content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import typing
from pydantic import BaseModel # noqa: E0611
from re import T
def describe_response(
status: typing.Union[int, HTTPStatus],
description: str = "",
*,
content: typing.Union[typing.Type[BaseModel], type, dict] = None,
headers: dict = None,
links: dict = None,
) -> typing.Callable[... | 8cbe3b5c519ea2383a2d20a1f46abd967084866d | 40,049 |
def report_exception(f):
""" Minimal decorator for reporting exceptions that occur within a
function. Does not support generators."""
@wraps(f)
def wrapped_f(*args, **kwargs):
try:
return f(*args, **kwargs)
except:
sentry_sdk.capture_exception()
raise
... | 5af0ace66d157ed84b03e0b5256d2a75f56eec07 | 40,050 |
def uncorr_noise_deprojection_bias(f1, map_var):
"""
Computes the bias associated to contaminant removal in the presence of uncorrelated inhomogeneous noise to the auto-pseudo-Cl of a given field f1.
:param NmtField f1: fields to correlate
:param map_cls_guess: array containing a HEALPix map correspond... | 588379d9011fec22be3d9f1f4888ff4569e59499 | 40,053 |
def convert_expression(lst_tkn:list):
"""
Parameters:
-----------
* lst_tkn [list]: list containing the raw tokens.
Return:
-------
* lst_res [list]: NPI tokens list obtained by shunting-yeard algorithm.
"""
lst_tkn = natural_conversion(lst_tkn)
lst_res = shunting_yard_al... | 2b8954b092f1d4de9c46b2ab608e363ec5aa71f2 | 40,054 |
def value(colors: list):
"""
Each resistor has a resistance value.
Manufacturers print color-coded bands onto
the resistors to denote their resistance values.
Each band acts as a digit of a number.
The program will take two colors as input,
and output the correct number.
:param colors:
... | 14a52f12bfcfccd921ade8fa7708d3563c9c2508 | 40,055 |
import array
def intersect_curve_surface(curve, surface, itol=None):
"""
Find the intersection points of a curve and a surface.
:param curve: Curve to intersect.
:type curve: :class:`.BezierCurve` or :class:`.NurbsCurve`
:param surface: Surface to intersect.
:type surface: :class:`.BezierSurf... | 4c75b0f41b2345060f63032a0466bc0ed07cce69 | 40,056 |
def get_test_batch(data, batch_size=100, stim_history=30, min_window=10):
"""Get a batch of training data."""
stim = data['stimulus']
resp = data['responses']
ei_mag = data['ei_magnitude']
stim_batch = np.zeros((batch_size, stim.shape[1],
stim.shape[2], stim_history))
resp_batch =... | c07642e213414fa192b5fd7c50822ed03ecf8afb | 40,057 |
def rgb_to_hex(r, g, b):
"""
Generate a html hex color string from r,g,b values
:params r,g,b: (0,1) range floats
:return: a html compatible hex color string
"""
assert is_valid_rgb(r, g, b), "Error, r,g,b must be (0,1) range floats"
R,G,B = rgb_to_RGB(r,g,b)
return "#{:02x}{:02x}{:... | a71b30a96231940a019b9e16c7a2b06afe622073 | 40,058 |
def load_transforms(name):
"""Load data transformations.
Note:
- Gaussian Blur is defined at the bottom of this file.
"""
_name = name.lower()
if _name == "cifar_sup":
normalize = transforms.Normalize([0.4914, 0.4822, 0.4465], [0.2023, 0.1994, 0.2010])
aug_transform... | e925adebd7c414f53f20a902622734509922138c | 40,059 |
def set_axes(ax: Axes, x_scale: str = 'linear', y_scale: str = 'linear', xlim: tuple = (), ylim: tuple = (),
fontsize: int = 20, show_grid: bool = True,
hide_xticklabels: bool = False, hide_yticklabels: bool = False) -> Axes:
"""
Sets axes to an existing ax. The explanation of the argu... | 78f793f76af961c6785dcc8ee1d8f12dd0d71e8f | 40,060 |
def parallel_run(tasks):
"""
Tasks is an iterable of bound functions. The wrapper makes it easy for us
to run a list of different functions, rather than one function over a list
of inputs.
