content stringlengths 39 14.9k | sha1 stringlengths 40 40 | id int64 0 710k |
|---|---|---|
def get_workitem_id_from_task_name(task_name: str):
"""Parse the Task Name to get the Work Item ID"""
return task_name.split(" ")[0] | 2f5c22b02fc132e319404fb43f444f9f2044315e | 30,627 |
import torch
def get_model(model='PGAN', dataset='celebAHQ-512', use_gpu=True):
"""Returns a pretrained GAN from (https://github.com/facebookresearch/pytorch_GAN_zoo).
Args:
model (str): Available values are "PGAN", "DCGAN".
dataset (str: Available values are "celebAHQ-256", "celebAHQ-512', "... | bb8df4164d27566960acf01d3664b3802d0c4fe7 | 30,628 |
import re
def __expand_ranges(expression: str) -> str:
"""Expand ranges in a given expression.
Args:
expression: The expression to expand.
Returns:
The expression with ranges expanded.
"""
# Find {n}..{n} in the expression.
pattern = re.compile("(\\d+)\.\.(\\d+)")
# Exp... | 3563e4b452d49eca3c04ace0e796a14a7347700a | 30,632 |
def fmtcols(mylist, cols):
"""Generate a string of tab and newline delimited columns from a list
"""
lines = ("\t".join(mylist[i:i + cols])
for i in range(0, len(mylist), cols))
return '\n'.join(lines) | 5f83aa16039edafa6789c8cd1580ff45ae495f67 | 30,637 |
def split_list(l: list, n: int = 1) -> list:
"""Split list into n parts"""
length = len(l)
split = []
for i in range(n):
split.append(l[i*length // n: (i+1)*length // n])
return split | 76bfc987dca606fda945a3222a852d0c0c8489db | 30,638 |
def get_start(maze):
"""Searches for the 1 inside the maze.
Returns:
The row and column of the found 1.
E.g. if 1 was in row 3 and column 4, this would return:
3, 4
If there is no 1 in the maze, this returns
-1, -1
"""
for y, row in enumerate(maze):
... | f2561d9af924eb28c86807e079c9515f8c395bf1 | 30,641 |
def get_nonzero_either_mask(vector_a, vector_b):
"""Returns a numpy array of boolean values indicating where values in two
vectors are both greater than zero.
Parameters
----------
vector_a : numpy.ndarray
Array of counts or RPKM
vector_b : numpy.ndarray
Array of counts or RPKM... | 82f7433bcbcfcfc799b46083b112a9a7abcab918 | 30,642 |
def get_setting_name_and_refid(node):
"""Extract setting name from directive index node"""
entry_type, info, refid = node['entries'][0][:3]
return info.replace('; setting', ''), refid | f72908c1f3adfc1d37f4760a240f68c66031dc19 | 30,643 |
import csv
def get_func_rep(thresh_results, input_comps, conf_values = True):
"""
Find the functional representation of a set of components based on the results of data mining
Parameters
----------
thresh_results : dict
The return dictionary from the "get_top_results" function
input_c... | a24d2f4833330dbcc33a422225e517e29b38f868 | 30,644 |
def version_sum(packet: dict) -> int:
"""
Recursively calculate the sum of version numbers in packet.
"""
return packet["version"] + sum(version_sum(sub) for sub in packet["subpackets"]) | 2559e2531c59d93f6bd00a625e7a1e21c6bdeaa1 | 30,645 |
import pickle
def load_clf(trained_mod):
"""Load a trained model from pickle file.
Args:
trained_mod (str): file path to pickle file.
Returns:
sklearn.classifier: A trained sklearn classifier.
"""
# save model with open(wb) + pickle.dump.
with open(trained_mod, 'rb') as ... | 21a9dbd4e5455e8909ed0f46b78cd5fb7d161b04 | 30,646 |
def r_perimeter(l, b):
"""Function for calculating Perimeter of Rectangle"""
return 2 * (l + b) | 7860ebc843faf55a3ad893f4359e802775260a0f | 30,648 |
def tree_pop_fields(root, fields):
"""deletes given fields (as iterable of keys) from root and all its children (recursively)
returnes updated root """
for f in fields:
root.pop(f)
if root['is_leaf']: return root
for i in range(len(root['children'])):
root['children'][i]['child'] = t... | 1dca88301219ad2a9c83642024ab0db08472b507 | 30,652 |
from typing import Tuple
from typing import Callable
def interpolate(p1: Tuple[int, float], p2: Tuple[int, float]) -> Callable[[int], float]:
""" Returns a function that linearly interpolates between these two points.
