content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_shape_tags(tags, font_info=(cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.75, (255,255,255), 1)):
"""Get information about how much the list of tags will occupy (width and height)
with the current configuration.
Arguments:
tags -- list of strings/tags you want to check shape.
Keyword arguments:
fo... | a95d546432adb1e0d1656a8420ba63c29e4d23bd | 37,400 |
def Intersection(S1x, S1y, D1x, D1y, S2x, S2y, D2x, D2y):
"""
Find intersection of 2 line segments
:param S1x: x coordinate of segment 1's start point
:param S1y: y coordinate of segment 1's start point
:param D1x: x coordinate of segment 1's end point
:param D1y: y coordinate of segment 1's end... | 2dba8839ebf24b55fe3c1b7797e53c7e0c3ed72a | 37,401 |
def optimization_writer():
""" Writes an input file for a geometry optimization.
"""
return opt_string | b3cc7ba7d96c0f2ee584a09e0dadc8db2b8e3eb4 | 37,402 |
def _offset(ax, x, y):
"""Provide offset in pixels
Parameters
----------
x : int
Offset in pixels for x
y : int
Offset in pixels for y
Idea borrowed from
http://www.scipy.org/Cookbook/Matplotlib/Transformations
but then heavily extended to be compatible with many
reinc... | e8051a75f5cdcb5de0f36d354ee10bd72398045c | 37,403 |
def augment(input_img, input_angle):
"""
Increase the training data set.
"""
output_images, output_angles = [],[]
"""
Fun fact: I had this condition around the data flipping code
but these function calls somehow SIGNIFICANTLY slowed down
the training process!!!
if ((abs(in... | 56b5e06a71631264a897f4b6a7fd78f93410c304 | 37,404 |
def check_host(hwaddr, ipaddr, config, args, timestr):
"""
check host infos against the config
returns changes, updated_config
"""
changes = []
# get hostname
hostname = get_hostname(ipaddr)
if hwaddr in config:
# shortcut
c = config[hwaddr]
# check statu... | 6d20938332dec55acb480abcde32e53cb30c7084 | 37,405 |
def Update(dEntities):
"""This will initiate all of the different updates that need done for
the Chunk Manager Entity."""
Update_Load_List({"LoadList":dEntities["ChunkMan"].get_component("LIST:LoadList"), \
"ChunkDataDir":dEntities["ChunkMan"].get_component("MISC:C... | 18518cdb7718718599c7943db86e0adfe4e93945 | 37,406 |
import sqlite3
def getIdForTable(table):
"""resolve a table name to an ID"""
with sqlite3.connect(DB_PATH) as conn:
db = conn.cursor()
db.execute('SELECT table_id FROM tables WHERE table_name=?', [table])
return db.fetchone()[0] | 8b11309b50d4bc7fef35a3096f5bf8f42e36b0a2 | 37,407 |
def blasi(wood, gas, tar, char, T, dt, s=1):
"""
Primary and secondary kinetic reactions from Table 1 in Blasi 1993 paper.
Note that primary reaction parameters in table are not cited correctly from
the Thurner and Mann 1981 paper, this function uses the correct parameters.
Parameters
---------... | 813f532b5750ec6c7e1a402a980ac2041b0bdebf | 37,408 |
import os
def run(num, roi_class_name, trials_name):
""" For subject <num>, run all models for all ROIs.
Note: Must be run from the parent folder of all the fMRI datasets."""
sdir = subdir(num)
roi_class_path = roi_class_name.split('.')
txt_classes = ['CatMean', 'Nobox', 'CatMeanFir', 'Subtime']... | 30f7d68aa28c4c9e821ebf729379ac040b80de3d | 37,409 |
def davis_southern_women_graph() -> nx.Graph:
"""Returns Davis Southern women social network.
This is a bipartite graph.
References
----------
.. [1] A. Davis, Gardner, B. B., Gardner, M. R., 1941. Deep South.
University of Chicago Press, Chicago, IL.
