content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Dict
from pathlib import Path
from sys import path
from typing import Counter
def get_word_counts(filepath: str) -> Dict[str, int]:
"""
Return a dictionary of key-value pairs where keys are words
from the given file and values are their counts. If there is
no such file, return an em... | 30fd14031b00766320ad0f1728042438cb05fd4e | 13,800 |
import ctypes
def getVanHoveDistances(positions, displacements, L):
"""
Compte van Hove distances between particles of a system of size `L', with
`positions' and `displacements'.
Parameters
----------
positions : (*, 2) float array-like
Positions of the particles.
displacements : ... | a66150cfe238b151f098733d4570c438f1c93906 | 13,801 |
from typing import Any
from typing import Union
from typing import List
def plot_local_coordinate_system_matplotlib(
lcs,
axes: plt.Axes.axes = None,
color: Any = None,
label: str = None,
time: Union[pd.DatetimeIndex, pd.TimedeltaIndex, List[pd.Timestamp]] = None,
time_ref: pd.Timestamp = None... | 2df77f0e3343f6ac541ff37991208fb894b44660 | 13,802 |
def saved_searches_list(request):
"""
Renders the saved_searches_list html
"""
args = get_saved_searches_list(request.user)
return render('saved_searches_list.html', args, request) | a2f92c06733113f05501cb242d2ee2bad91917be | 13,803 |
import os
def upload():
"""Upload files. This endpoint is used to upload "trusted" files;
E.i. files created by CERT-EU
E.g. CITAR, CIMBL, IDS signatures, etc.
**Example request**:
.. sourcecode:: http
POST /api/1.0/upload HTTP/1.1
Host: do.cert.europa.eu
Accept: applic... | 5da57c64928c9212162667d036423070acbdb4f7 | 13,804 |
def get_active_loan_by_item_pid(item_pid):
"""Return any active loans for the given item."""
return search_by_pid(
item_pid=item_pid,
filter_states=current_app.config.get(
"CIRCULATION_STATES_LOAN_ACTIVE", []
),
) | 6922336876fddd72ce7655bf2cfee298fdc4a766 | 13,805 |
from typing import Set
from re import X
def _get_szymkiewicz_simpson_coefficient(a: Set[X], b: Set[X]) -> float:
"""Calculate the Szymkiewicz–Simpson coefficient.
.. seealso:: https://en.wikipedia.org/wiki/Overlap_coefficient
"""
if a and b:
return len(a.intersection(b)) / min(len(a), len(b))... | 42d39edf9fa2465605717e0892bcbca05df7799b | 13,806 |
def data_splitter(
input: pd.DataFrame,
) -> Output(train=pd.DataFrame, test=pd.DataFrame,):
"""Splits the input dataset into train and test slices."""
train, test = train_test_split(input, test_size=0.1, random_state=13)
return train, test | ddcc28b4430a8901fcde540cf321d4ea43f123d7 | 13,807 |
def reload(module, exclude=('sys', 'os.path', 'builtins', '__main__',
'numpy', 'numpy._globals')):
"""Recursively reload all modules used in the given module. Optionally
takes a list of modules to exclude from reloading. The default exclude
list contains sys, __main__, and __bu... | c97fd1942dae583ff236ed73d33b53b685cafd32 | 13,808 |
def get_words_for_board(words, board_size, packing_constant=1.1):
"""Pick a cutoff which is just beyond limit of the board size."""
# Order the words by length. It's easier to pack shorter words, so prioritize them.
# This is SUPER hacky, should have a Word class that handles these representational differe... | e5f74806fa15c1f1fbe78e0ac218d6d808611dfe | 13,809 |
def booleans(key, val):
"""returns ucsc formatted boolean"""
if val in (1, True, "on", "On", "ON"):
val = "on"
else:
val = "off"
return val | f210a2ce6b998e65d2e5934f1318efea0f96c709 | 13,810 |
def merge_param_classes(*cls_list,
merge_positional_params: bool = True) -> type(Params):
"""
Merge multiple Params classes into a single merged params class and return the merged class.
Note that this will not flatten the nested classes.
:param cls_list: A list of Params subcla... | c42907652f971d7cd6d208017b8faaacacddb5b2 | 13,811 |
import random
import collections
def make_pin_list(eff_cnt):
"""Generates a pin list with an effect pin count given by eff_cnt."""
cards = [1] * eff_cnt
cards.extend([0] * (131 - len(cards)))
random.shuffle(cards)
deck = collections.deque(cards)
pin_list = []
for letters, _ in KEY_WHEEL_DA... | 2c15a09928231993f09a373354ee29723463280d | 13,812 |
import select
def drop(cols, stmt):
"""
Function: Drops columns from the statement.
