content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def diff_kerning(font_before, font_after, thresh=2, scale_upms=True):
"""Find kerning differences between two fonts.
Class kerns are flattened and then tested for differences.
Rows are matched by the left and right glyph keys.
Some fonts use a kern table instead of gpos kerns, test these
if no gp... | 156b60e132da47e5f25dda68bdd8cb969adaba34 | 49,700 |
def str_tspec(tspec, arg_names):
""" Turn a single tspec into human readable form"""
# an all "False" will convert to an empty string unless we do the following
# where we create an all False tuple of the appropriate length
if tspec==tuple([False]*len(arg_names)):
return "(nothing)"
return "... | eaba40d79561d8f8cdb2c0a3a29dffd62f256217 | 49,701 |
def get_option(prompt: str, options: list[str] = MENU_OPTIONS) -> int:
"""Gets an option from the user and ensures it's valid."""
while True:
option: int = int(input(prompt))
if option > 0 and option <= len(options):
return option
else:
raise ValueError('Not a val... | 211041c437330eab3f50b3bfcb4cfd4881fcd81a | 49,702 |
from datetime import datetime
def form_DateDifferentEmpty(request):
"""
A simple date field but with the ``empty`` attribute value set to todays date
"""
schema = schemaish.Structure()
schema.add('myDateField', schemaish.Date())
form = formish.Form(schema, 'form')
form['myDateField'].widge... | 145e6f48b3a490edc21e39f0ce9fd473957f1f03 | 49,703 |
def render_toolbar(context, config):
"""Render the toolbar for the given config."""
quill_config = getattr(quill_app, config)
t = template.loader.get_template(quill_config['toolbar_template'])
return t.render(context) | 50bce69f078b7a787b009383d055cb638af3c5c9 | 49,704 |
def get_commit_timestamps(commits):
"""Get all commit timestamps for the given ebuild.
Args:
commits (list[Commit]): The commits in question.
Returns:
list[int]: The uprev commit unix timestamps, in order.
"""
return [int(commit.timestamp) for commit in commits] | 72694219664d0d6cf83d793e9ccce2b0642ec89f | 49,705 |
def mask_tokens_after_eos(input_ids, input_masks,
eos_token_id=VatexDataset.EOS, pad_token_id=VatexDataset.PAD):
"""replace values after `[EOS]` with `[PAD]`,
used to compute memory for next sentence generation"""
for row_idx in range(len(input_ids)):
# possibly more than o... | 589b13c266836ca2641f2d796ace1dd8ba001212 | 49,706 |
def xywh_to_xyxy(xywh):
"""Convert [x1 y1 w h] box format to [x1 y1 x2 y2] format."""
if isinstance(xywh, (list, tuple)):
# Single box given as a list of coordinates
assert len(xywh) == 4
x1, y1 = xywh[0], xywh[1]
x2 = x1 + np.maximum(0.0, xywh[2] - 1.0)
y2 = y1 + np.maxi... | 2d6469d309c92354f33cd196be2d24967bf9d966 | 49,707 |
from pathlib import Path
from typing import List
import ast
import re
def get_entry_point(filename: Path, prefix: str, import_path: str) -> List[str]:
"""Returns the entry point string for a given path.
This looks for LIBTBX_SET_DISPATCHER_NAME, and a root function
named 'run'. It can return multiple res... | 02031fe25f58f8aed009c407349cfbfb7002c63f | 49,708 |
def DataUsed_TypeInfo():
"""DataUsed_TypeInfo() -> RTTI"""
return _DataModel.DataUsed_TypeInfo() | b8468185277d98d5190b1d0b697f3471d69764af | 49,709 |
def get_min(filename):
"""
Isolate the minimum search size from a file name.
Example
input: github_notebooks_200..203_p3.json
output: 200
"""
return int(filename.split("_")[2].split("..")[0]) | defc634a9b41ec2c6a4c821014e3c34119c3ea24 | 49,710 |
def scatter_complex(series: pd.Series) -> str:
"""Scatter plot (or hexbin plot) from a series of complex values
Examples:
>>> complex_series = pd.Series([complex(1, 3), complex(3, 1)])
>>> scatter_complex(complex_series)
Args:
series: the Series
Returns:
A string conta... | 75026a609fe1656a80a95115a5caa491ded1fcca | 49,711 |
from typing import Mapping
def get_operations(managed_portfolio: portfolio.Portfolio
) -> Mapping[Text, operation.Operation]:
"""Gets all the position of all assets in the portfolio.
Args:
managed_portfolio: Portfolio from which to obtain operations.