"""
G = nx.Graph()
# Top n... | af8d628cb03db7a64609b36af59c93b24299f2cc | 37,410 |
def is_extension_enabled(extension_name, service):
"""A function that will check the list of enabled extensions from config
"""
config_dict = {
'compute': CONF.compute_feature_enabled.api_extensions,
'volume': CONF.volume_feature_enabled.api_extensions,
'network': CONF.network_featu... | 524fc5abb3826058ab16cb3ee4b516d6eb3e2a01 | 37,411 |
import requests
def existing_droplets(token):
"""infos about existing Marian droplets."""
params = {
'tag_name': 'marian'
}
url = 'https://api.digitalocean.com/v2/droplets'
request = requests.get(url, headers=headers(token), params=params)
return request.json()['droplets'] | 824a955d4c928004c265991b7268061f24c1cd27 | 37,412 |
import io
import numpy
def overlayLabel(dataSource, labelSource, sink = None, alpha = False, labelColorMap = 'jet', x = all, y = all, z = all):
"""Overlay a gray scale image with colored labeled image
Arguments:
dataSouce (str or array): volumetric image data
labelSource (str or array): ... | 7f84924fac34a0aea0fefc088b45eee32ac24f8d | 37,413 |
def constrain_sum(a, b, result):
"""Constrain a + b == result. Note that overflows are forbidden,
even if the result is never used."""
# This is a ripple-carry adder.
c = False # carry bit
# Optimization: stop at the the necessary number of bits.
max_bit = max([i+1 for i in BITS if a.bits[i].i... | 09371cbae682bfdef52b5db95b5dc904b7eb2ca2 | 37,414 |
def min_pos_root(a, b, c):
"""Returns the minimum positive root for the function ax²+bx+c = 0. If no positive roots exist, returns None"""
roots = all_pos_roots(a, b, c)
if not roots or len(roots) == 0:
return None
return roots[0] | afd619261002d8f65b982f74858b198d848eb572 | 37,415 |
from typing import Iterable
def patch_module(module):
"""
Extends all iterables in the module
with ``asq.queryables.Queryable`` methods.
Applies the same as ``patch_type`` to every appropriate member of
the module.
Args:
module: Module object or its __dict__.
Returns:
A ... | d5f0f7e7def1ca0938e0a52930eb3f746996e403 | 37,416 |
def trace_func(resource):
"""Trace calls to function using provided resource name"""
@wrapt.function_wrapper
def _trace_func(wrapped, instance, args, kwargs):
pin = Pin.get_from(molten)
if not pin or not pin.enabled():
return wrapped(*args, **kwargs)
with pin.tracer.tr... | 968fc735e755d8960d5d457f3ae2923a655a087e | 37,417 |
def search_for_item(project):
"""Generate a string search key for a project"""
elements = []
elements.append(project['attributes']['title'])
return u' '.join(elements) | 3ca0850b0c7b01900609aedfa41fd3fb8b86abac | 37,418 |
def sort_by_status(ori_list):
"""
sort feature progress
:param ori_list:
:return:
"""
for i in range(len(ori_list) - 1):
for j in range(len(ori_list) - 1 - i):
if compare_two_features(ori_list[j], ori_list[j + 1]):
ori_list[j], ori_list[j + 1] = ori_list[j + 1... | 389add5b03278b7cee490b507fcc0b9261a2dd4c | 37,419 |
def perturb_word(word: str, skip_stopwords=True, skip_punctuation=True):
"""
:param skip_stopwords:
:param word:
:return: pertubed word, None if no perturbation is available
"""
if skip_stopwords and word.lower() in stopwords.words('english') \
or skip_punctuation and not word.lowe... | 6334896e3f489ed1cc0baa7cfe785179579c77c5 | 37,420 |
def boxzoom(viewer, event):
"""Enable box zoom."""
def _get_shape():
if "Control" in event.modifiers:
return Shape.VERTICAL
elif "Shift" in event.modifiers:
return Shape.HORIZONTAL
return Shape.BOX
# make sure box is visible
if not viewer.drag_tool.tool.... | 49716b217b04a78c4dada95a60c9aa6c4f8e2f4c | 37,421 |
def gen_coeffs(num_dim):
"""
Helper function for generating a linear simulation.
:param num_dim: number of dimensions for the simulation
:return: a vector of coefficients
"""
coeff_vec = np.array([1 / (x+1) for x in range(num_dim)])
return coeff_vec.reshape(-1, 1) | 87fe28331ec0be2d4eef59ca68fbd2055d49304f | 37,422 |
def read_passwords(addr):
""" read passwords as list from a file """
with open(addr) as f:
lines = f.readlines()
pwlist = [clean_word(line) for line in lines]
pwlist = [x for x in pwlist if x != ""]
return pwlist | e2190dee8fe0b5afbc3f0b7e23d7267e837be975 | 37,423 |
def get_model(name, version, project_name=None):
"""
Get a specific model version given a model name and a version.
