content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def backproject_to_plane(cam, img_pt, plane):
"""Back an image point to a specified world plane"""
# map to normalized image coordinates
npt = np.matrix(npl.solve(cam[0], np.array(list(img_pt)+[1.0])))
M = cam[1].transpose()
n = np.matrix(plane[:3]).flatten()
d = plane.flat[3]
Mt = M * cam[2... | 47ae45103460db5a5447900dda10783c8f92362e | 3,640,100 |
from datetime import datetime
def format_cell(cell, datetime_fmt=None):
"""Format a cell."""
if datetime_fmt and isinstance(cell, datetime):
return cell.strftime(datetime_fmt)
return cell | 8d3fb41bb3d7d3f3b341482e2d050d32092118bf | 3,640,101 |
def optimize(gradients, optim, global_step, summaries, global_norm=None, global_norm_clipped=None, appendix=''):
"""Modified from sugartensor"""
# Add Summary
if summaries is None:
summaries = ["loss", "learning_rate"]
# if "gradient_norm" in summaries:
# if global_norm is None:
# ... | 4887d45d5b9eb5a96008daeab5d11c97afed27fd | 3,640,102 |
def _get_desired_asg_capacity(region, stack_name):
"""Retrieve the desired capacity of the autoscaling group for a specific cluster."""
asg_conn = boto3.client("autoscaling", region_name=region)
tags = asg_conn.describe_tags(Filters=[{"Name": "value", "Values": [stack_name]}])
asg_name = tags.get("Tags"... | cdcec8493333a001fe3883b0c815da521c571f7a | 3,640,103 |
def _default_geo_type_precision():
""" default digits after decimal for geo types """
return 4 | eef082c8a8b38f4ede7bfb5d631b2679041b650c | 3,640,104 |
import scipy
def load_movietimes(filepath_timestamps, filepath_daq):
"""Load daq and cam time stamps, create muxer"""
df = pd.read_csv(filepath_timestamps)
# DAQ time stamps
with h5py.File(filepath_daq, 'r') as f:
daq_stamps = f['systemtime'][:]
daq_sampleinterval = f['samplenumber'][... | 4d54f7378f3d189a5bea4c14f68d5556958ba4f3 | 3,640,105 |
def is_valid_hotkey(hotkey: str) -> bool:
"""Returns True if hotkey string is valid."""
mode_opts = ["press", "click", "wheel"]
btn_opts = [b.name for b in Button]
wheel_opts = ["up", "down"]
hotkeylist = hotkey[2:].split("_")
if len(hotkeylist) == 0 or len(hotkeylist) % 2 != 0:
return ... | 2fb47b3f77b4cb3da2b70340b6ed96bd03c0bd14 | 3,640,106 |
def find_range_with_sum(values : list[int], target : int) -> tuple[int, int]:
"""Given a list of positive integers, find a range which sums to a target
value."""
i = j = acc = 0
while j < len(values):
if acc == target:
return i, j
elif acc < target:
acc += values... | d54f185c98c03f985724a29471ecb1e301c14df5 | 3,640,107 |
def output_AR1(outfile, fmri_image, clobber=False):
"""
Create an output file of the AR1 parameter from the OLS pass of
fmristat.
Parameters
----------
outfile :
fmri_image : ``FmriImageList`` or 4D image
object such that ``object[0]`` has attributes ``coordmap`` and ``shape``
cl... | b805e73992a51045378d5e8f86ccf780d049002b | 3,640,108 |
def feature_bit_number(current):
"""Fuzz bit number field of a feature name table header extension."""
constraints = UINT8_V
return selector(current, constraints) | 4a2103f399765aec9d84c8152922db3801e4a718 | 3,640,109 |
def render_page(context, slot, payload): # pylint: disable=R0201,W0613
""" Base template slot """
chapter = request.args.get('chapter', '')
module = request.args.get('module', '')
page = request.args.get('page', '')
try:
if page:
return render_template(f"{chapter.lower()}/{modul... | 69e5a837d90084b4c215ff75fb08a47aab1cff97 | 3,640,110 |
def add_stripe_customer_if_not_existing(f):
"""
Decorator which creates user as a customer if not already existing before making a request to the Stripe API
"""
@wraps(f)
def wrapper(user: DjangoUserProtocol, *args, **kwargs):
user = create_customer(user)
return f(user, *args, **kwar... | 676e9fad5de545a2627d52942917a49af3c6539d | 3,640,111 |
def debug():
"""
Import the test utils module to be able to:
- Use the trace tool and get context variables after making a request to Apigee
"""
return ApigeeApiTraceDebug(proxy=config.PROXY_NAME) | 0639a52e1a838b0408a820dd29ae4a08f89b0adc | 3,640,112 |
def FromModuleToDoc(importedMod,filDfltText):
"""
Returns the doc string of a module as a literal node. Possibly truncated
so it can be displayed.