Returns:
Map of portfolio operat... | 28c5fa37482b70aa51ba571f4cbf27286181a7fe | 49,712 |
def commonprefix(m):
"""Given a list of pathnames, returns the longest common leading component without trailing /"""
if not m:
return ""
m = [p.rstrip("/").split("/") for p in m]
s1 = min(m)
s2 = max(m)
s = s1
for i, (c1, c2) in enumerate(zip(s1, s2)):
if c1 != c2:
... | 4d0bb25fd1eb1dbcd4ee28f67b61574751b6e091 | 49,713 |
def edgecolor_by_source(G, node_colors):
""" Returns a list of colors to set as edge colors based on the source node for each edge.
Parameters
----------
G : graph.
A networkx graph.
node_colors : list
List of node colors.
Example
--------
>>> colormap = {'male':... | 961205e100cf208f5471c08afdd8b3c7328713c0 | 49,714 |
def get_random_colors(n, name="hsv", hex_format=True):
"""Returns a function that maps each index in 0, 1, ..., n-1 to a distinct
RGB color; the keyword argument name must be a standard mpl colormap name."""
cmap = plt.cm.get_cmap(name, n)
result = []
for i in range(n):
color = cmap(i)
... | c077e0e143c539766907c961b3246a9fc9ae6ab0 | 49,715 |
def fdwDdz(k,t,a):
"""Function for calculating :math:`\\frac{dt}{dz}` in order to calculate the electric field in x and y direction.
"""
return fdwDdt(k,t)*fdtDdz(a) | eac9405be9e9cf2a44076479b4e1be129b9e39c0 | 49,716 |
import json
import base64
def _load_credentials_file(credentials_file):
"""Load credentials from the given file handle.
The file is expected to be in this format:
{
"file_version": 2,
"credentials": {
"key": "base64 encoded json representation of credentials."... | e01c47db0d1849a70d9623a9a5c4c33c40584d42 | 49,717 |
def __CallStoredProcedure(self, sProcedureName, pArguments):
"""Calls the given SQL stored procedure"""
pRows = None
error_string = ""
locked_state = False
try:
# Acquire the database lock
self.database_lock.Acquire(10)
locked_state = True
# Acquire the cursor and in... | da2cdf71254b38c687b1c3cb0a1771e85ec44341 | 49,718 |
from telegram import Message
from telegram import Update
def effective_message_type(entity):
"""
Extracts the type of message as a string identifier from a :class:`telegram.Message` or a
:class:`telegram.Update`.
Args:
entity (:obj:`Update` | :obj:`Message`) The ``update`` or ``message`` to e... | 5ed152cc88900d1d6167b9cf28637f29099189fc | 49,719 |
from datetime import datetime
def create_post(i):
"""
Helper to create one remote post.
:param i:
:return:
"""
i = i.get('posts')[0]
post = Post()
post.id = i.get('id')
post.author = create_author(i.get('author'))
post.contentType = i.get('contentType')
post.description = ... | c0ff9d105ad7a4ebc78c2c10a29eca7cfd2fcedb | 49,720 |
import os
def parse_internal_field(fn):
"""
parse internal field, extract data to numpy.array
:param fn: file name
:return: numpy array of internal field
"""
if not os.path.exists(fn):
print("Can not open file " + fn)
return None
with open(fn, "rb") as f:
content = ... | 1c7b99a252e631517327e9d84debf5ae0e3df2da | 49,721 |
import pathlib
def get_valid_executable_path_or_empty_path(arg_string: str) -> pathlib.Path:
"""
>>> if lib_detect_testenv.is_doctest_active(): assert get_valid_executable_path_or_empty_path(__main__.__file__) == empty_path
>>> assert get_valid_executable_path_or_empty_path(__file__) == pathlib.Path(__fil... | 9134817cf8e191855f416208bfe329e2a0b66201 | 49,722 |
def _ignore_filter(referrers, ignore, extraids, getid=id):
""" Ignore objects on the referrers list if ignore(x) is true or if x is in extra """
r = []
for ref in referrers:
if ignore is not None:
extraids.update(set([getid(o) for o in ignore(ref)]))
if getid(ref) in extraids: c... | e13a28ba1610de9d6bc835a03cf02a0f6752f7b2 | 49,723 |
def request_fake():
"""Create request with fake i18n subscribers on."""
config = testing.setUp()
config.scan("pyramid_localize.subscribers.fake")
request = Request({})
request.registry = config.registry
return request | 6f6cd5e6388b6ab5d495fabd2d7da0e13f91a4be | 49,724 |
def read_settings(key=None):
"""
Read application settings.
Parameters
----------
key : str, optional
Setting key to read, by default `None`.