For example if you run this:
>>> from hops import model
>>> model.get_model('mnist', 1)
You will get version 1 of the model 'mnist'
Args:
:name: name of the model
... | 2e82f7b6703df0313abc29cbadbe6e140a01aeb2 | 37,424 |
def index():
"""Return the home page."""
return render_template('index.html') | 193f867973725dc89f5b213217cb15bc6980a66a | 37,425 |
def generate_scope_name(data_loader):
"""
Generate scope name according to computation graph.
Args:
data_loader (OnnxDataLoader): Data loader instance.
Returns:
list[str], generated scope name.
"""
init_dag = _build_connection(data_loader)
try:
if USER_DEFINED_PATTE... | d57495866f8c100271b2327669b6245409052060 | 37,426 |
import os
def write_jobfile(cmd, jobname, sbatchpath='./sbatch/',
nodes=1, ppn=1, gpus=0, mem=16, nhours=3):
"""
Create a job file.
Args:
cmd : str, Command to execute.
jobname : str, Name of the job.
sbatchpath : str, Directory to store SBATCH file in.
s... | 0493f480fa42eb5dc8d108c59999d8a9430e4669 | 37,427 |
def get_active_questions(netid, course_id):
"""Gets all questions that are not yet being helped
Returns a list of questions with their question text, id, enqueue_time, and the asking student's name
or None if the requester is not a TA
"""
if not verify_is_ta(netid, course_id):
return None
... | 95d670927231e20cbbc9f468dace1ebe6c760eef | 37,428 |
def hamiltonian(edges, directed=False, time_limit=5, concorde=False, precision=0):
"""
Calculates shortest path that traverses each node exactly once. Convert
Hamiltonian path problem to TSP by adding one dummy point that has a distance
of zero to all your other points. Solve the TSP and get rid of the ... | 24a857d2184c20ef00b46fb06aa2a1c87a21299c | 37,429 |
def analytic_kernel(k):
"""Calculate the X4 kernel from the X2 kernel (for proof see appendix in paper)"""
k_size = k.shape[0]
# Calculate the big kernels size
big_k = np.zeros((3 * k_size - 2, 3 * k_size - 2))
# Loop over the small kernel to fill the big one
for r in range(k_size):
for ... | 385ccd1e2ae4906780df909aa2e7830208466e48 | 37,430 |
def simple_3dof_arm(seg1_len, seg2_len, seg3_len, q0, base=None):
"""Creates a simple human-like robotic arm with 7 links and 2 segments
with the desired lengths and starting joint configuration
:param seg1_len: The length of the first segment of the arm
:type seg1_len: int
:param seg2_len: The le... | 8a0c211cf72c764dc8b973c04ce8a045397660c8 | 37,431 |
def collect_nodes(points, highlighted_nodes=[], color='#79FF06', highlighted_color='blue', width=200, highlighted_width=400):
"""
Собирает необходимые нам вершины в нужный формат
Parameters
----------
points : [str, str, ...]
Вершины графа.
highlighted_nodes : [str, str, ...], optional
... | a3a218b5f8c8c25a0f13a4154f12779a84726f9d | 37,432 |
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
conv3x3 = nn.Sequential(
nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False),
nn.BatchNorm2d(out_planes),
nn.ReLU(inplace=True),
)
return conv3x3 | f1c658e9115a741b34ebb9e6c89965d97d18cbf9 | 37,433 |
import typing
import re
from datetime import datetime
import requests
def check_url_content(
url: str, content_match: typing.Optional[re.Pattern] = None
) -> typing.Tuple[str, int, float, bool, datetime.datetime]:
"""
Get URL and return basic information.
Args:
url (str): The URL to check.
... | 4d7643fd812b499254af74b706acb894f28bad4d | 37,434 |
def post_reasoner_query(request_body):
"""Get associations for a given ReasonerAPI query.