"""
workers = max(1, len(tasks))
with Pool(processes=workers) as pool:
# As soon as any one ta... | 067d437c5fe6269d8df8fbbe11dc797e0e94a41a | 40,062 |
def bgr_to_hex(b, g, r):
"""Converts (blue, green, red) to a "#rrbbgg" string.
Args:
b, g, r: the BGR values
Returns:
a hex string
"""
return rgb_to_hex(r, g, b) | 97d91cfd544a0dc3bae97fb81e0f626c40dc0ebe | 40,063 |
from typing import List
def get_all_csv_files_in_folder(folder: str) -> List[str]:
"""Returns list of strings including path to folder for CSV files"""
return get_all_files_in_folder_ending_with(folder=folder, ending=OUTPUT_FILE_ENDING) | b025404edd4a23cbb96c67ae9e02dfdc59562767 | 40,064 |
import numpy
def linear_correct_byte(image: numpy.ndarray, gamma: float = 2.2) -> numpy.ndarray:
"""
:param image:
:type image:
:param gamma:
:type gamma:
:return:
:rtype:"""
return gamma_correct_float_to_byte(image / 255, gamma) | a307a28724ae0dfd4470a163b489b18397f36a5e | 40,065 |
import base64
def is_authenticated(request, username, password):
"""Authenticate the request using HTTP Basic authorization"""
authenticated = False
if 'HTTP_AUTHORIZATION' in request.META:
auth = request.META['HTTP_AUTHORIZATION'].split()
if len(auth) == 2:
if auth[0].lower() ... | 9ea596245283d34146058e7c79964646661c2151 | 40,066 |
def inspect_object(object_: object):
"""Find all members of Python object.
Example:
def say_hi(name: str) -> str:
print(f"hi {name}")
print(inspect_object(say_hi))
>>> say_hi=>
type=<class 'function'>
parameters=>
name=>
annotation=<class 'str'>
default=None
kind=POSITIONAL_OR_KEYWORD
... | 06dc3558861dd2488e7e88c379a9c6d103812b3b | 40,067 |
def recall(prediction, ground_truth, average="macro"):
"""
Return the recall score evaluated between PREDICTION and GROUND_TRUTH
average - (default: "macro") mode of averaging for multi-class prediction
"""
return metrics.recall_score(
prediction,
ground_truth,
... | f526752e1187b4eaef8c44169442faca8e04e6cf | 40,068 |
def tf_lipschitz_constant(M, G, phi, phiT, tol=1e-3, verbose=None):
"""Compute lipschitz constant for FISTA
It uses a power iteration method.
"""
n_times = M.shape[1]
n_points = G.shape[1]
iv = np.ones((n_points, n_times), dtype=np.float)
v = phi(iv)
L = 1e100
for it in range(100):
... | 75c66a3909debc23c06894e2040737be6e2081f0 | 40,069 |
def fourCornersSort(pts):
""" Sort corners: top-left, bot-left, bot-right, top-right """
# Difference and sum of x and y value
# Inspired by http://www.pyimagesearch.com
diff = np.diff(pts, axis=1)
summ = pts.sum(axis=1)
# Top-left point has smallest sum...
# np.argmin() returns INDEX o... | 05fa8b611b4f42853282f0d55d301be74f78e873 | 40,070 |
import abc
import copy
def populate_user_output_from_schema_and_outputs(output_schema, output_names, outputs):
"""Follows the schema to generate an output that is expected by the user"""
def _replace_stub_with_tensor_value(user_output, outputs, output_idx):
# Recursively traverse across user_output a... | 600d72ae8d886b35cc62bb1250163fb82f309727 | 40,071 |
def get_current_mapset():
"""Return the current mapset
This is the fastest way to receive the current mapset.
The current mapset is set by init() and stored in a global variable.
This function provides access to this global variable.
"""
global current_mapset
return current_mapset | 90c183d91cdf8c8db2a56c49a3e0d843087a9436 | 40,072 |
def compress_image_to_file(path, terms, annotate, iterations=None, path_out=None):
"""
Compresses the image from `path` using singular value expansion.
The image is saved to an output file which name is chosen automatically,
unless `path_out` is specified.