Returns
-------
str | dict
If `key` is given, the corresponding value. If key is `None`, return all settings in
a dictio... | c99b13864889f8af9a3f71ab4213f45693236858 | 49,725 |
def navigable_thresh(img, rgb_thresh=(160, 160, 160)):
"""Identify the image pixels that are above the provided threshold. Each
threshold value can range between 0 and 255, with 160 doing a nice job
of identifying ground pixels only.
:param img: Numpy 3d array (x, y, RGB layers)
:param rgb_threh: 3 ... | ba5d927149c26bd96611840250c92a4e844c514f | 49,726 |
def Hbeta(D=np.array([]), sigma=1.0):
"""
Compute the P_ji matrix and the entropy for some data given a sigma value.
Params:
D - Squared difference of two vectors. Must be a numpy array.
sigma - a float
Output:
H, P - Entropy and P_ji matrix
"""
# Compute P-row and corresponding pe... | 3035d88e1db6d0cc46076dc5cdf23fc04e9cf765 | 49,727 |
def gaia_morph(gaia):
"""Retrieve morphological type for Gaia sources.
Parameters
----------
gaia: :class:`~numpy.ndarray`
Numpy structured array containing at least the columns,
`GAIA_PHOT_G_MEAN_MAG` and `GAIA_ASTROMETRIC_EXCESS_NOISE`.
Returns
-------
:class:`~numpy.arra... | 7433d0b148d37c2310d0200bfc3e5af6d2deadbe | 49,728 |
def motherfucking_rainbows(string, inputmode=False, end="\n"):
"""
I cANtT FeELLE MyYE FACECsEE ANYrrMOROeeee
"""
for character in string:
print(choice(colors) + character, end="")
print('\033[0m', end="")
if inputmode:
return input("")
return print(end, end="") | 9359889925841df59b25c964d37349fb3318caf9 | 49,729 |
def comp_joule_losses(self, out_dict, machine):
"""Compute the electrical Joule losses
Parameters
----------
self : Electrical
an Electrical object
out_dict : dict
Dict containing all magnetic quantities that have been calculated in comp_parameters of EEC
machine : Machine
... | cc106b6602424cbd4f55f98da156a557e17e79e2 | 49,730 |
from typing import Tuple
def negative_distances(
negative_mining_strategy: str,
distances: FloatTensor,
negative_mask: BoolTensor,
positive_mask: BoolTensor,
) -> Tuple[FloatTensor, FloatTensor]:
"""Negative distance computation.
Args:
negative_mining_strategy: What mining strategy to... | 64ea23280fd1fce937f9561d5873d3fab0dfc810 | 49,731 |
def get_courses(input_urls: list[str]):
"""
Return course_dict of list of courses
"""
courses = []
for input_url in input_urls:
course_data = get_course_data(input_url)
course_dict = {}
if course_data:
course_dict = get_course_dict(course_data)
courses.app... | d13534fad5e35cd24d179917fc8e8010050fc090 | 49,732 |
import requests
import json
def get_course_info(orgUnitId):
"""Returns basic info for a course offering"""
url = DOMAIN + "/lp/{}/courses/{}".format(LP_VERSION, orgUnitId)
response = requests.get(url, headers=HEADERS)
code_log(response, "GET course offering info org unit".format(orgUnitId))
return... | c7e0d465634a1457623a01c94c77f9b88de5ebb2 | 49,733 |
def process_remove_outliers_ph(df: pd.DataFrame) -> pd.DataFrame:
"""Remove waters with ph <= 1 or ph>13 and potability=1."""
df = df[
~((df["Potability"] == 1) & (df["ph"].apply(lambda x: x <= 1 or x >= 13)))
].copy()
return df | 1ba7615045f4bf2624c355fbf1ddce63f1f80f35 | 49,734 |
import numpy as np
def deserialize_numpy(serialized_np, shape):
"""
Deserializes a numpy array from a JSON-compatible string.
from https://stackoverflow.com/questions/30698004/how-can-i-serialize-a-numpy-array-while-preserving-matrix-dimensions#30699208
Parameters
----------
serialized_np : ... | b8981fc98909eb570e59c36c9c0f003e445e2358 | 49,735 |
import json
def get_field_data_from_room():
"""
1. Get required arguments
2. Call the worker method
3. Render the response
"""
# 1. Get required arguments
args = Eg003Controller.get_args()
try:
# 2. Call the worker method
results = Eg003Controller.worker(args)
exce... | 5c9c95308a3774e547fae1089118517a6d269424 | 49,736 |
def build_tuple_for_feet_structure(quantity):
"""
Builds the tuple required to create a FeetAndInches object
:param quantity: string containing the feet, inches, and fractional inches
:return: tuple containing feet, inches, and calculated fractional inches
"""
feet = float(quantity[0])
inche... | 2a66e7bf859e120d224c097a628445342a987067 | 49,737 |
def _all(itr):
"""Similar to Python's all, but returns the first value that doesn't match."""