:param request_body: The ReasonerStdAPI query in JSON
:return: Results as a ReasonerStdAPI Message
"""
query_graph = request_body["message"]["query_graph"]
print(query_graph)
if len(query_graph["ed... | 14817b6722bf84aaad440d1cc2758794d5f08f63 | 37,435 |
def get_ransac_pipeline():
""" Function return pipeline with lagged transformation in it """
node_ransac = PrimaryNode('ransac_lin_reg')
node_final = SecondaryNode('linear', nodes_from=[node_ransac])
pipeline = Pipeline(node_final)
return pipeline | 4a6e0b21fe35691753885cd509c5344b96f4da67 | 37,436 |
def feature_names_from_extractor_list(feature_extractors):
"""
get a list of feature names from a list of feature extractors
:param feature_extractors: a list of feature extractors
:return: a list of the feature names for each extractor (think first row of .csv file)
"""
feature_names = [feature... | 2f23aa860137e70270e9c7d564df5dacfa1d22a2 | 37,437 |
import os
from shutil import copyfile
def upload_files(local_path, warm_up=False):
"""
upload files to hdfs
"""
remote = os.getenv("OUTPUT_PATH")
job_id = os.getenv("SYS_JOB_ID")
local = local_path.split('/')[-1]
remote_path = "{}/{}/{}/{}".format(remote, job_id, "model", local)
client... | 7f8e8d92f07905de5d399a488f61cfe15e364f71 | 37,438 |
def blank_publish_view(request):
"""Save posts into db w/o publishing."""
return poster(lambda: tasks.fetch_and_publish(force=True, blank=True)) | 6883c038bdfbee7d975134152fd83f61f830b22f | 37,439 |
import io
def read_txt(filename, encoding='utf-8'):
"""Text file reader."""
with io.open(filename, 'r', encoding=encoding) as f:
return f.read() | 2ca0d80bddc49b793e8cbc63c513410154b4d460 | 37,440 |
def level_detect(x, fs, attack_ms=0.1, release_ms=100, mode='peak'):
"""Performs level detection on an input signal
Parameters
----------
x : ndarray
Input vector
fs : float
Sample rate [Hz]
attack_ms : float, optional
Time constant for attack [ms]
release_ms : float... | dacde4e210f2d9d821c26cfc7a2965dbc3bcebe4 | 37,441 |
import copy
def get_doc_permissions(doc, verbose=False, user=None, ptype=None):
"""Returns a dict of evaluated permissions for given `doc` like `{"read":1, "write":1}`"""
if not user: user = frappe.session.user
if frappe.is_table(doc.doctype): return {"read": 1, "write": 1}
meta = frappe.get_meta(doc.doctype)
... | 06698057696dbb6385de951668baddd535ae7b5c | 37,442 |
def get_job_type(name):
"""Returns job type based on its name."""
if 'phase1' in name:
return 'phase1'
elif 'phase2' in name:
return 'phase2'
elif 'dfg' in name:
return 'dfg'
else:
return 'other' | 50db4a7833028b0a0944a4b915d82a8cabf91595 | 37,443 |
def ames_score(emb):
"""
Measure the ames positive probability of molecule,
more close to 1, more "toxic"
Parameters
----------
emb : numpy.ndarray, size (x,512)
the cddd descriptor of molecule
Returns
-------
ames : float
ames score
"""
ames = ames_model.p... | 5dc55dd36c8627ea97314227e9f72e168b488da8 | 37,444 |
def quadrature(func,a,b,args=(),tol=1.49e-8,maxiter=50, reference=False):
"""Compute a definite integral using fixed-tolerance Gaussian quadrature.
Description:
Integrate func from a to b using Gaussian quadrature
with absolute tolerance tol.
Inputs:
func -- a Python function or method to integr... | dc3188ced57ae6d138410bcbd34595f4142f078c | 37,445 |
import argparse
def getargs():
""" Parse program arguments.
"""
parser = argparse.ArgumentParser(
description=DESCRIPTION,
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('ori_lst', type=str,
help='original image list')
parser.add_argumen... | 900eedc7e29f4ff2553a1c9c002f00f4fc9e2cfe | 37,446 |
def read_sensor():
"""Returns the orientation in quaternion form"""
quat = sensor.quaternion
return quat | f8dfc128987f03de35ef9ed7e1bd184919411989 | 37,447 |
def is_resnet(name):
"""
Simply checks if name represents a resnet, by convention, all resnet names start with 'resnet'
:param name:
:return:
"""
name = name.lower()
return name.startswith('resnet') | 6310d849b76a1006c7c2e97405aa9f0ebc53a78b | 37,448 |
from typing import Optional
def _get_object_system_id(obj) -> Optional[str]:
"""Finds the System id (as a string) for the supplied object"""
system_id = None
if isinstance(obj, System):
system_id = obj.id
elif isinstance(obj, BrewtilsSystem):
system_id = ObjectId(obj.id)
elif type... | 40545e2a572954a8ed1e2e81de17e47a7941616c | 37,449 |
import os
def find_closest_config_file():
"""
Returns the location of the closest Verta config file.