"""
try:
docModuAll = importedMod.__doc__
if docModuAll:
docModuAll = docModuAll.strip()
# Take only the firs... | e79882283e232166df67a1a5333e60fcdb2a136f | 3,640,113 |
def noisify_patternnet_asymmetric(y_train, noise, random_state=None):
""" mistakes in labelling the land cover classes in PatternNet dataset
cemetery -> christmas_tree_fram
harbor <--> ferry terminal
Den.Res --> costal home
overpass <--> intersection
park.space --> park.lot
runway_mark --> p... | ef37d5c39081cba489076956c0cd948a93ba0387 | 3,640,114 |
def group_superset_counts(pred, label):
"""
Return TP if all label spans appear within pred spans
:param pred, label: A group, represeted as a dict
:return: A Counts namedtuple with TP, FP and FN counts
"""
if (pred["label"] != label["label"]):
return Counts(0, 1, 1)
for label_span i... | 8fddd5cfdb0050e97ec60d37e4d939b40cf5d891 | 3,640,115 |
def other():
""" Queries all of the logged in user's Campaigns
and plugs them into the campaigns template """
entities = db.session.query(Entity)
entities = [e.to_dict() for e in entities]
return render_template('other.html', entities=entities) | 7c7613f919bf5eecc223cf90715e9bd2ae6eb130 | 3,640,116 |
def rel_angle(vec_set1, vec_set2):
"""
Calculate the relative angle between two vector sets
Args:
vec_set1(array[array]): an array of two vectors
vec_set2(array[array]): second array of two vectors
"""
return vec_angle(vec_set2[0], vec_set2[1]) / vec_angle(vec_set1[0], vec_set1[1]) ... | af89a10e26968f53200294919d8b72b532aa3522 | 3,640,117 |
def check_position_axes(chgcar1: CHGCAR, chgcar2: CHGCAR) -> bool:
"""Check the cell vectors and atom positions are same in two CHGCAR.
Parameters
-----------
chgcar1, chgcar2: vaspy.CHGCAR
Returns
-------
bool
"""
cell1 = chgcar1.poscar.cell_vecs
cell2 = chgcar2.poscar.cell_v... | 29eabfd72a664c77d55164953b6819f3eabd72f1 | 3,640,118 |
def path_shortest(graph, start):
""" Pythonic minheap implementation of dijkstra's algorithm """
# Initialize all distances to infinity but the start one.
distances = {node: float('infinity') for node in graph}
distances[start] = 0
paths = [(0, start)]
while paths:
current_distance, cu... | 32fe7df3fb02c3a0c3882f5cc5135417c5193985 | 3,640,119 |
import urllib
import json
def request(url, *args, **kwargs):
"""Requests a single JSON resource from the Wynncraft API.
:param url: The URL of the resource to fetch
:type url: :class:`str`
:param args: Positional arguments to pass to the URL
:param kwargs: Keyword arguments (:class:`str`) to pass... | 66f23e5a15b44b5c9bc0777c717154749d25987e | 3,640,120 |
def destagger(var, stagger_dim, meta=False):
"""Return the variable on the unstaggered grid.
This function destaggers the variable by taking the average of the
values located on either side of the grid box.
Args:
var (:class:`xarray.DataArray` or :class:`numpy.ndarray`): A variable
... | 89bb08618fa8890001f72a43da06ee8b15b328be | 3,640,121 |
from typing import Optional
from typing import Dict
from typing import Any
def predict_pipeline_acceleration(
data: arr_t, sampling_rate: float, convert_to_g: Optional[bool] = True, **kwargs
) -> Dict[str, Any]:
"""Apply sleep processing pipeline on raw acceleration data.
This function processes raw acce... | f714a29925c2733d0e8baf8d95b2884bf9d98e6e | 3,640,122 |
def create_blueprint(request_manager: RequestManager, cache: Cache,
dataset_factory: DatasetFactory):
"""
Creates an instance of the blueprint.