Input: List of columns to drop.
Output: Statement with columns that are not dropped.
"""
col_dict = column_dict(stmt)
col_names = [c for c in col_dict.keys()]
colintention = [c.evaluate(stmt).name if i... | 73ecf35077824281a5ebc4e26776b963e0cb378e | 13,813 |
def ConvertVolumeSizeString(volume_size_gb):
"""Converts the volume size defined in the schema to an int."""
volume_sizes = {
"500 GB (128 GB PD SSD x 4)": 500,
"1000 GB (256 GB PD SSD x 4)": 1000,
}
return volume_sizes[volume_size_gb] | b1f90e5ded4d543d88c4f129ea6ac03aeda0c04d | 13,814 |
def render_template_with_system_context(value):
"""
Render provided template with a default system context.
:param value: Template string.
:type value: ``str``
:param context: Template context.
:type context: ``dict``
"""
context = {
SYSTEM_KV_PREFIX: KeyValueLookup(),
}
... | 6df2e7a652595b35919638791aae5465258edf0f | 13,815 |
def ToTranslation(tree, placeholders):
"""Converts the tree back to a translation, substituting the placeholders
back in as required.
"""
text = tree.ToString()
assert text.count(PLACEHOLDER_STRING) == len(placeholders)
transl = tclib.Translation()
for placeholder in placeholders:
index = text.find(PL... | 36fca25dfc78e0f37ddc6193a17f2d29c6192228 | 13,816 |
import torch
def complex(real, imag):
"""Return a 'complex' tensor
- If `fft` module is present, returns a propert complex tensor
- Otherwise, stack the real and imaginary compoenents along the last
dimension.
Parameters
----------
real : tensor
imag : tensor
Returns
... | 272a293e3918e5e067f251a7dae10a4d2c56abf4 | 13,817 |
def get_snps(x: str) -> tuple:
"""Parse a SNP line and return name, chromsome, position."""
snp, loc = x.split(' ')
chrom, position = loc.strip('()').split(':')
return snp, chrom, int(position) | 52672c550c914d70033ab45fd582fb9e0f97f023 | 13,818 |
def qr_match(event, context, user=None):
"""
Function used to associate a given QR code with the given email
"""
user_coll = coll('users')
result = user_coll.update_one({'email': event["link_email"]}, {'$push': {'qrcode': event["qr_code"]}})
if result.matched_count == 1:
return {"status... | 7af48bc9fc97d34eb182eb8f429d93396079db87 | 13,819 |
def update_has_started(epoch, settings):
"""
Tells whether update has started or not
:param epoch: epoch number
:param settings: settings dictionary
:return: True if the update has started, False otherwise
"""
return is_baseline_with_update(settings['baseline']) and epoch >= settings['updat... | d2d2c8d7d8de0a13414a116121fb3cec47bc1d3f | 13,820 |
import torch
def compute_i_th_moment_batches(input, i):
"""
compute the i-th moment for every feature map in the batch
:param input: tensor
:param i: the moment to be computed
:return:
"""
n, c, h, w = input.size()
input = input.view(n, c, -1)
mean = torch.mean(input, dim=2).view(n... | 2ab3b7bfd34b482cdf55d5a066b57852182b5b6a | 13,821 |
def hs_online_check(onion, put_url):
"""Online check for hidden service."""
try:
print onion
return hs_http_checker(onion, put_url)
except Exception as error:
print "Returned nothing."
print error
return "" | 19b7b2f45581e2bdb907d416be1885f569841a86 | 13,822 |
def plotfile(fname, cols=(0,), plotfuncs=None,
comments='#', skiprows=0, checkrows=5, delimiter=',',
names=None, subplots=True, newfig=True, **kwargs):
"""
Plot the data in a file.
*cols* is a sequence of column identifiers to plot. An identifier
is either an int or a string.... | 493fccdf7d3661b9acffd22dbfd5799126a3d4f8 | 13,823 |
import argparse
def parse_options():
"""Parses and checks the command-line options.
Returns:
A tuple containing the options structure.
"""
usage = 'Usage: ./update_mapping.py [options]'
desc = ('Example: ./update_mapping.py -o mapping.json.\n'
'This script generates and stores a file that gives the\n... | 7f7ee6a90e152023dbf6c6e163361a8c327108ae | 13,824 |
def retrieve(object_type, **kwargs):
"""Get objects from the Metatlas object database.