Returns
-------
config_filepath: str or None
Path to config file.
"""
for dirpath in get_possible_config_file_dirs():
# TODO: raise error if YAML and JSON in same dir
... | 7bf80befdbcc6d7b907e6e32fde7e3bad40b9499 | 37,450 |
def _regress_1d(design_matrix, boot_mean, boot_var, Nc_list, treatment_idx, **kwargs):
"""
Performs hypothesis testing for a single gene for many bootstrap iterations.
Here, :X_center:, :X_center_Sq:, :boot_var:, :boot_mean: should have the same number of rows
"""
num_boot = boot_mean.shape[1]
nonneg = Fal... | 042f3ea973db7602c7b3e3e712715c39788e1ca4 | 37,451 |
import os
import re
import logging
def convert_output_record(data):
"""Covert data record into a list for output csv
"""
output_record = []
# Participant ID
output_record.append(os.path.basename(data['filename']).replace('.eaf', ''))
# Speaker
output_record.append(data['speaker'])
#... | 046fe65ae63e5559e4bccde5817a4c4f238b0467 | 37,452 |
def handle_pmid_25502872(filename):
"""Bergseng, ..., Sollid. Immunogenetics 2015 [PMID 25502872]"""
return None | 25a11d19293c59e4ae636b0b26389dbfd6b74955 | 37,453 |
def expand_schema_for_inheritance(schema):
"""
Allows the schema to support inheritance.
The schema supports configs that (optionally) point to zero or more parent YAML configs
(using a path) that will be taken as base configurations to be overwritten.
"""
return merge({'inherit': stlistorstring... | 045505ea4634aef392196c1c174fefd8c1b541e6 | 37,454 |
def option_two(choice_two):
"""Functions to for different methods to search the database"""
if choice_two == 1:
query_sub = search_record.search_date()
elif choice_two == 2:
query_sub = search_record.search_time()
elif choice_two == 3:
query_sub = search_record.search_string()
... | 6b1b20f452cfa24eed6c67346215da204a5d3012 | 37,455 |
import re
def parse_fmt(fmt: str) -> (int, int):
"""Parse Q<m>.<n> string
Parameters
----------
fmt
Format string in the form 'Qm.n', where
m is the number of integer bits
n is the number of fractional bits
Returns
-------
n, m
Number o... | f72133fdef9bbf40eb89d977d217376df8f2a3bd | 37,456 |
from typing import Dict
def invert_dictionary(mapping: Dict) -> Dict:
"""Invert the keys and values of a dictionary."""
remap = {v: k for k, v in mapping.items()}
if len(remap) != len(mapping):
raise ValueError("Dictionary cannot be inverted; some values were not unique")
return remap | 911aee48eff3bf0d980e5ad054c77c8a3081e232 | 37,457 |
def store_file(file):
"""Stores the file to specified destination"""
destination = "/".join(["api/test_docs", file.name])
file.save(destination)
return destination | 1118415a1c1b7c2a33ecc539df7bf27dfd783d16 | 37,458 |
import torch
import os
def model_fn(model_dir):
"""Load the PyTorch model from the `model_dir` directory."""
print("Loading model.")
# Determine the device and construct the model.
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
name = 'cnn.pth'
checkpoint = torch.l... | a677b51daed36cd0d1e50c34cd12a7dbb59aa3e8 | 37,459 |
def getNumberedTypedString(items, maxLen=5000, numPrefix=''):
"""get a string that has each item of the list on its own line,
and each item is numbered on the left from zero"""
digits = 0
n = len(items)
while n > 0:
digits += 1
n //= 10
digits = digits
format = numPrefix + '%... | 4fa1f93c420c555093f1fc3b3ba3e43a4ce839f0 | 37,460 |
def mpl_dict(params):
""""Convert _ to . for easier mpl rcparams grid definition"""
return {k.replace('_', '.'): v for k, v in params.items()} | a8c4ae683205a1412a73f00e6965cb345ec63a3e | 37,461 |
def _format_accelerations(pivot_x, pivot_y, is_acceleration, h):
""" Returns the pivot movement as acceleration
The user is allowed to enter the pivot's movement as two functions of time.