"""
blueprint = Blueprint('metadata', __name__, url_prefix='/metadata')
@cache.memoize()
def _get_method_types_per_approach():
... | 32693a6286e4ffb15e4820dbd7ad5fdbe6632e95 | 3,640,123 |
def sides(function_ast, parameters, function_callback):
"""
Given an ast, parses both sides of an expression.
sides(b != c) => None
"""
left = side(function_ast['leftExpression'], parameters, function_callback)
right = side(function_ast['rightExpression'], parameters, function_callback)
... | 9ed00100122f821340a0db37e77bfcf786eacdf9 | 3,640,124 |
def print_url(host, port, datasets):
"""
Prints a list of available dataset URLs, if any. Otherwise, prints a
generic URL.
"""
def url(path = None):
return colored(
"blue",
"http://{host}:{port}/{path}".format(
host = host,
port = por... | 37d58dce1672f60d72936d6e1b9644fdd5ab689f | 3,640,125 |
def get_default_sample_path_random(data_path):
"""Return path to sample with default parameters as suffix"""
extra_suffix = get_default_extra_suffix(related_docs=False)
return get_default_sample_path(data_path, sample_suffix=extra_suffix) | 54220840dc6ef1831859a60058506e7503effcb7 | 3,640,126 |
def VectorShadersAddMaterialDesc(builder, materialDesc):
"""This method is deprecated. Please switch to AddMaterialDesc."""
return AddMaterialDesc(builder, materialDesc) | 0aaec1d3e14536a65c9cb876075d12348176096c | 3,640,127 |
import math
def phase_randomize(D, random_state=0):
"""Randomly shift signal phases
For each timecourse (from each voxel and each subject), computes its DFT
and then randomly shifts the phase of each frequency before inverting
back into the time domain. This yields timecourses with the same power
... | d8f3230acdf8b3df98995adaadc92f41497a27ea | 3,640,128 |
def monospaced(text):
"""
Convert all contiguous whitespace into single space and strip leading and
trailing spaces.
Parameters
----------
text : str
Text to be re-spaced
Returns
-------
str
Copy of input string with all contiguous white space replaced with
... | 51f07908dde10ef67bd70b5eb65e03ee832c3755 | 3,640,129 |
def molecule_block(*args, **kwargs):
"""
Generates the TRIPOS Mol2 block for a given molecule, returned as a string
"""
mol = Molecule(*args, **kwargs)
block = mol.molecule_block() + mol.atom_block() + mol.bond_block() + '\n'
return block | 79ebf821e105666fb81396197fa0f218b2cf3e48 | 3,640,130 |
def setup_test_env(settings_key='default'):
"""Allows easier integration testing by creating RPC and HTTP clients
:param settings_key: Desired server to use
:return: Tuple of RPC client, HTTP client, and thrift module
"""
return RpcClient(handler), HttpClient(), load_module(settings_key) | 827a71692dd2eb9946db34289dcf48d5b5d4415b | 3,640,131 |
from typing import List
from typing import Tuple
def calculateCentroid(
pointCloud : List[Tuple[float, float, float]]
) -> Tuple[float, float, float]:
"""Calculate centroid of point cloud.
Arguments
--------------------------------------------------------------------------
pointCloud (flo... | 0e8d6d578a0a983fe1e68bff22c5cc613503ee76 | 3,640,132 |
def timber_load():
"""
Calculate Timber's IO load since the last call
"""
#io(read_count=454556, write_count=3456, read_bytes=110592, write_bytes=0)
global timber_io_stat
try:
new_stat = p.get_io_counters()
readCount = new_stat.read_count - timber_io_stat.read_count
write... | eebd8c3b0cc48b01f361de0455c34daee5942ea9 | 3,640,133 |
def get_num_uniq_users(csv_file, userid_col):
"""
A Helper function to help get the number of unique users
:param csv_file: path to CSV file
:param userid_col: Column for user ID
:return:
"""
# Read the CSV file using pandas
df = pd.read_csv(csv_file)
# Use the nunique() method to g... | ade25596bb308414c80e1aea87d412bd5a340288 | 3,640,134 |
def generate_graph_batch(n_examples, sample_length):
""" generate all of the training data
Parameters
----------
n_examples: int
Num of the samples
sample_length: int
Length of the samples.
# TODO we should implement samples of different lens as in the DeepMind example.
... | 8f98b86e069070a44c84368592a023311ebcdc7d | 3,640,135 |
from zooniverse_web.models import Survey, QuestionResponse, Response, QuestionOption
from zooniverse_web.utility.survey import generate_new_survey
def administration(request):
"""Administration actions ((re)train acton predictor for a new survey)
Parameters
----------
request:
POST request
... | 7d5a08450c9058f6fd33a13fc4cf6b714bc7e657 | 3,640,136 |
from typing import Counter
def checkout(skus):
"""
Calculate the total amount for the checkout based on the SKUs entered in
:param skus: string, each char is an item
:return: int, total amount of the cart, including special offers
"""
total = 0
counter = Counter(skus)
# got through t... | ad00a9c3e3cd4f34cfd7b5b306d3863decc0751b | 3,640,137 |
def func_tradeg(filename, hdulist=None, whichhdu=None):
"""Return the fits header value TELRA in degrees.