Implements the equation given in https://mathworld.wolfram.com/Two-PointForm.html
Args:
p1: ... | 2196e99e1ae22328d45047474cd5d5b092ee01ce | 30,653 |
def count(value, node):
"""
Count number of list elements that match a value
:param value: value to search for
:param node: value of head node, start of list
:return: int: number of elements that match the value
"""
if node is not None:
if value == node.value: # basically same as l... | 05ffe8ce83e3fff981d8953090f6615463627e43 | 30,656 |
import torch
def clamp(image, min=0., max=1.):
"""Clamp values in input tensor exceeding (min, max) to (min, max)"""
return torch.clamp(image, min, max) | 4b7fe6100d0e85a7ee1ae00a53df5a6616bd65c9 | 30,658 |
def split_out_internet_rules(rule_list):
"""Separate rules targeting the Internet versus normal rules"""
normal_rules = filter(lambda x: x.target_zone != 'internet', rule_list)
internet_rules = filter(lambda x: x.target_zone == 'internet', rule_list)
return list(normal_rules), list(internet_rules) | aa838ef7655658b3255c127f392c536bceb5a3bd | 30,661 |
def _get_response_status(response) -> int:
"""Get the HTTP status code from any type of response object."""
if hasattr(response, "status"):
# aiohttp-style
return response.status
elif hasattr(response, "status_code"):
# starlette-style
return response.status_code
raise Ty... | 1a9286db6277601240545e36c4a51536555a83d0 | 30,669 |
import click
def pywbem_error_exception(exc, intro=None):
"""
Return the standard click exception for a pywbem Error exception. These
exceptions do not cause interactive mode failure but display the exception
class and its str value and return to the repl mode.
Parameters:
exc (Exception)... | 3d99a69857d99e3e7c579a7e9be147574c9baf67 | 30,675 |
def getbinlen(value):
"""return the bit length of an integer"""
result = 0
if value == 0:
return 1
while value != 0:
value >>= 1
result += 1
return result | 523772f1c5eb856bff831e1565b2ff47fc19b2ff | 30,679 |
def calculate_mean(some_list):
"""
Function to calculate the mean of a dataset.
Takes the list as an input and outputs the mean.
"""
return (1.0 * sum(some_list) / len(some_list)) | d0374fc5321f6caa05f546e274490e906bf60106 | 30,681 |
def merge_media(forms, arg=None):
"""Merge media for a list of forms
Usage: {{ form_list|merge_media }}
* With no arg, returns all media from all forms with duplicates removed
Usage: {{ form_list|merge_media:'media_type' }}
* With an arg, returns only media of that type. Types 'css' an... | e4885524e3ac6c8598f485f55fa915b6a4874001 | 30,683 |
import re
def split_filenames(text):
"""Splits comma or newline separated filenames
and returns them as a list.
"""
names = [name.strip()
for name in re.split(r'[\n,]', text)]
return list(filter(None, names)) | 85d53b77a81d6c1133068932a510ff3c9087a3cd | 30,684 |
from typing import Dict
def _is_import_finished(log: Dict) -> bool:
"""Returns whether the import has finished (failed or succeeded)."""
return log['state'] not in ('QUEUED', 'RUNNING') | 4dbb9ee522b210781bbc25542dd1ab86dc0cd397 | 30,690 |
from typing import Dict
def _query_dict_to_qs(dic: Dict[str, str]) -> str:
"""
{'k1': 'v1', 'k2': 'v2'} -> ?k1=v1&k2=v2
"""
if not dic:
return ''
return '?' + '&'.join(f'{k}={v}' for k, v in dic.items()) | 27e9d7de3da75a9ed589d2a40a00b6cc2461afcd | 30,691 |
def extents_overlap(a_extent, b_extent):
"""Test if two extents overlap"""
if (a_extent.xmin > b_extent.xmax or
a_extent.xmax < b_extent.xmin or
a_extent.ymin > b_extent.ymax or
a_extent.ymax < b_extent.ymin):
return False
else:
return True | 09f30e3982fd139b4208501236c2a0fc4a413b96 | 30,693 |
def get_high_lows_lookback(high, low, lookback_days):
"""
Get the highs and lows in a lookback window.
