), (152, 189), (152, 190), (152, 191), (152, 192),
(152, 193), (152, 194), (152, 195), (152, 196), (152, 197), (152, 198), (152, 199), (152, 200), (152, 201), (152, 202), (152, 203), (152, 204), (152, 205), (152, 206), (152, 207), (152, 208), (152, 209), (152, 210), (152, 211), (152, 212), (152, 213), (152, 214), (152, 215), (152, 216), (152, 217), (152, 218), (152, 219), (152, 220), (152, 221), (152, 222), (152, 223), (152, 224), (152, 225), (152, 226), (152, 227), (152, 228), (152, 230), (153, 181), (153, 182), (153, 183), (153, 184), (153, 185), (153, 186), (153, 187), (153, 188), (153, 189), (153, 190), (153, 191), (153, 192), (153, 193), (153, 194), (153, 195), (153, 196), (153, 197), (153, 198), (153, 199), (153, 200), (153, 201), (153, 202), (153, 203), (153, 204), (153, 205), (153, 206), (153, 207), (153, 208), (153, 209), (153, 210), (153, 211), (153, 212), (153, 213), (153, 214), (153, 215),
(153, 216), (153, 217), (153, 218), (153, 219), (153, 220), (153, 221), (153, 222), (153, 223), (153, 224), (153, 225), (153, 226), (153, 227), (153, 228), (153, 230), (154, 179), (154, 181), (154, 182), (154, 183), (154, 184), (154, 185), (154, 186), (154, 187), (154, 188), (154, 189), (154, 190), (154, 191), (154, 192), (154, 193), (154, 194), (154, 195), (154, 196), (154, 197), (154, 198), (154, 199), (154, 200), (154, 201), (154, 202), (154, 203), (154, 204), (154, 205), (154, 206), (154, 207), (154, 208), (154, 209), (154, 210), (154, 211), (154, 212), (154, 213), (154, 214), (154, 215), (154, 216), (154, 217), (154, 218), (154, 219), (154, 220), (154, 221), (154, 222), (154, 223), (154, 224), (154, 225), (154, 226), (154, 227), (154, 228), (154, 230), (155, 180), (155, 183), (155, 184), (155, 185), (155, 186), (155, 187), (155, 188), (155, 189),
(155, 190), (155, 191), (155, 192), (155, 193), (155, 194), (155, 195), (155, 196), (155, 197), (155, 198), (155, 199), (155, 200), (155, 201), (155, 202), (155, 203), (155, 204), (155, 205), (155, 206), (155, 207), (155, 208), (155, 209), (155, 210), (155, 211), (155, 212), (155, 213), (155, 214), (155, 215), (155, 216), (155, 217), (155, 218), (155, 219), (155, 220), (155, 221), (155, 222), (155, 223), (155, 224), (155, 225), (155, 226), (155, 227), (155, 228), (155, 230), (156, 181), (156, 184), (156, 185), (156, 186), (156, 187), (156, 188), (156, 189), (156, 190), (156, 191), (156, 192), (156, 193), (156, 194), (156, 195), (156, 196), (156, 197), (156, 198), (156, 199), (156, 200), (156, 201), (156, 202), (156, 203), (156, 204), (156, 205), (156, 206), (156, 207), (156, 208), (156, 209), (156, 210), (156, 211), (156, 212), (156, 213), (156, 214),
(156, 215), (156, 216), (156, 217), (156, 218), (156, 219), (156, 220), (156, 221), (156, 222), (156, 223), (156, 224), (156, 225), (156, 226), (156, 227), (156, 229), (157, 182), (157, 183), (157, 186), (157, 187), (157, 188), (157, 189), (157, 190), (157, 191), (157, 192), (157, 193), (157, 194), (157, 195), (157, 196), (157, 197), (157, 198), (157, 199), (157, 200), (157, 201), (157, 202), (157, 203), (157, 204), (157, 205), (157, 206), (157, 207), (157, 208), (157, 209), (157, 210), (157, 211), (157, 212), (157, 213), (157, 214), (157, 215), (157, 216), (157, 217), (157, 218), (157, 219), (157, 220), (157, 221), (157, 222), (157, 223), (157, 224), (157, 225), (157, 226), (157, 227), (157, 229), (158, 184), (158, 189), (158, 190), (158, 191), (158, 192), (158, 193), (158, 194), (158, 195), (158, 196), (158, 197), (158, 198), (158, 199), (158, 200),
(158, 201), (158, 202), (158, 203), (158, 204), (158, 205), (158, 206), (158, 207), (158, 208), (158, 209), (158, 210), (158, 211), (158, 212), (158, 213), (158, 214), (158, 215), (158, 216), (158, 217), (158, 218), (158, 219), (158, 220), (158, 221), (158, 222), (158, 223), (158, 224), (158, 225), (158, 226), (158, 229), (159, 187), (159, 188), (159, 191), (159, 192), (159, 193), (159, 194), (159, 195), (159, 196), (159, 197), (159, 198), (159, 199), (159, 200), (159, 201), (159, 202), (159, 203), (159, 204), (159, 205), (159, 215), (159, 216), (159, 217), (159, 218), (159, 219), (159, 220), (159, 221), (159, 222), (159, 223), (159, 224), (159, 227), (159, 229), (160, 189), (160, 193), (160, 194), (160, 195), (160, 196), (160, 197), (160, 198), (160, 199), (160, 200), (160, 201), (160, 202), (160, 203), (160, 204), (160, 207), (160, 208), (160, 209),
(160, 210), (160, 211), (160, 212), (160, 213), (160, 214), (160, 218), (160, 219), (160, 220), (160, 221), (160, 222), (160, 223), (160, 226), (161, 191), (161, 194), (161, 195), (161, 196), (161, 197), (161, 198), (161, 199), (161, 200), (161, 201), (161, 202), (161, 205), (161, 215), (161, 216), (161, 217), (161, 220), (161, 221), (161, 222), (161, 224), (162, 193), (162, 195), (162, 196), (162, 197), (162, 198), (162, 199), (162, 200), (162, 203), (162, 218), (162, 219), (162, 223), (163, 194), (163, 201), (163, 202), (163, 222), (164, 195), (164, 197), (164, 198), (164, 200), (235, 195), (235, 197), (235, 198), (235, 200), (236, 194), (236, 202), (236, 220), (236, 222), (237, 193), (237, 195), (237, 196), (237, 197), (237, 198), (237, 199), (237, 200), (237, 203), (237, 204), (237, 218), (237, 219), (237, 223), (238, 191), (238, 194), (238, 195),
(238, 196), (238, 197), (238, 198), (238, 199), (238, 200), (238, 201), (238, 202), (238, 205), (238, 215), (238, 216), (238, 217), (238, 220), (238, 221), (238, 222), (238, 224), (239, 189), (239, 193), (239, 194), (239, 195), (239, 196), (239, 197), (239, 198), (239, 199), (239, 200), (239, 201), (239, 202), (239, 203), (239, 204), (239, 207), (239, 208), (239, 209), (239, 210), (239, 211), (239, 212), (239, 213), (239, 214), (239, 218), (239, 219), (239, 220), (239, 221), (239, 222), (239, 223), (239, 226), (240, 186), (240, 187), (240, 191), (240, 192), (240, 193), (240, 194), (240, 195), (240, 196), (240, 197), (240, 198), (240, 199), (240, 200), (240, 201), (240, 202), (240, 203), (240, 204), (240, 205), (240, 206), (240, 215), (240, 216), (240, 217), (240, 218), (240, 219), (240, 220), (240, 221), (240, 222), (240, 223), (240, 224), (240, 227),
(240, 229), (241, 184), (241, 189), (241, 190), (241, 191), (241, 192), (241, 193), (241, 194), (241, 195), (241, 196), (241, 197), (241, 198), (241, 199), (241, 200), (241, 201), (241, 202), (241, 203), (241, 204), (241, 205), (241, 206), (241, 207), (241, 208), (241, 209), (241, 210), (241, 211), (241, 212), (241, 213), (241, 214), (241, 215), (241, 216), (241, 217), (241, 218), (241, 219), (241, 220), (241, 221), (241, 222), (241, 223), (241, 224), (241, 225), (241, 226), (241, 229), (242, 182), (242, 186), (242, 187), (242, 188), (242, 189), (242, 190), (242, 191), (242, 192), (242, 193), (242, 194), (242, 195), (242, 196), (242, 197), (242, 198), (242, 199), (242, 200), (242, 201), (242, 202), (242, 203), (242, 204), (242, 205), (242, 206), (242, 207), (242, 208), (242, 209), (242, 210), (242, 211), (242, 212), (242, 213), (242, 214), (242, 215),
(242, 216), (242, 217), (242, 218), (242, 219), (242, 220), (242, 221), (242, 222), (242, 223), (242, 224), (242, 225), (242, 226), (242, 227), (242, 229), (243, 181), (243, 184), (243, 185), (243, 186), (243, 187), (243, 188), (243, 189), (243, 190), (243, 191), (243, 192), (243, 193), (243, 194), (243, 195), (243, 196), (243, 197), (243, 198), (243, 199), (243, 200), (243, 201), (243, 202), (243, 203), (243, 204), (243, 205), (243, 206), (243, 207), (243, 208), (243, 209), (243, 210), (243, 211), (243, 212), (243, 213), (243, 214), (243, 215), (243, 216), (243, 217), (243, 218), (243, 219), (243, 220), (243, 221), (243, 222), (243, 223), (243, 224), (243, 225), (243, 226), (243, 227), (243, 229), (244, 180), (244, 182), (244, 183), (244, 184), (244, 185), (244, 186), (244, 187), (244, 188), (244, 189), (244, 190), (244, 191), (244, 192), (244, 193),
(244, 194), (244, 195), (244, 196), (244, 197), (244, 198), (244, 199), (244, 200), (244, 201), (244, 202), (244, 203), (244, 204), (244, 205), (244, 206), (244, 207), (244, 208), (244, 209), (244, 210), (244, 211), (244, 212), (244, 213), (244, 214), (244, 215), (244, 216), (244, 217), (244, 218), (244, 219), (244, 220), (244, 221), (244, 222), (244, 223), (244, 224), (244, 225), (244, 226), (244, 227), (244, 228), (244, 230), (245, 179), (245, 181), (245, 182), (245, 183), (245, 184), (245, 185), (245, 186), (245, 187), (245, 188), (245, 189), (245, 190), (245, 191), (245, 192), (245, 193), (245, 194), (245, 195), (245, 196), (245, 197), (245, 198), (245, 199), (245, 200), (245, 201), (245, 202), (245, 203), (245, 204), (245, 205), (245, 206), (245, 207), (245, 208), (245, 209), (245, 210), (245, 211), (245, 212), (245, 213), (245, 214), (245, 215),
(245, 216), (245, 217), (245, 218), (245, 219), (245, 220), (245, 221), (245, 222), (245, 223), (245, 224), (245, 225), (245, 226), (245, 227), (245, 228), (245, 230), (246, 178), (246, 180), (246, 181), (246, 182), (246, 183), (246, 184), (246, 185), (246, 186), (246, 187), (246, 188), (246, 189), (246, 190), (246, 191), (246, 192), (246, 193), (246, 194), (246, 195), (246, 196), (246, 197), (246, 198), (246, 199), (246, 200), (246, 201), (246, 202), (246, 203), (246, 204), (246, 205), (246, 206), (246, 207), (246, 208), (246, 209), (246, 210), (246, 211), (246, 212), (246, 213), (246, 214), (246, 215), (246, 216), (246, 217), (246, 218), (246, 219), (246, 220), (246, 221), (246, 222), (246, 223), (246, 224), (246, 225), (246, 226), (246, 227), (246, 228), (246, 230), (247, 178), (247, 180), (247, 181), (247, 182), (247, 183), (247, 184), (247, 185),
(247, 186), (247, 187), (247, 188), (247, 189), (247, 190), (247, 191), (247, 192), (247, 193), (247, 194), (247, 195), (247, 196), (247, 197), (247, 198), (247, 199), (247, 200), (247, 201), (247, 202), (247, 203), (247, 204), (247, 205), (247, 206), (247, 207), (247, 208), (247, 209), (247, 210), (247, 211), (247, 212), (247, 213), (247, 214), (247, 215), (247, 216), (247, 217), (247, 218), (247, 219), (247, 220), (247, 221), (247, 222), (247, 223), (247, 224), (247, 225), (247, 226), (247, 227), (247, 228), (247, 230), (248, 177), (248, 179), (248, 180), (248, 181), (248, 182), (248, 183), (248, 184), (248, 185), (248, 186), (248, 187), (248, 188), (248, 189), (248, 190), (248, 191), (248, 192), (248, 193), (248, 194), (248, 195), (248, 196), (248, 197), (248, 198), (248, 199), (248, 200), (248, 201), (248, 202), (248, 203), (248, 204), (248, 205),
(248, 206), (248, 207), (248, 208), (248, 209), (248, 210), (248, 211), (248, 212), (248, 213), (248, 214), (248, 215), (248, 216), (248, 217), (248, 218), (248, 219), (248, 220), (248, 221), (248, 222), (248, 223), (248, 224), (248, 225), (248, 226), (248, 227), (248, 228), (248, 230), (249, 176), (249, 178), (249, 179), (249, 180), (249, 181), (249, 182), (249, 183), (249, 184), (249, 185), (249, 186), (249, 187), (249, 188), (249, 189), (249, 190), (249, 191), (249, 192), (249, 193), (249, 194), (249, 195), (249, 196), (249, 197), (249, 198), (249, 199), (249, 200), (249, 201), (249, 202), (249, 203), (249, 204), (249, 205), (249, 206), (249, 207), (249, 208), (249, 209), (249, 210), (249, 211), (249, 212), (249, 213), (249, 214), (249, 215), (249, 216), (249, 217), (249, 218), (249, 219), (249, 220), (249, 221), (249, 222), (249, 223), (249, 224),
(249, 225), (249, 226), (249, 227), (249, 228), (249, 230), (250, 176), (250, 178), (250, 179), (250, 180), (250, 181), (250, 182), (250, 183), (250, 184), (250, 185), (250, 186), (250, 187), (250, 188), (250, 189), (250, 190), (250, 191), (250, 192), (250, 193), (250, 194), (250, 195), (250, 196), (250, 197), (250, 198), (250, 199), (250, 200), (250, 201), (250, 202), (250, 203), (250, 204), (250, 205), (250, 206), (250, 207), (250, 208), (250, 209), (250, 210), (250, 211), (250, 212), (250, 213), (250, 214), (250, 215), (250, 216), (250, 217), (250, 218), (250, 219), (250, 220), (250, 221), (250, 222), (250, 223), (250, 224), (250, 225), (250, 226), (250, 227), (250, 228), (250, 230), (251, 175), (251, 177), (251, 178), (251, 179), (251, 180), (251, 181), (251, 182), (251, 183), (251, 184), (251, 185), (251, 186), (251, 187), (251, 188), (251, 189),
(251, 190), (251, 191), (251, 192), (251, 193), (251, 194), (251, 195), (251, 196), (251, 197), (251, 198), (251, 199), (251, 200), (251, 201), (251, 202), (251, 203), (251, 204), (251, 205), (251, 206), (251, 207), (251, 208), (251, 209), (251, 210), (251, 211), (251, 212), (251, 213), (251, 214), (251, 215), (251, 216), (251, 217), (251, 218), (251, 219), (251, 220), (251, 221), (251, 222), (251, 223), (251, 224), (251, 225), (251, 226), (251, 227), (251, 229), (252, 174), (252, 176), (252, 177), (252, 178), (252, 179), (252, 180), (252, 181), (252, 182), (252, 183), (252, 184), (252, 185), (252, 186), (252, 187), (252, 188), (252, 189), (252, 190), (252, 191), (252, 192), (252, 193), (252, 194), (252, 195), (252, 196), (252, 197), (252, 198), (252, 199), (252, 200), (252, 201), (252, 202), (252, 203), (252, 204), (252, 205), (252, 206), (252, 207),
(252, 208), (252, 209), (252, 210), (252, 211), (252, 212), (252, 213), (252, 214), (252, 215), (252, 216), (252, 217), (252, 218), (252, 219), (252, 220), (252, 221), (252, 222), (252, 223), (252, 224), (252, 225), (252, 226), (252, 227), (252, 229), (253, 176), (253, 177), (253, 178), (253, 179), (253, 180), (253, 181), (253, 182), (253, 183), (253, 184), (253, 185), (253, 186), (253, 187), (253, 188), (253, 189), (253, 190), (253, 191), (253, 192), (253, 193), (253, 194), (253, 195), (253, 196), (253, 197), (253, 198), (253, 199), (253, 200), (253, 201), (253, 202), (253, 203), (253, 204), (253, 205), (253, 206), (253, 207), (253, 208), (253, 209), (253, 210), (253, 211), (253, 212), (253, 213), (253, 214), (253, 215), (253, 216), (253, 217), (253, 218), (253, 219), (253, 220), (253, 221), (253, 222), (253, 223), (253, 224), (253, 225), (253, 226),
(253, 228), (254, 173), (254, 175), (254, 176), (254, 177), (254, 178), (254, 179), (254, 180), (254, 181), (254, 182), (254, 183), (254, 184), (254, 185), (254, 186), (254, 187), (254, 188), (254, 189), (254, 190), (254, 191), (254, 192), (254, 193), (254, 194), (254, 195), (254, 196), (254, 197), (254, 198), (254, 199), (254, 200), (254, 201), (254, 202), (254, 203), (254, 204), (254, 205), (254, 206), (254, 207), (254, 208), (254, 209), (254, 210), (254, 211), (254, 212), (254, 213), (254, 214), (254, 215), (254, 216), (254, 217), (254, 218), (254, 219), (254, 220), (254, 221), (254, 222), (254, 223), (254, 224), (254, 225), (254, 226), (254, 228), (255, 174), (255, 175), (255, 176), (255, 177), (255, 178), (255, 179), (255, 180), (255, 181), (255, 182), (255, 183), (255, 184), (255, 185), (255, 186), (255, 187), (255, 188), (255, 189), (255, 190),
(255, 191), (255, 192), (255, 193), (255, 194), (255, 195), (255, 196), (255, 197), (255, 198), (255, 199), (255, 200), (255, 201), (255, 202), (255, 203), (255, 204), (255, 205), (255, 206), (255, 207), (255, 208), (255, 209), (255, 210), (255, 211), (255, 212), (255, 213), (255, 214), (255, 215), (255, 216), (255, 217), (255, 218), (255, 219), (255, 220), (255, 221), (255, 222), (255, 223), (255, 224), (255, 225), (255, 226), (255, 228), (256, 170), (256, 173), (256, 174), (256, 175), (256, 176), (256, 177), (256, 178), (256, 179), (256, 180), (256, 181), (256, 182), (256, 183), (256, 184), (256, 185), (256, 186), (256, 187), (256, 188), (256, 189), (256, 190), (256, 191), (256, 192), (256, 193), (256, 194), (256, 195), (256, 196), (256, 197), (256, 198), (256, 199), (256, 200), (256, 201), (256, 202), (256, 203), (256, 204), (256, 205), (256, 206),
(256, 207), (256, 208), (256, 209), (256, 210), (256, 211), (256, 212), (256, 213), (256, 214), (256, 215), (256, 216), (256, 217), (256, 218), (256, 219), (256, 220), (256, 221), (256, 222), (256, 223), (256, 224), (256, 225), (256, 226), (256, 228), (257, 168), (257, 172), (257, 173), (257, 174), (257, 175), (257, 176), (257, 177), (257, 178), (257, 179), (257, 180), (257, 181), (257, 182), (257, 183), (257, 184), (257, 185), (257, 186), (257, 187), (257, 188), (257, 189), (257, 190), (257, 191), (257, 192), (257, 193), (257, 194), (257, 195), (257, 196), (257, 197), (257, 198), (257, 199), (257, 200), (257, 201), (257, 202), (257, 203), (257, 204), (257, 205), (257, 206), (257, 207), (257, 208), (257, 209), (257, 210), (257, 211), (257, 212), (257, 213), (257, 214), (257, 215), (257, 216), (257, 217), (257, 218), (257, 219), (257, 220), (257, 221),
(257, 222), (257, 223), (257, 224), (257, 225), (257, 226), (257, 228), (258, 166), (258, 170), (258, 171), (258, 172), (258, 173), (258, 174), (258, 175), (258, 176), (258, 177), (258, 178), (258, 179), (258, 180), (258, 181), (258, 182), (258, 183), (258, 184), (258, 185), (258, 186), (258, 187), (258, 188), (258, 189), (258, 190), (258, 191), (258, 192), (258, 193), (258, 194), (258, 195), (258, 196), (258, 197), (258, 198), (258, 199), (258, 200), (258, 201), (258, 202), (258, 203), (258, 204), (258, 205), (258, 206), (258, 207), (258, 208), (258, 209), (258, 210), (258, 211), (258, 212), (258, 213), (258, 214), (258, 215), (258, 216), (258, 217), (258, 218), (258, 219), (258, 220), (258, 221), (258, 222), (258, 223), (258, 224), (258, 225), (258, 226), (258, 228), (259, 164), (259, 168), (259, 169), (259, 170), (259, 171), (259, 172), (259, 173),
(259, 174), (259, 175), (259, 176), (259, 177), (259, 178), (259, 179), (259, 180), (259, 181), (259, 182), (259, 183), (259, 184), (259, 185), (259, 186), (259, 187), (259, 188), (259, 189), (259, 190), (259, 191), (259, 192), (259, 193), (259, 194), (259, 195), (259, 196), (259, 197), (259, 198), (259, 199), (259, 200), (259, 201), (259, 202), (259, 203), (259, 204), (259, 205), (259, 206), (259, 207), (259, 208), (259, 209), (259, 210), (259, 211), (259, 212), (259, 213), (259, 214), (259, 215), (259, 216), (259, 217), (259, 218), (259, 219), (259, 220), (259, 221), (259, 222), (259, 223), (259, 224), (259, 225), (259, 226), (259, 228), (260, 163), (260, 166), (260, 167), (260, 168), (260, 169), (260, 170), (260, 171), (260, 172), (260, 173), (260, 174), (260, 175), (260, 176), (260, 177), (260, 178), (260, 179), (260, 180), (260, 181), (260, 182),
(260, 183), (260, 184), (260, 185), (260, 186), (260, 187), (260, 188), (260, 189), (260, 190), (260, 191), (260, 192), (260, 193), (260, 194), (260, 195), (260, 196), (260, 197), (260, 198), (260, 199), (260, 200), (260, 201), (260, 202), (260, 203), (260, 204), (260, 205), (260, 206), (260, 207), (260, 208), (260, 209), (260, 210), (260, 211), (260, 212), (260, 213), (260, 214), (260, 215), (260, 216), (260, 217), (260, 218), (260, 219), (260, 220), (260, 221), (260, 222), (260, 223), (260, 224), (260, 225), (260, 226), (260, 228), (261, 162), (261, 164), (261, 165), (261, 166), (261, 167), (261, 168), (261, 169), (261, 170), (261, 171), (261, 172), (261, 173), (261, 174), (261, 175), (261, 176), (261, 177), (261, 178), (261, 179), (261, 180), (261, 181), (261, 182), (261, 183), (261, 184), (261, 185), (261, 186), (261, 187), (261, 188), (261, 189),
(261, 190), (261, 191), (261, 192), (261, 193), (261, 194), (261, 195), (261, 196), (261, 197), (261, 198), (261, 199), (261, 200), (261, 201), (261, 202), (261, 203), (261, 204), (261, 205), (261, 206), (261, 207), (261, 208), (261, 209), (261, 210), (261, 211), (261, 212), (261, 213), (261, 214), (261, 215), (261, 216), (261, 217), (261, 218), (261, 219), (261, 220), (261, 221), (261, 222), (261, 223), (261, 224), (261, 225), (261, 227), (262, 161), (262, 163), (262, 164), (262, 165), (262, 166), (262, 167), (262, 168), (262, 169), (262, 170), (262, 171), (262, 172), (262, 173), (262, 174), (262, 175), (262, 176), (262, 177), (262, 178), (262, 179), (262, 180), (262, 181), (262, 182), (262, 183), (262, 184), (262, 185), (262, 186), (262, 187), (262, 188), (262, 189), (262, 190), (262, 191), (262, 192), (262, 193), (262, 194), (262, 195), (262, 196),
(262, 197), (262, 198), (262, 199), (262, 200), (262, 201), (262, 202), (262, 203), (262, 204), (262, 205), (262, 206), (262, 207), (262, 208), (262, 209), (262, 210), (262, 211), (262, 212), (262, 213), (262, 214), (262, 215), (262, 216), (262, 217), (262, 218), (262, 219), (262, 220), (262, 221), (262, 222), (262, 223), (262, 224), (262, 227), (263, 160), (263, 162), (263, 163), (263, 164), (263, 165), (263, 166), (263, 167), (263, 168), (263, 169), (263, 170), (263, 171), (263, 172), (263, 173), (263, 174), (263, 175), (263, 176), (263, 177), (263, 178), (263, 179), (263, 180), (263, 181), (263, 182), (263, 183), (263, 184), (263, 185), (263, 186), (263, 187), (263, 188), (263, 189), (263, 190), (263, 191), (263, 192), (263, 193), (263, 194), (263, 195), (263, 196), (263, 197), (263, 198), (263, 199), (263, 200), (263, 201), (263, 202), (263, 203),
(263, 204), (263, 205), (263, 206), (263, 207), (263, 208), (263, 209), (263, 210), (263, 211), (263, 212), (263, 213), (263, 214), (263, 215), (263, 216), (263, 217), (263, 218), (263, 219), (263, 220), (263, 221), (263, 222), (263, 223), (264, 160), (264, 162), (264, 163), (264, 164), (264, 165), (264, 166), (264, 167), (264, 168), (264, 169), (264, 170), (264, 171), (264, 172), (264, 173), (264, 174), (264, 175), (264, 176), (264, 177), (264, 178), (264, 179), (264, 180), (264, 181), (264, 182), (264, 183), (264, 184), (264, 185), (264, 186), (264, 187), (264, 188), (264, 189), (264, 190), (264, 191), (264, 192), (264, 193), (264, 194), (264, 195), (264, 196), (264, 197), (264, 198), (264, 199), (264, 200), (264, 201), (264, 202), (264, 203), (264, 204), (264, 205), (264, 206), (264, 207), (264, 208), (264, 209), (264, 210), (264, 211), (264, 212),
(264, 213), (264, 214), (264, 215), (264, 216), (264, 217), (264, 218), (264, 219), (264, 220), (264, 221), (264, 222), (264, 224), (265, 160), (265, 162), (265, 163), (265, 164), (265, 165), (265, 166), (265, 167), (265, 168), (265, 169), (265, 170), (265, 171), (265, 172), (265, 173), (265, 174), (265, 175), (265, 176), (265, 177), (265, 178), (265, 179), (265, 180), (265, 181), (265, 182), (265, 183), (265, 184), (265, 185), (265, 186), (265, 187), (265, 188), (265, 189), (265, 190), (265, 191), (265, 192), (265, 193), (265, 194), (265, 195), (265, 196), (265, 197), (265, 198), (265, 199), (265, 200), (265, 201), (265, 202), (265, 203), (265, 204), (265, 205), (265, 206), (265, 207), (265, 208), (265, 209), (265, 210), (265, 211), (265, 212), (265, 213), (265, 214), (265, 215), (265, 216), (265, 217), (265, 218), (265, 219), (265, 220), (265, 221),
(265, 223), (266, 159), (266, 161), (266, 162), (266, 163), (266, 164), (266, 165), (266, 166), (266, 167), (266, 168), (266, 169), (266, 170), (266, 171), (266, 172), (266, 173), (266, 174), (266, 175), (266, 176), (266, 177), (266, 178), (266, 179), (266, 180), (266, 181), (266, 182), (266, 183), (266, 184), (266, 185), (266, 186), (266, 187), (266, 188), (266, 189), (266, 190), (266, 191), (266, 192), (266, 193), (266, 194), (266, 195), (266, 196), (266, 197), (266, 198), (266, 199), (266, 200), (266, 201), (266, 202), (266, 203), (266, 204), (266, 205), (266, 206), (266, 207), (266, 208), (266, 209), (266, 210), (266, 211), (266, 212), (266, 213), (266, 214), (266, 215), (266, 216), (266, 217), (266, 218), (266, 219), (266, 220), (266, 222), (267, 159), (267, 161), (267, 162), (267, 163), (267, 164), (267, 165), (267, 166), (267, 167), (267, 168),
(267, 169), (267, 170), (267, 171), (267, 172), (267, 173), (267, 174), (267, 175), (267, 176), (267, 177), (267, 178), (267, 179), (267, 180), (267, 181), (267, 182), (267, 183), (267, 184), (267, 185), (267, 186), (267, 187), (267, 188), (267, 189), (267, 190), (267, 191), (267, 192), (267, 193), (267, 194), (267, 195), (267, 196), (267, 197), (267, 198), (267, 199), (267, 200), (267, 201), (267, 202), (267, 203), (267, 204), (267, 205), (267, 206), (267, 207), (267, 208), (267, 209), (267, 210), (267, 211), (267, 212), (267, 213), (267, 214), (267, 215), (267, 216), (267, 217), (267, 218), (267, 219), (267, 221), (268, 159), (268, 161), (268, 162), (268, 163), (268, 164), (268, 165), (268, 166), (268, 167), (268, 168), (268, 169), (268, 170), (268, 171), (268, 172), (268, 173), (268, 174), (268, 175), (268, 176), (268, 177), (268, 178), (268, 179),
(268, 180), (268, 181), (268, 182), (268, 183), (268, 184), (268, 185), (268, 186), (268, 187), (268, 188), (268, 189), (268, 190), (268, 191), (268, 192), (268, 193), (268, 194), (268, 195), (268, 196), (268, 197), (268, 198), (268, 199), (268, 200), (268, 201), (268, 202), (268, 203), (268, 204), (268, 205), (268, 206), (268, 207), (268, 208), (268, 209), (268, 210), (268, 211), (268, 212), (268, 213), (268, 214), (268, 215), (268, 216), (268, 217), (268, 218), (268, 220), (269, 159), (269, 161), (269, 162), (269, 163), (269, 164), (269, 165), (269, 166), (269, 167), (269, 168), (269, 169), (269, 170), (269, 171), (269, 172), (269, 173), (269, 174), (269, 175), (269, 176), (269, 177), (269, 178), (269, 179), (269, 180), (269, 181), (269, 182), (269, 183), (269, 184), (269, 185), (269, 186), (269, 187), (269, 188), (269, 189), (269, 190), (269, 191),
(269, 192), (269, 193), (269, 194), (269, 195), (269, 196), (269, 197), (269, 198), (269, 199), (269, 200), (269, 201), (269, 202), (269, 203), (269, 204), (269, 205), (269, 206), (269, 207), (269, 208), (269, 209), (269, 210), (269, 211), (269, 212), (269, 213), (269, 214), (269, 215), (269, 216), (269, 220), (270, 159), (270, 161), (270, 162), (270, 163), (270, 164), (270, 165), (270, 166), (270, 167), (270, 168), (270, 169), (270, 170), (270, 171), (270, 172), (270, 173), (270, 174), (270, 175), (270, 176), (270, 177), (270, 178), (270, 179), (270, 180), (270, 181), (270, 182), (270, 183), (270, 184), (270, 185), (270, 186), (270, 187), (270, 188), (270, 189), (270, 190), (270, 191), (270, 192), (270, 193), (270, 194), (270, 195), (270, 196), (270, 197), (270, 198), (270, 199), (270, 200), (270, 201), (270, 202), (270, 203), (270, 204), (270, 205),
(270, 206), (270, 207), (270, 208), (270, 209), (270, 210), (270, 211), (270, 212), (270, 213), (270, 214), (270, 215), (270, 218), (271, 159), (271, 161), (271, 162), (271, 163), (271, 164), (271, 165), (271, 166), (271, 167), (271, 168), (271, 169), (271, 170), (271, 171), (271, 172), (271, 173), (271, 174), (271, 175), (271, 176), (271, 177), (271, 178), (271, 179), (271, 180), (271, 181), (271, 182), (271, 183), (271, 184), (271, 185), (271, 186), (271, 187), (271, 188), (271, 189), (271, 190), (271, 191), (271, 192), (271, 193), (271, 194), (271, 195), (271, 196), (271, 197), (271, 198), (271, 199), (271, 200), (271, 201), (271, 202), (271, 203), (271, 204), (271, 205), (271, 206), (271, 207), (271, 208), (271, 209), (271, 210), (271, 211), (271, 212), (271, 213), (271, 214), (271, 216), (272, 159), (272, 161), (272, 162), (272, 163), (272, 164),
(272, 165), (272, 166), (272, 167), (272, 168), (272, 169), (272, 170), (272, 171), (272, 172), (272, 173), (272, 174), (272, 175), (272, 176), (272, 177), (272, 178), (272, 179), (272, 180), (272, 181), (272, 182), (272, 183), (272, 184), (272, 185), (272, 186), (272, 187), (272, 188), (272, 189), (272, 190), (272, 191), (272, 192), (272, 193), (272, 194), (272, 195), (272, 196), (272, 197), (272, 198), (272, 199), (272, 200), (272, 201), (272, 202), (272, 203), (272, 204), (272, 205), (272, 206), (272, 207), (272, 208), (272, 209), (272, 210), (272, 211), (272, 212), (272, 213), (272, 215), (273, 159), (273, 161), (273, 162), (273, 163), (273, 164), (273, 165), (273, 166), (273, 167), (273, 168), (273, 169), (273, 170), (273, 171), (273, 172), (273, 173), (273, 174), (273, 175), (273, 176), (273, 177), (273, 178), (273, 179), (273, 180), (273, 181),
(273, 182), (273, 183), (273, 184), (273, 185), (273, 186), (273, 187), (273, 188), (273, 189), (273, 190), (273, 191), (273, 192), (273, 193), (273, 194), (273, 195), (273, 196), (273, 197), (273, 198), (273, 199), (273, 200), (273, 201), (273, 202), (273, 203), (273, 204), (273, 205), (273, 206), (273, 207), (273, 208), (273, 209), (273, 210), (273, 211), (273, 212), (273, 214), (274, 159), (274, 161), (274, 162), (274, 163), (274, 164), (274, 165), (274, 166), (274, 167), (274, 168), (274, 169), (274, 170), (274, 171), (274, 172), (274, 173), (274, 174), (274, 175), (274, 176), (274, 177), (274, 178), (274, 179), (274, 180), (274, 181), (274, 182), (274, 183), (274, 184), (274, 185), (274, 186), (274, 187), (274, 188), (274, 189), (274, 190), (274, 191), (274, 192), (274, 193), (274, 194), (274, 195), (274, 196), (274, 197), (274, 198), (274, 199),
(274, 200), (274, 201), (274, 202), (274, 203), (274, 204), (274, 205), (274, 206), (274, 207), (274, 208), (274, 209), (274, 210), (274, 211), (274, 213), (275, 159), (275, 161), (275, 162), (275, 163), (275, 164), (275, 165), (275, 166), (275, 167), (275, 168), (275, 169), (275, 170), (275, 171), (275, 172), (275, 173), (275, 174), (275, 175), (275, 176), (275, 177), (275, 178), (275, 179), (275, 180), (275, 181), (275, 182), (275, 183), (275, 184), (275, 185), (275, 186), (275, 187), (275, 188), (275, 189), (275, 190), (275, 191), (275, 192), (275, 193), (275, 194), (275, 195), (275, 196), (275, 197), (275, 198), (275, 199), (275, 200), (275, 201), (275, 202), (275, 203), (275, 204), (275, 205), (275, 206), (275, 207), (275, 208), (275, 209), (275, 210), (275, 212), (276, 159), (276, 161), (276, 162), (276, 163), (276, 164), (276, 165), (276, 166),
(276, 167), (276, 168), (276, 169), (276, 170), (276, 171), (276, 172), (276, 173), (276, 174), (276, 175), (276, 176), (276, 177), (276, 178), (276, 179), (276, 180), (276, 181), (276, 182), (276, 183), (276, 184), (276, 185), (276, 186), (276, 187), (276, 188), (276, 189), (276, 190), (276, 191), (276, 192), (276, 193), (276, 194), (276, 195), (276, 196), (276, 197), (276, 198), (276, 199), (276, 200), (276, 201), (276, 202), (276, 203), (276, 204), (276, 205), (276, 206), (276, 207), (276, 208), (276, 209), (276, 210), (276, 212), (277, 160), (277, 162), (277, 163), (277, 164), (277, 165), (277, 166), (277, 167), (277, 168), (277, 169), (277, 170), (277, 171), (277, 172), (277, 173), (277, 174), (277, 175), (277, 176), (277, 177), (277, 178), (277, 179), (277, 180), (277, 181), (277, 182), (277, 183), (277, 184), (277, 185), (277, 186), (277, 187),
(277, 188), (277, 189), (277, 190), (277, 191), (277, 192), (277, 193), (277, 194), (277, 195), (277, 196), (277, 197), (277, 198), (277, 199), (277, 200), (277, 201), (277, 202), (277, 203), (277, 204), (277, 205), (277, 206), (277, 207), (277, 208), (277, 209), (277, 211), (278, 160), (278, 162), (278, 163), (278, 164), (278, 165), (278, 166), (278, 167), (278, 168), (278, 169), (278, 170), (278, 171), (278, 172), (278, 173), (278, 174), (278, 175), (278, 176), (278, 177), (278, 178), (278, 179), (278, 180), (278, 181), (278, 182), (278, 183), (278, 184), (278, 185), (278, 186), (278, 187), (278, 188), (278, 189), (278, 190), (278, 191), (278, 192), (278, 193), (278, 194), (278, 195), (278, 196), (278, 197), (278, 198), (278, 199), (278, 200), (278, 201), (278, 202), (278, 203), (278, 204), (278, 205), (278, 206), (278, 207), (278, 208), (278, 210),
(279, 160), (279, 162), (279, 163), (279, 164), (279, 165), (279, 166), (279, 167), (279, 168), (279, 169), (279, 170), (279, 171), (279, 172), (279, 173), (279, 174), (279, 175), (279, 176), (279, 177), (279, 178), (279, 179), (279, 180), (279, 181), (279, 182), (279, 183), (279, 184), (279, 185), (279, 186), (279, 187), (279, 188), (279, 189), (279, 190), (279, 191), (279, 192), (279, 193), (279, 194), (279, 195), (279, 196), (279, 197), (279, 198), (279, 199), (279, 200), (279, 201), (279, 202), (279, 203), (279, 204), (279, 205), (279, 206), (279, 207), (279, 208), (279, 210), (280, 161), (280, 163), (280, 164), (280, 165), (280, 166), (280, 167), (280, 168), (280, 169), (280, 170), (280, 171), (280, 172), (280, 173), (280, 174), (280, 175), (280, 176), (280, 177), (280, 178), (280, 179), (280, 180), (280, 181), (280, 182), (280, 183), (280, 184),
(280, 185), (280, 186), (280, 187), (280, 188), (280, 189), (280, 190), (280, 191), (280, 192), (280, 193), (280, 194), (280, 195), (280, 196), (280, 197), (280, 198), (280, 199), (280, 200), (280, 201), (280, 202), (280, 203), (280, 204), (280, 205), (280, 206), (280, 207), (280, 209), (281, 161), (281, 163), (281, 164), (281, 165), (281, 166), (281, 167), (281, 168), (281, 169), (281, 170), (281, 171), (281, 172), (281, 173), (281, 174), (281, 175), (281, 176), (281, 177), (281, 178), (281, 179), (281, 180), (281, 181), (281, 182), (281, 183), (281, 184), (281, 185), (281, 186), (281, 187), (281, 188), (281, 189), (281, 190), (281, 191), (281, 192), (281, 193), (281, 194), (281, 195), (281, 196), (281, 197), (281, 198), (281, 199), (281, 200), (281, 201), (281, 202), (281, 203), (281, 204), (281, 205), (281, 206), (281, 207), (281, 209), (282, 162),
(282, 164), (282, 165), (282, 166), (282, 167), (282, 168), (282, 169), (282, 170), (282, 171), (282, 172), (282, 173), (282, 174), (282, 175), (282, 176), (282, 177), (282, 178), (282, 179), (282, 180), (282, 181), (282, 182), (282, 183), (282, 184), (282, 185), (282, 186), (282, 187), (282, 188), (282, 189), (282, 190), (282, 191), (282, 192), (282, 193), (282, 194), (282, 195), (282, 196), (282, 197), (282, 198), (282, 199), (282, 200), (282, 201), (282, 202), (282, 203), (282, 204), (282, 205), (282, 206), (282, 208), (283, 162), (283, 164), (283, 165), (283, 166), (283, 167), (283, 168), (283, 169), (283, 170), (283, 171), (283, 172), (283, 173), (283, 174), (283, 175), (283, 176), (283, 177), (283, 178), (283, 179), (283, 180), (283, 181), (283, 182), (283, 183), (283, 184), (283, 185), (283, 186), (283, 187), (283, 188), (283, 189), (283, 190),
(283, 191), (283, 192), (283, 193), (283, 194), (283, 195), (283, 196), (283, 197), (283, 198), (283, 199), (283, 200), (283, 201), (283, 202), (283, 203), (283, 204), (283, 207), (284, 163), (284, 165), (284, 166), (284, 167), (284, 168), (284, 169), (284, 170), (284, 171), (284, 172), (284, 173), (284, 174), (284, 175), (284, 176), (284, 177), (284, 178), (284, 179), (284, 180), (284, 181), (284, 182), (284, 183), (284, 184), (284, 185), (284, 186), (284, 187), (284, 188), (284, 189), (284, 190), (284, 191), (284, 192), (284, 193), (284, 194), (284, 195), (284, 196), (284, 197), (284, 198), (284, 199), (284, 200), (284, 201), (284, 202), (284, 206), (285, 164), (285, 166), (285, 167), (285, 168), (285, 169), (285, 170), (285, 171), (285, 172), (285, 173), (285, 174), (285, 175), (285, 176), (285, 177), (285, 178), (285, 179), (285, 180), (285, 181),
(285, 182), (285, 183), (285, 184), (285, 185), (285, 186), (285, 187), (285, 188), (285, 189), (285, 190), (285, 191), (285, 192), (285, 193), (285, 194), (285, 195), (285, 196), (285, 197), (285, 198), (285, 199), (285, 200), (285, 204), (286, 165), (286, 167), (286, 168), (286, 169), (286, 170), (286, 171), (286, 172), (286, 173), (286, 174), (286, 175), (286, 176), (286, 177), (286, 178), (286, 179), (286, 180), (286, 181), (286, 182), (286, 183), (286, 184), (286, 185), (286, 186), (286, 187), (286, 188), (286, 189), (286, 190), (286, 191), (286, 192), (286, 193), (286, 194), (286, 195), (286, 196), (286, 197), (286, 198), (286, 202), (287, 166), (287, 168), (287, 169), (287, 170), (287, 171), (287, 172), (287, 173), (287, 174), (287, 175), (287, 176), (287, 177), (287, 178), (287, 179), (287, 180), (287, 181), (287, 182), (287, 183), (287, 184),
(287, 185), (287, 186), (287, 187), (287, 188), (287, 189), (287, 190), (287, 191), (287, 192), (287, 193), (287, 194), (287, 195), (287, 196), (287, 200), (288, 167), (288, 170), (288, 171), (288, 172), (288, 173), (288, 174), (288, 175), (288, 176), (288, 177), (288, 178), (288, 179), (288, 180), (288, 181), (288, 182), (288, 183), (288, 184), (288, 185), (288, 186), (288, 187), (288, 188), (288, 189), (288, 190), (288, 191), (288, 192), (288, 193), (288, 194), (288, 198), (289, 168), (289, 174), (289, 175), (289, 176), (289, 177), (289, 178), (289, 179), (289, 180), (289, 181), (289, 182), (289, 183), (289, 184), (289, 185), (289, 186), (289, 187), (289, 188), (289, 189), (289, 190), (289, 191), (289, 192), (289, 196), (290, 170), (290, 171), (290, 172), (290, 173), (290, 177), (290, 178), (290, 179), (290, 180), (290, 181), (290, 182), (290, 183),
(290, 184), (290, 185), (290, 186), (290, 194), (291, 174), (291, 176), (291, 180), (291, 181), (291, 182), (291, 186), (291, 187), (291, 188), (291, 189), (291, 190), (291, 192), (292, 177), (292, 178), (292, 179), (292, 180), (292, 183), (292, 184), (292, 185), (293, 182), )
coordinates_13007F = ((103, 234),
(104, 233), (104, 234), (105, 232), (105, 235), (106, 231), (106, 233), (106, 234), (106, 236), (107, 230), (107, 232), (107, 233), (107, 234), (107, 236), (108, 229), (108, 231), (108, 232), (108, 233), (108, 234), (108, 235), (108, 237), (109, 227), (109, 230), (109, 231), (109, 232), (109, 233), (109, 234), (109, 235), (109, 237), (110, 225), (110, 229), (110, 230), (110, 231), (110, 232), (110, 237), (110, 238), (111, 225), (111, 227), (111, 228), (111, 229), (111, 230), (111, 233), (111, 234), (111, 235), (111, 236), (112, 225), (112, 227), (112, 228), (112, 231), (112, 232), (113, 225), (113, 230), (114, 225), (114, 228), (115, 225), (115, 226), (284, 225), (285, 225), (285, 228), (286, 225), (286, 230), (287, 225), (287, 227), (287, 228), (287, 231), (287, 232), (288, 225), (288, 227), (288, 228), (288, 229), (288, 230), (288, 234), (288, 235),
(288, 236), (288, 238), (289, 225), (289, 229), (289, 230), (289, 231), (289, 232), (289, 233), (289, 237), (290, 228), (290, 230), (290, 231), (290, 232), (290, 233), (290, 234), (290, 235), (290, 237), (291, 229), (291, 231), (291, 232), (291, 233), (291, 234), (291, 235), (291, 237), (292, 230), (292, 232), (292, 233), (292, 234), (292, 236), (293, 231), (293, 233), (293, 235), (294, 232), (294, 235), (295, 233), (295, 234), (296, 234), )
coordinates_357F00 = ((64, 189),
(64, 191), (64, 192), (64, 193), (64, 194), (65, 189), (65, 196), (66, 189), (66, 191), (66, 192), (66, 193), (66, 194), (66, 195), (66, 197), (67, 189), (67, 191), (67, 192), (67, 193), (67, 194), (67, 195), (67, 197), (67, 202), (68, 189), (68, 191), (68, 192), (68, 193), (68, 194), (68, 195), (68, 196), (68, 197), (68, 203), (68, 205), (69, 190), (69, 192), (69, 193), (69, 194), (69, 199), (69, 200), (69, 201), (69, 202), (70, 190), (70, 195), (70, 196), (70, 197), (70, 198), (71, 190), (71, 192), (71, 193), (71, 194), (328, 190), (328, 192), (328, 193), (328, 194), (329, 190), (329, 196), (329, 197), (329, 198), (330, 190), (330, 192), (330, 193), (330, 194), (330, 195), (330, 199), (330, 200), (330, 202), (331, 189), (331, 191), (331, 192), (331, 193), (331, 194), (331, 195), (331, 197), (331, 201),
(331, 203), (331, 205), (332, 189), (332, 191), (332, 192), (332, 193), (332, 194), (332, 195), (332, 197), (332, 202), (333, 189), (333, 191), (333, 192), (333, 193), (333, 194), (333, 197), (334, 189), (334, 196), (335, 189), (335, 191), (335, 192), (335, 193), (335, 194), )
coordinates_00FF57 = ((73, 200),
(73, 202), (73, 203), (73, 204), (73, 205), (73, 206), (74, 198), (74, 199), (74, 208), (75, 196), (75, 200), (75, 201), (75, 202), (75, 203), (75, 204), (75, 205), (75, 206), (75, 207), (75, 210), (75, 211), (76, 194), (76, 197), (76, 198), (76, 199), (76, 200), (76, 201), (76, 202), (76, 203), (76, 204), (76, 205), (76, 206), (76, 207), (76, 208), (76, 209), (76, 213), (77, 192), (77, 195), (77, 196), (77, 197), (77, 198), (77, 199), (77, 200), (77, 201), (77, 202), (77, 203), (77, 204), (77, 205), (77, 206), (77, 207), (77, 208), (77, 209), (77, 210), (77, 211), (77, 215), (78, 190), (78, 191), (78, 194), (78, 195), (78, 196), (78, 197), (78, 198), (78, 199), (78, 200), (78, 201), (78, 202), (78, 203), (78, 204), (78, 205), (78, 206), (78, 207), (78, 208), (78, 209), (78, 210),
(78, 211), (78, 212), (78, 213), (78, 216), (79, 189), (79, 192), (79, 193), (79, 194), (79, 195), (79, 196), (79, 197), (79, 198), (79, 199), (79, 200), (79, 201), (79, 202), (79, 203), (79, 204), (79, 205), (79, 206), (79, 207), (79, 208), (79, 209), (79, 210), (79, 211), (79, 212), (79, 213), (79, 214), (79, 215), (79, 218), (80, 187), (80, 190), (80, 191), (80, 192), (80, 193), (80, 194), (80, 195), (80, 196), (80, 197), (80, 198), (80, 199), (80, 200), (80, 201), (80, 202), (80, 203), (80, 204), (80, 205), (80, 206), (80, 207), (80, 208), (80, 209), (80, 210), (80, 211), (80, 212), (80, 213), (80, 214), (80, 215), (80, 216), (80, 219), (81, 186), (81, 189), (81, 190), (81, 191), (81, 192), (81, 193), (81, 194), (81, 195), (81, 196), (81, 197), (81, 198), (81, 199), (81, 200),
(81, 201), (81, 202), (81, 203), (81, 204), (81, 205), (81, 206), (81, 207), (81, 208), (81, 209), (81, 210), (81, 211), (81, 212), (81, 213), (81, 214), (81, 215), (81, 216), (81, 217), (81, 218), (81, 221), (82, 184), (82, 187), (82, 188), (82, 189), (82, 190), (82, 191), (82, 192), (82, 193), (82, 194), (82, 195), (82, 196), (82, 197), (82, 198), (82, 199), (82, 200), (82, 201), (82, 202), (82, 203), (82, 204), (82, 205), (82, 206), (82, 207), (82, 208), (82, 209), (82, 210), (82, 211), (82, 212), (82, 213), (82, 215), (82, 216), (82, 217), (82, 218), (82, 219), (82, 222), (83, 181), (83, 186), (83, 187), (83, 188), (83, 189), (83, 190), (83, 191), (83, 192), (83, 193), (83, 194), (83, 195), (83, 196), (83, 197), (83, 198), (83, 199), (83, 200), (83, 201), (83, 202), (83, 203),
(83, 204), (83, 205), (83, 206), (83, 207), (83, 208), (83, 209), (83, 210), (83, 211), (83, 216), (83, 217), (83, 218), (83, 219), (83, 220), (83, 222), (84, 184), (84, 185), (84, 186), (84, 187), (84, 188), (84, 189), (84, 190), (84, 191), (84, 192), (84, 193), (84, 194), (84, 195), (84, 196), (84, 197), (84, 198), (84, 199), (84, 200), (84, 201), (84, 202), (84, 203), (84, 204), (84, 205), (84, 206), (84, 207), (84, 208), (84, 209), (84, 210), (84, 211), (84, 216), (84, 217), (84, 218), (84, 219), (84, 220), (84, 221), (84, 223), (85, 180), (85, 182), (85, 183), (85, 184), (85, 185), (85, 186), (85, 187), (85, 188), (85, 189), (85, 190), (85, 191), (85, 192), (85, 193), (85, 194), (85, 195), (85, 196), (85, 197), (85, 198), (85, 199), (85, 200), (85, 201), (85, 202), (85, 203),
(85, 204), (85, 205), (85, 206), (85, 207), (85, 208), (85, 209), (85, 210), (85, 212), (85, 216), (85, 218), (85, 219), (85, 220), (85, 221), (85, 222), (85, 224), (86, 179), (86, 181), (86, 182), (86, 183), (86, 184), (86, 185), (86, 186), (86, 187), (86, 188), (86, 189), (86, 190), (86, 191), (86, 192), (86, 193), (86, 194), (86, 195), (86, 196), (86, 197), (86, 198), (86, 199), (86, 200), (86, 201), (86, 202), (86, 203), (86, 204), (86, 205), (86, 206), (86, 207), (86, 208), (86, 209), (86, 211), (86, 216), (86, 218), (86, 219), (86, 220), (86, 221), (86, 222), (86, 224), (87, 178), (87, 180), (87, 181), (87, 182), (87, 183), (87, 184), (87, 185), (87, 186), (87, 187), (87, 188), (87, 189), (87, 190), (87, 191), (87, 192), (87, 193), (87, 194), (87, 195), (87, 196), (87, 197),
(87, 198), (87, 199), (87, 200), (87, 201), (87, 202), (87, 203), (87, 204), (87, 205), (87, 206), (87, 207), (87, 208), (87, 210), (87, 216), (87, 218), (87, 219), (87, 220), (87, 221), (87, 222), (87, 223), (87, 225), (88, 177), (88, 179), (88, 180), (88, 181), (88, 182), (88, 183), (88, 184), (88, 185), (88, 186), (88, 187), (88, 188), (88, 189), (88, 190), (88, 191), (88, 192), (88, 193), (88, 194), (88, 195), (88, 196), (88, 197), (88, 198), (88, 199), (88, 200), (88, 201), (88, 202), (88, 203), (88, 204), (88, 205), (88, 206), (88, 207), (88, 209), (88, 217), (88, 219), (88, 220), (88, 221), (88, 222), (88, 223), (88, 224), (88, 226), (89, 176), (89, 178), (89, 179), (89, 180), (89, 181), (89, 182), (89, 183), (89, 184), (89, 185), (89, 186), (89, 187), (89, 188), (89, 189),
(89, 190), (89, 191), (89, 192), (89, 193), (89, 194), (89, 195), (89, 196), (89, 197), (89, 198), (89, 199), (89, 200), (89, 201), (89, 202), (89, 203), (89, 204), (89, 205), (89, 206), (89, 207), (89, 209), (89, 217), (89, 219), (89, 220), (89, 221), (89, 222), (89, 223), (89, 224), (89, 227), (90, 176), (90, 178), (90, 179), (90, 180), (90, 181), (90, 182), (90, 183), (90, 184), (90, 185), (90, 186), (90, 187), (90, 188), (90, 189), (90, 190), (90, 191), (90, 192), (90, 193), (90, 194), (90, 195), (90, 196), (90, 197), (90, 198), (90, 199), (90, 200), (90, 201), (90, 202), (90, 203), (90, 204), (90, 205), (90, 206), (90, 208), (90, 218), (90, 220), (90, 221), (90, 222), (90, 223), (90, 225), (90, 228), (91, 176), (91, 178), (91, 179), (91, 180), (91, 181), (91, 182), (91, 183),
(91, 184), (91, 185), (91, 186), (91, 187), (91, 188), (91, 189), (91, 190), (91, 191), (91, 192), (91, 193), (91, 194), (91, 195), (91, 196), (91, 197), (91, 198), (91, 199), (91, 200), (91, 201), (91, 202), (91, 203), (91, 204), (91, 205), (91, 206), (91, 208), (91, 218), (91, 220), (91, 221), (91, 224), (91, 229), (92, 176), (92, 180), (92, 181), (92, 182), (92, 183), (92, 184), (92, 185), (92, 186), (92, 187), (92, 188), (92, 189), (92, 190), (92, 191), (92, 192), (92, 193), (92, 194), (92, 195), (92, 196), (92, 197), (92, 198), (92, 199), (92, 200), (92, 201), (92, 202), (92, 203), (92, 204), (92, 205), (92, 207), (92, 218), (92, 223), (93, 177), (93, 179), (93, 196), (93, 197), (93, 198), (93, 199), (93, 200), (93, 201), (93, 202), (93, 203), (93, 204), (93, 205), (93, 206),
(93, 207), (93, 219), (93, 221), (94, 180), (94, 181), (94, 182), (94, 183), (94, 184), (94, 185), (94, 186), (94, 187), (94, 188), (94, 189), (94, 190), (94, 191), (94, 192), (94, 193), (94, 194), (94, 195), (94, 198), (94, 199), (94, 200), (94, 201), (94, 202), (94, 203), (94, 204), (94, 206), (94, 219), (95, 196), (95, 197), (95, 201), (95, 202), (95, 203), (95, 204), (95, 206), (96, 198), (96, 200), (96, 205), (97, 201), (97, 203), (97, 205), (106, 222), (106, 224), (106, 225), (106, 226), (106, 228), (106, 229), (107, 223), (107, 227), (108, 224), (108, 226), (291, 224), (291, 226), (292, 223), (292, 227), (292, 228), (293, 222), (293, 224), (293, 225), (293, 226), (293, 227), (293, 229), (301, 205), (302, 201), (302, 202), (302, 203), (302, 205), (303, 198), (303, 200), (303, 205), (304, 196), (304, 197),
(304, 201), (304, 202), (304, 203), (304, 204), (304, 206), (305, 180), (305, 181), (305, 182), (305, 183), (305, 184), (305, 185), (305, 186), (305, 187), (305, 188), (305, 189), (305, 190), (305, 191), (305, 192), (305, 193), (305, 194), (305, 195), (305, 198), (305, 199), (305, 200), (305, 201), (305, 202), (305, 203), (305, 204), (305, 206), (305, 219), (306, 177), (306, 179), (306, 196), (306, 197), (306, 198), (306, 199), (306, 200), (306, 201), (306, 202), (306, 203), (306, 204), (306, 205), (306, 207), (306, 219), (306, 221), (307, 176), (307, 180), (307, 181), (307, 182), (307, 183), (307, 184), (307, 185), (307, 186), (307, 187), (307, 188), (307, 189), (307, 190), (307, 191), (307, 192), (307, 193), (307, 194), (307, 195), (307, 196), (307, 197), (307, 198), (307, 199), (307, 200), (307, 201), (307, 202), (307, 203), (307, 204), (307, 205),
(307, 207), (307, 218), (307, 220), (307, 223), (308, 176), (308, 178), (308, 179), (308, 180), (308, 181), (308, 182), (308, 183), (308, 184), (308, 185), (308, 186), (308, 187), (308, 188), (308, 189), (308, 190), (308, 191), (308, 192), (308, 193), (308, 194), (308, 195), (308, 196), (308, 197), (308, 198), (308, 199), (308, 200), (308, 201), (308, 202), (308, 203), (308, 204), (308, 205), (308, 206), (308, 208), (308, 218), (308, 220), (308, 221), (308, 224), (308, 229), (309, 176), (309, 178), (309, 179), (309, 180), (309, 181), (309, 182), (309, 183), (309, 184), (309, 185), (309, 186), (309, 187), (309, 188), (309, 189), (309, 190), (309, 191), (309, 192), (309, 193), (309, 194), (309, 195), (309, 196), (309, 197), (309, 198), (309, 199), (309, 200), (309, 201), (309, 202), (309, 203), (309, 204), (309, 205), (309, 206), (309, 208), (309, 218),
(309, 220), (309, 221), (309, 222), (309, 223), (309, 227), (310, 176), (310, 178), (310, 179), (310, 180), (310, 181), (310, 182), (310, 183), (310, 184), (310, 185), (310, 186), (310, 187), (310, 188), (310, 189), (310, 190), (310, 191), (310, 192), (310, 193), (310, 194), (310, 195), (310, 196), (310, 197), (310, 198), (310, 199), (310, 200), (310, 201), (310, 202), (310, 203), (310, 204), (310, 205), (310, 206), (310, 207), (310, 209), (310, 217), (310, 219), (310, 220), (310, 221), (310, 222), (310, 223), (310, 224), (310, 226), (311, 177), (311, 179), (311, 180), (311, 181), (311, 182), (311, 183), (311, 184), (311, 185), (311, 186), (311, 187), (311, 188), (311, 189), (311, 190), (311, 191), (311, 192), (311, 193), (311, 194), (311, 195), (311, 196), (311, 197), (311, 198), (311, 199), (311, 200), (311, 201), (311, 202), (311, 203), (311, 204),
(311, 205), (311, 206), (311, 207), (311, 209), (311, 217), (311, 219), (311, 220), (311, 221), (311, 222), (311, 223), (311, 225), (312, 178), (312, 180), (312, 181), (312, 182), (312, 183), (312, 184), (312, 185), (312, 186), (312, 187), (312, 188), (312, 189), (312, 190), (312, 191), (312, 192), (312, 193), (312, 194), (312, 195), (312, 196), (312, 197), (312, 198), (312, 199), (312, 200), (312, 201), (312, 202), (312, 203), (312, 204), (312, 205), (312, 206), (312, 207), (312, 208), (312, 210), (312, 216), (312, 218), (312, 219), (312, 220), (312, 221), (312, 222), (312, 224), (313, 179), (313, 181), (313, 182), (313, 183), (313, 184), (313, 185), (313, 186), (313, 187), (313, 188), (313, 189), (313, 190), (313, 191), (313, 192), (313, 193), (313, 194), (313, 195), (313, 196), (313, 197), (313, 198), (313, 199), (313, 200), (313, 201), (313, 202),
(313, 203), (313, 204), (313, 205), (313, 206), (313, 207), (313, 208), (313, 209), (313, 211), (313, 216), (313, 218), (313, 219), (313, 220), (313, 221), (313, 222), (313, 224), (314, 180), (314, 182), (314, 183), (314, 184), (314, 185), (314, 186), (314, 187), (314, 188), (314, 189), (314, 190), (314, 191), (314, 192), (314, 193), (314, 194), (314, 195), (314, 196), (314, 197), (314, 198), (314, 199), (314, 200), (314, 201), (314, 202), (314, 203), (314, 204), (314, 205), (314, 206), (314, 207), (314, 208), (314, 209), (314, 210), (314, 212), (314, 216), (314, 218), (314, 219), (314, 220), (314, 221), (314, 223), (315, 181), (315, 184), (315, 185), (315, 186), (315, 187), (315, 188), (315, 189), (315, 190), (315, 191), (315, 192), (315, 193), (315, 194), (315, 195), (315, 196), (315, 197), (315, 198), (315, 199), (315, 200), (315, 201), (315, 202),
(315, 203), (315, 204), (315, 205), (315, 206), (315, 207), (315, 208), (315, 209), (315, 210), (315, 211), (315, 213), (315, 216), (315, 217), (315, 218), (315, 219), (315, 220), (315, 222), (316, 181), (316, 183), (316, 186), (316, 187), (316, 188), (316, 189), (316, 190), (316, 191), (316, 192), (316, 193), (316, 194), (316, 195), (316, 196), (316, 197), (316, 198), (316, 199), (316, 200), (316, 201), (316, 202), (316, 203), (316, 204), (316, 205), (316, 206), (316, 207), (316, 208), (316, 209), (316, 210), (316, 211), (316, 212), (316, 216), (316, 217), (316, 218), (316, 219), (316, 222), (317, 184), (317, 185), (317, 188), (317, 189), (317, 190), (317, 191), (317, 192), (317, 193), (317, 194), (317, 195), (317, 196), (317, 197), (317, 198), (317, 199), (317, 200), (317, 201), (317, 202), (317, 203), (317, 204), (317, 205), (317, 206), (317, 207),