"""
hdulist2 = None
if hdulist is None:
hdulist2 = fits.open(filename, 'readonly')
else:
hdulist2 = hdulist
telra = fitsutils.get_hdr_value(hdulist2, 'TELRA')
if hdulis... | 4e6751d2eb0ac9e6264f768e932cbd42c2fc2c4e | 3,640,138 |
def column_indexes(column_names, row_header):
"""項目位置の取得
Args:
column_names (str): column name
row_header (dict): row header info.
Returns:
[type]: [description]
"""
column_indexes = {}
for idx in column_names:
column_indexes[idx] = row_header.index(column_names... | 4205e31e91cd64f833abd9ad87a02d91eebc8c61 | 3,640,139 |
import logging
import pickle
def dmx_psrs(caplog):
"""Sample pytest fixture.
See more at: http://doc.pytest.org/en/latest/fixture.html
"""
caplog.set_level(logging.CRITICAL)
psrs = []
for p in psr_names:
with open(datadir+'/{0}_ng9yr_dmx_DE436_epsr.pkl'.format(p), 'rb') as fin:
... | 6bbb5df017374f207d7c9338a737212f5c7e5b23 | 3,640,140 |
def fit_stats(act_map, param, func=KentFunc):
"""Generate fitting statistics from scipy's curve fitting"""
phi_grid, theta_grid = meshgrid(phi_arr, theta_arr)
Xin = np.array([theta_grid.flatten(), phi_grid.flatten()]).T
fval = act_map.flatten()
fpred = func(Xin, *param) # KentFunc
res = fval - ... | 97e4223daf3e140f1a091491f18012840b8c006a | 3,640,141 |
def conv2d_for_hpool_valid_width_wrapper(inputs,filters,strides,padding,**kwargs):
"""
Wraps tf.layers.conv2d to allow valid convolution across signal width and
'same' convolution across signal height when padding is set to "valid_time"
Arguments:
inputs (TF Tensor): Tensor input.
filters (TF... | 9b4438c687232245e645ea5714e7ad7899ecd98b | 3,640,142 |
import copy
def resample_cells(tree, params, current_node = 'root', inplace = False):
"""
Runs a new simulation of the cell evolution on a fixed tree
"""
if not inplace:
tree = copy.deepcopy(tree)
for child in tree.successors(current_node):
initial_cell = tree.nodes[current_node][... | 10cde9abdf3a6271aa20276c3e193b1c93ca7908 | 3,640,143 |
def get_sql_query(table_name:str) -> str:
"""Fetch SQL query file for generation of dim or fact table(s)"""
f = open(f'./models/sql/{table_name}.sql')
f_sql_query = f.read()
f.close()
return f_sql_query | fc3308eae51b7d10667a50a0f4ee4e295bfea8d0 | 3,640,144 |
def _map_args(call_node, function):
"""Maps AST call nodes to the actual function's arguments.
Args:
call_node: ast.Call
function: Callable[..., Any], the actual function matching call_node
Returns:
Dict[Text, ast.AST], mapping each of the function's argument names to
the respective AST node.
"... | b19befded386e6081be9858c7eb31ffd45c96ef3 | 3,640,145 |
def sub_bases( motif ):
"""
Return all possible specifications of a motif with degenerate bases.
"""
subs = {"W":"[AT]", \
"S":"[CG]", \
"M":"[AC]", \
"K":"[GT]", \
"R":"[AG]", \
"Y":"[CT]", \
"B":"[CGT]", \
"D":"[AGT]", \
"H":"[ACT]", \
"V":"[ACG]", \
"N":"[ACGTN]"}
for symbol,... | 10ff2ea1959aba103f1956398afb5f1d8801edd7 | 3,640,146 |
import logging
def parse(input_file_path):
"""
Parse input file
:param input_file_path: input file path
:return: Image list
"""
verticals, horizontals = 0, 0
logging.info("parsing %s", input_file_path)
with open(input_file_path, 'r') as input_file:
nb = int(input_file.readline(... | ecd4fd066d1128f385da59965a93e59c038052bd | 3,640,147 |
def char(ctx, number):
"""
Returns the character specified by a number
"""
return chr(conversions.to_integer(number, ctx)) | 5c5254978055f690b6801479b180ff39b31e2248 | 3,640,148 |
import re
import logging
async def get_character_name(gear_url, message):
"""
It is *sometimes* the case that discord users don't update their username
to be their character name (eg for alts).