If is_acceleration is set to True, these functions are interpreted as
pivot's acceleration. Otherwise, they are int... | 51f57ed84e86939db430b45d87dbf99f5ef5ee36 | 37,462 |
def data_source_get(context, data_source):
"""Return the Data Source or None if it does not exist."""
return IMPL.data_source_get(context, data_source) | 5da4900f1e1099830253293ddf7391279d75c38e | 37,463 |
def add_pseudo_counts(ccm,ad=None,num=None):
"""Add a small number of fake mutations or 'pseudo counts' to the co-clustering and ancestor-descendant matrices for
subchallenges 2 and 3, each in their own, new cluster. This ensures that there are not cases where
either of these matrices has a variance of zero... | f239f26ac0349bb3011b74f8a8d040fb34adb8a9 | 37,464 |
def compute_coefficients(xyz):
"""Fit a plane to the first three dimensions of a matrix
Parameters
----------
xyz : array-like
The matrix of data to fit the plane to.
Returns
-------
np.array
1-dimensional array with four values, the coefficients `a`, `b`, `c`
and `... | 07fb6af0c63a75f2a4e88e2a01836a212b2a8a57 | 37,465 |
def _build_step(
docker_api, variables, build_config, step_config, from_image, should_ignore_cache,
should_remove_container):
"""
Builds the image for the given step
:param docker_api: The api interface that is to be used to connect to the docker daemon
:param variables: The list of var... | 437a279364bd89e83ffb01d39089bf23f2480994 | 37,466 |
from functools import reduce
def Sum(onnx_node, ng_inputs): # type: (NodeWrapper, List[TensorOp]) -> Op
"""Calculate element-wise sum of the input tensors."""
return reduce(ng.add, ng_inputs) | 7d1080e490a4cf6d7d06d0f95c903013df730525 | 37,467 |
def test_df_keys():
"""List of keys to be used for populating a bucket with DataFrames"""
return {
'avro': ['df.avro'],
'csv': ['df.csv'],
'csv.gz': ['df.csv.gz'],
'csv.zip': ['df.csv.zip'],
'csv.bz2': ['df.csv.bz2'],
'csv.xz': ['df.csv.xz'],
'psv': ['df.p... | 3b008664744fb6abf8960caebe658ecc2f6525af | 37,468 |
def first_existing(d, keys):
"""Returns the value of the first key in keys which exists in d."""
for key in keys:
if key in d:
return d[key]
return None | eb9f34f1f5adb0a8e44127fe777e35ca8d36dc04 | 37,469 |
import os
def aseg_stats_subcortical(fspath, subjid):
"""
Returns all the subcortical volumes found in stats/aseg.stats.
Equivalent of load_fs_segstats.m
"""
ignore_seg_names = cfg.freesurfer_subcortical_seg_names_to_ignore
segstatsfile = os.path.join(fspath, subjid, 'stats', 'aseg.stats')... | 36c458c4825802c1f87954ded3d1e5c39e647db2 | 37,470 |
def _expand_right(a, n):
"""Insert multiple axes of size 1 at right end of tensor's shape.
Equivalent to performing `expand_dims(..., -1)` `n` times.
Args:
a: tensor into which extra axes will be inserted.
n: number of inserted axes.
"""
return tf.reshape(a, tf.concat([
tf.shape(a), tf.ones([... | 69a3acb3aa717070ac3e1410c0f30fa71acbc56b | 37,471 |
def unregister_mod(mod: Mod) -> bool:
"""
unregisters a mod from the global cache `mods`
:param mod: mod to unregister
:return: if it successfully unregistered it
"""
if mod.name_or_class_name() not in mods:
return False
get_event_loop().create_task(mod.unloaded())
del mods[mod.... | 48e018ebb2d56fd2e6713a6df4ae3f59160d78a8 | 37,472 |
import os
def resolve_usr_filename(filename):
"""Resolve the filename to an absolute path.
:param filename: The input file name.
"""
full_filename = filename
if os.path.isabs(full_filename) == False:
full_filename = os.path.join(os.path.expanduser("~"),
full_filename)
retu... | e239c80c9e11f79c786557d4de3e1fc51a4f791d | 37,473 |
def errors(module):
""" dict: {name:Exception or None} for tests in module. """
modname = module.__name__
errors = ((k, do(v)) for k, v in all_tests(module))
errors = ((k, v) for k, v in errors if v is not None)
return {f"{modname}.{name}": err for name, err in errors} | d60e604a821b4e56f1b560425157d11bc21c0be7 | 37,474 |
def add_column(graph, results, selector):
"""Add a column to `graph`, produce a new graph.