This will automatically select only objects created by the current
user unless `username` is provided. Use `username='*'` to search
against all users.
Parameters
----------
object_type: string
The ... | 54d35c23dd92ad65c5911d8c451b5b1fcbd131da | 13,825 |
def read_plot_pars() :
"""
Parameters are (in this order):
Minimum box width,
Maximum box width,
Box width iterations,
Minimum box length,
Maximum box length,
Box length iterations,
Voltage difference
"""
def extract_parameter_from_string(string):
#returns the part ... | c78dc8e2a86b20eb6007850a70c038de5bf9f841 | 13,826 |
import typing
def create(subscribe: typing.Subscription) -> Observable:
"""Creates an observable sequence object from the specified
subscription function.
.. marble::
:alt: create
[ create(a) ]
---1---2---3---4---|
Args:
subscribe: Subscription function.
... | 79c149545475a7686f8f8dffaed8f343604dd4aa | 13,827 |
def tocl(d):
"""Generate TOC, in-page links to the IDs we're going to define below"""
anchors = sorted(d.keys(), key=_lower)
return TemplateData(t='All The Things', e=[a for a in anchors]) | 8c27c42f05e4055a8e195d4d352345acc7821bae | 13,828 |
def get_upper_parentwidget(widget, parent_position: int):
"""This function replaces this:
self.parentWidget().parentWidget().parentWidget()
with this:
get_upper_parentwidget(self, 3)
:param widget: QWidget
:param parent_position: Which parent
:return: Wanted parent widget
... | ff010f3d9e000cfa3c58160e150c858490f2412d | 13,829 |
def DirectorySizeAsString(directory):
"""Returns size of directory as a string."""
return SizeAsString(DirectorySize(directory)) | 3e3d3b029da40502c2f0e7e5867786d586ad8109 | 13,830 |
def patch_is_tty(value):
""" Wrapped test function will have peltak.core.shell.is_tty set to *value*. """
def decorator(fn): # pylint: disable=missing-docstring
@wraps(fn)
def wrapper(*args, **kw): # pylint: disable=missing-docstring
is_tty = shell.is_tty
shell.is_tty ... | 77655d32a5572824978910a12378a54d83b7e81e | 13,831 |
import torch
import math
def uniform_unit_scaling(tensor: torch.Tensor, nonlinearity: str = "linear"):
"""
An initaliser which preserves output variance for approximately gaussian
distributed inputs. This boils down to initialising layers using a uniform
distribution in the range `(-sqrt(3/dim[0]) * s... | aa14ec45c389c55c141d9bffd6ef370313fdf446 | 13,832 |
def get_results(elfFile):
"""Converts and returns collected data."""
staticSizes = parseElf(elfFile)
romSize = sum([size for key, size in staticSizes.items() if key.startswith("rom_")])
ramSize = sum([size for key, size in staticSizes.items() if key.startswith("ram_")])
results = {
"rom": ... | b60052f702e53655ab1a109ea2bb039e78aabaf5 | 13,833 |
def path_element_to_dict(pb):
"""datastore.entity_pb.Path_Element converter."""
return {
'type': pb.type(),
'id': pb.id(),
'name': pb.name(),
} | 2a4e757dedf6707dc412248f84b377c2f375e70c | 13,834 |
import tempfile
import os
def copy_to_tmp(in_file):
"""Copies a file to a tempfile.
The point of this is to copy small files from CNS to tempdirs on
the client when using code that's that hasn't been Google-ified yet.
Examples of files are the vocab and config files of the Hugging Face
tokenizer.
Argume... | 97b98214df23079d5aa9ee0ece072204d36d2f33 | 13,835 |
def get_orr_tensor(struct):
""" Gets orientation of all molecules in the struct """
molecule_list = get_molecules(struct)
orr_tensor = np.zeros((len(molecule_list),3,3))
for i,molecule_struct in enumerate(molecule_list):
orr_tensor[i,:,:] = get_molecule_orientation(molecule_struct)
return or... | faf42cf76168191835d9dd354ae9bc03198829ad | 13,836 |
def make_request_for_quotation(supplier_data=None):
"""
:param supplier_data: List containing supplier data
"""
supplier_data = supplier_data if supplier_data else get_supplier_data()
rfq = frappe.new_doc('Request for Quotation')
rfq.transaction_date = nowdate()
rfq.status = 'Draft'
rfq.company = '_Test Company... | ee0663231fc0bb06f6f43fa5abecdced048c1458 | 13,837 |
def mlrPredict(W, data):
"""
mlrObjFunction predicts the label of data given the data and parameter W
of Logistic Regression
Input:
W: the matrix of weight of size (D + 1) x 10. Each column is the weight
vector of a Logistic Regression classifier.