This method renders the gear_url in an HTML session and parses the page
to attempt to find the charact... | cdd18e0123f226d2c59d41bbf39e0dfc02188d73 | 3,640,149 |
import pandas
def get_treant_df(tags, path='.'):
"""Get treants as a Pandas DataFrame
Args:
tags: treant tags to identify the treants
path: the path to search for treants
Returns:
a Pandas DataFrame with the treant name, tags and categories
>>> from click.testing import CliRunner
... | a5972646e27ffd88d18f1c0d212a2ae081ebe4f1 | 3,640,150 |
def gather_keypoints(keypoints_1, keypoints_2, matches):
"""
Gather matched keypoints in a (n x 4) array,
where each row correspond to a pair of matching
keypoints' coordinates in two images.
"""
res = []
for m in matches:
idx_1 = m.queryIdx
idx_2 = m.trainIdx
pt... | 5abef87c570493b57e81dcddc2732ed541aa6a08 | 3,640,151 |
async def stop():
""" Stop any playing audio. """
Sound.stop()
return Sound.get_state() | 3c7ea7aae3e8dd7e3b33ddd9beed0ce2182800bc | 3,640,152 |
def is_numeric(X, compress=True):
"""
Determine whether input is numeric array
Parameters
----------
X: Numpy array
compress: Boolean
Returns
-------
V: Numpy Boolean array if compress is False, otherwise Boolean Value
"""
def is_float(val):
try:
float(v... | ad28657f51680cd193671a6a8a8da6a91390dc15 | 3,640,153 |
def figure_ellipse_fitting(img, seg, ellipses, centers, crits, fig_size=9):
""" show figure with result of the ellipse fitting
:param ndarray img:
:param ndarray seg:
:param [(int, int, int, int, float)] ellipses:
:param [(int, int)] centers:
:param [float] crits:
:param float fig_size:
... | de6b58a01a64c3123f5aad4dfb6935c6c19a041c | 3,640,154 |
def fmt_bytesize(num: float, suffix: str = "B") -> str:
"""Change a number of bytes in a human readable format.
Args:
num: number to format
suffix: (Default value = 'B')
Returns:
The value formatted in human readable format (e.g. KiB).
"""
for unit in ["", "Ki", "Mi", "Gi", "Ti",... | 09b36d229856004b6df108ab1ce4ef0a9c1e6289 | 3,640,155 |
def get_kpoint_mesh(structure: Structure, cutoff_length: float, force_odd: bool = True):
"""Calculate reciprocal-space sampling with real-space cut-off."""
reciprocal_lattice = structure.lattice.reciprocal_lattice_crystallographic
# Get reciprocal cell vector magnitudes
abc_recip = np.array(reciprocal_... | 0536b5e2c37b7ba98d240fc3099fad93d246f730 | 3,640,156 |
def resnet_v1_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
reuse=None,
scope='resnet_v1_101', **kwargs):
"""ResNet-101 model of... | 138289084d48edd9d9c1096bd790b1479d902ec1 | 3,640,157 |
def is_package_authorized(package_name):
"""
get user information if it is authorized user in the package config
Returns:
[JSON string]: [user information session]
"""
authorized_users = get_package_admins(package_name)
user_info = get_user_info()
user_dict = j.data.serializers.json... | 59b89ebb9c8579d61a18a194e7f5f4bd41d738b6 | 3,640,158 |
def submit_search_query(query_string, query_limit, query_offset,
class_resource):
"""
Submit a search query request to the RETS API
"""
search_result = class_resource.search(
query='%s' % query_string, limit=query_limit, offset=query_offset)
return search_result | f8c30c86f7ff7c33fc96b26b1491ddaa48710fbc | 3,640,159 |
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.... | 6895dfbc4bb57d5e8d9a5552e2ac7fcb94e07434 | 3,640,160 |
def assert_increasing(a):
"""Utility function for enforcing ascending values.
This function's handle can be supplied as :py:kwarg:`post_method` to a
:py:func:`processed_proprty <pyproprop>` to enforce values within a
:py:type:`ndarray <numpy>` are in ascending order. This is useful for
enforcing ti... | f1ded37b40686cf400da23f567880e73180a78fe | 3,640,161 |
def copy_to_device(device,
remote_path,
local_path='harddisk:',
server=None,
protocol='http',
vrf=None,
timeout=300,
compact=False,
use_kstack=False,
... | 762ef928656473458e0fee8dc47c1a581103ed0e | 3,640,162 |
import os
def get_credentials():
"""Gets valid user credentials from storage.
