content stringlengths 35 416k | sha1 stringlengths 40 40 | id int64 0 710k |
|---|---|---|
def dice_coefficient(outputs, targets, eps=1.0):
"""Calculates the Dice coefficient between the predicted and target masks.
More information:
- https://en.wikipedia.org/wiki/Sørensen–Dice_coefficient
Args:
outputs (torch.tensor): Outputs of the model (N x 1 x H x W).
targets (torch... | b74d2ae00e30bc1127c098a17b427e9fcc3ac30b | 36,064 |
def guid2string(val):
""" convert an active directory binary objectGUID value as returned by
python-ldap into a string that can be used as an LDAP query value """
s = ['\\%02X' % ord(x) for x in val]
return ''.join(s) | b9c7db839b150278406c44bcaa10f1472b5b0598 | 36,065 |
def intersection(a, b=None):
"""
A : bedtool
B : bedtool
Returns A - B and A intersect B
A with b and returns everything in a but not b and everything in a but... ???
"""
overlapping = a.intersect(b, wa=True, u=True, stream=True).saveas()
remaining = a.intersect(b, w... | d01786484431fcec20deffa057c4218af03ed03b | 36,067 |
def calculate_center(shape: tuple):
"""
Calculate and return the center point of ``shape``.
:param shape: A tuple (width, height) of odd numbers
:return: A ``tuple`` (x, y) containing the center points coordinates
"""
if any(d%2 == 0 for d in shape):
raise ValueError("width and height ... | dbe2485b39c7670adfb832d3626e7e9106e5b2c0 | 36,070 |
def format_datetime(datetime_):
"""Convert datetime object to something JSON-serializable."""
if datetime_ is None:
return None
return datetime_.strftime('%Y-%m-%dT%H:%M:%SZ') | 16fbcff4737ec985405c8267b74e9085f56d06df | 36,071 |
def _set_key2sl(key):
"""Convert a key part to a slice part."""
if isinstance(key, int) or key is Ellipsis:
return key
elif isinstance(key, slice):
# Forbid slice steps
if key.step is not None:
raise ValueError("farray slice step is not supported")
return key
... | c735f009ef5576f4eaf293152b715aed8d20f965 | 36,073 |
def calc_clean_summary_stats(df_time, category):
"""Calculate summary statistics (ALSFRS-R subscores, vital capacity max/average)"""
# Add subject-project identifier, drop incomplete rows
df_time['subj_proj_id'] = df_time['SubjectUID'].astype('str') + '_' + df_time['dataset']
if category == 'alsfrs':
... | 318e12ee7bb86ca99e942e748907567a589aff0a | 36,075 |
def contains(arr, s):
"""
反向逻辑，当 arr 中没有一个包含 s 的时候才为 true
"""
return not len(tuple(filter(lambda item: (not (item.find(s) < 0)), arr))) | 470ce16553db4140c0d912537dc9ea068978e367 | 36,077 |
def transform_vec(t, tf):
"""
transforming a vector
:param t: a list of vector
:param tf: a matrix
:return: transform t
"""
result = []
for item in t:
result.append(tf*item)
return result | 238ec13ccd4d4cac088ea741239789341daa8341 | 36,078 |
def sb_xs_compare(sb, sheet):
"""Compute the absolute and percentage difference between the maximum fields of one CrossSection in a SectionBook and all the other CrossSections
args:
sb - SectionBook object
sheet - sheet string of the CrossSection in sb that should be
compared wit... | 491dd1ada0b23882d2f9de474b2ccb56c36eb705 | 36,079 |
def peak_hr(df_pk):
"""Performs Peak Hour calculations by combining directional aadt values
with vehicle hourly volume factors determined by Metro.
Args: df_pk, a pandas dataframe.
Returns: df_pk, a pandas dataframe conaining new PK_HR column with
completed calculations.
"""
df_pk['PK_HR'] =... | ec5dfafd2a9ee53af8c7aff59ee8a38096be91a4 | 36,080 |
def percent_change(a,b):
"""
Returns the percentage change from a to b.