X: the data matrix of siz... | a37359433b020eb625b37ea57cb15282c4f82c8d | 13,838 |
import glob
import filecmp
import subprocess
def write_urdb_rate_data(urdb_rate_data, urdb_filepath = './', overwrite_identical=True):
"""
Takes Pandas DataFrame containing URDB rate data and stores as .csv at
urdb_filepath. The 'overwrite_identical' variable indicates whether
'urdb_rate_data' should... | cde6f16f4ba8abf2c744fb6ef579c0beddd407fd | 13,839 |
def add(n):
"""Add 1."""
return n + 1 | c62cee4660540ae62b5b73369bdeb56ccb0088d6 | 13,840 |
import psutil
import os
def get_system_status(memory_total=False,
memory_total_actual=False,
memory_total_usage=False,
memory_total_free=False,
all_pids=False,
swap_memory=False,
pid=Fal... | 79b3b43a3e046c2fc1237cde103c6f416ae1f01b | 13,841 |
def _area(x1, y1, x2, y2, x3, y3):
"""Heron's formula."""
a = np.sqrt(pow(x1 - x2, 2) + pow(y1 - y2, 2))
b = np.sqrt(pow(x3 - x2, 2) + pow(y3 - y2, 2))
c = np.sqrt(pow(x1 - x3, 2) + pow(y3 - y1, 2))
s = (a + b + c) / 2
return np.sqrt(s * (s - a) * (s - b) * (s - c)) | 456ffe56a76fbea082939c278b5f0f2ebaf8c395 | 13,842 |
def plot_coarray(array, ax=None, show_location_errors=False):
"""Visualizes the difference coarray of the input array.
Args:
array (~doatools.model.arrays.ArrayDesign): A sensor array.
ax (~matplotlib.axes.Axes): Matplotlib axes used for the plot. If not
specified, a new figure will... | e4a0d1fe4ab48b5050c55d44bd4ca4342cc9f9a9 | 13,843 |
def get_publicKey(usrID): # TODO: from barbican
"""
Get the user's public key
Returns:
Public key from meta-container (Keys) in meta-tenant
"""
auth = v3.Password(auth_url=AUTH_URL,username=SWIFT_USER,password=SWIFT_PASS,project_name='demo',project_domain_id="Default",user_domain_name='De... | 545dec9826273830767f395903cae878df8213b0 | 13,844 |
def pad_sequence(sequences, batch_first=False, padding_value=0.0):
"""Pad a list of variable-length Variables.
This method stacks a list of variable-length :obj:`nnabla.Variable` s with the padding_value.
:math:`T_i` is the length of the :math:`i`-th Variable in the sequences.
:math:`B` is the batch s... | 449c7681d39edc0494269aefd488aa44548a68df | 13,845 |
import urllib
import yaml
import requests
def _fetch_global_config(config_url, github_release_url, gh_token):
"""
Fetch the index_runner_spec configuration file from the Github release
using either the direct URL to the file or by querying the repo's release
info using the GITHUB API.
"""
if c... | c436bfb7692ce0d100367691588d511ed95bce99 | 13,846 |
def parse_color(c, desc):
"""Check that a given value is a color."""
return c | ebabefbd56de120a753723f1dccb0f7c12af2fe6 | 13,847 |
import os
def get_package_dir():
"""
Gets directory where package is installed
:return:
"""
return os.path.dirname(ndextcgaloader.__file__) | 447b6ed962119787c3c11f457fcf81bc31b0ae0d | 13,848 |
def __virtual__():
"""Only load gnocchiv1 if requirements are available."""
if REQUIREMENTS_MET:
return 'gnocchiv1'
else:
return False, ("The gnocchiv1 execution module cannot be loaded: "
"os_client_config or keystoneauth are unavailable.") | 5dc2a83ba6a93a37f037978bfe89edf6ec2fe103 | 13,849 |
def setup():
"""Start headless Chrome in docker container."""
options = webdriver.ChromeOptions()
options.add_argument('--no-sandbox')
options.add_argument('--headless')
options.add_argument('--disable-gpu')
driver = webdriver.Chrome(options=options)
driver.implicitly_wait(5)
return driv... | 79c135732b39513f270ac0f670ffddc89b576f75 | 13,850 |
import json
def lambdaResponse(statusCode,
body,
headers={},
isBase64Encoded=False):
"""
A utility to wrap the lambda function call returns with the right status code,
body, and switches.