Parameters
----------
high : DataFrame
High price for each ticker and date
low : DataFrame
Low price for each ticker and date
lookback_days : int
The number of ... | d24905db2ae2425f7d57e3af503802c597d0c212 | 30,698 |
def _get_weights(model, features):
"""
If the model is a linear model, parse the weights to a list of strings.
Parameters
----------
model : estimator
An sklearn linear_model object
features : list of str
The feature names, in order.
Returns
-------
list of str
... | f26947922505cb3c06f1421238fdcde11064a686 | 30,705 |
import socket
def is_port_available(port: int, udp: bool = False) -> bool:
"""Checks whether a specified port is available to be attached to.
From `podman_compose <https://github.com/containers/podman-compose/blob/devel/podman_compose.py>`_.
Args:
port (int): The port to check.
udp (bool... | a963ad45477fc43bca1a356c6b76f8995f7df60b | 30,706 |
def remove_character_at(str, idx):
"""Removes the character from str at index idx, returning the remaining string
str, int -> str
>>> remove_character_at("boats", 2)
'bots'
"""
return str[:idx] + str[idx+1:] | abc7bedb33c5c9e024dd8cf5830f3b3ee8b08f42 | 30,708 |
def get_scope(field):
"""For a single field get the scope variable
Return a tuple with name:scope pairs"""
name = field['name']
if 'scope' in field['field']:
scope = field['field']['scope']
else:
scope = ''
return (name, scope) | 1b931ec1a7c5a629fe6b39034c23fd02568ed5a7 | 30,724 |
import torch
def quantile_features(density, q_vals):
"""
Input
- density: tensor of shape [n_samples]
- q_vals: list of numbers between 0 and 1 with the quantiles to use
Output
- quartile_sigs: tensor of shape [len(q_vals)]
"""
q_vals = torch.tensor(q_vals, dtype=density.dtype... | f720125b43250403a6164b7a94bd97f25cfea422 | 30,727 |
def And(s1, s2):
""" And(s1, s2) returns a new selector that selects a node only if BOTH
s1, and s2 select the node."""
return lambda x: s1(x) and s2(x) | 2de67c6b7109bf6b12c187f85bf8ca4483289156 | 30,728 |
def get_cell(caves, row, col):
"""Get (row, col) cell in caves."""
return caves[row][col] | 743068c3be8e0e60b56cc8f0c9c99a0cea07e4c2 | 30,731 |
def namebunch(abunch, aname):
"""give the bunch object a name, if it has a Name field"""
if abunch.Name == None:
pass
else:
abunch.Name = aname
return abunch | d3a32d578ef604760d1f5adb009c96de519f0ec3 | 30,737 |
def convert_bytes_to_bits(byte_value):
""" Convert input bytes to bits """
return byte_value * 8 | e6cda98e84b133dc48a19ebc3e98e79bd577bf47 | 30,740 |
import random
def _drawRandom(nbToDraw, maxValue, exclusion=None):
"""Draws random numbers from 0 to maxValue.
Args:
nbToDraw (int): number of numbers to draw
maxValue (int): max value for the numbers to draw
exclusion (set): numbers to exclude
"""
numbers = set()... | 24e44dc52cce7722bb1074b747457fc160912664 | 30,753 |
def get_bound(atom, bound=None):
"""
Return appropriate `bound` parameter.
"""
if bound is None:
bound = atom.bound
if bound is None:
raise ValueError('either atom must be in bound '
+ 'mode or a keyword "bound" '
+ 'argument must be ... | f9223945011fbc056db170a943cf33fb09662920 | 30,761 |
import math
def solve_tangent_angle(distance, radius):
"""
Helper function to calculate the angle between the
centre of a circle and the tangent point, as seen from
a point a certain distance from the circle.
:Parameters:
distance: float
Distance of point from centre of ... | 6db4a340f50d0fd426dbae3e2248624cc3c50563 | 30,766 |
import uuid
def _obtain_signed_blob_storage_urls(self, workspace_id, id_count=1, blob_path=None):
"""Obtain a signed blob storage url.
Returns:
[dict]: blob storage urls
[dict]: blob storage ids
"""
blob_url = f'{self.HOME}/{self.API_1}/project/{workspace_id}/signed_blob_url'
if ... | e6fa3e492930162ff7963ce0a8aedc2d91bd3583 | 30,773 |
import re
def gettime_s(text):
"""
Parse text and return a time in seconds.