"""
return float((b - a)/a) | 34bf312683f72107404919bb01b9f01464e23c47 | 36,081 |
import torch
def make_cuda(tensor):
"""Turn the tensor into cuda if possible."""
if torch.cuda.is_available():
return tensor.cuda()
return tensor | 14f05f1f27a0f846448ac89a2e8371b4acac9711 | 36,083 |
def parseConfigParser(config_data=dict({}), theConfig=None, overwrite=True):
"""
Merges the Configuration Dictionary into a configparser.
param config_data - dict the configuration to merge.
param theConfig - configparser.ConfigParser the ConfigParser.
param overwrite - boolean determining if the dict is record of... | de0f895c612f8fa7177c1fb23f6b864eeba0fbe5 | 36,085 |
def check_rent_history(rent_list, username):
"""
return farm ids that the given username has rented before
"""
farm_rent_before = []
for rent in rent_list:
if rent.get('username') == username:
farm_rent_before.append(str(rent.get('farm_id')))
return farm_rent_before | b480651ab7e17673df91c7e34dc5d70f8f360ac7 | 36,086 |
def GetMavenVersion(api, language_version):
"""Returns the maven version."""
if api.get('ownerDomain') == 'google.com':
return '%s-rev%s-%s' %(api['version'],
api['revision'],
language_version)
return '%s-%s-SNAPSHOT' % (api['version'], language_version) | 74d60f3309b596087932406e33717c246d9e3905 | 36,087 |
def db2lin(x):
"""From decibel to linear"""
return 10.0**(x/10.0) | 653fb36943baeb393d4cec07544df95a230a5880 | 36,088 |
def remove_nan_columns(dataframe):
"""Removes columns of data frame where any value is NaN.
Args:
dataframe (pandas.DataFrame): Input dataframe.
Returns:
tuple: tuple containing:
pandas.DataFrame: Dataframe with columns containing NaN values removed.
numpy.array: A... | 058c0469dd93a71866e1a09d8dd16b80379c7d15 | 36,090 |
def ztf_magnitude_zero_point(bands=''):
"""
Sample from the ZTF zeropoint distribution
"""
dist = {'g': 26.325, 'r': 26.275, 'i': 25.660}
return [dist[b] for b in bands.split(',')] | 3aecf6b0c1ca3162924cca3494e91d2f792c0338 | 36,091 |
from typing import Dict
from typing import Any
from typing import List
def extractFields(data: Dict[str, Any], fields: List[str], returnEmpty: bool = True) -> Dict[str, Any]:
"""
Extracts the Listed Params from the dict
"""
cleanedData = {}
for field in fields:
if field in data:
... | f82f6f97cb585fc4ce4a40d43e24b7c0d4640e3b | 36,092 |
import re
def to_methods(function_str):
"""
to_methods is a helper function that aims to replace all the "toX" methods
from PyQt4-apiV1.0.
:param function_str: String that represents something that may have the
toX methods in it.
:type function_str: str
:return: A string that, if a me... | af7a7dc5f332e10b5ea7e8fda52d1dbad016db61 | 36,094 |
from bs4 import BeautifulSoup
import re
def get_trademark_url(downloaded_htmls) -> list:
"""Parse the data, extract trademark application ID and url and save all in a dictionary."""
tm_name_url_list = []
for clean_tm_file in downloaded_htmls:
html = open(clean_tm_file, 'r', encoding='utf-8')
... | fc7736e8d294cefb8ea6622e8c9cf156a6c6a417 | 36,095 |
import torch
def kl_divergence(q, p):
"""Calculates the KL divergence between q and p.
Tries to compute the KL divergence in closed form, if it
is not possible, returns the Monte Carlo approximation
using a single sample.
Args:
q : torch.distribution
Input distribution (posterior... | 3d0be3599332840057f07d9bee71681f4a710557 | 36,096 |
import re
def ipv4_address_validator(addr):
"""
Regex to validate an ipv4 address.
Checks if each octet is in range 0-255.
Returns True/False
"""
pattern = re.compile(
r"^([1]?\d?\d|2[0-4]\d|25[0-5])\.([1]?\d?\d|2[0-4]\d|25[0-5])\.([1]?\d?\d|2[0-4]\d|25[0-5])\.([1]?\d?\d|2[0-4]\d|25[0... | 6204d9d54536e510b5556d13ee259ec3d7b3fc95 | 36,098 |
import base64
def load_signature(filepath: str) -> bytes:
"""Load the signature"""
with open(filepath, "rb") as f:
signature: bytes = base64.b64decode(f.read())
return signature | 10765be49229f3f061649cab7b6ece2bc5eb5284 | 36,100 |
def plot_hist(self, parameters=None, mean_line=False, **kwds):
"""
Make a histogram of the WaterFrame's.