"""
# Make sure the body is a json object
if not... | 0159ba871c38ce550752d47ffea536c33a5d6b3e | 13,851 |
def singleton(class_):
"""
Specify that a class is a singleton
:param class_:
:return:
"""
instances = {}
def getinstance(*args, **kwargs):
if class_ not in instances:
instances[class_] = class_(*args, **kwargs)
return instances[class_]
return getinstance | 678205d133783f6b0720876546deed9ed7c59d72 | 13,852 |
from typing import Optional
from typing import Union
from typing import List
from datetime import datetime
def is_datetime(
value: Scalar, formats: Optional[Union[str, List[str]]] = None,
typecast: Optional[bool] = True
) -> bool:
"""Test if a given string value can be converted into a datetime object for... | 642fbe509c7b13a905dc4c65b43dcec20f36fb7e | 13,853 |
def sortkey(d):
"""Split d on "_", reverse and return as a tuple."""
parts=d.split("_")
parts.reverse()
return tuple(parts) | 1d8f8864a3d0bfd7dae8711bca183317e0f3fc0e | 13,854 |
def resolve_stream_name(streams, stream_name):
"""Returns the real stream name of a synonym."""
if stream_name in STREAM_SYNONYMS and stream_name in streams:
for name, stream in streams.items():
if stream is streams[stream_name] and name not in STREAM_SYNONYMS:
return name
... | 48fe2f5eca72b30bd669477807c9b7476eb4ef18 | 13,855 |
def get_split_cifar100_tasks(num_tasks, batch_size,run,paradigm,dataset):
"""
Returns data loaders for all tasks of split CIFAR-100
:param num_tasks:
:param batch_size:
:return:
datasets = {}
# convention: tasks starts from 1 not 0 !
# task_id = 1 (i.e., first task) => start_class = 0, end_class = 4
cifar_... | 003c74a55a4e9a1f645a6bc930abf65342abd0fc | 13,856 |
def is_point_in_triangle(pt, v1, v2, v3):
"""Returns True if the 2D point pt is within the triangle defined by v1-3.
https://www.gamedev.net/forums/topic/295943-is-this-a-better-point-in-triangle-test-2d/
"""
b1 = sign(pt, v1, v2) < 0.0
b2 = sign(pt, v2, v3) < 0.0
b3 = sign(pt, v3, v1) < 0.0
... | 2ff58dfb4efe939513cc901772aa744296ebb960 | 13,857 |
def precomputed_aug_experiment(
clf,
auged_featurized_x_train,
auged_featurized_y_train,
auged_featurized_x_train_to_source_idxs,
auged_featurized_x_test,
auged_featurized_y_test,
auged_featurized_x_test_to_source_idxs,
aug_iter,
train_idxs_scores,... | 50f03f08c7ce0777658ca3f84691b940f190e4cd | 13,858 |
def get_yahoo_data(symbol, start_date, end_date):
"""Returns pricing data for a YAHOO stock symbol.
Parameters
----------
symbol : str
Symbol of the stock in the Yahoo. You can refer to this link:
https://www.nasdaq.com/market-activity/stocks/screener?exchange=nasdaq.
start_date : s... | adc2a6186d96c76a75a62391c7f8d7534836f5bd | 13,859 |
def first_n(m: dict, n: int):
"""Return first n items of dict"""
return {k: m[k] for k in list(m.keys())[:n]} | 57ccc9f8913c60c592b38211900fe8d28feffb4c | 13,860 |
from typing import List
from typing import Dict
from typing import Union
def listdictnp_combine(
lst: List,
method: str = "concatenate",
axis: int = 0,
keep_nested: bool = False,
allow_error: bool = False,
) -> Dict[str, Union[np.ndarray, List]]:
"""Concatenate or stack a list of dictionaries ... | b4527342c8a3b90c797e7ef88326c97b4933d1b0 | 13,861 |
def find_pure_symbol(symbols, clauses):
"""Find a symbol and its value if it appears only as a positive literal
(or only as a negative) in clauses.