(317, 208), (317, 209), (317, 210), (317, 211), (317, 212), (317, 213), (317, 215), (317, 216), (317, 217), (317, 218), (317, 219), (317, 221), (318, 186), (318, 189), (318, 190), (318, 191), (318, 192), (318, 193), (318, 194), (318, 195), (318, 196), (318, 197), (318, 198), (318, 199), (318, 200), (318, 201), (318, 202), (318, 203), (318, 204), (318, 205), (318, 206), (318, 207), (318, 208), (318, 209), (318, 210), (318, 211), (318, 212), (318, 213), (318, 214), (318, 215), (318, 216), (318, 217), (318, 220), (319, 188), (319, 190), (319, 191), (319, 192), (319, 193), (319, 194), (319, 195), (319, 196), (319, 197), (319, 198), (319, 199), (319, 200), (319, 201), (319, 202), (319, 203), (319, 204), (319, 205), (319, 206), (319, 207), (319, 208), (319, 209), (319, 210), (319, 211), (319, 212), (319, 213), (319, 214), (319, 215), (319, 216), (319, 219),
(320, 189), (320, 192), (320, 193), (320, 194), (320, 195), (320, 196), (320, 197), (320, 198), (320, 199), (320, 200), (320, 201), (320, 202), (320, 203), (320, 204), (320, 205), (320, 206), (320, 207), (320, 208), (320, 209), (320, 210), (320, 211), (320, 212), (320, 213), (320, 214), (320, 215), (320, 218), (321, 190), (321, 193), (321, 194), (321, 195), (321, 196), (321, 197), (321, 198), (321, 199), (321, 200), (321, 201), (321, 202), (321, 203), (321, 204), (321, 205), (321, 206), (321, 207), (321, 208), (321, 209), (321, 210), (321, 211), (321, 212), (321, 213), (321, 216), (322, 192), (322, 194), (322, 195), (322, 196), (322, 197), (322, 198), (322, 199), (322, 200), (322, 201), (322, 202), (322, 203), (322, 204), (322, 205), (322, 206), (322, 207), (322, 208), (322, 209), (322, 210), (322, 211), (322, 215), (323, 193), (323, 196), (323, 197),
(323, 198), (323, 199), (323, 200), (323, 201), (323, 202), (323, 203), (323, 204), (323, 205), (323, 206), (323, 207), (323, 208), (323, 213), (324, 194), (324, 195), (324, 199), (324, 200), (324, 201), (324, 202), (324, 203), (324, 204), (324, 211), (325, 196), (325, 198), (325, 205), (325, 206), (325, 207), (325, 208), (326, 200), (326, 201), (326, 202), (326, 203), (326, 204), )
coordinates_001D7F = ((189, 183),
(189, 184), (189, 185), (189, 186), (189, 187), (189, 188), (189, 189), (189, 190), (189, 191), (189, 192), (189, 193), (189, 194), (190, 178), (190, 179), (190, 180), (190, 181), (190, 182), (190, 195), (190, 196), (191, 175), (191, 177), (191, 182), (191, 183), (191, 184), (191, 185), (191, 186), (191, 187), (191, 188), (191, 189), (191, 190), (191, 191), (191, 192), (191, 193), (191, 194), (191, 197), (191, 198), (192, 163), (192, 164), (192, 165), (192, 166), (192, 167), (192, 168), (192, 169), (192, 170), (192, 171), (192, 172), (192, 173), (192, 174), (192, 178), (192, 179), (192, 180), (192, 181), (192, 182), (192, 183), (192, 184), (192, 185), (192, 186), (192, 187), (192, 188), (192, 189), (192, 190), (192, 191), (192, 192), (192, 193), (192, 194), (192, 195), (192, 196), (192, 200), (192, 201), (193, 161), (193, 162), (193, 175), (193, 176),
(193, 177), (193, 178), (193, 179), (193, 180), (193, 181), (193, 182), (193, 183), (193, 184), (193, 185), (193, 186), (193, 187), (193, 188), (193, 189), (193, 190), (193, 191), (193, 192), (193, 193), (193, 194), (193, 195), (193, 196), (193, 197), (193, 198), (193, 199), (193, 202), (193, 203), (193, 204), (193, 206), (194, 159), (194, 160), (194, 163), (194, 164), (194, 165), (194, 166), (194, 167), (194, 168), (194, 169), (194, 170), (194, 171), (194, 172), (194, 173), (194, 174), (194, 175), (194, 176), (194, 177), (194, 178), (194, 179), (194, 180), (194, 181), (194, 182), (194, 183), (194, 184), (194, 185), (194, 186), (194, 187), (194, 188), (194, 189), (194, 190), (194, 191), (194, 192), (194, 193), (194, 194), (194, 195), (194, 196), (194, 197), (194, 198), (194, 199), (194, 200), (194, 201), (194, 206), (195, 157), (195, 158), (195, 161),
(195, 162), (195, 163), (195, 164), (195, 165), (195, 166), (195, 167), (195, 168), (195, 169), (195, 170), (195, 171), (195, 172), (195, 173), (195, 174), (195, 175), (195, 176), (195, 177), (195, 178), (195, 179), (195, 180), (195, 181), (195, 182), (195, 183), (195, 184), (195, 185), (195, 186), (195, 187), (195, 188), (195, 189), (195, 190), (195, 191), (195, 192), (195, 193), (195, 194), (195, 195), (195, 196), (195, 197), (195, 198), (195, 199), (195, 200), (195, 201), (195, 202), (195, 203), (195, 206), (196, 155), (196, 156), (196, 159), (196, 160), (196, 161), (196, 162), (196, 163), (196, 164), (196, 165), (196, 166), (196, 167), (196, 168), (196, 169), (196, 170), (196, 171), (196, 172), (196, 173), (196, 174), (196, 175), (196, 176), (196, 177), (196, 178), (196, 179), (196, 180), (196, 181), (196, 182), (196, 183), (196, 184), (196, 185),
(196, 186), (196, 187), (196, 188), (196, 189), (196, 190), (196, 191), (196, 192), (196, 193), (196, 194), (196, 195), (196, 196), (196, 204), (196, 205), (197, 154), (197, 157), (197, 158), (197, 159), (197, 160), (197, 161), (197, 162), (197, 163), (197, 164), (197, 165), (197, 166), (197, 167), (197, 168), (197, 169), (197, 170), (197, 171), (197, 172), (197, 173), (197, 174), (197, 175), (197, 176), (197, 177), (197, 178), (197, 179), (197, 180), (197, 181), (197, 182), (197, 183), (197, 184), (197, 185), (197, 186), (197, 187), (197, 188), (197, 189), (197, 190), (197, 191), (197, 192), (197, 193), (197, 194), (197, 195), (197, 197), (197, 198), (197, 199), (197, 200), (197, 201), (197, 202), (198, 154), (198, 156), (198, 157), (198, 158), (198, 159), (198, 160), (198, 161), (198, 162), (198, 163), (198, 164), (198, 165), (198, 166), (198, 167),
(198, 168), (198, 169), (198, 170), (198, 171), (198, 172), (198, 173), (198, 174), (198, 175), (198, 176), (198, 177), (198, 178), (198, 179), (198, 180), (198, 181), (198, 182), (198, 183), (198, 184), (198, 185), (198, 186), (198, 187), (198, 188), (198, 189), (198, 190), (198, 191), (198, 192), (198, 193), (198, 194), (198, 195), (198, 196), (199, 154), (199, 156), (199, 157), (199, 158), (199, 159), (199, 160), (199, 161), (199, 162), (199, 163), (199, 164), (199, 165), (199, 166), (199, 167), (199, 168), (199, 169), (199, 170), (199, 171), (199, 172), (199, 173), (199, 174), (199, 175), (199, 176), (199, 177), (199, 178), (199, 179), (199, 180), (199, 181), (199, 182), (199, 183), (199, 184), (199, 185), (199, 186), (199, 187), (199, 188), (199, 189), (199, 190), (199, 191), (199, 192), (199, 193), (199, 195), (200, 154), (200, 156), (200, 157),
(200, 158), (200, 159), (200, 160), (200, 161), (200, 162), (200, 163), (200, 164), (200, 165), (200, 166), (200, 167), (200, 168), (200, 169), (200, 170), (200, 171), (200, 172), (200, 173), (200, 174), (200, 175), (200, 176), (200, 177), (200, 178), (200, 179), (200, 180), (200, 181), (200, 182), (200, 183), (200, 184), (200, 185), (200, 186), (200, 187), (200, 188), (200, 189), (200, 190), (200, 191), (200, 192), (200, 193), (200, 194), (200, 195), (201, 154), (201, 156), (201, 157), (201, 158), (201, 159), (201, 160), (201, 161), (201, 162), (201, 163), (201, 164), (201, 165), (201, 166), (201, 167), (201, 168), (201, 169), (201, 170), (201, 171), (201, 172), (201, 173), (201, 174), (201, 175), (201, 176), (201, 177), (201, 178), (201, 179), (201, 180), (201, 181), (201, 182), (201, 183), (201, 184), (201, 185), (201, 186), (201, 187), (201, 188),
(201, 189), (201, 190), (201, 191), (201, 192), (201, 193), (201, 194), (201, 195), (201, 196), (201, 197), (201, 198), (201, 199), (201, 200), (202, 154), (202, 158), (202, 159), (202, 160), (202, 161), (202, 162), (202, 163), (202, 164), (202, 165), (202, 166), (202, 167), (202, 168), (202, 169), (202, 170), (202, 171), (202, 172), (202, 173), (202, 174), (202, 175), (202, 176), (202, 177), (202, 178), (202, 179), (202, 180), (202, 181), (202, 182), (202, 183), (202, 184), (202, 185), (202, 186), (202, 187), (202, 188), (202, 189), (202, 190), (202, 191), (202, 192), (202, 193), (202, 194), (202, 195), (202, 201), (202, 203), (203, 156), (203, 160), (203, 161), (203, 162), (203, 163), (203, 164), (203, 165), (203, 166), (203, 167), (203, 168), (203, 169), (203, 170), (203, 171), (203, 172), (203, 173), (203, 174), (203, 175), (203, 176), (203, 177),
(203, 178), (203, 179), (203, 180), (203, 181), (203, 182), (203, 183), (203, 184), (203, 185), (203, 186), (203, 187), (203, 188), (203, 189), (203, 190), (203, 191), (203, 192), (203, 193), (203, 194), (203, 195), (203, 196), (203, 197), (203, 198), (203, 199), (203, 200), (203, 205), (204, 158), (204, 162), (204, 163), (204, 164), (204, 165), (204, 166), (204, 167), (204, 168), (204, 169), (204, 170), (204, 171), (204, 172), (204, 173), (204, 174), (204, 175), (204, 176), (204, 177), (204, 178), (204, 179), (204, 180), (204, 181), (204, 182), (204, 183), (204, 184), (204, 185), (204, 186), (204, 187), (204, 188), (204, 189), (204, 190), (204, 191), (204, 192), (204, 193), (204, 194), (204, 195), (204, 196), (204, 197), (204, 198), (204, 199), (204, 200), (204, 201), (204, 202), (204, 203), (204, 206), (205, 160), (205, 163), (205, 164), (205, 165),
(205, 166), (205, 167), (205, 168), (205, 169), (205, 170), (205, 171), (205, 172), (205, 173), (205, 174), (205, 175), (205, 176), (205, 177), (205, 178), (205, 179), (205, 180), (205, 181), (205, 182), (205, 183), (205, 184), (205, 185), (205, 186), (205, 187), (205, 188), (205, 189), (205, 190), (205, 191), (205, 192), (205, 193), (205, 194), (205, 195), (205, 196), (205, 197), (205, 198), (205, 199), (205, 200), (205, 201), (205, 206), (206, 162), (206, 175), (206, 176), (206, 177), (206, 178), (206, 179), (206, 180), (206, 181), (206, 182), (206, 183), (206, 184), (206, 185), (206, 186), (206, 187), (206, 188), (206, 189), (206, 190), (206, 191), (206, 192), (206, 193), (206, 194), (206, 195), (206, 196), (206, 197), (206, 198), (206, 202), (206, 203), (206, 204), (207, 164), (207, 165), (207, 166), (207, 167), (207, 168), (207, 169), (207, 170),
(207, 171), (207, 172), (207, 173), (207, 174), (207, 178), (207, 179), (207, 180), (207, 181), (207, 182), (207, 183), (207, 184), (207, 185), (207, 186), (207, 187), (207, 188), (207, 189), (207, 190), (207, 191), (207, 192), (207, 193), (207, 194), (207, 195), (207, 196), (207, 200), (207, 201), (208, 175), (208, 176), (208, 177), (208, 183), (208, 184), (208, 185), (208, 186), (208, 187), (208, 188), (208, 189), (208, 190), (208, 191), (208, 192), (208, 193), (208, 197), (208, 198), (209, 179), (209, 180), (209, 181), (209, 182), (209, 196), (210, 183), (210, 184), (210, 185), (210, 186), (210, 187), (210, 188), (210, 189), (210, 190), (210, 191), (210, 192), (210, 193), )
coordinates_7F002B = ((65, 268),
(65, 270), (66, 267), (66, 272), (67, 267), (67, 268), (67, 269), (67, 270), (67, 274), (68, 265), (68, 267), (68, 268), (68, 269), (68, 270), (68, 271), (68, 272), (68, 275), (69, 261), (69, 262), (69, 263), (69, 264), (69, 267), (69, 268), (69, 269), (69, 270), (69, 271), (69, 272), (69, 273), (69, 274), (69, 277), (70, 257), (70, 259), (70, 260), (70, 265), (70, 266), (70, 267), (70, 268), (70, 269), (70, 270), (70, 271), (70, 272), (70, 273), (70, 274), (70, 275), (70, 278), (71, 255), (71, 261), (71, 262), (71, 263), (71, 264), (71, 265), (71, 266), (71, 267), (71, 268), (71, 269), (71, 270), (71, 271), (71, 272), (71, 273), (71, 274), (71, 275), (71, 276), (71, 279), (72, 254), (72, 257), (72, 258), (72, 259), (72, 260), (72, 261), (72, 262), (72, 263), (72, 264), (72, 265),
(72, 266), (72, 267), (72, 268), (72, 269), (72, 270), (72, 271), (72, 272), (72, 273), (72, 274), (72, 275), (72, 276), (72, 277), (72, 278), (72, 280), (73, 254), (73, 256), (73, 257), (73, 258), (73, 259), (73, 260), (73, 261), (73, 262), (73, 263), (73, 264), (73, 265), (73, 266), (73, 267), (73, 268), (73, 269), (73, 270), (73, 271), (73, 272), (73, 273), (73, 274), (73, 275), (73, 276), (73, 277), (73, 278), (73, 279), (73, 281), (74, 253), (74, 255), (74, 256), (74, 257), (74, 258), (74, 259), (74, 260), (74, 261), (74, 262), (74, 263), (74, 264), (74, 265), (74, 266), (74, 267), (74, 268), (74, 269), (74, 270), (74, 271), (74, 272), (74, 273), (74, 274), (74, 275), (74, 276), (74, 277), (74, 278), (74, 279), (74, 280), (74, 282), (75, 253), (75, 255), (75, 256), (75, 257),
(75, 258), (75, 259), (75, 260), (75, 261), (75, 262), (75, 263), (75, 264), (75, 265), (75, 266), (75, 267), (75, 268), (75, 269), (75, 270), (75, 271), (75, 272), (75, 273), (75, 274), (75, 275), (75, 276), (75, 277), (75, 278), (75, 279), (75, 280), (75, 281), (75, 283), (76, 253), (76, 255), (76, 256), (76, 257), (76, 258), (76, 259), (76, 260), (76, 261), (76, 262), (76, 263), (76, 264), (76, 265), (76, 266), (76, 267), (76, 268), (76, 269), (76, 270), (76, 271), (76, 272), (76, 273), (76, 274), (76, 275), (76, 276), (76, 277), (76, 278), (76, 279), (76, 280), (76, 281), (76, 282), (76, 284), (77, 253), (77, 255), (77, 256), (77, 257), (77, 258), (77, 259), (77, 260), (77, 261), (77, 262), (77, 263), (77, 264), (77, 265), (77, 266), (77, 267), (77, 268), (77, 269), (77, 270),
(77, 271), (77, 272), (77, 273), (77, 274), (77, 275), (77, 276), (77, 277), (77, 278), (77, 279), (77, 280), (77, 281), (77, 282), (77, 283), (77, 285), (78, 239), (78, 240), (78, 253), (78, 256), (78, 257), (78, 258), (78, 259), (78, 260), (78, 261), (78, 262), (78, 263), (78, 264), (78, 265), (78, 266), (78, 267), (78, 268), (78, 269), (78, 270), (78, 271), (78, 272), (78, 273), (78, 274), (78, 275), (78, 276), (78, 277), (78, 278), (78, 279), (78, 280), (78, 281), (78, 282), (78, 283), (78, 284), (78, 286), (79, 238), (79, 242), (79, 254), (79, 255), (79, 259), (79, 260), (79, 261), (79, 262), (79, 263), (79, 264), (79, 265), (79, 266), (79, 267), (79, 268), (79, 269), (79, 270), (79, 271), (79, 272), (79, 273), (79, 274), (79, 275), (79, 276), (79, 277), (79, 278), (79, 279),
(79, 280), (79, 281), (79, 282), (79, 283), (79, 284), (79, 285), (79, 287), (80, 237), (80, 239), (80, 240), (80, 243), (80, 256), (80, 258), (80, 262), (80, 263), (80, 264), (80, 265), (80, 266), (80, 267), (80, 268), (80, 269), (80, 270), (80, 271), (80, 272), (80, 273), (80, 274), (80, 275), (80, 276), (80, 277), (80, 278), (80, 279), (80, 280), (80, 281), (80, 282), (80, 283), (80, 284), (80, 285), (80, 286), (80, 288), (81, 236), (81, 238), (81, 239), (81, 240), (81, 241), (81, 244), (81, 259), (81, 261), (81, 265), (81, 266), (81, 267), (81, 268), (81, 269), (81, 270), (81, 271), (81, 272), (81, 273), (81, 274), (81, 275), (81, 276), (81, 277), (81, 278), (81, 279), (81, 280), (81, 281), (81, 282), (81, 283), (81, 284), (81, 285), (81, 286), (81, 288), (82, 235), (82, 237),
(82, 238), (82, 239), (82, 240), (82, 241), (82, 242), (82, 245), (82, 263), (82, 264), (82, 267), (82, 268), (82, 269), (82, 270), (82, 271), (82, 272), (82, 273), (82, 274), (82, 275), (82, 276), (82, 277), (82, 278), (82, 279), (82, 280), (82, 281), (82, 282), (82, 283), (82, 284), (82, 285), (82, 286), (82, 287), (82, 289), (83, 235), (83, 237), (83, 238), (83, 239), (83, 240), (83, 241), (83, 242), (83, 243), (83, 246), (83, 265), (83, 269), (83, 270), (83, 271), (83, 272), (83, 273), (83, 274), (83, 275), (83, 276), (83, 277), (83, 278), (83, 279), (83, 280), (83, 281), (83, 282), (83, 283), (83, 284), (83, 285), (83, 286), (83, 287), (83, 288), (83, 290), (84, 234), (84, 236), (84, 237), (84, 238), (84, 239), (84, 240), (84, 241), (84, 242), (84, 243), (84, 244), (84, 267),
(84, 270), (84, 271), (84, 272), (84, 273), (84, 274), (84, 275), (84, 276), (84, 277), (84, 278), (84, 279), (84, 280), (84, 281), (84, 282), (84, 283), (84, 284), (84, 285), (84, 286), (84, 287), (84, 288), (84, 290), (85, 235), (85, 236), (85, 237), (85, 238), (85, 239), (85, 240), (85, 241), (85, 242), (85, 243), (85, 244), (85, 245), (85, 269), (85, 272), (85, 273), (85, 274), (85, 275), (85, 276), (85, 277), (85, 278), (85, 279), (85, 280), (85, 281), (85, 282), (85, 283), (85, 284), (85, 285), (85, 286), (85, 287), (85, 288), (85, 289), (85, 291), (86, 230), (86, 234), (86, 235), (86, 236), (86, 237), (86, 238), (86, 239), (86, 240), (86, 241), (86, 242), (86, 243), (86, 244), (86, 245), (86, 246), (86, 248), (86, 270), (86, 273), (86, 274), (86, 275), (86, 276), (86, 277),
(86, 278), (86, 279), (86, 280), (86, 281), (86, 282), (86, 283), (86, 284), (86, 285), (86, 286), (86, 287), (86, 288), (86, 289), (86, 290), (86, 292), (87, 230), (87, 232), (87, 233), (87, 234), (87, 235), (87, 236), (87, 237), (87, 238), (87, 239), (87, 240), (87, 241), (87, 242), (87, 243), (87, 244), (87, 245), (87, 246), (87, 247), (87, 249), (87, 274), (87, 275), (87, 276), (87, 277), (87, 278), (87, 279), (87, 280), (87, 281), (87, 282), (87, 283), (87, 284), (87, 285), (87, 286), (87, 287), (87, 288), (87, 289), (87, 290), (87, 292), (88, 231), (88, 233), (88, 234), (88, 235), (88, 236), (88, 237), (88, 238), (88, 239), (88, 240), (88, 241), (88, 242), (88, 243), (88, 244), (88, 245), (88, 246), (88, 247), (88, 248), (88, 250), (88, 273), (88, 275), (88, 276), (88, 277),
(88, 278), (88, 279), (88, 280), (88, 281), (88, 282), (88, 283), (88, 284), (88, 285), (88, 286), (88, 287), (88, 288), (88, 289), (88, 290), (88, 291), (88, 293), (89, 232), (89, 235), (89, 236), (89, 237), (89, 238), (89, 239), (89, 240), (89, 241), (89, 242), (89, 243), (89, 244), (89, 245), (89, 246), (89, 247), (89, 248), (89, 249), (89, 251), (89, 274), (89, 277), (89, 278), (89, 279), (89, 280), (89, 281), (89, 282), (89, 283), (89, 284), (89, 285), (89, 286), (89, 287), (89, 288), (89, 289), (89, 290), (89, 291), (89, 293), (90, 233), (90, 236), (90, 237), (90, 238), (90, 239), (90, 240), (90, 241), (90, 242), (90, 243), (90, 244), (90, 245), (90, 246), (90, 247), (90, 248), (90, 249), (90, 250), (90, 252), (90, 275), (90, 278), (90, 279), (90, 280), (90, 281), (90, 282),
(90, 283), (90, 284), (90, 285), (90, 286), (90, 287), (90, 288), (90, 289), (90, 290), (90, 291), (90, 293), (91, 235), (91, 238), (91, 239), (91, 240), (91, 241), (91, 242), (91, 243), (91, 244), (91, 245), (91, 246), (91, 247), (91, 248), (91, 249), (91, 250), (91, 251), (91, 253), (91, 277), (91, 279), (91, 280), (91, 281), (91, 282), (91, 283), (91, 284), (91, 285), (91, 286), (91, 287), (91, 288), (91, 289), (91, 290), (91, 291), (91, 292), (91, 294), (92, 236), (92, 240), (92, 241), (92, 242), (92, 243), (92, 244), (92, 245), (92, 246), (92, 247), (92, 248), (92, 249), (92, 250), (92, 251), (92, 253), (92, 278), (92, 280), (92, 281), (92, 282), (92, 283), (92, 284), (92, 285), (92, 286), (92, 287), (92, 288), (92, 289), (92, 290), (92, 291), (92, 292), (92, 294), (93, 238),
(93, 241), (93, 242), (93, 243), (93, 244), (93, 245), (93, 246), (93, 247), (93, 248), (93, 249), (93, 250), (93, 252), (93, 279), (93, 281), (93, 282), (93, 283), (93, 284), (93, 285), (93, 286), (93, 287), (93, 288), (93, 289), (93, 290), (93, 291), (93, 292), (93, 294), (94, 240), (94, 242), (94, 243), (94, 244), (94, 245), (94, 246), (94, 247), (94, 248), (94, 249), (94, 251), (94, 280), (94, 282), (94, 283), (94, 284), (94, 285), (94, 286), (94, 287), (94, 288), (94, 289), (94, 290), (94, 291), (94, 293), (95, 241), (95, 243), (95, 244), (95, 245), (95, 246), (95, 247), (95, 248), (95, 250), (95, 281), (95, 283), (95, 284), (95, 285), (95, 286), (95, 287), (95, 288), (95, 289), (95, 290), (95, 293), (96, 242), (96, 244), (96, 245), (96, 246), (96, 247), (96, 249), (96, 282),
(96, 284), (96, 285), (96, 286), (96, 287), (96, 288), (96, 289), (96, 290), (96, 292), (97, 243), (97, 248), (97, 284), (97, 285), (97, 286), (97, 287), (97, 288), (97, 291), (98, 244), (98, 247), (98, 283), (98, 285), (98, 286), (98, 287), (98, 290), (99, 284), (99, 286), (99, 289), (100, 284), (100, 287), (101, 285), (101, 286), (298, 285), (298, 286), (299, 284), (299, 287), (300, 244), (300, 284), (300, 286), (300, 289), (301, 244), (301, 247), (301, 283), (301, 285), (301, 286), (301, 287), (301, 290), (302, 243), (302, 282), (302, 284), (302, 285), (302, 286), (302, 287), (302, 288), (302, 291), (303, 242), (303, 244), (303, 245), (303, 246), (303, 247), (303, 249), (303, 282), (303, 284), (303, 285), (303, 286), (303, 287), (303, 288), (303, 289), (303, 290), (303, 292), (304, 241), (304, 243), (304, 244), (304, 245),
(304, 246), (304, 247), (304, 248), (304, 250), (304, 281), (304, 283), (304, 284), (304, 285), (304, 286), (304, 287), (304, 288), (304, 289), (304, 290), (304, 291), (304, 293), (305, 242), (305, 243), (305, 244), (305, 245), (305, 246), (305, 247), (305, 248), (305, 249), (305, 251), (305, 280), (305, 282), (305, 283), (305, 284), (305, 285), (305, 286), (305, 287), (305, 288), (305, 289), (305, 290), (305, 291), (305, 293), (306, 238), (306, 241), (306, 242), (306, 243), (306, 244), (306, 245), (306, 246), (306, 247), (306, 248), (306, 249), (306, 250), (306, 252), (306, 279), (306, 281), (306, 282), (306, 283), (306, 284), (306, 285), (306, 286), (306, 287), (306, 288), (306, 289), (306, 290), (306, 291), (306, 292), (306, 294), (307, 236), (307, 240), (307, 241), (307, 242), (307, 243), (307, 244), (307, 245), (307, 246), (307, 247), (307, 248),
(307, 249), (307, 250), (307, 251), (307, 253), (307, 278), (307, 280), (307, 281), (307, 282), (307, 283), (307, 284), (307, 285), (307, 286), (307, 287), (307, 288), (307, 289), (307, 290), (307, 291), (307, 292), (307, 294), (308, 235), (308, 238), (308, 239), (308, 240), (308, 241), (308, 242), (308, 243), (308, 244), (308, 245), (308, 246), (308, 247), (308, 248), (308, 249), (308, 250), (308, 251), (308, 253), (308, 279), (308, 280), (308, 281), (308, 282), (308, 283), (308, 284), (308, 285), (308, 286), (308, 287), (308, 288), (308, 289), (308, 290), (308, 291), (308, 292), (308, 294), (309, 233), (309, 236), (309, 237), (309, 238), (309, 239), (309, 240), (309, 241), (309, 242), (309, 243), (309, 244), (309, 245), (309, 246), (309, 247), (309, 248), (309, 249), (309, 250), (309, 252), (309, 275), (309, 278), (309, 279), (309, 280), (309, 281),
(309, 282), (309, 283), (309, 284), (309, 285), (309, 286), (309, 287), (309, 288), (309, 289), (309, 290), (309, 291), (309, 293), (310, 232), (310, 235), (310, 236), (310, 237), (310, 238), (310, 239), (310, 240), (310, 241), (310, 242), (310, 243), (310, 244), (310, 245), (310, 246), (310, 247), (310, 248), (310, 249), (310, 251), (310, 274), (310, 277), (310, 278), (310, 279), (310, 280), (310, 281), (310, 282), (310, 283), (310, 284), (310, 285), (310, 286), (310, 287), (310, 288), (310, 289), (310, 290), (310, 291), (310, 293), (311, 231), (311, 233), (311, 234), (311, 235), (311, 236), (311, 237), (311, 238), (311, 239), (311, 240), (311, 241), (311, 242), (311, 243), (311, 244), (311, 245), (311, 246), (311, 247), (311, 248), (311, 250), (311, 273), (311, 275), (311, 276), (311, 277), (311, 278), (311, 279), (311, 280), (311, 281), (311, 282),
(311, 283), (311, 284), (311, 285), (311, 286), (311, 287), (311, 288), (311, 289), (311, 290), (311, 291), (311, 293), (312, 230), (312, 232), (312, 233), (312, 234), (312, 235), (312, 236), (312, 237), (312, 238), (312, 239), (312, 240), (312, 241), (312, 242), (312, 243), (312, 244), (312, 245), (312, 246), (312, 247), (312, 249), (312, 271), (312, 274), (312, 275), (312, 276), (312, 277), (312, 278), (312, 279), (312, 280), (312, 281), (312, 282), (312, 283), (312, 284), (312, 285), (312, 286), (312, 287), (312, 288), (312, 289), (312, 290), (312, 292), (313, 230), (313, 234), (313, 235), (313, 236), (313, 237), (313, 238), (313, 239), (313, 240), (313, 241), (313, 242), (313, 243), (313, 244), (313, 245), (313, 246), (313, 248), (313, 270), (313, 273), (313, 274), (313, 275), (313, 276), (313, 277), (313, 278), (313, 279), (313, 280), (313, 281),
(313, 282), (313, 283), (313, 284), (313, 285), (313, 286), (313, 287), (313, 288), (313, 289), (313, 290), (313, 292), (314, 235), (314, 236), (314, 237), (314, 238), (314, 239), (314, 240), (314, 241), (314, 242), (314, 243), (314, 244), (314, 245), (314, 247), (314, 268), (314, 271), (314, 272), (314, 273), (314, 274), (314, 275), (314, 276), (314, 277), (314, 278), (314, 279), (314, 280), (314, 281), (314, 282), (314, 283), (314, 284), (314, 285), (314, 286), (314, 287), (314, 288), (314, 289), (314, 291), (315, 234), (315, 236), (315, 237), (315, 238), (315, 239), (315, 240), (315, 241), (315, 242), (315, 243), (315, 244), (315, 267), (315, 270), (315, 271), (315, 272), (315, 273), (315, 274), (315, 275), (315, 276), (315, 277), (315, 278), (315, 279), (315, 280), (315, 281), (315, 282), (315, 283), (315, 284), (315, 285), (315, 286), (315, 287),
(315, 288), (315, 290), (316, 235), (316, 237), (316, 238), (316, 239), (316, 240), (316, 241), (316, 242), (316, 243), (316, 265), (316, 268), (316, 269), (316, 270), (316, 271), (316, 272), (316, 273), (316, 274), (316, 275), (316, 276), (316, 277), (316, 278), (316, 279), (316, 280), (316, 281), (316, 282), (316, 283), (316, 284), (316, 285), (316, 286), (316, 287), (316, 288), (316, 290), (317, 235), (317, 237), (317, 238), (317, 239), (317, 240), (317, 241), (317, 242), (317, 245), (317, 262), (317, 263), (317, 264), (317, 267), (317, 268), (317, 269), (317, 270), (317, 271), (317, 272), (317, 273), (317, 274), (317, 275), (317, 276), (317, 277), (317, 278), (317, 279), (317, 280), (317, 281), (317, 282), (317, 283), (317, 284), (317, 285), (317, 286), (317, 287), (317, 289), (318, 236), (318, 238), (318, 239), (318, 240), (318, 241), (318, 244),
(318, 259), (318, 261), (318, 265), (318, 266), (318, 267), (318, 268), (318, 269), (318, 270), (318, 271), (318, 272), (318, 273), (318, 274), (318, 275), (318, 276), (318, 277), (318, 278), (318, 279), (318, 280), (318, 281), (318, 282), (318, 283), (318, 284), (318, 285), (318, 286), (318, 288), (319, 237), (319, 239), (319, 240), (319, 243), (319, 256), (319, 258), (319, 262), (319, 263), (319, 264), (319, 265), (319, 266), (319, 267), (319, 268), (319, 269), (319, 270), (319, 271), (319, 272), (319, 273), (319, 274), (319, 275), (319, 276), (319, 277), (319, 278), (319, 279), (319, 280), (319, 281), (319, 282), (319, 283), (319, 284), (319, 285), (320, 238), (320, 254), (320, 259), (320, 260), (320, 261), (320, 262), (320, 263), (320, 264), (320, 265), (320, 266), (320, 267), (320, 268), (320, 269), (320, 270), (320, 271), (320, 272), (320, 273),
(320, 274), (320, 275), (320, 276), (320, 277), (320, 278), (320, 279), (320, 280), (320, 281), (320, 282), (320, 283), (320, 284), (320, 285), (320, 287), (321, 239), (321, 240), (321, 253), (321, 256), (321, 257), (321, 258), (321, 259), (321, 260), (321, 261), (321, 262), (321, 263), (321, 264), (321, 265), (321, 266), (321, 267), (321, 268), (321, 269), (321, 270), (321, 271), (321, 272), (321, 273), (321, 274), (321, 275), (321, 276), (321, 277), (321, 278), (321, 279), (321, 280), (321, 281), (321, 282), (321, 283), (321, 284), (321, 286), (322, 253), (322, 255), (322, 256), (322, 257), (322, 258), (322, 259), (322, 260), (322, 261), (322, 262), (322, 263), (322, 264), (322, 265), (322, 266), (322, 267), (322, 268), (322, 269), (322, 270), (322, 271), (322, 272), (322, 273), (322, 274), (322, 275), (322, 276), (322, 277), (322, 278), (322, 279),
(322, 280), (322, 281), (322, 282), (322, 283), (322, 285), (323, 253), (323, 255), (323, 256), (323, 257), (323, 258), (323, 259), (323, 260), (323, 261), (323, 262), (323, 263), (323, 264), (323, 265), (323, 266), (323, 267), (323, 268), (323, 269), (323, 270), (323, 271), (323, 272), (323, 273), (323, 274), (323, 275), (323, 276), (323, 277), (323, 278), (323, 279), (323, 280), (323, 281), (323, 282), (323, 284), (324, 253), (324, 255), (324, 256), (324, 257), (324, 258), (324, 259), (324, 260), (324, 261), (324, 262), (324, 263), (324, 264), (324, 265), (324, 266), (324, 267), (324, 268), (324, 269), (324, 270), (324, 271), (324, 272), (324, 273), (324, 274), (324, 275), (324, 276), (324, 277), (324, 278), (324, 279), (324, 280), (324, 281), (324, 283), (325, 253), (325, 255), (325, 256), (325, 257), (325, 258), (325, 259), (325, 260), (325, 261),
(325, 262), (325, 263), (325, 264), (325, 265), (325, 266), (325, 267), (325, 268), (325, 269), (325, 270), (325, 271), (325, 272), (325, 273), (325, 274), (325, 275), (325, 276), (325, 277), (325, 278), (325, 279), (325, 280), (325, 282), (326, 254), (326, 256), (326, 257), (326, 258), (326, 259), (326, 260), (326, 261), (326, 262), (326, 263), (326, 264), (326, 265), (326, 266), (326, 267), (326, 268), (326, 269), (326, 270), (326, 271), (326, 272), (326, 273), (326, 274), (326, 275), (326, 276), (326, 277), (326, 278), (326, 279), (326, 281), (327, 254), (327, 257), (327, 258), (327, 259), (327, 260), (327, 261), (327, 262), (327, 263), (327, 264), (327, 265), (327, 266), (327, 267), (327, 268), (327, 269), (327, 270), (327, 271), (327, 272), (327, 273), (327, 274), (327, 275), (327, 276), (327, 277), (327, 278), (327, 280), (328, 255), (328, 261),
(328, 262), (328, 263), (328, 264), (328, 265), (328, 266), (328, 267), (328, 268), (328, 269), (328, 270), (328, 271), (328, 272), (328, 273), (328, 274), (328, 275), (328, 276), (328, 279), (329, 257), (329, 259), (329, 260), (329, 265), (329, 266), (329, 267), (329, 268), (329, 269), (329, 270), (329, 271), (329, 272), (329, 273), (329, 274), (329, 275), (329, 278), (330, 261), (330, 262), (330, 263), (330, 264), (330, 267), (330, 268), (330, 269), (330, 270), (330, 271), (330, 272), (330, 273), (330, 274), (330, 276), (331, 265), (331, 267), (331, 268), (331, 269), (331, 270), (331, 271), (331, 272), (331, 275), (332, 267), (332, 269), (332, 270), (332, 274), (333, 267), (333, 272), (334, 268), (334, 270), )
coordinates_C3FF00 = ((94, 296),
(95, 295), (95, 297), (96, 294), (96, 297), (97, 293), (97, 295), (97, 296), (97, 298), (98, 292), (98, 294), (98, 295), (98, 296), (98, 298), (99, 291), (99, 293), (99, 294), (99, 295), (99, 296), (99, 297), (99, 299), (100, 290), (100, 292), (100, 293), (100, 294), (100, 295), (100, 296), (100, 297), (100, 299), (101, 289), (101, 291), (101, 292), (101, 293), (101, 294), (101, 295), (101, 296), (101, 297), (101, 299), (102, 287), (102, 290), (102, 291), (102, 292), (102, 293), (102, 294), (102, 295), (102, 296), (102, 297), (102, 298), (102, 300), (103, 285), (103, 286), (103, 289), (103, 290), (103, 291), (103, 292), (103, 293), (103, 294), (103, 295), (103, 296), (103, 297), (103, 298), (103, 300), (104, 268), (104, 283), (104, 287), (104, 288), (104, 289), (104, 290), (104, 291), (104, 292), (104, 293), (104, 294), (104, 295),
(104, 296), (104, 297), (104, 298), (104, 299), (104, 301), (105, 268), (105, 270), (105, 271), (105, 282), (105, 285), (105, 286), (105, 287), (105, 288), (105, 289), (105, 290), (105, 291), (105, 292), (105, 293), (105, 294), (105, 295), (105, 296), (105, 297), (105, 298), (105, 299), (105, 300), (105, 302), (106, 268), (106, 272), (106, 282), (106, 284), (106, 285), (106, 286), (106, 287), (106, 288), (106, 289), (106, 290), (106, 291), (106, 292), (106, 293), (106, 294), (106, 295), (106, 296), (106, 297), (106, 298), (106, 299), (106, 300), (106, 301), (106, 303), (107, 269), (107, 271), (107, 274), (107, 282), (107, 284), (107, 285), (107, 286), (107, 287), (107, 288), (107, 289), (107, 290), (107, 291), (107, 292), (107, 293), (107, 294), (107, 295), (107, 296), (107, 297), (107, 298), (107, 299), (107, 300), (107, 301), (107, 303), (108, 269),
(108, 271), (108, 272), (108, 273), (108, 276), (108, 282), (108, 284), (108, 285), (108, 286), (108, 287), (108, 288), (108, 289), (108, 290), (108, 291), (108, 292), (108, 293), (108, 294), (108, 295), (108, 296), (108, 297), (108, 298), (108, 299), (108, 300), (108, 301), (108, 302), (108, 304), (109, 269), (109, 271), (109, 272), (109, 273), (109, 274), (109, 277), (109, 278), (109, 281), (109, 283), (109, 284), (109, 285), (109, 286), (109, 287), (109, 288), (109, 289), (109, 290), (109, 291), (109, 292), (109, 293), (109, 294), (109, 295), (109, 296), (109, 297), (109, 298), (109, 299), (109, 300), (109, 301), (109, 302), (109, 303), (109, 305), (110, 269), (110, 271), (110, 272), (110, 273), (110, 274), (110, 275), (110, 276), (110, 279), (110, 282), (110, 283), (110, 284), (110, 285), (110, 286), (110, 287), (110, 288), (110, 289), (110, 290),
(110, 291), (110, 292), (110, 293), (110, 294), (110, 295), (110, 296), (110, 297), (110, 298), (110, 299), (110, 300), (110, 301), (110, 302), (110, 303), (110, 305), (111, 270), (111, 272), (111, 273), (111, 274), (111, 275), (111, 276), (111, 277), (111, 278), (111, 281), (111, 282), (111, 283), (111, 284), (111, 285), (111, 286), (111, 287), (111, 288), (111, 289), (111, 290), (111, 291), (111, 292), (111, 293), (111, 294), (111, 295), (111, 296), (111, 297), (111, 298), (111, 299), (111, 300), (111, 301), (111, 302), (111, 303), (111, 304), (111, 306), (112, 270), (112, 272), (112, 273), (112, 274), (112, 275), (112, 276), (112, 277), (112, 278), (112, 279), (112, 280), (112, 281), (112, 282), (112, 283), (112, 284), (112, 285), (112, 286), (112, 287), (112, 288), (112, 289), (112, 290), (112, 291), (112, 292), (112, 293), (112, 294), (112, 295),
(112, 296), (112, 297), (112, 298), (112, 299), (112, 300), (112, 301), (112, 302), (112, 303), (112, 304), (112, 306), (113, 270), (113, 272), (113, 273), (113, 274), (113, 275), (113, 276), (113, 277), (113, 278), (113, 279), (113, 280), (113, 281), (113, 282), (113, 283), (113, 284), (113, 285), (113, 286), (113, 287), (113, 288), (113, 289), (113, 290), (113, 291), (113, 292), (113, 293), (113, 294), (113, 295), (113, 296), (113, 297), (113, 298), (113, 299), (113, 300), (113, 301), (113, 302), (113, 303), (113, 304), (113, 306), (114, 270), (114, 272), (114, 273), (114, 274), (114, 275), (114, 276), (114, 277), (114, 278), (114, 279), (114, 280), (114, 281), (114, 282), (114, 283), (114, 284), (114, 285), (114, 286), (114, 287), (114, 288), (114, 289), (114, 290), (114, 291), (114, 292), (114, 293), (114, 294), (114, 295), (114, 296), (114, 297),
(114, 298), (114, 299), (114, 300), (114, 301), (114, 302), (114, 303), (114, 304), (114, 306), (115, 270), (115, 272), (115, 273), (115, 274), (115, 275), (115, 276), (115, 277), (115, 278), (115, 279), (115, 280), (115, 281), (115, 282), (115, 283), (115, 284), (115, 285), (115, 286), (115, 287), (115, 288), (115, 289), (115, 290), (115, 291), (115, 292), (115, 293), (115, 294), (115, 295), (115, 296), (115, 297), (115, 298), (115, 299), (115, 300), (115, 301), (115, 302), (115, 303), (115, 304), (115, 306), (116, 269), (116, 271), (116, 272), (116, 273), (116, 274), (116, 275), (116, 276), (116, 277), (116, 278), (116, 279), (116, 280), (116, 281), (116, 282), (116, 283), (116, 284), (116, 285), (116, 286), (116, 287), (116, 288), (116, 289), (116, 290), (116, 291), (116, 292), (116, 293), (116, 294), (116, 295), (116, 296), (116, 297), (116, 298),
(116, 299), (116, 300), (116, 301), (116, 302), (116, 303), (116, 304), (116, 305), (116, 306), (116, 307), (117, 265), (117, 266), (117, 269), (117, 271), (117, 272), (117, 273), (117, 274), (117, 275), (117, 276), (117, 277), (117, 278), (117, 279), (117, 280), (117, 281), (117, 282), (117, 283), (117, 284), (117, 285), (117, 286), (117, 287), (117, 288), (117, 289), (117, 290), (117, 291), (117, 292), (117, 293), (117, 294), (117, 295), (117, 296), (117, 297), (117, 298), (117, 299), (117, 300), (117, 301), (117, 302), (117, 303), (117, 304), (117, 305), (117, 307), (118, 264), (118, 269), (118, 270), (118, 271), (118, 272), (118, 273), (118, 274), (118, 275), (118, 276), (118, 277), (118, 278), (118, 279), (118, 280), (118, 281), (118, 282), (118, 283), (118, 284), (118, 285), (118, 286), (118, 287), (118, 288), (118, 289), (118, 290), (118, 291),
(118, 292), (118, 293), (118, 294), (118, 295), (118, 296), (118, 297), (118, 298), (118, 299), (118, 300), (118, 301), (118, 302), (118, 303), (118, 304), (118, 305), (118, 307), (119, 264), (119, 266), (119, 269), (119, 270), (119, 271), (119, 272), (119, 273), (119, 274), (119, 275), (119, 276), (119, 277), (119, 278), (119, 279), (119, 280), (119, 281), (119, 282), (119, 283), (119, 284), (119, 285), (119, 286), (119, 287), (119, 288), (119, 289), (119, 290), (119, 291), (119, 292), (119, 293), (119, 294), (119, 295), (119, 296), (119, 297), (119, 298), (119, 299), (119, 300), (119, 301), (119, 302), (119, 303), (119, 304), (119, 305), (119, 307), (120, 264), (120, 266), (120, 267), (120, 268), (120, 269), (120, 270), (120, 271), (120, 272), (120, 273), (120, 274), (120, 275), (120, 276), (120, 277), (120, 278), (120, 279), (120, 280), (120, 281),
(120, 282), (120, 283), (120, 284), (120, 285), (120, 286), (120, 287), (120, 288), (120, 289), (120, 290), (120, 291), (120, 292), (120, 293), (120, 294), (120, 295), (120, 296), (120, 297), (120, 298), (120, 299), (120, 300), (120, 301), (120, 302), (120, 303), (120, 304), (120, 305), (120, 307), (121, 263), (121, 264), (121, 265), (121, 266), (121, 267), (121, 268), (121, 269), (121, 270), (121, 271), (121, 272), (121, 273), (121, 274), (121, 275), (121, 276), (121, 277), (121, 278), (121, 279), (121, 280), (121, 281), (121, 282), (121, 283), (121, 284), (121, 285), (121, 286), (121, 287), (121, 288), (121, 289), (121, 290), (121, 291), (121, 292), (121, 293), (121, 294), (121, 295), (121, 296), (121, 297), (121, 298), (121, 299), (121, 300), (121, 301), (121, 302), (121, 303), (121, 304), (121, 305), (121, 306), (121, 307), (122, 263), (122, 265),
(122, 266), (122, 267), (122, 268), (122, 269), (122, 270), (122, 271), (122, 272), (122, 273), (122, 274), (122, 275), (122, 276), (122, 277), (122, 278), (122, 279), (122, 280), (122, 281), (122, 282), (122, 283), (122, 284), (122, 285), (122, 286), (122, 287), (122, 288), (122, 289), (122, 290), (122, 291), (122, 292), (122, 293), (122, 294), (122, 295), (122, 296), (122, 297), (122, 298), (122, 299), (122, 300), (122, 301), (122, 302), (122, 303), (122, 304), (122, 306), (123, 263), (123, 265), (123, 266), (123, 267), (123, 268), (123, 269), (123, 270), (123, 271), (123, 272), (123, 273), (123, 274), (123, 275), (123, 276), (123, 277), (123, 278), (123, 279), (123, 280), (123, 281), (123, 282), (123, 283), (123, 284), (123, 285), (123, 286), (123, 287), (123, 288), (123, 289), (123, 290), (123, 291), (123, 292), (123, 293), (123, 294), (123, 295),
(123, 296), (123, 297), (123, 298), (123, 299), (123, 300), (123, 301), (123, 302), (123, 303), (123, 304), (123, 306), (124, 263), (124, 265), (124, 266), (124, 267), (124, 268), (124, 269), (124, 270), (124, 271), (124, 272), (124, 273), (124, 274), (124, 275), (124, 276), (124, 277), (124, 278), (124, 279), (124, 280), (124, 281), (124, 282), (124, 283), (124, 284), (124, 285), (124, 286), (124, 287), (124, 288), (124, 289), (124, 290), (124, 291), (124, 292), (124, 293), (124, 294), (124, 295), (124, 296), (124, 297), (124, 298), (124, 299), (124, 300), (124, 301), (124, 302), (124, 303), (124, 304), (124, 306), (125, 263), (125, 265), (125, 266), (125, 267), (125, 268), (125, 269), (125, 270), (125, 271), (125, 272), (125, 273), (125, 274), (125, 275), (125, 276), (125, 277), (125, 278), (125, 279), (125, 280), (125, 281), (125, 282), (125, 283),
(125, 284), (125, 285), (125, 286), (125, 287), (125, 288), (125, 289), (125, 290), (125, 291), (125, 292), (125, 293), (125, 294), (125, 295), (125, 296), (125, 297), (125, 298), (125, 299), (125, 300), (125, 301), (125, 302), (125, 303), (125, 304), (125, 306), (126, 263), (126, 265), (126, 266), (126, 267), (126, 268), (126, 269), (126, 270), (126, 271), (126, 272), (126, 273), (126, 274), (126, 275), (126, 276), (126, 277), (126, 278), (126, 279), (126, 280), (126, 281), (126, 282), (126, 283), (126, 284), (126, 285), (126, 286), (126, 287), (126, 288), (126, 289), (126, 290), (126, 291), (126, 292), (126, 293), (126, 294), (126, 295), (126, 296), (126, 297), (126, 298), (126, 299), (126, 300), (126, 301), (126, 302), (126, 303), (126, 304), (126, 306), (127, 263), (127, 265), (127, 266), (127, 267), (127, 268), (127, 269), (127, 270), (127, 271),
(127, 272), (127, 273), (127, 274), (127, 275), (127, 276), (127, 277), (127, 278), (127, 279), (127, 280), (127, 281), (127, 282), (127, 283), (127, 284), (127, 285), (127, 286), (127, 287), (127, 288), (127, 289), (127, 290), (127, 291), (127, 292), (127, 293), (127, 294), (127, 295), (127, 296), (127, 297), (127, 298), (127, 299), (127, 300), (127, 301), (127, 302), (127, 303), (127, 305), (128, 263), (128, 265), (128, 266), (128, 267), (128, 268), (128, 269), (128, 270), (128, 271), (128, 272), (128, 273), (128, 274), (128, 275), (128, 276), (128, 277), (128, 278), (128, 279), (128, 280), (128, 281), (128, 282), (128, 283), (128, 284), (128, 285), (128, 286), (128, 287), (128, 288), (128, 289), (128, 290), (128, 291), (128, 292), (128, 293), (128, 294), (128, 295), (128, 296), (128, 297), (128, 298), (128, 299), (128, 300), (128, 301), (128, 302),
(128, 303), (128, 305), (129, 263), (129, 265), (129, 266), (129, 267), (129, 268), (129, 269), (129, 270), (129, 271), (129, 272), (129, 273), (129, 274), (129, 275), (129, 276), (129, 277), (129, 278), (129, 279), (129, 280), (129, 281), (129, 282), (129, 283), (129, 284), (129, 285), (129, 286), (129, 287), (129, 288), (129, 289), (129, 290), (129, 291), (129, 292), (129, 293), (129, 294), (129, 295), (129, 296), (129, 297), (129, 298), (129, 299), (129, 300), (129, 301), (129, 302), (129, 303), (129, 305), (130, 263), (130, 265), (130, 266), (130, 267), (130, 268), (130, 269), (130, 270), (130, 271), (130, 272), (130, 273), (130, 274), (130, 275), (130, 276), (130, 277), (130, 278), (130, 279), (130, 280), (130, 281), (130, 282), (130, 283), (130, 284), (130, 285), (130, 286), (130, 287), (130, 288), (130, 289), (130, 290), (130, 291), (130, 292),
(130, 293), (130, 294), (130, 295), (130, 296), (130, 297), (130, 298), (130, 299), (130, 300), (130, 301), (130, 302), (130, 304), (131, 264), (131, 266), (131, 267), (131, 268), (131, 269), (131, 270), (131, 271), (131, 272), (131, 273), (131, 274), (131, 275), (131, 276), (131, 277), (131, 278), (131, 279), (131, 280), (131, 281), (131, 282), (131, 283), (131, 284), (131, 285), (131, 286), (131, 287), (131, 288), (131, 289), (131, 290), (131, 291), (131, 292), (131, 293), (131, 294), (131, 295), (131, 296), (131, 297), (131, 298), (131, 299), (131, 300), (131, 301), (131, 302), (131, 304), (132, 264), (132, 266), (132, 267), (132, 268), (132, 269), (132, 270), (132, 271), (132, 272), (132, 273), (132, 274), (132, 275), (132, 276), (132, 277), (132, 278), (132, 279), (132, 280), (132, 281), (132, 282), (132, 283), (132, 284), (132, 285), (132, 286),
(132, 287), (132, 288), (132, 289), (132, 290), (132, 291), (132, 292), (132, 293), (132, 294), (132, 295), (132, 296), (132, 297), (132, 298), (132, 299), (132, 300), (132, 301), (132, 303), (133, 265), (133, 267), (133, 268), (133, 269), (133, 270), (133, 271), (133, 272), (133, 273), (133, 274), (133, 275), (133, 276), (133, 277), (133, 278), (133, 279), (133, 280), (133, 281), (133, 282), (133, 283), (133, 284), (133, 285), (133, 286), (133, 287), (133, 288), (133, 289), (133, 290), (133, 291), (133, 292), (133, 293), (133, 294), (133, 295), (133, 296), (133, 297), (133, 298), (133, 299), (133, 300), (133, 301), (133, 303), (134, 265), (134, 269), (134, 270), (134, 271), (134, 272), (134, 273), (134, 274), (134, 275), (134, 276), (134, 277), (134, 278), (134, 279), (134, 280), (134, 281), (134, 282), (134, 283), (134, 284), (134, 285), (134, 286),
(134, 287), (134, 288), (134, 289), (134, 290), (134, 291), (134, 292), (134, 293), (134, 294), (134, 295), (134, 296), (134, 297), (134, 298), (134, 299), (134, 300), (134, 302), (135, 266), (135, 268), (135, 271), (135, 272), (135, 273), (135, 274), (135, 275), (135, 276), (135, 277), (135, 278), (135, 279), (135, 280), (135, 281), (135, 282), (135, 283), (135, 284), (135, 285), (135, 286), (135, 287), (135, 288), (135, 289), (135, 290), (135, 291), (135, 292), (135, 293), (135, 294), (135, 295), (135, 296), (135, 297), (135, 298), (135, 299), (135, 301), (136, 269), (136, 278), (136, 279), (136, 280), (136, 281), (136, 282), (136, 283), (136, 284), (136, 285), (136, 286), (136, 287), (136, 288), (136, 289), (136, 290), (136, 291), (136, 292), (136, 293), (136, 294), (136, 295), (136, 296), (136, 297), (136, 298), (136, 300), (137, 271), (137, 273),
(137, 274), (137, 275), (137, 276), (137, 277), (137, 280), (137, 281), (137, 282), (137, 283), (137, 284), (137, 285), (137, 286), (137, 287), (137, 288), (137, 289), (137, 290), (137, 291), (137, 292), (137, 293), (137, 294), (137, 295), (137, 299), (138, 279), (138, 283), (138, 284), (138, 285), (138, 286), (138, 287), (138, 288), (138, 289), (138, 290), (138, 291), (138, 292), (138, 293), (138, 297), (139, 280), (139, 281), (139, 282), (139, 287), (139, 288), (139, 289), (139, 294), (139, 295), (140, 283), (140, 285), (140, 286), (140, 290), (140, 291), (140, 293), (141, 287), (141, 288), (141, 289), (258, 286), (258, 287), (258, 288), (258, 289), (259, 283), (259, 284), (259, 285), (259, 286), (259, 290), (259, 291), (259, 293), (260, 280), (260, 286), (260, 287), (260, 288), (260, 289), (260, 290), (260, 294), (260, 295), (261, 278), (261, 279),
(261, 283), (261, 284), (261, 285), (261, 286), (261, 287), (261, 288), (261, 289), (261, 290), (261, 291), (261, 292), (261, 293), (261, 297), (261, 298), (262, 270), (262, 271), (262, 272), (262, 273), (262, 274), (262, 275), (262, 276), (262, 277), (262, 280), (262, 281), (262, 282), (262, 283), (262, 284), (262, 285), (262, 286), (262, 287), (262, 288), (262, 289), (262, 290), (262, 291), (262, 292), (262, 293), (262, 294), (262, 295), (262, 296), (262, 299), (263, 269), (263, 278), (263, 279), (263, 280), (263, 281), (263, 282), (263, 283), (263, 284), (263, 285), (263, 286), (263, 287), (263, 288), (263, 289), (263, 290), (263, 291), (263, 292), (263, 293), (263, 294), (263, 295), (263, 296), (263, 297), (263, 298), (264, 266), (264, 268), (264, 270), (264, 271), (264, 272), (264, 273), (264, 274), (264, 275), (264, 276), (264, 277), (264, 278),
(264, 279), (264, 280), (264, 281), (264, 282), (264, 283), (264, 284), (264, 285), (264, 286), (264, 287), (264, 288), (264, 289), (264, 290), (264, 291), (264, 292), (264, 293), (264, 294), (264, 295), (264, 296), (264, 297), (264, 298), (264, 299), (265, 265), (265, 269), (265, 270), (265, 271), (265, 272), (265, 273), (265, 274), (265, 275), (265, 276), (265, 277), (265, 278), (265, 279), (265, 280), (265, 281), (265, 282), (265, 283), (265, 284), (265, 285), (265, 286), (265, 287), (265, 288), (265, 289), (265, 290), (265, 291), (265, 292), (265, 293), (265, 294), (265, 295), (265, 296), (265, 297), (265, 298), (265, 299), (265, 300), (265, 302), (266, 265), (266, 267), (266, 268), (266, 269), (266, 270), (266, 271), (266, 272), (266, 273), (266, 274), (266, 275), (266, 276), (266, 277), (266, 278), (266, 279), (266, 280), (266, 281), (266, 282),
(266, 283), (266, 284), (266, 285), (266, 286), (266, 287), (266, 288), (266, 289), (266, 290), (266, 291), (266, 292), (266, 293), (266, 294), (266, 295), (266, 296), (266, 297), (266, 298), (266, 299), (266, 300), (266, 301), (266, 303), (267, 264), (267, 266), (267, 267), (267, 268), (267, 269), (267, 270), (267, 271), (267, 272), (267, 273), (267, 274), (267, 275), (267, 276), (267, 277), (267, 278), (267, 279), (267, 280), (267, 281), (267, 282), (267, 283), (267, 284), (267, 285), (267, 286), (267, 287), (267, 288), (267, 289), (267, 290), (267, 291), (267, 292), (267, 293), (267, 294), (267, 295), (267, 296), (267, 297), (267, 298), (267, 299), (267, 300), (267, 301), (267, 302), (267, 303), (268, 264), (268, 266), (268, 267), (268, 268), (268, 269), (268, 270), (268, 271), (268, 272), (268, 273), (268, 274), (268, 275), (268, 276), (268, 277),
(268, 278), (268, 279), (268, 280), (268, 281), (268, 282), (268, 283), (268, 284), (268, 285), (268, 286), (268, 287), (268, 288), (268, 289), (268, 290), (268, 291), (268, 292), (268, 293), (268, 294), (268, 295), (268, 296), (268, 297), (268, 298), (268, 299), (268, 300), (268, 301), (268, 302), (268, 304), (269, 263), (269, 265), (269, 266), (269, 267), (269, 268), (269, 269), (269, 270), (269, 271), (269, 272), (269, 273), (269, 274), (269, 275), (269, 276), (269, 277), (269, 278), (269, 279), (269, 280), (269, 281), (269, 282), (269, 283), (269, 284), (269, 285), (269, 286), (269, 287), (269, 288), (269, 289), (269, 290), (269, 291), (269, 292), (269, 293), (269, 294), (269, 295), (269, 296), (269, 297), (269, 298), (269, 299), (269, 300), (269, 301), (269, 302), (269, 304), (270, 263), (270, 265), (270, 266), (270, 267), (270, 268), (270, 269),
(270, 270), (270, 271), (270, 272), (270, 273), (270, 274), (270, 275), (270, 276), (270, 277), (270, 278), (270, 279), (270, 280), (270, 281), (270, 282), (270, 283), (270, 284), (270, 285), (270, 286), (270, 287), (270, 288), (270, 289), (270, 290), (270, 291), (270, 292), (270, 293), (270, 294), (270, 295), (270, 296), (270, 297), (270, 298), (270, 299), (270, 300), (270, 301), (270, 302), (270, 303), (270, 305), (271, 263), (271, 265), (271, 266), (271, 267), (271, 268), (271, 269), (271, 270), (271, 271), (271, 272), (271, 273), (271, 274), (271, 275), (271, 276), (271, 277), (271, 278), (271, 279), (271, 280), (271, 281), (271, 282), (271, 283), (271, 284), (271, 285), (271, 286), (271, 287), (271, 288), (271, 289), (271, 290), (271, 291), (271, 292), (271, 293), (271, 294), (271, 295), (271, 296), (271, 297), (271, 298), (271, 299), (271, 300),
(271, 301), (271, 302), (271, 303), (271, 305), (272, 263), (272, 265), (272, 266), (272, 267), (272, 268), (272, 269), (272, 270), (272, 271), (272, 272), (272, 273), (272, 274), (272, 275), (272, 276), (272, 277), (272, 278), (272, 279), (272, 280), (272, 281), (272, 282), (272, 283), (272, 284), (272, 285), (272, 286), (272, 287), (272, 288), (272, 289), (272, 290), (272, 291), (272, 292), (272, 293), (272, 294), (272, 295), (272, 296), (272, 297), (272, 298), (272, 299), (272, 300), (272, 301), (272, 302), (272, 303), (272, 305), (273, 263), (273, 265), (273, 266), (273, 267), (273, 268), (273, 269), (273, 270), (273, 271), (273, 272), (273, 273), (273, 274), (273, 275), (273, 276), (273, 277), (273, 278), (273, 279), (273, 280), (273, 281), (273, 282), (273, 283), (273, 284), (273, 285), (273, 286), (273, 287), (273, 288), (273, 289), (273, 290),
(273, 291), (273, 292), (273, 293), (273, 294), (273, 295), (273, 296), (273, 297), (273, 298), (273, 299), (273, 300), (273, 301), (273, 302), (273, 303), (273, 304), (273, 306), (274, 263), (274, 265), (274, 266), (274, 267), (274, 268), (274, 269), (274, 270), (274, 271), (274, 272), (274, 273), (274, 274), (274, 275), (274, 276), (274, 277), (274, 278), (274, 279), (274, 280), (274, 281), (274, 282), (274, 283), (274, 284), (274, 285), (274, 286), (274, 287), (274, 288), (274, 289), (274, 290), (274, 291), (274, 292), (274, 293), (274, 294), (274, 295), (274, 296), (274, 297), (274, 298), (274, 299), (274, 300), (274, 301), (274, 302), (274, 303), (274, 304), (274, 306), (275, 263), (275, 265), (275, 266), (275, 267), (275, 268), (275, 269), (275, 270), (275, 271), (275, 272), (275, 273), (275, 274), (275, 275), (275, 276), (275, 277), (275, 278),