Args:
graph (:class:`Graph`): Source ArrowProperty graph.
results (:class:`Context`): Results that generated by previous app querying.
selector (str): Used to select a subrange of data of results,... | 947160324c54d7d0d2fb7841513269be53f41642 | 37,475 |
def list_templates(sitename):
"""return a list of template names for this site"""
path = WEBROOT / sitename / '.templates'
if not path.exists():
return []
return sorted([f.name for f in path.iterdir() if f.suffix == '.tpl']) | 05c6501b17ec1d6466aa82e818b95bede51c4713 | 37,476 |
def resample(myarray, shift, include_edge=False):
"""
Resample an array, e.g. duration or start times, with a certain delta step (shift).
Parameters:
myarray -- input array to resample
shift -- unit to shift
Outputs:
myarray -- resampled
"""
ishift = int(shift / (myarray[1]-myarr... | 8bcd3711a5c0c24a37d82b1ea20a730698e5eba1 | 37,477 |
import collections
def from_pyqtgraph_struct(dct):
"""
Get simple structured dict from pyqtgraph params saveState() export.
:param dct: dct = parameters.saveState()
:return:
"""
output = {}
key = dct["name"]
if "children" in dct.keys():
reconstruction_type = "dict"
if... | 1c8d5b9f5fa10d0feb812e13dc3f7a8435958c61 | 37,478 |
def receive_msg(topic):
"""
Decorator
"""
def inner(func):
@sio.on(topic)
async def handle_request(data):
# call 'func' to return the data
func(data)
# returning inner function
return inner | 5e9ccdf39762777850ba94beb9a46167256ebf3b | 37,479 |
def get_requirements():
"""Return a list of package requirements from the requirements.txt file."""
with open('requirements.txt') as f:
return f.read().split() | 85efbe71d02ced7c5987f08a56a1a966bff2e1ef | 37,480 |
def MissalignmentTest(windows):
"""Run the test on the windows passed in"""
refAlignments = {}
#find the controls alligned along each axis
for win in windows:
if not win.ref:
continue
for side in ("top", "left", "right", "bottom"):
sideValue = getattr(win.ref.r... | 77d62d1ba1dcc81170de44c6d92332024eb8a083 | 37,481 |
def integer_to_real_mapper(integers):
"""Define Integer Mapping Function Here(If Needed.)"""
real_numbers = []
range_of_integers = 32767 # each value goes from 0-32767(2 ^ length_of_chromosome)
integer_to_real_number_mapper = 1 / range_of_integers # will produce number between 0-1 when multiplied by ... | 18cc9dc1efe2dd8122d4953a4256cedd5fe234c9 | 37,482 |
import os
def get_feature_normalizer_filename(fold, path, extension='cpickle'):
"""Get normalizer filename
Parameters
----------
fold : int >= 0
evaluation fold number
path : str
normalizer path
extension : str
file extension
(Default value='cpickle')
R... | c2956766f891b6285dfb8b1d5a0a7f36c160351f | 37,483 |
def fake_post_data(target, data_dict):
"""
In order for form to don't fail submission, all permission fields need
to receive values. This function populates data dict with default values
for permissions, making form validation pass
"""
for form in get_permissions_forms(target):
for field... | c9e49956051059a79453c211c7f6fd1ba60c64f4 | 37,484 |
def get_3d_kgrid(fk,alat,nk,exclude_gamma=False):
""" put a k-space function fk onto an FFT grid for inverse Fourier transform
fr = np.fft.ifft(fk)*(alat/nk)**ndim ! Don't forget the normalization! """
kgrid = np.zeros([nk,nk,nk],dtype=complex)
kint_unit = lambda x:kint_to_kvec(x,nk,alat)
for kx in... | a064d5de47c3db4f872baeabba09df3e64cc93e3 | 37,485 |
import torch
def prune_equal_fanin(model: torch.nn.Module, k: int = 2,
validate: bool = True,
device: torch.device = torch.device('cpu')) -> torch.nn.Module:
"""
Prune the dense layers of the network such that each neuron has the same fan-in.