The text is of the format 0h : 0.min:0.0s:0 ms:0us:0 ns.
Spaces are not taken into account and any of the specifiers can be ignored.
"""
pattern = r'([+-]?\d+\.?\d*) ?([mμnsinh]+)'
matches = re.findall(pattern, te... | 49f315b9f92dc04eea450f7d8b93a7f9bd08da14 | 30,774 |
def convert_openlayers_roi_to_numpy_image_roi(roi: list, image_height: int) -> list:
"""In both openlayers and numpy, the same roi format applies
Args:
roi (list): roi in format [x, y, width, height]
image_height (int): height of the original image from which the roi is cropped
Returns:
... | 6fe3247b0b1dcc7a9f9da23cbde1e42d71199d88 | 30,775 |
def _adjust_map_extent(extent, relocate=True, scale_ratio=1):
"""
Adjust the extent (left, right, bottom, top) to a new staring point and
new unit. extent values will be divided by the scale_ratio
Example:
if scale_ratio = 1000, and the original extent unit is meter, then the
unit is ... | ee1d6c4195daab7cc8473b05f334357d25b5b7b5 | 30,776 |
def fbexp(db, dp, rhog, rhos, umf, us):
"""
Bed expansion factor for calculating expanded bed height of a bubbling
fluidized bed reactor. See equations 14.7 and 14.8 in Souza-Santos [1]_.
Parameters
----------
db : float
Diameter of the bed [m]
dp : float
Diameter of the bed... | c78b94639f1d6835ee490636e85d49f04b09ebe1 | 30,780 |
from typing import List
def write_floats_10e(vals: List[float]) -> List[str]:
"""writes a series of Nastran formatted 10.3 floats"""
vals2 = []
for v in vals:
v2 = '%10.3E' % v
if v2 in (' 0.000E+00', '-0.000E+00'):
v2 = ' 0.0'
vals2.append(v2)
return vals2 | 7e2f9b1a9e4560d3d9194c18601d22a57ed0811e | 30,782 |
def dup_integrate(f, m, K):
"""
Computes the indefinite integral of ``f`` in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, QQ
>>> R, x = ring("x", QQ)
>>> R.dup_integrate(x**2 + 2*x, 1)
1/3*x**3 + x**2
>>> R.dup_integrate(x**2 + 2*x, 2)
1/12*x**4 + 1/3*x**3
... | 0f1981d699c4c80b61d4f0aececa1ccc4601712b | 30,783 |
from typing import Dict
import torch
def inputs_to_cuda(inputs: Dict[str, torch.Tensor]):
"""
Move tensors in the inputs to cuda.
Args:
inputs (dict[str, torch.Tensor]): Inputs dict
Returns:
dict[str, torch.Tensor]: Moved inputs dict
"""
if not torch.cuda.is_available():
... | 1c67e915463ea04b2df03f3697a2eb83dedb07a2 | 30,784 |
def pruneNullRows(df):
"""
Removes rows that are all nulls.
:param pd.DataFrame df:
This is done in place to avoid storage problems with large dataframes.
:return pd.DataFrame:
"""
return df.dropna(axis=0, how='all') | af0a34bed71f937d6ff970f521d5f82720fffdc9 | 30,785 |
def load_ed25519_vectors(vector_data):
"""
djb's ed25519 vectors are structured as a colon delimited array:
0: secret key (32 bytes) + public key (32 bytes)
1: public key (32 bytes)
2: message (0+ bytes)
3: signature + message (64+ bytes)
"""
data = []
for line in vec... | 618ea06c408d131664bbfe0b4350fee5e6a3edd0 | 30,786 |
from bs4 import BeautifulSoup
def parse_html(html: str) -> BeautifulSoup:
"""Parse the HTML with Beautiful Soup"""
return BeautifulSoup(html, features="html.parser") | 8e10667747f24b9f9790b2b512bc9d5635ec7cd9 | 30,787 |
import hashlib
def convert_email(email):
""" MD5 hash the email address """
email = email.strip().encode('utf-8').lower()
return hashlib.md5(email).hexdigest() | a556147ffb9111b6001c4d76f6cd82c3442e115e | 30,788 |
def get_n_lines(fin: str, size: int = 65536) -> int:
"""Given a filename, return how many lines (i.e. line endings) it has.