(275, 279), (275, 280), (275, 281), (275, 282), (275, 283), (275, 284), (275, 285), (275, 286), (275, 287), (275, 288), (275, 289), (275, 290), (275, 291), (275, 292), (275, 293), (275, 294), (275, 295), (275, 296), (275, 297), (275, 298), (275, 299), (275, 300), (275, 301), (275, 302), (275, 303), (275, 304), (275, 306), (276, 263), (276, 265), (276, 266), (276, 267), (276, 268), (276, 269), (276, 270), (276, 271), (276, 272), (276, 273), (276, 274), (276, 275), (276, 276), (276, 277), (276, 278), (276, 279), (276, 280), (276, 281), (276, 282), (276, 283), (276, 284), (276, 285), (276, 286), (276, 287), (276, 288), (276, 289), (276, 290), (276, 291), (276, 292), (276, 293), (276, 294), (276, 295), (276, 296), (276, 297), (276, 298), (276, 299), (276, 300), (276, 301), (276, 302), (276, 303), (276, 304), (276, 306), (277, 263), (277, 265), (277, 266),
(277, 267), (277, 268), (277, 269), (277, 270), (277, 271), (277, 272), (277, 273), (277, 274), (277, 275), (277, 276), (277, 277), (277, 278), (277, 279), (277, 280), (277, 281), (277, 282), (277, 283), (277, 284), (277, 285), (277, 286), (277, 287), (277, 288), (277, 289), (277, 290), (277, 291), (277, 292), (277, 293), (277, 294), (277, 295), (277, 296), (277, 297), (277, 298), (277, 299), (277, 300), (277, 301), (277, 302), (277, 303), (277, 304), (277, 306), (278, 263), (278, 264), (278, 265), (278, 266), (278, 267), (278, 268), (278, 269), (278, 270), (278, 271), (278, 272), (278, 273), (278, 274), (278, 275), (278, 276), (278, 277), (278, 278), (278, 279), (278, 280), (278, 281), (278, 282), (278, 283), (278, 284), (278, 285), (278, 286), (278, 287), (278, 288), (278, 289), (278, 290), (278, 291), (278, 292), (278, 293), (278, 294), (278, 295),
(278, 296), (278, 297), (278, 298), (278, 299), (278, 300), (278, 301), (278, 302), (278, 303), (278, 304), (278, 305), (278, 306), (278, 307), (279, 264), (279, 266), (279, 267), (279, 268), (279, 269), (279, 270), (279, 271), (279, 272), (279, 273), (279, 274), (279, 275), (279, 276), (279, 277), (279, 278), (279, 279), (279, 280), (279, 281), (279, 282), (279, 283), (279, 284), (279, 285), (279, 286), (279, 287), (279, 288), (279, 289), (279, 290), (279, 291), (279, 292), (279, 293), (279, 294), (279, 295), (279, 296), (279, 297), (279, 298), (279, 299), (279, 300), (279, 301), (279, 302), (279, 303), (279, 304), (279, 305), (279, 307), (280, 264), (280, 266), (280, 269), (280, 270), (280, 271), (280, 272), (280, 273), (280, 274), (280, 275), (280, 276), (280, 277), (280, 278), (280, 279), (280, 280), (280, 281), (280, 282), (280, 283), (280, 284),
(280, 285), (280, 286), (280, 287), (280, 288), (280, 289), (280, 290), (280, 291), (280, 292), (280, 293), (280, 294), (280, 295), (280, 296), (280, 297), (280, 298), (280, 299), (280, 300), (280, 301), (280, 302), (280, 303), (280, 304), (280, 305), (280, 307), (281, 264), (281, 267), (281, 269), (281, 270), (281, 271), (281, 272), (281, 273), (281, 274), (281, 275), (281, 276), (281, 277), (281, 278), (281, 279), (281, 280), (281, 281), (281, 282), (281, 283), (281, 284), (281, 285), (281, 286), (281, 287), (281, 288), (281, 289), (281, 290), (281, 291), (281, 292), (281, 293), (281, 294), (281, 295), (281, 296), (281, 297), (281, 298), (281, 299), (281, 300), (281, 301), (281, 302), (281, 303), (281, 304), (281, 305), (281, 307), (282, 265), (282, 266), (282, 269), (282, 271), (282, 272), (282, 273), (282, 274), (282, 275), (282, 276), (282, 277),
(282, 278), (282, 279), (282, 280), (282, 281), (282, 282), (282, 283), (282, 284), (282, 285), (282, 286), (282, 287), (282, 288), (282, 289), (282, 290), (282, 291), (282, 292), (282, 293), (282, 294), (282, 295), (282, 296), (282, 297), (282, 298), (282, 299), (282, 300), (282, 301), (282, 302), (282, 303), (282, 304), (282, 305), (282, 307), (283, 269), (283, 271), (283, 272), (283, 273), (283, 274), (283, 275), (283, 276), (283, 277), (283, 278), (283, 279), (283, 280), (283, 281), (283, 282), (283, 283), (283, 284), (283, 285), (283, 286), (283, 287), (283, 288), (283, 289), (283, 290), (283, 291), (283, 292), (283, 293), (283, 294), (283, 295), (283, 296), (283, 297), (283, 298), (283, 299), (283, 300), (283, 301), (283, 302), (283, 303), (283, 304), (283, 305), (283, 306), (283, 307), (284, 270), (284, 272), (284, 273), (284, 274), (284, 275),
(284, 276), (284, 277), (284, 278), (284, 279), (284, 280), (284, 281), (284, 282), (284, 283), (284, 284), (284, 285), (284, 286), (284, 287), (284, 288), (284, 289), (284, 290), (284, 291), (284, 292), (284, 293), (284, 294), (284, 295), (284, 296), (284, 297), (284, 298), (284, 299), (284, 300), (284, 301), (284, 302), (284, 303), (284, 304), (284, 306), (285, 270), (285, 272), (285, 273), (285, 274), (285, 275), (285, 276), (285, 277), (285, 278), (285, 279), (285, 280), (285, 281), (285, 282), (285, 283), (285, 284), (285, 285), (285, 286), (285, 287), (285, 288), (285, 289), (285, 290), (285, 291), (285, 292), (285, 293), (285, 294), (285, 295), (285, 296), (285, 297), (285, 298), (285, 299), (285, 300), (285, 301), (285, 302), (285, 303), (285, 304), (285, 306), (286, 270), (286, 272), (286, 273), (286, 274), (286, 275), (286, 276), (286, 277),
(286, 278), (286, 279), (286, 280), (286, 281), (286, 282), (286, 283), (286, 284), (286, 285), (286, 286), (286, 287), (286, 288), (286, 289), (286, 290), (286, 291), (286, 292), (286, 293), (286, 294), (286, 295), (286, 296), (286, 297), (286, 298), (286, 299), (286, 300), (286, 301), (286, 302), (286, 303), (286, 304), (286, 306), (287, 270), (287, 272), (287, 273), (287, 274), (287, 275), (287, 276), (287, 277), (287, 278), (287, 279), (287, 280), (287, 281), (287, 282), (287, 283), (287, 284), (287, 285), (287, 286), (287, 287), (287, 288), (287, 289), (287, 290), (287, 291), (287, 292), (287, 293), (287, 294), (287, 295), (287, 296), (287, 297), (287, 298), (287, 299), (287, 300), (287, 301), (287, 302), (287, 303), (287, 304), (287, 306), (288, 270), (288, 272), (288, 273), (288, 274), (288, 275), (288, 276), (288, 277), (288, 278), (288, 281),
(288, 282), (288, 283), (288, 284), (288, 285), (288, 286), (288, 287), (288, 288), (288, 289), (288, 290), (288, 291), (288, 292), (288, 293), (288, 294), (288, 295), (288, 296), (288, 297), (288, 298), (288, 299), (288, 300), (288, 301), (288, 302), (288, 303), (288, 304), (288, 306), (289, 269), (289, 271), (289, 272), (289, 273), (289, 274), (289, 275), (289, 276), (289, 279), (289, 280), (289, 282), (289, 283), (289, 284), (289, 285), (289, 286), (289, 287), (289, 288), (289, 289), (289, 290), (289, 291), (289, 292), (289, 293), (289, 294), (289, 295), (289, 296), (289, 297), (289, 298), (289, 299), (289, 300), (289, 301), (289, 302), (289, 303), (289, 305), (290, 269), (290, 271), (290, 272), (290, 273), (290, 274), (290, 277), (290, 281), (290, 283), (290, 284), (290, 285), (290, 286), (290, 287), (290, 288), (290, 289), (290, 290), (290, 291),
(290, 292), (290, 293), (290, 294), (290, 295), (290, 296), (290, 297), (290, 298), (290, 299), (290, 300), (290, 301), (290, 302), (290, 303), (290, 305), (291, 269), (291, 271), (291, 272), (291, 276), (291, 282), (291, 284), (291, 285), (291, 286), (291, 287), (291, 288), (291, 289), (291, 290), (291, 291), (291, 292), (291, 293), (291, 294), (291, 295), (291, 296), (291, 297), (291, 298), (291, 299), (291, 300), (291, 301), (291, 302), (291, 304), (292, 269), (292, 274), (292, 282), (292, 284), (292, 285), (292, 286), (292, 287), (292, 288), (292, 289), (292, 290), (292, 291), (292, 292), (292, 293), (292, 294), (292, 295), (292, 296), (292, 297), (292, 298), (292, 299), (292, 300), (292, 301), (292, 303), (293, 268), (293, 272), (293, 282), (293, 284), (293, 285), (293, 286), (293, 287), (293, 288), (293, 289), (293, 290), (293, 291), (293, 292),
(293, 293), (293, 294), (293, 295), (293, 296), (293, 297), (293, 298), (293, 299), (293, 300), (293, 301), (293, 303), (294, 268), (294, 270), (294, 282), (294, 285), (294, 286), (294, 287), (294, 288), (294, 289), (294, 290), (294, 291), (294, 292), (294, 293), (294, 294), (294, 295), (294, 296), (294, 297), (294, 298), (294, 299), (294, 300), (294, 302), (295, 268), (295, 283), (295, 287), (295, 288), (295, 289), (295, 290), (295, 291), (295, 292), (295, 293), (295, 294), (295, 295), (295, 296), (295, 297), (295, 298), (295, 299), (295, 301), (296, 286), (296, 289), (296, 290), (296, 291), (296, 292), (296, 293), (296, 294), (296, 295), (296, 296), (296, 297), (296, 298), (296, 300), (297, 287), (297, 290), (297, 291), (297, 292), (297, 293), (297, 294), (297, 295), (297, 296), (297, 297), (297, 298), (297, 300), (298, 289), (298, 291), (298, 292),
(298, 293), (298, 294), (298, 295), (298, 296), (298, 297), (298, 299), (299, 290), (299, 293), (299, 294), (299, 295), (299, 296), (299, 297), (299, 299), (300, 291), (300, 294), (300, 295), (300, 296), (300, 297), (300, 299), (301, 292), (301, 295), (301, 296), (301, 298), (302, 293), (302, 295), (302, 296), (302, 298), (303, 294), (303, 297), (304, 295), (304, 297), (305, 296), )
coordinates_097F00 = ((162, 207),
(162, 209), (162, 210), (162, 211), (162, 212), (162, 213), (163, 205), (163, 214), (163, 216), (164, 203), (164, 207), (164, 208), (164, 209), (164, 210), (164, 211), (164, 212), (164, 213), (164, 217), (164, 218), (164, 219), (165, 201), (165, 202), (165, 205), (165, 206), (165, 207), (165, 208), (165, 209), (165, 210), (165, 211), (165, 212), (165, 213), (165, 214), (165, 215), (165, 216), (165, 220), (165, 222), (166, 200), (166, 203), (166, 204), (166, 205), (166, 206), (166, 207), (166, 208), (166, 209), (166, 210), (166, 211), (166, 212), (166, 213), (166, 214), (166, 215), (166, 216), (166, 217), (166, 218), (166, 219), (166, 222), (167, 200), (167, 202), (167, 203), (167, 204), (167, 205), (167, 206), (167, 207), (167, 208), (167, 209), (167, 210), (167, 211), (167, 212), (167, 213), (167, 214), (167, 215), (167, 216), (167, 217), (167, 218),
(167, 219), (167, 220), (167, 222), (168, 200), (168, 202), (168, 203), (168, 204), (168, 205), (168, 206), (168, 207), (168, 208), (168, 209), (168, 210), (168, 211), (168, 212), (168, 213), (168, 214), (168, 215), (168, 216), (168, 217), (168, 218), (168, 219), (168, 220), (168, 222), (169, 199), (169, 201), (169, 202), (169, 203), (169, 204), (169, 205), (169, 206), (169, 207), (169, 208), (169, 209), (169, 210), (169, 211), (169, 212), (169, 213), (169, 214), (169, 215), (169, 216), (169, 217), (169, 218), (169, 219), (169, 220), (169, 222), (170, 199), (170, 201), (170, 202), (170, 203), (170, 204), (170, 205), (170, 206), (170, 207), (170, 208), (170, 209), (170, 210), (170, 211), (170, 212), (170, 213), (170, 214), (170, 215), (170, 216), (170, 217), (170, 218), (170, 219), (170, 220), (170, 222), (171, 199), (171, 201), (171, 202), (171, 203),
(171, 204), (171, 205), (171, 206), (171, 207), (171, 208), (171, 209), (171, 210), (171, 211), (171, 212), (171, 213), (171, 214), (171, 215), (171, 216), (171, 217), (171, 218), (171, 219), (171, 220), (171, 221), (171, 223), (172, 198), (172, 199), (172, 200), (172, 201), (172, 202), (172, 203), (172, 204), (172, 205), (172, 206), (172, 207), (172, 208), (172, 209), (172, 210), (172, 211), (172, 212), (172, 213), (172, 214), (172, 215), (172, 216), (172, 217), (172, 218), (172, 219), (172, 220), (172, 222), (173, 198), (173, 200), (173, 201), (173, 202), (173, 203), (173, 204), (173, 205), (173, 206), (173, 207), (173, 208), (173, 209), (173, 210), (173, 211), (173, 212), (173, 213), (173, 214), (173, 215), (173, 216), (173, 217), (173, 218), (173, 219), (173, 221), (174, 198), (174, 200), (174, 201), (174, 202), (174, 203), (174, 204), (174, 205),
(174, 206), (174, 207), (174, 208), (174, 209), (174, 210), (174, 211), (174, 212), (174, 213), (174, 214), (174, 215), (174, 216), (174, 217), (174, 218), (174, 219), (174, 221), (175, 197), (175, 199), (175, 200), (175, 201), (175, 202), (175, 203), (175, 204), (175, 205), (175, 206), (175, 207), (175, 208), (175, 209), (175, 210), (175, 211), (175, 212), (175, 213), (175, 214), (175, 215), (175, 216), (175, 217), (175, 218), (175, 220), (176, 197), (176, 199), (176, 200), (176, 201), (176, 202), (176, 203), (176, 204), (176, 205), (176, 206), (176, 207), (176, 208), (176, 209), (176, 210), (176, 211), (176, 212), (176, 213), (176, 214), (176, 215), (176, 216), (176, 219), (177, 197), (177, 199), (177, 200), (177, 201), (177, 202), (177, 203), (177, 204), (177, 205), (177, 206), (177, 207), (177, 208), (177, 209), (177, 210), (177, 211), (177, 212),
(177, 213), (177, 214), (177, 215), (177, 218), (178, 196), (178, 198), (178, 199), (178, 200), (178, 201), (178, 202), (178, 203), (178, 204), (178, 205), (178, 206), (178, 207), (178, 208), (178, 209), (178, 210), (178, 211), (178, 212), (178, 216), (179, 196), (179, 213), (179, 214), (180, 196), (180, 198), (180, 199), (180, 200), (180, 201), (180, 202), (180, 203), (180, 204), (180, 205), (180, 206), (180, 207), (180, 208), (180, 209), (180, 210), (180, 211), (218, 196), (219, 196), (219, 198), (219, 199), (219, 200), (219, 201), (219, 202), (219, 203), (219, 204), (219, 205), (219, 206), (219, 207), (219, 208), (219, 209), (219, 210), (219, 211), (219, 212), (220, 196), (220, 213), (220, 215), (221, 196), (221, 198), (221, 199), (221, 200), (221, 201), (221, 202), (221, 203), (221, 204), (221, 205), (221, 206), (221, 207), (221, 208), (221, 209),
(221, 210), (221, 211), (221, 212), (221, 216), (221, 217), (222, 197), (222, 199), (222, 200), (222, 201), (222, 202), (222, 203), (222, 204), (222, 205), (222, 206), (222, 207), (222, 208), (222, 209), (222, 210), (222, 211), (222, 212), (222, 213), (222, 214), (222, 215), (222, 218), (223, 197), (223, 199), (223, 200), (223, 201), (223, 202), (223, 203), (223, 204), (223, 205), (223, 206), (223, 207), (223, 208), (223, 209), (223, 210), (223, 211), (223, 212), (223, 213), (223, 214), (223, 215), (223, 216), (223, 217), (223, 219), (224, 197), (224, 199), (224, 200), (224, 201), (224, 202), (224, 203), (224, 204), (224, 205), (224, 206), (224, 207), (224, 208), (224, 209), (224, 210), (224, 211), (224, 212), (224, 213), (224, 214), (224, 215), (224, 216), (224, 217), (224, 218), (224, 220), (225, 198), (225, 200), (225, 201), (225, 202), (225, 203),
(225, 204), (225, 205), (225, 206), (225, 207), (225, 208), (225, 209), (225, 210), (225, 211), (225, 212), (225, 213), (225, 214), (225, 215), (225, 216), (225, 217), (225, 218), (225, 219), (225, 221), (226, 198), (226, 200), (226, 201), (226, 202), (226, 203), (226, 204), (226, 205), (226, 206), (226, 207), (226, 208), (226, 209), (226, 210), (226, 211), (226, 212), (226, 213), (226, 214), (226, 215), (226, 216), (226, 217), (226, 218), (226, 219), (226, 220), (227, 199), (227, 201), (227, 202), (227, 203), (227, 204), (227, 205), (227, 206), (227, 207), (227, 208), (227, 209), (227, 210), (227, 211), (227, 212), (227, 213), (227, 214), (227, 215), (227, 216), (227, 217), (227, 218), (227, 219), (227, 220), (227, 222), (228, 199), (228, 201), (228, 202), (228, 203), (228, 204), (228, 205), (228, 206), (228, 207), (228, 208), (228, 209), (228, 210),
(228, 211), (228, 212), (228, 213), (228, 214), (228, 215), (228, 216), (228, 217), (228, 218), (228, 219), (228, 220), (228, 221), (228, 223), (229, 199), (229, 201), (229, 202), (229, 203), (229, 204), (229, 205), (229, 206), (229, 207), (229, 208), (229, 209), (229, 210), (229, 211), (229, 212), (229, 213), (229, 214), (229, 215), (229, 216), (229, 217), (229, 218), (229, 219), (229, 220), (229, 222), (230, 199), (230, 201), (230, 202), (230, 203), (230, 204), (230, 205), (230, 206), (230, 207), (230, 208), (230, 209), (230, 210), (230, 211), (230, 212), (230, 213), (230, 214), (230, 215), (230, 216), (230, 217), (230, 218), (230, 219), (230, 220), (230, 222), (231, 200), (231, 202), (231, 203), (231, 204), (231, 205), (231, 206), (231, 207), (231, 208), (231, 209), (231, 210), (231, 211), (231, 212), (231, 213), (231, 214), (231, 215), (231, 216),
(231, 217), (231, 218), (231, 219), (231, 220), (231, 222), (232, 200), (232, 202), (232, 203), (232, 204), (232, 205), (232, 206), (232, 207), (232, 208), (232, 209), (232, 210), (232, 211), (232, 212), (232, 213), (232, 214), (232, 215), (232, 216), (232, 217), (232, 218), (232, 219), (232, 220), (232, 222), (233, 200), (233, 203), (233, 204), (233, 205), (233, 206), (233, 207), (233, 208), (233, 209), (233, 210), (233, 211), (233, 212), (233, 213), (233, 214), (233, 215), (233, 216), (233, 217), (233, 218), (233, 219), (233, 222), (234, 202), (234, 205), (234, 206), (234, 207), (234, 208), (234, 209), (234, 210), (234, 211), (234, 212), (234, 213), (234, 214), (234, 215), (234, 216), (234, 220), (234, 222), (235, 203), (235, 204), (235, 207), (235, 208), (235, 209), (235, 210), (235, 211), (235, 212), (235, 213), (235, 217), (235, 218), (236, 205),
(236, 214), (236, 216), (237, 207), (237, 209), (237, 210), (237, 211), (237, 212), (237, 213), )
coordinates_92FF00 = ((161, 227),
(161, 229), (162, 226), (162, 229), (163, 225), (163, 227), (163, 228), (163, 229), (163, 230), (164, 224), (164, 226), (164, 227), (164, 228), (164, 230), (165, 224), (165, 226), (165, 227), (165, 228), (165, 229), (165, 231), (166, 224), (166, 226), (166, 227), (166, 228), (166, 229), (166, 231), (167, 224), (167, 226), (167, 227), (167, 228), (167, 229), (167, 231), (168, 224), (168, 225), (168, 226), (168, 227), (168, 228), (168, 229), (168, 231), (169, 225), (169, 227), (169, 228), (169, 229), (169, 231), (170, 225), (170, 227), (170, 228), (170, 229), (170, 231), (171, 225), (171, 227), (171, 228), (171, 229), (171, 231), (172, 224), (172, 226), (172, 227), (172, 228), (172, 230), (173, 224), (173, 226), (173, 227), (173, 228), (173, 230), (174, 223), (174, 225), (174, 226), (174, 227), (174, 229), (175, 222), (175, 224), (175, 225), (175, 226),
(175, 227), (175, 229), (176, 222), (176, 224), (176, 225), (176, 226), (176, 227), (176, 229), (177, 221), (177, 223), (177, 224), (177, 225), (177, 226), (177, 227), (177, 229), (178, 222), (178, 223), (178, 224), (178, 225), (178, 226), (178, 227), (178, 229), (179, 218), (179, 221), (179, 222), (179, 223), (179, 224), (179, 225), (179, 226), (179, 227), (179, 229), (180, 216), (180, 220), (180, 221), (180, 222), (180, 223), (180, 224), (180, 225), (180, 226), (180, 228), (181, 214), (181, 215), (181, 218), (181, 219), (181, 220), (181, 221), (181, 222), (181, 223), (181, 224), (181, 225), (181, 226), (181, 228), (182, 208), (182, 209), (182, 210), (182, 211), (182, 212), (182, 216), (182, 217), (182, 218), (182, 219), (182, 220), (182, 221), (182, 222), (182, 223), (182, 224), (182, 225), (182, 226), (182, 228), (183, 194), (183, 196), (183, 197),
(183, 198), (183, 199), (183, 200), (183, 201), (183, 202), (183, 203), (183, 204), (183, 205), (183, 206), (183, 207), (183, 214), (183, 215), (183, 216), (183, 217), (183, 218), (183, 219), (183, 220), (183, 221), (183, 222), (183, 223), (183, 224), (183, 225), (183, 227), (184, 193), (184, 208), (184, 209), (184, 210), (184, 211), (184, 212), (184, 213), (184, 214), (184, 215), (184, 216), (184, 217), (184, 218), (184, 219), (184, 220), (184, 221), (184, 222), (184, 223), (184, 224), (184, 225), (184, 227), (185, 192), (185, 194), (185, 195), (185, 196), (185, 197), (185, 198), (185, 199), (185, 200), (185, 201), (185, 202), (185, 203), (185, 204), (185, 205), (185, 206), (185, 207), (185, 208), (185, 209), (185, 210), (185, 211), (185, 212), (185, 213), (185, 214), (185, 215), (185, 216), (185, 217), (185, 218), (185, 219), (185, 220), (185, 221),
(185, 222), (185, 223), (185, 224), (185, 226), (186, 191), (186, 195), (186, 196), (186, 197), (186, 198), (186, 199), (186, 200), (186, 201), (186, 202), (186, 203), (186, 204), (186, 205), (186, 206), (186, 207), (186, 208), (186, 209), (186, 210), (186, 211), (186, 212), (186, 213), (186, 214), (186, 215), (186, 216), (186, 217), (186, 218), (186, 219), (186, 220), (186, 221), (186, 222), (186, 223), (186, 226), (187, 191), (187, 193), (187, 194), (187, 198), (187, 199), (187, 200), (187, 201), (187, 202), (187, 203), (187, 204), (187, 205), (187, 206), (187, 207), (187, 208), (187, 209), (187, 210), (187, 211), (187, 212), (187, 213), (187, 214), (187, 215), (187, 216), (187, 217), (187, 218), (187, 225), (188, 196), (188, 197), (188, 200), (188, 201), (188, 202), (188, 203), (188, 204), (188, 205), (188, 206), (188, 207), (188, 208), (188, 209),
(188, 210), (188, 218), (188, 219), (188, 220), (188, 221), (188, 223), (189, 198), (189, 199), (189, 203), (189, 204), (189, 205), (189, 206), (189, 207), (189, 211), (189, 212), (189, 213), (189, 214), (189, 215), (189, 216), (189, 217), (190, 200), (190, 202), (190, 208), (190, 209), (190, 210), (191, 203), (191, 205), (191, 207), (208, 203), (208, 204), (208, 205), (208, 207), (209, 200), (209, 209), (209, 210), (209, 211), (210, 198), (210, 199), (210, 203), (210, 204), (210, 205), (210, 206), (210, 207), (210, 212), (210, 213), (210, 214), (210, 215), (210, 216), (210, 217), (210, 218), (211, 195), (211, 196), (211, 200), (211, 201), (211, 202), (211, 203), (211, 204), (211, 205), (211, 206), (211, 207), (211, 208), (211, 209), (211, 210), (211, 211), (211, 219), (211, 220), (211, 221), (211, 222), (211, 223), (211, 224), (212, 191), (212, 193),
(212, 194), (212, 198), (212, 199), (212, 200), (212, 201), (212, 202), (212, 203), (212, 204), (212, 205), (212, 206), (212, 207), (212, 208), (212, 209), (212, 210), (212, 211), (212, 212), (212, 213), (212, 214), (212, 215), (212, 216), (212, 217), (212, 218), (212, 225), (213, 191), (213, 195), (213, 196), (213, 197), (213, 198), (213, 199), (213, 200), (213, 201), (213, 202), (213, 203), (213, 204), (213, 205), (213, 206), (213, 207), (213, 208), (213, 209), (213, 210), (213, 211), (213, 212), (213, 213), (213, 214), (213, 215), (213, 216), (213, 217), (213, 218), (213, 219), (213, 220), (213, 221), (213, 222), (213, 223), (213, 226), (214, 192), (214, 194), (214, 195), (214, 196), (214, 197), (214, 198), (214, 199), (214, 200), (214, 201), (214, 202), (214, 203), (214, 204), (214, 205), (214, 206), (214, 207), (214, 208), (214, 209), (214, 210),
(214, 211), (214, 212), (214, 213), (214, 214), (214, 215), (214, 216), (214, 217), (214, 218), (214, 219), (214, 220), (214, 221), (214, 222), (214, 223), (214, 224), (214, 226), (215, 193), (215, 209), (215, 210), (215, 211), (215, 212), (215, 213), (215, 214), (215, 215), (215, 216), (215, 217), (215, 218), (215, 219), (215, 220), (215, 221), (215, 222), (215, 223), (215, 224), (215, 225), (215, 227), (216, 194), (216, 196), (216, 197), (216, 198), (216, 199), (216, 200), (216, 201), (216, 202), (216, 203), (216, 204), (216, 205), (216, 206), (216, 207), (216, 208), (216, 214), (216, 215), (216, 216), (216, 217), (216, 218), (216, 219), (216, 220), (216, 221), (216, 222), (216, 223), (216, 224), (216, 225), (216, 226), (216, 227), (217, 209), (217, 210), (217, 211), (217, 212), (217, 213), (217, 216), (217, 217), (217, 218), (217, 219), (217, 220),
(217, 221), (217, 222), (217, 223), (217, 224), (217, 225), (217, 226), (217, 228), (218, 214), (218, 215), (218, 218), (218, 219), (218, 220), (218, 221), (218, 222), (218, 223), (218, 224), (218, 225), (218, 226), (218, 228), (219, 216), (219, 217), (219, 220), (219, 221), (219, 222), (219, 223), (219, 224), (219, 225), (219, 226), (219, 228), (220, 218), (220, 221), (220, 222), (220, 223), (220, 224), (220, 225), (220, 226), (220, 227), (220, 229), (221, 222), (221, 223), (221, 224), (221, 225), (221, 226), (221, 227), (221, 229), (222, 221), (222, 223), (222, 224), (222, 225), (222, 226), (222, 227), (222, 229), (223, 222), (223, 224), (223, 225), (223, 226), (223, 227), (223, 229), (224, 224), (224, 225), (224, 226), (224, 227), (224, 229), (225, 223), (225, 225), (225, 226), (225, 227), (225, 229), (226, 224), (226, 226), (226, 227), (226, 228),
(226, 230), (227, 224), (227, 226), (227, 227), (227, 228), (227, 230), (228, 225), (228, 227), (228, 228), (228, 229), (228, 231), (229, 225), (229, 227), (229, 228), (229, 229), (229, 231), (230, 225), (230, 227), (230, 228), (230, 229), (230, 231), (231, 224), (231, 226), (231, 227), (231, 228), (231, 229), (231, 231), (232, 224), (232, 226), (232, 227), (232, 228), (232, 229), (232, 231), (233, 224), (233, 226), (233, 227), (233, 228), (233, 229), (233, 231), (234, 224), (234, 226), (234, 227), (234, 228), (234, 229), (234, 231), (235, 224), (235, 226), (235, 227), (235, 228), (235, 230), (236, 225), (236, 228), (236, 229), (236, 230), (237, 226), (237, 229), (238, 229), )
coordinates_7F006B = ((98, 86),
(98, 88), (98, 89), (98, 90), (98, 91), (98, 92), (98, 93), (99, 84), (99, 94), (99, 95), (100, 83), (100, 86), (100, 87), (100, 88), (100, 89), (100, 90), (100, 91), (100, 92), (100, 93), (100, 97), (100, 98), (101, 82), (101, 84), (101, 85), (101, 86), (101, 87), (101, 88), (101, 89), (101, 90), (101, 91), (101, 92), (101, 93), (101, 94), (101, 95), (101, 99), (101, 100), (101, 101), (102, 81), (102, 83), (102, 84), (102, 85), (102, 86), (102, 87), (102, 88), (102, 89), (102, 90), (102, 91), (102, 92), (102, 93), (102, 94), (102, 95), (102, 96), (102, 97), (102, 98), (102, 102), (102, 103), (102, 104), (102, 105), (103, 80), (103, 82), (103, 83), (103, 84), (103, 85), (103, 86), (103, 87), (103, 88), (103, 89), (103, 90), (103, 91), (103, 92), (103, 93), (103, 94), (103, 95),
(103, 96), (103, 97), (103, 98), (103, 99), (103, 100), (103, 101), (103, 106), (103, 107), (103, 109), (104, 79), (104, 81), (104, 82), (104, 83), (104, 84), (104, 85), (104, 86), (104, 87), (104, 88), (104, 89), (104, 90), (104, 91), (104, 92), (104, 93), (104, 94), (104, 95), (104, 96), (104, 97), (104, 98), (104, 99), (104, 100), (104, 101), (104, 102), (104, 103), (104, 104), (104, 105), (104, 106), (104, 110), (105, 78), (105, 80), (105, 81), (105, 82), (105, 83), (105, 84), (105, 85), (105, 86), (105, 87), (105, 88), (105, 89), (105, 90), (105, 91), (105, 92), (105, 93), (105, 94), (105, 95), (105, 96), (105, 97), (105, 98), (105, 99), (105, 100), (105, 101), (105, 102), (105, 103), (105, 104), (105, 105), (105, 106), (105, 107), (105, 108), (105, 109), (105, 111), (106, 79), (106, 80), (106, 81),
(106, 82), (106, 83), (106, 84), (106, 85), (106, 86), (106, 87), (106, 88), (106, 89), (106, 90), (106, 91), (106, 92), (106, 93), (106, 94), (106, 95), (106, 96), (106, 97), (106, 98), (106, 99), (106, 100), (106, 101), (106, 102), (106, 103), (106, 104), (106, 105), (106, 106), (106, 107), (106, 108), (106, 109), (106, 111), (107, 77), (107, 79), (107, 80), (107, 81), (107, 82), (107, 83), (107, 84), (107, 85), (107, 86), (107, 87), (107, 88), (107, 89), (107, 90), (107, 91), (107, 92), (107, 93), (107, 94), (107, 95), (107, 96), (107, 97), (107, 98), (107, 99), (107, 100), (107, 101), (107, 102), (107, 103), (107, 104), (107, 105), (107, 106), (107, 107), (107, 108), (107, 109), (107, 110), (107, 112), (108, 76), (108, 78), (108, 79), (108, 80), (108, 81), (108, 82), (108, 83), (108, 84), (108, 85),
(108, 86), (108, 87), (108, 88), (108, 89), (108, 90), (108, 91), (108, 92), (108, 93), (108, 94), (108, 95), (108, 96), (108, 97), (108, 98), (108, 99), (108, 100), (108, 101), (108, 102), (108, 103), (108, 104), (108, 105), (108, 106), (108, 107), (108, 108), (108, 109), (108, 110), (108, 112), (109, 77), (109, 78), (109, 79), (109, 80), (109, 81), (109, 82), (109, 83), (109, 84), (109, 85), (109, 86), (109, 87), (109, 88), (109, 89), (109, 90), (109, 91), (109, 92), (109, 93), (109, 94), (109, 95), (109, 96), (109, 97), (109, 98), (109, 99), (109, 100), (109, 101), (109, 102), (109, 103), (109, 104), (109, 105), (109, 106), (109, 107), (109, 108), (109, 109), (109, 110), (109, 111), (109, 113), (110, 75), (110, 77), (110, 78), (110, 79), (110, 80), (110, 81), (110, 82), (110, 83), (110, 84), (110, 85),
(110, 86), (110, 87), (110, 88), (110, 89), (110, 90), (110, 91), (110, 92), (110, 93), (110, 94), (110, 95), (110, 96), (110, 97), (110, 98), (110, 99), (110, 100), (110, 101), (110, 102), (110, 103), (110, 104), (110, 105), (110, 106), (110, 107), (110, 108), (110, 109), (110, 110), (110, 111), (110, 113), (111, 74), (111, 76), (111, 77), (111, 78), (111, 79), (111, 80), (111, 81), (111, 82), (111, 83), (111, 84), (111, 85), (111, 86), (111, 87), (111, 88), (111, 89), (111, 90), (111, 91), (111, 92), (111, 93), (111, 94), (111, 95), (111, 96), (111, 97), (111, 98), (111, 99), (111, 100), (111, 101), (111, 102), (111, 103), (111, 104), (111, 105), (111, 106), (111, 107), (111, 108), (111, 109), (111, 110), (111, 111), (111, 113), (112, 74), (112, 76), (112, 77), (112, 78), (112, 79), (112, 80), (112, 81),
(112, 82), (112, 83), (112, 84), (112, 85), (112, 86), (112, 87), (112, 88), (112, 89), (112, 90), (112, 91), (112, 92), (112, 93), (112, 94), (112, 95), (112, 96), (112, 97), (112, 98), (112, 99), (112, 100), (112, 101), (112, 102), (112, 103), (112, 104), (112, 105), (112, 106), (112, 107), (112, 108), (112, 109), (112, 110), (112, 111), (112, 113), (113, 73), (113, 75), (113, 76), (113, 77), (113, 78), (113, 79), (113, 80), (113, 81), (113, 82), (113, 83), (113, 84), (113, 85), (113, 86), (113, 87), (113, 88), (113, 89), (113, 90), (113, 91), (113, 92), (113, 93), (113, 94), (113, 95), (113, 96), (113, 97), (113, 98), (113, 99), (113, 100), (113, 101), (113, 102), (113, 103), (113, 104), (113, 105), (113, 106), (113, 107), (113, 108), (113, 109), (113, 110), (113, 111), (113, 113), (114, 73), (114, 75),
(114, 76), (114, 77), (114, 78), (114, 79), (114, 80), (114, 81), (114, 82), (114, 83), (114, 84), (114, 85), (114, 86), (114, 87), (114, 88), (114, 89), (114, 90), (114, 91), (114, 92), (114, 93), (114, 94), (114, 95), (114, 96), (114, 97), (114, 98), (114, 99), (114, 100), (114, 101), (114, 102), (114, 103), (114, 104), (114, 105), (114, 106), (114, 107), (114, 108), (114, 109), (114, 110), (114, 111), (114, 113), (115, 72), (115, 74), (115, 75), (115, 76), (115, 77), (115, 78), (115, 79), (115, 80), (115, 81), (115, 82), (115, 83), (115, 84), (115, 85), (115, 86), (115, 87), (115, 88), (115, 89), (115, 90), (115, 91), (115, 92), (115, 93), (115, 94), (115, 95), (115, 96), (115, 97), (115, 98), (115, 99), (115, 100), (115, 101), (115, 102), (115, 103), (115, 104), (115, 105), (115, 106), (115, 107),
(115, 108), (115, 109), (115, 110), (115, 111), (115, 113), (116, 72), (116, 74), (116, 75), (116, 76), (116, 77), (116, 78), (116, 79), (116, 80), (116, 81), (116, 82), (116, 83), (116, 84), (116, 85), (116, 86), (116, 87), (116, 88), (116, 89), (116, 90), (116, 91), (116, 92), (116, 93), (116, 94), (116, 95), (116, 96), (116, 97), (116, 98), (116, 99), (116, 100), (116, 101), (116, 102), (116, 103), (116, 104), (116, 105), (116, 106), (116, 107), (116, 108), (116, 109), (116, 110), (116, 111), (116, 113), (117, 71), (117, 73), (117, 74), (117, 75), (117, 76), (117, 77), (117, 78), (117, 79), (117, 80), (117, 81), (117, 82), (117, 83), (117, 84), (117, 85), (117, 86), (117, 87), (117, 88), (117, 89), (117, 90), (117, 91), (117, 92), (117, 93), (117, 94), (117, 95), (117, 96), (117, 97), (117, 98),
(117, 99), (117, 100), (117, 101), (117, 102), (117, 103), (117, 104), (117, 105), (117, 106), (117, 107), (117, 108), (117, 109), (117, 110), (117, 111), (117, 113), (118, 71), (118, 73), (118, 74), (118, 75), (118, 76), (118, 77), (118, 78), (118, 79), (118, 80), (118, 81), (118, 82), (118, 83), (118, 84), (118, 85), (118, 86), (118, 87), (118, 88), (118, 89), (118, 90), (118, 91), (118, 92), (118, 93), (118, 94), (118, 95), (118, 96), (118, 97), (118, 98), (118, 99), (118, 100), (118, 101), (118, 102), (118, 103), (118, 104), (118, 105), (118, 106), (118, 107), (118, 108), (118, 109), (118, 110), (118, 111), (118, 113), (119, 70), (119, 72), (119, 73), (119, 74), (119, 75), (119, 76), (119, 77), (119, 78), (119, 79), (119, 80), (119, 81), (119, 82), (119, 83), (119, 84), (119, 85), (119, 86), (119, 87),
(119, 88), (119, 89), (119, 90), (119, 91), (119, 92), (119, 93), (119, 94), (119, 95), (119, 96), (119, 97), (119, 98), (119, 99), (119, 100), (119, 101), (119, 102), (119, 103), (119, 104), (119, 105), (119, 106), (119, 107), (119, 108), (119, 109), (119, 110), (119, 111), (119, 113), (120, 70), (120, 72), (120, 73), (120, 74), (120, 75), (120, 76), (120, 77), (120, 78), (120, 79), (120, 80), (120, 81), (120, 82), (120, 83), (120, 84), (120, 85), (120, 86), (120, 87), (120, 88), (120, 89), (120, 90), (120, 91), (120, 92), (120, 93), (120, 94), (120, 95), (120, 96), (120, 97), (120, 98), (120, 99), (120, 100), (120, 101), (120, 102), (120, 103), (120, 104), (120, 105), (120, 106), (120, 107), (120, 108), (120, 109), (120, 110), (120, 111), (120, 113), (121, 69), (121, 71), (121, 72), (121, 73), (121, 74),
(121, 75), (121, 76), (121, 77), (121, 78), (121, 79), (121, 80), (121, 81), (121, 82), (121, 83), (121, 84), (121, 85), (121, 86), (121, 87), (121, 88), (121, 89), (121, 90), (121, 91), (121, 92), (121, 93), (121, 94), (121, 95), (121, 96), (121, 97), (121, 98), (121, 99), (121, 100), (121, 101), (121, 102), (121, 103), (121, 104), (121, 105), (121, 106), (121, 107), (121, 108), (121, 109), (121, 110), (121, 111), (121, 113), (122, 69), (122, 71), (122, 72), (122, 73), (122, 74), (122, 75), (122, 76), (122, 77), (122, 78), (122, 79), (122, 80), (122, 81), (122, 82), (122, 83), (122, 84), (122, 85), (122, 86), (122, 87), (122, 88), (122, 89), (122, 90), (122, 91), (122, 92), (122, 93), (122, 94), (122, 95), (122, 96), (122, 97), (122, 98), (122, 99), (122, 100), (122, 101), (122, 102), (122, 103),
(122, 104), (122, 105), (122, 106), (122, 107), (122, 108), (122, 109), (122, 110), (122, 111), (122, 113), (123, 68), (123, 70), (123, 71), (123, 72), (123, 73), (123, 74), (123, 75), (123, 76), (123, 77), (123, 78), (123, 79), (123, 80), (123, 81), (123, 82), (123, 83), (123, 84), (123, 85), (123, 86), (123, 87), (123, 88), (123, 89), (123, 90), (123, 91), (123, 92), (123, 93), (123, 94), (123, 95), (123, 96), (123, 97), (123, 98), (123, 99), (123, 100), (123, 101), (123, 102), (123, 103), (123, 104), (123, 105), (123, 106), (123, 107), (123, 108), (123, 109), (123, 110), (123, 111), (123, 112), (123, 114), (124, 68), (124, 69), (124, 70), (124, 71), (124, 72), (124, 73), (124, 74), (124, 75), (124, 76), (124, 77), (124, 78), (124, 79), (124, 80), (124, 81), (124, 82), (124, 83), (124, 84), (124, 85),
(124, 86), (124, 87), (124, 88), (124, 89), (124, 90), (124, 91), (124, 92), (124, 93), (124, 94), (124, 95), (124, 96), (124, 97), (124, 98), (124, 99), (124, 100), (124, 101), (124, 102), (124, 103), (124, 104), (124, 105), (124, 106), (124, 107), (124, 108), (124, 109), (124, 110), (124, 111), (124, 112), (124, 114), (125, 67), (125, 69), (125, 70), (125, 71), (125, 72), (125, 73), (125, 74), (125, 75), (125, 76), (125, 77), (125, 78), (125, 79), (125, 80), (125, 81), (125, 82), (125, 83), (125, 84), (125, 85), (125, 86), (125, 87), (125, 88), (125, 89), (125, 90), (125, 91), (125, 92), (125, 93), (125, 94), (125, 95), (125, 96), (125, 97), (125, 98), (125, 99), (125, 100), (125, 101), (125, 102), (125, 103), (125, 104), (125, 105), (125, 106), (125, 107), (125, 108), (125, 109), (125, 110), (125, 111),
(125, 112), (125, 113), (125, 114), (125, 116), (125, 117), (126, 66), (126, 68), (126, 69), (126, 70), (126, 71), (126, 72), (126, 73), (126, 74), (126, 75), (126, 76), (126, 77), (126, 78), (126, 79), (126, 80), (126, 81), (126, 82), (126, 83), (126, 84), (126, 85), (126, 86), (126, 87), (126, 88), (126, 89), (126, 90), (126, 91), (126, 92), (126, 93), (126, 94), (126, 95), (126, 96), (126, 97), (126, 98), (126, 99), (126, 100), (126, 101), (126, 102), (126, 103), (126, 104), (126, 105), (126, 106), (126, 107), (126, 108), (126, 109), (126, 110), (126, 111), (126, 112), (126, 113), (126, 114), (126, 117), (127, 66), (127, 68), (127, 69), (127, 70), (127, 71), (127, 72), (127, 73), (127, 74), (127, 75), (127, 76), (127, 77), (127, 78), (127, 79), (127, 80), (127, 81), (127, 82), (127, 83), (127, 84),
(127, 85), (127, 86), (127, 93), (127, 94), (127, 95), (127, 96), (127, 97), (127, 98), (127, 99), (127, 100), (127, 101), (127, 102), (127, 103), (127, 104), (127, 105), (127, 106), (127, 107), (127, 108), (127, 109), (127, 110), (127, 111), (127, 112), (127, 113), (127, 114), (127, 115), (127, 117), (128, 65), (128, 67), (128, 68), (128, 69), (128, 70), (128, 71), (128, 72), (128, 73), (128, 74), (128, 75), (128, 76), (128, 77), (128, 78), (128, 79), (128, 80), (128, 81), (128, 82), (128, 83), (128, 84), (128, 85), (128, 88), (128, 89), (128, 90), (128, 91), (128, 94), (128, 95), (128, 96), (128, 97), (128, 98), (128, 99), (128, 100), (128, 101), (128, 102), (128, 103), (128, 104), (128, 105), (128, 106), (128, 107), (128, 108), (128, 109), (128, 110), (128, 111), (128, 112), (128, 113), (128, 114), (128, 115),
(128, 117), (129, 65), (129, 67), (129, 68), (129, 69), (129, 70), (129, 71), (129, 72), (129, 73), (129, 74), (129, 75), (129, 76), (129, 77), (129, 78), (129, 79), (129, 80), (129, 81), (129, 82), (129, 83), (129, 86), (129, 93), (129, 96), (129, 97), (129, 98), (129, 99), (129, 100), (129, 101), (129, 102), (129, 103), (129, 104), (129, 105), (129, 106), (129, 107), (129, 108), (129, 109), (129, 110), (129, 111), (129, 112), (129, 113), (129, 114), (129, 115), (129, 117), (130, 64), (130, 66), (130, 67), (130, 68), (130, 69), (130, 70), (130, 71), (130, 72), (130, 73), (130, 74), (130, 75), (130, 76), (130, 77), (130, 78), (130, 79), (130, 80), (130, 81), (130, 82), (130, 85), (130, 97), (130, 98), (130, 99), (130, 100), (130, 101), (130, 102), (130, 103), (130, 104), (130, 105), (130, 106), (130, 107),
(130, 108), (130, 109), (130, 110), (130, 111), (130, 112), (130, 113), (130, 114), (130, 115), (130, 117), (131, 64), (131, 66), (131, 67), (131, 68), (131, 69), (131, 70), (131, 71), (131, 72), (131, 73), (131, 74), (131, 75), (131, 76), (131, 77), (131, 78), (131, 79), (131, 80), (131, 81), (131, 96), (131, 98), (131, 99), (131, 100), (131, 101), (131, 102), (131, 103), (131, 104), (131, 105), (131, 106), (131, 107), (131, 108), (131, 109), (131, 110), (131, 111), (131, 112), (131, 113), (131, 114), (131, 115), (131, 116), (131, 118), (132, 63), (132, 65), (132, 66), (132, 67), (132, 68), (132, 69), (132, 70), (132, 71), (132, 72), (132, 73), (132, 74), (132, 75), (132, 76), (132, 77), (132, 78), (132, 79), (132, 80), (132, 81), (132, 83), (132, 97), (132, 99), (132, 100), (132, 101), (132, 102), (132, 103),
(132, 104), (132, 105), (132, 106), (132, 107), (132, 108), (132, 109), (132, 110), (132, 111), (132, 112), (132, 113), (132, 114), (132, 115), (132, 116), (132, 118), (133, 63), (133, 65), (133, 66), (133, 67), (133, 68), (133, 69), (133, 70), (133, 71), (133, 72), (133, 73), (133, 74), (133, 75), (133, 76), (133, 77), (133, 78), (133, 79), (133, 80), (133, 82), (133, 98), (133, 100), (133, 101), (133, 102), (133, 103), (133, 104), (133, 105), (133, 106), (133, 107), (133, 108), (133, 109), (133, 110), (133, 111), (133, 112), (133, 113), (133, 114), (133, 115), (133, 116), (133, 118), (134, 62), (134, 64), (134, 65), (134, 66), (134, 67), (134, 68), (134, 69), (134, 70), (134, 71), (134, 72), (134, 73), (134, 74), (134, 75), (134, 76), (134, 77), (134, 78), (134, 79), (134, 81), (134, 99), (134, 101), (134, 102),
(134, 103), (134, 104), (134, 105), (134, 106), (134, 107), (134, 108), (134, 109), (134, 110), (134, 111), (134, 112), (134, 113), (134, 114), (134, 115), (134, 116), (134, 118), (135, 62), (135, 64), (135, 65), (135, 66), (135, 67), (135, 68), (135, 69), (135, 70), (135, 71), (135, 72), (135, 73), (135, 74), (135, 75), (135, 76), (135, 77), (135, 78), (135, 79), (135, 81), (135, 100), (135, 102), (135, 103), (135, 104), (135, 105), (135, 106), (135, 107), (135, 108), (135, 109), (135, 110), (135, 111), (135, 112), (135, 113), (135, 114), (135, 115), (135, 116), (135, 117), (135, 119), (136, 61), (136, 63), (136, 64), (136, 65), (136, 66), (136, 67), (136, 68), (136, 69), (136, 70), (136, 71), (136, 72), (136, 73), (136, 74), (136, 75), (136, 76), (136, 77), (136, 78), (136, 80), (136, 101), (136, 103), (136, 104),
(136, 105), (136, 106), (136, 107), (136, 108), (136, 109), (136, 110), (136, 111), (136, 112), (136, 113), (136, 114), (136, 115), (136, 116), (136, 117), (136, 119), (137, 61), (137, 63), (137, 64), (137, 65), (137, 66), (137, 67), (137, 68), (137, 69), (137, 70), (137, 71), (137, 72), (137, 73), (137, 74), (137, 75), (137, 76), (137, 77), (137, 78), (137, 80), (137, 102), (137, 104), (137, 105), (137, 106), (137, 107), (137, 108), (137, 109), (137, 110), (137, 111), (137, 112), (137, 113), (137, 114), (137, 115), (137, 116), (137, 117), (137, 119), (138, 60), (138, 62), (138, 63), (138, 64), (138, 65), (138, 66), (138, 67), (138, 68), (138, 69), (138, 70), (138, 71), (138, 72), (138, 73), (138, 74), (138, 75), (138, 76), (138, 77), (138, 78), (138, 80), (138, 103), (138, 105), (138, 106), (138, 107), (138, 108),
(138, 109), (138, 110), (138, 111), (138, 112), (138, 113), (138, 114), (138, 115), (138, 116), (138, 117), (138, 119), (139, 60), (139, 62), (139, 63), (139, 64), (139, 65), (139, 66), (139, 67), (139, 68), (139, 69), (139, 70), (139, 71), (139, 72), (139, 73), (139, 74), (139, 75), (139, 76), (139, 77), (139, 78), (139, 80), (139, 104), (139, 106), (139, 107), (139, 108), (139, 109), (139, 110), (139, 111), (139, 112), (139, 113), (139, 114), (139, 115), (139, 116), (139, 117), (139, 119), (140, 59), (140, 61), (140, 62), (140, 63), (140, 64), (140, 65), (140, 66), (140, 67), (140, 68), (140, 69), (140, 70), (140, 71), (140, 72), (140, 73), (140, 74), (140, 75), (140, 76), (140, 77), (140, 79), (140, 105), (140, 108), (140, 109), (140, 110), (140, 111), (140, 112), (140, 113), (140, 114), (140, 115), (140, 118),
(140, 119), (141, 59), (141, 61), (141, 62), (141, 63), (141, 64), (141, 65), (141, 66), (141, 67), (141, 68), (141, 69), (141, 70), (141, 71), (141, 72), (141, 73), (141, 74), (141, 75), (141, 76), (141, 77), (141, 79), (141, 106), (141, 109), (141, 110), (141, 111), (141, 112), (141, 116), (142, 58), (142, 60), (142, 61), (142, 62), (142, 63), (142, 64), (142, 65), (142, 66), (142, 67), (142, 68), (142, 69), (142, 70), (142, 71), (142, 72), (142, 73), (142, 74), (142, 75), (142, 76), (142, 77), (142, 79), (142, 107), (142, 114), (142, 115), (143, 58), (143, 60), (143, 61), (143, 62), (143, 63), (143, 64), (143, 65), (143, 66), (143, 67), (143, 68), (143, 69), (143, 70), (143, 71), (143, 72), (143, 73), (143, 74), (143, 75), (143, 76), (143, 77), (143, 79), (143, 109), (143, 112), (144, 57),
(144, 59), (144, 60), (144, 61), (144, 62), (144, 63), (144, 64), (144, 65), (144, 66), (144, 67), (144, 68), (144, 69), (144, 70), (144, 71), (144, 72), (144, 73), (144, 74), (144, 75), (144, 76), (144, 77), (144, 78), (144, 79), (145, 57), (145, 59), (145, 60), (145, 61), (145, 62), (145, 63), (145, 64), (145, 65), (145, 66), (145, 67), (145, 68), (145, 69), (145, 70), (145, 71), (145, 72), (145, 73), (145, 74), (145, 75), (145, 76), (145, 78), (146, 57), (146, 59), (146, 60), (146, 61), (146, 62), (146, 63), (146, 64), (146, 65), (146, 66), (146, 67), (146, 68), (146, 69), (146, 70), (146, 71), (146, 72), (146, 73), (146, 74), (146, 75), (146, 76), (146, 78), (147, 56), (147, 58), (147, 59), (147, 60), (147, 61), (147, 62), (147, 63), (147, 64), (147, 65), (147, 66), (147, 67),
(147, 68), (147, 69), (147, 70), (147, 71), (147, 72), (147, 73), (147, 74), (147, 75), (147, 77), (148, 56), (148, 58), (148, 59), (148, 60), (148, 61), (148, 62), (148, 63), (148, 64), (148, 65), (148, 66), (148, 67), (148, 68), (148, 69), (148, 70), (148, 71), (148, 72), (148, 73), (148, 74), (148, 75), (148, 77), (149, 55), (149, 57), (149, 58), (149, 59), (149, 60), (149, 61), (149, 62), (149, 63), (149, 64), (149, 65), (149, 66), (149, 67), (149, 68), (149, 69), (149, 70), (149, 71), (149, 72), (149, 73), (149, 74), (149, 76), (150, 55), (150, 57), (150, 58), (150, 59), (150, 60), (150, 61), (150, 62), (150, 63), (150, 64), (150, 65), (150, 66), (150, 67), (150, 68), (150, 69), (150, 70), (150, 71), (150, 72), (150, 73), (150, 74), (150, 76), (151, 55), (151, 57), (151, 58),
(151, 59), (151, 60), (151, 61), (151, 62), (151, 63), (151, 64), (151, 65), (151, 66), (151, 67), (151, 68), (151, 69), (151, 70), (151, 71), (151, 72), (151, 73), (151, 75), (152, 54), (152, 56), (152, 57), (152, 58), (152, 59), (152, 60), (152, 61), (152, 62), (152, 63), (152, 64), (152, 65), (152, 66), (152, 67), (152, 68), (152, 69), (152, 70), (152, 71), (152, 72), (152, 73), (152, 75), (153, 54), (153, 56), (153, 57), (153, 58), (153, 59), (153, 60), (153, 61), (153, 62), (153, 63), (153, 64), (153, 65), (153, 66), (153, 67), (153, 68), (153, 69), (153, 70), (153, 71), (153, 72), (153, 74), (154, 53), (154, 55), (154, 56), (154, 57), (154, 58), (154, 59), (154, 60), (154, 61), (154, 62), (154, 63), (154, 64), (154, 65), (154, 66), (154, 67), (154, 68), (154, 69), (154, 70),
(154, 71), (154, 72), (154, 74), (155, 53), (155, 55), (155, 56), (155, 57), (155, 58), (155, 59), (155, 60), (155, 61), (155, 62), (155, 63), (155, 64), (155, 65), (155, 66), (155, 67), (155, 68), (155, 69), (155, 70), (155, 71), (155, 73), (156, 53), (156, 55), (156, 56), (156, 57), (156, 58), (156, 59), (156, 60), (156, 61), (156, 62), (156, 63), (156, 64), (156, 65), (156, 66), (156, 67), (156, 68), (156, 69), (156, 70), (156, 72), (157, 52), (157, 54), (157, 55), (157, 56), (157, 57), (157, 58), (157, 59), (157, 60), (157, 61), (157, 62), (157, 63), (157, 64), (157, 65), (157, 66), (157, 67), (157, 68), (157, 69), (157, 70), (157, 72), (158, 52), (158, 54), (158, 55), (158, 56), (158, 57), (158, 58), (158, 59), (158, 60), (158, 61), (158, 62), (158, 63), (158, 64), (158, 65),
(158, 66), (158, 67), (158, 68), (158, 69), (158, 71), (159, 52), (159, 54), (159, 55), (159, 56), (159, 57), (159, 58), (159, 59), (159, 60), (159, 61), (159, 62), (159, 63), (159, 64), (159, 65), (159, 66), (159, 67), (159, 68), (159, 69), (159, 71), (160, 51), (160, 53), (160, 54), (160, 55), (160, 56), (160, 57), (160, 58), (160, 59), (160, 60), (160, 61), (160, 62), (160, 63), (160, 64), (160, 65), (160, 66), (160, 67), (160, 68), (160, 70), (161, 51), (161, 53), (161, 54), (161, 55), (161, 56), (161, 57), (161, 58), (161, 59), (161, 60), (161, 61), (161, 62), (161, 63), (161, 64), (161, 65), (161, 66), (161, 67), (161, 68), (161, 70), (162, 51), (162, 53), (162, 54), (162, 55), (162, 56), (162, 57), (162, 58), (162, 59), (162, 60), (162, 61), (162, 62), (162, 63), (162, 64),
(162, 65), (162, 66), (162, 67), (162, 69), (163, 51), (163, 53), (163, 54), (163, 55), (163, 56), (163, 57), (163, 58), (163, 59), (163, 60), (163, 61), (163, 62), (163, 63), (163, 64), (163, 65), (163, 66), (163, 67), (163, 69), (164, 50), (164, 52), (164, 53), (164, 54), (164, 55), (164, 56), (164, 57), (164, 58), (164, 59), (164, 60), (164, 61), (164, 62), (164, 63), (164, 64), (164, 65), (164, 66), (164, 68), (165, 50), (165, 52), (165, 53), (165, 54), (165, 55), (165, 56), (165, 57), (165, 58), (165, 59), (165, 60), (165, 61), (165, 62), (165, 63), (165, 64), (165, 65), (165, 66), (165, 67), (166, 50), (166, 52), (166, 53), (166, 54), (166, 55), (166, 56), (166, 57), (166, 58), (166, 59), (166, 60), (166, 61), (166, 62), (166, 63), (166, 64), (166, 65), (166, 67), (167, 50),
(167, 52), (167, 53), (167, 54), (167, 55), (167, 56), (167, 57), (167, 58), (167, 59), (167, 60), (167, 61), (167, 62), (167, 63), (167, 64), (167, 65), (167, 66), (168, 50), (168, 52), (168, 53), (168, 54), (168, 55), (168, 56), (168, 57), (168, 58), (168, 59), (168, 60), (168, 61), (168, 62), (168, 63), (168, 64), (168, 66), (169, 49), (169, 51), (169, 52), (169, 53), (169, 54), (169, 55), (169, 56), (169, 57), (169, 58), (169, 59), (169, 60), (169, 61), (169, 62), (169, 63), (169, 64), (169, 66), (170, 49), (170, 51), (170, 52), (170, 53), (170, 54), (170, 55), (170, 56), (170, 57), (170, 58), (170, 59), (170, 60), (170, 61), (170, 62), (170, 63), (170, 65), (171, 49), (171, 51), (171, 52), (171, 53), (171, 54), (171, 55), (171, 56), (171, 57), (171, 58), (171, 59), (171, 60),
(171, 61), (171, 62), (171, 63), (171, 65), (172, 49), (172, 51), (172, 52), (172, 53), (172, 54), (172, 55), (172, 56), (172, 57), (172, 58), (172, 59), (172, 60), (172, 61), (172, 62), (172, 64), (173, 49), (173, 51), (173, 52), (173, 53), (173, 54), (173, 55), (173, 56), (173, 57), (173, 58), (173, 59), (173, 60), (173, 61), (173, 62), (173, 64), (174, 49), (174, 51), (174, 52), (174, 53), (174, 54), (174, 55), (174, 56), (174, 57), (174, 58), (174, 59), (174, 60), (174, 61), (174, 62), (174, 64), (175, 49), (175, 51), (175, 52), (175, 53), (175, 54), (175, 55), (175, 56), (175, 57), (175, 58), (175, 59), (175, 60), (175, 61), (175, 63), (176, 49), (176, 52), (176, 53), (176, 54), (176, 55), (176, 56), (176, 57), (176, 58), (176, 59), (176, 60), (176, 61), (176, 63), (177, 49),
(177, 51), (177, 52), (177, 63), (178, 52), (178, 53), (178, 54), (178, 55), (178, 56), (178, 57), (178, 58), (178, 59), (178, 60), (178, 61), (178, 63), (221, 51), (221, 52), (221, 53), (221, 54), (221, 55), (221, 56), (221, 57), (221, 58), (221, 59), (221, 60), (221, 61), (221, 63), (222, 49), (222, 63), (223, 49), (223, 51), (223, 52), (223, 53), (223, 54), (223, 55), (223, 56), (223, 57), (223, 58), (223, 59), (223, 60), (223, 61), (223, 63), (224, 49), (224, 51), (224, 52), (224, 53), (224, 54), (224, 55), (224, 56), (224, 57), (224, 58), (224, 59), (224, 60), (224, 61), (224, 63), (225, 49), (225, 51), (225, 52), (225, 53), (225, 54), (225, 55), (225, 56), (225, 57), (225, 58), (225, 59), (225, 60), (225, 61), (225, 62), (225, 64), (226, 49), (226, 51), (226, 52), (226, 53),
(226, 54), (226, 55), (226, 56), (226, 57), (226, 58), (226, 59), (226, 60), (226, 61), (226, 62), (226, 64), (227, 49), (227, 51), (227, 52), (227, 53), (227, 54), (227, 55), (227, 56), (227, 57), (227, 58), (227, 59), (227, 60), (227, 61), (227, 62), (227, 64), (228, 49), (228, 51), (228, 52), (228, 53), (228, 54), (228, 55), (228, 56), (228, 57), (228, 58), (228, 59), (228, 60), (228, 61), (228, 62), (228, 63), (228, 65), (229, 49), (229, 51), (229, 52), (229, 53), (229, 54), (229, 55), (229, 56), (229, 57), (229, 58), (229, 59), (229, 60), (229, 61), (229, 62), (229, 63), (229, 65), (230, 49), (230, 51), (230, 52), (230, 53), (230, 54), (230, 55), (230, 56), (230, 57), (230, 58), (230, 59), (230, 60), (230, 61), (230, 62), (230, 63), (230, 64), (230, 66), (231, 50), (231, 52),
(231, 53), (231, 54), (231, 55), (231, 56), (231, 57), (231, 58), (231, 59), (231, 60), (231, 61), (231, 62), (231, 63), (231, 64), (231, 66), (232, 50), (232, 52), (232, 53), (232, 54), (232, 55), (232, 56), (232, 57), (232, 58), (232, 59), (232, 60), (232, 61), (232, 62), (232, 63), (232, 64), (232, 65), (232, 67), (233, 50), (233, 52), (233, 53), (233, 54), (233, 55), (233, 56), (233, 57), (233, 58), (233, 59), (233, 60), (233, 61), (233, 62), (233, 63), (233, 64), (233, 65), (233, 67), (234, 50), (234, 52), (234, 53), (234, 54), (234, 55), (234, 56), (234, 57), (234, 58), (234, 59), (234, 60), (234, 61), (234, 62), (234, 63), (234, 64), (234, 65), (234, 66), (234, 68), (235, 50), (235, 52), (235, 53), (235, 54), (235, 55), (235, 56), (235, 57), (235, 58), (235, 59), (235, 60),
(235, 61), (235, 62), (235, 63), (235, 64), (235, 65), (235, 66), (235, 68), (236, 51), (236, 53), (236, 54), (236, 55), (236, 56), (236, 57), (236, 58), (236, 59), (236, 60), (236, 61), (236, 62), (236, 63), (236, 64), (236, 65), (236, 66), (236, 67), (236, 69), (237, 51), (237, 53), (237, 54), (237, 55), (237, 56), (237, 57), (237, 58), (237, 59), (237, 60), (237, 61), (237, 62), (237, 63), (237, 64), (237, 65), (237, 66), (237, 67), (237, 69), (238, 51), (238, 53), (238, 54), (238, 55), (238, 56), (238, 57), (238, 58), (238, 59), (238, 60), (238, 61), (238, 62), (238, 63), (238, 64), (238, 65), (238, 66), (238, 67), (238, 68), (238, 70), (239, 51), (239, 52), (239, 53), (239, 54), (239, 55), (239, 56), (239, 57), (239, 58), (239, 59), (239, 60), (239, 61), (239, 62), (239, 63),