A histogram is a representation of the distribution of data.
This function calls pandas.DataFrame.hist(), on each parameter of the
WaterFrame, resulting in one histogram per parameter.
Param... | 5c927a170fff37691135dd367f0b42247d4aa3e1 | 36,101 |
def isDelimited(value):
"""
This method simply checks to see if the user supplied value has delimiters.
That is, if it starts and ends with double-quotes, then it is delimited.
"""
if len(value) < 2:
return False
if value[0] == '"' and value[-1] == '"':
return True
else:
... | 4a89211c27f6cf826b3b29cc718b0e00a4184a0f | 36,103 |
def createArrays(trainDf, testDf):
"""createArrays
Saves predictions into a .csv file.
Input:
trainDf -- the training DataFrame (pandas)
testDf -- the testing DataFrame (pandas)
Output:
train_X -- training set (sample)
train_y -- target feature
test_X -- testing set
"""
train_X = tr... | 6abdcfcfb33d53f90f2dffd04f624048f9738436 | 36,104 |
import types
def asmodule(module):
"""
Return the module references by `module` name. If `module` is
already an imported module instance, return it as is.
"""
if isinstance(module, types.ModuleType):
return module
elif isinstance(module, str):
return __import__(module, fromlis... | 1e2def23f770f9bc84aa8af3273f830fedea3282 | 36,105 |
def flatten(list_of_lists):
"""Takes a list of lists and turns it into a list of the sub-elements"""
return [item for sublist in list_of_lists for item in sublist] | 11df76be33e96295e4e5230873368be707ae032f | 36,106 |
def leftmost(n):
"""
Return the leftmost item in a binary tree.
"""
while n.left is not None:
n = n.left
return n | f22dbb611a088e52c37002c1dad3a704033145e0 | 36,107 |
def binary_search(list_: list, item: int = 0):
"""Returns the index of the number to find in the SORTED list
:param list_: SORTED list to find the item
:type list_: list
:param item: The number to find the index
:type item: int
:rtype: int, else: None
:return: The index of the number foun... | 5f5256a0d26ed89bb038e0b06432686eb01e12c7 | 36,109 |
def clean_symbol_code(code):
"""Cleans Weather Symbol code"""
sentence = code.split('_')
return (' '.join(sentence)).capitalize() | 3dd7061da7dd40c80991e94f20feeb7539ff7db8 | 36,111 |
def sdfGetPropList(mol):
"""
sdfGetPropList() returns the list of all property names in molecule mol
"""
sdfkeyvals = mol["keyvals"]
return [pair[0] for pair in sdfkeyvals] if sdfkeyvals else [] | da897a54a4e0bfc59ca2bd78a2d39d0b64b32db1 | 36,112 |
import os
def parserSingle(in_file):
"""
single file version for placeholder for if("do preproc step")
.. this is now a mess and just a placeholder
"""
out_file = os.path.abspath(in_file)
return in_file | 7091526e6809fc97f565666387829b84bb86f8bf | 36,116 |
from typing import Dict
def str_dict_to_bytes(str_dict: Dict[str, str]) -> Dict[bytes, bytes]:
"""
Converts the key and the value of a dict from str to bytes.
"""
out = {}
for key, value in str_dict.items():
out[key.encode()] = value.encode()
return out | 43b62237b9c80c6e613c363aace17324647086b9 | 36,117 |
import subprocess
import logging
def update_docker(canary, version='18.06.3~ce~3-0~ubuntu'): # pragma: no cover
"""Update the docker package prior to reboot.
This will automatically keep the docker package up to date and running prior
to reboot will ensure that no containers are running, so no disruptions. Th... | 81616509688ffac67d03eb8cf40db8b82c25d01b | 36,118 |
def gcd(x, y):
"""
Euclid's algorithm
- If n divides m evenly, then n is the GCD. Otherwise the GCD is the GCD of n and the remainder of m divided by n.