:param fin: input file
:param size: size in bytes to use as chunks
:return: number of lines (i.e. line endings) that `fin` has
"""
# borrowed from https://stackoverflow.com... | 0259c71681a9779e3df311ff03010262ded8f058 | 30,790 |
def auth_token(pytestconfig):
"""Get API token from command line"""
return pytestconfig.getoption("token") | 419a0e617f242ac9b657b7b397e8b06e447a7efe | 30,796 |
def conv_params(sz_in: int, sz_out: int):
"""Solves for filter_size, padding and stride per the following equation,
sz_out = (sz_in - filter_size + 2*padding) / stride + 1
Attempts to find a solution by iterating over various filter_size, stride and padding
in that order. If no solution is foun... | 86c1a2437231d2fb6515a6581719d3568cdee813 | 30,799 |
def get_model_io_names(model):
"""Gets names of the input and output nodes of the model
Args:
model (keras Model): model to parse
Returns:
inputs (list): names of all the input nodes
outputs (list): names of all the output nodes
"""
num_inputs = len(model.inputs)
num_o... | b8bc93bd2bf01597b16eaee5bc0f1a210e185dbe | 30,800 |
def get_value(input_data, field_name, required=False):
"""
Return an unencoded value from an MMTF data structure.
:param input_data:
:param field_name:
:param required:
:return:
"""
if field_name in input_data:
return input_data[field_name]
elif required:
raise Excep... | 3e4ec623528f279a61b5ad9897935a5fda8af2d1 | 30,806 |
def seconds_to_string(seconds):
"""
Format a time given in seconds to a string HH:MM:SS. Used for the
'leg time/cum. time' columns of the table view.
"""
hours, seconds = divmod(int(seconds), 3600)
minutes, seconds = divmod(seconds, 60)
return f"{hours:02d}:{minutes:02d}:{seconds:02d}" | 23db1370e887a9dad3d6dbd40bc2f25c244f1f77 | 30,807 |
def get_min_max(arr):
"""
Return a tuple(min, max) out of list of unsorted integers.
Args:
arr(list): list of integers containing one or more integers
Returns:
(int, int): A tuple of min and max numbers.
"""
if len(arr) == 0:
return None, None
min_number = max_number ... | d7cd2304092c766bfd0ffcb2235e7ad0c6428e61 | 30,814 |
def size_for(s):
"""
This function takes a string representing an amount of bytes and converts
it into the int corresponding to that many bytes. The string can be a plain
int which gets directly converted to that number of bytes or can end in a specifier
such as 100k. This indicates it is 100 kiloby... | 3e88f0555f0ab1b06432d87c5ebca7f33b24d1c7 | 30,816 |
def _is_whitenoise_installed() -> bool:
"""
Helper function to check if `whitenoise` is installed.
"""
try:
return True
except ModuleNotFoundError:
pass
return False | 3732d32de4fae1d9f65baeb481c9eb6a6dcdd7bd | 30,820 |
def sanitize_version_number(version):
"""Removes common non-numerical characters from version numbers obtained from git tags, such as '_rc', etc."""
if version.startswith('.'):
version = '-1' + version
version = version.replace('_rc', '.')
return version | 4627ce6ad06046b575da3a272e8d8acc41183000 | 30,822 |
def get_cells(worksheet, get_range: str):
"""
Get cells from sheet
params
------
workbook: openpyxl.WorkSheet
loaded worksheet.
get_range: str
Get cells range.
Ex: "A1:B3"
return
------
cells: Tuple[Cell]
Got cells tuple
"""
cells = worksheet[... | 179c20419975daac5913b149efb60b4cc22537d9 | 30,825 |
import torch
def ent_loss(probs):
"""Entropy loss"""
ent = -probs * torch.log(probs + 1e-8)
return ent.mean() | 4ccd777d3b434b3d1c79f36c735cf6252d749587 | 30,827 |
def IPRange(first, last):
"""
Generate a list of IP addresses
Args:
first: the first IP in the range
last: the last IP in the range
Returns:
A list of IPs from first to last, inclusive (list of str)
"""
all_ips = []
ip = first
while ip <= last:
all_ip... | 16bd7302b02e0b15b85edb8a60bfc7749744b3fe | 30,828 |
from datetime import datetime
def python_type_to_sql_type(_python_type):
"""
Convert a python data type to ab SQL type.