>>> find_pure_symbol([A, B, C], [A|~B,~B|~C,C|A])
(A, True)
"""
for s in symbols:
found_pos, found_neg = False, False
for c in claus... | 657c011fb0ee865252e7deed4672cde08c6db2e9 | 13,862 |
def cross_entropy_emphasized_loss(labels,
predictions,
corrupted_inds,
axis=0,
alpha=0.3,
beta=0.7,
regularizer=None... | e4ebb4e3198dea085789c81388522130ed867e3f | 13,863 |
def get_process_list(node: Node):
"""Analyse the process description and return the Actinia process chain and the name of the processing result
:param node: The process node
:return: (output_objects, actinia_process_list)
"""
input_objects, process_list = check_node_parents(node=node)
output_o... | 00f5e6c767975def09fbea800a8b74cfcd12f935 | 13,864 |
def _validate_image_formation(the_sicd):
"""
Validate the image formation.
Parameters
----------
the_sicd : sarpy.io.complex.sicd_elements.SICD.SICDType
Returns
-------
bool
"""
if the_sicd.ImageFormation is None:
the_sicd.log_validity_error(
'ImageFormatio... | b68c9a767e2499b8149389e2e207a0f05d20bf44 | 13,865 |
def handle_closet(player, level, reward_list):
"""
Handle a closet
:param player: The player object for the player
:param level: The level that the player is on
:return reward: The reward given to the player
"""
# Print the dialogue for the closet
print "You found a closet. It appears t... | ab170cb556fd688edeac80eac9bb7577df771a33 | 13,866 |
def module_path_to_test_path(module):
"""Convert a module locator to a proper test filename.
"""
return "test_%s.py" % module_path_to_name(module) | 17997d17d64686deec97d4aa9f23a14f04ff5516 | 13,867 |
def inspect_bom(filename):
"""Inspect file for bom."""
encoding = None
try:
with open(filename, "rb") as f:
encoding = has_bom(f.read(4))
except Exception: # pragma: no cover
# print(traceback.format_exc())
pass
return encoding | 84da40bc941053c4e6d18934c27b3e1d63318762 | 13,868 |
from packaging.specifiers import SpecifierSet
def parse_requirement(text):
"""
Parse a requirement such as 'foo>=1.0'.
Returns a (name, specifier) named tuple.
"""
match = REQUIREMENT_RE.match(text)
if not match:
raise ValueError("Invalid requirement: %s" % text)
name = match.gro... | 95dab6f3dd6784bf73233e80cfb946f904984a1d | 13,869 |
def H_split(k, N, eps):
"""Entropy of the split in binary search including overlap, specified by
eps"""
return (k / N) * (np.log(k) + H_epsilon(k, eps)) + ((N - k) / N) * (np.log(N - k) + H_epsilon(N - k, eps)) | 555d5e56550851084fdfa148dc7936c75649a197 | 13,870 |
def date_features(inputs, features_slice, columns_index) -> tf.Tensor:
"""Return an input and output date tensors from the features tensor."""
date = features(inputs, features_slice, columns_index)
date = tf.cast(date, tf.int32)
date = tf.strings.as_string(date)
return tf.strings.reduce_join(date, ... | 3362019b24a6f3104d858d2ddf17f0fae4060d7b | 13,871 |
import pickle
def save_calib(filename, calib_params):
""" Saves calibration parameters as '.pkl' file.
Parameters
----------
filename : str
Path to save file, must be '.pkl' extension
calib_params : dict
Calibration parameters to save
Returns
-------
saved : bool
Saved successfully.
"""
i... | 6735c8a6e96158b9fc580b6e61609b5ae7733fe0 | 13,872 |
def context_to_dict(context):
"""convert a django context to a dict"""
the_dict = {}
for elt in context:
the_dict.update(dict(elt))
return the_dict | b319c6be4efa83c91eefa249c8be90824bc0158f | 13,873 |
def returnItemsWithMinSupport(itemSet, transactionList, minSupport, freqSet):
"""calculates the support for items in the itemSet and returns a subset
of the itemSet each of whose elements satisfies the minimum support"""
_itemSet = set()
localSet = defaultdict(int)
for item in it... | e1290778548f198f87fc210c8a78bbfadaf0de9f | 13,874 |
def create_P(P_δ, P_ζ, P_ι):
"""
Combine `P_δ`, `P_ζ` and `P_ι` into a single matrix.
Parameters
----------
P_δ : ndarray(float, ndim=1)
Probability distribution over the values of δ.
P_ζ : ndarray(float, ndim=2)
Markov transition matrix for ζ.
P_ι : ndarray(float, ndim=1)... | 0afdef50c50563421bb7c6f3f928fa6b3e5f4733 | 13,875 |
import attrs
def sel_nearest(
dset,
lons,
lats,
tolerance=2.0,
unique=False,
exact=False,
dset_lons=None,
dset_lats=None,
):
"""Select sites from nearest distance.