"""
if x % y == 0:
return y
else:
return gcd(y, x%y) | db31a4b36929c9b7e83508beee724b94eea27a12 | 36,119 |
def string_breakdown(the_string :str) -> list:
"""Accepts a string and returns a list of tuples of form [(char, count)]"""
checked = []
components = []
for char in the_string:
if char not in checked:
count = the_string.count(char)
checked.append(char... | 2283297aff80d548625930482249a31284e49eae | 36,121 |
def read_lines(path):
"""Return list of lines comprising specified file.
Newlines at the end are included.
"""
with open(path, "r") as file:
return file.readlines() | e0986c649ab6b64c665e8aa887c2625ad21b77be | 36,122 |
from typing import List
def _sampling_from_alias_wiki(
alias: List[int],
probs: List[float],
random_val: float,
) -> int:
"""
Draw sample from a non-uniform discrete distribution using Alias sampling.
This implementation is aligned with the wiki description using 1 random number.
:param a... | c67d2d698ace15c798cda51049b7ddd880c48a71 | 36,124 |
import torch
def get_bins(attr, ncenters, radius):
"""Sort attributes into bins and return indices
Parameters:
-----------
attr : torch FloatTensor, N x Na
Attributes
"""
# sort attributes
centers = torch.linspace(0, 1, ncenters).to(attr.device)
lower_edge = centers - radius
... | 9c92e6208ac272eff4be6f6b868ae12cc989205e | 36,125 |
from typing import List
def _filter_nums(*, nums: List[int], min_lim: int=0, max_lim: int) -> List[int]:
"""Given two limits, remove elements from the list that aren't in that range."""
return [num for num in nums if num > min_lim and num <= max_lim] | 8e6e0b274e17eb38dcd25e0b307a26b26f1d1fbd | 36,126 |
def get_item_attr(idmap, access):
"""
Utility for accessing dict by different key types (for get).
For example::
>>> idmap = {(1,): 2}
>>> get_item_attr(idmap, 1)
2
>>> idmap = {(1,): 2}
>>> get_item_attr(idmap, {"pk": 1})
2
>>> get_item_attr(idmap, (... | abaf1250c34b94393851e7a0764af3bf1c3eb116 | 36,127 |
import torch
def gdt_torch(X, Y, cutoffs, weights=None):
""" Assumes x,y are both (B x D x N). see below for wrapper.
* cutoffs is a list of `K` thresholds
* weights is a list of `K` weights (1 x each threshold)
"""
device = X.device
if weights is None:
weights = torch.ones(1,l... | 7d4646504bfff5651ca9c0b15519f000546fca56 | 36,128 |
def validate_domain(email, domains):
"""Check that the domain matches that of the assessment."""
if email.split("@")[1].lower() in domains:
return True
return False | b1fbf9ca276ce72b826a0a49086d3c6bdc044ccb | 36,129 |
def round_to_second(dt):
"""
datetime对象round到秒
:param dt:
:return:
"""
res = dt.replace(microsecond=0)
return res | 2be5f589be54bbb113b307d5b38ba5d6e0a13a32 | 36,131 |
import re
def sub_strong(line, regex):
"""Surround some patterns in <strong> tags."""
result = re.search(regex, line)
if result:
for match in result.groups():
line = line.replace(match, '<strong>{}</strong>'.format(match), 1)
return line | a539420012db702501f293c081457392ba0ec4a7 | 36,132 |
from typing import List
from typing import Dict
from typing import Any
def split_docker_list(d_list: List[Dict[str, Any]]):
"""Splits the list of docker in test generation docker and test environment docker.
The split is done by checking for the 'generator' key in the dockers dict defined in the json file.