:param _python_type: A Python internal type
"""
if _python_type == str:
return 'string'
elif _python_type == bytes:
return "blob"
elif _python_type == fl... | d74c0a8e8b1ef2340e1fc1decddcd60aba718570 | 30,832 |
import re
def string_to_list(s):
"""Return a list of strings from s where items are separated by any of , ; |"""
try:
return [text for text in re.split(r'\s*[,;\|]\s*', s) if text]
except TypeError:
if type(s) == list:
return s
raise | 4e679bfaf0d51120a2194a4db173d34a9eaf47d0 | 30,834 |
def standardise_name(name):
"""
Standardise field names: Survey (Title) -> survery_title
"""
result = name.lower().replace(" ", "_").replace("(", "").replace(")", "")
# remove any starting and ending "_" that have been inserted
start_loc = 1 if result[0] == "_" else 0
loc = result.rfind("_"... | af9c5b52c1c7fc86ea758cb29dabb2f6405bb16e | 30,836 |
from typing import Iterable
def check_all_dicts(iterable_dict: Iterable[dict]):
"""Check if Iterable contains all dictionaries
Args:
iterable_dict (Iterable[dict]): Iterable of dictionaries
"""
# Check if dict
def check_dict(d):
return isinstance(d, dict)
# Check if all insta... | 0e87989d600d303e9bdadf04725c398841bcd214 | 30,839 |
def _get_timezone_name(timezone):
"""
Return the offset for fixed offset timezones, or the name of timezone if
not set.
"""
return timezone.tzname(None) or str(timezone) | 4cb02cdf53269b328c727eaa11c3d16acd99e3bb | 30,841 |
def trailing_silence_mask(f0):
"""
>>> f0 = torch.tensor([1.0, 2.0, 0.0, 1.0, 0.0, 0.0, 0.0])
>>> trailing_silence_mask(f0)
tensor([False, False, False, False, True, True, True])
"""
assert f0.ndim == 1
mask = ((f0.flip(0) != 0.0).cumsum(0) == 0).flip(0)
return mask | 03c76e96a94d9c80ca9ab38e5ce735bc161d1929 | 30,847 |
def df_if_two_one(value):
""" Final Data Cleaning Function
- This is run against station, latitude, longitude, and elevation for indidividual records
- Many of these records have usable data, so don't want to just throw them out.
- Example issues:
- Instead of a station of '000248532' a valu... | c417c683e2cedb37b2c557a78e358112f060edfe | 30,848 |
import hashlib
def hex_hash(path):
"""
Return the first 2 hex digits of the md5 of the given path.
Suitable for creating sub dirs to break up a large directory
"""
return hashlib.md5(path).hexdigest()[:2] | b3629cd8034e1944cdb3998592d1caca96deacb9 | 30,851 |
def get_manhattan_distance(node):
"""Function to calculate the manhattan distance for a
particular configuration
Parameters
----------
node : [list]
[list to check for the heuristics]
Return
------
[int]
[returns the heuristic distance for a particular node]
"""
... | 99d2b8828babf09509984289bf460914aa0eac69 | 30,854 |
def within_date(date_min, date_max, current_date):
"""
Test if a provided date is greater than or equal to a min date or less than max date
"""
if date_min <= current_date < date_max:
return True
else:
return False | 44d96e463b97fa9ca82e34b0c2bed3694959b525 | 30,857 |
def find_episode(episode_id, seasons):
"""
Return metadata for a specific episode from within a nested
metadata dict.
Returns an empty dict if the episode could not be found.
"""
for season in seasons:
for episode in season['episodes']:
if str(episode['id']) == episode_id:
... | 64255ca8e330c3b45768704644ac8bfddbfc1416 | 30,862 |
def child_or_children(value):
""" Return num followed by 'child' or 'children' as appropriate """
try:
value = int(value)
except ValueError:
return ''
if value == 1:
return '1 child'
return '%d children' | a22be46a3fd1086dac116c187189204b5ea1a6db | 30,864 |
def _decoding_base_info(encoded_info):
"""
Decode base info
Args:
encoded_info(list or dict): encoded base info
"""
if isinstance(encoded_info, dict):
return encoded_info
base_info = dict()
for item in encoded_info:
base_info[item['symbol']] = item['base']
return... | d47e7940af8dc1f42168d5630d95345a6111c865 | 30,868 |
def is_table_taxa_alike(feature_table1, feature_table2):
"""This method checks if `feature_table2` instance contains same taxonomy
as `feature_table1`
Parameters
----------
feature_table1
First FeatureTable
feature_table2
Second FeatureTable
Returns
-------
bool
... | e4fef557c168c885917d8183f3d0f0ab3969abb6 | 30,873 |
def _gen_eval_kwargs(name):
"""
Find the keyword arguments to pass to numexpr for the given operation.