any_iterations = False
val = None
for val in itr:
any_iterations = True
if not val:
return val
return val if any_iterations else True | bb1145abaaaa1c6910371178ca5ebe68600bb287 | 49,738 |
def list_plot3d_array_of_arrays(v, interpolation_type, texture, **kwds):
"""
A 3-dimensional plot of a surface defined by a list of lists ``v``
defining points in 3-dimensional space. This is done by making the
list of lists into a matrix and passing back to :func:`list_plot3d`.
See :func:`list_plo... | d3099b55a37f57a9df111b3f8b55033732b1ebcc | 49,739 |
import six
def volume(input, copyFrom=None, rescale=True, voltype=None):
"""
Read an existing geoprobe volue or make a new one based on input data
Input:
input: Either the path to a geoprobe volume file or data to
create a geoprobe object from (either a numpy array or
... | c04a5d5060a0afd25d9b3f12b5d6a207582739ea | 49,740 |
def view_related_developers(request, tag, slug):
"""
Tutorial > View Related Developers
"""
namespace = CacheHelper.ns('tutorial:views:view_related_developers', tag=tag, slug=slug)
response_data = CacheHelper.io.get(namespace)
if response_data is None:
response_data, tutorial = RelatedH... | f36355eb0635dd29edd1fe548ff88f22ec51ffdb | 49,741 |
def compute_neuron_head_importance(task_name,
model,
data_loader,
num_layers,
num_heads,
loss_fct=nn.loss.CrossEntropyLoss(),
... | be0d52c34539db4650aba53c0bb41a958af17ab9 | 49,742 |
def no_init(_data, weights):
"""
Return the entered weights.
Parameters
----------
_data: ndarray
Data to pick to initialize weights.
weights: ndarray
Previous weight values.
Returns
-------
weights: ndarray
New weight values
Notes
-----
Useful ... | f120b49ab26fa1051360b4e4ae85dd07025ae5cc | 49,743 |
def primeFactors(someInt):
"""
return a list of the prime factors of
someInt.
e.g.
primeFactors(24)=[2,2,2,3]
primeFactors(23)=[23]
primeFactors(25)=[5,5]
"""
return "stub" | 4afe8491585721852571ecda89c7cd33fb05d1f7 | 49,744 |
def create_local_gateway_route(client, local_cidr, **route_kwargs):
"""[summary]
Arguments:
client {[type]} -- [description]
local_cidr {[type]} -- [description]
Keyword Arguments:
gateway {[type]} -- [description] (default: {None})
Returns:
OperationResult
"""
... | e7f07f133be40d7eb71a6c40ec610f3ceba3e6c8 | 49,745 |
def validate_ui(self, value):
"""Validate EngineUI objects."""
if not isinstance(value, EngineUI):
reason = 'not an EngineUI object'
raise ValueError(self.msg.format(reason))
return value | dbe3eb7377164a2c98dd875f1e5715a84d613176 | 49,746 |
import uuid
def is_valid_uuid(val):
"""
Check if a string is a valid uuid
:param val: uuid String
:return: Returns true if is a string is a valid uuid else False
"""
try:
uuid.UUID(str(val))
return True
except ValueError:
return False | d04f658d3ae2fa85377e110b0a6716bc34ee9df0 | 49,747 |
def generate_stat_string(stat_distribution, name):
"""generates the gear rating string based on the count of the stat"""
count = stat_distribution.count(name)
extra_line = "\n" if name == "versatility" else ""
return "gear_{0}_rating={1}{2}".format(name, count * config["stats"]["steps"], extra_line) | bab062276be57fbc134bc49c70eda1d96513de86 | 49,748 |
from typing import Tuple
from typing import List
def pad_dialog(
dialog: Dialog, max_dialog_size: int, max_utterance_size: int
) -> Tuple[List[List[int]], List[List[int]], List[List[int]], List[List[int]]]:
"""Pads utterances in a dialog up to max dialog sizes."""
dialog_usr_input, dialog_usr_mask, dialog_sy... | 2456716cd0ffc9b0d8613adb04ff206c250cc0c8 | 49,749 |
from pathlib import Path
import warnings
import shlex
def _make_sbatch_string(
command: str,
folder: tp.Union[str, Path],
job_name: str = "submitit",
partition: tp.Optional[str] = None,
time: int = 5,
nodes: int = 1,
ntasks_per_node: tp.Optional[int] = None,
cpus_per_task: tp.Optional[... | bde05036f280d2cf9b88e2b768bb2b93806682dd | 49,750 |
import warnings
import urllib
def parse_redis_url(url):
"""
Given a url like redis://localhost:6379/0, return a dict with host, port,
and db members.