(239, 64), (239, 65), (239, 66), (239, 67), (239, 68), (239, 70), (240, 52), (240, 54), (240, 55), (240, 56), (240, 57), (240, 58), (240, 59), (240, 60), (240, 61), (240, 62), (240, 63), (240, 64), (240, 65), (240, 66), (240, 67), (240, 68), (240, 69), (240, 71), (241, 52), (241, 54), (241, 55), (241, 56), (241, 57), (241, 58), (241, 59), (241, 60), (241, 61), (241, 62), (241, 63), (241, 64), (241, 65), (241, 66), (241, 67), (241, 68), (241, 69), (241, 71), (242, 52), (242, 54), (242, 55), (242, 56), (242, 57), (242, 58), (242, 59), (242, 60), (242, 61), (242, 62), (242, 63), (242, 64), (242, 65), (242, 66), (242, 67), (242, 68), (242, 69), (242, 70), (242, 72), (243, 53), (243, 55), (243, 56), (243, 57), (243, 58), (243, 59), (243, 60), (243, 61), (243, 62), (243, 63), (243, 64),
(243, 65), (243, 66), (243, 67), (243, 68), (243, 69), (243, 70), (243, 72), (244, 53), (244, 55), (244, 56), (244, 57), (244, 58), (244, 59), (244, 60), (244, 61), (244, 62), (244, 63), (244, 64), (244, 65), (244, 66), (244, 67), (244, 68), (244, 69), (244, 70), (244, 71), (244, 73), (245, 53), (245, 55), (245, 56), (245, 57), (245, 58), (245, 59), (245, 60), (245, 61), (245, 62), (245, 63), (245, 64), (245, 65), (245, 66), (245, 67), (245, 68), (245, 69), (245, 70), (245, 71), (245, 72), (245, 74), (246, 54), (246, 56), (246, 57), (246, 58), (246, 59), (246, 60), (246, 61), (246, 62), (246, 63), (246, 64), (246, 65), (246, 66), (246, 67), (246, 68), (246, 69), (246, 70), (246, 71), (246, 72), (246, 74), (247, 54), (247, 56), (247, 57), (247, 58), (247, 59), (247, 60), (247, 61),
(247, 62), (247, 63), (247, 64), (247, 65), (247, 66), (247, 67), (247, 68), (247, 69), (247, 70), (247, 71), (247, 72), (247, 73), (247, 75), (248, 55), (248, 57), (248, 58), (248, 59), (248, 60), (248, 61), (248, 62), (248, 63), (248, 64), (248, 65), (248, 66), (248, 67), (248, 68), (248, 69), (248, 70), (248, 71), (248, 72), (248, 73), (248, 75), (249, 55), (249, 57), (249, 58), (249, 59), (249, 60), (249, 61), (249, 62), (249, 63), (249, 64), (249, 65), (249, 66), (249, 67), (249, 68), (249, 69), (249, 70), (249, 71), (249, 72), (249, 73), (249, 74), (249, 76), (250, 55), (250, 57), (250, 58), (250, 59), (250, 60), (250, 61), (250, 62), (250, 63), (250, 64), (250, 65), (250, 66), (250, 67), (250, 68), (250, 69), (250, 70), (250, 71), (250, 72), (250, 73), (250, 74), (250, 76),
(251, 56), (251, 58), (251, 59), (251, 60), (251, 61), (251, 62), (251, 63), (251, 64), (251, 65), (251, 66), (251, 67), (251, 68), (251, 69), (251, 70), (251, 71), (251, 72), (251, 73), (251, 74), (251, 75), (251, 77), (252, 56), (252, 58), (252, 59), (252, 60), (252, 61), (252, 62), (252, 63), (252, 64), (252, 65), (252, 66), (252, 67), (252, 68), (252, 69), (252, 70), (252, 71), (252, 72), (252, 73), (252, 74), (252, 75), (252, 77), (253, 57), (253, 59), (253, 60), (253, 61), (253, 62), (253, 63), (253, 64), (253, 65), (253, 66), (253, 67), (253, 68), (253, 69), (253, 70), (253, 71), (253, 72), (253, 73), (253, 74), (253, 75), (253, 76), (253, 78), (254, 57), (254, 59), (254, 60), (254, 61), (254, 62), (254, 63), (254, 64), (254, 65), (254, 66), (254, 67), (254, 68), (254, 69),
(254, 70), (254, 71), (254, 72), (254, 73), (254, 74), (254, 75), (254, 76), (254, 78), (255, 58), (255, 60), (255, 61), (255, 62), (255, 63), (255, 64), (255, 65), (255, 66), (255, 67), (255, 68), (255, 69), (255, 70), (255, 71), (255, 72), (255, 73), (255, 74), (255, 75), (255, 76), (255, 77), (255, 79), (256, 58), (256, 60), (256, 61), (256, 62), (256, 63), (256, 64), (256, 65), (256, 66), (256, 67), (256, 68), (256, 69), (256, 70), (256, 71), (256, 72), (256, 73), (256, 74), (256, 75), (256, 76), (256, 77), (256, 79), (256, 109), (256, 111), (256, 112), (257, 58), (257, 60), (257, 61), (257, 62), (257, 63), (257, 64), (257, 65), (257, 66), (257, 67), (257, 68), (257, 69), (257, 70), (257, 71), (257, 72), (257, 73), (257, 74), (257, 75), (257, 76), (257, 77), (257, 79), (257, 107),
(257, 115), (258, 59), (258, 61), (258, 62), (258, 63), (258, 64), (258, 65), (258, 66), (258, 67), (258, 68), (258, 69), (258, 70), (258, 71), (258, 72), (258, 73), (258, 74), (258, 75), (258, 76), (258, 77), (258, 79), (258, 106), (258, 109), (258, 110), (258, 111), (258, 112), (258, 113), (258, 116), (258, 117), (259, 59), (259, 61), (259, 62), (259, 63), (259, 64), (259, 65), (259, 66), (259, 67), (259, 68), (259, 69), (259, 70), (259, 71), (259, 72), (259, 73), (259, 74), (259, 75), (259, 76), (259, 77), (259, 79), (259, 105), (259, 107), (259, 108), (259, 109), (259, 110), (259, 111), (259, 112), (259, 113), (259, 114), (259, 115), (259, 118), (259, 119), (260, 60), (260, 62), (260, 63), (260, 64), (260, 65), (260, 66), (260, 67), (260, 68), (260, 69), (260, 70), (260, 71), (260, 72), (260, 73),
(260, 74), (260, 75), (260, 76), (260, 77), (260, 78), (260, 80), (260, 104), (260, 106), (260, 107), (260, 108), (260, 109), (260, 110), (260, 111), (260, 112), (260, 113), (260, 114), (260, 115), (260, 116), (260, 117), (261, 60), (261, 62), (261, 63), (261, 64), (261, 65), (261, 66), (261, 67), (261, 68), (261, 69), (261, 70), (261, 71), (261, 72), (261, 73), (261, 74), (261, 75), (261, 76), (261, 77), (261, 78), (261, 80), (261, 103), (261, 105), (261, 106), (261, 107), (261, 108), (261, 109), (261, 110), (261, 111), (261, 112), (261, 113), (261, 114), (261, 115), (261, 116), (261, 117), (261, 119), (262, 61), (262, 63), (262, 64), (262, 65), (262, 66), (262, 67), (262, 68), (262, 69), (262, 70), (262, 71), (262, 72), (262, 73), (262, 74), (262, 75), (262, 76), (262, 77), (262, 78), (262, 80), (262, 102),
(262, 104), (262, 105), (262, 106), (262, 107), (262, 108), (262, 109), (262, 110), (262, 111), (262, 112), (262, 113), (262, 114), (262, 115), (262, 116), (262, 117), (262, 119), (263, 61), (263, 63), (263, 64), (263, 65), (263, 66), (263, 67), (263, 68), (263, 69), (263, 70), (263, 71), (263, 72), (263, 73), (263, 74), (263, 75), (263, 76), (263, 77), (263, 78), (263, 79), (263, 80), (263, 81), (263, 101), (263, 103), (263, 104), (263, 105), (263, 106), (263, 107), (263, 108), (263, 109), (263, 110), (263, 111), (263, 112), (263, 113), (263, 114), (263, 115), (263, 116), (263, 117), (263, 119), (264, 62), (264, 64), (264, 65), (264, 66), (264, 67), (264, 68), (264, 69), (264, 70), (264, 71), (264, 72), (264, 73), (264, 74), (264, 75), (264, 76), (264, 77), (264, 78), (264, 79), (264, 81), (264, 100), (264, 102),
(264, 103), (264, 104), (264, 105), (264, 106), (264, 107), (264, 108), (264, 109), (264, 110), (264, 111), (264, 112), (264, 113), (264, 114), (264, 115), (264, 116), (264, 117), (264, 119), (265, 62), (265, 64), (265, 65), (265, 66), (265, 67), (265, 68), (265, 69), (265, 70), (265, 71), (265, 72), (265, 73), (265, 74), (265, 75), (265, 76), (265, 77), (265, 78), (265, 79), (265, 81), (265, 99), (265, 101), (265, 102), (265, 103), (265, 104), (265, 105), (265, 106), (265, 107), (265, 108), (265, 109), (265, 110), (265, 111), (265, 112), (265, 113), (265, 114), (265, 115), (265, 116), (265, 118), (266, 63), (266, 65), (266, 66), (266, 67), (266, 68), (266, 69), (266, 70), (266, 71), (266, 72), (266, 73), (266, 74), (266, 75), (266, 76), (266, 77), (266, 78), (266, 79), (266, 80), (266, 82), (266, 98), (266, 100),
(266, 101), (266, 102), (266, 103), (266, 104), (266, 105), (266, 106), (266, 107), (266, 108), (266, 109), (266, 110), (266, 111), (266, 112), (266, 113), (266, 114), (266, 115), (266, 116), (266, 118), (267, 63), (267, 65), (267, 66), (267, 67), (267, 68), (267, 69), (267, 70), (267, 71), (267, 72), (267, 73), (267, 74), (267, 75), (267, 76), (267, 77), (267, 78), (267, 79), (267, 80), (267, 81), (267, 83), (267, 97), (267, 99), (267, 100), (267, 101), (267, 102), (267, 103), (267, 104), (267, 105), (267, 106), (267, 107), (267, 108), (267, 109), (267, 110), (267, 111), (267, 112), (267, 113), (267, 114), (267, 115), (267, 116), (267, 118), (268, 64), (268, 66), (268, 67), (268, 68), (268, 69), (268, 70), (268, 71), (268, 72), (268, 73), (268, 74), (268, 75), (268, 76), (268, 77), (268, 78), (268, 79), (268, 80),
(268, 81), (268, 82), (268, 84), (268, 96), (268, 98), (268, 99), (268, 100), (268, 101), (268, 102), (268, 103), (268, 104), (268, 105), (268, 106), (268, 107), (268, 108), (268, 109), (268, 110), (268, 111), (268, 112), (268, 113), (268, 114), (268, 115), (268, 116), (268, 118), (269, 64), (269, 66), (269, 67), (269, 68), (269, 69), (269, 70), (269, 71), (269, 72), (269, 73), (269, 74), (269, 75), (269, 76), (269, 77), (269, 78), (269, 79), (269, 80), (269, 81), (269, 82), (269, 85), (269, 94), (269, 97), (269, 98), (269, 99), (269, 100), (269, 101), (269, 102), (269, 103), (269, 104), (269, 105), (269, 106), (269, 107), (269, 108), (269, 109), (269, 110), (269, 111), (269, 112), (269, 113), (269, 114), (269, 115), (269, 117), (270, 65), (270, 67), (270, 68), (270, 69), (270, 70), (270, 71), (270, 72), (270, 73),
(270, 74), (270, 75), (270, 76), (270, 77), (270, 78), (270, 79), (270, 80), (270, 81), (270, 82), (270, 83), (270, 86), (270, 93), (270, 96), (270, 97), (270, 98), (270, 99), (270, 100), (270, 101), (270, 102), (270, 103), (270, 104), (270, 105), (270, 106), (270, 107), (270, 108), (270, 109), (270, 110), (270, 111), (270, 112), (270, 113), (270, 114), (270, 115), (270, 117), (271, 65), (271, 67), (271, 68), (271, 69), (271, 70), (271, 71), (271, 72), (271, 73), (271, 74), (271, 75), (271, 76), (271, 77), (271, 78), (271, 79), (271, 80), (271, 81), (271, 82), (271, 83), (271, 84), (271, 85), (271, 88), (271, 89), (271, 90), (271, 91), (271, 94), (271, 95), (271, 96), (271, 97), (271, 98), (271, 99), (271, 100), (271, 101), (271, 102), (271, 103), (271, 104), (271, 105), (271, 106), (271, 107), (271, 108),
(271, 109), (271, 110), (271, 111), (271, 112), (271, 113), (271, 114), (271, 115), (271, 117), (272, 66), (272, 68), (272, 69), (272, 70), (272, 71), (272, 72), (272, 73), (272, 74), (272, 75), (272, 76), (272, 77), (272, 78), (272, 79), (272, 80), (272, 81), (272, 82), (272, 83), (272, 84), (272, 85), (272, 86), (272, 92), (272, 93), (272, 94), (272, 95), (272, 96), (272, 97), (272, 98), (272, 99), (272, 100), (272, 101), (272, 102), (272, 103), (272, 104), (272, 105), (272, 106), (272, 107), (272, 108), (272, 109), (272, 110), (272, 111), (272, 112), (272, 113), (272, 114), (272, 115), (272, 117), (273, 67), (273, 68), (273, 69), (273, 70), (273, 71), (273, 72), (273, 73), (273, 74), (273, 75), (273, 76), (273, 77), (273, 78), (273, 79), (273, 80), (273, 81), (273, 82), (273, 83), (273, 84), (273, 85),
(273, 86), (273, 87), (273, 88), (273, 89), (273, 90), (273, 91), (273, 92), (273, 93), (273, 94), (273, 95), (273, 96), (273, 97), (273, 98), (273, 99), (273, 100), (273, 101), (273, 102), (273, 103), (273, 104), (273, 105), (273, 106), (273, 107), (273, 108), (273, 109), (273, 110), (273, 111), (273, 112), (273, 113), (273, 114), (273, 117), (274, 67), (274, 69), (274, 70), (274, 71), (274, 72), (274, 73), (274, 74), (274, 75), (274, 76), (274, 77), (274, 78), (274, 79), (274, 80), (274, 81), (274, 82), (274, 83), (274, 84), (274, 85), (274, 86), (274, 87), (274, 88), (274, 89), (274, 90), (274, 91), (274, 92), (274, 93), (274, 94), (274, 95), (274, 96), (274, 97), (274, 98), (274, 99), (274, 100), (274, 101), (274, 102), (274, 103), (274, 104), (274, 105), (274, 106), (274, 107), (274, 108), (274, 109),
(274, 110), (274, 111), (274, 112), (274, 113), (274, 116), (275, 68), (275, 70), (275, 71), (275, 72), (275, 73), (275, 74), (275, 75), (275, 76), (275, 77), (275, 78), (275, 79), (275, 80), (275, 81), (275, 82), (275, 83), (275, 84), (275, 85), (275, 86), (275, 87), (275, 88), (275, 89), (275, 90), (275, 91), (275, 92), (275, 93), (275, 94), (275, 95), (275, 96), (275, 97), (275, 98), (275, 99), (275, 100), (275, 101), (275, 102), (275, 103), (275, 104), (275, 105), (275, 106), (275, 107), (275, 108), (275, 109), (275, 110), (275, 111), (275, 112), (275, 114), (276, 68), (276, 70), (276, 71), (276, 72), (276, 73), (276, 74), (276, 75), (276, 76), (276, 77), (276, 78), (276, 79), (276, 80), (276, 81), (276, 82), (276, 83), (276, 84), (276, 85), (276, 86), (276, 87), (276, 88), (276, 89), (276, 90),
(276, 91), (276, 92), (276, 93), (276, 94), (276, 95), (276, 96), (276, 97), (276, 98), (276, 99), (276, 100), (276, 101), (276, 102), (276, 103), (276, 104), (276, 105), (276, 106), (276, 107), (276, 108), (276, 109), (276, 110), (276, 111), (276, 112), (276, 113), (276, 114), (277, 69), (277, 71), (277, 72), (277, 73), (277, 74), (277, 75), (277, 76), (277, 77), (277, 78), (277, 79), (277, 80), (277, 81), (277, 82), (277, 83), (277, 84), (277, 85), (277, 86), (277, 87), (277, 88), (277, 89), (277, 90), (277, 91), (277, 92), (277, 93), (277, 94), (277, 95), (277, 96), (277, 97), (277, 98), (277, 99), (277, 100), (277, 101), (277, 102), (277, 103), (277, 104), (277, 105), (277, 106), (277, 107), (277, 108), (277, 109), (277, 110), (277, 111), (277, 113), (278, 69), (278, 71), (278, 72), (278, 73), (278, 74),
(278, 75), (278, 76), (278, 77), (278, 78), (278, 79), (278, 80), (278, 81), (278, 82), (278, 83), (278, 84), (278, 85), (278, 86), (278, 87), (278, 88), (278, 89), (278, 90), (278, 91), (278, 92), (278, 93), (278, 94), (278, 95), (278, 96), (278, 97), (278, 98), (278, 99), (278, 100), (278, 101), (278, 102), (278, 103), (278, 104), (278, 105), (278, 106), (278, 107), (278, 108), (278, 109), (278, 110), (278, 111), (278, 113), (279, 70), (279, 72), (279, 73), (279, 74), (279, 75), (279, 76), (279, 77), (279, 78), (279, 79), (279, 80), (279, 81), (279, 82), (279, 83), (279, 84), (279, 85), (279, 86), (279, 87), (279, 88), (279, 89), (279, 90), (279, 91), (279, 92), (279, 93), (279, 94), (279, 95), (279, 96), (279, 97), (279, 98), (279, 99), (279, 100), (279, 101), (279, 102), (279, 103), (279, 104),
(279, 105), (279, 106), (279, 107), (279, 108), (279, 109), (279, 110), (279, 111), (279, 113), (280, 70), (280, 72), (280, 73), (280, 74), (280, 75), (280, 76), (280, 77), (280, 78), (280, 79), (280, 80), (280, 81), (280, 82), (280, 83), (280, 84), (280, 85), (280, 86), (280, 87), (280, 88), (280, 89), (280, 90), (280, 91), (280, 92), (280, 93), (280, 94), (280, 95), (280, 96), (280, 97), (280, 98), (280, 99), (280, 100), (280, 101), (280, 102), (280, 103), (280, 104), (280, 105), (280, 106), (280, 107), (280, 108), (280, 109), (280, 110), (280, 111), (280, 113), (281, 71), (281, 73), (281, 74), (281, 75), (281, 76), (281, 77), (281, 78), (281, 79), (281, 80), (281, 81), (281, 82), (281, 83), (281, 84), (281, 85), (281, 86), (281, 87), (281, 88), (281, 89), (281, 90), (281, 91), (281, 92), (281, 93),
(281, 94), (281, 95), (281, 96), (281, 97), (281, 98), (281, 99), (281, 100), (281, 101), (281, 102), (281, 103), (281, 104), (281, 105), (281, 106), (281, 107), (281, 108), (281, 109), (281, 110), (281, 111), (281, 113), (282, 71), (282, 73), (282, 74), (282, 75), (282, 76), (282, 77), (282, 78), (282, 79), (282, 80), (282, 81), (282, 82), (282, 83), (282, 84), (282, 85), (282, 86), (282, 87), (282, 88), (282, 89), (282, 90), (282, 91), (282, 92), (282, 93), (282, 94), (282, 95), (282, 96), (282, 97), (282, 98), (282, 99), (282, 100), (282, 101), (282, 102), (282, 103), (282, 104), (282, 105), (282, 106), (282, 107), (282, 108), (282, 109), (282, 110), (282, 111), (282, 113), (283, 72), (283, 74), (283, 75), (283, 76), (283, 77), (283, 78), (283, 79), (283, 80), (283, 81), (283, 82), (283, 83), (283, 84),
(283, 85), (283, 86), (283, 87), (283, 88), (283, 89), (283, 90), (283, 91), (283, 92), (283, 93), (283, 94), (283, 95), (283, 96), (283, 97), (283, 98), (283, 99), (283, 100), (283, 101), (283, 102), (283, 103), (283, 104), (283, 105), (283, 106), (283, 107), (283, 108), (283, 109), (283, 110), (283, 111), (283, 113), (284, 72), (284, 74), (284, 75), (284, 76), (284, 77), (284, 78), (284, 79), (284, 80), (284, 81), (284, 82), (284, 83), (284, 84), (284, 85), (284, 86), (284, 87), (284, 88), (284, 89), (284, 90), (284, 91), (284, 92), (284, 93), (284, 94), (284, 95), (284, 96), (284, 97), (284, 98), (284, 99), (284, 100), (284, 101), (284, 102), (284, 103), (284, 104), (284, 105), (284, 106), (284, 107), (284, 108), (284, 109), (284, 110), (284, 111), (284, 113), (285, 73), (285, 75), (285, 76), (285, 77),
(285, 78), (285, 79), (285, 80), (285, 81), (285, 82), (285, 83), (285, 84), (285, 85), (285, 86), (285, 87), (285, 88), (285, 89), (285, 90), (285, 91), (285, 92), (285, 93), (285, 94), (285, 95), (285, 96), (285, 97), (285, 98), (285, 99), (285, 100), (285, 101), (285, 102), (285, 103), (285, 104), (285, 105), (285, 106), (285, 107), (285, 108), (285, 109), (285, 110), (285, 111), (285, 113), (286, 73), (286, 75), (286, 76), (286, 77), (286, 78), (286, 79), (286, 80), (286, 81), (286, 82), (286, 83), (286, 84), (286, 85), (286, 86), (286, 87), (286, 88), (286, 89), (286, 90), (286, 91), (286, 92), (286, 93), (286, 94), (286, 95), (286, 96), (286, 97), (286, 98), (286, 99), (286, 100), (286, 101), (286, 102), (286, 103), (286, 104), (286, 105), (286, 106), (286, 107), (286, 108), (286, 109), (286, 110),
(286, 111), (286, 113), (287, 74), (287, 76), (287, 77), (287, 78), (287, 79), (287, 80), (287, 81), (287, 82), (287, 83), (287, 84), (287, 85), (287, 86), (287, 87), (287, 88), (287, 89), (287, 90), (287, 91), (287, 92), (287, 93), (287, 94), (287, 95), (287, 96), (287, 97), (287, 98), (287, 99), (287, 100), (287, 101), (287, 102), (287, 103), (287, 104), (287, 105), (287, 106), (287, 107), (287, 108), (287, 109), (287, 110), (287, 111), (287, 113), (288, 74), (288, 76), (288, 77), (288, 78), (288, 79), (288, 80), (288, 81), (288, 82), (288, 83), (288, 84), (288, 85), (288, 86), (288, 87), (288, 88), (288, 89), (288, 90), (288, 91), (288, 92), (288, 93), (288, 94), (288, 95), (288, 96), (288, 97), (288, 98), (288, 99), (288, 100), (288, 101), (288, 102), (288, 103), (288, 104), (288, 105), (288, 106),
(288, 107), (288, 108), (288, 109), (288, 110), (288, 111), (288, 113), (289, 75), (289, 77), (289, 78), (289, 79), (289, 80), (289, 81), (289, 82), (289, 83), (289, 84), (289, 85), (289, 86), (289, 87), (289, 88), (289, 89), (289, 90), (289, 91), (289, 92), (289, 93), (289, 94), (289, 95), (289, 96), (289, 97), (289, 98), (289, 99), (289, 100), (289, 101), (289, 102), (289, 103), (289, 104), (289, 105), (289, 106), (289, 107), (289, 108), (289, 109), (289, 110), (289, 111), (289, 113), (290, 76), (290, 78), (290, 79), (290, 80), (290, 81), (290, 82), (290, 83), (290, 84), (290, 85), (290, 86), (290, 87), (290, 88), (290, 89), (290, 90), (290, 91), (290, 92), (290, 93), (290, 94), (290, 95), (290, 96), (290, 97), (290, 98), (290, 99), (290, 100), (290, 101), (290, 102), (290, 103), (290, 104), (290, 105),
(290, 106), (290, 107), (290, 108), (290, 109), (290, 110), (290, 111), (290, 112), (290, 113), (291, 76), (291, 78), (291, 79), (291, 80), (291, 81), (291, 82), (291, 83), (291, 84), (291, 85), (291, 86), (291, 87), (291, 88), (291, 89), (291, 90), (291, 91), (291, 92), (291, 93), (291, 94), (291, 95), (291, 96), (291, 97), (291, 98), (291, 99), (291, 100), (291, 101), (291, 102), (291, 103), (291, 104), (291, 105), (291, 106), (291, 107), (291, 108), (291, 109), (291, 110), (291, 112), (292, 77), (292, 79), (292, 80), (292, 81), (292, 82), (292, 83), (292, 84), (292, 85), (292, 86), (292, 87), (292, 88), (292, 89), (292, 90), (292, 91), (292, 92), (292, 93), (292, 94), (292, 95), (292, 96), (292, 97), (292, 98), (292, 99), (292, 100), (292, 101), (292, 102), (292, 103), (292, 104), (292, 105), (292, 106),
(292, 107), (292, 108), (292, 109), (292, 110), (292, 112), (293, 78), (293, 80), (293, 81), (293, 82), (293, 83), (293, 84), (293, 85), (293, 86), (293, 87), (293, 88), (293, 89), (293, 90), (293, 91), (293, 92), (293, 93), (293, 94), (293, 95), (293, 96), (293, 97), (293, 98), (293, 99), (293, 100), (293, 101), (293, 102), (293, 103), (293, 104), (293, 105), (293, 106), (293, 107), (293, 108), (293, 109), (293, 111), (294, 78), (294, 80), (294, 81), (294, 82), (294, 83), (294, 84), (294, 85), (294, 86), (294, 87), (294, 88), (294, 89), (294, 90), (294, 91), (294, 92), (294, 93), (294, 94), (294, 95), (294, 96), (294, 97), (294, 98), (294, 99), (294, 100), (294, 101), (294, 102), (294, 103), (294, 104), (294, 105), (294, 106), (294, 107), (294, 108), (294, 109), (294, 111), (295, 79), (295, 81), (295, 82),
(295, 83), (295, 84), (295, 85), (295, 86), (295, 87), (295, 88), (295, 89), (295, 90), (295, 91), (295, 92), (295, 93), (295, 94), (295, 95), (295, 96), (295, 97), (295, 98), (295, 99), (295, 100), (295, 101), (295, 102), (295, 103), (295, 104), (295, 105), (295, 110), (296, 80), (296, 82), (296, 83), (296, 84), (296, 85), (296, 86), (296, 87), (296, 88), (296, 89), (296, 90), (296, 91), (296, 92), (296, 93), (296, 94), (296, 95), (296, 96), (296, 97), (296, 98), (296, 99), (296, 100), (296, 101), (296, 106), (296, 107), (296, 109), (297, 81), (297, 83), (297, 84), (297, 85), (297, 86), (297, 87), (297, 88), (297, 89), (297, 90), (297, 91), (297, 92), (297, 93), (297, 94), (297, 95), (297, 96), (297, 97), (297, 98), (297, 102), (297, 103), (297, 104), (297, 105), (298, 82), (298, 84), (298, 85),
(298, 86), (298, 87), (298, 88), (298, 89), (298, 90), (298, 91), (298, 92), (298, 93), (298, 94), (298, 95), (298, 99), (298, 100), (299, 83), (299, 86), (299, 87), (299, 88), (299, 89), (299, 90), (299, 91), (299, 92), (299, 93), (299, 96), (299, 97), (299, 98), (300, 84), (300, 95), (301, 86), (301, 88), (301, 89), (301, 90), (301, 91), (301, 92), )
coordinates_7F004E = ((101, 244),
(101, 246), (102, 244), (102, 247), (103, 244), (103, 247), (104, 244), (104, 246), (104, 248), (105, 245), (105, 247), (105, 249), (106, 245), (106, 247), (106, 248), (106, 250), (107, 245), (107, 247), (107, 248), (107, 249), (107, 251), (108, 245), (108, 247), (108, 248), (108, 249), (108, 250), (108, 252), (109, 245), (109, 247), (109, 248), (109, 249), (109, 250), (109, 252), (110, 245), (110, 247), (110, 248), (110, 249), (110, 250), (110, 252), (111, 246), (111, 248), (111, 249), (111, 250), (111, 252), (112, 246), (112, 248), (112, 249), (112, 250), (112, 252), (113, 234), (113, 236), (113, 238), (113, 246), (113, 248), (113, 249), (113, 250), (113, 252), (114, 232), (114, 233), (114, 238), (114, 246), (114, 248), (114, 249), (114, 250), (114, 252), (115, 230), (115, 234), (115, 235), (115, 236), (115, 238), (115, 246), (115, 248), (115, 249),
(115, 250), (115, 251), (115, 253), (116, 228), (116, 232), (116, 233), (116, 234), (116, 235), (116, 237), (116, 247), (116, 249), (116, 250), (116, 251), (116, 253), (117, 225), (117, 230), (117, 231), (117, 232), (117, 233), (117, 234), (117, 235), (117, 237), (117, 247), (117, 249), (117, 250), (117, 251), (117, 253), (118, 225), (118, 228), (118, 229), (118, 230), (118, 231), (118, 232), (118, 233), (118, 234), (118, 235), (118, 237), (118, 247), (118, 249), (118, 253), (119, 225), (119, 227), (119, 228), (119, 229), (119, 230), (119, 231), (119, 232), (119, 233), (119, 234), (119, 235), (119, 237), (119, 247), (119, 248), (119, 251), (120, 224), (120, 226), (120, 227), (120, 228), (120, 229), (120, 230), (120, 231), (120, 232), (120, 233), (120, 234), (120, 235), (120, 237), (120, 248), (121, 224), (121, 226), (121, 227), (121, 228), (121, 229),
(121, 230), (121, 231), (121, 232), (121, 233), (121, 234), (121, 235), (121, 237), (121, 248), (122, 224), (122, 226), (122, 227), (122, 228), (122, 229), (122, 230), (122, 231), (122, 232), (122, 233), (122, 234), (122, 235), (122, 237), (122, 248), (123, 223), (123, 225), (123, 226), (123, 227), (123, 228), (123, 229), (123, 230), (123, 231), (123, 232), (123, 233), (123, 234), (123, 235), (123, 237), (124, 223), (124, 225), (124, 226), (124, 227), (124, 228), (124, 229), (124, 230), (124, 231), (124, 232), (124, 233), (124, 234), (124, 235), (124, 237), (124, 249), (125, 223), (125, 225), (125, 226), (125, 227), (125, 228), (125, 229), (125, 230), (125, 231), (125, 232), (125, 233), (125, 234), (125, 235), (125, 236), (125, 237), (125, 250), (126, 222), (126, 224), (126, 225), (126, 226), (126, 227), (126, 228), (126, 229), (126, 230), (126, 231),
(126, 232), (126, 233), (126, 234), (126, 236), (126, 250), (126, 251), (127, 222), (127, 224), (127, 225), (127, 226), (127, 227), (127, 228), (127, 229), (127, 230), (127, 231), (127, 232), (127, 233), (127, 234), (127, 236), (127, 250), (128, 222), (128, 224), (128, 225), (128, 226), (128, 227), (128, 228), (128, 229), (128, 230), (128, 231), (128, 232), (128, 233), (128, 234), (128, 236), (128, 251), (129, 222), (129, 224), (129, 225), (129, 226), (129, 227), (129, 228), (129, 229), (129, 230), (129, 231), (129, 232), (129, 233), (129, 234), (129, 236), (129, 252), (130, 222), (130, 224), (130, 225), (130, 226), (130, 227), (130, 228), (130, 229), (130, 230), (130, 231), (130, 232), (130, 233), (130, 234), (130, 236), (131, 223), (131, 225), (131, 226), (131, 227), (131, 228), (131, 229), (131, 230), (131, 231), (131, 232), (131, 233), (131, 234),
(131, 236), (132, 223), (132, 226), (132, 227), (132, 228), (132, 229), (132, 230), (132, 231), (132, 232), (132, 233), (132, 235), (133, 225), (133, 227), (133, 228), (133, 229), (133, 230), (133, 231), (133, 232), (133, 233), (133, 235), (134, 226), (134, 228), (134, 229), (134, 230), (134, 231), (134, 232), (134, 233), (134, 235), (135, 227), (135, 229), (135, 230), (135, 231), (135, 232), (135, 233), (135, 235), (136, 228), (136, 230), (136, 231), (136, 232), (136, 234), (137, 229), (137, 231), (137, 232), (137, 234), (138, 230), (138, 234), (139, 230), (139, 233), (260, 230), (260, 233), (261, 234), (262, 229), (262, 231), (262, 232), (262, 234), (263, 228), (263, 230), (263, 231), (263, 232), (263, 234), (264, 227), (264, 229), (264, 230), (264, 231), (264, 232), (264, 233), (264, 235), (265, 226), (265, 228), (265, 229), (265, 230), (265, 231),
(265, 232), (265, 233), (265, 235), (266, 224), (266, 227), (266, 228), (266, 229), (266, 230), (266, 231), (266, 232), (266, 233), (266, 235), (267, 223), (267, 226), (267, 227), (267, 228), (267, 229), (267, 230), (267, 231), (267, 232), (267, 233), (267, 235), (268, 223), (268, 225), (268, 226), (268, 227), (268, 228), (268, 229), (268, 230), (268, 231), (268, 232), (268, 233), (268, 234), (268, 236), (269, 222), (269, 224), (269, 225), (269, 226), (269, 227), (269, 228), (269, 229), (269, 230), (269, 231), (269, 232), (269, 233), (269, 234), (269, 236), (269, 252), (270, 222), (270, 224), (270, 225), (270, 226), (270, 227), (270, 228), (270, 229), (270, 230), (270, 231), (270, 232), (270, 233), (270, 234), (270, 236), (270, 251), (271, 222), (271, 224), (271, 225), (271, 226), (271, 227), (271, 228), (271, 229), (271, 230), (271, 231), (271, 232),
(271, 233), (271, 234), (271, 236), (271, 250), (271, 253), (272, 222), (272, 224), (272, 225), (272, 226), (272, 227), (272, 228), (272, 229), (272, 230), (272, 231), (272, 232), (272, 233), (272, 234), (272, 236), (272, 250), (272, 252), (273, 222), (273, 224), (273, 225), (273, 226), (273, 227), (273, 228), (273, 229), (273, 230), (273, 231), (273, 232), (273, 233), (273, 234), (273, 236), (273, 250), (273, 251), (274, 223), (274, 225), (274, 226), (274, 227), (274, 228), (274, 229), (274, 230), (274, 231), (274, 232), (274, 233), (274, 234), (274, 235), (274, 237), (274, 250), (275, 223), (275, 225), (275, 226), (275, 227), (275, 228), (275, 229), (275, 230), (275, 231), (275, 232), (275, 233), (275, 234), (275, 235), (275, 237), (276, 223), (276, 225), (276, 226), (276, 227), (276, 228), (276, 229), (276, 230), (276, 231), (276, 232), (276, 233),
(276, 234), (276, 235), (276, 237), (277, 224), (277, 226), (277, 227), (277, 228), (277, 229), (277, 230), (277, 231), (277, 232), (277, 233), (277, 234), (277, 235), (277, 237), (277, 248), (278, 224), (278, 226), (278, 227), (278, 228), (278, 229), (278, 230), (278, 231), (278, 232), (278, 233), (278, 234), (278, 235), (278, 237), (278, 248), (278, 249), (279, 224), (279, 226), (279, 227), (279, 228), (279, 229), (279, 230), (279, 231), (279, 232), (279, 233), (279, 234), (279, 235), (279, 237), (279, 248), (279, 250), (280, 225), (280, 227), (280, 228), (280, 229), (280, 230), (280, 231), (280, 232), (280, 233), (280, 234), (280, 235), (280, 237), (280, 247), (280, 249), (280, 252), (281, 225), (281, 228), (281, 229), (281, 230), (281, 231), (281, 232), (281, 233), (281, 234), (281, 235), (281, 237), (281, 247), (281, 249), (281, 250), (281, 253),
(282, 225), (282, 230), (282, 231), (282, 232), (282, 233), (282, 234), (282, 235), (282, 237), (282, 247), (282, 249), (282, 250), (282, 251), (282, 253), (283, 228), (283, 232), (283, 233), (283, 234), (283, 235), (283, 237), (283, 247), (283, 249), (283, 250), (283, 251), (283, 253), (284, 230), (284, 234), (284, 235), (284, 236), (284, 238), (284, 246), (284, 248), (284, 249), (284, 250), (284, 251), (284, 253), (285, 232), (285, 233), (285, 238), (285, 246), (285, 248), (285, 249), (285, 250), (285, 251), (285, 253), (286, 234), (286, 235), (286, 236), (286, 238), (286, 246), (286, 248), (286, 249), (286, 250), (286, 252), (287, 246), (287, 248), (287, 249), (287, 250), (287, 252), (288, 246), (288, 248), (288, 249), (288, 250), (288, 252), (289, 245), (289, 247), (289, 248), (289, 249), (289, 251), (290, 245), (290, 247), (290, 248), (290, 249),
(290, 251), (291, 245), (291, 247), (291, 248), (291, 249), (291, 251), (292, 245), (292, 247), (292, 248), (292, 249), (292, 251), (293, 245), (293, 247), (293, 248), (293, 249), (293, 250), (294, 245), (294, 247), (294, 248), (294, 250), (295, 244), (295, 246), (295, 247), (296, 244), (296, 246), (296, 248), (297, 244), (297, 247), (298, 244), (298, 246), )
coordinates_FF0013 = ((141, 230),
(141, 232), (142, 230), (142, 232), (143, 230), (143, 232), (144, 230), (144, 232), (145, 230), (145, 232), (146, 231), (146, 232), (147, 231), (147, 232), (148, 232), (149, 232), (150, 232), (151, 232), (152, 232), (153, 232), (154, 232), (155, 232), (156, 232), (157, 231), (157, 232), (158, 231), (158, 232), (159, 231), (159, 232), (160, 231), (160, 232), (161, 231), (161, 232), (162, 232), (163, 232), (174, 231), (175, 231), (176, 231), (223, 231), (224, 231), (236, 232), (237, 231), (237, 232), (238, 231), (238, 232), (239, 231), (239, 232), (240, 231), (240, 232), (241, 231), (241, 232), (242, 231), (242, 232), (243, 232), (244, 232), (245, 232), (246, 232), (247, 232), (248, 232), (249, 232), (250, 232), (251, 232), (252, 231), (252, 232), (253, 231), (253, 232), (254, 230), (254, 232), (255, 230), (255, 232), (256, 230), (256, 232), (257, 230),
(257, 232), (258, 230), (258, 232), )
coordinates_61FF00 = ((69, 145),
(69, 146), (69, 147), (69, 149), (70, 142), (70, 144), (70, 150), (71, 140), (71, 141), (71, 145), (71, 146), (71, 147), (71, 148), (71, 150), (72, 137), (72, 138), (72, 142), (72, 143), (72, 144), (72, 145), (72, 146), (72, 147), (72, 148), (72, 150), (73, 135), (73, 136), (73, 139), (73, 140), (73, 141), (73, 142), (73, 143), (73, 144), (73, 145), (73, 146), (73, 147), (73, 148), (73, 149), (73, 151), (74, 134), (74, 137), (74, 138), (74, 139), (74, 140), (74, 141), (74, 142), (74, 143), (74, 144), (74, 145), (74, 146), (74, 147), (74, 148), (74, 149), (74, 151), (75, 132), (75, 135), (75, 136), (75, 137), (75, 138), (75, 139), (75, 140), (75, 141), (75, 142), (75, 143), (75, 144), (75, 145), (75, 146), (75, 147), (75, 148), (75, 149), (75, 150), (75, 152), (76, 130), (76, 133),
(76, 134), (76, 135), (76, 136), (76, 137), (76, 138), (76, 139), (76, 140), (76, 141), (76, 142), (76, 143), (76, 144), (76, 145), (76, 146), (76, 147), (76, 148), (76, 149), (76, 150), (76, 152), (77, 129), (77, 132), (77, 133), (77, 134), (77, 135), (77, 136), (77, 137), (77, 138), (77, 139), (77, 140), (77, 141), (77, 142), (77, 143), (77, 144), (77, 145), (77, 146), (77, 147), (77, 148), (77, 149), (77, 150), (77, 152), (78, 127), (78, 130), (78, 131), (78, 132), (78, 133), (78, 134), (78, 135), (78, 136), (78, 137), (78, 138), (78, 139), (78, 140), (78, 141), (78, 142), (78, 143), (78, 144), (78, 145), (78, 146), (78, 147), (78, 148), (78, 149), (78, 150), (78, 151), (78, 153), (79, 126), (79, 129), (79, 130), (79, 131), (79, 132), (79, 133), (79, 134), (79, 135), (79, 136),
(79, 137), (79, 138), (79, 139), (79, 140), (79, 141), (79, 142), (79, 143), (79, 144), (79, 145), (79, 146), (79, 147), (79, 148), (79, 149), (79, 150), (79, 151), (79, 153), (80, 124), (80, 127), (80, 128), (80, 129), (80, 130), (80, 131), (80, 132), (80, 133), (80, 134), (80, 135), (80, 136), (80, 137), (80, 138), (80, 139), (80, 140), (80, 141), (80, 142), (80, 143), (80, 144), (80, 145), (80, 146), (80, 147), (80, 148), (80, 149), (80, 150), (80, 151), (80, 152), (80, 154), (81, 123), (81, 126), (81, 127), (81, 128), (81, 129), (81, 130), (81, 131), (81, 132), (81, 133), (81, 134), (81, 135), (81, 136), (81, 137), (81, 138), (81, 139), (81, 140), (81, 141), (81, 142), (81, 143), (81, 144), (81, 145), (81, 146), (81, 147), (81, 148), (81, 149), (81, 150), (81, 151), (81, 152),
(81, 154), (82, 122), (82, 124), (82, 125), (82, 126), (82, 127), (82, 128), (82, 129), (82, 130), (82, 131), (82, 132), (82, 133), (82, 134), (82, 135), (82, 136), (82, 137), (82, 138), (82, 139), (82, 140), (82, 141), (82, 142), (82, 143), (82, 144), (82, 145), (82, 146), (82, 147), (82, 148), (82, 149), (82, 150), (82, 151), (82, 152), (82, 154), (83, 121), (83, 123), (83, 124), (83, 125), (83, 126), (83, 127), (83, 128), (83, 129), (83, 130), (83, 131), (83, 132), (83, 133), (83, 134), (83, 135), (83, 136), (83, 137), (83, 138), (83, 139), (83, 140), (83, 141), (83, 142), (83, 143), (83, 144), (83, 145), (83, 146), (83, 147), (83, 148), (83, 149), (83, 150), (83, 151), (83, 152), (83, 153), (83, 155), (84, 120), (84, 122), (84, 123), (84, 124), (84, 125), (84, 126), (84, 127),
(84, 128), (84, 129), (84, 130), (84, 131), (84, 132), (84, 133), (84, 134), (84, 135), (84, 136), (84, 137), (84, 138), (84, 139), (84, 140), (84, 141), (84, 142), (84, 143), (84, 144), (84, 145), (84, 146), (84, 147), (84, 148), (84, 149), (84, 150), (84, 151), (84, 152), (84, 153), (84, 155), (85, 121), (85, 122), (85, 123), (85, 124), (85, 125), (85, 126), (85, 127), (85, 128), (85, 129), (85, 130), (85, 131), (85, 132), (85, 133), (85, 134), (85, 135), (85, 136), (85, 137), (85, 138), (85, 139), (85, 140), (85, 141), (85, 142), (85, 143), (85, 144), (85, 145), (85, 146), (85, 147), (85, 148), (85, 149), (85, 150), (85, 151), (85, 152), (85, 153), (85, 155), (86, 117), (86, 120), (86, 121), (86, 122), (86, 123), (86, 124), (86, 125), (86, 126), (86, 127), (86, 128), (86, 129),
(86, 130), (86, 131), (86, 132), (86, 133), (86, 134), (86, 135), (86, 136), (86, 137), (86, 138), (86, 139), (86, 140), (86, 141), (86, 142), (86, 143), (86, 144), (86, 145), (86, 146), (86, 147), (86, 148), (86, 149), (86, 150), (86, 151), (86, 152), (86, 153), (86, 155), (87, 116), (87, 119), (87, 120), (87, 121), (87, 122), (87, 123), (87, 124), (87, 125), (87, 126), (87, 127), (87, 128), (87, 129), (87, 130), (87, 131), (87, 132), (87, 133), (87, 134), (87, 135), (87, 136), (87, 137), (87, 138), (87, 139), (87, 140), (87, 141), (87, 142), (87, 143), (87, 144), (87, 145), (87, 146), (87, 147), (87, 148), (87, 149), (87, 150), (87, 151), (87, 152), (87, 153), (87, 155), (88, 118), (88, 119), (88, 120), (88, 121), (88, 122), (88, 123), (88, 124), (88, 125), (88, 126), (88, 127),
(88, 128), (88, 129), (88, 130), (88, 131), (88, 132), (88, 133), (88, 134), (88, 135), (88, 136), (88, 137), (88, 138), (88, 139), (88, 140), (88, 141), (88, 142), (88, 143), (88, 144), (88, 145), (88, 146), (88, 147), (88, 148), (88, 149), (88, 150), (88, 151), (88, 152), (88, 153), (88, 155), (89, 115), (89, 117), (89, 118), (89, 119), (89, 120), (89, 121), (89, 122), (89, 123), (89, 124), (89, 125), (89, 126), (89, 127), (89, 128), (89, 129), (89, 130), (89, 131), (89, 132), (89, 133), (89, 134), (89, 135), (89, 136), (89, 137), (89, 138), (89, 139), (89, 140), (89, 141), (89, 142), (89, 143), (89, 144), (89, 145), (89, 146), (89, 147), (89, 148), (89, 149), (89, 150), (89, 151), (89, 152), (89, 153), (89, 154), (89, 156), (90, 114), (90, 116), (90, 117), (90, 118), (90, 119),
(90, 120), (90, 121), (90, 122), (90, 123), (90, 124), (90, 125), (90, 126), (90, 127), (90, 128), (90, 129), (90, 130), (90, 131), (90, 132), (90, 133), (90, 134), (90, 135), (90, 136), (90, 137), (90, 138), (90, 139), (90, 140), (90, 141), (90, 142), (90, 143), (90, 144), (90, 145), (90, 146), (90, 147), (90, 148), (90, 149), (90, 150), (90, 151), (90, 152), (90, 153), (90, 154), (90, 156), (91, 113), (91, 115), (91, 116), (91, 117), (91, 118), (91, 119), (91, 120), (91, 121), (91, 122), (91, 123), (91, 124), (91, 125), (91, 126), (91, 127), (91, 128), (91, 129), (91, 130), (91, 131), (91, 132), (91, 133), (91, 134), (91, 135), (91, 136), (91, 137), (91, 138), (91, 139), (91, 140), (91, 141), (91, 142), (91, 143), (91, 144), (91, 145), (91, 146), (91, 147), (91, 148), (91, 149),
(91, 150), (91, 151), (91, 152), (91, 153), (91, 154), (91, 156), (92, 112), (92, 114), (92, 115), (92, 116), (92, 117), (92, 118), (92, 119), (92, 120), (92, 121), (92, 122), (92, 123), (92, 124), (92, 125), (92, 126), (92, 127), (92, 128), (92, 129), (92, 130), (92, 131), (92, 132), (92, 133), (92, 134), (92, 135), (92, 136), (92, 137), (92, 138), (92, 139), (92, 140), (92, 141), (92, 142), (92, 143), (92, 144), (92, 145), (92, 146), (92, 147), (92, 148), (92, 149), (92, 150), (92, 151), (92, 152), (92, 153), (92, 154), (92, 156), (93, 112), (93, 114), (93, 115), (93, 116), (93, 117), (93, 118), (93, 119), (93, 120), (93, 121), (93, 122), (93, 123), (93, 124), (93, 125), (93, 126), (93, 127), (93, 128), (93, 129), (93, 130), (93, 131), (93, 132), (93, 133), (93, 134), (93, 135),
(93, 136), (93, 137), (93, 138), (93, 139), (93, 140), (93, 141), (93, 142), (93, 143), (93, 144), (93, 145), (93, 146), (93, 147), (93, 148), (93, 149), (93, 150), (93, 151), (93, 152), (93, 153), (93, 154), (93, 156), (94, 111), (94, 113), (94, 114), (94, 115), (94, 116), (94, 117), (94, 118), (94, 119), (94, 120), (94, 121), (94, 122), (94, 123), (94, 124), (94, 125), (94, 126), (94, 127), (94, 128), (94, 129), (94, 130), (94, 131), (94, 132), (94, 133), (94, 134), (94, 135), (94, 136), (94, 137), (94, 138), (94, 139), (94, 140), (94, 141), (94, 142), (94, 143), (94, 144), (94, 145), (94, 146), (94, 147), (94, 148), (94, 149), (94, 150), (94, 151), (94, 152), (94, 153), (94, 154), (94, 155), (94, 157), (95, 111), (95, 112), (95, 113), (95, 114), (95, 115), (95, 116), (95, 117),
(95, 118), (95, 119), (95, 120), (95, 121), (95, 122), (95, 123), (95, 124), (95, 125), (95, 126), (95, 127), (95, 128), (95, 129), (95, 130), (95, 131), (95, 132), (95, 133), (95, 134), (95, 135), (95, 136), (95, 137), (95, 138), (95, 139), (95, 140), (95, 141), (95, 142), (95, 143), (95, 144), (95, 145), (95, 146), (95, 147), (95, 148), (95, 149), (95, 150), (95, 151), (95, 152), (95, 153), (95, 154), (95, 155), (95, 157), (96, 110), (96, 112), (96, 113), (96, 114), (96, 115), (96, 116), (96, 117), (96, 118), (96, 119), (96, 120), (96, 121), (96, 122), (96, 123), (96, 124), (96, 125), (96, 126), (96, 127), (96, 128), (96, 129), (96, 130), (96, 131), (96, 132), (96, 133), (96, 134), (96, 135), (96, 136), (96, 137), (96, 138), (96, 139), (96, 140), (96, 141), (96, 142), (96, 143),
(96, 144), (96, 145), (96, 146), (96, 147), (96, 148), (96, 149), (96, 150), (96, 151), (96, 152), (96, 153), (96, 154), (96, 155), (96, 156), (96, 157), (97, 110), (97, 112), (97, 113), (97, 114), (97, 115), (97, 116), (97, 117), (97, 118), (97, 119), (97, 120), (97, 121), (97, 122), (97, 123), (97, 124), (97, 125), (97, 126), (97, 127), (97, 128), (97, 129), (97, 130), (97, 131), (97, 132), (97, 133), (97, 134), (97, 135), (97, 136), (97, 137), (97, 138), (97, 139), (97, 140), (97, 141), (97, 142), (97, 143), (97, 144), (97, 145), (97, 146), (97, 147), (97, 148), (97, 149), (97, 150), (97, 151), (97, 152), (97, 153), (97, 154), (97, 156), (98, 109), (98, 111), (98, 112), (98, 113), (98, 114), (98, 115), (98, 116), (98, 117), (98, 118), (98, 119), (98, 120), (98, 121), (98, 122),
(98, 123), (98, 124), (98, 125), (98, 126), (98, 127), (98, 128), (98, 129), (98, 130), (98, 131), (98, 132), (98, 133), (98, 134), (98, 135), (98, 136), (98, 137), (98, 138), (98, 139), (98, 140), (98, 141), (98, 142), (98, 143), (98, 144), (98, 145), (98, 146), (98, 147), (98, 148), (98, 149), (98, 150), (98, 151), (98, 152), (98, 153), (98, 154), (98, 156), (99, 109), (99, 111), (99, 112), (99, 113), (99, 114), (99, 115), (99, 116), (99, 117), (99, 118), (99, 119), (99, 120), (99, 121), (99, 122), (99, 123), (99, 124), (99, 125), (99, 126), (99, 127), (99, 128), (99, 129), (99, 130), (99, 131), (99, 132), (99, 133), (99, 134), (99, 135), (99, 136), (99, 137), (99, 138), (99, 139), (99, 140), (99, 141), (99, 142), (99, 143), (99, 144), (99, 145), (99, 146), (99, 147), (99, 148),
(99, 149), (99, 150), (99, 151), (99, 152), (99, 153), (99, 154), (99, 156), (100, 109), (100, 111), (100, 112), (100, 113), (100, 114), (100, 115), (100, 116), (100, 117), (100, 118), (100, 119), (100, 120), (100, 121), (100, 122), (100, 123), (100, 124), (100, 125), (100, 126), (100, 127), (100, 128), (100, 129), (100, 130), (100, 131), (100, 132), (100, 133), (100, 134), (100, 135), (100, 136), (100, 137), (100, 138), (100, 139), (100, 140), (100, 141), (100, 142), (100, 143), (100, 144), (100, 145), (100, 146), (100, 147), (100, 148), (100, 149), (100, 150), (100, 151), (100, 152), (100, 153), (100, 154), (100, 156), (101, 109), (101, 112), (101, 113), (101, 114), (101, 115), (101, 116), (101, 117), (101, 118), (101, 119), (101, 120), (101, 121), (101, 122), (101, 123), (101, 124), (101, 125), (101, 126), (101, 127), (101, 128), (101, 129),
(101, 130), (101, 131), (101, 132), (101, 133), (101, 134), (101, 135), (101, 136), (101, 137), (101, 138), (101, 139), (101, 140), (101, 141), (101, 142), (101, 143), (101, 144), (101, 145), (101, 146), (101, 147), (101, 148), (101, 149), (101, 150), (101, 151), (101, 152), (101, 153), (101, 154), (101, 156), (102, 111), (102, 113), (102, 114), (102, 115), (102, 116), (102, 117), (102, 118), (102, 119), (102, 120), (102, 121), (102, 122), (102, 123), (102, 124), (102, 125), (102, 126), (102, 127), (102, 128), (102, 129), (102, 130), (102, 131), (102, 132), (102, 133), (102, 134), (102, 135), (102, 136), (102, 137), (102, 138), (102, 139), (102, 140), (102, 141), (102, 142), (102, 143), (102, 144), (102, 145), (102, 146), (102, 147), (102, 148), (102, 149), (102, 150), (102, 151), (102, 152), (102, 153), (102, 155), (103, 112), (103, 114), (103, 115),
(103, 116), (103, 117), (103, 118), (103, 119), (103, 120), (103, 121), (103, 122), (103, 123), (103, 124), (103, 125), (103, 126), (103, 127), (103, 128), (103, 129), (103, 130), (103, 131), (103, 132), (103, 133), (103, 134), (103, 135), (103, 136), (103, 137), (103, 138), (103, 139), (103, 140), (103, 141), (103, 142), (103, 143), (103, 144), (103, 145), (103, 146), (103, 147), (103, 148), (103, 149), (103, 150), (103, 151), (103, 152), (103, 153), (103, 155), (104, 112), (104, 114), (104, 115), (104, 116), (104, 117), (104, 118), (104, 119), (104, 120), (104, 121), (104, 122), (104, 123), (104, 124), (104, 125), (104, 126), (104, 127), (104, 128), (104, 129), (104, 130), (104, 131), (104, 132), (104, 133), (104, 134), (104, 135), (104, 136), (104, 137), (104, 138), (104, 139), (104, 140), (104, 141), (104, 142), (104, 143), (104, 144), (104, 145),
(104, 146), (104, 147), (104, 148), (104, 149), (104, 150), (104, 151), (104, 152), (104, 153), (104, 155), (105, 113), (105, 115), (105, 116), (105, 117), (105, 118), (105, 119), (105, 120), (105, 121), (105, 122), (105, 123), (105, 124), (105, 125), (105, 126), (105, 127), (105, 128), (105, 129), (105, 130), (105, 131), (105, 132), (105, 133), (105, 134), (105, 135), (105, 136), (105, 137), (105, 138), (105, 139), (105, 140), (105, 141), (105, 142), (105, 143), (105, 144), (105, 145), (105, 146), (105, 147), (105, 148), (105, 149), (105, 150), (105, 151), (105, 152), (105, 154), (106, 114), (106, 116), (106, 117), (106, 118), (106, 119), (106, 120), (106, 121), (106, 122), (106, 123), (106, 124), (106, 125), (106, 126), (106, 127), (106, 128), (106, 129), (106, 130), (106, 131), (106, 132), (106, 133), (106, 134), (106, 135), (106, 136), (106, 137),
(106, 138), (106, 139), (106, 140), (106, 141), (106, 142), (106, 143), (106, 144), (106, 145), (106, 146), (106, 147), (106, 148), (106, 149), (106, 150), (106, 151), (106, 152), (106, 154), (107, 114), (107, 116), (107, 117), (107, 118), (107, 119), (107, 120), (107, 121), (107, 122), (107, 123), (107, 124), (107, 125), (107, 126), (107, 127), (107, 128), (107, 129), (107, 130), (107, 131), (107, 132), (107, 133), (107, 134), (107, 135), (107, 136), (107, 137), (107, 138), (107, 139), (107, 140), (107, 141), (107, 142), (107, 143), (107, 144), (107, 145), (107, 146), (107, 147), (107, 148), (107, 149), (107, 150), (107, 151), (107, 152), (107, 153), (108, 114), (108, 116), (108, 117), (108, 118), (108, 119), (108, 120), (108, 121), (108, 122), (108, 123), (108, 124), (108, 125), (108, 126), (108, 127), (108, 128), (108, 129), (108, 130), (108, 131),
(108, 132), (108, 133), (108, 134), (108, 135), (108, 136), (108, 137), (108, 138), (108, 139), (108, 140), (108, 141), (108, 142), (108, 143), (108, 144), (108, 145), (108, 146), (108, 147), (108, 148), (108, 149), (108, 150), (108, 151), (108, 153), (109, 115), (109, 117), (109, 118), (109, 119), (109, 120), (109, 121), (109, 122), (109, 123), (109, 124), (109, 125), (109, 126), (109, 127), (109, 128), (109, 129), (109, 130), (109, 131), (109, 132), (109, 133), (109, 134), (109, 135), (109, 136), (109, 137), (109, 138), (109, 139), (109, 140), (109, 141), (109, 142), (109, 143), (109, 144), (109, 145), (109, 146), (109, 147), (109, 148), (109, 149), (109, 150), (109, 151), (109, 152), (110, 115), (110, 117), (110, 118), (110, 119), (110, 120), (110, 121), (110, 122), (110, 123), (110, 124), (110, 125), (110, 126), (110, 127), (110, 128), (110, 129),
(110, 130), (110, 131), (110, 132), (110, 133), (110, 134), (110, 135), (110, 136), (110, 137), (110, 138), (110, 139), (110, 140), (110, 141), (110, 142), (110, 143), (110, 144), (110, 145), (110, 146), (110, 147), (110, 148), (110, 149), (110, 150), (110, 152), (111, 115), (111, 117), (111, 118), (111, 119), (111, 120), (111, 121), (111, 122), (111, 123), (111, 124), (111, 125), (111, 126), (111, 127), (111, 128), (111, 129), (111, 130), (111, 131), (111, 132), (111, 133), (111, 134), (111, 135), (111, 136), (111, 137), (111, 138), (111, 139), (111, 140), (111, 141), (111, 142), (111, 143), (111, 144), (111, 145), (111, 146), (111, 147), (111, 148), (111, 149), (111, 151), (112, 116), (112, 119), (112, 120), (112, 121), (112, 122), (112, 123), (112, 124), (112, 125), (112, 126), (112, 127), (112, 128), (112, 129), (112, 130), (112, 131), (112, 132),
(112, 133), (112, 134), (112, 135), (112, 136), (112, 137), (112, 138), (112, 139), (112, 140), (112, 141), (112, 142), (112, 143), (112, 144), (112, 145), (112, 146), (112, 147), (112, 148), (112, 149), (112, 151), (113, 116), (113, 117), (113, 120), (113, 121), (113, 122), (113, 123), (113, 124), (113, 125), (113, 126), (113, 127), (113, 128), (113, 129), (113, 130), (113, 131), (113, 132), (113, 133), (113, 134), (113, 135), (113, 136), (113, 137), (113, 138), (113, 139), (113, 140), (113, 141), (113, 142), (113, 143), (113, 144), (113, 145), (113, 146), (113, 147), (113, 148), (113, 150), (114, 119), (114, 121), (114, 122), (114, 123), (114, 124), (114, 125), (114, 126), (114, 127), (114, 128), (114, 129), (114, 130), (114, 131), (114, 132), (114, 133), (114, 134), (114, 135), (114, 136), (114, 137), (114, 138), (114, 139), (114, 140), (114, 141),
(114, 142), (114, 143), (114, 144), (114, 145), (114, 146), (114, 147), (114, 149), (115, 120), (115, 122), (115, 123), (115, 124), (115, 125), (115, 126), (115, 127), (115, 128), (115, 129), (115, 130), (115, 131), (115, 132), (115, 133), (115, 134), (115, 135), (115, 136), (115, 137), (115, 138), (115, 139), (115, 140), (115, 141), (115, 142), (115, 143), (115, 144), (115, 145), (115, 146), (115, 149), (116, 120), (116, 122), (116, 123), (116, 124), (116, 125), (116, 126), (116, 127), (116, 128), (116, 129), (116, 130), (116, 131), (116, 132), (116, 133), (116, 134), (116, 135), (116, 136), (116, 137), (116, 138), (116, 139), (116, 140), (116, 141), (116, 142), (116, 143), (116, 144), (116, 145), (116, 146), (116, 148), (117, 120), (117, 122), (117, 123), (117, 124), (117, 125), (117, 126), (117, 127), (117, 128), (117, 129), (117, 130), (117, 131),
(117, 132), (117, 133), (117, 134), (117, 135), (117, 136), (117, 137), (117, 138), (117, 139), (117, 140), (117, 141), (117, 142), (117, 143), (117, 144), (117, 145), (117, 147), (118, 120), (118, 122), (118, 123), (118, 124), (118, 125), (118, 126), (118, 127), (118, 128), (118, 129), (118, 130), (118, 131), (118, 132), (118, 133), (118, 134), (118, 135), (118, 136), (118, 137), (118, 138), (118, 139), (118, 140), (118, 141), (118, 142), (118, 143), (118, 144), (118, 146), (119, 120), (119, 122), (119, 123), (119, 124), (119, 125), (119, 126), (119, 127), (119, 128), (119, 129), (119, 130), (119, 131), (119, 132), (119, 133), (119, 134), (119, 135), (119, 136), (119, 137), (119, 138), (119, 139), (119, 140), (119, 141), (119, 142), (119, 143), (119, 145), (120, 120), (120, 122), (120, 123), (120, 124), (120, 125), (120, 126), (120, 127), (120, 128),
(120, 129), (120, 130), (120, 131), (120, 132), (120, 133), (120, 134), (120, 135), (120, 136), (120, 137), (120, 138), (120, 139), (120, 140), (120, 141), (120, 142), (120, 144), (121, 119), (121, 121), (121, 122), (121, 123), (121, 124), (121, 125), (121, 126), (121, 127), (121, 128), (121, 129), (121, 130), (121, 131), (121, 132), (121, 133), (121, 134), (121, 135), (121, 136), (121, 137), (121, 138), (121, 139), (121, 140), (121, 141), (121, 143), (122, 119), (122, 121), (122, 122), (122, 123), (122, 124), (122, 125), (122, 126), (122, 127), (122, 128), (122, 129), (122, 130), (122, 131), (122, 132), (122, 133), (122, 134), (122, 135), (122, 136), (122, 137), (122, 138), (122, 139), (122, 140), (122, 142), (123, 119), (123, 121), (123, 122), (123, 123), (123, 124), (123, 125), (123, 126), (123, 127), (123, 128), (123, 129), (123, 130), (123, 131),
(123, 132), (123, 133), (123, 134), (123, 135), (123, 136), (123, 137), (123, 138), (123, 141), (124, 119), (124, 121), (124, 122), (124, 123), (124, 124), (124, 125), (124, 126), (124, 127), (124, 128), (124, 129), (124, 130), (124, 131), (124, 132), (124, 133), (124, 134), (124, 135), (124, 136), (124, 137), (124, 140), (125, 119), (125, 121), (125, 122), (125, 123), (125, 124), (125, 125), (125, 126), (125, 127), (125, 128), (125, 129), (125, 130), (125, 131), (125, 132), (125, 133), (125, 134), (125, 135), (125, 138), (126, 119), (126, 121), (126, 122), (126, 123), (126, 124), (126, 125), (126, 126), (126, 127), (126, 128), (126, 129), (126, 130), (126, 131), (126, 132), (126, 133), (126, 137), (127, 119), (127, 121), (127, 122), (127, 123), (127, 124), (127, 125), (127, 126), (127, 127), (127, 128), (127, 129), (127, 130), (127, 131), (127, 132),