If nothing has been stored, or if the stored credentials are invalid,
the OAuth2 flow is completed to obtain the new credentials.
Returns:
Credentials, the obtained credential.
"""
home_dir = os.path.expand... | 51a17757d3d764c090efc0b8b213e9e6e9abca3d | 3,640,163 |
def decode_replay_header(contents):
"""Decodes and return the replay header from the contents byte string."""
decoder = VersionedDecoder(contents, protocol.typeinfos)
return decoder.instance(protocol.replay_header_typeid) | 1fcee7900a5c0c310e67afe31a154b8310da7089 | 3,640,164 |
def _generate_indexed(array: IndexedArray) -> str:
"""Generate an indexed Bash array."""
return (
"("
+ " ".join(
f"[{index}]={_generate_string(value)}"
for index, value in enumerate(array)
if value is not None
)
+ ")"
) | 2443b3c6be74684360c395995b3d16d4ebecf1d8 | 3,640,165 |
from datetime import datetime
def up_date(dte, r_quant, str_unit, bln_post_colon):
""" Adjust a date in the light of a (quantity, unit) tuple,
taking account of any recent colon
"""
if str_unit == 'w':
dte += timedelta(weeks=r_quant)
elif str_unit == 'd':
dte += timedelta(... | 684b09e5d37bf0d3445262b886c73188d35425ef | 3,640,166 |
from typing import MutableMapping
def read_options() -> Options:
"""
read command line arguments and options
Returns:
option class(Options)
Raises:
NotInspectableError: the file or the directory does not exists.
"""
args: MutableMapping = docopt(__doc__)
schema = Schema({... | 25cd3c29f6e206fd97334f7a48d267680a9e553c | 3,640,167 |
def test_generator_single_input_2():
"""
Feature: Test single str input
Description: input str
Expectation: success
"""
def generator_str():
for i in range(64):
yield chr(ord('a') + i)
class RandomAccessDatasetInner:
def __init__(self):
self.__data =... | d251279c0740b52c9d32c2ae572f6dbdf32f36ea | 3,640,168 |
def SLINK(Dataset, d):
"""function to execute SLINK algo
Args:
Dataset(List) :- list of data points, who are also lists
d(int) :- dimension of data points
Returns:
res(Iterables) :- list of triples sorted by the second element,
first element is index of poin... | d10a3f8cb3e6d81649bebd4a45f5be79d206f1be | 3,640,169 |
def static_file(path='index.html'):
"""static_file"""
return app.send_static_file(path) | 5c3f2d423d029a8e7bb8db5fbe3c557f7a6aa9c3 | 3,640,170 |
def lazy_property(function):
""" Decorator to make a lazily executed property """
attribute = '_' + function.__name__
@property
@wraps(function)
def wrapper(self):
if not hasattr(self, attribute):
setattr(self, attribute, function(self))
return getattr(self, attribute)
... | db1d62eb66a018bc166b67fe9c2e25d671261f77 | 3,640,171 |
from pathlib import Path
def basename(fname):
"""
Return file name without path.
Examples
--------
>>> fname = '../test/data/FSI.txt.zip'
>>> print('{}, {}, {}'.format(*basename(fname)))
../test/data, FSI.txt, .zip
"""
if not isinstance(fname, path_type):
fname = Path(fna... | 55cd53ec71e4e914493129e40fa216ddcdbe8083 | 3,640,172 |
def validate_lockstring(lockstring):
"""
Validate so lockstring is on a valid form.
Args:
lockstring (str): Lockstring to validate.
Returns:
is_valid (bool): If the lockstring is valid or not.
error (str or None): A string describing the error, or None
if no error w... | 0feb67597e31667013ab182159c8433ae4a80346 | 3,640,173 |
from typing import Iterable
def decode_geohash_collection(geohashes: Iterable[str]):
"""
Return collection of geohashes decoded into location coordinates.
Parameters
----------
geohashes: Iterable[str]
Collection of geohashes to be decoded
Returns
-------
Iterable[Tuple[float... | 2e673c852c7ac2775fd29b32243bdc8b1aa83d77 | 3,640,174 |
def renormalize_sparse(A: sp.spmatrix) -> sp.spmatrix:
"""Get (D**-0.5) * A * (D ** -0.5), where D is the diagonalized row sum."""