... | 6c01f81db08270c60d08153448dd8989ff87ad4c | 36,133 |
def in_docker():
"""Returns: True if running in a docker container, else False"""
try:
with open("/proc/1/cgroup", "rt") as ifh:
contents = ifh.read()
return any([word in contents for word in ["actions_job", "docker"]])
except OSError:
return False | eeb000ee4928105c5c978045ae50a27b85d5b735 | 36,135 |
def crimeScore(data, area=0.04):
"""
A simple function that is intended to take the amount of crimes and to divide them by the total search radius (0.04)
to return a sort of "crime score"
"""
return int(len(data["crimes"]) / area) | a684f9b37bdb403225dadf35ef4c92b6650b89d7 | 36,136 |
def round_to_int(number, precision):
"""Round a number to a precision"""
precision = int(precision)
rounded = (int(number) + precision / 2) // precision * precision
return rounded | 75f7b23c3f6426dc3ed0c54f3baa491e3c658a14 | 36,138 |
def mod_exponent(base, power, mod):
"""
Modular exponential of a number
:param base : number which is going to be raised
:param power : power to which the number is raised
:param mod : number by modulo has to be performed
:return : number raised to power and modulo by mod [(base ^ power) % mod... | f0b0de989c8ab38a11ca41126e30234765571ca6 | 36,140 |
import requests
def post_input_file(input_text):
"""Posts a string as a file (multipart/form-data) named 'input' to the
REST API and returns the response.
"""
url = 'http://localhost:5000/parse'
return requests.post(url, files={'input': input_text}) | 4b6613e95f3221e1a92c88d449aa41a562182304 | 36,141 |
def table2list(table, consider_floats_only=True):
"""
Given a pandas table, convert
it to a list of values
:param consider_floats_only: should we consider only floats?
:return list
"""
my_list = []
for col in table.columns:
column_values = table[col]
for i in column_value... | 3469123bd5e1fb2261164178df1d834104504e72 | 36,142 |
import subprocess
def list_installed_pkgs(args):
"""Lists the members of a given category of packages; returns list."""
prefix = "pm list packages"
if args.user:
suffix = "-3"
elif args.system:
suffix = "-s"
elif args.disabled:
suffix = "-d"
else:
suff... | 2db06ef60d6c3b79f2c3a9ced8ed3aa6d673da06 | 36,143 |
import os
def find_candidate_images(input_path):
"""
Finds all candidate images in the given folder and its sub-folders.
Returns:
images: a list of absolute paths to the discovered images.
"""
images = []
for root, dirs, files in os.walk(input_path):
for name in files:
... | 0078608652b311758e2b5d43a4772a17b7970f96 | 36,144 |
import numpy
def assemble_matrixQ (mat_prop, fail_type = None):
""" Assembles Q matrix (reduced elastic matrix) for a given layer. """
if not isinstance(mat_prop, dict):
raise TypeError('mat_prop must be a dictionary')
# Degradation Factor (for failed layers)
df = 0.001
if fail_type... | a0a12b3891e8e9fde9ed16faf6c402941523b107 | 36,146 |
def _get_low_pressure(self, g_l, d_l, frac_cells):
"""
Obtains the coefficients of the (projected) lower-dimensional pressures
Parameters
----------
g_l : PorePy object
Lower-dimensional grid.
d_l : Dictionary
Lower-dimensional data dictionary.
frac_cells : NumPy nd-Array
... | 374c812a39aa045b68d70515d62d13aad69655c3 | 36,147 |
def read_from_y(state):
"""Reads the contents of the Y scratch register."""
return state.y_register | f5d6f258f267d4c1392b393ffc680cdf8aa59748 | 36,150 |
def case_of(value: str) -> int:
"""Returns 1 for all uppercase, 0 for all lowercase, and -1 for
mixed case."""
if all(map(lambda x: x.isupper(), value)):
return 1
elif all(map(lambda x: x.islower(), value)):
return 0
return -1 | e0b56890ff73a9b59385e716be6ea3c41ab03bc6 | 36,151 |
def __filter_event_type__(trace_events, event_type):
"""
Looks for the events in the trace matching the event type
:param trace_events: Events found in the trace (filtered by family).
:param event_type: Event type to filter.
:return: Filtered trace
"""
filtered = []
for line in trace_ev... | 4a4b49272014ff2a2f552f3a4a381f859a886a5a | 36,152 |
from typing import Callable
def map(f: Callable, collection):
"""Transform each element of a collection.