"""
warnings.warn(
"Use redis.StrictRedis.from_url instead", DeprecationWarning,
stacklevel=2)
parsed = urllib.parse.urlsplit(ur... | 6d24b885feadf58a6f9a17486ba71e4473bce100 | 49,751 |
import numpy
def Torque(cc1,cc2,ccp,g,mass=1.0):
"""
cc1: origin of axis, cc2 head of axis
ccp: point
g: Gradients in Cartasian coordinate, [dx,dy,dz]
"""
torque=0.0
x21=cc2[0]-cc1[0]; y21=cc2[1]-cc1[1]; z21=cc2[2]-cc1[2]
xp1=ccp[0]-cc1[0]; yp1=ccp[1]-cc1[1]; zp1=ccp[2]-cc1[2]
dnom... | d4974f3e5997e44530ad7a1988fe36800d3dad4b | 49,752 |
import io
import tarfile
def write_tar_from_contents(contents, filter=None):
"""Writes a tar file from a dict of archive names to bytes that represent the
contents of each file.
"""
digest = io.BytesIO()
with tarfile.TarFile(mode="w", fileobj=digest) as tar:
for filename, content in conten... | c7918a131ca0038647f0de24198609b1f1e28363 | 49,753 |
def eliminate(values, s, d):
"""Eliminate d from values[s]; propagate when values or places <= 2.
Return values, except return False if a contradiction is detected."""
global counttotalsearches # DGTEMP
counttotalsearches += 1 # DGTEMP
if d not in values[s]:
return values ## Already elim... | 7df68c13c1088933a8601eecbcb3b8bd9aba5d03 | 49,754 |
def non_zero_uniform(shape):
"""Samples in open range (0, 1).
This avoids the value 0, which can be returned by tf.random.uniform, by
replacing all 0 values with 0.5.
Args:
shape: a list or tuple of integers.
Returns:
A Tensor of the given shape, a dtype of float32, and all values in the open
i... | c3c50d26d6c1e87e2c1049c5d2931e73f4c7dd86 | 49,755 |
import os
import torch
def load_detector(device='cpu'):
""" utility function to load a trained detector
"""
this_dir = os.path.dirname(__file__)
cfg.merge_from_file(this_dir + '/w32_256x256.yaml')
# pretrain state_dict by us
state_dict = torch.load(this_dir + '/model_best.pth', map_location=d... | 9c5bbed088763248bdb01aec71858044d6363830 | 49,756 |
def _format_moving_cutoff_predictions(y_preds, cutoffs):
"""Format moving-cutoff predictions"""
if not isinstance(y_preds, list):
raise ValueError(f"`y_preds` must be a list, but found: {type(y_preds)}")
if len(y_preds[0]) == 1:
# return series for single step ahead predictions
retu... | f52d70c72a00a84bcbb35eacf952eaee1e7dbb44 | 49,757 |
import os
def wipe_cluster(cluster, force=False):
""" Deletes data on all datanode and namenode disks.
Options:
force: If set to True, the user is not prompted. Default: no.
username: name of the user who is given permissions to
the storage directories. Default: hdfs
"""... | 177430592fd7ca2c0e1a064ddcedf103eebc6a26 | 49,758 |
import subprocess
def get_bom_contents(bom_file):
"""
Run lsbom on the provided file and return a nested dict representing
the file structure
"""
lsbom = subprocess.Popen(
["/usr/bin/lsbom", bom_file], stdout=subprocess.PIPE
).communicate()[0]
file_list = filter(None,
[ l... | c31c78a936879d7c97830b8c0f5b76b3bb0a07d1 | 49,759 |
import re
def get_possible_modes():
"""Get the set of possible modes."""
modes = set()
with open("web/src/helpers/constants.js", encoding="utf-8") as file_:
# The call to `eval` is a hack to parse the `modeOrder` array from the
# JavaScript source file.
for mode in eval(re.search(r... | 062159e1dffd24296264792fd8cf6e53441fb141 | 49,760 |
def convert_to_hexadecimal(bits, padding):
"""
Converts bits to a hexadecimal character with padding.
E.g.
Converts [False, False, False, True], 0 to "1".