Parameters
----------
name : str
Returns
-------
eval_kwargs : dict
Examples
--------
>>> _gen_eval_kwargs("__add__")
{}
>>> _gen_eval_kwargs("rtruediv")
{"r... | 17fc51c954ada4170a6fcfa68dda4018faa71cac | 30,876 |
def GetNiceArgs(level: int):
"""Returns the command/arguments to set the `nice` level of a new process.
Args:
level: The nice level to set (-20 <= `level` <= 19).
"""
if level < -20 or level > 19:
raise ValueError(
f"The level must be >= -20 and <= 19. The level specified is {level}.")
return... | 6805178232e96caea19035b4286d7d9dddff8a88 | 30,877 |
from datetime import datetime
import pytz
def utc_to_unix(t):
""" UTC Y-M-D -> UTC unix time (ignore float second point)
t = "2000-01-01T00:00:00.111" """
t = t.split('.')[0]
dt = datetime.strptime(t, '%Y-%m-%dT%H:%M:%S')
tz = pytz.timezone('UTC')
dt = tz.localize(dt)
unix_time = int(dt.ti... | 7f870d05bb3382923a2f9485194c3435673e4b77 | 30,878 |
def get_involved_objects(config):
"""Given a pytest config, get the list of objects specified via the
--involving flag"""
return config.getoption("--involving") or [] | 8da5599eb30bcd1a4960eefa8ed235b989badff2 | 30,880 |
def tmpdirec(tmp_path_factory):
"""Pytest fixture instantiating a new session-scope "data" folder.
Parameters
----------
tmpdir_factory :
Pytest fixture for creating temporary directories.
"""
return tmp_path_factory.mktemp("data") | 870e81aa93a95e9ce28be1c4a902f213ca13c626 | 30,884 |
def safe_subpath(path, altitudes, h):
"""
Computes the maximum subpath of path along which the safety constraint is
not violated
Parameters
----------
path: np.array
Contains the nodes that are visited along the path
altitudes: np.array
1-d vector with altitudes for each node... | 179fc42254a76ef4247140d7292d547c6b2681b6 | 30,889 |
def toggle_active_links(pathname):
"""Toggles active menu links based on url pathname
Args:
pathname (str): Url pathname
Returns:
bool: Active state for each page
"""
if pathname in ["/datyy/", "/datyy/summary"]:
return True, False, False, False, False
if pathname == "... | 9d362d2a3d57d16c9163a4b09cabdd730f6ebb5a | 30,894 |
def run_one_day(fish: list[int], start_time: int = 6, new_time: int = 8):
"""Runs one day of lanternfish reproducing."""
fishes = fish.copy()
for i, f in enumerate(fish):
if f == 0:
fishes[i] = start_time
fishes.append(new_time)
else:
fishes[i] = f - 1
... | ca4b1e533ba1604eaa688f4d7996ceafad3a7ed4 | 30,903 |
def sex2dec(rain,decin):
"""
Converts sexagesimal coordinates to decimal. HMS and DMS separated by colons (:)
Parameters
----------
rain : str
input Right Ascension as a sexagesimal string -- e.g., '03:45:6789'
decin : str
input Declination as a sexagesimal string -- e.g.... | 82a4fa431e483f59ed0fef0acd403714d18806e0 | 30,912 |
def ttfAutohintDict( parameterValue ):
"""Returns a dict for a TTFAutohint parameter value."""
ttfAutohintDict = {}
for ttfAutohintOption in parameterValue.split("--"):
if "=" in ttfAutohintOption:
[key, value] = ttfAutohintOption.split("=")
value = value.strip()
else:
key = ttfAutohintOption
value =... | aa9839f64c9eefb1404238c8689e4826d8e525fd | 30,913 |
def _fmt_date(date_as_bytes):
"""Format mail header Date for humans."""