Examples
--------
.. doctest::
>>> a = ['The', 'quick', 'brown', 'fox']
>>> hl.eval_expr(hl.map(lambda x: hl.len(x), a))
[3, 5, 5, 3]
Parameters
----------
f... | 677c8b5185e45126c85448020a6a914c0938f785 | 36,154 |
def _is_algorithm_kd_tree(model):
"""Checks if the algorithm for the scikit model is set to 'kd_tree'."""
return model.algorithm is 'kd_tree' or (model.algorithm is 'auto' and model._fit_method is 'kd_tree') | 24bb52161747753c462670c36609e3afe9989ca0 | 36,155 |
import argparse
def parse_args():
"""Parse command line arguments."""
parser = argparse.ArgumentParser(description='Convert plate reader '
'Excel file to fraction infectivity'
'csv.')
parser.add_argument('infile', type=str, help='Pa... | 4a6c309e90ec4b6752d4c197946414b5bed94c42 | 36,157 |
from functools import reduce
from operator import mul
def prod(iterable):
"""
Return the product of all numbers in an iterable.
"""
return reduce(mul, iterable) | d4ca281afd572aaae7da4bf13696ebc8d05be32f | 36,161 |
def span_search(line):
"""期間予定であるかを検出し,boolで返す."""
zen_tilde = '～'
# '～'が最初に検出された列
index = line.find(zen_tilde)
# .findで検出されない場合-1が返される
if index != -1:
# 2～5年といった学年の間隔を～記号で表しているため、その対策
# ～の２つ後にあるというスタイルに依存
# つまり一日予定
if line.startswith('年', index + 2):
... | ed1b1ea120b5ef1c09d6dac97a491aaf1615897e | 36,163 |
def get_project_from_manifest(manifest, pid):
"""
Returns the project entry from the manifest
:param manifest:
:param pid:
:return:
"""
if 'projects' not in manifest:
return None
for project in manifest['projects']:
if project['identifier'] == pid:
return proj... | 5f72faffeb14bc20568c2898ca3b9c65b2edb53f | 36,164 |
def case_conversation(text, text_lower = True):
"""
This function returns the corpus with all tokens lowercase or uppercase
text: String corpus
text_lower: Boolen, default is True
returns: Text corpus with all tokens converted
"""
if text_lower:
return text.lower()
els... | cc37b8473114de08c1fe0a01638eac063eebdc2f | 36,165 |
def all_properties(obj):
"""
Return a list of names of non-methods of 'obj'
"""
noncallables = []
for name in dir(obj):
if not hasattr(getattr(obj, name), '__call__'):
noncallables.append(name)
return noncallables | 58a86250e03e9cb4c9f6567eaf072173ff419e73 | 36,167 |
import re
def get_output1(filename):
"""
Supports Python, Julia
Return set of tuples: source_file, output_file
Use group_tuple_pairs() to organize these for output to yaml etc.
Cases:
(1)
writer(open())
writer.writerows(object)
(2) with open()
write
example from pythia:
def compose... | 27d9edc8053c1832f1b43a617bfda7772a538494 | 36,168 |
def power_level(serial: int, x: int, y: int) -> int:
"""Compute the power level of the fuel cell at x, y.
"""
rack_id = x + 10
p = rack_id * y + serial
p *= rack_id
p = (p // 100) % 10
return p - 5 | 316895b97f752867171ff4dd0463ea5395228b97 | 36,170 |
from pathlib import Path
def get_nprocs(modelpath):
"""Return the number of MPI processes specified in input.txt."""
return int(Path(modelpath, 'input.txt').read_text().split('\n')[21].split('#')[0]) | 82faad4d21e5a9acb7de123338e71b1123ad79cc | 36,172 |
import re
def padding(str, p=' ', remove_empty_lines=True):
"""
normalize newlines
remove leading and trailing spaces
collapse spaces
collapse newlines
pad lines
"""
str = re.sub(r'[ \t]+\n', '\n', str)
if remove_empty_lines:
str = str.replace('\n\n',... | d04c4f9d2a2da4dac050bbe567482821f2b8de9a | 36,173 |
def prep_data_single_sample_st(
adata, adata_i, use_rep, features, blur_pix, histo, fluor_channels
):
"""
Prepare dataframe for tissue-level clustering from a single AnnData sample
Parameters
----------
adata : anndata.AnnData
AnnData object containing Visium data
adata_i : int
... | 310fe731e44d47bca1af0b0a782ae5fdc2caa9f3 | 36,176 |
def _get_QColorButton(self):
"""
Get current value for QColorButton
"""
return self.color() | 7c56c2401c9c367f34b44b5ec347f5fd10907abc | 36,178 |
def _unique(session, cls, queryfunc, constructor, kw, unique_key='name'):
"""
Checks if a class instance is unique or not, only for those classes which have unique attributes
Like the User name and Image img_path
:param session: Session object
:param cls: Class object
:param queryfunc: The query... | b1ca3f004a288c489f424ae6c60e5f71914f5986 | 36,179 |
def ALMACombineCals(Cal1, Cal2=None, Cal3=None, Cal4=None):
"""
Combine a unique list of calibrators
Drops None sources
returns list of unique names
* Cal1 = List of calibrators (from ALMACalModel)
* Cal2 = List of calibrators, ignore if None
* Cal3 = List of calibrators, ... | 18866c26f904fbd1fa77651112efba77a3d7ff55 | 36,180 |
import pathlib
def is_relative_to(path: pathlib.Path, base: pathlib.Path) -> bool:
"""Check whether `path` is contained inside `base`."""