Converts [True, False, False, False], 2 to "08"
Args:
bits: List of boolean values.
padding: Integer of number of ... | b8cd1647a24072278aca65f7734934acd93d8f12 | 49,761 |
import fastapi
from typing import List
async def read_patron_list(
session: aio_session.AsyncSession = fastapi.Depends(
dependencies.get_session),
offset: int = 0,
limit: int = fastapi.Query(default=100, le=100),
current_patron: patron_model.Patron = fastapi.Depends( # pylint: disable=unused-... | 522407fd8b448564d80957b66df58feef3252f99 | 49,762 |
def beta_table(stocks_weights, start, end):
"""
Returns an attribution table for portfolio beta
:param stocks_weights: table of the name of equities in one column, weights in another
:param start: start date
:param end: end date
:return: table
"""
# Due to the nature of the percentchange... | 9cfb5f6658dc1a3d4960bc7451be06c9e48ac9fb | 49,763 |
def sepconv_relu_sepconv(inputs,
filter_size,
output_size,
first_kernel_size=(1, 1),
second_kernel_size=(1, 1),
padding="LEFT",
nonpadding_mask=None,
... | a7f94ec286df89e252262d6ada7031a92d133342 | 49,764 |
import wheel
def convert(context, base_path, rule):
"""
Convert the python representation of a targets file into a python
representation of a buck file.
"""
converters = [
discard.DiscardingConverter(context, 'cpp_binary_external'),
discard.DiscardingConverter(context, 'haskell_ge... | dcaa320255dc4286b73ab3750d465898060a4008 | 49,765 |
import json
def set_review_filters(request):
"""Sets review filters given by passed request.
"""
review_filters = request.session.get("review-filters", {})
if request.POST.get("name", "") != "":
review_filters["name"] = request.POST.get("name")
else:
if review_filters.get("name"):... | 9d9f7e1544e3eea9767f0f85677bcb2b23cdd81c | 49,766 |
import string
def _sanitize_title(title):
""" Remove all non alphanumeric characters from title and lowercase """
alphanumeric = string.ascii_lowercase + string.digits + ' '
title = title.lower()
title = "".join(filter(lambda x: x in alphanumeric, title))
return title | 6f0d1818140bc2a50b160f73b8b4590be8f31891 | 49,767 |
def IsBefore(version, major, minor, revision):
"""Decide if a given version is strictly before a given version.
@param version: (major, minor, revision) or None, with None being
before all versions
@type version: (int, int, int) or None
@param major: major version
@type major: int
@param minor: minor... | 3fe9f995b90d7406d0b0366b0bbe5a940f975893 | 49,768 |
import os
import shutil
from clinica.utils.longitudinal import save_long_id
from clinica.utils.stream import cprint
from clinica.utils.ux import print_end_image
def save_to_caps(
source_dir, image_id, list_session_ids, caps_dir, overwrite_caps=False
):
"""Save `source_dir`/`image_id`/ to CAPS folder.
Thi... | 2ca8425faa6affc6587614dc741e5c37839a62c6 | 49,769 |
def get_pdf_keys(template_pdf):
"""
Helper function for generating pdf form field keys, debugging, etc.
"""
template_pdf = pdfrw.PdfReader(template_pdf)
annotations = template_pdf.pages[0][ANNOT_KEY]
keys = {}
for page in template_pdf.pages:
annotations = page[ANNOT_KEY]
if ... | 1cfb92654cf87d200563f5b08291eed4076721b4 | 49,770 |
def generateRules(L, supportData, minConf=0.7):
"""
生成关联规则
Args:
L 频繁项集列表
supportData 频繁项集支持度的字典
minConf 最小置信度
Returns:
bigRuleList 可信度规则列表（关于 (A->B+置信度) 3个字段的组合）
"""
bigRuleList = []
for i in range(1, len(L)):
# 获取频繁项集中每个组合的所有元素
for freqSet in... | 2ab2c23450cfff8c80f6b2bd9783e73186f1d064 | 49,771 |
def domain_check(f, symbol, p):
"""Returns False if point p is infinite or any subexpression of f
is infinite or becomes so after replacing symbol with p. If none of
these conditions is met then True will be returned.
Examples
========
>>> from sympy import Mul, oo
>>> from sympy.abc impor... | 057665c5de32747a92b09f83831db36665f127c3 | 49,772 |
import math
def makePyramid(elem, graph, levels=4, scale=0.5):
"""
Create a pyramid of num images based upon elem, which becomes the
first child of the new pyramid
"""
p = elem.getparent()
minDim = round(levels / scale)
width = max(int(elem.get(swidth, str(minDim))), minDim)
height = m... | 822f54fcb78673101390d8aaa7bb8aefb022d90c | 49,773 |
import os
import errno
import logging
def get_file_handler(log_dir=None):
"""
This function is responsible for creating a file log handler with a global format and returning it.