Args:
dset (Dataset): Stations SpecDataset to select from.
lons (array): Longitude of sites to in... | ebf22cdeb30215a76312f2cdd8223a2d24bf6af6 | 13,876 |
import datasets
def evaluate(dataset, predictions, gts, output_folder):
"""evaluate dataset using different methods based on dataset type.
Args:
dataset: Dataset object
predictions(dict): each item in the list represents the
prediction results for one image.
gt(dict): Groun... | 85c0232c53de091f2293d042b944fe8768a9ac91 | 13,877 |
from vlescrapertools import getAuthedSession
def html_xml_save(
s=None, possible_sc_link=None, table="htmlxml", course_presentation=None
):
"""Save the HTML and XML for a VLE page page."""
if not possible_sc_link:
# should really raise error here
print("need a link")
if not s:
... | 37bb86769c86d851e3fec8dabc17534dfdecde60 | 13,878 |
import os
def app(request):
"""An instance of the Flask app that points at a test database.
If the TEST_DATABASE environment variable is set to "postgres", launch a temporary PostgreSQL
server that gets torn down at the end of the test run.
"""
database = os.environ.get('TEST_DATABASE', 'sqlite')... | 52cac3b340ef0fb5a92449242644c1061a5cba2b | 13,879 |
def htmr(t,axis="z"):
"""
Calculate the homogeneous transformation matrix of a rotation
respect to x,y or z axis.
"""
from sympy import sin,cos,tan
if axis in ("z","Z",3):
M = Matrix([[cos(t),-sin(t),0,0],
[sin(t),cos(t),0,0],
[0,0,1,0],
... | b3941680f22b2eb48da15b2bb1a6e39c05e3b5c3 | 13,880 |
def vt(n, gm, gsd, dmin=None, dmax=10.):
"""Evaluate the total volume of the particles between two diameters.
The CDF of the lognormal distribution is calculated using equation 8.12
from Seinfeld and Pandis.
Mathematically, it is represented as:
.. math::
V_t=\\frac{π}{6}∫_{-∞}^{∞}D_p^3n... | ba407dc86bbf3201bd597f729f2397ef9428e72b | 13,881 |
def core_value_encode(origin):
"""
转换utf-8编码为社会主义核心价值观编码
:param origin:
:return:
"""
hex_str = str2hex(origin)
twelve = hex2twelve(hex_str)
core_value_iter = twelve_2_core_value(twelve)
return ''.join(core_value_iter) | 7b81540f7e7184ec60fb6820e3548201d67eec29 | 13,882 |
def user_query_ahjs_is_ahj_official_of(self, request, queryset):
"""
Admin action for the User model. Redirects the admin to
a change list of AHJs the selected users are AHJ officials of.
"""
model_name = 'ahj'
field_key_pairs = [field_key_pair('AHJPK', 'AHJPK')]
queryset = AHJUserMaintains.... | 4d97f25f2647a92a9690bf3360bd3fd63b03d631 | 13,883 |
def get_cache_node_count(
cluster_id: str, configuration: Configuration = None, secrets: Secrets = None
) -> int:
"""Returns the number of cache nodes associated to the cluster
:param cluster_id: str: the name of the cache cluster
:param configuration: Configuration
:param secrets: Secrets
:ex... | e4a4b3cd6d0bf7416ffe5a3d86725a614ad1c41c | 13,884 |
import string
def top_sentences(query, sentences, idfs, n):
"""
Given a `query` (a set of words), `sentences` (a dictionary mapping
sentences to a list of their words), and `idfs` (a dictionary mapping words
to their IDF values), return a list of the `n` top sentences that match
the query, ranked ... | 5533b96848baea5afa614e691d2d2ae07c4a16a9 | 13,885 |
def load_distribution(label):
"""Load sample distributions as described by Seinfeld+Pandis Table 8.3.
There are currently 7 options including: Urban, Marine, Rural, Remote
continental, Free troposphere, Polar, and Desert.