:param model: pyto... | d33271af099f67e5469e3e67534e214b1804cc82 | 37,486 |
def filter_files(file_path, selected=('bacteria', 'virus')):
"""filter files based on filepath"""
base = file_path.stem
for s in selected:
if s in base:
return True
return False | e666d091eb41a128d39238181b9fef0396432cf8 | 37,487 |
import re
import json
async def _parse_at(text: str):
"""
@人格式：“@UID ”(注意最后有空格）
Args:
text (str): 原始文本
Returns:
tuple(str, int[], dict): 替换后文本，解析出艾特的 UID 列表，AT 数据
"""
pattern = re.compile(r"(?<=@)\d*?(?=\s)")
match_result = re.finditer(pattern, text)
uid_list = []
... | ce843adf8e481af0869a055dc1f1d83f1921a74a | 37,488 |
def mask_rcnn(features, mode, params, labels=None, class_targets=None,
box_targets=None, box_rois=None, proposal_to_label_map=None,
detections=None):
"""Mask-RCNN mask model.
This is the mask part of the model (Mask-RCNN), which generates mask outputs.
In addition, it also generates m... | a4ae501c451e8acd69100bb2d806eb203abb89b9 | 37,489 |
from numpy.linalg import inv
from typing import Tuple
def global_phik_from_rebinned_df(data_binned:pd.DataFrame, noise_correction:bool=True, dropna:bool=True,
drop_underflow:bool=True, drop_overflow:bool=True) -> Tuple[np.ndarray, np.ndarray]:
"""
Global correlation values of ... | 70fdbc54cd805e736785351c00f0d02a9c91da21 | 37,490 |
def findInWorkDir(filename):
"""Find a file name in user's work directory."""
return findFile(filename, sciflo.grid.getRootWorkDirFromConfiguration()) | 7a8255ff0bad7651cb30c11a2c998530cc4a8b8a | 37,491 |
import os
import glob
def get_tfrecords(dset_dir, split='train'):
"""Get tfrecords that match training, validation, and test sets.
Works off the TfSet protobuf.
Args:
dset_dir: dataset directory of tfrecords.
split: train or eval.
Returns:
Relevant tfrecords from dset_dir.
Raises:
IOErro... | f014dca8c05bb824c15fe635b186472abe2bae37 | 37,492 |
def VerboseCompleter(unused_self, event_object):
"""Completer function that suggests simple verbose settings."""
if '-v' in event_object.line:
return []
else:
return ['-v'] | e536e221f8f3465f72071d969b11b6623359cf58 | 37,493 |
def jpeg_dynamic_quality(original_photo, use_dynamic_quality=True):
"""Return an integer representing the quality that this JPEG image should be
saved at to attain the quality threshold specified for this photo class.
Args:
original_photo - a prepared PIL JPEG image (only JPEG is supported)
"""... | 1152a1a8e5105ecdcd17b402053dc368cc8f935f | 37,494 |
def load_input_into_list():
"""
Takes our input and returns it into a comprehensive list with split terms
:return: The list of lists for our input
:rtype: list
"""
return [line.replace('-', ' ').replace(':', '').split(' ') for line in open("inputs/day2_01.txt", "r").read().splitlines()] | 9d8f1a313712f11249f4612d38ed9831d666287b | 37,495 |
def isImageValid(img_path: str, min_sz: int = 256):
"""Validates whether the input image fits for the training/test procedure"""
img = Image.open(img_path)
if min(img.size) < min_sz or img.layers != 3:
return False
else:
return True | e7062c0f5f29bda8ab8e400fc8253afb65836c5a | 37,496 |
import os
def SplitClovisTask(task):
"""Splits a ClovisTask in smaller ClovisTasks.
Args:
task: (ClovisTask) The task to split.
Returns:
list: The list of ClovisTasks.
"""
# For report task, need to find the traces first.
if task.Action() == 'report':
trace_bucket = task.ActionParams().get('... | ac855c374274bd4a240f540c6e99184f3ea76cc1 | 37,497 |
import datasets
import torch
import torchvision
def load_cifar5(random_state=42):
"""Loads the datasets for CIFAR5 vs CIFAR5.
In-Distribution: 'dog', 'frog', 'horse', 'ship', 'truck'
Out-of-Distribution: 'airplane', 'automobile', 'bird', 'cat', 'deer'
Args:
random_state (int): The ra... | 95a22a84ba52e83491d48ce818f64ca67cb06f57 | 37,498 |
def MC2000BGetFrequency(hdl,frequency):
""" Get the internal reference frequency
Args:
hdl: the handle of opened MC2000B device
frequency:get internal reference frequency
Returns:
0: Success; negative number: failed.
"""
val = c_int(0)
ret = GetFrequency(hdl,val)
fr... | dff47c645aa0446347c722653f53db2945f73593 | 37,499 |
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