Returns:
- (obj): A log handler that is responsible for logging to a file.
"""
log_file_dir = log_dir if log_d... | 10ea32b41f296c2ae458dddbac3ea8dc3a9deba5 | 49,774 |
def parse_negline(neg_line):
"""
Parse the THIRD line of the .mmo file, where the negations are stored.
Why does it not do this per-phrase? Mystery.
We connect the negated-CUI to its appearance in the text using the
ConceptPositionalInfo which _appears_ to correspond to the PosInfo field
which ... | a412add79370a58f6bd00c0139a9fe334e808432 | 49,775 |
import json
def validate_cohort_project_allowed():
"""
Returns true if a valid project is provided. Remote call is set up in
static/js/cohortUpload.js.
"""
project = request.args.get('project')
valid = project in db.get_mw_projects()
return json.dumps(valid) | 79e568d2a8ec8f5541aa5c6ea97aac5d42d80bb5 | 49,776 |
def depthwise_2d_fast(feat, weights):
"""
"""
feat = tf.convert_to_tensor(feat)
weights = tf.convert_to_tensor(weights)
kernel_size = weights.shape.as_list()[0]
return graphics_tf_module.depthwise_conv_fast(feat, weights, kernel_size) | f3aa9989a7c7f4559a1184f19d303187d2d2e594 | 49,777 |
def handle_trace_length(state_trace_length):
"""
transform format of trace length
:return:
"""
trace_length_record = []
for length in state_trace_length:
for sub_length in range(0, int(length)):
trace_length_record.append(sub_length + 1)
return trace_length_record | 39631247d10dbaa024a0e8d553024718150ccc51 | 49,778 |
from time import time
from scipy.signal import fftconvolve
def compute_ts_map(counts, background, exposure, kernel, mask=None, flux=None,
method='root brentq', optimizer='Brent', parallel=True,
threshold=None):
"""
Compute TS map using different optimization methods.
... | ebfc3dada9e0e39ba8bea0c3e36948f5d6ffe134 | 49,779 |
import os
import sys
import json
def init_db_storage():
"""Creates and returns path to empty compilation database.
Terminates script if database already exists."""
working_directory = os.getcwd()
compilation_db_path = os.path.join(working_directory, DB_FILENAME)
if os.path.lexists(compilation_db_... | 2c3c10b49d73a4969f9d72e0db9282a62e89173f | 49,780 |
import sound
def audio_duration(filename):
"""
duration of a audio file (usually mp3)
Parameters
----------
filename : str
must be a valid audio file (usually mp3)
Returns
-------
duration in seconds : float
Note
----
Only supported on Windows and Pythonista. On ... | 6d51619957c6a6dc96eb1b3647bfe2176ae080fd | 49,781 |
def is_moderator(request, view):
"""
Helper function to check if a user is a moderator
Args:
request (HTTPRequest): django request object
view (APIView): a DRF view object
Returns:
bool: True if user is moderator on the channel
"""
user_api = request.channel_api
cha... | 31c8b53c28b3972a731b87b13177b3c01c45ade4 | 49,782 |
def monkeypatch(monkeypatch):
"""Adapt pytest's monkeypatch to support stdlib's pathlib."""
class Monkeypatcher:
"""Middle man for chdir."""
def _chdir(self, value):
"""Change dir, but converting to str first.
This is because Py35 monkeypatch doesn't support stdlib's p... | d7da33204cd0a2f07f51b47b95f106e053c28c1f | 49,783 |
def binom(n, k):
"""
Obtain the binomial coefficient, using a definition that is mathematically
equivalent but numerically stable to avoid arithmetic overflow.
The result of this method is "n choose k", the number of ways choose an
(unordered) subset of k elements from a fixed set of n elements.
... | b322712d1757df543ccdc92ffc7f883504804346 | 49,784 |
def no_auth(request):
"""
Use this if no auth is desired
"""
return request | 5871518399aee8204d2ece4c8bad575527270627 | 49,785 |
def bilstm_layer_cudnn(input_data, num_layers, rnn_size, keep_prob=1.):
"""Multi-layer BiLSTM cudnn version, faster
Args:
input_data: float32 Tensor of shape [seq_length, batch_size, dim].
num_layers: int64 scalar, number of layers.