Parameters
----------
label : {'Urban' | 'Marine' | 'Rural' | 'Remote C... | 3dfd2fea5c165c331255e3b350e1f92a37919726 | 13,886 |
from typing import List
def split_4d_itk(img_itk: sitk.Image) -> List[sitk.Image]:
"""
Helper function to split 4d itk images into multiple 3 images
Args:
img_itk: 4D input image
Returns:
List[sitk.Image]: 3d output images
"""
img_npy = sitk.GetArrayFromImage(img_itk)
spa... | 21ad4f6c0cbdb05cf6f67469e3d32e732d1500ee | 13,887 |
from bs4 import BeautifulSoup
def parse_results(html, keyword):
"""[summary]
Arguments:
html {str} -- google search engine html response
keyword {str} -- search term
Returns:
pandas.DataFrame -- Dataframe with the following columns ['keyword', 'rank', 'title', 'link', 'domain']
... | 4c89e919b3f3285565efe5bdf5c4ec5b87664c79 | 13,888 |
def maybe_iter_configs_with_path(x, with_params=False):
"""
Like x.maybe_iter_configs_with_path(), but returns [(x, [{}])] or [(x, {}, [{}])] if x is just a config object and not a Tuner object.
"""
if is_tuner(x):
return x.iter_configs_with_path(with_params=with_params)
else:
if wi... | 947a62067f3eacb4d5c8ba419d8018ad2ab3320c | 13,889 |
import typing
def median(vals: typing.List[float]) -> float:
"""Calculate median value of `vals`
Arguments:
vals {typing.List[float]} -- list of values
Returns:
float -- median value
"""
index = int(len(vals) / 2) - 1
return sorted(vals)[index] | 9f840d11409a570a718fdfe56d7a282af43bc798 | 13,890 |
def melody_mapper(notes):
"""
Makes a map of a melody to be played
each item in the list 'notes' should be formatted using these chars:
duration - length in seconds the sound will be played
note - the note to play
sleep - time in seconds to pause
(note, duration)
... | cf4c8f7864e91e771d3a70bfc4d8a7f4edb38967 | 13,891 |
def sample_bounding_box_scale_balanced_black(landmarks):
"""
Samples a bounding box for cropping so that the distribution of scales in the training data is uniform.
"""
bb_min = 0.9
bb_old = image.get_bounding_box(landmarks)
bb_old_shape = np.array((bb_old[2] - bb_old[0], bb_old[3] - bb_old[1])... | 789cbe92803b77614ab8a018434745b2d9bba3a4 | 13,892 |
import glob
import os
def get_files(data_path):
"""
获取目录下以及子目录下的图片
:param data_path:
:return:
"""
files = []
exts = ['jpg', 'png', 'jpeg', 'JPG','bmp']
for ext in exts:
# glob.glob 得到所有文件名
# 一层 2层子目录都取出来
files.extend(glob.glob(os.path.join(data_path, '*.{}'.form... | 1a81aa7679eb2c70d29d3e80423c4b2e860c307d | 13,893 |
def get_trainable_layers(layers):
"""Returns a list of layers that have weights."""
layers = []
# Loop through all layers
for l in layers:
# If layer is a wrapper, find inner trainable layer
l = find_trainable_layer(l)
# Include layer if it has weights
if l.get_weights():... | 2d3f00cb061a6c2ee7081468be564f0b8621441d | 13,894 |
def outcome_from_application_return_code(return_code: int) -> outcome.Outcome:
"""Create either an :class:`outcome.Value` in the case of a 0 `return_code` or an
:class:`outcome.Error` with a :class:`ReturnCodeError` otherwise.
Args:
return_code: The return code to be processed.
Returns:
... | c5b786906e0f3fd99ed6660c55213b18139003c0 | 13,895 |
import re
def group_by_scale(labels):
""" Utility that groups attribute labels by time scale """
groups = defaultdict(list)
# Extract scales from labels (assumes that the scale is given by the last numeral in a label)
for s in labels:
m = re.findall("\d+", s)
if m:
groups[m... | 661ea03f8d463b1e0d5746df60e9e2cb969737ab | 13,896 |
def FontMapper_GetEncodingDescription(*args, **kwargs):
"""FontMapper_GetEncodingDescription(int encoding) -> String"""
return _gdi_.FontMapper_GetEncodingDescription(*args, **kwargs) | 0f154eaa616c3b18bc8828f63137c26c75397d56 | 13,897 |
from typing import Counter
def create_merged_ngram_dictionaries(indices, n):
"""Generate a single dictionary for the full batch.
Args:
indices: List of lists of indices.
n: Degree of n-grams.
Returns:
Dictionary of hashed(n-gram tuples) to counts in the batch of indices.
"""
ngram_dicts = []... | bd313ea7eab835102e94f6c7d66fec8882531385 | 13,898 |
import base64
def compute_hash_base64(*fields):
"""bytes -> base64 string"""
value = compute_hash(*fields)
return base64.b64encode(value).decode() | b29b77b44a51417d63f8cae1970b5c1f4fb40317 | 13,899 |
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