try:
path.relative_to(base)
return True
except ValueError:
return False | 6a9bed0700d87d9c74ba8980f25f3de522fa5ca8 | 36,181 |
import os
def blankoutComments( filename ):
"""
Replace a file with blanks everywhere the file had C/C++ comments.
Return the resulting file as a list of strings.
"""
tmp_file = '/tmp/inserter.' + str(os.getpid())
os.system( 'stripcomments.py infile=' + filename + ' language=cpp '
... | 6b8d9922b77d220d8309aeb1f0caa61bcd4e02ab | 36,182 |
def skl_calculation_metrics(result_labels, test_labels):
"""
:param result_labels:
:param test_labels:
:return:
ref: http://blog.exsilio.com/all/accuracy-precision-recall-f1-score-interpretation-of-performance-measures/
"""
tp = 0.0
fp = 0.0
tn = 0.0
fn = 0.0
size = len(r... | dfc2bb19a4d674e83aaed953017ec2e4b91fee3e | 36,183 |
def multiples35(number):
"""
If we list all the natural numbers below 10 that are multiples of 3 or 5, we get 3, 5, 6 and 9. The sum of these
multiples is 23. Finish the solution so that it returns the sum of all the multiples of 3 or 5 below the number
passed in. Note: If the number is a multiple of bo... | 53582256eb17a81c7c5b90be13d9bb89943b2693 | 36,184 |
from functools import reduce
import operator
import collections
def strings_to_wordsets(strings, stop_words=None):
"""Build a dict of wordsets from a list of strings, with optional filter.
For each distinct word found in the list of strings, the wordset dict will
map that word to a set of the strings tha... | 407f604d6fe78e6aad10e972fcda63ebb42209f1 | 36,185 |
def tokenize(sentence):
"""
Converts a single sentence into a list of individual significant units
Args:
sentence (str): Input string ie. 'This is a sentence.'
Returns:
list<str>: List of tokens ie. ['this', 'is', 'a', 'sentence']
"""
tokens = []
class Vars:
start_po... | 05848512b0d171151056221b13cd54eae7680538 | 36,186 |
from typing import Union
import re
def _cast_valid_types(content: Union[str, int, bool]) -> Union[str, bool, int]:
"""
Cast an input that explicitly reads "true" or "false" (case-insensitive) as a boolean type and cast all strings
of only digits as an integer type. This function does nothing and returns t... | c06e3635c1f5d4ac6d33939db8d552d58803dda1 | 36,187 |
def more_like_this(_es, es_index, field, like_list, min_term_freq, max_query_terms):
"""Build and execute a more like this query on the like document
See https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-mlt-query.html
Returns
result (list): list of documents that match the ... | a48fcc6e44b9a25bafd7936122c5ecc91cfdb932 | 36,189 |
import sys
import os
def get_dirs(src,order="none"):
"""
Given a path to where simulation directories live,
create a list of directories from which simulation
data will be extracted in a user-specified order.
Parameters
----------
src : str
Path to simulation suite directory whic... | 32f72230e5a78a3ed5e9c5158bf660bc1c1693c4 | 36,190 |
import re
def _getXMLText(fileobj):
"""Convenience function for reading the XML header data in a ShakeMap grid file.
:param fileobj:
File-like object representing an open ShakeMap grid file.
:returns:
All XML header text.