rnn_size: int64 scalar, hidden size for undirectional L... | 6f55275787e7e5f68004cb5b5173008ab34ae6f1 | 49,786 |
from typing import Tuple
def calculate_smoothed_trends(
case_counts: np.ndarray,
death_counts: np.ndarray,
hosp_counts: np.ndarray,
smoothing_window: int) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
"""
Calculates the smoothed trends with the given smoothing window
:param case_counts: Cases per day
:par... | c8fc0ef3a071bb04c86bbed1e27d04a505b094ea | 49,787 |
def generate_swagger_params(crown: ViewCrown, swagger_params: dict) -> dict:
"""
assemble params for swagger_auto_schema by crown
"""
default_params = {}
if crown.body_in:
default_params = {"request_body": crown.get_in_serializer_instance()}
elif crown.query_in:
default_params = ... | dc91db1a6e9317a4b45346e6829df1d4d195a18c | 49,788 |
def total_size(metainfo):
"""
Compute sum of all files' size
"""
if metainfo.has_key('files'):
total = 0
for infile in metainfo['files']:
if infile.has_key('length'):
total += infile['length']
return total
else:
return None | 84deea16534e35f2c3c86c9674a8e83f880bd5a5 | 49,789 |
def diffmap(adata, **kwargs):
"""\
Scatter plot in diffmap basis.
Parameters
----------
{scatter}
Returns
-------
If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it.
"""
return scatter(adata, basis="diffmap", **kwargs) | f304e66f76fa143ff7102eec5388749c6e6014fe | 49,790 |
import random
import string
def makeHTMLword(body, fontsize):
"""take words and fontsize, and create an HTML word in that fontsize."""
#num = str(random.randint(0,255))
# return random color for every tags
color = 'rgb(%s, %s, %s)' % (str(random.randint(0, 255)), str(random.randint(0, 255)), str(rando... | 00bb65217f4b75344a38100cee88c1e928aa0698 | 49,791 |
def sigma_x_rk_new(
thickness,
radius,
length,
f_y_k,
fab_quality=None,
flex_kapa=None
):
"""
Meridional characteristic buckling stress.
Calculates the characteristic meridional buckling stress for a cylindrical shell according to EN1993-1-6 [1].
Paramet... | fc79d852b8878757d7e5e2eb794a1507986bb0cb | 49,792 |
import os
import subprocess
import sys
def exec_command(command, cwd=None, stdout=None, env=None):
"""Returns True in the command was executed successfully"""
try:
command_list = command if isinstance(command, list) else command.split()
env_vars = os.environ.copy()
if env:
... | 5849fd97dfa08d8402f08e730c3364d2c1e0d15c | 49,793 |
def ts_grismc_sim(pixels):
"""
Simple analytic wavelength calibration for Simulated GRISMC data
"""
disp = 0.0010035 ## microns per pixel (toward positive X in raw detector pixels, used in pynrc)
undevWav = 4.0 ## undeviated wavelength
undevPx = 1638.33
wavelengths = (pixels - undevPx) ... | f3491fea1fa1e8833384711076e6187f0f6cb42b | 49,794 |
from typing import Callable
def get_admin_principal_by(authentication_manager: AuthenticationManager) -> Callable[[Request], PrincipalService]:
"""
admin only
"""
return get_principal_by(authentication_manager, [UserRole.ADMIN]) | 8737f6a271d766560cb2f5c17e271d297c520195 | 49,795 |
def get_profile_avatar_upload_to(instance, filename):
""" Returns a valid upload path for the avatar associated with a forum profile. """
return instance.get_avatar_upload_to(filename) | 840e7482b225c0a456dbc8cd967203aa542945f8 | 49,796 |
from typing import Optional
def calc_r(alphas: np.ndarray, colvars: np.ndarray,
calc_jac: bool) -> tuple[np.ndarray, Optional[np.ndarray]]:
"""
Calculate linear combination of reaction coordinates given a weights vector
and colvars matrix. Also returns the jacobian with respect to the alphas if... | 2e14ddd98c296eb0250ff59cc84597594873c383 | 49,797 |
def discretized_exponential(lamb, up_bound, steps):
""" Exponential distribution on discretized interval [0, up_bound] """
return discretized_state(lambda x: stats.expon.pdf(x, scale=1 / lamb),
0, up_bound, steps) | 8ed948c7e7652fa15aefd41f02470864dfd5d1df | 49,798 |
def timedelta_to_string(dt):
"""
Return hh:min:sec from a timedelta64.
There doesn't seem to be a standard pandas or numpy function to
do this strangely.
"""
total_sec = dt / np.timedelta64(1, 's')
hours = int(total_sec // 3600)
minutes = int((total_sec // 60) % 60)
seconds = int(to... | 2615dc0f54272183325ddc441d8f489f323c1cfb | 49,799 |
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