A = sp.coo_matrix(A)
A.eliminate_zeros()
rowsum = np.array(A.sum(1))
assert np.all(rowsum >= 0)
d_inv_sqrt = np.power(rowsum, -0.5).flatten()
d_inv_sqrt[np.isinf... | 33122bcf018dba842f04e044cf9e799860a56042 | 3,640,175 |
from typing import Union
import torch
import os
def load_gloria(
name: str = "gloria_resnet50",
device: Union[str, torch.device] = "cuda" if torch.cuda.is_available() else "cpu",
):
"""Load a GLoRIA model
Parameters
----------
name : str
A model name listed by `gloria.available_models... | 5ec060dd7e430244b597891d10cb19bc176a727f | 3,640,176 |
import subprocess
import os
import re
def is_enabled():
"""
Check if `ufw` is enabled
:returns: True if ufw is enabled
"""
output = subprocess.check_output(['ufw', 'status'],
universal_newlines=True,
env={'LANG': 'en_US',
... | fa922cdb87e35e1fc7cf77c5eba6a7da651ea070 | 3,640,177 |
def _fetch(
self,
targets=None,
jobs=None,
remote=None,
all_branches=False,
show_checksums=False,
with_deps=False,
all_tags=False,
recursive=False,
):
"""Download data items from a cloud and imported repositories
Returns:
int: number of successfully downloaded files
... | 18238bb1c4c5bd0772757013173e26645d5cdf5a | 3,640,178 |
def get_connected_input_geometry(blend_shape):
"""
Return an array of blend_shape's input plugs that have an input connection.
pm.listConnections should do this, but it has bugs when the input array is sparse.
"""
results = []
blend_shape_plug = _get_plug_from_node('%s.input' % blend_shape)
num_input_elements ... | c69421ce452a1416006db0f22d279a6ed9694ebc | 3,640,179 |
import torch
from typing import Tuple
def get_median_and_stdev(arr: torch.Tensor) -> Tuple[float, float]:
"""Returns the median and standard deviation from a tensor."""
return torch.median(arr).item(), torch.std(arr).item() | d8fca5a97f00d14beecaa4b508442bc7a3637f86 | 3,640,180 |
def connect(user, host, port):
"""Create and return a new SSHClient connected to the given host."""
client = ssh.SSHClient()
if not env.disable_known_hosts:
client.load_system_host_keys()
if not env.reject_unknown_hosts:
client.set_missing_host_key_policy(ssh.AutoAddPolicy())
con... | a13a3ce5e80f603f21933c9e6ad48b073368b97e | 3,640,181 |
import scipy
def _chf_to_pdf(t, x, chf, **chf_args):
"""
Estimate by numerical integration, using ``scipy.integrate.quad``,
of the probability distribution described by the given characteristic
function. Integration errors are not reported/checked.
Either ``t`` or ``x`` must be a scalar.
"""
... | 7022d335d39c25b73203b63b40b1ebb8c178154b | 3,640,182 |
import re
import logging
def ParseTraceLocationLine(msg):
"""Parse the location line of a stack trace. If successfully parsed, returns (filename, line, method)."""
parsed = re.match(kCodeLocationLine, msg)
if not parsed:
return None
try:
return (parsed.group(1), parsed.group(2), parsed.group(3))
exc... | 15e74bb26a7c213cf24171ffdfa32b8d4e6d818a | 3,640,183 |
import pandas
import os
def get_rl_params(num, similarity_name, reward_name):
""" Get RL model parameters (alpha and beta) based on <num>'s data.
<similarity_name> is the name of the similarity metric you want to
use, see fmri.catreward.roi.data.get_similarity_data() for details.
<reward_name> ... | 08bc39fbc02b2fa3d459a3996a87e294e0ef1d94 | 3,640,184 |
import functools
def return_arg_type(at_position):
"""
Wrap the return value with the result of `type(args[at_position])`
"""
def decorator(to_wrap):
@functools.wraps(to_wrap)
def wrapper(*args, **kwargs):
result = to_wrap(*args, **kwargs)
ReturnType = type(arg... | 30bf4e4a46b0b64b6cb5752286a13c0e6f7618df | 3,640,185 |
def extend(s, var, val):
"""Copy dict s and extend it by setting var to val; return copy."""
try: # Python 3.5 and later
return eval('{**s, var: val}')
except SyntaxError: # Python 3.4
s2 = s.copy()
s2[var] = val
return s2 | 919e7102bf7f8766d9ddb9ea61a07ddd020d1bb8 | 3,640,186 |
from typing import Optional
from typing import Any
def rx_reduce(observable: Observable, accumulator: AccumulatorOperator, seed: Optional[Any] = None) -> Observable:
"""Create an observable which reduce source with accumulator and seed value.