"""
tline = fileobj.readline()
datamatch = re.compile('grid_... | a44091de4543142a83a13b010de7f5a471a21df8 | 36,191 |
def decorator_info(f_name, expected, actual, flag):
"""
Convenience function returns nicely formatted error/warning msg.
:param f_name:
:param expected:
:param actual:
:param flag:
:return:
"""
format = lambda types: ', '.join([str(t).split("'")[1] for t in types])
expected, actu... | eeba0b04c2dfd6be77862d2f301d7e47c573b27a | 36,192 |
def map_l2dist_gaussianmech_renyiDP(sensitivity, scale, alpha):
"""map an L2 distance `sensitivity` through the gaussian mechanism with parameter `scale` to (alpha, epsilon)-RDP
Proposition 7 and Corollary 3: https://arxiv.org/pdf/1702.07476.pdf#subsection.6.3
:param sensitivity: maximum L2 distance pertur... | 98b5454fdc299b345a73ad1473ff56e249a29397 | 36,193 |
import json
def to_dict(data):
"""Convert json to dict data, if input is not json return None"""
if isinstance(data, dict):
return data
try:
value = json.loads(data)
if not isinstance(value, dict):
raise
return value
except:
return None | 9419173d027b998cebe949e7a43424834fd50d7c | 36,194 |
from typing import Mapping
from typing import Any
def _get_param_or_die(input_params: Mapping[str, Any], param: str) -> Any:
"""Returns value of param. Dies with user-formatted message if not defined.
Args:
input_params: Mapping from input parameter names to values.
param: Name of the param to get the va... | f06bfb5ae5393cf0e41a33db1c03797e940fcdef | 36,197 |
from datetime import datetime
def get_now():
"""
Return the current timestamp as a string to be sent over the network.
"""
return datetime.utcnow().isoformat() | c9ba1ee9a7450d58777265cea20657ada11d8636 | 36,198 |
def sort_issues(issues):
"""Sorted list of issues
Args:
issues (list): list of issue dictionaries
Returns:
list: list of sorted issue dictionaries
"""
issues.sort(
key=lambda issue: (
issue.filename,
issue.linenumber,
issue.rule.id
... | 74aa0fe71962c47d6af8e73ce014b13be9921cf1 | 36,199 |
def fieldmap_minmax(fieldmap, variable):
"""Data limits for a given varible across all zones in a fieldmap"""
limits = None
for z in fieldmap.zones:
if limits is None:
limits = z.values(variable).minmax()
else:
low, high = z.values(variable).minmax()
limit... | 662da76d19fd73c8e93b0cbaf80a04d8f14f3135 | 36,200 |
def bogus_func(obj, *args, **kwargs):
"""Function that just returns the arguments modified by the decorator."""
return (obj, args, kwargs) | c37dc3a21953571f4a81e1178b379c78aaeb510d | 36,201 |
def reverse(sentence):
""" split original sentence into a list, then append elements of the old list to the new list starting from last to first. then join the list back toghether. """
original = sentence.split()
reverse = []
count = len(original) - 1
while count >= 0:
reverse.append(orig... | 258bb97834a177a90dbfcf436d3228bb7f9a7237 | 36,202 |
from typing import Dict
import torch
def create_ner_conditional_masks(id2label: Dict[int, str]) -> torch.Tensor:
"""Create a NER-conditional mask matrix which implies the relations between
before-tag and after-tag.
According to the rule of BIO-naming system, it is impossible that `I-Dog` cannot be
ap... | 0cda8db465b039349eff1022a8cd2cc071f21295 | 36,203 |
def acquire_image_url(soup):
"""
Take a BeautifulSoup content of a book page.
Return the url of the image of the book.
"""
partial_url = soup.img['src'][5:]
image_url = f"http://books.toscrape.com{partial_url}"
return image_url | c2c14823f3fa1dbe30838dbab2513653d7c0fa3c | 36,204 |
def encode_varint_1(num):
""" Encode an integer to a varint presentation. See
https://developers.google.com/protocol-buffers/docs/encoding?csw=1#varints
on how those can be produced.
Arguments:
num (int): Value to encode
Returns:
bytearray: Encoded presentation of i... | 3a5883a352a85c3c472889b8b1e347ba41df0615 | 36,205 |
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