(127, 135), (128, 119), (128, 121), (128, 122), (128, 123), (128, 124), (128, 125), (128, 126), (128, 127), (128, 128), (128, 129), (128, 130), (128, 131), (128, 133), (129, 119), (129, 121), (129, 122), (129, 123), (129, 124), (129, 125), (129, 126), (129, 127), (129, 128), (129, 129), (129, 130), (129, 132), (130, 120), (130, 122), (130, 123), (130, 124), (130, 125), (130, 126), (130, 127), (130, 128), (130, 129), (130, 131), (131, 120), (131, 122), (131, 123), (131, 124), (131, 125), (131, 126), (131, 127), (131, 128), (131, 130), (132, 120), (132, 122), (132, 123), (132, 124), (132, 125), (132, 126), (132, 127), (132, 129), (133, 120), (133, 122), (133, 123), (133, 124), (133, 125), (133, 126), (133, 128), (134, 121), (134, 123), (134, 124), (134, 125), (134, 126), (134, 128), (135, 121), (135, 123), (135, 124), (135, 125), (135, 127), (136, 121),
(136, 123), (136, 124), (136, 126), (137, 121), (137, 123), (137, 125), (138, 124), (139, 122), (139, 123), (260, 122), (260, 123), (261, 125), (262, 121), (262, 123), (263, 121), (263, 123), (263, 124), (263, 126), (264, 121), (264, 123), (264, 124), (264, 125), (264, 127), (265, 121), (265, 123), (265, 124), (265, 125), (265, 126), (265, 128), (266, 120), (266, 122), (266, 123), (266, 124), (266, 125), (266, 126), (266, 128), (267, 120), (267, 122), (267, 123), (267, 124), (267, 125), (267, 126), (267, 127), (267, 129), (268, 120), (268, 122), (268, 123), (268, 124), (268, 125), (268, 126), (268, 127), (268, 128), (268, 130), (269, 120), (269, 122), (269, 123), (269, 124), (269, 125), (269, 126), (269, 127), (269, 128), (269, 129), (269, 131), (270, 119), (270, 121), (270, 122), (270, 123), (270, 124), (270, 125), (270, 126), (270, 127), (270, 128),
(270, 129), (270, 130), (270, 132), (271, 119), (271, 121), (271, 122), (271, 123), (271, 124), (271, 125), (271, 126), (271, 127), (271, 128), (271, 129), (271, 130), (271, 131), (271, 133), (272, 119), (272, 121), (272, 122), (272, 123), (272, 124), (272, 125), (272, 126), (272, 127), (272, 128), (272, 129), (272, 130), (272, 131), (272, 132), (272, 135), (273, 119), (273, 121), (273, 122), (273, 123), (273, 124), (273, 125), (273, 126), (273, 127), (273, 128), (273, 129), (273, 130), (273, 131), (273, 132), (273, 133), (273, 137), (274, 119), (274, 121), (274, 122), (274, 123), (274, 124), (274, 125), (274, 126), (274, 127), (274, 128), (274, 129), (274, 130), (274, 131), (274, 132), (274, 133), (274, 134), (274, 135), (274, 138), (275, 119), (275, 121), (275, 122), (275, 123), (275, 124), (275, 125), (275, 126), (275, 127), (275, 128), (275, 129),
(275, 130), (275, 131), (275, 132), (275, 133), (275, 134), (275, 135), (275, 136), (275, 137), (275, 140), (276, 119), (276, 121), (276, 122), (276, 123), (276, 124), (276, 125), (276, 126), (276, 127), (276, 128), (276, 129), (276, 130), (276, 131), (276, 132), (276, 133), (276, 134), (276, 135), (276, 136), (276, 137), (276, 138), (276, 141), (277, 119), (277, 121), (277, 122), (277, 123), (277, 124), (277, 125), (277, 126), (277, 127), (277, 128), (277, 129), (277, 130), (277, 131), (277, 132), (277, 133), (277, 134), (277, 135), (277, 136), (277, 137), (277, 138), (277, 139), (277, 140), (277, 142), (278, 119), (278, 121), (278, 122), (278, 123), (278, 124), (278, 125), (278, 126), (278, 127), (278, 128), (278, 129), (278, 130), (278, 131), (278, 132), (278, 133), (278, 134), (278, 135), (278, 136), (278, 137), (278, 138), (278, 139), (278, 140),
(278, 141), (278, 143), (279, 120), (279, 122), (279, 123), (279, 124), (279, 125), (279, 126), (279, 127), (279, 128), (279, 129), (279, 130), (279, 131), (279, 132), (279, 133), (279, 134), (279, 135), (279, 136), (279, 137), (279, 138), (279, 139), (279, 140), (279, 141), (279, 142), (279, 144), (280, 120), (280, 122), (280, 123), (280, 124), (280, 125), (280, 126), (280, 127), (280, 128), (280, 129), (280, 130), (280, 131), (280, 132), (280, 133), (280, 134), (280, 135), (280, 136), (280, 137), (280, 138), (280, 139), (280, 140), (280, 141), (280, 142), (280, 143), (280, 145), (281, 120), (281, 122), (281, 123), (281, 124), (281, 125), (281, 126), (281, 127), (281, 128), (281, 129), (281, 130), (281, 131), (281, 132), (281, 133), (281, 134), (281, 135), (281, 136), (281, 137), (281, 138), (281, 139), (281, 140), (281, 141), (281, 142), (281, 143),
(281, 144), (281, 146), (282, 120), (282, 122), (282, 123), (282, 124), (282, 125), (282, 126), (282, 127), (282, 128), (282, 129), (282, 130), (282, 131), (282, 132), (282, 133), (282, 134), (282, 135), (282, 136), (282, 137), (282, 138), (282, 139), (282, 140), (282, 141), (282, 142), (282, 143), (282, 144), (282, 145), (282, 147), (283, 120), (283, 122), (283, 123), (283, 124), (283, 125), (283, 126), (283, 127), (283, 128), (283, 129), (283, 130), (283, 131), (283, 132), (283, 133), (283, 134), (283, 135), (283, 136), (283, 137), (283, 138), (283, 139), (283, 140), (283, 141), (283, 142), (283, 143), (283, 144), (283, 145), (283, 146), (283, 148), (284, 120), (284, 122), (284, 123), (284, 124), (284, 125), (284, 126), (284, 127), (284, 128), (284, 129), (284, 130), (284, 131), (284, 132), (284, 133), (284, 134), (284, 135), (284, 136), (284, 137),
(284, 138), (284, 139), (284, 140), (284, 141), (284, 142), (284, 143), (284, 144), (284, 145), (284, 146), (284, 147), (284, 149), (285, 119), (285, 121), (285, 122), (285, 123), (285, 124), (285, 125), (285, 126), (285, 127), (285, 128), (285, 129), (285, 130), (285, 131), (285, 132), (285, 133), (285, 134), (285, 135), (285, 136), (285, 137), (285, 138), (285, 139), (285, 140), (285, 141), (285, 142), (285, 143), (285, 144), (285, 145), (285, 146), (285, 147), (285, 149), (286, 116), (286, 120), (286, 121), (286, 122), (286, 123), (286, 124), (286, 125), (286, 126), (286, 127), (286, 128), (286, 129), (286, 130), (286, 131), (286, 132), (286, 133), (286, 134), (286, 135), (286, 136), (286, 137), (286, 138), (286, 139), (286, 140), (286, 141), (286, 142), (286, 143), (286, 144), (286, 145), (286, 146), (286, 147), (286, 148), (286, 150), (287, 116),
(287, 119), (287, 120), (287, 121), (287, 122), (287, 123), (287, 124), (287, 125), (287, 126), (287, 127), (287, 128), (287, 129), (287, 130), (287, 131), (287, 132), (287, 133), (287, 134), (287, 135), (287, 136), (287, 137), (287, 138), (287, 139), (287, 140), (287, 141), (287, 142), (287, 143), (287, 144), (287, 145), (287, 146), (287, 147), (287, 148), (287, 149), (287, 151), (288, 115), (288, 117), (288, 118), (288, 119), (288, 120), (288, 121), (288, 122), (288, 123), (288, 124), (288, 125), (288, 126), (288, 127), (288, 128), (288, 129), (288, 130), (288, 131), (288, 132), (288, 133), (288, 134), (288, 135), (288, 136), (288, 137), (288, 138), (288, 139), (288, 140), (288, 141), (288, 142), (288, 143), (288, 144), (288, 145), (288, 146), (288, 147), (288, 148), (288, 149), (288, 151), (289, 115), (289, 117), (289, 118), (289, 119), (289, 120),
(289, 121), (289, 122), (289, 123), (289, 124), (289, 125), (289, 126), (289, 127), (289, 128), (289, 129), (289, 130), (289, 131), (289, 132), (289, 133), (289, 134), (289, 135), (289, 136), (289, 137), (289, 138), (289, 139), (289, 140), (289, 141), (289, 142), (289, 143), (289, 144), (289, 145), (289, 146), (289, 147), (289, 148), (289, 149), (289, 150), (289, 152), (290, 115), (290, 117), (290, 118), (290, 119), (290, 120), (290, 121), (290, 122), (290, 123), (290, 124), (290, 125), (290, 126), (290, 127), (290, 128), (290, 129), (290, 130), (290, 131), (290, 132), (290, 133), (290, 134), (290, 135), (290, 136), (290, 137), (290, 138), (290, 139), (290, 140), (290, 141), (290, 142), (290, 143), (290, 144), (290, 145), (290, 146), (290, 147), (290, 148), (290, 149), (290, 150), (290, 151), (290, 153), (291, 114), (291, 116), (291, 117), (291, 118),
(291, 119), (291, 120), (291, 121), (291, 122), (291, 123), (291, 124), (291, 125), (291, 126), (291, 127), (291, 128), (291, 129), (291, 130), (291, 131), (291, 132), (291, 133), (291, 134), (291, 135), (291, 136), (291, 137), (291, 138), (291, 139), (291, 140), (291, 141), (291, 142), (291, 143), (291, 144), (291, 145), (291, 146), (291, 147), (291, 148), (291, 149), (291, 150), (291, 151), (291, 153), (292, 114), (292, 116), (292, 117), (292, 118), (292, 119), (292, 120), (292, 121), (292, 122), (292, 123), (292, 124), (292, 125), (292, 126), (292, 127), (292, 128), (292, 129), (292, 130), (292, 131), (292, 132), (292, 133), (292, 134), (292, 135), (292, 136), (292, 137), (292, 138), (292, 139), (292, 140), (292, 141), (292, 142), (292, 143), (292, 144), (292, 145), (292, 146), (292, 147), (292, 148), (292, 149), (292, 150), (292, 151), (292, 152),
(292, 154), (293, 114), (293, 116), (293, 117), (293, 118), (293, 119), (293, 120), (293, 121), (293, 122), (293, 123), (293, 124), (293, 125), (293, 126), (293, 127), (293, 128), (293, 129), (293, 130), (293, 131), (293, 132), (293, 133), (293, 134), (293, 135), (293, 136), (293, 137), (293, 138), (293, 139), (293, 140), (293, 141), (293, 142), (293, 143), (293, 144), (293, 145), (293, 146), (293, 147), (293, 148), (293, 149), (293, 150), (293, 151), (293, 152), (293, 154), (294, 113), (294, 115), (294, 116), (294, 117), (294, 118), (294, 119), (294, 120), (294, 121), (294, 122), (294, 123), (294, 124), (294, 125), (294, 126), (294, 127), (294, 128), (294, 129), (294, 130), (294, 131), (294, 132), (294, 133), (294, 134), (294, 135), (294, 136), (294, 137), (294, 138), (294, 139), (294, 140), (294, 141), (294, 142), (294, 143), (294, 144), (294, 145),
(294, 146), (294, 147), (294, 148), (294, 149), (294, 150), (294, 151), (294, 152), (294, 154), (295, 112), (295, 114), (295, 115), (295, 116), (295, 117), (295, 118), (295, 119), (295, 120), (295, 121), (295, 122), (295, 123), (295, 124), (295, 125), (295, 126), (295, 127), (295, 128), (295, 129), (295, 130), (295, 131), (295, 132), (295, 133), (295, 134), (295, 135), (295, 136), (295, 137), (295, 138), (295, 139), (295, 140), (295, 141), (295, 142), (295, 143), (295, 144), (295, 145), (295, 146), (295, 147), (295, 148), (295, 149), (295, 150), (295, 151), (295, 152), (295, 153), (295, 155), (296, 112), (296, 114), (296, 115), (296, 116), (296, 117), (296, 118), (296, 119), (296, 120), (296, 121), (296, 122), (296, 123), (296, 124), (296, 125), (296, 126), (296, 127), (296, 128), (296, 129), (296, 130), (296, 131), (296, 132), (296, 133), (296, 134),
(296, 135), (296, 136), (296, 137), (296, 138), (296, 139), (296, 140), (296, 141), (296, 142), (296, 143), (296, 144), (296, 145), (296, 146), (296, 147), (296, 148), (296, 149), (296, 150), (296, 151), (296, 152), (296, 153), (296, 155), (297, 111), (297, 113), (297, 114), (297, 115), (297, 116), (297, 117), (297, 118), (297, 119), (297, 120), (297, 121), (297, 122), (297, 123), (297, 124), (297, 125), (297, 126), (297, 127), (297, 128), (297, 129), (297, 130), (297, 131), (297, 132), (297, 133), (297, 134), (297, 135), (297, 136), (297, 137), (297, 138), (297, 139), (297, 140), (297, 141), (297, 142), (297, 143), (297, 144), (297, 145), (297, 146), (297, 147), (297, 148), (297, 149), (297, 150), (297, 151), (297, 152), (297, 153), (297, 155), (298, 109), (298, 112), (298, 113), (298, 114), (298, 115), (298, 116), (298, 117), (298, 118), (298, 119),
(298, 120), (298, 121), (298, 122), (298, 123), (298, 124), (298, 125), (298, 126), (298, 127), (298, 128), (298, 129), (298, 130), (298, 131), (298, 132), (298, 133), (298, 134), (298, 135), (298, 136), (298, 137), (298, 138), (298, 139), (298, 140), (298, 141), (298, 142), (298, 143), (298, 144), (298, 145), (298, 146), (298, 147), (298, 148), (298, 149), (298, 150), (298, 151), (298, 152), (298, 153), (298, 154), (298, 156), (299, 109), (299, 111), (299, 112), (299, 113), (299, 114), (299, 115), (299, 116), (299, 117), (299, 118), (299, 119), (299, 120), (299, 121), (299, 122), (299, 123), (299, 124), (299, 125), (299, 126), (299, 127), (299, 128), (299, 129), (299, 130), (299, 131), (299, 132), (299, 133), (299, 134), (299, 135), (299, 136), (299, 137), (299, 138), (299, 139), (299, 140), (299, 141), (299, 142), (299, 143), (299, 144), (299, 145),
(299, 146), (299, 147), (299, 148), (299, 149), (299, 150), (299, 151), (299, 152), (299, 153), (299, 154), (299, 156), (300, 109), (300, 111), (300, 112), (300, 113), (300, 114), (300, 115), (300, 116), (300, 117), (300, 118), (300, 119), (300, 120), (300, 121), (300, 122), (300, 123), (300, 124), (300, 125), (300, 126), (300, 127), (300, 128), (300, 129), (300, 130), (300, 131), (300, 132), (300, 133), (300, 134), (300, 135), (300, 136), (300, 137), (300, 138), (300, 139), (300, 140), (300, 141), (300, 142), (300, 143), (300, 144), (300, 145), (300, 146), (300, 147), (300, 148), (300, 149), (300, 150), (300, 151), (300, 152), (300, 153), (300, 154), (300, 156), (301, 109), (301, 111), (301, 112), (301, 113), (301, 114), (301, 115), (301, 116), (301, 117), (301, 118), (301, 119), (301, 120), (301, 121), (301, 122), (301, 123), (301, 124), (301, 125),
(301, 126), (301, 127), (301, 128), (301, 129), (301, 130), (301, 131), (301, 132), (301, 133), (301, 134), (301, 135), (301, 136), (301, 137), (301, 138), (301, 139), (301, 140), (301, 141), (301, 142), (301, 143), (301, 144), (301, 145), (301, 146), (301, 147), (301, 148), (301, 149), (301, 150), (301, 151), (301, 152), (301, 153), (301, 154), (301, 156), (302, 110), (302, 112), (302, 113), (302, 114), (302, 115), (302, 116), (302, 117), (302, 118), (302, 119), (302, 120), (302, 121), (302, 122), (302, 123), (302, 124), (302, 125), (302, 126), (302, 127), (302, 128), (302, 129), (302, 130), (302, 131), (302, 132), (302, 133), (302, 134), (302, 135), (302, 136), (302, 137), (302, 138), (302, 139), (302, 140), (302, 141), (302, 142), (302, 143), (302, 144), (302, 145), (302, 146), (302, 147), (302, 148), (302, 149), (302, 150), (302, 151), (302, 152),
(302, 153), (302, 154), (302, 156), (303, 110), (303, 112), (303, 113), (303, 114), (303, 115), (303, 116), (303, 117), (303, 118), (303, 119), (303, 120), (303, 121), (303, 122), (303, 123), (303, 124), (303, 125), (303, 126), (303, 127), (303, 128), (303, 129), (303, 130), (303, 131), (303, 132), (303, 133), (303, 134), (303, 135), (303, 136), (303, 137), (303, 138), (303, 139), (303, 140), (303, 141), (303, 142), (303, 143), (303, 144), (303, 145), (303, 146), (303, 147), (303, 148), (303, 149), (303, 150), (303, 151), (303, 152), (303, 153), (303, 154), (303, 155), (303, 156), (303, 157), (304, 111), (304, 113), (304, 114), (304, 115), (304, 116), (304, 117), (304, 118), (304, 119), (304, 120), (304, 121), (304, 122), (304, 123), (304, 124), (304, 125), (304, 126), (304, 127), (304, 128), (304, 129), (304, 130), (304, 131), (304, 132), (304, 133),
(304, 134), (304, 135), (304, 136), (304, 137), (304, 138), (304, 139), (304, 140), (304, 141), (304, 142), (304, 143), (304, 144), (304, 145), (304, 146), (304, 147), (304, 148), (304, 149), (304, 150), (304, 151), (304, 152), (304, 153), (304, 154), (304, 155), (304, 157), (305, 111), (305, 113), (305, 114), (305, 115), (305, 116), (305, 117), (305, 118), (305, 119), (305, 120), (305, 121), (305, 122), (305, 123), (305, 124), (305, 125), (305, 126), (305, 127), (305, 128), (305, 129), (305, 130), (305, 131), (305, 132), (305, 133), (305, 134), (305, 135), (305, 136), (305, 137), (305, 138), (305, 139), (305, 140), (305, 141), (305, 142), (305, 143), (305, 144), (305, 145), (305, 146), (305, 147), (305, 148), (305, 149), (305, 150), (305, 151), (305, 152), (305, 153), (305, 154), (305, 155), (305, 157), (306, 112), (306, 114), (306, 115), (306, 116),
(306, 117), (306, 118), (306, 119), (306, 120), (306, 121), (306, 122), (306, 123), (306, 124), (306, 125), (306, 126), (306, 127), (306, 128), (306, 129), (306, 130), (306, 131), (306, 132), (306, 133), (306, 134), (306, 135), (306, 136), (306, 137), (306, 138), (306, 139), (306, 140), (306, 141), (306, 142), (306, 143), (306, 144), (306, 145), (306, 146), (306, 147), (306, 148), (306, 149), (306, 150), (306, 151), (306, 152), (306, 153), (306, 154), (306, 156), (307, 112), (307, 114), (307, 115), (307, 116), (307, 117), (307, 118), (307, 119), (307, 120), (307, 121), (307, 122), (307, 123), (307, 124), (307, 125), (307, 126), (307, 127), (307, 128), (307, 129), (307, 130), (307, 131), (307, 132), (307, 133), (307, 134), (307, 135), (307, 136), (307, 137), (307, 138), (307, 139), (307, 140), (307, 141), (307, 142), (307, 143), (307, 144), (307, 145),
(307, 146), (307, 147), (307, 148), (307, 149), (307, 150), (307, 151), (307, 152), (307, 153), (307, 154), (307, 156), (308, 113), (308, 115), (308, 116), (308, 117), (308, 118), (308, 119), (308, 120), (308, 121), (308, 122), (308, 123), (308, 124), (308, 125), (308, 126), (308, 127), (308, 128), (308, 129), (308, 130), (308, 131), (308, 132), (308, 133), (308, 134), (308, 135), (308, 136), (308, 137), (308, 138), (308, 139), (308, 140), (308, 141), (308, 142), (308, 143), (308, 144), (308, 145), (308, 146), (308, 147), (308, 148), (308, 149), (308, 150), (308, 151), (308, 152), (308, 153), (308, 154), (308, 156), (309, 114), (309, 116), (309, 117), (309, 118), (309, 119), (309, 120), (309, 121), (309, 122), (309, 123), (309, 124), (309, 125), (309, 126), (309, 127), (309, 128), (309, 129), (309, 130), (309, 131), (309, 132), (309, 133), (309, 134),
(309, 135), (309, 136), (309, 137), (309, 138), (309, 139), (309, 140), (309, 141), (309, 142), (309, 143), (309, 144), (309, 145), (309, 146), (309, 147), (309, 148), (309, 149), (309, 150), (309, 151), (309, 152), (309, 153), (309, 154), (309, 156), (310, 115), (310, 117), (310, 118), (310, 119), (310, 120), (310, 121), (310, 122), (310, 123), (310, 124), (310, 125), (310, 126), (310, 127), (310, 128), (310, 129), (310, 130), (310, 131), (310, 132), (310, 133), (310, 134), (310, 135), (310, 136), (310, 137), (310, 138), (310, 139), (310, 140), (310, 141), (310, 142), (310, 143), (310, 144), (310, 145), (310, 146), (310, 147), (310, 148), (310, 149), (310, 150), (310, 151), (310, 152), (310, 153), (310, 154), (310, 156), (311, 116), (311, 118), (311, 119), (311, 120), (311, 121), (311, 122), (311, 123), (311, 124), (311, 125), (311, 126), (311, 127),
(311, 128), (311, 129), (311, 130), (311, 131), (311, 132), (311, 133), (311, 134), (311, 135), (311, 136), (311, 137), (311, 138), (311, 139), (311, 140), (311, 141), (311, 142), (311, 143), (311, 144), (311, 145), (311, 146), (311, 147), (311, 148), (311, 149), (311, 150), (311, 151), (311, 152), (311, 153), (311, 155), (312, 119), (312, 120), (312, 121), (312, 122), (312, 123), (312, 124), (312, 125), (312, 126), (312, 127), (312, 128), (312, 129), (312, 130), (312, 131), (312, 132), (312, 133), (312, 134), (312, 135), (312, 136), (312, 137), (312, 138), (312, 139), (312, 140), (312, 141), (312, 142), (312, 143), (312, 144), (312, 145), (312, 146), (312, 147), (312, 148), (312, 149), (312, 150), (312, 151), (312, 152), (312, 153), (312, 155), (313, 120), (313, 121), (313, 122), (313, 123), (313, 124), (313, 125), (313, 126), (313, 127), (313, 128),
(313, 129), (313, 130), (313, 131), (313, 132), (313, 133), (313, 134), (313, 135), (313, 136), (313, 137), (313, 138), (313, 139), (313, 140), (313, 141), (313, 142), (313, 143), (313, 144), (313, 145), (313, 146), (313, 147), (313, 148), (313, 149), (313, 150), (313, 151), (313, 152), (313, 153), (313, 155), (314, 119), (314, 121), (314, 122), (314, 123), (314, 124), (314, 125), (314, 126), (314, 127), (314, 128), (314, 129), (314, 130), (314, 131), (314, 132), (314, 133), (314, 134), (314, 135), (314, 136), (314, 137), (314, 138), (314, 139), (314, 140), (314, 141), (314, 142), (314, 143), (314, 144), (314, 145), (314, 146), (314, 147), (314, 148), (314, 149), (314, 150), (314, 151), (314, 152), (314, 153), (314, 155), (315, 120), (315, 122), (315, 123), (315, 124), (315, 125), (315, 126), (315, 127), (315, 128), (315, 129), (315, 130), (315, 131),
(315, 132), (315, 133), (315, 134), (315, 135), (315, 136), (315, 137), (315, 138), (315, 139), (315, 140), (315, 141), (315, 142), (315, 143), (315, 144), (315, 145), (315, 146), (315, 147), (315, 148), (315, 149), (315, 150), (315, 151), (315, 152), (315, 153), (315, 155), (316, 121), (316, 123), (316, 124), (316, 125), (316, 126), (316, 127), (316, 128), (316, 129), (316, 130), (316, 131), (316, 132), (316, 133), (316, 134), (316, 135), (316, 136), (316, 137), (316, 138), (316, 139), (316, 140), (316, 141), (316, 142), (316, 143), (316, 144), (316, 145), (316, 146), (316, 147), (316, 148), (316, 149), (316, 150), (316, 151), (316, 152), (316, 153), (316, 155), (317, 122), (317, 125), (317, 126), (317, 127), (317, 128), (317, 129), (317, 130), (317, 131), (317, 132), (317, 133), (317, 134), (317, 135), (317, 136), (317, 137), (317, 138), (317, 139),
(317, 140), (317, 141), (317, 142), (317, 143), (317, 144), (317, 145), (317, 146), (317, 147), (317, 148), (317, 149), (317, 150), (317, 151), (317, 152), (317, 154), (318, 123), (318, 126), (318, 127), (318, 128), (318, 129), (318, 130), (318, 131), (318, 132), (318, 133), (318, 134), (318, 135), (318, 136), (318, 137), (318, 138), (318, 139), (318, 140), (318, 141), (318, 142), (318, 143), (318, 144), (318, 145), (318, 146), (318, 147), (318, 148), (318, 149), (318, 150), (318, 151), (318, 152), (318, 154), (319, 127), (319, 128), (319, 129), (319, 130), (319, 131), (319, 132), (319, 133), (319, 134), (319, 135), (319, 136), (319, 137), (319, 138), (319, 139), (319, 140), (319, 141), (319, 142), (319, 143), (319, 144), (319, 145), (319, 146), (319, 147), (319, 148), (319, 149), (319, 150), (319, 151), (319, 152), (319, 154), (320, 126), (320, 129),
(320, 130), (320, 131), (320, 132), (320, 133), (320, 134), (320, 135), (320, 136), (320, 137), (320, 138), (320, 139), (320, 140), (320, 141), (320, 142), (320, 143), (320, 144), (320, 145), (320, 146), (320, 147), (320, 148), (320, 149), (320, 150), (320, 151), (320, 153), (321, 127), (321, 130), (321, 131), (321, 132), (321, 133), (321, 134), (321, 135), (321, 136), (321, 137), (321, 138), (321, 139), (321, 140), (321, 141), (321, 142), (321, 143), (321, 144), (321, 145), (321, 146), (321, 147), (321, 148), (321, 149), (321, 150), (321, 151), (321, 153), (322, 129), (322, 132), (322, 133), (322, 134), (322, 135), (322, 136), (322, 137), (322, 138), (322, 139), (322, 140), (322, 141), (322, 142), (322, 143), (322, 144), (322, 145), (322, 146), (322, 147), (322, 148), (322, 149), (322, 150), (322, 152), (323, 130), (323, 134), (323, 135), (323, 136),
(323, 137), (323, 138), (323, 139), (323, 140), (323, 141), (323, 142), (323, 143), (323, 144), (323, 145), (323, 146), (323, 147), (323, 148), (323, 149), (323, 150), (323, 152), (324, 132), (324, 135), (324, 136), (324, 137), (324, 138), (324, 139), (324, 140), (324, 141), (324, 142), (324, 143), (324, 144), (324, 145), (324, 146), (324, 147), (324, 148), (324, 149), (324, 150), (324, 152), (325, 134), (325, 137), (325, 138), (325, 139), (325, 140), (325, 141), (325, 142), (325, 143), (325, 144), (325, 145), (325, 146), (325, 147), (325, 148), (325, 149), (325, 151), (326, 136), (326, 139), (326, 140), (326, 141), (326, 142), (326, 143), (326, 144), (326, 145), (326, 146), (326, 147), (326, 148), (326, 149), (326, 151), (327, 137), (327, 138), (327, 142), (327, 143), (327, 144), (327, 145), (327, 146), (327, 147), (327, 148), (327, 150), (328, 140),
(328, 141), (328, 145), (328, 146), (328, 147), (328, 148), (328, 150), (329, 142), (329, 144), (329, 150), (330, 145), (330, 146), (330, 147), (330, 149), )
coordinates_8900FF = ((61, 184),
(61, 186), (61, 187), (61, 189), (62, 182), (62, 183), (62, 189), (63, 180), (63, 184), (63, 185), (63, 187), (64, 178), (64, 181), (64, 182), (64, 183), (64, 184), (64, 186), (65, 177), (65, 180), (65, 181), (65, 182), (65, 183), (65, 184), (65, 186), (66, 175), (66, 178), (66, 179), (66, 180), (66, 181), (66, 182), (66, 183), (66, 184), (66, 186), (67, 174), (67, 177), (67, 178), (67, 179), (67, 180), (67, 181), (67, 182), (67, 183), (67, 184), (67, 185), (67, 187), (68, 176), (68, 177), (68, 178), (68, 179), (68, 180), (68, 181), (68, 182), (68, 183), (68, 184), (68, 185), (68, 187), (69, 173), (69, 175), (69, 176), (69, 177), (69, 178), (69, 179), (69, 180), (69, 181), (69, 182), (69, 183), (69, 184), (69, 185), (69, 187), (70, 172), (70, 174), (70, 175), (70, 176), (70, 177),
(70, 178), (70, 179), (70, 180), (70, 181), (70, 182), (70, 183), (70, 184), (70, 185), (70, 186), (70, 188), (71, 171), (71, 173), (71, 174), (71, 175), (71, 176), (71, 177), (71, 178), (71, 179), (71, 180), (71, 181), (71, 182), (71, 183), (71, 184), (71, 185), (71, 186), (71, 188), (72, 171), (72, 173), (72, 174), (72, 175), (72, 176), (72, 177), (72, 178), (72, 179), (72, 180), (72, 181), (72, 182), (72, 183), (72, 184), (72, 187), (72, 188), (73, 170), (73, 172), (73, 173), (73, 174), (73, 175), (73, 176), (73, 177), (73, 178), (73, 179), (73, 180), (73, 181), (73, 182), (73, 183), (73, 185), (74, 169), (74, 171), (74, 172), (74, 173), (74, 174), (74, 175), (74, 176), (74, 177), (74, 178), (74, 179), (74, 180), (74, 181), (74, 182), (74, 184), (75, 169), (75, 171), (75, 172),
(75, 173), (75, 174), (75, 175), (75, 176), (75, 177), (75, 178), (75, 179), (75, 180), (75, 181), (75, 183), (76, 168), (76, 170), (76, 171), (76, 172), (76, 173), (76, 174), (76, 175), (76, 176), (76, 177), (76, 178), (76, 179), (76, 180), (76, 182), (77, 168), (77, 170), (77, 171), (77, 172), (77, 173), (77, 174), (77, 175), (77, 176), (77, 177), (77, 178), (77, 179), (77, 181), (78, 168), (78, 170), (78, 171), (78, 172), (78, 173), (78, 174), (78, 175), (78, 176), (78, 177), (78, 178), (78, 180), (79, 168), (79, 170), (79, 171), (79, 172), (79, 173), (79, 174), (79, 175), (79, 176), (79, 177), (79, 178), (79, 180), (80, 168), (80, 170), (80, 171), (80, 172), (80, 173), (80, 174), (80, 175), (80, 176), (80, 177), (80, 179), (81, 168), (81, 170), (81, 171), (81, 172), (81, 173),
(81, 174), (81, 175), (81, 176), (81, 177), (81, 179), (82, 168), (82, 170), (82, 171), (82, 172), (82, 173), (82, 174), (82, 175), (82, 176), (82, 177), (82, 179), (83, 169), (83, 171), (83, 172), (83, 173), (83, 174), (83, 175), (83, 176), (83, 177), (83, 179), (84, 169), (84, 171), (84, 172), (84, 173), (84, 174), (84, 175), (84, 176), (84, 178), (85, 169), (85, 171), (85, 172), (85, 173), (85, 174), (85, 175), (86, 170), (86, 172), (86, 173), (86, 174), (86, 176), (87, 170), (87, 173), (87, 175), (88, 171), (89, 172), (89, 174), (310, 172), (310, 174), (311, 171), (311, 175), (312, 170), (312, 173), (312, 175), (313, 170), (313, 172), (313, 173), (313, 174), (313, 177), (314, 169), (314, 171), (314, 172), (314, 173), (314, 174), (314, 175), (314, 178), (315, 169), (315, 171), (315, 172), (315, 173),
(315, 174), (315, 175), (315, 176), (315, 178), (316, 169), (316, 171), (316, 172), (316, 173), (316, 174), (316, 175), (316, 176), (316, 177), (316, 179), (317, 168), (317, 170), (317, 171), (317, 172), (317, 173), (317, 174), (317, 175), (317, 176), (317, 177), (317, 179), (318, 168), (318, 170), (318, 171), (318, 172), (318, 173), (318, 174), (318, 175), (318, 176), (318, 177), (318, 179), (319, 168), (319, 170), (319, 171), (319, 172), (319, 173), (319, 174), (319, 175), (319, 176), (319, 177), (319, 179), (320, 168), (320, 170), (320, 171), (320, 172), (320, 173), (320, 174), (320, 175), (320, 176), (320, 177), (320, 178), (320, 180), (321, 168), (321, 170), (321, 171), (321, 172), (321, 173), (321, 174), (321, 175), (321, 176), (321, 177), (321, 178), (321, 180), (322, 168), (322, 170), (322, 171), (322, 172), (322, 173), (322, 174), (322, 175),
(322, 176), (322, 177), (322, 178), (322, 179), (322, 181), (323, 168), (323, 170), (323, 171), (323, 172), (323, 173), (323, 174), (323, 175), (323, 176), (323, 177), (323, 178), (323, 179), (323, 180), (323, 182), (324, 169), (324, 171), (324, 172), (324, 173), (324, 174), (324, 175), (324, 176), (324, 177), (324, 178), (324, 179), (324, 180), (324, 181), (324, 183), (325, 169), (325, 171), (325, 172), (325, 173), (325, 174), (325, 175), (325, 176), (325, 177), (325, 178), (325, 179), (325, 180), (325, 181), (325, 182), (325, 184), (326, 170), (326, 172), (326, 173), (326, 174), (326, 175), (326, 176), (326, 177), (326, 178), (326, 179), (326, 180), (326, 181), (326, 182), (326, 183), (326, 186), (327, 171), (327, 173), (327, 174), (327, 175), (327, 176), (327, 177), (327, 178), (327, 179), (327, 180), (327, 181), (327, 182), (327, 183), (327, 184),
(327, 187), (327, 188), (328, 171), (328, 173), (328, 174), (328, 175), (328, 176), (328, 177), (328, 178), (328, 179), (328, 180), (328, 181), (328, 182), (328, 183), (328, 184), (328, 185), (328, 186), (328, 188), (329, 172), (329, 174), (329, 175), (329, 176), (329, 177), (329, 178), (329, 179), (329, 180), (329, 181), (329, 182), (329, 183), (329, 184), (329, 185), (329, 186), (329, 188), (330, 173), (330, 175), (330, 176), (330, 177), (330, 178), (330, 179), (330, 180), (330, 181), (330, 182), (330, 183), (330, 184), (330, 185), (330, 187), (331, 174), (331, 176), (331, 177), (331, 178), (331, 179), (331, 180), (331, 181), (331, 182), (331, 183), (331, 184), (331, 185), (331, 187), (332, 177), (332, 178), (332, 179), (332, 180), (332, 181), (332, 182), (332, 183), (332, 184), (332, 185), (332, 187), (333, 176), (333, 178), (333, 179), (333, 180),
(333, 181), (333, 182), (333, 183), (333, 184), (333, 186), (334, 177), (334, 180), (334, 181), (334, 182), (334, 183), (334, 184), (334, 186), (335, 178), (335, 182), (335, 183), (335, 184), (335, 186), (336, 180), (336, 184), (336, 185), (336, 187), (337, 182), (337, 183), (337, 189), (338, 185), (338, 186), (338, 187), (338, 189), )
coordinates_00C4FF = ((37, 171),
(37, 172), (37, 173), (37, 174), (37, 175), (37, 176), (37, 178), (38, 167), (38, 168), (38, 169), (38, 170), (38, 178), (39, 165), (39, 166), (39, 171), (39, 172), (39, 173), (39, 174), (39, 175), (39, 176), (39, 177), (39, 179), (40, 162), (40, 167), (40, 168), (40, 169), (40, 170), (40, 171), (40, 172), (40, 173), (40, 174), (40, 175), (40, 176), (40, 177), (40, 178), (41, 160), (41, 164), (41, 165), (41, 166), (41, 167), (41, 168), (41, 169), (41, 170), (41, 171), (41, 172), (41, 173), (41, 174), (41, 175), (41, 176), (41, 177), (41, 178), (41, 179), (41, 181), (42, 158), (42, 159), (42, 162), (42, 163), (42, 164), (42, 165), (42, 166), (42, 167), (42, 168), (42, 169), (42, 170), (42, 171), (42, 172), (42, 173), (42, 174), (42, 175), (42, 176), (42, 177), (42, 178), (42, 179),
(42, 180), (42, 183), (42, 184), (42, 185), (43, 153), (43, 154), (43, 155), (43, 156), (43, 160), (43, 161), (43, 162), (43, 163), (43, 164), (43, 165), (43, 166), (43, 167), (43, 168), (43, 169), (43, 170), (43, 171), (43, 172), (43, 173), (43, 174), (43, 175), (43, 176), (43, 177), (43, 178), (43, 179), (43, 180), (43, 181), (43, 186), (44, 146), (44, 147), (44, 148), (44, 149), (44, 150), (44, 151), (44, 152), (44, 157), (44, 158), (44, 159), (44, 160), (44, 161), (44, 162), (44, 163), (44, 164), (44, 165), (44, 166), (44, 167), (44, 168), (44, 169), (44, 170), (44, 171), (44, 172), (44, 173), (44, 174), (44, 175), (44, 176), (44, 177), (44, 178), (44, 179), (44, 180), (44, 181), (44, 182), (44, 183), (44, 184), (44, 187), (45, 142), (45, 143), (45, 144), (45, 145), (45, 153),
(45, 154), (45, 155), (45, 156), (45, 157), (45, 158), (45, 159), (45, 160), (45, 161), (45, 162), (45, 163), (45, 164), (45, 165), (45, 166), (45, 167), (45, 168), (45, 169), (45, 170), (45, 171), (45, 172), (45, 173), (45, 174), (45, 175), (45, 176), (45, 177), (45, 178), (45, 179), (45, 180), (45, 181), (45, 182), (45, 185), (46, 139), (46, 146), (46, 147), (46, 148), (46, 149), (46, 150), (46, 151), (46, 152), (46, 153), (46, 154), (46, 155), (46, 156), (46, 157), (46, 158), (46, 159), (46, 160), (46, 161), (46, 162), (46, 163), (46, 164), (46, 165), (46, 166), (46, 167), (46, 168), (46, 169), (46, 170), (46, 171), (46, 172), (46, 173), (46, 174), (46, 175), (46, 176), (46, 177), (46, 178), (46, 179), (46, 180), (46, 181), (46, 184), (47, 137), (47, 141), (47, 142), (47, 143),
(47, 144), (47, 145), (47, 146), (47, 147), (47, 148), (47, 149), (47, 150), (47, 151), (47, 152), (47, 153), (47, 154), (47, 155), (47, 156), (47, 157), (47, 158), (47, 159), (47, 160), (47, 161), (47, 162), (47, 163), (47, 164), (47, 165), (47, 166), (47, 167), (47, 168), (47, 169), (47, 170), (47, 171), (47, 172), (47, 173), (47, 174), (47, 175), (47, 176), (47, 177), (47, 178), (47, 179), (47, 182), (48, 135), (48, 139), (48, 140), (48, 141), (48, 142), (48, 143), (48, 144), (48, 145), (48, 146), (48, 147), (48, 148), (48, 149), (48, 150), (48, 151), (48, 152), (48, 153), (48, 154), (48, 155), (48, 156), (48, 157), (48, 158), (48, 159), (48, 160), (48, 161), (48, 162), (48, 163), (48, 164), (48, 165), (48, 166), (48, 167), (48, 168), (48, 169), (48, 170), (48, 171), (48, 172),
(48, 173), (48, 174), (48, 175), (48, 176), (48, 177), (48, 178), (48, 181), (49, 133), (49, 134), (49, 137), (49, 138), (49, 139), (49, 140), (49, 141), (49, 142), (49, 143), (49, 144), (49, 145), (49, 146), (49, 147), (49, 148), (49, 149), (49, 150), (49, 151), (49, 152), (49, 153), (49, 154), (49, 155), (49, 156), (49, 157), (49, 158), (49, 159), (49, 160), (49, 161), (49, 162), (49, 163), (49, 164), (49, 165), (49, 166), (49, 167), (49, 168), (49, 169), (49, 170), (49, 171), (49, 172), (49, 173), (49, 174), (49, 175), (49, 176), (49, 179), (50, 132), (50, 135), (50, 136), (50, 137), (50, 138), (50, 139), (50, 140), (50, 141), (50, 142), (50, 143), (50, 144), (50, 145), (50, 146), (50, 147), (50, 148), (50, 149), (50, 150), (50, 151), (50, 152), (50, 153), (50, 154), (50, 155),
(50, 156), (50, 157), (50, 158), (50, 159), (50, 160), (50, 161), (50, 162), (50, 163), (50, 164), (50, 165), (50, 166), (50, 167), (50, 168), (50, 169), (50, 170), (50, 171), (50, 172), (50, 173), (50, 174), (50, 178), (51, 130), (51, 133), (51, 134), (51, 135), (51, 136), (51, 137), (51, 138), (51, 139), (51, 140), (51, 141), (51, 142), (51, 143), (51, 144), (51, 145), (51, 146), (51, 147), (51, 148), (51, 149), (51, 150), (51, 151), (51, 152), (51, 153), (51, 154), (51, 155), (51, 156), (51, 157), (51, 158), (51, 159), (51, 160), (51, 161), (51, 162), (51, 163), (51, 164), (51, 165), (51, 166), (51, 167), (51, 168), (51, 169), (51, 170), (51, 171), (51, 172), (51, 176), (52, 129), (52, 132), (52, 133), (52, 134), (52, 135), (52, 136), (52, 137), (52, 138), (52, 139), (52, 140),
(52, 141), (52, 142), (52, 143), (52, 144), (52, 145), (52, 146), (52, 147), (52, 148), (52, 149), (52, 150), (52, 151), (52, 152), (52, 153), (52, 154), (52, 155), (52, 156), (52, 157), (52, 158), (52, 159), (52, 160), (52, 161), (52, 162), (52, 163), (52, 164), (52, 165), (52, 166), (52, 167), (52, 168), (52, 169), (52, 170), (52, 174), (53, 127), (53, 130), (53, 131), (53, 132), (53, 133), (53, 134), (53, 135), (53, 136), (53, 137), (53, 138), (53, 139), (53, 140), (53, 141), (53, 142), (53, 143), (53, 144), (53, 145), (53, 146), (53, 147), (53, 148), (53, 149), (53, 150), (53, 151), (53, 152), (53, 153), (53, 154), (53, 155), (53, 156), (53, 157), (53, 158), (53, 159), (53, 160), (53, 161), (53, 162), (53, 163), (53, 164), (53, 165), (53, 166), (53, 167), (53, 168), (53, 172),
(54, 126), (54, 129), (54, 130), (54, 131), (54, 132), (54, 133), (54, 134), (54, 135), (54, 136), (54, 137), (54, 138), (54, 139), (54, 140), (54, 141), (54, 142), (54, 143), (54, 144), (54, 145), (54, 146), (54, 147), (54, 148), (54, 149), (54, 150), (54, 151), (54, 152), (54, 153), (54, 154), (54, 155), (54, 156), (54, 157), (54, 158), (54, 159), (54, 160), (54, 161), (54, 162), (54, 163), (54, 164), (54, 165), (54, 166), (54, 170), (55, 124), (55, 127), (55, 128), (55, 129), (55, 130), (55, 131), (55, 132), (55, 133), (55, 134), (55, 135), (55, 136), (55, 137), (55, 138), (55, 139), (55, 140), (55, 141), (55, 142), (55, 143), (55, 144), (55, 145), (55, 146), (55, 147), (55, 148), (55, 149), (55, 150), (55, 151), (55, 152), (55, 153), (55, 154), (55, 155), (55, 156), (55, 157),
(55, 158), (55, 159), (55, 160), (55, 161), (55, 162), (55, 163), (55, 164), (55, 168), (56, 123), (56, 126), (56, 127), (56, 128), (56, 129), (56, 130), (56, 131), (56, 132), (56, 133), (56, 134), (56, 135), (56, 136), (56, 137), (56, 138), (56, 139), (56, 140), (56, 141), (56, 142), (56, 143), (56, 144), (56, 145), (56, 146), (56, 147), (56, 148), (56, 149), (56, 150), (56, 151), (56, 152), (56, 153), (56, 154), (56, 155), (56, 156), (56, 157), (56, 158), (56, 159), (56, 160), (56, 161), (56, 162), (56, 166), (57, 122), (57, 124), (57, 125), (57, 126), (57, 127), (57, 128), (57, 129), (57, 130), (57, 131), (57, 132), (57, 133), (57, 134), (57, 135), (57, 136), (57, 137), (57, 138), (57, 139), (57, 140), (57, 141), (57, 142), (57, 143), (57, 144), (57, 145), (57, 146), (57, 147),
(57, 148), (57, 149), (57, 150), (57, 151), (57, 152), (57, 153), (57, 154), (57, 155), (57, 156), (57, 157), (57, 158), (57, 159), (57, 160), (57, 163), (57, 164), (58, 120), (58, 123), (58, 124), (58, 125), (58, 126), (58, 127), (58, 128), (58, 129), (58, 130), (58, 131), (58, 132), (58, 133), (58, 134), (58, 135), (58, 136), (58, 137), (58, 138), (58, 139), (58, 140), (58, 141), (58, 142), (58, 143), (58, 144), (58, 145), (58, 146), (58, 147), (58, 148), (58, 149), (58, 150), (58, 151), (58, 152), (58, 153), (58, 154), (58, 155), (58, 156), (58, 157), (58, 161), (59, 119), (59, 122), (59, 123), (59, 124), (59, 125), (59, 126), (59, 127), (59, 128), (59, 129), (59, 130), (59, 131), (59, 132), (59, 133), (59, 134), (59, 135), (59, 136), (59, 137), (59, 138), (59, 139), (59, 140),
(59, 141), (59, 142), (59, 143), (59, 144), (59, 145), (59, 146), (59, 147), (59, 148), (59, 149), (59, 150), (59, 151), (59, 152), (59, 153), (59, 154), (59, 155), (59, 159), (60, 118), (60, 121), (60, 122), (60, 123), (60, 124), (60, 125), (60, 126), (60, 127), (60, 128), (60, 129), (60, 130), (60, 131), (60, 132), (60, 133), (60, 134), (60, 135), (60, 136), (60, 137), (60, 138), (60, 139), (60, 140), (60, 141), (60, 142), (60, 143), (60, 144), (60, 145), (60, 146), (60, 147), (60, 148), (60, 149), (60, 150), (60, 151), (60, 152), (60, 153), (60, 154), (60, 157), (61, 117), (61, 119), (61, 120), (61, 121), (61, 122), (61, 123), (61, 124), (61, 125), (61, 126), (61, 127), (61, 128), (61, 129), (61, 130), (61, 131), (61, 132), (61, 133), (61, 134), (61, 135), (61, 136), (61, 137),
(61, 138), (61, 139), (61, 140), (61, 141), (61, 142), (61, 143), (61, 144), (61, 145), (61, 146), (61, 147), (61, 148), (61, 149), (61, 150), (61, 151), (61, 152), (61, 153), (61, 155), (62, 116), (62, 118), (62, 119), (62, 120), (62, 121), (62, 122), (62, 123), (62, 124), (62, 125), (62, 126), (62, 127), (62, 128), (62, 129), (62, 130), (62, 131), (62, 132), (62, 133), (62, 134), (62, 135), (62, 136), (62, 137), (62, 138), (62, 139), (62, 140), (62, 141), (62, 142), (62, 143), (62, 144), (62, 145), (62, 146), (62, 147), (62, 148), (62, 149), (62, 150), (62, 151), (62, 152), (62, 154), (63, 115), (63, 117), (63, 118), (63, 119), (63, 120), (63, 121), (63, 122), (63, 123), (63, 124), (63, 125), (63, 126), (63, 127), (63, 128), (63, 129), (63, 130), (63, 131), (63, 132), (63, 133),
(63, 134), (63, 135), (63, 136), (63, 137), (63, 138), (63, 139), (63, 140), (63, 141), (63, 142), (63, 143), (63, 144), (63, 145), (63, 146), (63, 147), (63, 148), (63, 149), (63, 150), (63, 151), (63, 153), (64, 114), (64, 116), (64, 117), (64, 118), (64, 119), (64, 120), (64, 121), (64, 122), (64, 123), (64, 124), (64, 125), (64, 126), (64, 127), (64, 128), (64, 129), (64, 130), (64, 131), (64, 132), (64, 133), (64, 134), (64, 135), (64, 136), (64, 137), (64, 138), (64, 139), (64, 140), (64, 141), (64, 142), (64, 143), (64, 144), (64, 145), (64, 146), (64, 147), (64, 148), (64, 149), (64, 150), (64, 152), (65, 113), (65, 115), (65, 116), (65, 117), (65, 118), (65, 119), (65, 120), (65, 121), (65, 122), (65, 123), (65, 124), (65, 125), (65, 126), (65, 127), (65, 128), (65, 129),
(65, 130), (65, 131), (65, 132), (65, 133), (65, 134), (65, 135), (65, 136), (65, 137), (65, 138), (65, 139), (65, 140), (65, 141), (65, 142), (65, 143), (65, 144), (65, 145), (65, 146), (65, 147), (65, 151), (66, 112), (66, 114), (66, 115), (66, 116), (66, 117), (66, 118), (66, 119), (66, 120), (66, 121), (66, 122), (66, 123), (66, 124), (66, 125), (66, 126), (66, 127), (66, 128), (66, 129), (66, 130), (66, 131), (66, 132), (66, 133), (66, 134), (66, 135), (66, 136), (66, 137), (66, 138), (66, 139), (66, 140), (66, 141), (66, 142), (66, 143), (66, 148), (66, 150), (67, 111), (67, 113), (67, 114), (67, 115), (67, 116), (67, 117), (67, 118), (67, 119), (67, 120), (67, 121), (67, 122), (67, 123), (67, 124), (67, 125), (67, 126), (67, 127), (67, 128), (67, 129), (67, 130), (67, 131),
(67, 132), (67, 133), (67, 134), (67, 135), (67, 136), (67, 137), (67, 138), (67, 139), (67, 140), (67, 144), (67, 145), (67, 146), (67, 147), (68, 110), (68, 112), (68, 113), (68, 114), (68, 115), (68, 116), (68, 117), (68, 118), (68, 119), (68, 120), (68, 121), (68, 122), (68, 123), (68, 124), (68, 125), (68, 126), (68, 127), (68, 128), (68, 129), (68, 130), (68, 131), (68, 132), (68, 133), (68, 134), (68, 135), (68, 136), (68, 137), (68, 138), (68, 141), (68, 142), (68, 143), (69, 110), (69, 112), (69, 113), (69, 114), (69, 115), (69, 116), (69, 117), (69, 118), (69, 119), (69, 120), (69, 121), (69, 122), (69, 123), (69, 124), (69, 125), (69, 126), (69, 127), (69, 128), (69, 129), (69, 130), (69, 131), (69, 132), (69, 133), (69, 134), (69, 135), (69, 136), (69, 139), (69, 140),
(70, 109), (70, 111), (70, 112), (70, 113), (70, 114), (70, 115), (70, 116), (70, 117), (70, 118), (70, 119), (70, 120), (70, 121), (70, 122), (70, 123), (70, 124), (70, 125), (70, 126), (70, 127), (70, 128), (70, 129), (70, 130), (70, 131), (70, 132), (70, 133), (70, 134), (70, 137), (70, 138), (71, 108), (71, 110), (71, 111), (71, 112), (71, 113), (71, 114), (71, 115), (71, 116), (71, 117), (71, 118), (71, 119), (71, 120), (71, 121), (71, 122), (71, 123), (71, 124), (71, 125), (71, 126), (71, 127), (71, 128), (71, 129), (71, 130), (71, 131), (71, 132), (71, 135), (71, 136), (72, 107), (72, 109), (72, 110), (72, 111), (72, 112), (72, 113), (72, 114), (72, 115), (72, 116), (72, 117), (72, 118), (72, 119), (72, 120), (72, 121), (72, 122), (72, 123), (72, 124), (72, 125), (72, 126),
(72, 127), (72, 128), (72, 129), (72, 130), (72, 133), (72, 134), (73, 107), (73, 109), (73, 110), (73, 111), (73, 112), (73, 113), (73, 114), (73, 115), (73, 116), (73, 117), (73, 118), (73, 119), (73, 120), (73, 121), (73, 122), (73, 123), (73, 124), (73, 125), (73, 126), (73, 127), (73, 128), (73, 129), (73, 132), (74, 106), (74, 108), (74, 109), (74, 110), (74, 111), (74, 112), (74, 113), (74, 114), (74, 115), (74, 116), (74, 117), (74, 118), (74, 119), (74, 120), (74, 121), (74, 122), (74, 123), (74, 124), (74, 125), (74, 126), (74, 127), (74, 130), (75, 106), (75, 108), (75, 109), (75, 110), (75, 111), (75, 112), (75, 113), (75, 114), (75, 115), (75, 116), (75, 117), (75, 118), (75, 119), (75, 120), (75, 121), (75, 122), (75, 123), (75, 124), (75, 125), (75, 126), (75, 129),
(76, 105), (76, 107), (76, 108), (76, 109), (76, 110), (76, 111), (76, 112), (76, 113), (76, 114), (76, 115), (76, 116), (76, 117), (76, 118), (76, 119), (76, 120), (76, 121), (76, 122), (76, 123), (76, 124), (76, 127), (77, 105), (77, 107), (77, 108), (77, 109), (77, 110), (77, 111), (77, 112), (77, 113), (77, 114), (77, 115), (77, 116), (77, 117), (77, 118), (77, 119), (77, 120), (77, 121), (77, 122), (77, 123), (77, 126), (78, 104), (78, 106), (78, 107), (78, 108), (78, 109), (78, 110), (78, 111), (78, 112), (78, 113), (78, 114), (78, 115), (78, 116), (78, 117), (78, 118), (78, 119), (78, 120), (78, 121), (78, 124), (79, 103), (79, 105), (79, 106), (79, 107), (79, 108), (79, 109), (79, 110), (79, 111), (79, 112), (79, 113), (79, 114), (79, 115), (79, 116), (79, 117), (79, 118),
(79, 119), (79, 120), (79, 123), (80, 102), (80, 104), (80, 105), (80, 106), (80, 107), (80, 108), (80, 109), (80, 110), (80, 111), (80, 112), (80, 113), (80, 114), (80, 115), (80, 116), (80, 117), (80, 118), (80, 119), (80, 122), (81, 101), (81, 103), (81, 104), (81, 105), (81, 106), (81, 107), (81, 108), (81, 109), (81, 110), (81, 111), (81, 112), (81, 113), (81, 114), (81, 115), (81, 116), (81, 117), (81, 118), (81, 120), (82, 100), (82, 102), (82, 103), (82, 104), (82, 105), (82, 106), (82, 107), (82, 108), (82, 109), (82, 110), (82, 111), (82, 112), (82, 113), (82, 114), (82, 115), (82, 116), (82, 117), (82, 119), (83, 99), (83, 101), (83, 102), (83, 103), (83, 104), (83, 105), (83, 106), (83, 107), (83, 108), (83, 109), (83, 110), (83, 111), (83, 112), (83, 113), (83, 114),
(83, 115), (83, 116), (83, 118), (84, 98), (84, 100), (84, 101), (84, 102), (84, 103), (84, 104), (84, 105), (84, 106), (84, 107), (84, 108), (84, 109), (84, 110), (84, 111), (84, 112), (84, 113), (84, 114), (84, 115), (84, 117), (85, 97), (85, 99), (85, 100), (85, 101), (85, 102), (85, 103), (85, 104), (85, 105), (85, 106), (85, 107), (85, 108), (85, 109), (85, 110), (85, 111), (85, 112), (85, 113), (85, 114), (85, 116), (86, 96), (86, 98), (86, 99), (86, 100), (86, 101), (86, 102), (86, 103), (86, 104), (86, 105), (86, 106), (86, 107), (86, 108), (86, 109), (86, 110), (86, 111), (86, 112), (86, 113), (86, 115), (87, 95), (87, 97), (87, 98), (87, 99), (87, 100), (87, 101), (87, 102), (87, 103), (87, 104), (87, 105), (87, 106), (87, 107), (87, 108), (87, 109), (87, 110),
(87, 111), (87, 112), (87, 114), (88, 94), (88, 96), (88, 97), (88, 98), (88, 99), (88, 100), (88, 101), (88, 102), (88, 103), (88, 104), (88, 105), (88, 106), (88, 107), (88, 108), (88, 109), (88, 110), (88, 111), (88, 113), (89, 93), (89, 95), (89, 96), (89, 97), (89, 98), (89, 99), (89, 100), (89, 101), (89, 102), (89, 103), (89, 104), (89, 105), (89, 106), (89, 107), (89, 108), (89, 109), (89, 110), (89, 112), (90, 92), (90, 94), (90, 95), (90, 96), (90, 97), (90, 98), (90, 99), (90, 100), (90, 101), (90, 102), (90, 103), (90, 104), (90, 105), (90, 106), (90, 107), (90, 108), (90, 109), (90, 111), (91, 92), (91, 94), (91, 95), (91, 96), (91, 97), (91, 98), (91, 99), (91, 100), (91, 101), (91, 102), (91, 103), (91, 104), (91, 105), (91, 106), (91, 107),
(91, 108), (91, 109), (91, 111), (92, 91), (92, 93), (92, 94), (92, 95), (92, 96), (92, 97), (92, 98), (92, 99), (92, 100), (92, 101), (92, 102), (92, 103), (92, 104), (92, 105), (92, 106), (92, 107), (92, 108), (92, 110), (93, 90), (93, 92), (93, 93), (93, 94), (93, 95), (93, 96), (93, 97), (93, 98), (93, 99), (93, 100), (93, 101), (93, 102), (93, 103), (93, 104), (93, 105), (93, 106), (93, 107), (93, 109), (94, 90), (94, 92), (94, 93), (94, 94), (94, 95), (94, 96), (94, 97), (94, 98), (94, 99), (94, 100), (94, 101), (94, 102), (94, 103), (94, 104), (94, 105), (94, 106), (94, 107), (94, 109), (95, 90), (95, 94), (95, 95), (95, 96), (95, 97), (95, 98), (95, 99), (95, 100), (95, 101), (95, 102), (95, 103), (95, 104), (95, 105), (95, 106), (95, 108),
(96, 90), (96, 92), (96, 93), (96, 97), (96, 98), (96, 99), (96, 100), (96, 101), (96, 102), (96, 103), (96, 104), (96, 105), (96, 106), (96, 108), (97, 95), (97, 96), (97, 100), (97, 101), (97, 102), (97, 103), (97, 104), (97, 105), (97, 107), (98, 97), (98, 103), (98, 104), (98, 105), (98, 107), (99, 100), (99, 101), (99, 102), (99, 107), (100, 103), (100, 104), (100, 105), (100, 107), (299, 103), (299, 104), (299, 105), (299, 107), (300, 100), (300, 101), (300, 107), (301, 97), (301, 98), (301, 102), (301, 103), (301, 104), (301, 105), (301, 107), (302, 94), (302, 95), (302, 96), (302, 99), (302, 100), (302, 101), (302, 102), (302, 103), (302, 104), (302, 105), (302, 107), (303, 90), (303, 92), (303, 93), (303, 97), (303, 98), (303, 99), (303, 100), (303, 101), (303, 102), (303, 103), (303, 104),
(303, 105), (303, 106), (303, 108), (304, 90), (304, 94), (304, 95), (304, 96), (304, 97), (304, 98), (304, 99), (304, 100), (304, 101), (304, 102), (304, 103), (304, 104), (304, 105), (304, 106), (304, 108), (305, 90), (305, 92), (305, 93), (305, 94), (305, 95), (305, 96), (305, 97), (305, 98), (305, 99), (305, 100), (305, 101), (305, 102), (305, 103), (305, 104), (305, 105), (305, 106), (305, 107), (305, 109), (306, 91), (306, 92), (306, 93), (306, 94), (306, 95), (306, 96), (306, 97), (306, 98), (306, 99), (306, 100), (306, 101), (306, 102), (306, 103), (306, 104), (306, 105), (306, 106), (306, 107), (306, 109), (307, 91), (307, 93), (307, 94), (307, 95), (307, 96), (307, 97), (307, 98), (307, 99), (307, 100), (307, 101), (307, 102), (307, 103), (307, 104), (307, 105), (307, 106), (307, 107), (307, 108), (307, 110),
(308, 92), (308, 94), (308, 95), (308, 96), (308, 97), (308, 98), (308, 99), (308, 100), (308, 101), (308, 102), (308, 103), (308, 104), (308, 105), (308, 106), (308, 107), (308, 108), (308, 109), (308, 111), (309, 92), (309, 94), (309, 95), (309, 96), (309, 97), (309, 98), (309, 99), (309, 100), (309, 101), (309, 102), (309, 103), (309, 104), (309, 105), (309, 106), (309, 107), (309, 108), (309, 109), (310, 93), (310, 95), (310, 96), (310, 97), (310, 98), (310, 99), (310, 100), (310, 101), (310, 102), (310, 103), (310, 104), (310, 105), (310, 106), (310, 107), (310, 108), (310, 109), (310, 110), (310, 112), (311, 94), (311, 96), (311, 97), (311, 98), (311, 99), (311, 100), (311, 101), (311, 102), (311, 103), (311, 104), (311, 105), (311, 106), (311, 107), (311, 108), (311, 109), (311, 110), (311, 111), (311, 113), (312, 95),
(312, 97), (312, 98), (312, 99), (312, 100), (312, 101), (312, 102), (312, 103), (312, 104), (312, 105), (312, 106), (312, 107), (312, 108), (312, 109), (312, 110), (312, 111), (312, 112), (312, 114), (313, 96), (313, 98), (313, 99), (313, 100), (313, 101), (313, 102), (313, 103), (313, 104), (313, 105), (313, 106), (313, 107), (313, 108), (313, 109), (313, 110), (313, 111), (313, 112), (313, 113), (313, 115), (314, 97), (314, 99), (314, 100), (314, 101), (314, 102), (314, 103), (314, 104), (314, 105), (314, 106), (314, 107), (314, 108), (314, 109), (314, 110), (314, 111), (314, 112), (314, 113), (314, 114), (314, 116), (315, 98), (315, 100), (315, 101), (315, 102), (315, 103), (315, 104), (315, 105), (315, 106), (315, 107), (315, 108), (315, 109), (315, 110), (315, 111), (315, 112), (315, 113), (315, 114), (315, 115), (315, 117), (316, 99),
(316, 101), (316, 102), (316, 103), (316, 104), (316, 105), (316, 106), (316, 107), (316, 108), (316, 109), (316, 110), (316, 111), (316, 112), (316, 113), (316, 114), (316, 115), (316, 116), (316, 118), (317, 100), (317, 102), (317, 103), (317, 104), (317, 105), (317, 106), (317, 107), (317, 108), (317, 109), (317, 110), (317, 111), (317, 112), (317, 113), (317, 114), (317, 115), (317, 116), (317, 117), (317, 119), (318, 101), (318, 103), (318, 104), (318, 105), (318, 106), (318, 107), (318, 108), (318, 109), (318, 110), (318, 111), (318, 112), (318, 113), (318, 114), (318, 115), (318, 116), (318, 117), (318, 118), (318, 120), (319, 102), (319, 104), (319, 105), (319, 106), (319, 107), (319, 108), (319, 109), (319, 110), (319, 111), (319, 112), (319, 113), (319, 114), (319, 115), (319, 116), (319, 117), (319, 118), (319, 119), (319, 122), (320, 103),