date_as_string = date_as_bytes.decode()
_month = {
'Jan': 1,
'Feb': 2,
'Mar': 3,
'Apr': 4,
'May': 5,
'Jun': 6,
'Jul': 7,
'Aug': 8,
'Sep': 9,
'Oct': 10,
... | e1e273eb22d60ca945ce9b065f6c4b8cf62cf82e | 30,914 |
from typing import Any
def parse_error(err: Any, raw: bool = True) -> dict:
"""
Parse single error object (such as pydantic-based or fastapi-based) to dict
:param err: Error object
:param raw: Whether this is a raw error or wrapped pydantic error
:return: dict with name of the field (or "__all__"... | 73bb041e3d6e2259cf390d42485a9e9b7e77abba | 30,917 |
from datetime import datetime
import pytz
def from_timestamp(timestamp):
"""
Transform a UNIX UTC timestamp to a Python datetime object.
"""
if timestamp is None:
return None
return datetime.fromtimestamp(timestamp, tz=pytz.UTC) | 85bf1f0c5d4fb8395e86acce7a322885ec565e16 | 30,920 |
def rollout(env, maxsteps=100):
""" Random policy for rollouts """
G = 0
for i in range(maxsteps):
action = env.action_space.sample()
_, reward, terminal, _ = env.step(action)
G += reward
if terminal:
return G
return G | cef1043e82e048999f89e1ca6ed6011a62b83aaa | 30,921 |
from typing import Tuple
from typing import List
def read_fastq(filename: str) -> Tuple[List[str], List[str]]:
"""
Reads sequences and qualities from a .fastq file
filename: relative or absolute path of the .fa file to be read from
Returns:
List of sequence reads
List of qualities co... | cd4ffc29b2cd7b76b256c82e7ed438939e5c6ec4 | 30,925 |
def enable_runtime_call_stats() -> dict:
"""Enable run time call stats collection.
**Experimental**
"""
return {"method": "Profiler.enableRuntimeCallStats", "params": {}} | e9af8c51a8ab8e2c10f0023bebecd8703ce09b08 | 30,926 |
def create_bed_info_gp(gp):
"""Creates the block_starts, block_sizes and exon_frames fields from a GenePredTranscript object"""
block_starts = ','.join(map(str, gp.block_starts))
block_sizes = ','.join(map(str, gp.block_sizes))
exon_frames = ','.join(map(str, gp.exon_frames))
return block_starts, bl... | 260ecdef20f4ec25e873b978e644e5d90755774e | 30,929 |
def char_ngrams(n, word, **kwargs):
"""This function extracts character ngrams for the given word
Args:
n (int): Max size of n-gram to extract
word (str): The word to be extract n-grams from
Returns:
list: A list of character n-grams for the given word
"""
del kwargs
ch... | 27d46d014198e7290d98bfc8e31aa24f74454b48 | 30,930 |
import copy
def redact_loc(image_meta, copy_dict=True):
"""
Create a shallow copy of image meta with 'location' removed
for security (as it can contain credentials).
"""
if copy_dict:
new_image_meta = copy.copy(image_meta)
else:
new_image_meta = image_meta
new_image_meta.po... | f34e0577510c6cc05b1e36e02a48d9be2722c777 | 30,934 |
from typing import OrderedDict
def sort_request(request):
"""
Sort a JSON-RPC request dict.
This has no effect other than making the request nicer to read.
>>> json.dumps(sort_request(
... {'id': 2, 'params': [2, 3], 'method': 'add', 'jsonrpc': '2.0'}))
'{"jsonrpc": "2.0", "m... | 0602f0e65845d942f39db0cd1dac18923e00d0b4 | 30,935 |
def get_mf6_mshape(disfile):
"""Return the shape of the MODFLOW 6 model.
Parameters
----------
disfile : str
path to a MODFLOW 6 discretization file
Returns
-------
mshape : tuple
tuple with the shape of the MODFLOW 6 model.
"""
with open(disfile, "r") as f:
... | 32f25a2a8a49737296bf3f5c4d6c8bc2768e935a | 30,938 |
def para_size_greater_than_n(para_list, n = 1):
"""
Returns paragraphs whose length are greater than n
:param para_list: a list of paragraphs
:param n: paragraphs having length >n are selected
:return: list of paragraphs having length >n
"""
if n > 0:
return [para for para in para_li... | fb8b2a43f43b70821ae1a9be21fad39440ce75dd | 30,943 |
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