Args:
observable (Observable): source
accumulator ... | 600d5c47fd7b29ead5293c7a172c8ebdb026706a | 3,640,187 |
import logging
import torch
def predict(image: Image.Image):
""" Take an image and run it through the inference model. This returns a ModelOutput object with all of the
information that the model returns. Furthermore, bounding box coordinates are normalized.
"""
logging.debug("Sending image to model ... | eb90a598fb573dd8f345c62408bbf921f765a1f3 | 3,640,188 |
def minimum_filter(
input,
size=None,
footprint=None,
output=None,
mode="reflect",
cval=0.0,
origin=0,
):
"""Multi-dimensional minimum filter.
Args:
input (cupy.ndarray): The input array.
size (int or sequence of int): One of ``size`` or ``footprint`` must be
... | fbbda2abbd470b98cb03158377256c7397c17da6 | 3,640,189 |
import copy
def lowpass(data, cutoff=0.25, fs=30, order=2, nyq=0.75):
"""
Butter low pass filter for a single or spectra or a list of them.
:type data: list[float]
:param data: List of vectors in line format (each line is a vector).
:type cutoff: float
:param cutoff: Desired cuto... | ac42a32c406b1c5a182a1af805e86bf0b0c0606f | 3,640,190 |
from re import M
def format(value, limit=LIMIT, code=True, offset=0, hard_stop=None, hard_end=0):
"""
Recursively dereferences an address into string representation, or convert the list representation
of address dereferences into string representation.
Arguments:
value(int|list): Either the s... | d8eae5b2cc8dbab9a26d7248faf17fe638f5e603 | 3,640,191 |
def sogs_put(client, url, json, user):
"""
PUTs a test `client` request to `url` with the given `json` as body and X-SOGS-* signature
headers signing the request for `user`.
"""
data = dumps(json).encode()
return client.put(
url, data=data, content_type='application/json', headers=x_sog... | 7bb3f34d7aff75f422b898ba6eee2908c8bc4ca4 | 3,640,192 |
import tqdm
import requests
def get_results(heading):
"""Get all records under a given record heading from PubChem/
Update results from those records."""
page = 1
results = {}
with tqdm(total=100) as pbar:
while True:
url = (f"https://pubchem.ncbi.nlm.nih.gov/rest/pug_view/anno... | fba50023290dfde12a54f6d7792f578ecc66e3d9 | 3,640,193 |
def create_dictionary(documents):
"""Creates word dictionary for given corpus.
Parameters:
documents (list of str): set of documents
Returns:
dictionary (gensim.corpora.Dictionary): gensim dicionary of words from dataset
"""
dictionary = Dictionary(documents)
dictionary.compactif... | bba8e6af363da3fcdde983c6ebf52432323ccf96 | 3,640,194 |
def clone_bitarray(other, src=None):
"""
Fast clone of the bit array. The actual function used depends on the implementation
:param other:
:param src:
:return:
"""
if FAST_IMPL_PH4 and src is not None:
src.fast_copy(other)
return src
return to_bitarray(other) | 9196474dff0e6c1b79f9307409c5f351f2c015d7 | 3,640,195 |
from typing import List
from typing import Optional
from typing import Dict
def _create_graph(
expressions: List[expression.Expression],
options: calculate_options.Options,
feed_dict: Optional[Dict[expression.Expression, prensor.Prensor]] = None
) -> "ExpressionGraph":
"""Create graph and calculate expr... | e7f5a9dbaf3c34a3c925c5d390d6ee44fac57062 | 3,640,196 |
import warnings
def power_to_db(S, ref=1.0, amin=1e-10, top_db=80.0):
"""Convert a power spectrogram (amplitude squared) to decibel (dB) units
This computes the scaling ``10 * log10(S / ref)`` in a numerically
stable way.
Parameters
----------
S : np.ndarray
input power
ref : sc... | bee32e8b9be49d4797a83ec940c6a29ae09e144e | 3,640,197 |
def generate_arn(service, arn_suffix, region=None):
"""Returns a formatted arn for AWS.
Keyword arguments:
service -- the AWS service
arn_suffix -- the majority of the arn after the initial common data
region -- the region (can be None for region free arns)
"""
arn_value = "arn"... | 53dcf55c3fb15784770d1c2d62375d1e750469f8 | 3,640,198 |
def prod_list(lst):
"""returns the product of all numbers in a list"""
if lst:
res = 1
for num in lst:
res *= num
return res
else:
raise ValueError("List cannot be empty.") | 8179e2906fb4b517d02972fd4647095d37caf6cd | 3,640,199 |
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