(320, 105), (320, 106), (320, 107), (320, 108), (320, 109), (320, 110), (320, 111), (320, 112), (320, 113), (320, 114), (320, 115), (320, 116), (320, 117), (320, 118), (320, 119), (320, 120), (320, 123), (321, 104), (321, 106), (321, 107), (321, 108), (321, 109), (321, 110), (321, 111), (321, 112), (321, 113), (321, 114), (321, 115), (321, 116), (321, 117), (321, 118), (321, 119), (321, 120), (321, 121), (321, 122), (321, 124), (322, 105), (322, 107), (322, 108), (322, 109), (322, 110), (322, 111), (322, 112), (322, 113), (322, 114), (322, 115), (322, 116), (322, 117), (322, 118), (322, 119), (322, 120), (322, 121), (322, 122), (322, 123), (322, 126), (323, 105), (323, 107), (323, 108), (323, 109), (323, 110), (323, 111), (323, 112), (323, 113), (323, 114), (323, 115), (323, 116), (323, 117), (323, 118), (323, 119), (323, 120), (323, 121), (323, 122),
(323, 123), (323, 124), (323, 127), (324, 106), (324, 108), (324, 109), (324, 110), (324, 111), (324, 112), (324, 113), (324, 114), (324, 115), (324, 116), (324, 117), (324, 118), (324, 119), (324, 120), (324, 121), (324, 122), (324, 123), (324, 124), (324, 125), (324, 126), (324, 129), (325, 106), (325, 108), (325, 109), (325, 110), (325, 111), (325, 112), (325, 113), (325, 114), (325, 115), (325, 116), (325, 117), (325, 118), (325, 119), (325, 120), (325, 121), (325, 122), (325, 123), (325, 124), (325, 125), (325, 126), (325, 127), (325, 130), (326, 107), (326, 109), (326, 110), (326, 111), (326, 112), (326, 113), (326, 114), (326, 115), (326, 116), (326, 117), (326, 118), (326, 119), (326, 120), (326, 121), (326, 122), (326, 123), (326, 124), (326, 125), (326, 126), (326, 127), (326, 128), (326, 129), (326, 132), (327, 109), (327, 110), (327, 111),
(327, 112), (327, 113), (327, 114), (327, 115), (327, 116), (327, 117), (327, 118), (327, 119), (327, 120), (327, 121), (327, 122), (327, 123), (327, 124), (327, 125), (327, 126), (327, 127), (327, 128), (327, 129), (327, 130), (327, 134), (328, 108), (328, 110), (328, 111), (328, 112), (328, 113), (328, 114), (328, 115), (328, 116), (328, 117), (328, 118), (328, 119), (328, 120), (328, 121), (328, 122), (328, 123), (328, 124), (328, 125), (328, 126), (328, 127), (328, 128), (328, 129), (328, 130), (328, 131), (328, 132), (328, 135), (328, 136), (329, 109), (329, 111), (329, 112), (329, 113), (329, 114), (329, 115), (329, 116), (329, 117), (329, 118), (329, 119), (329, 120), (329, 121), (329, 122), (329, 123), (329, 124), (329, 125), (329, 126), (329, 127), (329, 128), (329, 129), (329, 130), (329, 131), (329, 132), (329, 133), (329, 134), (329, 137),
(329, 138), (330, 110), (330, 112), (330, 113), (330, 114), (330, 115), (330, 116), (330, 117), (330, 118), (330, 119), (330, 120), (330, 121), (330, 122), (330, 123), (330, 124), (330, 125), (330, 126), (330, 127), (330, 128), (330, 129), (330, 130), (330, 131), (330, 132), (330, 133), (330, 134), (330, 135), (330, 136), (330, 139), (330, 140), (331, 110), (331, 112), (331, 113), (331, 114), (331, 115), (331, 116), (331, 117), (331, 118), (331, 119), (331, 120), (331, 121), (331, 122), (331, 123), (331, 124), (331, 125), (331, 126), (331, 127), (331, 128), (331, 129), (331, 130), (331, 131), (331, 132), (331, 133), (331, 134), (331, 135), (331, 136), (331, 137), (331, 138), (331, 141), (331, 142), (331, 143), (332, 111), (332, 113), (332, 114), (332, 115), (332, 116), (332, 117), (332, 118), (332, 119), (332, 120), (332, 121), (332, 122), (332, 123),
(332, 124), (332, 125), (332, 126), (332, 127), (332, 128), (332, 129), (332, 130), (332, 131), (332, 132), (332, 133), (332, 134), (332, 135), (332, 136), (332, 137), (332, 138), (332, 139), (332, 140), (332, 144), (332, 145), (332, 146), (332, 147), (332, 149), (333, 112), (333, 114), (333, 115), (333, 116), (333, 117), (333, 118), (333, 119), (333, 120), (333, 121), (333, 122), (333, 123), (333, 124), (333, 125), (333, 126), (333, 127), (333, 128), (333, 129), (333, 130), (333, 131), (333, 132), (333, 133), (333, 134), (333, 135), (333, 136), (333, 137), (333, 138), (333, 139), (333, 140), (333, 141), (333, 142), (333, 143), (333, 150), (334, 113), (334, 115), (334, 116), (334, 117), (334, 118), (334, 119), (334, 120), (334, 121), (334, 122), (334, 123), (334, 124), (334, 125), (334, 126), (334, 127), (334, 128), (334, 129), (334, 130), (334, 131),
(334, 132), (334, 133), (334, 134), (334, 135), (334, 136), (334, 137), (334, 138), (334, 139), (334, 140), (334, 141), (334, 142), (334, 143), (334, 144), (334, 145), (334, 146), (334, 147), (334, 148), (334, 151), (335, 114), (335, 116), (335, 117), (335, 118), (335, 119), (335, 120), (335, 121), (335, 122), (335, 123), (335, 124), (335, 125), (335, 126), (335, 127), (335, 128), (335, 129), (335, 130), (335, 131), (335, 132), (335, 133), (335, 134), (335, 135), (335, 136), (335, 137), (335, 138), (335, 139), (335, 140), (335, 141), (335, 142), (335, 143), (335, 144), (335, 145), (335, 146), (335, 147), (335, 148), (335, 149), (335, 150), (335, 152), (336, 115), (336, 117), (336, 118), (336, 119), (336, 120), (336, 121), (336, 122), (336, 123), (336, 124), (336, 125), (336, 126), (336, 127), (336, 128), (336, 129), (336, 130), (336, 131), (336, 132),
(336, 133), (336, 134), (336, 135), (336, 136), (336, 137), (336, 138), (336, 139), (336, 140), (336, 141), (336, 142), (336, 143), (336, 144), (336, 145), (336, 146), (336, 147), (336, 148), (336, 149), (336, 150), (336, 151), (336, 153), (337, 116), (337, 118), (337, 119), (337, 120), (337, 121), (337, 122), (337, 123), (337, 124), (337, 125), (337, 126), (337, 127), (337, 128), (337, 129), (337, 130), (337, 131), (337, 132), (337, 133), (337, 134), (337, 135), (337, 136), (337, 137), (337, 138), (337, 139), (337, 140), (337, 141), (337, 142), (337, 143), (337, 144), (337, 145), (337, 146), (337, 147), (337, 148), (337, 149), (337, 150), (337, 151), (337, 152), (337, 154), (338, 117), (338, 119), (338, 120), (338, 121), (338, 122), (338, 123), (338, 124), (338, 125), (338, 126), (338, 127), (338, 128), (338, 129), (338, 130), (338, 131), (338, 132),
(338, 133), (338, 134), (338, 135), (338, 136), (338, 137), (338, 138), (338, 139), (338, 140), (338, 141), (338, 142), (338, 143), (338, 144), (338, 145), (338, 146), (338, 147), (338, 148), (338, 149), (338, 150), (338, 151), (338, 152), (338, 153), (339, 118), (339, 121), (339, 122), (339, 123), (339, 124), (339, 125), (339, 126), (339, 127), (339, 128), (339, 129), (339, 130), (339, 131), (339, 132), (339, 133), (339, 134), (339, 135), (339, 136), (339, 137), (339, 138), (339, 139), (339, 140), (339, 141), (339, 142), (339, 143), (339, 144), (339, 145), (339, 146), (339, 147), (339, 148), (339, 149), (339, 150), (339, 151), (339, 152), (339, 153), (339, 154), (339, 157), (340, 119), (340, 122), (340, 123), (340, 124), (340, 125), (340, 126), (340, 127), (340, 128), (340, 129), (340, 130), (340, 131), (340, 132), (340, 133), (340, 134), (340, 135),
(340, 136), (340, 137), (340, 138), (340, 139), (340, 140), (340, 141), (340, 142), (340, 143), (340, 144), (340, 145), (340, 146), (340, 147), (340, 148), (340, 149), (340, 150), (340, 151), (340, 152), (340, 153), (340, 154), (340, 155), (340, 156), (340, 159), (341, 123), (341, 124), (341, 125), (341, 126), (341, 127), (341, 128), (341, 129), (341, 130), (341, 131), (341, 132), (341, 133), (341, 134), (341, 135), (341, 136), (341, 137), (341, 138), (341, 139), (341, 140), (341, 141), (341, 142), (341, 143), (341, 144), (341, 145), (341, 146), (341, 147), (341, 148), (341, 149), (341, 150), (341, 151), (341, 152), (341, 153), (341, 154), (341, 155), (341, 156), (341, 157), (341, 158), (341, 161), (341, 162), (342, 122), (342, 124), (342, 125), (342, 126), (342, 127), (342, 128), (342, 129), (342, 130), (342, 131), (342, 132), (342, 133), (342, 134),
(342, 135), (342, 136), (342, 137), (342, 138), (342, 139), (342, 140), (342, 141), (342, 142), (342, 143), (342, 144), (342, 145), (342, 146), (342, 147), (342, 148), (342, 149), (342, 150), (342, 151), (342, 152), (342, 153), (342, 154), (342, 155), (342, 156), (342, 157), (342, 158), (342, 159), (342, 160), (342, 164), (343, 123), (343, 126), (343, 127), (343, 128), (343, 129), (343, 130), (343, 131), (343, 132), (343, 133), (343, 134), (343, 135), (343, 136), (343, 137), (343, 138), (343, 139), (343, 140), (343, 141), (343, 142), (343, 143), (343, 144), (343, 145), (343, 146), (343, 147), (343, 148), (343, 149), (343, 150), (343, 151), (343, 152), (343, 153), (343, 154), (343, 155), (343, 156), (343, 157), (343, 158), (343, 159), (343, 160), (343, 161), (343, 162), (343, 166), (344, 124), (344, 127), (344, 128), (344, 129), (344, 130), (344, 131),
(344, 132), (344, 133), (344, 134), (344, 135), (344, 136), (344, 137), (344, 138), (344, 139), (344, 140), (344, 141), (344, 142), (344, 143), (344, 144), (344, 145), (344, 146), (344, 147), (344, 148), (344, 149), (344, 150), (344, 151), (344, 152), (344, 153), (344, 154), (344, 155), (344, 156), (344, 157), (344, 158), (344, 159), (344, 160), (344, 161), (344, 162), (344, 163), (344, 164), (344, 168), (345, 126), (345, 129), (345, 130), (345, 131), (345, 132), (345, 133), (345, 134), (345, 135), (345, 136), (345, 137), (345, 138), (345, 139), (345, 140), (345, 141), (345, 142), (345, 143), (345, 144), (345, 145), (345, 146), (345, 147), (345, 148), (345, 149), (345, 150), (345, 151), (345, 152), (345, 153), (345, 154), (345, 155), (345, 156), (345, 157), (345, 158), (345, 159), (345, 160), (345, 161), (345, 162), (345, 163), (345, 164), (345, 165),
(345, 166), (345, 170), (346, 127), (346, 130), (346, 131), (346, 132), (346, 133), (346, 134), (346, 135), (346, 136), (346, 137), (346, 138), (346, 139), (346, 140), (346, 141), (346, 142), (346, 143), (346, 144), (346, 145), (346, 146), (346, 147), (346, 148), (346, 149), (346, 150), (346, 151), (346, 152), (346, 153), (346, 154), (346, 155), (346, 156), (346, 157), (346, 158), (346, 159), (346, 160), (346, 161), (346, 162), (346, 163), (346, 164), (346, 165), (346, 166), (346, 167), (346, 168), (346, 172), (347, 129), (347, 132), (347, 133), (347, 134), (347, 135), (347, 136), (347, 137), (347, 138), (347, 139), (347, 140), (347, 141), (347, 142), (347, 143), (347, 144), (347, 145), (347, 146), (347, 147), (347, 148), (347, 149), (347, 150), (347, 151), (347, 152), (347, 153), (347, 154), (347, 155), (347, 156), (347, 157), (347, 158), (347, 159),
(347, 160), (347, 161), (347, 162), (347, 163), (347, 164), (347, 165), (347, 166), (347, 167), (347, 168), (347, 169), (347, 170), (347, 174), (348, 130), (348, 134), (348, 135), (348, 136), (348, 137), (348, 138), (348, 139), (348, 140), (348, 141), (348, 142), (348, 143), (348, 144), (348, 145), (348, 146), (348, 147), (348, 148), (348, 149), (348, 150), (348, 151), (348, 152), (348, 153), (348, 154), (348, 155), (348, 156), (348, 157), (348, 158), (348, 159), (348, 160), (348, 161), (348, 162), (348, 163), (348, 164), (348, 165), (348, 166), (348, 167), (348, 168), (348, 169), (348, 170), (348, 171), (348, 172), (348, 176), (349, 132), (349, 135), (349, 136), (349, 137), (349, 138), (349, 139), (349, 140), (349, 141), (349, 142), (349, 143), (349, 144), (349, 145), (349, 146), (349, 147), (349, 148), (349, 149), (349, 150), (349, 151), (349, 152),
(349, 153), (349, 154), (349, 155), (349, 156), (349, 157), (349, 158), (349, 159), (349, 160), (349, 161), (349, 162), (349, 163), (349, 164), (349, 165), (349, 166), (349, 167), (349, 168), (349, 169), (349, 170), (349, 171), (349, 172), (349, 173), (349, 174), (349, 175), (349, 178), (350, 134), (350, 137), (350, 138), (350, 139), (350, 140), (350, 141), (350, 142), (350, 143), (350, 144), (350, 145), (350, 146), (350, 147), (350, 148), (350, 149), (350, 150), (350, 151), (350, 152), (350, 153), (350, 154), (350, 155), (350, 156), (350, 157), (350, 158), (350, 159), (350, 160), (350, 161), (350, 162), (350, 163), (350, 164), (350, 165), (350, 166), (350, 167), (350, 168), (350, 169), (350, 170), (350, 171), (350, 172), (350, 173), (350, 174), (350, 175), (350, 176), (350, 179), (351, 135), (351, 139), (351, 140), (351, 141), (351, 142), (351, 143),
(351, 144), (351, 145), (351, 146), (351, 147), (351, 148), (351, 149), (351, 150), (351, 151), (351, 152), (351, 153), (351, 154), (351, 155), (351, 156), (351, 157), (351, 158), (351, 159), (351, 160), (351, 161), (351, 162), (351, 163), (351, 164), (351, 165), (351, 166), (351, 167), (351, 168), (351, 169), (351, 170), (351, 171), (351, 172), (351, 173), (351, 174), (351, 175), (351, 176), (351, 177), (351, 178), (351, 181), (352, 137), (352, 142), (352, 143), (352, 144), (352, 145), (352, 146), (352, 147), (352, 148), (352, 149), (352, 150), (352, 151), (352, 152), (352, 153), (352, 154), (352, 155), (352, 156), (352, 157), (352, 158), (352, 159), (352, 160), (352, 161), (352, 162), (352, 163), (352, 164), (352, 165), (352, 166), (352, 167), (352, 168), (352, 169), (352, 170), (352, 171), (352, 172), (352, 173), (352, 174), (352, 175), (352, 176),
(352, 177), (352, 178), (352, 179), (352, 182), (353, 139), (353, 141), (353, 147), (353, 148), (353, 149), (353, 150), (353, 151), (353, 152), (353, 153), (353, 154), (353, 155), (353, 156), (353, 157), (353, 158), (353, 159), (353, 160), (353, 161), (353, 162), (353, 163), (353, 164), (353, 165), (353, 166), (353, 167), (353, 168), (353, 169), (353, 170), (353, 171), (353, 172), (353, 173), (353, 174), (353, 175), (353, 176), (353, 177), (353, 178), (353, 179), (353, 180), (353, 181), (353, 184), (354, 142), (354, 143), (354, 144), (354, 145), (354, 146), (354, 154), (354, 155), (354, 156), (354, 157), (354, 158), (354, 159), (354, 160), (354, 161), (354, 162), (354, 163), (354, 164), (354, 165), (354, 166), (354, 167), (354, 168), (354, 169), (354, 170), (354, 171), (354, 172), (354, 173), (354, 174), (354, 175), (354, 176), (354, 177), (354, 178),
(354, 179), (354, 180), (354, 181), (354, 182), (354, 185), (354, 186), (355, 147), (355, 148), (355, 149), (355, 150), (355, 151), (355, 152), (355, 153), (355, 158), (355, 159), (355, 160), (355, 161), (355, 162), (355, 163), (355, 164), (355, 165), (355, 166), (355, 167), (355, 168), (355, 169), (355, 170), (355, 171), (355, 172), (355, 173), (355, 174), (355, 175), (355, 176), (355, 177), (355, 178), (355, 179), (355, 180), (355, 181), (355, 182), (355, 183), (355, 184), (355, 187), (356, 154), (356, 155), (356, 156), (356, 157), (356, 160), (356, 161), (356, 162), (356, 163), (356, 164), (356, 165), (356, 166), (356, 167), (356, 168), (356, 169), (356, 170), (356, 171), (356, 172), (356, 173), (356, 174), (356, 175), (356, 176), (356, 177), (356, 178), (356, 179), (356, 180), (356, 181), (356, 186), (357, 158), (357, 159), (357, 162), (357, 163),
(357, 164), (357, 165), (357, 166), (357, 167), (357, 168), (357, 169), (357, 170), (357, 171), (357, 172), (357, 173), (357, 174), (357, 175), (357, 176), (357, 177), (357, 178), (357, 179), (357, 182), (357, 183), (357, 184), (358, 160), (358, 165), (358, 166), (358, 167), (358, 168), (358, 169), (358, 170), (358, 171), (358, 172), (358, 173), (358, 174), (358, 175), (358, 176), (358, 177), (358, 178), (358, 181), (359, 162), (359, 167), (359, 168), (359, 169), (359, 170), (359, 171), (359, 172), (359, 173), (359, 174), (359, 175), (359, 176), (359, 177), (359, 178), (359, 179), (360, 165), (360, 166), (360, 171), (360, 172), (360, 173), (360, 174), (360, 175), (360, 176), (360, 177), (360, 179), (361, 168), (361, 169), (361, 170), (361, 178), (362, 171), (362, 172), (362, 173), (362, 174), (362, 175), (362, 176), (362, 178), )
coordinates_7F0027 = ((53, 219),
(54, 218), (54, 220), (55, 218), (55, 221), (56, 218), (56, 220), (56, 222), (57, 217), (57, 219), (57, 220), (57, 221), (57, 223), (58, 217), (58, 219), (58, 220), (58, 221), (58, 222), (58, 224), (59, 216), (59, 218), (59, 219), (59, 220), (59, 221), (59, 222), (59, 223), (60, 216), (60, 218), (60, 219), (60, 220), (60, 221), (60, 222), (60, 223), (60, 224), (61, 216), (61, 218), (61, 219), (61, 220), (61, 221), (61, 222), (61, 223), (61, 224), (61, 225), (61, 228), (62, 215), (62, 217), (62, 218), (62, 219), (62, 220), (62, 221), (62, 222), (62, 223), (62, 224), (62, 225), (62, 226), (62, 229), (63, 215), (63, 217), (63, 218), (63, 219), (63, 220), (63, 221), (63, 222), (63, 223), (63, 224), (63, 225), (63, 226), (63, 227), (63, 230), (64, 215), (64, 217), (64, 218), (64, 219),
(64, 220), (64, 221), (64, 222), (64, 223), (64, 224), (64, 225), (64, 226), (64, 227), (64, 228), (64, 231), (65, 215), (65, 217), (65, 218), (65, 219), (65, 220), (65, 221), (65, 222), (65, 223), (65, 224), (65, 225), (65, 226), (65, 227), (65, 228), (65, 229), (65, 232), (66, 215), (66, 217), (66, 218), (66, 219), (66, 220), (66, 221), (66, 222), (66, 223), (66, 224), (66, 225), (66, 226), (66, 227), (66, 228), (66, 229), (66, 230), (66, 231), (66, 233), (67, 215), (67, 217), (67, 218), (67, 219), (67, 220), (67, 221), (67, 222), (67, 223), (67, 224), (67, 225), (67, 226), (67, 227), (67, 228), (67, 229), (67, 230), (67, 231), (67, 232), (67, 234), (68, 215), (68, 217), (68, 218), (68, 219), (68, 220), (68, 221), (68, 222), (68, 223), (68, 224), (68, 225), (68, 226), (68, 227),
(68, 228), (68, 229), (68, 230), (68, 231), (68, 232), (68, 233), (68, 235), (69, 217), (69, 218), (69, 219), (69, 220), (69, 221), (69, 222), (69, 223), (69, 224), (69, 225), (69, 226), (69, 227), (69, 228), (69, 229), (69, 230), (69, 231), (69, 232), (69, 233), (69, 234), (69, 236), (70, 216), (70, 218), (70, 219), (70, 220), (70, 221), (70, 222), (70, 223), (70, 224), (70, 225), (70, 226), (70, 227), (70, 228), (70, 229), (70, 230), (70, 231), (70, 232), (70, 233), (70, 234), (70, 235), (70, 237), (71, 217), (71, 219), (71, 220), (71, 221), (71, 222), (71, 223), (71, 224), (71, 225), (71, 226), (71, 227), (71, 228), (71, 229), (71, 230), (71, 231), (71, 232), (71, 233), (71, 234), (71, 235), (71, 237), (72, 218), (72, 221), (72, 222), (72, 223), (72, 224), (72, 225), (72, 226),
(72, 227), (72, 228), (72, 229), (72, 230), (72, 231), (72, 232), (72, 233), (72, 234), (72, 235), (72, 237), (73, 219), (73, 222), (73, 223), (73, 224), (73, 225), (73, 226), (73, 227), (73, 228), (73, 229), (73, 230), (73, 231), (73, 232), (73, 233), (73, 234), (73, 235), (73, 236), (73, 237), (73, 238), (74, 221), (74, 224), (74, 225), (74, 226), (74, 227), (74, 228), (74, 229), (74, 230), (74, 231), (74, 232), (74, 233), (74, 234), (74, 235), (74, 236), (74, 238), (75, 222), (75, 225), (75, 226), (75, 227), (75, 228), (75, 229), (75, 230), (75, 231), (75, 232), (75, 233), (75, 234), (75, 235), (75, 236), (75, 237), (76, 224), (76, 226), (76, 227), (76, 228), (76, 229), (76, 230), (76, 231), (76, 232), (76, 233), (76, 234), (76, 235), (76, 236), (76, 239), (77, 224), (77, 226),
(77, 227), (77, 228), (77, 229), (77, 230), (77, 231), (77, 232), (77, 233), (77, 234), (77, 235), (77, 237), (78, 225), (78, 227), (78, 228), (78, 229), (78, 230), (78, 231), (78, 232), (78, 233), (78, 234), (78, 236), (79, 225), (79, 227), (79, 228), (79, 229), (79, 230), (79, 231), (79, 232), (79, 233), (79, 235), (80, 226), (80, 228), (80, 229), (80, 230), (80, 231), (80, 232), (80, 233), (80, 235), (81, 226), (81, 228), (81, 229), (81, 230), (81, 231), (81, 232), (81, 234), (82, 226), (82, 228), (82, 229), (82, 230), (82, 231), (82, 233), (83, 227), (83, 232), (84, 227), (84, 229), (84, 231), (315, 227), (315, 229), (315, 231), (316, 227), (316, 232), (317, 226), (317, 228), (317, 229), (317, 230), (317, 231), (317, 233), (318, 226), (318, 228), (318, 229), (318, 230), (318, 231), (318, 232),
(318, 234), (319, 226), (319, 228), (319, 229), (319, 230), (319, 231), (319, 232), (319, 233), (319, 235), (320, 225), (320, 227), (320, 228), (320, 229), (320, 230), (320, 231), (320, 232), (320, 233), (320, 235), (321, 225), (321, 227), (321, 228), (321, 229), (321, 230), (321, 231), (321, 232), (321, 233), (321, 234), (321, 236), (322, 224), (322, 226), (322, 227), (322, 228), (322, 229), (322, 230), (322, 231), (322, 232), (322, 233), (322, 234), (322, 235), (322, 237), (323, 223), (323, 225), (323, 226), (323, 227), (323, 228), (323, 229), (323, 230), (323, 231), (323, 232), (323, 233), (323, 234), (323, 235), (323, 236), (323, 239), (324, 222), (324, 224), (324, 225), (324, 226), (324, 227), (324, 228), (324, 229), (324, 230), (324, 231), (324, 232), (324, 233), (324, 234), (324, 235), (324, 236), (324, 238), (325, 221), (325, 224), (325, 225),
(325, 226), (325, 227), (325, 228), (325, 229), (325, 230), (325, 231), (325, 232), (325, 233), (325, 234), (325, 235), (325, 236), (325, 238), (326, 219), (326, 222), (326, 223), (326, 224), (326, 225), (326, 226), (326, 227), (326, 228), (326, 229), (326, 230), (326, 231), (326, 232), (326, 233), (326, 234), (326, 235), (326, 237), (327, 218), (327, 221), (327, 222), (327, 223), (327, 224), (327, 225), (327, 226), (327, 227), (327, 228), (327, 229), (327, 230), (327, 231), (327, 232), (327, 233), (327, 234), (327, 235), (327, 237), (328, 219), (328, 220), (328, 221), (328, 222), (328, 223), (328, 224), (328, 225), (328, 226), (328, 227), (328, 228), (328, 229), (328, 230), (328, 231), (328, 232), (328, 233), (328, 234), (328, 235), (328, 237), (329, 216), (329, 218), (329, 219), (329, 220), (329, 221), (329, 222), (329, 223), (329, 224), (329, 225),
(329, 226), (329, 227), (329, 228), (329, 229), (329, 230), (329, 231), (329, 232), (329, 233), (329, 234), (329, 235), (329, 237), (330, 215), (330, 217), (330, 218), (330, 219), (330, 220), (330, 221), (330, 222), (330, 223), (330, 224), (330, 225), (330, 226), (330, 227), (330, 228), (330, 229), (330, 230), (330, 231), (330, 232), (330, 233), (330, 234), (330, 236), (331, 215), (331, 217), (331, 218), (331, 219), (331, 220), (331, 221), (331, 222), (331, 223), (331, 224), (331, 225), (331, 226), (331, 227), (331, 228), (331, 229), (331, 230), (331, 231), (331, 232), (331, 233), (331, 235), (332, 215), (332, 217), (332, 218), (332, 219), (332, 220), (332, 221), (332, 222), (332, 223), (332, 224), (332, 225), (332, 226), (332, 227), (332, 228), (332, 229), (332, 230), (332, 231), (332, 232), (332, 234), (333, 215), (333, 217), (333, 218), (333, 219),
(333, 220), (333, 221), (333, 222), (333, 223), (333, 224), (333, 225), (333, 226), (333, 227), (333, 228), (333, 229), (333, 230), (333, 233), (334, 215), (334, 217), (334, 218), (334, 219), (334, 220), (334, 221), (334, 222), (334, 223), (334, 224), (334, 225), (334, 226), (334, 227), (334, 228), (334, 229), (334, 232), (335, 215), (335, 217), (335, 218), (335, 219), (335, 220), (335, 221), (335, 222), (335, 223), (335, 224), (335, 225), (335, 226), (335, 227), (335, 228), (335, 231), (336, 215), (336, 217), (336, 218), (336, 219), (336, 220), (336, 221), (336, 222), (336, 223), (336, 224), (336, 225), (336, 226), (336, 227), (336, 230), (337, 215), (337, 217), (337, 218), (337, 219), (337, 220), (337, 221), (337, 222), (337, 223), (337, 224), (337, 225), (337, 226), (337, 229), (338, 216), (338, 218), (338, 219), (338, 220), (338, 221), (338, 222),
(338, 223), (338, 224), (338, 225), (339, 216), (339, 218), (339, 219), (339, 220), (339, 221), (339, 222), (339, 223), (339, 224), (339, 226), (340, 216), (340, 217), (340, 218), (340, 219), (340, 220), (340, 221), (340, 222), (340, 223), (340, 225), (341, 217), (341, 219), (341, 220), (341, 221), (341, 222), (341, 224), (342, 217), (342, 219), (342, 220), (342, 221), (342, 223), (343, 218), (343, 220), (343, 222), (344, 218), (344, 221), (345, 218), (345, 220), (346, 219), )
coordinates_FF004E = ((44, 223),
(44, 224), (44, 225), (44, 226), (45, 221), (45, 227), (45, 228), (45, 230), (46, 220), (46, 223), (46, 224), (46, 225), (46, 226), (46, 231), (46, 233), (47, 219), (47, 221), (47, 222), (47, 223), (47, 224), (47, 225), (47, 226), (47, 227), (47, 228), (47, 229), (47, 230), (47, 234), (47, 235), (48, 219), (48, 221), (48, 222), (48, 223), (48, 224), (48, 225), (48, 226), (48, 227), (48, 228), (48, 229), (48, 230), (48, 231), (48, 232), (48, 233), (48, 237), (49, 219), (49, 221), (49, 222), (49, 223), (49, 224), (49, 225), (49, 226), (49, 227), (49, 228), (49, 229), (49, 230), (49, 231), (49, 232), (49, 233), (49, 234), (49, 235), (49, 240), (50, 219), (50, 221), (50, 222), (50, 223), (50, 224), (50, 225), (50, 226), (50, 227), (50, 228), (50, 229), (50, 230), (50, 231), (50, 232),
(50, 233), (50, 234), (50, 235), (50, 236), (50, 237), (50, 238), (50, 240), (51, 220), (51, 222), (51, 223), (51, 224), (51, 225), (51, 226), (51, 227), (51, 228), (51, 229), (51, 230), (51, 231), (51, 232), (51, 233), (51, 234), (51, 235), (51, 236), (51, 237), (51, 238), (51, 240), (52, 221), (52, 223), (52, 224), (52, 225), (52, 226), (52, 227), (52, 228), (52, 229), (52, 230), (52, 231), (52, 232), (52, 233), (52, 234), (52, 235), (52, 236), (52, 237), (52, 238), (52, 240), (53, 222), (53, 224), (53, 225), (53, 226), (53, 227), (53, 228), (53, 229), (53, 230), (53, 231), (53, 232), (53, 233), (53, 234), (53, 235), (53, 236), (53, 237), (53, 238), (53, 240), (54, 223), (54, 225), (54, 226), (54, 227), (54, 228), (54, 229), (54, 230), (54, 231), (54, 232), (54, 233), (54, 234),
(54, 235), (54, 236), (54, 237), (54, 238), (54, 239), (54, 240), (55, 224), (55, 226), (55, 227), (55, 228), (55, 229), (55, 230), (55, 231), (55, 232), (55, 233), (55, 234), (55, 235), (55, 236), (55, 237), (55, 239), (56, 225), (56, 227), (56, 228), (56, 229), (56, 230), (56, 231), (56, 232), (56, 233), (56, 234), (56, 235), (56, 236), (56, 237), (56, 239), (57, 226), (57, 228), (57, 229), (57, 230), (57, 231), (57, 232), (57, 233), (57, 234), (57, 235), (57, 236), (57, 237), (57, 239), (58, 227), (58, 229), (58, 230), (58, 231), (58, 232), (58, 233), (58, 234), (58, 235), (58, 236), (58, 237), (58, 239), (59, 228), (59, 230), (59, 231), (59, 232), (59, 233), (59, 234), (59, 235), (59, 236), (59, 237), (59, 239), (60, 229), (60, 231), (60, 232), (60, 233), (60, 234), (60, 235),
(60, 236), (60, 237), (60, 239), (61, 230), (61, 232), (61, 233), (61, 234), (61, 235), (61, 236), (61, 237), (61, 239), (62, 231), (62, 233), (62, 234), (62, 235), (62, 236), (62, 237), (62, 239), (63, 232), (63, 235), (63, 236), (63, 237), (63, 239), (64, 233), (64, 236), (64, 237), (64, 239), (65, 234), (65, 237), (65, 239), (66, 235), (66, 239), (67, 236), (67, 239), (68, 239), (331, 237), (331, 239), (332, 236), (332, 239), (333, 235), (333, 239), (334, 234), (334, 237), (334, 239), (335, 233), (335, 236), (335, 237), (335, 239), (336, 232), (336, 234), (336, 235), (336, 236), (336, 237), (336, 239), (337, 231), (337, 233), (337, 234), (337, 235), (337, 236), (337, 237), (337, 239), (338, 230), (338, 232), (338, 233), (338, 234), (338, 235), (338, 236), (338, 237), (338, 239), (339, 229), (339, 231), (339, 232),
(339, 233), (339, 234), (339, 235), (339, 236), (339, 237), (339, 239), (340, 228), (340, 230), (340, 231), (340, 232), (340, 233), (340, 234), (340, 235), (340, 236), (340, 237), (340, 239), (341, 227), (341, 229), (341, 230), (341, 231), (341, 232), (341, 233), (341, 234), (341, 235), (341, 236), (341, 237), (341, 239), (342, 226), (342, 228), (342, 229), (342, 230), (342, 231), (342, 232), (342, 233), (342, 234), (342, 235), (342, 236), (342, 237), (342, 239), (343, 225), (343, 227), (343, 228), (343, 229), (343, 230), (343, 231), (343, 232), (343, 233), (343, 234), (343, 235), (343, 236), (343, 237), (343, 239), (344, 224), (344, 226), (344, 227), (344, 228), (344, 229), (344, 230), (344, 231), (344, 232), (344, 233), (344, 234), (344, 235), (344, 236), (344, 237), (344, 239), (345, 223), (345, 225), (345, 226), (345, 227), (345, 228), (345, 229),
(345, 230), (345, 231), (345, 232), (345, 233), (345, 234), (345, 235), (345, 236), (345, 237), (345, 238), (345, 239), (345, 240), (346, 222), (346, 224), (346, 225), (346, 226), (346, 227), (346, 228), (346, 229), (346, 230), (346, 231), (346, 232), (346, 233), (346, 234), (346, 235), (346, 236), (346, 237), (346, 238), (346, 240), (347, 221), (347, 223), (347, 224), (347, 225), (347, 226), (347, 227), (347, 228), (347, 229), (347, 230), (347, 231), (347, 232), (347, 233), (347, 234), (347, 235), (347, 236), (347, 237), (347, 238), (347, 240), (348, 222), (348, 223), (348, 224), (348, 225), (348, 226), (348, 227), (348, 228), (348, 229), (348, 230), (348, 231), (348, 232), (348, 233), (348, 234), (348, 235), (348, 236), (348, 237), (348, 238), (348, 240), (349, 219), (349, 221), (349, 222), (349, 223), (349, 224), (349, 225), (349, 226), (349, 227),
(349, 228), (349, 229), (349, 230), (349, 231), (349, 232), (349, 233), (349, 234), (349, 235), (349, 236), (349, 237), (349, 240), (350, 219), (350, 221), (350, 222), (350, 223), (350, 224), (350, 225), (350, 226), (350, 227), (350, 228), (350, 229), (350, 230), (350, 231), (350, 232), (350, 233), (350, 234), (350, 235), (350, 240), (351, 219), (351, 221), (351, 222), (351, 223), (351, 224), (351, 225), (351, 226), (351, 227), (351, 228), (351, 229), (351, 230), (351, 231), (351, 232), (351, 233), (351, 237), (352, 221), (352, 222), (352, 223), (352, 224), (352, 225), (352, 226), (352, 227), (352, 228), (352, 229), (352, 230), (352, 234), (352, 235), (353, 220), (353, 224), (353, 225), (353, 231), (353, 232), (353, 233), (354, 221), (354, 223), (354, 226), (354, 227), (354, 228), (354, 229), (354, 230), (355, 224), (355, 225), )
coordinates_FF3000 = ((50, 242),
(50, 244), (51, 242), (51, 245), (51, 247), (52, 242), (52, 244), (52, 249), (53, 242), (53, 244), (53, 245), (53, 246), (53, 247), (53, 251), (54, 242), (54, 244), (54, 245), (54, 246), (54, 247), (54, 248), (54, 249), (54, 253), (55, 242), (55, 244), (55, 245), (55, 246), (55, 247), (55, 248), (55, 249), (55, 250), (55, 251), (55, 255), (56, 242), (56, 244), (56, 245), (56, 246), (56, 247), (56, 248), (56, 249), (56, 250), (56, 251), (56, 252), (56, 253), (56, 257), (57, 242), (57, 244), (57, 245), (57, 246), (57, 247), (57, 248), (57, 249), (57, 250), (57, 251), (57, 252), (57, 253), (57, 254), (57, 255), (57, 258), (57, 259), (58, 241), (58, 242), (58, 243), (58, 244), (58, 245), (58, 246), (58, 247), (58, 248), (58, 249), (58, 250), (58, 251), (58, 252), (58, 253), (58, 254),
(58, 255), (58, 256), (58, 257), (58, 260), (59, 241), (59, 243), (59, 244), (59, 245), (59, 246), (59, 247), (59, 248), (59, 249), (59, 250), (59, 251), (59, 252), (59, 253), (59, 254), (59, 255), (59, 256), (59, 257), (59, 258), (59, 259), (59, 262), (60, 241), (60, 243), (60, 244), (60, 245), (60, 246), (60, 247), (60, 248), (60, 249), (60, 250), (60, 251), (60, 252), (60, 253), (60, 254), (60, 255), (60, 256), (60, 257), (60, 258), (60, 259), (60, 260), (60, 263), (61, 241), (61, 243), (61, 244), (61, 245), (61, 246), (61, 247), (61, 248), (61, 249), (61, 250), (61, 251), (61, 252), (61, 253), (61, 254), (61, 255), (61, 256), (61, 257), (61, 258), (61, 259), (61, 260), (61, 261), (61, 262), (61, 264), (62, 241), (62, 243), (62, 244), (62, 245), (62, 246), (62, 247), (62, 248),
(62, 249), (62, 250), (62, 251), (62, 252), (62, 253), (62, 254), (62, 255), (62, 256), (62, 257), (62, 258), (62, 259), (62, 260), (62, 261), (62, 262), (62, 263), (62, 265), (63, 241), (63, 243), (63, 244), (63, 245), (63, 246), (63, 247), (63, 248), (63, 249), (63, 250), (63, 251), (63, 252), (63, 253), (63, 254), (63, 255), (63, 256), (63, 257), (63, 258), (63, 259), (63, 260), (63, 261), (63, 262), (63, 263), (63, 264), (63, 266), (64, 241), (64, 243), (64, 244), (64, 245), (64, 246), (64, 247), (64, 248), (64, 249), (64, 250), (64, 251), (64, 252), (64, 253), (64, 254), (64, 255), (64, 256), (64, 257), (64, 258), (64, 259), (64, 260), (64, 261), (64, 262), (64, 263), (64, 264), (64, 266), (65, 241), (65, 243), (65, 244), (65, 245), (65, 246), (65, 247), (65, 248), (65, 249),
(65, 250), (65, 251), (65, 252), (65, 253), (65, 254), (65, 255), (65, 256), (65, 257), (65, 258), (65, 259), (65, 260), (65, 261), (65, 262), (65, 263), (66, 241), (66, 243), (66, 244), (66, 245), (66, 246), (66, 247), (66, 248), (66, 249), (66, 250), (66, 251), (66, 252), (66, 253), (66, 254), (66, 255), (66, 256), (66, 257), (66, 258), (66, 259), (66, 265), (67, 241), (67, 243), (67, 244), (67, 245), (67, 246), (67, 247), (67, 248), (67, 249), (67, 250), (67, 251), (67, 252), (67, 253), (67, 254), (67, 255), (67, 260), (67, 261), (67, 263), (68, 241), (68, 243), (68, 244), (68, 245), (68, 246), (68, 247), (68, 248), (68, 249), (68, 250), (68, 251), (68, 252), (68, 253), (68, 254), (68, 257), (68, 258), (68, 259), (69, 241), (69, 243), (69, 244), (69, 245), (69, 246), (69, 247),
(69, 248), (69, 249), (69, 250), (69, 251), (69, 252), (69, 255), (70, 241), (70, 244), (70, 245), (70, 246), (70, 247), (70, 248), (70, 249), (70, 250), (70, 251), (71, 242), (71, 245), (71, 246), (71, 247), (71, 248), (71, 249), (71, 250), (71, 251), (71, 252), (72, 243), (72, 247), (72, 248), (72, 249), (72, 250), (72, 252), (73, 245), (73, 249), (73, 251), (74, 247), (74, 251), (75, 249), (75, 251), (324, 249), (324, 251), (325, 247), (325, 251), (326, 245), (326, 249), (326, 251), (327, 243), (327, 247), (327, 248), (327, 249), (327, 250), (327, 252), (328, 242), (328, 245), (328, 246), (328, 247), (328, 248), (328, 249), (328, 250), (328, 251), (328, 253), (329, 241), (329, 244), (329, 245), (329, 246), (329, 247), (329, 248), (329, 249), (329, 250), (329, 251), (329, 252), (329, 254), (330, 241), (330, 243),
(330, 244), (330, 245), (330, 246), (330, 247), (330, 248), (330, 249), (330, 250), (330, 251), (330, 252), (330, 255), (331, 241), (331, 243), (331, 244), (331, 245), (331, 246), (331, 247), (331, 248), (331, 249), (331, 250), (331, 251), (331, 252), (331, 253), (331, 254), (331, 257), (331, 258), (331, 259), (332, 241), (332, 243), (332, 244), (332, 245), (332, 246), (332, 247), (332, 248), (332, 249), (332, 250), (332, 251), (332, 252), (332, 253), (332, 254), (332, 255), (332, 256), (332, 260), (332, 261), (332, 263), (333, 241), (333, 243), (333, 244), (333, 245), (333, 246), (333, 247), (333, 248), (333, 249), (333, 250), (333, 251), (333, 252), (333, 253), (333, 254), (333, 255), (333, 256), (333, 257), (333, 258), (333, 259), (333, 265), (334, 241), (334, 243), (334, 244), (334, 245), (334, 246), (334, 247), (334, 248), (334, 249), (334, 250),
(334, 251), (334, 252), (334, 253), (334, 254), (334, 255), (334, 256), (334, 257), (334, 258), (334, 259), (334, 260), (334, 261), (334, 262), (334, 263), (334, 266), (335, 241), (335, 243), (335, 244), (335, 245), (335, 246), (335, 247), (335, 248), (335, 249), (335, 250), (335, 251), (335, 252), (335, 253), (335, 254), (335, 255), (335, 256), (335, 257), (335, 258), (335, 259), (335, 260), (335, 261), (335, 262), (335, 263), (335, 264), (335, 266), (336, 241), (336, 243), (336, 244), (336, 245), (336, 246), (336, 247), (336, 248), (336, 249), (336, 250), (336, 251), (336, 252), (336, 253), (336, 254), (336, 255), (336, 256), (336, 257), (336, 258), (336, 259), (336, 260), (336, 261), (336, 262), (336, 263), (336, 264), (336, 266), (337, 241), (337, 243), (337, 244), (337, 245), (337, 246), (337, 247), (337, 248), (337, 249), (337, 250), (337, 251),
(337, 252), (337, 253), (337, 254), (337, 255), (337, 256), (337, 257), (337, 258), (337, 259), (337, 260), (337, 261), (337, 262), (337, 263), (337, 265), (338, 241), (338, 243), (338, 244), (338, 245), (338, 246), (338, 247), (338, 248), (338, 249), (338, 250), (338, 251), (338, 252), (338, 253), (338, 254), (338, 255), (338, 256), (338, 257), (338, 258), (338, 259), (338, 260), (338, 261), (338, 264), (339, 241), (339, 243), (339, 244), (339, 245), (339, 246), (339, 247), (339, 248), (339, 249), (339, 250), (339, 251), (339, 252), (339, 253), (339, 254), (339, 255), (339, 256), (339, 257), (339, 258), (339, 259), (339, 260), (339, 263), (340, 241), (340, 243), (340, 244), (340, 245), (340, 246), (340, 247), (340, 248), (340, 249), (340, 250), (340, 251), (340, 252), (340, 253), (340, 254), (340, 255), (340, 256), (340, 257), (340, 258), (340, 261),
(340, 262), (341, 241), (341, 242), (341, 243), (341, 244), (341, 245), (341, 246), (341, 247), (341, 248), (341, 249), (341, 250), (341, 251), (341, 252), (341, 253), (341, 254), (341, 255), (341, 256), (341, 257), (341, 260), (342, 242), (342, 244), (342, 245), (342, 246), (342, 247), (342, 248), (342, 249), (342, 250), (342, 251), (342, 252), (342, 253), (342, 254), (342, 255), (342, 258), (343, 242), (343, 244), (343, 245), (343, 246), (343, 247), (343, 248), (343, 249), (343, 250), (343, 251), (343, 252), (343, 253), (343, 257), (344, 242), (344, 244), (344, 245), (344, 246), (344, 247), (344, 248), (344, 249), (344, 250), (344, 251), (344, 255), (345, 242), (345, 244), (345, 245), (345, 246), (345, 247), (345, 248), (345, 249), (345, 253), (346, 242), (346, 244), (346, 245), (346, 246), (346, 247), (346, 251), (347, 242), (347, 244), (347, 249),
(348, 242), (348, 245), (348, 246), (349, 242), (349, 244), )
coordinates_FF0057 = ((94, 253),
(94, 254), (94, 256), (95, 257), (96, 252), (96, 254), (96, 255), (96, 256), (96, 258), (97, 251), (97, 253), (97, 254), (97, 255), (97, 256), (97, 257), (97, 259), (98, 250), (98, 252), (98, 253), (98, 254), (98, 255), (98, 256), (98, 257), (98, 258), (99, 249), (99, 251), (99, 252), (99, 253), (99, 254), (99, 255), (99, 256), (99, 257), (99, 258), (99, 260), (100, 247), (100, 250), (100, 251), (100, 252), (100, 253), (100, 254), (100, 255), (100, 256), (100, 257), (100, 258), (100, 259), (100, 261), (101, 248), (101, 250), (101, 251), (101, 252), (101, 253), (101, 254), (101, 255), (101, 256), (101, 257), (101, 258), (101, 259), (101, 260), (101, 262), (102, 249), (102, 251), (102, 252), (102, 253), (102, 254), (102, 255), (102, 256), (102, 257), (102, 258), (102, 259), (102, 260), (103, 250), (103, 252), (103, 253),
(103, 254), (103, 255), (103, 256), (103, 257), (103, 258), (103, 259), (103, 260), (103, 261), (103, 264), (104, 251), (104, 253), (104, 254), (104, 255), (104, 256), (104, 257), (104, 258), (104, 259), (104, 260), (104, 261), (104, 262), (104, 266), (105, 252), (105, 254), (105, 255), (105, 256), (105, 257), (105, 258), (105, 259), (105, 260), (105, 261), (105, 262), (105, 263), (105, 264), (105, 266), (106, 253), (106, 255), (106, 256), (106, 257), (106, 258), (106, 259), (106, 260), (106, 261), (106, 262), (106, 263), (106, 264), (106, 266), (107, 253), (107, 255), (107, 256), (107, 257), (107, 258), (107, 259), (107, 260), (107, 261), (107, 262), (107, 263), (107, 264), (107, 266), (108, 254), (108, 256), (108, 257), (108, 258), (108, 259), (108, 260), (108, 261), (108, 262), (108, 263), (108, 264), (108, 265), (108, 267), (109, 254), (109, 256),
(109, 257), (109, 258), (109, 259), (109, 260), (109, 261), (109, 262), (109, 263), (109, 264), (109, 265), (109, 267), (110, 254), (110, 256), (110, 257), (110, 258), (110, 259), (110, 260), (110, 261), (110, 262), (110, 263), (110, 264), (110, 265), (110, 267), (111, 254), (111, 256), (111, 257), (111, 258), (111, 259), (111, 260), (111, 261), (111, 262), (111, 263), (111, 264), (111, 265), (111, 267), (112, 254), (112, 256), (112, 257), (112, 258), (112, 259), (112, 260), (112, 261), (112, 262), (112, 263), (112, 264), (112, 265), (112, 266), (112, 268), (113, 254), (113, 256), (113, 257), (113, 258), (113, 259), (113, 260), (113, 261), (113, 262), (113, 263), (113, 264), (113, 265), (113, 266), (113, 268), (114, 254), (114, 256), (114, 257), (114, 258), (114, 259), (114, 260), (114, 261), (114, 262), (114, 263), (114, 268), (115, 255), (115, 257),
(115, 258), (115, 259), (115, 260), (115, 261), (115, 262), (115, 267), (116, 255), (116, 257), (116, 258), (116, 259), (116, 260), (116, 261), (116, 263), (117, 255), (117, 257), (117, 258), (117, 259), (117, 260), (117, 261), (117, 263), (118, 255), (118, 257), (118, 258), (118, 259), (118, 260), (118, 262), (119, 255), (119, 257), (119, 258), (119, 259), (119, 260), (119, 262), (120, 253), (120, 255), (120, 256), (120, 257), (120, 258), (120, 259), (120, 261), (121, 251), (121, 255), (121, 256), (121, 257), (121, 258), (121, 259), (121, 261), (122, 250), (122, 253), (122, 254), (122, 255), (122, 256), (122, 257), (122, 258), (122, 259), (122, 261), (123, 251), (123, 253), (123, 254), (123, 255), (123, 256), (123, 257), (123, 258), (123, 259), (123, 261), (124, 252), (124, 254), (124, 255), (124, 256), (124, 257), (124, 258), (124, 259), (124, 261),
(125, 252), (125, 254), (125, 255), (125, 256), (125, 257), (125, 258), (125, 259), (125, 261), (126, 253), (126, 256), (126, 257), (126, 258), (126, 259), (126, 261), (127, 254), (127, 261), (128, 257), (128, 258), (128, 259), (128, 261), (270, 261), (271, 255), (271, 257), (271, 258), (271, 259), (271, 261), (272, 254), (272, 261), (273, 254), (273, 256), (273, 257), (273, 258), (273, 259), (273, 261), (274, 253), (274, 255), (274, 256), (274, 257), (274, 258), (274, 259), (274, 261), (275, 254), (275, 255), (275, 256), (275, 257), (275, 258), (275, 259), (275, 261), (276, 250), (276, 253), (276, 254), (276, 255), (276, 256), (276, 257), (276, 258), (276, 259), (276, 261), (277, 251), (277, 253), (277, 254), (277, 255), (277, 256), (277, 257), (277, 258), (277, 259), (277, 261), (278, 252), (278, 255), (278, 256), (278, 257), (278, 258), (278, 259),
(278, 261), (279, 253), (279, 255), (279, 256), (279, 257), (279, 258), (279, 259), (279, 261), (280, 254), (280, 256), (280, 257), (280, 258), (280, 259), (280, 260), (280, 262), (281, 255), (281, 257), (281, 258), (281, 259), (281, 260), (281, 262), (282, 256), (282, 258), (282, 259), (282, 260), (282, 261), (282, 263), (283, 256), (283, 258), (283, 259), (283, 260), (283, 261), (283, 263), (283, 267), (284, 255), (284, 257), (284, 258), (284, 259), (284, 260), (284, 261), (284, 262), (284, 263), (284, 265), (284, 267), (285, 255), (285, 257), (285, 258), (285, 259), (285, 260), (285, 261), (285, 262), (285, 263), (285, 268), (286, 255), (286, 257), (286, 258), (286, 259), (286, 260), (286, 261), (286, 262), (286, 263), (286, 264), (286, 265), (286, 266), (286, 268), (287, 254), (287, 256), (287, 257), (287, 258), (287, 259), (287, 260), (287, 261),
(287, 262), (287, 263), (287, 264), (287, 265), (287, 266), (287, 268), (288, 254), (288, 256), (288, 257), (288, 258), (288, 259), (288, 260), (288, 261), (288, 262), (288, 263), (288, 264), (288, 265), (288, 267), (289, 254), (289, 256), (289, 257), (289, 258), (289, 259), (289, 260), (289, 261), (289, 262), (289, 263), (289, 264), (289, 265), (289, 267), (290, 253), (290, 255), (290, 256), (290, 257), (290, 258), (290, 259), (290, 260), (290, 261), (290, 262), (290, 263), (290, 264), (290, 265), (290, 267), (291, 253), (291, 255), (291, 256), (291, 257), (291, 258), (291, 259), (291, 260), (291, 261), (291, 262), (291, 263), (291, 264), (291, 265), (291, 267), (292, 253), (292, 255), (292, 256), (292, 257), (292, 258), (292, 259), (292, 260), (292, 261), (292, 262), (292, 263), (292, 264), (292, 266), (293, 253), (293, 255), (293, 256), (293, 257),
(293, 258), (293, 259), (293, 260), (293, 261), (293, 262), (293, 263), (293, 264), (293, 266), (294, 252), (294, 254), (294, 255), (294, 256), (294, 257), (294, 258), (294, 259), (294, 260), (294, 261), (294, 262), (294, 263), (294, 266), (295, 252), (295, 254), (295, 255), (295, 256), (295, 257), (295, 258), (295, 259), (295, 260), (295, 261), (295, 262), (295, 266), (296, 251), (296, 253), (296, 254), (296, 255), (296, 256), (296, 257), (296, 258), (296, 259), (296, 260), (296, 261), (297, 250), (297, 252), (297, 253), (297, 254), (297, 255), (297, 256), (297, 257), (297, 258), (297, 259), (297, 260), (298, 249), (298, 251), (298, 252), (298, 253), (298, 254), (298, 255), (298, 256), (298, 257), (298, 258), (298, 259), (298, 260), (298, 262), (299, 248), (299, 250), (299, 251), (299, 252), (299, 253), (299, 254), (299, 255), (299, 256), (299, 257),
(299, 258), (299, 259), (299, 261), (300, 249), (300, 251), (300, 252), (300, 253), (300, 254), (300, 255), (300, 256), (300, 257), (300, 258), (300, 260), (301, 250), (301, 252), (301, 253), (301, 254), (301, 255), (301, 256), (301, 257), (301, 259), (302, 251), (302, 253), (302, 254), (302, 255), (302, 256), (302, 257), (302, 259), (303, 252), (303, 254), (303, 255), (303, 256), (303, 258), (304, 253), (304, 257), (305, 254), (305, 256), )
coordinates_4E007F = ((34, 185),
(34, 187), (34, 188), (34, 189), (34, 190), (34, 191), (35, 182), (35, 183), (35, 184), (35, 192), (35, 193), (35, 194), (35, 195), (35, 197), (36, 180), (36, 185), (36, 186), (36, 187), (36, 188), (36, 189), (36, 190), (36, 191), (36, 196), (37, 180), (37, 182), (37, 183), (37, 184), (37, 185), (37, 186), (37, 187), (37, 188), (37, 189), (37, 190), (37, 191), (37, 195), (38, 180), (38, 183), (38, 184), (38, 185), (38, 186), (38, 187), (38, 188), (38, 189), (38, 190), (38, 193), (39, 181), (39, 186), (39, 187), (39, 188), (39, 189), (39, 191), (40, 183), (40, 185), (40, 188), (40, 190), (41, 186), (41, 189), (42, 188), (43, 188), (356, 188), (357, 188), (358, 186), (358, 189), (359, 183), (359, 185), (359, 188), (359, 190), (360, 181), (360, 186), (360, 187), (360, 188), (360, 189), (360, 191),
(361, 180), (361, 183), (361, 184), (361, 185), (361, 186), (361, 187), (361, 188), (361, 189), (361, 190), (361, 193), (362, 180), (362, 182), (362, 183), (362, 184), (362, 185), (362, 186), (362, 187), (362, 188), (362, 189), (362, 190), (362, 191), (362, 195), (363, 180), (363, 185), (363, 186), (363, 187), (363, 188), (363, 189), (363, 190), (363, 191), (363, 196), (364, 183), (364, 184), (364, 192), (364, 193), (364, 194), (364, 195), (365, 185), (365, 187), (365, 188), (365, 189), (365, 190), )
coordinates_137F00 = ((86, 213),
(86, 214), (87, 212), (87, 214), (88, 212), (88, 215), (89, 211), (89, 213), (89, 215), (90, 210), (90, 212), (90, 213), (90, 215), (91, 210), (91, 212), (91, 213), (91, 214), (91, 216), (92, 209), (92, 211), (92, 212), (92, 213), (92, 214), (92, 216), (92, 226), (92, 228), (93, 209), (93, 211), (93, 212), (93, 213), (93, 214), (93, 215), (93, 217), (93, 224), (93, 229), (94, 208), (94, 210), (94, 211), (94, 212), (94, 213), (94, 214), (94, 215), (94, 217), (94, 223), (94, 226), (94, 227), (94, 230), (95, 208), (95, 210), (95, 211), (95, 212), (95, 213), (95, 214), (95, 215), (95, 216), (95, 217), (95, 221), (95, 224), (95, 225), (95, 226), (95, 227), (95, 228), (95, 232), (96, 208), (96, 210), (96, 211), (96, 212), (96, 213), (96, 214), (96, 215), (96, 216), (96, 217), (96, 219),
(96, 220), (96, 223), (96, 224), (96, 225), (96, 226), (96, 227), (96, 228), (96, 229), (96, 230), (97, 207), (97, 210), (97, 211), (97, 212), (97, 213), (97, 214), (97, 215), (97, 216), (97, 217), (97, 218), (97, 221), (97, 222), (97, 223), (97, 224), (97, 225), (97, 226), (97, 227), (97, 228), (97, 229), (97, 230), (97, 231), (97, 233), (98, 207), (98, 209), (98, 212), (98, 213), (98, 214), (98, 215), (98, 216), (98, 217), (98, 218), (98, 219), (98, 220), (98, 221), (98, 222), (98, 223), (98, 224), (98, 225), (98, 226), (98, 227), (98, 228), (98, 229), (98, 230), (98, 231), (98, 233), (99, 210), (99, 213), (99, 214), (99, 215), (99, 216), (99, 217), (99, 218), (99, 219), (99, 220), (99, 221), (99, 222), (99, 223), (99, 224), (99, 225), (99, 226), (99, 227), (99, 228), (99, 229),
(99, 230), (99, 231), (99, 233), (100, 212), (100, 215), (100, 216), (100, 217), (100, 218), (100, 219), (100, 220), (100, 221), (100, 222), (100, 223), (100, 224), (100, 225), (100, 226), (100, 227), (100, 228), (100, 229), (100, 230), (100, 231), (100, 232), (100, 234), (101, 213), (101, 216), (101, 217), (101, 218), (101, 219), (101, 220), (101, 221), (101, 222), (101, 223), (101, 224), (101, 225), (101, 226), (101, 227), (101, 228), (101, 229), (101, 230), (101, 231), (101, 234), (102, 215), (102, 218), (102, 219), (102, 220), (102, 221), (102, 222), (102, 223), (102, 224), (102, 225), (102, 226), (102, 227), (102, 228), (102, 229), (102, 230), (102, 232), (103, 216), (103, 228), (103, 231), (104, 218), (104, 220), (104, 221), (104, 222), (104, 223), (104, 224), (104, 225), (104, 226), (104, 227), (104, 228), (104, 230), (295, 218), (295, 220),
(295, 221), (295, 222), (295, 223), (295, 224), (295, 225), (295, 226), (295, 227), (295, 228), (295, 230), (296, 216), (296, 231), (297, 214), (297, 218), (297, 219), (297, 220), (297, 221), (297, 222), (297, 223), (297, 224), (297, 225), (297, 226), (297, 227), (297, 228), (297, 229), (297, 230), (297, 232), (298, 213), (298, 216), (298, 217), (298, 218), (298, 219), (298, 220), (298, 221), (298, 222), (298, 223), (298, 224), (298, 225), (298, 226), (298, 227), (298, 228), (298, 229), (298, 230), (298, 231), (298, 234), (299, 212), (299, 214), (299, 215), (299, 216), (299, 217), (299, 218), (299, 219), (299, 220), (299, 221), (299, 222), (299, 223), (299, 224), (299, 225), (299, 226), (299, 227), (299, 228), (299, 229), (299, 230), (299, 231), (299, 232), (299, 234), (300, 210), (300, 213), (300, 214), (300, 215), (300, 216), (300, 217), (300, 218),
(300, 219), (300, 220), (300, 221), (300, 222), (300, 223), (300, 224), (300, 225), (300, 226), (300, 227), (300, 228), (300, 229), (300, 230), (300, 231), (300, 233), (301, 207), (301, 209), (301, 212), (301, 213), (301, 214), (301, 215), (301, 216), (301, 217), (301, 218), (301, 219), (301, 220), (301, 221), (301, 222), (301, 223), (301, 224), (301, 225), (301, 226), (301, 227), (301, 228), (301, 229), (301, 230), (301, 231), (301, 233), (302, 207), (302, 210), (302, 211), (302, 212), (302, 213), (302, 214), (302, 215), (302, 216), (302, 217), (302, 218), (302, 221), (302, 222), (302, 223), (302, 224), (302, 225), (302, 226), (302, 227), (302, 228), (302, 229), (302, 230), (302, 231), (302, 233), (303, 208), (303, 210), (303, 211), (303, 212), (303, 213), (303, 214), (303, 215), (303, 216), (303, 217), (303, 219), (303, 220), (303, 223), (303, 224),
(303, 225), (303, 226), (303, 227), (303, 228), (303, 229), (303, 230), (304, 208), (304, 210), (304, 211), (304, 212), (304, 213), (304, 214), (304, 215), (304, 216), (304, 217), (304, 221), (304, 222), (304, 225), (304, 226), (304, 227), (304, 228), (304, 232), (305, 208), (305, 210), (305, 211), (305, 212), (305, 213), (305, 214), (305, 215), (305, 217), (305, 223), (305, 226), (305, 227), (305, 230), (306, 209), (306, 211), (306, 212), (306, 213), (306, 214), (306, 215), (306, 216), (306, 217), (306, 224), (306, 228), (307, 209), (307, 211), (307, 212), (307, 213), (307, 214), (307, 216), (307, 226), (307, 227), (308, 210), (308, 212), (308, 213), (308, 214), (308, 216), (309, 212), (309, 213), (309, 215), (310, 211), (310, 213), (310, 215), (311, 212), (311, 214), (311, 215), (312, 212), (312, 214), (313, 213), (313, 214), )
coordinates_7F0061 = ((130, 254),
(130, 256), (130, 257), (130, 258), (130, 259), (130, 261), (131, 256), (131, 261), (132, 257), (132, 262), (133, 259), (134, 261), (134, 263), (265, 261), (265, 263), (266, 259), (267, 257), (267, 262), (268, 256), (268, 261), (269, 254), (269, 256), (269, 257), (269, 258), (269, 259), )
| 782.235641
| 865
| 0.485855
|
9fee91fe2e8d112a7a12578571967ac17dd261c6
| 1,417
|
py
|
Python
|
src/pyrfc/__init__.py
|
coledong/PyRFC
|
073bfbd330a6f5581d507c7936974b19147355ea
|
[
"Apache-2.0"
] | 1
|
2020-06-03T17:56:51.000Z
|
2020-06-03T17:56:51.000Z
|
src/pyrfc/__init__.py
|
coledong/PyRFC
|
073bfbd330a6f5581d507c7936974b19147355ea
|
[
"Apache-2.0"
] | null | null | null |
src/pyrfc/__init__.py
|
coledong/PyRFC
|
073bfbd330a6f5581d507c7936974b19147355ea
|
[
"Apache-2.0"
] | null | null | null |
# Copyright 2013 SAP AG.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http: //www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an.
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
# either express or implied. See the License for the specific.
# language governing permissions and limitations under the License.
# import from internal modules that they could be directly imported from
# the pyrfc package
# Set DLL path, due to https://docs.python.org/3.8/whatsnew/3.8.html#bpo-36085-whatsnew
import os
if os.name == "nt":
try:
os.add_dll_directory(os.path.join(os.environ["SAPNWRFC_HOME"], "lib"))
except Exception:
pass
from ._exception import (
RFCError,
RFCLibError,
CommunicationError,
LogonError,
ABAPApplicationError,
ABAPRuntimeError,
ExternalAuthorizationError,
ExternalApplicationError,
ExternalRuntimeError,
)
from .pyrfc import (
get_nwrfclib_version,
Connection,
Throughput,
TypeDescription,
FunctionDescription,
)
__author__ = """"Srdjan Boskovic"""
__email__ = "srdjan.boskovic@sap.com"
__version__ = "2.0.5"
| 28.34
| 88
| 0.703599
|
082d881741a10b0ce11d96970cda7042f4cec15e
| 6,808
|
py
|
Python
|
rich/_palettes.py
|
BIGBALLON/rich
|
4e24f2ef1a978ce5f1b01b2b26b36f87b87566f2
|
[
"MIT"
] | 16
|
2020-09-20T22:32:54.000Z
|
2021-04-02T17:14:25.000Z
|
rich/_palettes.py
|
BIGBALLON/rich
|
4e24f2ef1a978ce5f1b01b2b26b36f87b87566f2
|
[
"MIT"
] | 42
|
2020-12-16T07:03:59.000Z
|
2022-03-28T20:11:50.000Z
|
rich/_palettes.py
|
BIGBALLON/rich
|
4e24f2ef1a978ce5f1b01b2b26b36f87b87566f2
|
[
"MIT"
] | 3
|
2021-05-21T21:26:34.000Z
|
2021-10-05T16:57:57.000Z
|
from .palette import Palette
# The standard ansi colors
WINDOWS_PALETTE = Palette(
[
(0, 0, 0),
(128, 0, 0),
(0, 128, 0),
(128, 128, 0),
(0, 0, 128),
(128, 0, 128),
(0, 128, 128),
(192, 192, 192),
]
)
# # The standard ansi colors (including bright variants)
STANDARD_PALETTE = Palette(
[
(0, 0, 0),
(170, 0, 0),
(0, 170, 0),
(170, 85, 0),
(0, 0, 170),
(170, 0, 170),
(0, 170, 170),
(170, 170, 170),
(85, 85, 85),
(255, 85, 85),
(85, 255, 85),
(255, 255, 85),
(85, 85, 255),
(255, 85, 255),
(85, 255, 255),
(255, 255, 255),
]
)
# The 256 color palette
EIGHT_BIT_PALETTE = Palette(
[
(0, 0, 0),
(128, 0, 0),
(0, 128, 0),
(128, 128, 0),
(0, 0, 128),
(128, 0, 128),
(0, 128, 128),
(192, 192, 192),
(128, 128, 128),
(255, 0, 0),
(0, 255, 0),
(255, 255, 0),
(0, 0, 255),
(255, 0, 255),
(0, 255, 255),
(255, 255, 255),
(0, 0, 0),
(0, 0, 95),
(0, 0, 135),
(0, 0, 175),
(0, 0, 215),
(0, 0, 255),
(0, 95, 0),
(0, 95, 95),
(0, 95, 135),
(0, 95, 175),
(0, 95, 215),
(0, 95, 255),
(0, 135, 0),
(0, 135, 95),
(0, 135, 135),
(0, 135, 175),
(0, 135, 215),
(0, 135, 255),
(0, 175, 0),
(0, 175, 95),
(0, 175, 135),
(0, 175, 175),
(0, 175, 215),
(0, 175, 255),
(0, 215, 0),
(0, 215, 95),
(0, 215, 135),
(0, 215, 175),
(0, 215, 215),
(0, 215, 255),
(0, 255, 0),
(0, 255, 95),
(0, 255, 135),
(0, 255, 175),
(0, 255, 215),
(0, 255, 255),
(95, 0, 0),
(95, 0, 95),
(95, 0, 135),
(95, 0, 175),
(95, 0, 215),
(95, 0, 255),
(95, 95, 0),
(95, 95, 95),
(95, 95, 135),
(95, 95, 175),
(95, 95, 215),
(95, 95, 255),
(95, 135, 0),
(95, 135, 95),
(95, 135, 135),
(95, 135, 175),
(95, 135, 215),
(95, 135, 255),
(95, 175, 0),
(95, 175, 95),
(95, 175, 135),
(95, 175, 175),
(95, 175, 215),
(95, 175, 255),
(95, 215, 0),
(95, 215, 95),
(95, 215, 135),
(95, 215, 175),
(95, 215, 215),
(95, 215, 255),
(95, 255, 0),
(95, 255, 95),
(95, 255, 135),
(95, 255, 175),
(95, 255, 215),
(95, 255, 255),
(135, 0, 0),
(135, 0, 95),
(135, 0, 135),
(135, 0, 175),
(135, 0, 215),
(135, 0, 255),
(135, 95, 0),
(135, 95, 95),
(135, 95, 135),
(135, 95, 175),
(135, 95, 215),
(135, 95, 255),
(135, 135, 0),
(135, 135, 95),
(135, 135, 135),
(135, 135, 175),
(135, 135, 215),
(135, 135, 255),
(135, 175, 0),
(135, 175, 95),
(135, 175, 135),
(135, 175, 175),
(135, 175, 215),
(135, 175, 255),
(135, 215, 0),
(135, 215, 95),
(135, 215, 135),
(135, 215, 175),
(135, 215, 215),
(135, 215, 255),
(135, 255, 0),
(135, 255, 95),
(135, 255, 135),
(135, 255, 175),
(135, 255, 215),
(135, 255, 255),
(175, 0, 0),
(175, 0, 95),
(175, 0, 135),
(175, 0, 175),
(175, 0, 215),
(175, 0, 255),
(175, 95, 0),
(175, 95, 95),
(175, 95, 135),
(175, 95, 175),
(175, 95, 215),
(175, 95, 255),
(175, 135, 0),
(175, 135, 95),
(175, 135, 135),
(175, 135, 175),
(175, 135, 215),
(175, 135, 255),
(175, 175, 0),
(175, 175, 95),
(175, 175, 135),
(175, 175, 175),
(175, 175, 215),
(175, 175, 255),
(175, 215, 0),
(175, 215, 95),
(175, 215, 135),
(175, 215, 175),
(175, 215, 215),
(175, 215, 255),
(175, 255, 0),
(175, 255, 95),
(175, 255, 135),
(175, 255, 175),
(175, 255, 215),
(175, 255, 255),
(215, 0, 0),
(215, 0, 95),
(215, 0, 135),
(215, 0, 175),
(215, 0, 215),
(215, 0, 255),
(215, 95, 0),
(215, 95, 95),
(215, 95, 135),
(215, 95, 175),
(215, 95, 215),
(215, 95, 255),
(215, 135, 0),
(215, 135, 95),
(215, 135, 135),
(215, 135, 175),
(215, 135, 215),
(215, 135, 255),
(215, 175, 0),
(215, 175, 95),
(215, 175, 135),
(215, 175, 175),
(215, 175, 215),
(215, 175, 255),
(215, 215, 0),
(215, 215, 95),
(215, 215, 135),
(215, 215, 175),
(215, 215, 215),
(215, 215, 255),
(215, 255, 0),
(215, 255, 95),
(215, 255, 135),
(215, 255, 175),
(215, 255, 215),
(215, 255, 255),
(255, 0, 0),
(255, 0, 95),
(255, 0, 135),
(255, 0, 175),
(255, 0, 215),
(255, 0, 255),
(255, 95, 0),
(255, 95, 95),
(255, 95, 135),
(255, 95, 175),
(255, 95, 215),
(255, 95, 255),
(255, 135, 0),
(255, 135, 95),
(255, 135, 135),
(255, 135, 175),
(255, 135, 215),
(255, 135, 255),
(255, 175, 0),
(255, 175, 95),
(255, 175, 135),
(255, 175, 175),
(255, 175, 215),
(255, 175, 255),
(255, 215, 0),
(255, 215, 95),
(255, 215, 135),
(255, 215, 175),
(255, 215, 215),
(255, 215, 255),
(255, 255, 0),
(255, 255, 95),
(255, 255, 135),
(255, 255, 175),
(255, 255, 215),
(255, 255, 255),
(8, 8, 8),
(18, 18, 18),
(28, 28, 28),
(38, 38, 38),
(48, 48, 48),
(58, 58, 58),
(68, 68, 68),
(78, 78, 78),
(88, 88, 88),
(98, 98, 98),
(108, 108, 108),
(118, 118, 118),
(128, 128, 128),
(138, 138, 138),
(148, 148, 148),
(158, 158, 158),
(168, 168, 168),
(178, 178, 178),
(188, 188, 188),
(198, 198, 198),
(208, 208, 208),
(218, 218, 218),
(228, 228, 228),
(238, 238, 238),
]
)
| 22.543046
| 56
| 0.328437
|
9c9b53c4944db740fb42850c8b5af13165bfe2fb
| 7,962
|
py
|
Python
|
TimeWrapper_JE/venv/Lib/site-packages/pip/_internal/cli/base_command.py
|
JE-Chen/je_old_repo
|
a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5
|
[
"MIT"
] | null | null | null |
TimeWrapper_JE/venv/Lib/site-packages/pip/_internal/cli/base_command.py
|
JE-Chen/je_old_repo
|
a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5
|
[
"MIT"
] | null | null | null |
TimeWrapper_JE/venv/Lib/site-packages/pip/_internal/cli/base_command.py
|
JE-Chen/je_old_repo
|
a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5
|
[
"MIT"
] | 1
|
2021-06-20T19:28:37.000Z
|
2021-06-20T19:28:37.000Z
|
"""Base Command class, and related routines"""
import logging
import logging.config
import optparse
import os
import sys
import traceback
from optparse import Values
from typing import Any, List, Optional, Tuple
from pip._internal.cli import cmdoptions
from pip._internal.cli.command_context import CommandContextMixIn
from pip._internal.cli.parser import ConfigOptionParser, UpdatingDefaultsHelpFormatter
from pip._internal.cli.status_codes import (
ERROR,
PREVIOUS_BUILD_DIR_ERROR,
UNKNOWN_ERROR,
VIRTUALENV_NOT_FOUND,
)
from pip._internal.exceptions import (
BadCommand,
CommandError,
InstallationError,
NetworkConnectionError,
PreviousBuildDirError,
UninstallationError,
)
from pip._internal.utils.deprecation import deprecated
from pip._internal.utils.filesystem import check_path_owner
from pip._internal.utils.logging import BrokenStdoutLoggingError, setup_logging
from pip._internal.utils.misc import get_prog, normalize_path
from pip._internal.utils.temp_dir import TempDirectoryTypeRegistry as TempDirRegistry
from pip._internal.utils.temp_dir import global_tempdir_manager, tempdir_registry
from pip._internal.utils.virtualenv import running_under_virtualenv
__all__ = ["Command"]
logger = logging.getLogger(__name__)
class Command(CommandContextMixIn):
usage = None # type: str
ignore_require_venv = False # type: bool
def __init__(self, name, summary, isolated=False):
# type: (str, str, bool) -> None
super().__init__()
self.name = name
self.summary = summary
self.parser = ConfigOptionParser(
usage=self.usage,
prog=f"{get_prog()} {name}",
formatter=UpdatingDefaultsHelpFormatter(),
add_help_option=False,
name=name,
description=self.__doc__,
isolated=isolated,
)
self.tempdir_registry = None # type: Optional[TempDirRegistry]
# Commands should add options to this option group
optgroup_name = f"{self.name.capitalize()} Options"
self.cmd_opts = optparse.OptionGroup(self.parser, optgroup_name)
# Add the general options
gen_opts = cmdoptions.make_option_group(
cmdoptions.general_group,
self.parser,
)
self.parser.add_option_group(gen_opts)
self.add_options()
def add_options(self):
# type: () -> None
pass
def handle_pip_version_check(self, options):
# type: (Values) -> None
"""
This is a no-op so that commands by default do not do the pip version
check.
"""
# Make sure we do the pip version check if the index_group options
# are present.
assert not hasattr(options, "no_index")
def run(self, options, args):
# type: (Values, List[Any]) -> int
raise NotImplementedError
def parse_args(self, args):
# type: (List[str]) -> Tuple[Any, Any]
# factored out for testability
return self.parser.parse_args(args)
def main(self, args):
# type: (List[str]) -> int
try:
with self.main_context():
return self._main(args)
finally:
logging.shutdown()
def _main(self, args):
# type: (List[str]) -> int
# We must initialize this before the tempdir manager, otherwise the
# configuration would not be accessible by the time we clean up the
# tempdir manager.
self.tempdir_registry = self.enter_context(tempdir_registry())
# Intentionally set as early as possible so globally-managed temporary
# directories are available to the rest of the code.
self.enter_context(global_tempdir_manager())
options, args = self.parse_args(args)
# Set verbosity so that it can be used elsewhere.
self.verbosity = options.verbose - options.quiet
level_number = setup_logging(
verbosity=self.verbosity,
no_color=options.no_color,
user_log_file=options.log,
)
# TODO: Try to get these passing down from the command?
# without resorting to os.environ to hold these.
# This also affects isolated builds and it should.
if options.no_input:
os.environ["PIP_NO_INPUT"] = "1"
if options.exists_action:
os.environ["PIP_EXISTS_ACTION"] = " ".join(options.exists_action)
if options.require_venv and not self.ignore_require_venv:
# If a venv is required check if it can really be found
if not running_under_virtualenv():
logger.critical("Could not find an activated virtualenv (required).")
sys.exit(VIRTUALENV_NOT_FOUND)
if options.cache_dir:
options.cache_dir = normalize_path(options.cache_dir)
if not check_path_owner(options.cache_dir):
logger.warning(
"The directory '%s' or its parent directory is not owned "
"or is not writable by the current user. The cache "
"has been disabled. Check the permissions and owner of "
"that directory. If executing pip with sudo, you should "
"use sudo's -H flag.",
options.cache_dir,
)
options.cache_dir = None
if getattr(options, "build_dir", None):
deprecated(
reason=(
"The -b/--build/--build-dir/--build-directory "
"option is deprecated and has no effect anymore."
),
replacement=(
"use the TMPDIR/TEMP/TMP environment variable, "
"possibly combined with --no-clean"
),
gone_in="21.3",
issue=8333,
)
if "2020-resolver" in options.features_enabled:
logger.warning(
"--use-feature=2020-resolver no longer has any effect, "
"since it is now the default dependency resolver in pip. "
"This will become an error in pip 21.0."
)
try:
status = self.run(options, args)
assert isinstance(status, int)
return status
except PreviousBuildDirError as exc:
logger.critical(str(exc))
logger.debug("Exception information:", exc_info=True)
return PREVIOUS_BUILD_DIR_ERROR
except (
InstallationError,
UninstallationError,
BadCommand,
NetworkConnectionError,
) as exc:
logger.critical(str(exc))
logger.debug("Exception information:", exc_info=True)
return ERROR
except CommandError as exc:
logger.critical("%s", exc)
logger.debug("Exception information:", exc_info=True)
return ERROR
except BrokenStdoutLoggingError:
# Bypass our logger and write any remaining messages to stderr
# because stdout no longer works.
print("ERROR: Pipe to stdout was broken", file=sys.stderr)
if level_number <= logging.DEBUG:
traceback.print_exc(file=sys.stderr)
return ERROR
except KeyboardInterrupt:
logger.critical("Operation cancelled by user")
logger.debug("Exception information:", exc_info=True)
return ERROR
except BaseException:
logger.critical("Exception:", exc_info=True)
return UNKNOWN_ERROR
finally:
self.handle_pip_version_check(options)
| 35.864865
| 87
| 0.601105
|
f58c115847f3d0e2109da87a3245c07b6f82922b
| 26
|
py
|
Python
|
terrascript/kubernetes/__init__.py
|
GarnerCorp/python-terrascript
|
ec6c2d9114dcd3cb955dd46069f8ba487e320a8c
|
[
"BSD-2-Clause"
] | null | null | null |
terrascript/kubernetes/__init__.py
|
GarnerCorp/python-terrascript
|
ec6c2d9114dcd3cb955dd46069f8ba487e320a8c
|
[
"BSD-2-Clause"
] | null | null | null |
terrascript/kubernetes/__init__.py
|
GarnerCorp/python-terrascript
|
ec6c2d9114dcd3cb955dd46069f8ba487e320a8c
|
[
"BSD-2-Clause"
] | 1
|
2018-11-15T16:23:05.000Z
|
2018-11-15T16:23:05.000Z
|
"""2019-05-28 10:49:51"""
| 13
| 25
| 0.538462
|
6ef8dc1caadc6a1ad2e7410242b2e7f50a4d6285
| 2,801
|
py
|
Python
|
src/ralph_assets/models_util.py
|
vi4m/ralph_assets
|
d174e8f769da2d5a335d24bbef5d0ca2e205383c
|
[
"Apache-2.0"
] | null | null | null |
src/ralph_assets/models_util.py
|
vi4m/ralph_assets
|
d174e8f769da2d5a335d24bbef5d0ca2e205383c
|
[
"Apache-2.0"
] | null | null | null |
src/ralph_assets/models_util.py
|
vi4m/ralph_assets
|
d174e8f769da2d5a335d24bbef5d0ca2e205383c
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Model utilities and mixins."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from django.contrib.contenttypes.models import ContentType
from django.contrib.contenttypes import generic
from django.db import models
from lck.django.choices import Choices
from ralph.account.models import Region
from ralph import middleware
from datetime import datetime
from django.utils.translation import ugettext_lazy as _
class LastSeen(models.Model):
last_seen = models.DateTimeField(verbose_name=_("last seen"),
default=datetime.now)
class Meta:
abstract = True
def save(self, update_last_seen=False, *args, **kwargs):
if update_last_seen:
self.last_seen = datetime.now()
super(LastSeen, self).save(*args, **kwargs)
class SavingUser(models.Model):
class Meta:
abstract = True
def save(self, user=None, *args, **kwargs):
self.saving_user = user
return super(SavingUser, self).save(user=user, *args, **kwargs)
class ProblemSeverity(Choices):
_ = Choices.Choice
warning = _("Warning")
correct_me = _("Correct me")
error = _("Error")
class ImportProblem(models.Model):
"""Any problem with importing the resource from XLS/CSV."""
content_type = models.ForeignKey(ContentType)
object_id = models.PositiveIntegerField()
resource = generic.GenericForeignKey('content_type', 'object_id')
severity = models.PositiveSmallIntegerField(choices=ProblemSeverity())
message = models.TextField()
def __str__(self):
return self.message
def add_problem(resource, severity, message):
"""Add a problem to the resource
:param resource: Any django model instance
:param severity: An instance of `ralph_assets.models.util.ProblemSeverity`
:param message: A string describing the problem"""
problem = ImportProblem(
severity=severity,
message=message,
)
problem.resource = resource
problem.save()
class RegionalizedDBManager(models.Manager):
def get_query_set(self):
query_set = super(RegionalizedDBManager, self).get_query_set()
regions = middleware.get_actual_regions()
query_set = query_set.filter(region__in=regions)
return query_set
class Regionalized(models.Model):
"""Describes an abstract model with region definition in ``region`` field
defined in ralph.accounts.models.Region"""
objects = RegionalizedDBManager()
admin_objects = models.Manager()
region = models.ForeignKey(Region)
class Meta:
abstract = True
def __unicode__(self):
return self.region.name
| 28.01
| 78
| 0.706176
|
b96bbe4c152fd198cecca087eeee0a2cb6bc663b
| 5,757
|
py
|
Python
|
tools/generate-tempest-plugins-list.py
|
cityofships/tempest
|
59aa6811a3664d88b8939603b8e974644fbe21fa
|
[
"Apache-2.0"
] | 254
|
2015-01-05T19:22:52.000Z
|
2022-03-29T08:14:54.000Z
|
tools/generate-tempest-plugins-list.py
|
cityofships/tempest
|
59aa6811a3664d88b8939603b8e974644fbe21fa
|
[
"Apache-2.0"
] | 13
|
2015-03-02T15:53:04.000Z
|
2022-02-16T02:28:14.000Z
|
tools/generate-tempest-plugins-list.py
|
cityofships/tempest
|
59aa6811a3664d88b8939603b8e974644fbe21fa
|
[
"Apache-2.0"
] | 367
|
2015-01-07T15:05:39.000Z
|
2022-03-04T09:50:35.000Z
|
#! /usr/bin/env python
# Copyright 2016 Hewlett Packard Enterprise Development Company, L.P.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
# This script is intended to be run as part of a periodic proposal bot
# job in OpenStack infrastructure.
#
# In order to function correctly, the environment in which the
# script runs must have
# * network access to the review.opendev.org Gerrit API
# working directory
# * network access to https://opendev.org/openstack
import json
import re
import sys
import urllib3
from urllib3.util import retry
# List of projects having tempest plugin stale or unmaintained for a long time
# (6 months or more)
# TODO(masayukig): Some of these can be removed from NON_ACTIVE_LIST in the
# future when the patches are merged.
NON_ACTIVE_LIST = [
'x/gce-api', # It looks gce-api doesn't support python3 yet
# https://bugs.launchpad.net/gce-api/+bug/1931094
'x/glare', # To avoid sanity-job failure
'x/group-based-policy',
# https://bugs.launchpad.net/group-based-policy/+bug/1931091
'x/intel-nfv-ci-tests', # To avoid sanity-job failure
'openstack/networking-generic-switch',
# This is not a real tempest plugin,
# https://review.opendev.org/#/c/634846/
'x/networking-plumgrid', # No longer contains tempest tests
'x/networking-spp', # https://review.opendev.org/#/c/635098/
# networking-spp is missing neutron-tempest-plugin as a dep plus
# test-requirements.txt is nested in a openstack dir and sanity script
# doesn't count with such scenario yet
'openstack/neutron-dynamic-routing',
# As tests have been migrated to neutron-tempest-plugin:
# https://review.opendev.org/#/c/637718/
'openstack/neutron-vpnaas',
# As tests have been migrated to neutron-tempest-plugin:
# https://review.opendev.org/c/openstack/neutron-vpnaas/+/695834
'x/valet', # valet is unmaintained now
# https://review.opendev.org/c/x/valet/+/638339
'x/kingbird', # kingbird is unmaintained now
# https://bugs.launchpad.net/kingbird/+bug/1869722
'x/mogan',
# mogan is unmaintained now, remove from the list when this is merged:
# https://review.opendev.org/c/x/mogan/+/767718
'x/vmware-nsx-tempest-plugin'
# Failing since 2021-08-27
# https://zuul.opendev.org/t/openstack/build
# /45f6c8d3c62d4387a70b7b471ec687c8
# Below plugins failing for error in psycopg2 __init__
# ImportError: libpq.so.5: cannot open shared object
# file: No such file or directory
# https://zuul.opendev.org/t/openstack/build
# /b61a48196dfa476d83645aea4853e544/log/job-output.txt#271722
# Failing since 2021-09-08
'x/networking-l2gw-tempest-plugin'
'x/novajoin-tempest-plugin'
'x/ranger-tempest-plugin'
'x/tap-as-a-service-tempest-plugin'
'x/trio2o'
]
url = 'https://review.opendev.org/projects/'
# This is what a project looks like
'''
"openstack-attic/akanda": {
"id": "openstack-attic%2Fakanda",
"state": "READ_ONLY"
},
'''
http = urllib3.PoolManager(cert_reqs='CERT_REQUIRED')
retries = retry.Retry(status_forcelist=[500], backoff_factor=1.0)
def has_tempest_plugin(proj):
try:
r = http.request('GET', "https://opendev.org/%s/raw/branch/"
"master/setup.cfg" % proj, retries=retries)
if r.status == 404:
return False
except urllib3.exceptions.MaxRetryError as err:
# We should not ignore non 404 errors.
raise err
p = re.compile(r'^tempest\.test_plugins', re.M)
if p.findall(r.data.decode('utf-8')):
return True
else:
False
if len(sys.argv) > 1 and sys.argv[1] == 'nonactivelist':
for non_active_plugin in NON_ACTIVE_LIST:
print(non_active_plugin)
# We just need NON_ACTIVE_LIST when we use this `nonactivelist` option.
# So, this exits here.
sys.exit()
r = http.request('GET', url, retries=retries)
# Gerrit prepends 4 garbage octets to the JSON, in order to counter
# cross-site scripting attacks. Therefore we must discard it so the
# json library won't choke.
content = r.data.decode('utf-8')[4:]
projects = sorted(json.loads(content))
# Retrieve projects having no deployment tool repo (such as deb,
# puppet, ansible, etc.), infra repos, ui or spec namespace as those
# namespaces do not contains tempest plugins.
projects_list = [i for i in projects if not (
i.startswith('openstack-dev/') or
i.startswith('openstack-infra/') or
i.startswith('openstack/ansible-') or
i.startswith('openstack/charm-') or
i.startswith('openstack/cookbook-openstack-') or
i.startswith('openstack/devstack-') or
i.startswith('openstack/fuel-') or
i.startswith('openstack/deb-') or
i.startswith('openstack/puppet-') or
i.startswith('openstack/openstack-ansible-') or
i.startswith('x/deb-') or
i.startswith('x/fuel-') or
i.startswith('x/python-') or
i.startswith('zuul/') or
i.endswith('-ui') or
i.endswith('-specs'))]
found_plugins = list(filter(has_tempest_plugin, projects_list))
# We have tempest plugins not only in 'openstack/' namespace but also the
# other name spaces such as 'airship/', 'x/', etc.
# So, we print all of them here.
for project in found_plugins:
print(project)
| 37.383117
| 78
| 0.70106
|
2e6084ccc55954e25925ca6df8701f9d4b67bd15
| 185
|
py
|
Python
|
x_rebirth_station_calculator/station_data/wares/surface_miner_urv_mk2.py
|
Phipsz/XRebirthStationCalculator
|
ac31c2f5816be34a7df2d7c4eb4bd5e01f7ff835
|
[
"MIT"
] | 1
|
2016-04-17T11:00:22.000Z
|
2016-04-17T11:00:22.000Z
|
x_rebirth_station_calculator/station_data/wares/surface_miner_urv_mk2.py
|
Phipsz/XRebirthStationCalculator
|
ac31c2f5816be34a7df2d7c4eb4bd5e01f7ff835
|
[
"MIT"
] | null | null | null |
x_rebirth_station_calculator/station_data/wares/surface_miner_urv_mk2.py
|
Phipsz/XRebirthStationCalculator
|
ac31c2f5816be34a7df2d7c4eb4bd5e01f7ff835
|
[
"MIT"
] | null | null | null |
from x_rebirth_station_calculator.station_data.station_base import Ware
names = {'L044': 'Surface Miner URV Mk2',
'L049': 'Tagebau-URV Mk2'}
SurfaceMinerURVMk2 = Ware(names)
| 26.428571
| 71
| 0.740541
|
d9f2ff0aeca975dd1e71c83436607932dcf8a1a6
| 2,346
|
py
|
Python
|
iriusrisk-python-client-lib/test/test_threats_api.py
|
iriusrisk/iriusrisk-python-client-lib
|
4912706cd1e5c0bc555dbc7da02fb64cbeab3b18
|
[
"Apache-2.0"
] | null | null | null |
iriusrisk-python-client-lib/test/test_threats_api.py
|
iriusrisk/iriusrisk-python-client-lib
|
4912706cd1e5c0bc555dbc7da02fb64cbeab3b18
|
[
"Apache-2.0"
] | null | null | null |
iriusrisk-python-client-lib/test/test_threats_api.py
|
iriusrisk/iriusrisk-python-client-lib
|
4912706cd1e5c0bc555dbc7da02fb64cbeab3b18
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
"""
IriusRisk API
Products API # noqa: E501
OpenAPI spec version: 1
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import unittest
import iriusrisk_python_client_lib
from iriusrisk_python_client_lib.api.threats_api import ThreatsApi # noqa: E501
from iriusrisk_python_client_lib.rest import ApiException
class TestThreatsApi(unittest.TestCase):
"""ThreatsApi unit test stubs"""
def setUp(self):
self.api = iriusrisk_python_client_lib.api.threats_api.ThreatsApi() # noqa: E501
def tearDown(self):
pass
def test_libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_post(self):
"""Test case for libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_post
Creates a new threat in a library. # noqa: E501
"""
pass
def test_libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_threat_ref_countermeasures_put(self):
"""Test case for libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_threat_ref_countermeasures_put
Associates a countermeasure to a threat in a risk pattern. # noqa: E501
"""
pass
def test_libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_threat_ref_weaknesses_put(self):
"""Test case for libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_threat_ref_weaknesses_put
Associates weakness to a threat in a risk pattern. # noqa: E501
"""
pass
def test_libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_threat_ref_weaknesses_weakness_ref_countermeasures_put(self):
"""Test case for libraries_library_ref_riskpatterns_risk_pattern_ref_usecases_use_case_ref_threats_threat_ref_weaknesses_weakness_ref_countermeasures_put
Associates a countermeasure to a weakness in a risk pattern. # noqa: E501
"""
pass
def test_products_ref_threats_get(self):
"""Test case for products_ref_threats_get
Gets a list of all threats of a product # noqa: E501
"""
pass
if __name__ == '__main__':
unittest.main()
| 33.514286
| 161
| 0.768542
|
65f7bba3b5c556a183226c492f4fde582343e814
| 874
|
py
|
Python
|
gaphor/UML/usecases/extend.py
|
bertob/gaphor
|
a1d6f8dd8c878f299980bba6c055436148573274
|
[
"Apache-2.0"
] | null | null | null |
gaphor/UML/usecases/extend.py
|
bertob/gaphor
|
a1d6f8dd8c878f299980bba6c055436148573274
|
[
"Apache-2.0"
] | null | null | null |
gaphor/UML/usecases/extend.py
|
bertob/gaphor
|
a1d6f8dd8c878f299980bba6c055436148573274
|
[
"Apache-2.0"
] | null | null | null |
"""Use case extension relationship."""
from gaphor import UML
from gaphor.diagram.presentation import LinePresentation, Named
from gaphor.diagram.shapes import Box, EditableText, Text, draw_arrow_head
from gaphor.diagram.support import represents
from gaphor.UML.modelfactory import stereotypes_str
@represents(UML.Extend)
class ExtendItem(LinePresentation, Named):
"""Use case extension relationship."""
def __init__(self, id=None, model=None):
super().__init__(id, model, style={"dash-style": (7.0, 5.0)})
self.shape_middle = Box(
Text(text=lambda: stereotypes_str(self.subject, ("extend",))),
EditableText(text=lambda: self.subject.name or ""),
)
self.watch("subject.appliedStereotype.classifier.name").watch(
"subject[NamedElement].name"
)
self.draw_head = draw_arrow_head
| 34.96
| 74
| 0.697941
|
9c265d7af0dc76b2721d6537a935c688e8cd0ab1
| 835
|
py
|
Python
|
app/core/tests/test_commands.py
|
Mimicx/recipe-app-api
|
4aa0ad098d414861b628e50948b741dc56a5847a
|
[
"MIT"
] | null | null | null |
app/core/tests/test_commands.py
|
Mimicx/recipe-app-api
|
4aa0ad098d414861b628e50948b741dc56a5847a
|
[
"MIT"
] | null | null | null |
app/core/tests/test_commands.py
|
Mimicx/recipe-app-api
|
4aa0ad098d414861b628e50948b741dc56a5847a
|
[
"MIT"
] | null | null | null |
from unittest.mock import patch
from django.core.management import call_command
from django.db.utils import OperationalError
from django.test import TestCase
class CommandTests(TestCase):
def test_wait_for_db_ready(self):
"""Test Waiting for db when db is available"""
with patch('django.db.utils.ConnectionHandler.__getitem__') as gi:
gi.return_value = True
call_command('wait_for_db')
self.assertEqual(gi.call_count, 1)
@patch('time.sleep', return_value=True)
def test_wait_for_db(self, ts):
""" TEST waiting fro db """
with patch('django.db.utils.ConnectionHandler.__getitem__') as gi:
gi.side_effect = [OperationalError] * 5 + [True]
call_command('wait_for_db')
self.assertEqual(gi.call_count, 6)
| 33.4
| 74
| 0.665868
|
be9a755e995d43297395442ccbd32758e60581f6
| 1,597
|
py
|
Python
|
jenkjobs/__init__.py
|
UCL/jenkjobs
|
63945399310111f35f39b6ae74cfca4d9eb1d75b
|
[
"Apache-2.0"
] | null | null | null |
jenkjobs/__init__.py
|
UCL/jenkjobs
|
63945399310111f35f39b6ae74cfca4d9eb1d75b
|
[
"Apache-2.0"
] | null | null | null |
jenkjobs/__init__.py
|
UCL/jenkjobs
|
63945399310111f35f39b6ae74cfca4d9eb1d75b
|
[
"Apache-2.0"
] | null | null | null |
def rsdt_doxygen(parser, xml_parent, data):
"""yaml: junit
Publish Doxygen documentation
Sameas as jenkins
Example::
publishers:
- rsdt_doxygen:
doxyfile: path to doxyfile relative to workspace. Required.
folder: path to working directory relative to workspace.
Defaults to ""
node: nodename. Defaults to "".
keep: whether to keep previous docs. Defaults to false.
"""
from jenkins_jobs.errors import JenkinsJobsException
from xml.etree.ElementTree import SubElement
doxygen = SubElement(xml_parent, 'hudson.plugins.doxygen.DoxygenArchiver')
if not data['doxyfile']:
raise JenkinsJobsException("The path to a doxyfile must be specified.")
SubElement(doxygen, 'doxyfilePath').text = data['doxyfile']
SubElement(doxygen, 'runOnChild').text = data.get("node", "")
SubElement(doxygen, 'folderWhereYouRunDoxygen').text \
= data.get("folder", "")
SubElement(doxygen, 'keepAll').text = data.get("keep", "false")
def trac(parser, xml_parent, data):
"""yaml: trac
Adds trac property.
Requires trac plugin.
Example::
properties:
- track:
url: url to trac
"""
from jenkins_jobs.errors import JenkinsJobsException
from xml.etree.ElementTree import SubElement
trac = SubElement(xml_parent, 'hudson.plugins.trac.TracProjectProperty')
if not data['url']:
raise JenkinsJobsException("The path to a doxyfile must be specified.")
SubElement(trac, 'tracWebsite').text = data['url']
| 33.978723
| 79
| 0.66124
|
9d8b32e80f2eb829d0b4b554273e23770f8111b4
| 1,794
|
py
|
Python
|
pymatgen/tests/test_init.py
|
JiQi535/pymatgen
|
9dc1a8e3658da846e79c25d55c399c13ec25646b
|
[
"MIT"
] | null | null | null |
pymatgen/tests/test_init.py
|
JiQi535/pymatgen
|
9dc1a8e3658da846e79c25d55c399c13ec25646b
|
[
"MIT"
] | null | null | null |
pymatgen/tests/test_init.py
|
JiQi535/pymatgen
|
9dc1a8e3658da846e79c25d55c399c13ec25646b
|
[
"MIT"
] | 1
|
2020-10-20T02:09:02.000Z
|
2020-10-20T02:09:02.000Z
|
import os
import unittest
import warnings
import ruamel.yaml as yaml
from pymatgen import (
SETTINGS,
SETTINGS_FILE,
Structure,
_load_pmg_settings,
get_structure_from_mp,
loadfn,
)
from pymatgen.io.vasp import Vasprun
test_dir = os.path.join(os.path.dirname(__file__), "..", "..", "test_files")
class SettingsTestCase(unittest.TestCase):
# def test_something(self):
# SETTINGS = _load_pmg_settings()
# if os.path.exists(SETTINGS_FILE):
# with open(SETTINGS_FILE, "rt") as f:
# d = yaml.safe_load(f)
# for k, v in d.items():
# self.assertEqual(v, SETTINGS[k])
# else:
# for k, v in SETTINGS.items():
# self.assertEqual(v, os.environ.get(k))
@unittest.skipIf(
not SETTINGS.get("PMG_MAPI_KEY"), "PMG_MAPI_KEY environment variable not set."
)
def test_get_structure_from_mp(self):
with warnings.catch_warnings():
warnings.simplefilter("ignore")
self.assertEqual(get_structure_from_mp("Li2O").formula, "Li2 O1")
self.assertRaises(ValueError, get_structure_from_mp, "LiNaKCs")
def test_loadfn(self):
with warnings.catch_warnings():
warnings.simplefilter("ignore")
obj = loadfn(os.path.join(test_dir, "Li2O.cif"))
self.assertIsInstance(obj, Structure)
obj = loadfn(os.path.join(test_dir, "POSCAR"))
self.assertIsInstance(obj, Structure)
obj = loadfn(os.path.join(test_dir, "LiFePO4.vasp"))
self.assertIsInstance(obj, Structure)
obj = loadfn(os.path.join(test_dir, "vasprun.xml"))
self.assertIsInstance(obj, Vasprun)
if __name__ == "__main__":
unittest.main()
| 31.473684
| 86
| 0.618729
|
b49319025df18d07f9b6b31ca9b68fefc2004be3
| 1,921
|
py
|
Python
|
CloudBackup/utils.py
|
520github/CloudBackup
|
ec4a48f1ba438dbaf45d518c5ae0f192b6e7aa96
|
[
"Apache-2.0"
] | 9
|
2015-08-23T09:08:14.000Z
|
2019-04-29T02:08:11.000Z
|
CloudBackup/utils.py
|
chineking/CloudBackup
|
ec4a48f1ba438dbaf45d518c5ae0f192b6e7aa96
|
[
"Apache-2.0"
] | null | null | null |
CloudBackup/utils.py
|
chineking/CloudBackup
|
ec4a48f1ba438dbaf45d518c5ae0f192b6e7aa96
|
[
"Apache-2.0"
] | 5
|
2016-07-19T03:38:10.000Z
|
2017-12-06T21:13:42.000Z
|
#!/usr/bin/env python
#coding=utf-8
'''
Copyright (c) 2012 chine <qin@qinxuye.me>
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Created on 2012-5-1
@author: Chine
'''
__author__ = "Chine King"
import os
import sys
import platform
import subprocess
from CloudBackup.test.settings import EXE_COMPILE
def join_path(*path):
return '/'.join([p.strip('/') for p in path])
def join_local_path(*path):
return os.path.join(*(p.replace('/', os.sep) for p in path))
def get_sys_encoding():
return sys.getfilesystemencoding()
def is_windows():
return platform.system() is 'Windows'
def win_hide_file(log_file):
if isinstance(log_file, str): log_file = log_file.decode('utf-8')
if is_windows() and os.path.exists(log_file):
try:
subprocess.call('attrib +h %s' % log_file.encode('gbk'), shell=True)
except UnicodeEncodeError:
subprocess.call('attrib +h %s' % log_file.encode('utf-8'), shell=True)
get_root_path = lambda: os.path.dirname(__file__)
def get_info_path():
if is_windows() and EXE_COMPILE:
import win32api
exe_name = win32api.GetModuleFileName((win32api.GetModuleHandle(None)))
dirname = os.path.dirname(exe_name)
return os.path.join(dirname, '.info')
else:
return os.path.join(get_root_path(), '.info')
def ensure_folder_exsits(dirname):
if not os.path.exists(dirname):
os.makedirs(dirname)
| 29.106061
| 82
| 0.704321
|
c8ea3272ace7d8f099460af09d5a19a8dbd84349
| 10,548
|
py
|
Python
|
softgym/envs/flex_env.py
|
ipab-rad/softgym
|
eeee770d8720c2cebaa9c5f72408b3340b07d367
|
[
"BSD-3-Clause"
] | 147
|
2020-11-12T16:48:55.000Z
|
2022-03-29T02:21:13.000Z
|
softgym/envs/flex_env.py
|
ipab-rad/softgym
|
eeee770d8720c2cebaa9c5f72408b3340b07d367
|
[
"BSD-3-Clause"
] | 28
|
2020-11-20T23:09:58.000Z
|
2022-03-31T14:51:16.000Z
|
softgym/envs/flex_env.py
|
ipab-rad/softgym
|
eeee770d8720c2cebaa9c5f72408b3340b07d367
|
[
"BSD-3-Clause"
] | 29
|
2020-11-12T06:25:19.000Z
|
2022-03-28T14:10:55.000Z
|
import os
import copy
from gym import error
import numpy as np
import gym
from softgym.utils.visualization import save_numpy_as_gif
import cv2
import os.path as osp
import pickle
try:
import pyflex
except ImportError as e:
raise error.DependencyNotInstalled("{}. (You need to first compile the python binding)".format(e))
class FlexEnv(gym.Env):
def __init__(self,
device_id=-1,
headless=False,
render=True,
horizon=100,
camera_width=720,
camera_height=720,
num_variations=1,
action_repeat=8,
camera_name='default_camera',
deterministic=True,
use_cached_states=True,
save_cached_states=True, **kwargs):
self.camera_params, self.camera_width, self.camera_height, self.camera_name = {}, camera_width, camera_height, camera_name
pyflex.init(headless, render, camera_width, camera_height)
self.record_video, self.video_path, self.video_name = False, None, None
self.metadata = {'render.modes': ['human', 'rgb_array']}
if device_id == -1 and 'gpu_id' in os.environ:
device_id = int(os.environ['gpu_id'])
self.device_id = device_id
self.horizon = horizon
self.time_step = 0
self.action_repeat = action_repeat
self.recording = False
self.prev_reward = None
self.deterministic = deterministic
self.use_cached_states = use_cached_states
self.save_cached_states = save_cached_states
self.current_config = self.get_default_config()
self.current_config_id = None
self.cached_configs, self.cached_init_states = None, None
self.num_variations = num_variations
self.dim_position = 4
self.dim_velocity = 3
self.dim_shape_state = 14
self.particle_num = 0
self.eval_flag = False
# version 1 does not support robot, while version 2 does.
pyflex_root = os.environ['PYFLEXROOT']
if 'Robotics' in pyflex_root:
self.version = 2
else:
self.version = 1
def get_cached_configs_and_states(self, cached_states_path, num_variations):
"""
If the path exists, load from it. Should be a list of (config, states)
:param cached_states_path:
:return:
"""
if self.cached_configs is not None and self.cached_init_states is not None and len(self.cached_configs) == num_variations:
return self.cached_configs, self.cached_init_states
if not cached_states_path.startswith('/'):
cur_dir = osp.dirname(osp.abspath(__file__))
cached_states_path = osp.join(cur_dir, '../cached_initial_states', cached_states_path)
if self.use_cached_states and osp.exists(cached_states_path):
# Load from cached file
with open(cached_states_path, "rb") as handle:
self.cached_configs, self.cached_init_states = pickle.load(handle)
print('{} config and state pairs loaded from {}'.format(len(self.cached_init_states), cached_states_path))
if len(self.cached_configs) == num_variations:
return self.cached_configs, self.cached_init_states
self.cached_configs, self.cached_init_states = self.generate_env_variation(num_variations)
if self.save_cached_states:
with open(cached_states_path, 'wb') as handle:
pickle.dump((self.cached_configs, self.cached_init_states), handle, protocol=pickle.HIGHEST_PROTOCOL)
print('{} config and state pairs generated and saved to {}'.format(len(self.cached_init_states), cached_states_path))
return self.cached_configs, self.cached_init_states
def get_current_config(self):
return self.current_config
def update_camera(self, camera_name, camera_param=None):
"""
:param camera_name: The camera_name to switch to
:param camera_param: None if only switching cameras. Otherwise, should be a dictionary
:return:
"""
if camera_param is not None:
self.camera_params[camera_name] = camera_param
else:
camera_param = self.camera_params[camera_name]
pyflex.set_camera_params(
np.array([*camera_param['pos'], *camera_param['angle'], camera_param['width'], camera_param['height']]))
def get_state(self):
pos = pyflex.get_positions()
vel = pyflex.get_velocities()
shape_pos = pyflex.get_shape_states()
phase = pyflex.get_phases()
camera_params = copy.deepcopy(self.camera_params)
return {'particle_pos': pos, 'particle_vel': vel, 'shape_pos': shape_pos, 'phase': phase, 'camera_params': camera_params,
'config_id': self.current_config_id}
def set_state(self, state_dict):
pyflex.set_positions(state_dict['particle_pos'])
pyflex.set_velocities(state_dict['particle_vel'])
pyflex.set_shape_states(state_dict['shape_pos'])
pyflex.set_phases(state_dict['phase'])
self.camera_params = copy.deepcopy(state_dict['camera_params'])
self.update_camera(self.camera_name)
def close(self):
pyflex.clean()
def get_colors(self):
'''
Overload the group parameters as colors also
'''
groups = pyflex.get_groups()
return groups
def set_colors(self, colors):
pyflex.set_groups(colors)
def start_record(self):
self.video_frames = []
self.recording = True
def end_record(self, video_path=None, **kwargs):
if not self.recording:
print('function end_record: Error! Not recording video')
self.recording = False
if video_path is not None:
save_numpy_as_gif(np.array(self.video_frames), video_path, **kwargs)
del self.video_frames
def reset(self, config=None, initial_state=None, config_id=None):
if config is None:
if config_id is None:
if self.eval_flag:
eval_beg = int(0.8 * len(self.cached_configs))
config_id = np.random.randint(low=eval_beg, high=len(self.cached_configs)) if not self.deterministic else eval_beg
else:
train_high = int(0.8 * len(self.cached_configs))
config_id = np.random.randint(low=0, high=max(train_high, 1)) if not self.deterministic else 0
self.current_config = self.cached_configs[config_id]
self.current_config_id = config_id
self.set_scene(self.cached_configs[config_id], self.cached_init_states[config_id])
else:
self.current_config = config
self.set_scene(config, initial_state)
self.particle_num = pyflex.get_n_particles()
self.prev_reward = 0.
self.time_step = 0
obs = self._reset()
if self.recording:
self.video_frames.append(self.render(mode='rgb_array'))
return obs
def step(self, action, record_continuous_video=False, img_size=None):
""" If record_continuous_video is set to True, will record an image for each sub-step"""
frames = []
for i in range(self.action_repeat):
self._step(action)
if record_continuous_video and i % 2 == 0: # No need to record each step
frames.append(self.get_image(img_size, img_size))
obs = self._get_obs()
reward = self.compute_reward(action, obs, set_prev_reward=True)
info = self._get_info()
if self.recording:
self.video_frames.append(self.render(mode='rgb_array'))
self.time_step += 1
done = False
if self.time_step >= self.horizon:
done = True
if record_continuous_video:
info['flex_env_recorded_frames'] = frames
return obs, reward, done, info
def initialize_camera(self):
"""
This function sets the postion and orientation of the camera
camera_pos: np.ndarray (3x1). (x,y,z) coordinate of the camera
camera_angle: np.ndarray (3x1). (x,y,z) angle of the camera (in degree).
Note: to set camera, you need
1) implement this function in your environement, set value of self.camera_pos and self.camera_angle.
2) add the self.camera_pos and self.camera_angle to your scene parameters,
and pass it when initializing your scene.
3) implement the CenterCamera function in your scene.h file.
Pls see a sample usage in pour_water.py and softgym_PourWater.h
if you do not want to set the camera, you can just not implement CenterCamera in your scene.h file,
and pass no camera params to your scene.
"""
raise NotImplementedError
def render(self, mode='rgb_array'):
if mode == 'rgb_array':
img = pyflex.render()
width, height = self.camera_params['default_camera']['width'], self.camera_params['default_camera']['height']
img = img.reshape(height, width, 4)[::-1, :, :3] # Need to reverse the height dimension
return img
elif mode == 'human':
raise NotImplementedError
def get_image(self, width=720, height=720):
""" use pyflex.render to get a rendered image. """
img = self.render(mode='rgb_array')
img = img.astype(np.uint8)
if width != img.shape[0] or height != img.shape[1]:
img = cv2.resize(img, (width, height))
return img
def set_scene(self, config, state=None):
""" Set up the flex scene """
raise NotImplementedError
def get_default_config(self):
""" Generate the default config of the environment scenes"""
raise NotImplementedError
def generate_env_variation(self, num_variations, **kwargs):
"""
Generate a list of configs and states
:return:
"""
raise NotImplementedError
def compute_reward(self, action=None, obs=None, set_prev_reward=False):
""" set_prev_reward is used for calculate delta rewards"""
raise NotImplementedError
def _get_obs(self):
raise NotImplementedError
def _get_info(self):
raise NotImplementedError
def _reset(self):
raise NotImplementedError
def _step(self, action):
raise NotImplementedError
def _seed(self):
pass
| 39.505618
| 134
| 0.639173
|
fd690743d6cf0b6844287fe92101ded8d030480a
| 2,486
|
py
|
Python
|
Accuracy.py
|
ChrisZeThird/Image-Recognition-without-using-Neural-Network
|
305b78b23cd1af2f60384180b1a0d9323e40c427
|
[
"Apache-2.0"
] | 1
|
2021-09-14T17:19:38.000Z
|
2021-09-14T17:19:38.000Z
|
Accuracy.py
|
ChrisZeThird/Image-Recognition-without-using-Neural-Network
|
305b78b23cd1af2f60384180b1a0d9323e40c427
|
[
"Apache-2.0"
] | null | null | null |
Accuracy.py
|
ChrisZeThird/Image-Recognition-without-using-Neural-Network
|
305b78b23cd1af2f60384180b1a0d9323e40c427
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Tue Sep 14 15:25:24 2021
@author: ChrisZeThird
"""
"""Separated file, meant to calculate the accuracy of the PictureRecognition programm, for different values of:
- K : the size of the batch
- delta : the precision
The goal is to plot thanks to matplotlib, the evolution of the accuracy depending on K and delta, in order to maximise it."""
import matplotlib.pyplot as plt
import PictureRecognition as pr
import Image_Recognition_MNIST as irm
"""Accuracy calculation"""
def accuracy(x,y,K,delta):
"""Input -> x : list of numpy array, contains the pictures
y : numpy array, contains the labels
K : integer, gives the size of the batch studied
delta : flot, precision given by the user, with delta in [0,1]
Output -> float, gives the accuracy of the programm"""
R = pr.Recognition(x, y, 28, 28, K, delta)
result = [0]*K
for k in range(K):
p = R.prediction(x[k])
if p == y[k,0]:
result[k] = 1
return sum(result)/K
"""Variable call"""
x = irm.x
y = irm.y
"""PLotting of the different accuracy"""
delta_list = [0.70, 0.80, 0.90] #list of different threshold values
K_list = [100, 200, 500, 1000] #list of different size of batches
acc_list100 = []
acc_list200 = []
acc_list500 = []
acc_list1000 = []
K0 = 100
K1 = 200
K2 = 500
K3 = 1000
for n in range(3):
delta0 = delta_list[n]
a0 = accuracy(x, y, K0, delta0)
a1 = accuracy(x, y, K1, delta0)
a2 = accuracy(x, y, K2, delta0)
a3 = accuracy(x, y, K3, delta0)
acc_list100.append(a0)
acc_list200.append(a1)
acc_list500.append(a2)
acc_list1000.append(a3)
#setting plot
fig = plt.figure(figsize=(16,9))
ax1 = fig.add_subplot(2, 2, 1)
ax2 = fig.add_subplot(2, 2, 2)
ax3 = fig.add_subplot(2, 2, 3)
ax4 = fig.add_subplot(2, 2, 4)
ax1.set_ylabel('Accuracy', fontsize=9)
ax1.set_xlabel('Threshold', labelpad = 9)
ax1.bar(delta_list,acc_list1000)
ax2.set_ylabel('Accuracy', fontsize=9)
ax2.set_xlabel('Threshold', labelpad = 9)
ax2.plot(delta_list,acc_list200)
ax3.set_ylabel('Accuracy', fontsize=9)
ax3.set_xlabel('Threshold', labelpad = 9)
ax3.plot(delta_list,acc_list500)
ax4.set_ylabel('Accuracy', fontsize=9)
ax4.set_xlabel('Threshold', labelpad = 9)
ax4.plot(delta_list,acc_list1000)
plt.show()
| 25.628866
| 129
| 0.628721
|
90889b450d7bf8d6c7ebe763ef2667c8c26640b0
| 8,821
|
py
|
Python
|
intro-ansible/venv3/lib/python3.8/site-packages/ansible_collections/fortinet/fortimanager/plugins/modules/fmgr_system_replacemsggroup_nntp.py
|
Stienvdh/statrick
|
7b092fc42171e226718a70a285a4b323f2f395ad
|
[
"MIT"
] | null | null | null |
intro-ansible/venv3/lib/python3.8/site-packages/ansible_collections/fortinet/fortimanager/plugins/modules/fmgr_system_replacemsggroup_nntp.py
|
Stienvdh/statrick
|
7b092fc42171e226718a70a285a4b323f2f395ad
|
[
"MIT"
] | null | null | null |
intro-ansible/venv3/lib/python3.8/site-packages/ansible_collections/fortinet/fortimanager/plugins/modules/fmgr_system_replacemsggroup_nntp.py
|
Stienvdh/statrick
|
7b092fc42171e226718a70a285a4b323f2f395ad
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python
from __future__ import absolute_import, division, print_function
# Copyright 2019-2020 Fortinet, Inc.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
__metaclass__ = type
ANSIBLE_METADATA = {'status': ['preview'],
'supported_by': 'community',
'metadata_version': '1.1'}
DOCUMENTATION = '''
---
module: fmgr_system_replacemsggroup_nntp
short_description: Replacement message table entries.
description:
- This module is able to configure a FortiManager device.
- Examples include all parameters and values which need to be adjusted to data sources before usage.
version_added: "2.10"
author:
- Link Zheng (@chillancezen)
- Jie Xue (@JieX19)
- Frank Shen (@fshen01)
- Hongbin Lu (@fgtdev-hblu)
notes:
- Running in workspace locking mode is supported in this FortiManager module, the top
level parameters workspace_locking_adom and workspace_locking_timeout help do the work.
- To create or update an object, use state present directive.
- To delete an object, use state absent directive.
- Normally, running one module can fail when a non-zero rc is returned. you can also override
the conditions to fail or succeed with parameters rc_failed and rc_succeeded
options:
bypass_validation:
description: only set to True when module schema diffs with FortiManager API structure, module continues to execute without validating parameters
required: false
type: bool
default: false
workspace_locking_adom:
description: the adom to lock for FortiManager running in workspace mode, the value can be global and others including root
required: false
type: str
workspace_locking_timeout:
description: the maximum time in seconds to wait for other user to release the workspace lock
required: false
type: int
default: 300
state:
description: the directive to create, update or delete an object
type: str
required: true
choices:
- present
- absent
rc_succeeded:
description: the rc codes list with which the conditions to succeed will be overriden
type: list
required: false
rc_failed:
description: the rc codes list with which the conditions to fail will be overriden
type: list
required: false
adom:
description: the parameter (adom) in requested url
type: str
required: true
replacemsg-group:
description: the parameter (replacemsg-group) in requested url
type: str
required: true
system_replacemsggroup_nntp:
description: the top level parameters set
required: false
type: dict
suboptions:
buffer:
type: str
description: 'Message string.'
format:
type: str
description: 'Format flag.'
choices:
- 'none'
- 'text'
- 'html'
- 'wml'
header:
type: str
description: 'Header flag.'
choices:
- 'none'
- 'http'
- '8bit'
msg-type:
type: str
description: 'Message type.'
'''
EXAMPLES = '''
- hosts: fortimanager-inventory
collections:
- fortinet.fortimanager
connection: httpapi
vars:
ansible_httpapi_use_ssl: True
ansible_httpapi_validate_certs: False
ansible_httpapi_port: 443
tasks:
- name: Replacement message table entries.
fmgr_system_replacemsggroup_nntp:
bypass_validation: False
workspace_locking_adom: <value in [global, custom adom including root]>
workspace_locking_timeout: 300
rc_succeeded: [0, -2, -3, ...]
rc_failed: [-2, -3, ...]
adom: <your own value>
replacemsg-group: <your own value>
state: <value in [present, absent]>
system_replacemsggroup_nntp:
buffer: <value of string>
format: <value in [none, text, html, ...]>
header: <value in [none, http, 8bit]>
msg-type: <value of string>
'''
RETURN = '''
request_url:
description: The full url requested
returned: always
type: str
sample: /sys/login/user
response_code:
description: The status of api request
returned: always
type: int
sample: 0
response_message:
description: The descriptive message of the api response
type: str
returned: always
sample: OK.
'''
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils.connection import Connection
from ansible_collections.fortinet.fortimanager.plugins.module_utils.napi import NAPIManager
from ansible_collections.fortinet.fortimanager.plugins.module_utils.napi import check_galaxy_version
from ansible_collections.fortinet.fortimanager.plugins.module_utils.napi import check_parameter_bypass
def main():
jrpc_urls = [
'/pm/config/adom/{adom}/obj/system/replacemsg-group/{replacemsg-group}/nntp',
'/pm/config/global/obj/system/replacemsg-group/{replacemsg-group}/nntp'
]
perobject_jrpc_urls = [
'/pm/config/adom/{adom}/obj/system/replacemsg-group/{replacemsg-group}/nntp/{nntp}',
'/pm/config/global/obj/system/replacemsg-group/{replacemsg-group}/nntp/{nntp}'
]
url_params = ['adom', 'replacemsg-group']
module_primary_key = 'msg-type'
module_arg_spec = {
'bypass_validation': {
'type': 'bool',
'required': False,
'default': False
},
'workspace_locking_adom': {
'type': 'str',
'required': False
},
'workspace_locking_timeout': {
'type': 'int',
'required': False,
'default': 300
},
'rc_succeeded': {
'required': False,
'type': 'list'
},
'rc_failed': {
'required': False,
'type': 'list'
},
'state': {
'type': 'str',
'required': True,
'choices': [
'present',
'absent'
]
},
'adom': {
'required': True,
'type': 'str'
},
'replacemsg-group': {
'required': True,
'type': 'str'
},
'system_replacemsggroup_nntp': {
'required': False,
'type': 'dict',
'options': {
'buffer': {
'required': False,
'type': 'str'
},
'format': {
'required': False,
'choices': [
'none',
'text',
'html',
'wml'
],
'type': 'str'
},
'header': {
'required': False,
'choices': [
'none',
'http',
'8bit'
],
'type': 'str'
},
'msg-type': {
'required': True,
'type': 'str'
}
}
}
}
params_validation_blob = []
check_galaxy_version(module_arg_spec)
module = AnsibleModule(argument_spec=check_parameter_bypass(module_arg_spec, 'system_replacemsggroup_nntp'),
supports_check_mode=False)
fmgr = None
if module._socket_path:
connection = Connection(module._socket_path)
fmgr = NAPIManager(jrpc_urls, perobject_jrpc_urls, module_primary_key, url_params, module, connection, top_level_schema_name='data')
fmgr.validate_parameters(params_validation_blob)
fmgr.process_curd()
else:
module.fail_json(msg='MUST RUN IN HTTPAPI MODE')
module.exit_json(meta=module.params)
if __name__ == '__main__':
main()
| 32.430147
| 153
| 0.578052
|
de7d5f726ff7202c0a52af62d0fa46f24ed034ca
| 4,644
|
py
|
Python
|
src/faro/proto/proto_types.py
|
amanvell/faro
|
2c4e5b86406937e1dd3fa9f339cfbca2325d98d6
|
[
"MIT"
] | null | null | null |
src/faro/proto/proto_types.py
|
amanvell/faro
|
2c4e5b86406937e1dd3fa9f339cfbca2325d98d6
|
[
"MIT"
] | null | null | null |
src/faro/proto/proto_types.py
|
amanvell/faro
|
2c4e5b86406937e1dd3fa9f339cfbca2325d98d6
|
[
"MIT"
] | null | null | null |
'''
MIT License
Copyright 2019 Oak Ridge National Laboratory
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Created on Jul 26, 2018
@author: bolme
'''
import numpy as np
import pyvision as pv
import faro.proto.geometry_pb2 as geometry
import faro.proto.image_pb2 as image
import faro.proto.face_service_pb2 as fsd
def image_np2proto(im):
'''Convert a numpy array to a protobuf format.'''
#if isinstance(im,pv.Image):
# im = im.asOpenCV2()[:,:,::-1] # Convert bgr to rgb
#im = np.array(im,dtype=np.uint8)
#print('dtype',im.dtype,im.shape,im)
assert im.dtype == np.uint8 # Currently only uint8 supported
result = image.Image()
result.width = im.shape[1]
result.height = im.shape[0]
if len(im.shape) > 2:
result.channels = im.shape[2]
else:
result.channels = 1
result.type = image.Image.UINT8
result.data = im.tostring()
return result
def image_pv2proto(im):
'''Convert a numpy array to a protobuf format.'''
assert isinstance(im,pv.Image)
im = im.asOpenCV2()[:,:,::-1] # Convert bgr to rgb
assert im.dtype == np.uint8 # Currently only uint8 supported
result = image.Image()
result.width = im.shape[1]
result.height = im.shape[0]
result.channels = im.shape[2]
result.type = image.Image.UINT8
result.data = im.tostring()
return result
def image_proto2np(pb_data):
'''Convert a protobuf image to a numpy array.'''
shape = pb_data.height,pb_data.width,pb_data.channels
assert pb_data.type == image.Image.UINT8 # Currently only uint8 supported
data = np.fromstring(pb_data.data,dtype=np.uint8)
data.shape = shape
return data
def image_proto2pv(pb_data):
'''Convert a protobuf image to a numpy array.'''
shape = pb_data.height,pb_data.width,pb_data.channels
assert pb_data.type == image.Image.UINT8 # Currently only uint8 supported
data = np.fromstring(pb_data.data,dtype=np.uint8)
data.shape = shape
if shape[2] == 3:
data = pv.Image(data[:,:,::-1]) # convert rgb to bgr
elif shape[2] == 1:
data = pv.Image(1.0*data[:,:,0].T) # convert rgb to bgr
else:
raise ValueError("Unhandled image format. shape=%s type=%s"%(shape,data.dtype))
return data
def detection_val2proto(score=-1000000,x=0,y=0,width=0,height=0):
det = fsd.FaceDetection()
det.score = score
det.location.x = x
det.location.y = y
det.location.width = width
det.location.height = height
return det
def rect_val2proto(x=0,y=0,width=0,height=0):
'''
Examples:
createRect(x,y,width,height)
'''
location = geometry.Rect()
location.x = x
location.y = y
location.width = width
location.height = height
return location
def rect_proto2pv(proto_rect):
return pv.Rect(proto_rect.x, proto_rect.y, proto_rect.width, proto_rect.height)
def vector_np2proto(vec):
protovec = geometry.Vector()
assert len(vec.shape) == 1
protovec.data.extend(vec)
return protovec
def vector_proto2np(protovec):
vec = np.array(protovec.data,dtype=np.float32)
return vec
def matrix_np2proto(mat):
result = geometry.Matrix()
for row in mat:
result.rows.add().CopyFrom(vector_np2proto(row))
return result
#protovec = geometry.Vector()
#assert len(vec.shape) == 1
#protovec.length=vec.shape[0]
#protovec.data.extend(vec)
#return protovec
def matrix_proto2np(protomat):
mat = []
for row in protomat.rows:
vec = vector_proto2np(row)
mat.append(vec)
mat = np.array(mat,dtype=np.float32)
return mat
| 30.96
| 88
| 0.687123
|
1050627f9c9c549b5d570ecb31c9941c2a9a19f1
| 4,062
|
py
|
Python
|
tests/test_UniformMultiLayerLeverDrive2d_historic.py
|
tdegeus/FrictionQPotGooseFEM
|
094d3dbe3a458b56203e5151157b26ca5bb6b497
|
[
"MIT"
] | null | null | null |
tests/test_UniformMultiLayerLeverDrive2d_historic.py
|
tdegeus/FrictionQPotGooseFEM
|
094d3dbe3a458b56203e5151157b26ca5bb6b497
|
[
"MIT"
] | null | null | null |
tests/test_UniformMultiLayerLeverDrive2d_historic.py
|
tdegeus/FrictionQPotGooseFEM
|
094d3dbe3a458b56203e5151157b26ca5bb6b497
|
[
"MIT"
] | null | null | null |
import os
import unittest
import FrictionQPotFEM
import GMatElastoPlasticQPot.Cartesian2d as GMat
import GooseFEM
import h5py
import numpy as np
import prrng
class test_UniformMultiLayerIndividualDrive2d(unittest.TestCase):
"""
Tests
"""
def test_historic(self):
"""
A simple historic run.
Thanks to prrng this test can be run on any platform, but also from any API (Python or C++).
"""
# Define a geometry
N = 3**2
h = np.pi
L = h * float(N)
mesh = GooseFEM.Mesh.Quad4.Regular(N, 11, h)
coor = mesh.coor()
conn = mesh.conn()
dofs = mesh.dofs()
elem = mesh.elementgrid()
height = [1.5 * h, 3.5 * h, 5.5 * h, 7.5 * h, 9.5 * h]
active = [[False, False], [False, False], [True, False], [False, False], [True, False]]
layers = [
elem[:3, :].ravel(),
elem[3, :].ravel(),
elem[4:7, :].ravel(),
elem[7, :].ravel(),
elem[8:, :].ravel(),
]
layers = [np.sort(i) for i in layers]
left = mesh.nodesLeftOpenEdge()
right = mesh.nodesRightOpenEdge()
dofs[left] = dofs[right]
top = mesh.nodesTopEdge()
bottom = mesh.nodesBottomEdge()
np.concatenate((dofs[bottom].ravel(), dofs[top].ravel()))
system = FrictionQPotFEM.UniformMultiLayerLeverDrive2d.System(
coor=coor,
conn=conn,
dofs=dofs,
iip=dofs[mesh.nodesBottomEdge(), :].ravel(),
elem=layers,
node=[np.unique(conn[i, :]) for i in layers],
layer_is_plastic=[False, True, False, True, False],
)
nelas = system.elastic().size
nplas = system.plastic().size
# Parameters
c = 1.0
G = 1.0
K = 10.0 * G
rho = G / c**2.0
qL = 2.0 * np.pi / L
qh = 2.0 * np.pi / h
alpha = np.sqrt(2.0) * qL * c * rho
dt = 1.0 / (c * qh) / 10.0
generators = prrng.pcg32_array(np.arange(nplas), np.zeros(nplas))
epsy = np.hstack((generators.random([1]), generators.weibull([1000], k=2.0)))
epsy *= 1.0e-3
epsy += 1.0e-5
epsy = np.cumsum(epsy, 1)
# Initialise system
system.setMassMatrix(rho * np.ones(mesh.nelem()))
system.setDampingMatrix(alpha * np.ones(mesh.nelem()))
system.setElastic(K * np.ones(nelas), G * np.ones(nelas))
system.setPlastic(K * np.ones(nplas), G * np.ones(nplas), epsy)
system.setDt(dt)
system.layerSetTargetActive(active)
system.layerSetDriveStiffness(1e-3)
system.setLeverProperties(12 * h, height)
# Drive
system.initEventDriven(0.1, active)
ninc = 20
collect_Eps = np.zeros(ninc)
collect_Sig = np.zeros(ninc)
collect_Sig_plastic = np.zeros(ninc)
quad = system.quad()
dV = quad.AsTensor(2, quad.dV())
for inc in range(ninc):
if inc % 2 == 0:
system.eventDrivenStep(deps=1e-5, kick=True, iterative=True, yield_element=False)
system.minimise()
else:
system.eventDrivenStep(deps=1e-5, kick=False, iterative=True, yield_element=False)
Epsbar = np.average(system.Eps(), weights=dV, axis=(0, 1))
Sigbar = np.average(system.Sig(), weights=dV, axis=(0, 1))
collect_Eps[inc] = GMat.Epsd(Epsbar)
collect_Sig[inc] = GMat.Sigd(Sigbar)
collect_Sig_plastic[inc] = GMat.Sigd(np.mean(system.plastic_Sig(), axis=(0, 1)))
with h5py.File(os.path.splitext(__file__)[0] + ".h5") as file:
self.assertTrue(np.allclose(collect_Eps, file["Eps"][...]))
self.assertTrue(np.allclose(collect_Sig, file["Sig"][...]))
self.assertTrue(np.allclose(collect_Sig_plastic, file["Sig_plastic"][...]))
self.assertTrue(np.allclose(system.u(), file["u_last"][...]))
if __name__ == "__main__":
unittest.main()
| 31.007634
| 100
| 0.552437
|
f816dbcf18adf40376ffcce2541c413d6d5d3ddc
| 1,717
|
py
|
Python
|
clipl/scripts/csv2root.py
|
thomas-mueller/clipl
|
4c8c61dd4a09fee6ad2ec65f3baa6854cf9cce69
|
[
"MIT"
] | null | null | null |
clipl/scripts/csv2root.py
|
thomas-mueller/clipl
|
4c8c61dd4a09fee6ad2ec65f3baa6854cf9cce69
|
[
"MIT"
] | null | null | null |
clipl/scripts/csv2root.py
|
thomas-mueller/clipl
|
4c8c61dd4a09fee6ad2ec65f3baa6854cf9cce69
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import logging
import clipl.utility.logger as logger
log = logging.getLogger(__name__)
import argparse
import numpy
import os
import ROOT
ROOT.gROOT.SetBatch(True)
ROOT.PyConfig.IgnoreCommandLineOptions = True
ROOT.gErrorIgnoreLevel = ROOT.kError
import clipl.utility.tfilecontextmanager as tfilecontextmanager
import clipl.utility.tools as tools
def csv2root(args):
csv_filename = args[0]
variable_list = args[1]
root_filename = os.path.splitext(csv_filename)[0]+".root"
with tfilecontextmanager.TFileContextManager(root_filename, "RECREATE") as root_file:
tree = ROOT.TTree("tree", csv_filename)
tree.ReadFile(csv_filename, variable_list)
tree.Write(tree.GetName())
log.info("Converted {csv} to {root}:tree.".format(csv=csv_filename, root=root_filename))
def main():
parser = argparse.ArgumentParser(description="Convert CSV files to ROOT files.",
parents=[logger.loggingParser])
parser.add_argument("files", nargs="+",
help="CSV Files.")
parser.add_argument("--variable-lists", nargs="+", default=[""],
help="Variable lists (in case the CSV has no header), e.g. var1:var2:... [Default: %(default)s]")
parser.add_argument("-n", "--n-processes", type=int, default=1,
help="Number of (parallel) processes. [Default: %(default)s]")
args = parser.parse_args()
logger.initLogger(args)
if len(args.variable_lists) == 1:
args.variable_lists = args.variable_lists * len(args.files)
tools.parallelize(csv2root, zip(args.files, args.variable_lists), n_processes=args.n_processes, description="Converting")
if __name__ == "__main__":
main()
| 31.218182
| 122
| 0.704718
|
97fd67068c265539675a46166cee4a9aff92d7c7
| 7,117
|
py
|
Python
|
modules/tools/open_space_visualization/auto_param_tuning.py
|
seeclong/apollo
|
99c8afb5ebcae2a3c9359a156a957ff03944b27b
|
[
"Apache-2.0"
] | 27
|
2019-04-06T02:27:14.000Z
|
2021-11-27T13:47:06.000Z
|
modules/tools/open_space_visualization/auto_param_tuning.py
|
seeclong/apollo
|
99c8afb5ebcae2a3c9359a156a957ff03944b27b
|
[
"Apache-2.0"
] | 7
|
2021-03-10T18:14:25.000Z
|
2022-02-27T04:46:46.000Z
|
modules/tools/open_space_visualization/auto_param_tuning.py
|
seeclong/apollo
|
99c8afb5ebcae2a3c9359a156a957ff03944b27b
|
[
"Apache-2.0"
] | 38
|
2019-04-15T10:58:37.000Z
|
2022-01-27T08:52:39.000Z
|
#!/usr/bin/env python
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import random
import argparse
from google.protobuf.internal import decoder
from google.protobuf.internal import encoder
import hybrid_a_star_visualizer
import distance_approach_visualizer
import common.proto_utils as proto_utils
from modules.planning.proto import planner_open_space_config_pb2
random.seed(99999)
rand_num = 1000
original_file_path = "/apollo/modules/planning/conf/planner_open_space_config.pb.txt"
optimal_file_path = "/apollo/modules/planning/conf/optimal_planner_open_space_config_-8_4.pb.txt"
# tunning_object = "coarse_trajectory"
tunning_object = "smooth_trajectory"
def load_open_space_protobuf(filename):
open_space_params = planner_open_space_config_pb2.PlannerOpenSpaceConfig()
proto_utils.get_pb_from_text_file(filename, open_space_params)
return open_space_params
def GetParamsForTunning(tunning_object):
param_names_and_range = []
if tunning_object == "coarse_trajectory":
param_names_and_range.append(
("warm_start_config.traj_forward_penalty", 2.0))
param_names_and_range.append(
("warm_start_config.traj_back_penalty", 2.0))
param_names_and_range.append(
("warm_start_config.traj_gear_switch_penalty", 2.0))
param_names_and_range.append(
("warm_start_config.traj_steer_penalty", 3.0))
param_names_and_range.append(
("warm_start_config.traj_steer_change_penalty", 2.0))
elif tunning_object == "smooth_trajectory":
param_names_and_range.append(
("distance_approach_config.weight_steer", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_a", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_steer_rate", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_a_rate", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_x", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_y", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_phi", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_v", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_steer_stitching", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_a_stitching", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_first_order_time", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_second_order_time", 2.0))
return param_names_and_range
def RandSampling(param_names_and_range, origin_open_space_params):
params_lists = []
for iter in range(0, rand_num):
rand_params = planner_open_space_config_pb2.PlannerOpenSpaceConfig()
rand_params.CopyFrom(origin_open_space_params)
for param in param_names_and_range:
exec("rand_params." +
str(param[0]) + "=random.uniform(max(rand_params." +
str(param[0])
+ " - " + str(param[1]) + ",0.0)"
+ " ,rand_params." + str(param[0]) + " + " + str(param[1]) + ")")
params_lists.append(rand_params)
return params_lists
def TestingParams(params_lists, tunning_object):
key_to_evaluations = {}
for iter in range(0, len(params_lists)):
evaluation = ParamEvaluation(params_lists[iter], tunning_object)
key_to_evaluations[iter] = evaluation
return key_to_evaluations
def ParamEvaluation(params, tunning_object):
proto_utils.write_pb_to_text_file(params, original_file_path)
if tunning_object == "coarse_trajectory":
visualize_flag = False
success, x_out, y_out, phi_out, v_out, a_out, steer_out, planning_time = hybrid_a_star_visualizer.HybridAStarPlan(
visualize_flag)
if not success:
return float('inf')
else:
return planning_time
elif tunning_object == "smooth_trajectory":
visualize_flag = False
success, opt_x_out, opt_y_out, opt_phi_out, opt_v_out, opt_a_out, opt_steer_out, opt_time_out, planning_time = distance_approach_visualizer.SmoothTrajectory(
visualize_flag)
if not success:
return float('inf')
else:
return planning_time
def GetOptimalParams(params_lists, key_to_evaluations):
tmp = []
for key, value in key_to_evaluations.items():
tmptuple = (value, key)
tmp.append(tmptuple)
tmp = sorted(tmp)
optimal_params = params_lists[tmp[0][1]]
optimal_evaluation = tmp[0][0]
return optimal_params, optimal_evaluation
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
"--InputConfig", help="original conf address to be tuned", type=str, default=original_file_path)
parser.add_argument("--OutputConfig", help="tuned conf address",
type=str, default=optimal_file_path)
parser.add_argument("--TunningObject",
help="algorithm to be tuned", type=str, default=tunning_object)
args = parser.parse_args()
original_file_path = args.InputConfig
optimal_file_path = args.OutputConfig
tunning_object = args.TunningObject
param_names_and_range = GetParamsForTunning(tunning_object)
origin_open_space_params = load_open_space_protobuf(original_file_path)
params_lists = RandSampling(
param_names_and_range, origin_open_space_params)
key_to_evaluations = TestingParams(params_lists, tunning_object)
optimal_params, optimal_evaluation = GetOptimalParams(
params_lists, key_to_evaluations)
origin_evaluation = ParamEvaluation(
origin_open_space_params, tunning_object)
print("optimal_evaluation is " + str(optimal_evaluation))
print("origin_evaluation is " + str(origin_evaluation))
improvement_percentage = (
origin_evaluation - optimal_evaluation) / origin_evaluation
print("improvement_percentage is " + str(improvement_percentage))
proto_utils.write_pb_to_text_file(optimal_params, optimal_file_path)
proto_utils.write_pb_to_text_file(
origin_open_space_params, original_file_path)
| 42.616766
| 165
| 0.701138
|
22e994ea03651bba511bb46735cb31fe285bb524
| 7,207
|
py
|
Python
|
judger.py
|
SkyErnest/legal_basis
|
7fc2aaffa54c6bc6fc8713e5755edff9b3d296e4
|
[
"BSD-3-Clause"
] | null | null | null |
judger.py
|
SkyErnest/legal_basis
|
7fc2aaffa54c6bc6fc8713e5755edff9b3d296e4
|
[
"BSD-3-Clause"
] | null | null | null |
judger.py
|
SkyErnest/legal_basis
|
7fc2aaffa54c6bc6fc8713e5755edff9b3d296e4
|
[
"BSD-3-Clause"
] | null | null | null |
from math import log
import os
import json
import numpy as np
class Judger:
# Initialize Judger, with the path of accusation list and law articles list
def __init__(self, accusation_path, law_path):
self.accu_dic = {}
f = open(accusation_path, "r",encoding='utf-8')
self.task1_cnt = 0
for line in f:
self.task1_cnt += 1
self.accu_dic[line[:-1]] = self.task1_cnt
self.law_dic = {}
f = open(law_path, "r",encoding='utf-8')
self.task2_cnt = 0
for line in f:
self.task2_cnt += 1
self.law_dic[int(line[:-1])] = self.task2_cnt
# Format the result generated by the Predictor class
@staticmethod
def format_result(result):
rex = {"accusation": [], "articles": [], "imprisonment": -3}
res_acc = []
for x in result["accusation"]:
if not (x is None):
res_acc.append(int(x))
rex["accusation"] = res_acc
if not (result["imprisonment"] is None):
rex["imprisonment"] = int(result["imprisonment"])
else:
rex["imprisonment"] = -3
res_art = []
for x in result["articles"]:
if not (x is None):
res_art.append(int(x))
rex["articles"] = res_art
return rex
# Gen new results according to the truth and users output
def gen_new_result(self, result, truth, label):
s1 = set(label["accusation"])
s2 = set()
for name in truth["accusation"]:
s2.add(self.accu_dic[name.replace("[", "").replace("]", "")])
for a in range(0, self.task1_cnt):
in1 = (a + 1) in s1
in2 = (a + 1) in s2
if in1:
if in2:
result[0][a]["TP"] += 1
else:
result[0][a]["FP"] += 1
else:
if in2:
result[0][a]["FN"] += 1
else:
result[0][a]["TN"] += 1
s1 = set(label["articles"])
s2 = set()
for name in truth["relevant_articles"]:
s2.add(self.law_dic[name])
for a in range(0, self.task2_cnt):
in1 = (a + 1) in s1
in2 = (a + 1) in s2
if in1:
if in2:
result[1][a]["TP"] += 1
else:
result[1][a]["FP"] += 1
else:
if in2:
result[1][a]["FN"] += 1
else:
result[1][a]["TN"] += 1
result[2]["cnt"] += 1
sc = 0
if truth["term_of_imprisonment"]["death_penalty"]:
if label["imprisonment"] == -2:
sc = 1
elif truth["term_of_imprisonment"]["life_imprisonment"]:
if label["imprisonment"] == -1:
sc = 1
else:
if label["imprisonment"] < 0:
sc = 0
else:
v1 = truth["term_of_imprisonment"]["imprisonment"]
v2 = label["imprisonment"]
v = abs(log(v1 + 1) - log(v2 + 1))
if v <= 0.2:
sc = 1
elif v <= 0.4:
sc = 0.8
elif v <= 0.6:
sc = 0.6
elif v <= 0.8:
sc = 0.4
elif v <= 1.0:
sc = 0.2
else:
sc = 0
sc = sc * 1.0
result[2]["score"] += sc
return result
# Calculate precision, recall and f1 value
# According to https://github.com/dice-group/gerbil/wiki/Precision,-Recall-and-F1-measure
@staticmethod
def get_value(res):
if res["TP"] == 0:
if res["FP"] == 0 and res["FN"] == 0:
precision = 1.0
recall = 1.0
f1 = 1.0
else:
precision = 0.0
recall = 0.0
f1 = 0.0
else:
precision = 1.0 * res["TP"] / (res["TP"] + res["FP"])
recall = 1.0 * res["TP"] / (res["TP"] + res["FN"])
f1 = 2 * precision * recall / (precision + recall)
return precision, recall, f1
# Generate score for the first two subtasks
def gen_score(self, arr):
sumf = 0
y = {"TP": 0, "FP": 0, "FN": 0, "TN": 0}
for x in arr:
p, r, f = self.get_value(x)
sumf += f
for z in x.keys():
y[z] += x[z]
_, __, f_ = self.get_value(y)
return (f_ + sumf * 1.0 / len(arr)) / 2.0
# Generatue all scores
def get_score(self, result):
s1 = self.gen_score(result[0])
s2 = self.gen_score(result[1])
s3 = 1.0 * result[2]["score"] / result[2]["cnt"]
return [s1, s2, s3]
# Test with ground truth path and the user's output path
def test(self, truth_path, output_path):
cnt = 0
result = [[], [], {}]
for a in range(0, self.task1_cnt):
result[0].append({"TP": 0, "FP": 0, "TN": 0, "FN": 0})
for a in range(0, self.task2_cnt):
result[1].append({"TP": 0, "FP": 0, "TN": 0, "FN": 0})
result[2] = {"cnt": 0, "score": 0}
inf = open(truth_path, "r",encoding='utf-8')
ouf = open(output_path, "r",encoding='utf-8')
for line in inf:
ground_truth = json.loads(line)["meta"]
user_output = json.loads(ouf.readline())
cnt += 1
result = self.gen_new_result(result, ground_truth, user_output)
return result
if __name__ == '__main__':
J = Judger('accu.txt', 'law.txt')
res = J.test('data_test.json', 'data_test_predict.json')
total_score = 0
for task_idx in range(2):
TP_micro = 0
FP_micro = 0
FN_micro = 0
f1 = []
for class_idx in range(len(res[task_idx])):
if res[task_idx][class_idx]["TP"] == 0:
f1.append(0)
continue
TP_micro += res[task_idx][class_idx]["TP"]
FP_micro += res[task_idx][class_idx]["FP"]
FN_micro += res[task_idx][class_idx]["FN"]
precision = res[task_idx][class_idx]["TP"] * 1.0 / (res[task_idx][class_idx]["TP"] + res[task_idx][class_idx]["FP"])
recall = res[task_idx][class_idx]["TP"] * 1.0 / (res[task_idx][class_idx]["TP"] + res[task_idx][class_idx]["FN"])
f1.append(2 * precision * recall / (precision + recall))
precision_micro = TP_micro * 1.0 / (TP_micro + FP_micro)
recall_micro = TP_micro * 1.0 / (TP_micro + FN_micro)
F1_micro = 2 * precision_micro * recall_micro / (precision_micro + recall_micro)
F1_macro = np.sum(f1) / len(f1)
total_score += 100.0 * (F1_micro + F1_macro)/2
print('task id: {}, F1_micro: {}, F1_macro: {}, final score: {}'.format(task_idx + 1, F1_micro, F1_macro, 100.0 * (F1_micro + F1_macro)/2))
total_score += res[2]['score'] / res[2]['cnt'] * 100
print('task id: 3, score:{}'.format(res[2]['score'] / res[2]['cnt'] * 100))
print('total score:', total_score)
| 33.995283
| 147
| 0.475371
|
9e95c5c83911e24fca27e522db17f04abe6efa75
| 981
|
py
|
Python
|
tests/validation/test_square_client_id_validation.py
|
babenek/CredSweeper
|
4d69ec934b45fd2f68e00b636077e5edfd1ff6ca
|
[
"MIT"
] | 17
|
2021-10-22T00:29:46.000Z
|
2022-03-21T03:05:56.000Z
|
tests/validation/test_square_client_id_validation.py
|
babenek/CredSweeper
|
4d69ec934b45fd2f68e00b636077e5edfd1ff6ca
|
[
"MIT"
] | 29
|
2021-11-05T21:10:51.000Z
|
2022-03-30T10:41:08.000Z
|
tests/validation/test_square_client_id_validation.py
|
babenek/CredSweeper
|
4d69ec934b45fd2f68e00b636077e5edfd1ff6ca
|
[
"MIT"
] | 16
|
2021-11-05T20:39:54.000Z
|
2022-03-11T00:57:32.000Z
|
from os import environ
from typing import List
import pytest
from credsweeper.common.constants import KeyValidationOption
from credsweeper.credentials import LineData
from credsweeper.validations import SquareClientIdValidation
from tests.test_utils.dummy_line_data import get_line_data
@pytest.mark.api_validation
class TestSquareClientIdValidation:
@pytest.fixture
def line_data_list(self) -> List[LineData]:
line_data_list = []
line_data = get_line_data()
line_data.value = "sq0idp-1235567212325-12355672"
line_data_list.append(line_data)
return line_data_list
@pytest.mark.skipif(environ.get("CIRCLE_PROJECT_USERNAME") is not None,
reason="Server blocking requests from CI server")
def test_verify_n(self, line_data_list: pytest.fixture) -> None:
validation_result = SquareClientIdValidation.verify(line_data_list)
assert validation_result is KeyValidationOption.INVALID_KEY
| 35.035714
| 75
| 0.763507
|
d76dd38661bf94014edf6b1833bc964eafb0b52b
| 10,970
|
py
|
Python
|
lexilla/scripts/LexillaData.py
|
xelliott/Notepad3
|
984e637ceae20b085d84e6294b6c63ca9ec78839
|
[
"BSD-3-Clause"
] | null | null | null |
lexilla/scripts/LexillaData.py
|
xelliott/Notepad3
|
984e637ceae20b085d84e6294b6c63ca9ec78839
|
[
"BSD-3-Clause"
] | null | null | null |
lexilla/scripts/LexillaData.py
|
xelliott/Notepad3
|
984e637ceae20b085d84e6294b6c63ca9ec78839
|
[
"BSD-3-Clause"
] | null | null | null |
#!/usr/bin/env python3
# ScintillaData.py - implemented 2013 by Neil Hodgson neilh@scintilla.org
# Released to the public domain.
# Common code used by Scintilla and SciTE for source file regeneration.
# The ScintillaData object exposes information about Scintilla as properties:
# Version properties
# version
# versionDotted
# versionCommad
#
# Date last modified
# dateModified
# yearModified
# mdyModified
# dmyModified
# myModified
#
# Information about lexers and properties defined in lexers
# lexFiles
# sorted list of lexer files
# lexerModules
# sorted list of module names
# lexerProperties
# sorted list of lexer properties
# propertyDocuments
# dictionary of property documentation { name: document string }
# sclexFromName
# dictionary of SCLEX_* IDs { name: SCLEX_ID }
# fileFromSclex
# dictionary of file names { SCLEX_ID: file name }
# This file can be run to see the data it provides.
# Requires Python 3.6 or later
import datetime, pathlib, sys, textwrap
thisPath = pathlib.Path(__file__).resolve()
sys.path.append(str(thisPath.parent.parent.parent / "scintilla" / "scripts"))
import FileGenerator
neutralEncoding = "latin_1"
def FindModules(lexFile):
modules = []
partLine = ""
with lexFile.open(encoding=neutralEncoding) as f:
for l in f.readlines():
l = l.rstrip()
if partLine or l.startswith("LexerModule"):
if ")" in l:
l = partLine + l
l = l.replace("(", " ")
l = l.replace(")", " ")
l = l.replace(",", " ")
parts = l.split()
modules.append([parts[1], parts[2], parts[4][1:-1]])
partLine = ""
else:
partLine = partLine + l
return modules
def FindLexersInXcode(xCodeProject):
lines = FileGenerator.ReadFileAsList(xCodeProject)
uidsOfBuild = {}
markersPBXBuildFile = ["Begin PBXBuildFile section", "", "End PBXBuildFile section"]
for buildLine in lines[FileGenerator.FindSectionInList(lines, markersPBXBuildFile)]:
# Occurs for each file in the build. Find the UIDs used for the file.
#\t\t[0-9A-F]+ /* [a-zA-Z]+.cxx in sources */ = {isa = PBXBuildFile; fileRef = [0-9A-F]+ /* [a-zA-Z]+ */; };
pieces = buildLine.split()
uid1 = pieces[0]
filename = pieces[2].split(".")[0]
uid2 = pieces[12]
uidsOfBuild[filename] = [uid1, uid2]
lexers = {}
markersLexers = ["/* Lexers */ =", "children", ");"]
for lexerLine in lines[FileGenerator.FindSectionInList(lines, markersLexers)]:
#\t\t\t\t[0-9A-F]+ /* [a-zA-Z]+.cxx */,
uid, _, rest = lexerLine.partition("/* ")
uid = uid.strip()
lexer, _, _ = rest.partition(".")
lexers[lexer] = uidsOfBuild[lexer]
return lexers
# Properties that start with lexer. or fold. are automatically found but there are some
# older properties that don't follow this pattern so must be explicitly listed.
knownIrregularProperties = [
"fold",
"styling.within.preprocessor",
"tab.timmy.whinge.level",
"asp.default.language",
"html.tags.case.sensitive",
"ps.level",
"ps.tokenize",
"sql.backslash.escapes",
"nsis.uservars",
"nsis.ignorecase"
]
def FindProperties(lexFile):
properties = {}
with open(lexFile, encoding=neutralEncoding) as f:
for l in f.readlines():
if ("GetProperty" in l or "DefineProperty" in l) and "\"" in l:
l = l.strip()
if not l.startswith("//"): # Drop comments
propertyName = l.split("\"")[1]
if propertyName.lower() == propertyName:
# Only allow lower case property names
if propertyName in knownIrregularProperties or \
propertyName.startswith("fold.") or \
propertyName.startswith("lexer."):
properties[propertyName] = 1
return properties
def FindPropertyDocumentation(lexFile):
documents = {}
with lexFile.open(encoding=neutralEncoding) as f:
name = ""
for l in f.readlines():
l = l.strip()
if "// property " in l:
propertyName = l.split()[2]
if propertyName.lower() == propertyName:
# Only allow lower case property names
name = propertyName
documents[name] = ""
elif "DefineProperty" in l and "\"" in l:
propertyName = l.split("\"")[1]
if propertyName.lower() == propertyName:
# Only allow lower case property names
name = propertyName
documents[name] = ""
elif name:
if l.startswith("//"):
if documents[name]:
documents[name] += " "
documents[name] += l[2:].strip()
elif l.startswith("\""):
l = l[1:].strip()
if l.endswith(";"):
l = l[:-1].strip()
if l.endswith(")"):
l = l[:-1].strip()
if l.endswith("\""):
l = l[:-1]
# Fix escaped double quotes
l = l.replace("\\\"", "\"")
documents[name] += l
else:
name = ""
for name in list(documents.keys()):
if documents[name] == "":
del documents[name]
return documents
def FindCredits(historyFile):
credits = []
stage = 0
with historyFile.open(encoding="utf-8") as f:
for l in f.readlines():
l = l.strip()
if stage == 0 and l == "<table>":
stage = 1
elif stage == 1 and l == "</table>":
stage = 2
if stage == 1 and l.startswith("<td>"):
credit = l[4:-5]
if "<a" in l:
title, a, rest = credit.partition("<a href=")
urlplus, _bracket, end = rest.partition(">")
name = end.split("<")[0]
url = urlplus[1:-1]
credit = title.strip()
if credit:
credit += " "
credit += name + " " + url
credits.append(credit)
return credits
def ciKey(a):
return str(a).lower()
def SortListInsensitive(l):
l.sort(key=ciKey)
class LexillaData:
def __init__(self, scintillaRoot):
# Discover version information
self.version = (scintillaRoot / "version.txt").read_text().strip()
self.versionDotted = self.version[0] + '.' + self.version[1] + '.' + \
self.version[2]
self.versionCommad = self.versionDotted.replace(".", ", ") + ', 0'
with (scintillaRoot / "doc" / "Lexilla.html").open() as f:
self.dateModified = [l for l in f.readlines() if "Date.Modified" in l]\
[0].split('\"')[3]
# 20130602
# Lexilla.html
dtModified = datetime.datetime.strptime(self.dateModified, "%Y%m%d")
self.yearModified = self.dateModified[0:4]
monthModified = dtModified.strftime("%B")
dayModified = "%d" % dtModified.day
self.mdyModified = monthModified + " " + dayModified + " " + self.yearModified
# May 22 2013
# Lexilla.html, SciTE.html
self.dmyModified = dayModified + " " + monthModified + " " + self.yearModified
# 22 May 2013
# LexillaHistory.html -- only first should change
self.myModified = monthModified + " " + self.yearModified
# Find all the lexer source code files
lexFilePaths = list((scintillaRoot / "lexers").glob("Lex*.cxx"))
lexFilePathsEx = list((scintillaRoot / "lexers_x").glob("Lex*.cxx"))
lexFilePaths.extend(lexFilePathsEx)
SortListInsensitive(lexFilePaths)
self.lexFiles = [f.stem for f in lexFilePaths]
self.lexerModules = []
lexerProperties = set()
self.propertyDocuments = {}
self.sclexFromName = {}
self.fileFromSclex = {}
for lexFile in lexFilePaths:
modules = FindModules(lexFile)
for module in modules:
self.sclexFromName[module[2]] = module[1]
self.fileFromSclex[module[1]] = lexFile
self.lexerModules.append(module[0])
for k in FindProperties(lexFile).keys():
lexerProperties.add(k)
documents = FindPropertyDocumentation(lexFile)
for k in documents.keys():
if k not in self.propertyDocuments:
self.propertyDocuments[k] = documents[k]
SortListInsensitive(self.lexerModules)
self.lexerProperties = list(lexerProperties)
SortListInsensitive(self.lexerProperties)
self.lexersXcode = FindLexersInXcode(scintillaRoot /
"src/Lexilla/Lexilla.xcodeproj/project.pbxproj")
self.credits = FindCredits(scintillaRoot / "doc" / "LexillaHistory.html")
def printWrapped(text):
print(textwrap.fill(text, subsequent_indent=" "))
if __name__=="__main__":
sci = LexillaData(pathlib.Path(__file__).resolve().parent.parent)
print("Version %s %s %s" % (sci.version, sci.versionDotted, sci.versionCommad))
print("Date last modified %s %s %s %s %s" % (
sci.dateModified, sci.yearModified, sci.mdyModified, sci.dmyModified, sci.myModified))
printWrapped(str(len(sci.lexFiles)) + " lexer files: " + ", ".join(sci.lexFiles))
printWrapped(str(len(sci.lexerModules)) + " lexer modules: " + ", ".join(sci.lexerModules))
#~ printWrapped(str(len(sci.lexersXcode)) + " Xcode lexer references: " + ", ".join(
#~ [lex+":"+uids[0]+","+uids[1] for lex, uids in sci.lexersXcode.items()]))
print("Lexer name to ID:")
lexNames = sorted(sci.sclexFromName.keys())
for lexName in lexNames:
sclex = sci.sclexFromName[lexName]
fileName = sci.fileFromSclex[sclex].name
print(" " + lexName + " -> " + sclex + " in " + fileName)
printWrapped("Lexer properties: " + ", ".join(sci.lexerProperties))
print("Lexer property documentation:")
documentProperties = list(sci.propertyDocuments.keys())
SortListInsensitive(documentProperties)
for k in documentProperties:
print(" " + k)
print(textwrap.fill(sci.propertyDocuments[k], initial_indent=" ",
subsequent_indent=" "))
print("Credits:")
for c in sci.credits:
sys.stdout.buffer.write(b" " + c.encode("utf-8") + b"\n")
| 39.602888
| 116
| 0.555971
|
31296104b82e438ac3520f0576d7c7cf6af130f8
| 5,017
|
py
|
Python
|
src/fileutil.py
|
militiaonly/spark1707
|
3d4a3945ca2190628ea6a8593d3adadfd1a71dfb
|
[
"MIT"
] | null | null | null |
src/fileutil.py
|
militiaonly/spark1707
|
3d4a3945ca2190628ea6a8593d3adadfd1a71dfb
|
[
"MIT"
] | null | null | null |
src/fileutil.py
|
militiaonly/spark1707
|
3d4a3945ca2190628ea6a8593d3adadfd1a71dfb
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# -*- encoding=utf-8 -*-
########################################
# Copyright (c) 2017 Shanghai Kimstars #
########################################
import os
import json
import logging
import random
import datetime
# wrtnode.__name__
logger = logging.getLogger('wrtnode.' + __name__)
def dt_to_strftime(dt, randomsecond=False):
"""
@brief format datetime to string in '%Y-%m-%d %H:%M:%S.%f'
@param utcdt The utcdt
@return { description_of_the_return_value }
"""
if not isinstance(dt, datetime.datetime):
return None
if randomsecond:
randomsecond = dt.second + random.randint(0, 2)
else:
randomsecond = dt.second
strftime = '%0.4d-%0.2d-%0.2d %0.2d:%0.2d:%0.2d' % (dt.year,
dt.month,
dt.day,
dt.hour,
dt.minute,
randomsecond)
return strftime
def read_json_file(path):
#######################
# read JSON file
#######################
json_string = ""
file_error = False
try:
jfile = open(path, "r")
lines = jfile.readlines()
except IOError as err:
logger.error('read_json_file: ' + str(err))
file_error = True
else:
for line in lines:
json_string = json_string + line.strip()
# allow comma in the last line
json_string = json_string.replace(',}', '}')
finally:
if 'jfile' in locals():
jfile.close()
if file_error:
return None
try:
jsonObject = json.loads(json_string)
except Exception as e:
jsonObject = None
logger.error('read_json_file: ' + str(e))
return jsonObject
def read_txt_file(path):
#######################
# read txt file
# real all lines
#######################
json_string = ""
file_error = False
try:
jfile = open(path, "r")
lines = jfile.read()
except IOError as err:
logger.error('read_txt_file: ' + str(err))
file_error = True
finally:
if 'jfile' in locals():
jfile.close()
if file_error:
return None
else:
return lines
def write_json_file(path, contentOject):
# json_string = json.dumps(contentOject, 'utf-8')
json_string = json.dumps(contentOject, sort_keys=True, indent=4,
ensure_ascii=False)
try:
config_file = open(path, "w")
config_file.write(json_string)
r = True
except IOError as err:
errorStr = 'File Error:' + str(err)
logger.error(errorStr)
r = False
finally:
if 'config_file' in locals():
config_file.close()
return r
def check_key_types(jsonObject, key, types):
"""
@brief check the dict key and type
@param jsonObject The json object
@param key The key
@param types tuple of types
@return True/False
"""
if not isinstance(jsonObject, dict):
return False
if not (key in jsonObject):
# s = "%s not found in jsonObject" % key
# logger.debug(s)
return False
if not isinstance(jsonObject[key], types):
# s = "jsonObject['%s'] is not in types %s" % (key, str(types))
# logger.debug(s)
return False
return True
def list_files(path=None, postfix=None):
if path is None:
path = '.'
files = []
postfix_list = []
if isinstance(postfix, str):
postfix_list.append(postfix)
elif isinstance(postfix, tuple):
for item in postfix:
postfix_list.append(item)
elif postfix is None:
postfix_list = None
for file in os.listdir(path):
if postfix_list is None:
files.append(file)
else:
s = file.split('.')
if len(s) > 1 and s[1] in postfix_list:
files.append(file)
return files
def check_mqtt_config(jsonObject):
if not isinstance(jsonObject, dict):
return False
if not check_key_types(jsonObject, 'host', str):
err = "key 'host' error"
logger.error(err)
return False
if not check_key_types(jsonObject, 'port', (int, float)):
err = "key 'port' error"
logger.error(err)
return False
if not check_key_types(jsonObject, 'keepalive', (int, float)):
err = "key 'keepalive' error"
logger.error(err)
return False
if not check_key_types(jsonObject, 'topicPrefix', str):
err = "key 'topicPrefix' error"
logger.error(err)
return False
if not check_key_types(jsonObject, 'useTLS', bool):
err = "key 'useTLS' error"
logger.error(err)
return False
return True
| 25.467005
| 71
| 0.527407
|
209fd46c9c5a3475246dfa73ee923f0b8e428619
| 2,115
|
py
|
Python
|
AutoPoly/extern/moltemplate/common/amber/amberparm_pair_to_lt.py
|
Chenghao-Wu/AutoPoly
|
e7b5d098c1fa33a11189e831ce6e5f121fc7615c
|
[
"MIT"
] | 1
|
2021-09-09T21:53:41.000Z
|
2021-09-09T21:53:41.000Z
|
AutoPoly/extern/moltemplate/common/amber/amberparm_pair_to_lt.py
|
Chenghao-Wu/AutoPoly
|
e7b5d098c1fa33a11189e831ce6e5f121fc7615c
|
[
"MIT"
] | null | null | null |
AutoPoly/extern/moltemplate/common/amber/amberparm_pair_to_lt.py
|
Chenghao-Wu/AutoPoly
|
e7b5d098c1fa33a11189e831ce6e5f121fc7615c
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
import sys
lines_gaff = sys.stdin.readlines()
#pair_style = 'lj/charmm/coul/long'
# NOTE: Long-range coulombic forces were disabled intentionally. (See below)
# If you want to use long-range electrostatics, uncomment these lines:
# Instead I use hybrid lj/charmm/coul/charmm by default, because
# LAMMPS complains if you attempt to use lj/charmm/coul/long on a
# system if it does not contain any charged particles.
# Currently, moltemplate does not assign atomic charge,
# so this problem occurs frequently.
#pair_style = 'lj/charmm/coul/charmm'
pair_style = 'lj/charmm/coul/long'
sys.stdout.write(' write_once(\"In Settings\") {\n')
for i in range(0, len(lines_gaff)):
line = lines_gaff[i]
tokens= line.split()
atype = tokens[0]
# UGGHHH
# OLD CODE:
#sig=tokens[1]
# CORRECTION #1
# It looks the number in this part of the file is an atom radii, not a
# diameter. In other words, this number is 0.5*sigma instead of sigma.
# So we multiply it by 2.0.
#sig=str(2.0*float(tokens[1]))
#
# CORRECTION #2
# It also appears as though they are using this convention for LennardJones
# U(r)=epsilon*((s/r)^12-2*(s/r)^6) instead of 4*eps*((s/r)^12-(s/r)^6)
# ...where "s" is shorthand for "sigma"..
# This means we must ALSO multiply sigma in gaff.dat by 2**(-1.0/6)
# (This change makes the two U(r) formulas equivalent.)
# I had to figure this out by iterations of trial and error.
# The official AMBER documentation is quite vague about the LJ parameters.
# My apologies to everyone effected by this bug! -Andrew 2014-5-19
# http://ambermd.org/formats.html#parm.dat
# http://structbio.vanderbilt.edu/archives/amber-archive/2009/5072.php)
sig=str(float(tokens[1])*2.0*pow(2.0, (-1.0/6.0)))
eps=tokens[2]
comments=' '.join(tokens[3:])
sys.stdout.write(' pair_coeff @atom:'+atype+' @atom:'+atype+' '+pair_style+' '+eps+' '+sig+' # '+comments+'\n')
sys.stdout.write(' } # (end of pair_coeffs)\n')
sys.stdout.write('\n')
| 36.465517
| 120
| 0.655792
|
4d50934172f1c53deda5ac95ad59d75afb849e5d
| 451
|
py
|
Python
|
test_minHeap.py
|
codeocelot/datastructures
|
cec1253a287b00b72fbbc82660cd464a376c967d
|
[
"Apache-2.0"
] | null | null | null |
test_minHeap.py
|
codeocelot/datastructures
|
cec1253a287b00b72fbbc82660cd464a376c967d
|
[
"Apache-2.0"
] | null | null | null |
test_minHeap.py
|
codeocelot/datastructures
|
cec1253a287b00b72fbbc82660cd464a376c967d
|
[
"Apache-2.0"
] | null | null | null |
from unittest import TestCase
from min_heap import MinHeap
class TestMinHeap(TestCase):
def test_pop(self):
init = [1, 2, 3, 4, 5, 6, 7]
heap = MinHeap(init)
r = heap.pop()
self.assertEqual(r, 1)
self.assertEqual(heap.values, [2, 4, 3, 7, 5, 6])
def test_push(self):
init = [2, 7, 9, 5]
heap = MinHeap(init)
heap.push(1)
self.assertEqual(heap.values, [1, 2, 9, 7, 5])
| 25.055556
| 57
| 0.554324
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.