Parameters
----------
path : path
... | 20385189911c25ebe0c4ede335091542fd7fb7a4 | 40,073 |
from typing import Counter
def merge_vocabs(vocabs, vocab_size=None):
"""
Merge individual vocabularies (assumed to be generated from disjoint
documents) into a larger vocabulary.
Args:
vocabs: `torchtext.vocab.Vocab` vocabularies to be merged
vocab_size: `int` the final vocabulary si... | f7237ad4342acabf444c9facf6dc4eb841140082 | 40,074 |
import torch
def nan_mode(input):
"""Mode value for tensor (ignoring NaNs)."""
return torch.mode(input[~torch.isnan(input)])[0] | cf2ef4fb23a0dfbc251dd385a38ed8e01142ac08 | 40,075 |
import pandas
from re import T
import numpy
def event_values_block(
da: xarray.DataArray,
events: pandas.DataFrame,
offset: T.Union[T.Iterable[int], T.Dict[T.Hashable, int]],
load: bool = True,
):
"""
Gets the values from da where an event is active
"""
if load:
da = da.load()... | 419b10f9ef9384cf60a4277e6fdaa518cd43d2f7 | 40,076 |
def get_signing_pubkey(client, secret_url):
"""
Gets a PEM file from the vault, and returns one of RSAPublicKey, DSAPublicKey, or
EllipticCurvePublicKey depending on the contents of the secret.
"""
try:
raw_pubkey = client.get_secret(secret_url).value
return load_ssh_public_key(
... | 3b23e7c3d95b07a1460fd1e136ce42e5782b0990 | 40,077 |
def validate_dandiset_yaml(filepath):
"""Validate dandiset.yaml"""
with open(filepath) as f:
meta = yaml_load(f, typ="safe")
return _check_required_fields(meta, _required_dandiset_metadata_fields) | 86d199a89b72c8df361af7be163ee7ca57cb9600 | 40,079 |
def get_grads(spike_stats, targets_frs, update_rule=0.0005):
"""Calculate gradients for updating the synaptic weights"""
mean_frs = spike_stats['firing_rate']['mean']
fr_diffs = {pop_name: (trg_fr - mean_frs.loc[pop_name]) for pop_name, trg_fr in targets_frs.items()}
mse = np.sum(np.power(list(fr_diffs.... | 6fd845f811bee0abc0f512bd9e8d5a0b91064f1a | 40,080 |
def _im_to_blocks(im, width, roi=None, roi_method="all"):
"""
Converts image to list of square subimages called "blocks."
Parameters
----------
im: array_like
Image to convert to a list of blocks.
width: int
Width of square blocks in units of pixels.
roi: array_like, dtype b... | 029751c9b2c0052e9718f44c231066dc37b569d6 | 40,081 |
from typing import Dict
import re
import string
def preprocess(docs: Dict[str,str], **kwargs):
"""
Takes as input a dictionary of the documents for clustering and transforms them into the compact data structures of corpus and Vocabulary in preperation for clustering.
This process turns each document from... | 7e2adfeed7f7738763829bfed8784f7f993933c0 | 40,082 |
def activation(func_a):
"""Activation function wrapper
"""
return eval(func_a) | ad7f668aec546de452ef4968b22c338c2ca873b6 | 40,083 |
def gravity(z, g0, r0):
"""Relates Earth gravity field magnitude with the geometric height.
Parameters
----------
z: float
Geometric height.
g0: float
Gravity value at sea level.
r0: float
Planet/Natural satellite radius.
Returns
-------
g: float
Gra... | 28b0fdacbadf63755870024acec99b4a38057e24 | 40,084 |
def tfunc(t, rdd):
"""
Transforming function. Converts our blank RDD to something usable
:param t: datetime
:param rdd: rdd
Current rdd we're mapping to
"""
return rdd.flatMap(lambda x: stream_twitter_data()) | d60a9731e3134e04c38f855aedb202ec895a15e1 | 40,085 |
def quote_columns_data(data: str) -> str:
"""When projecting Queries using dot notation (f.e. inventory [ facts.osfamily ])
we need to quote the dot in such column name for the DataTables library or it will
interpret the dot a way to get into a nested results object.
See https://datatables.net/referenc... | db5e82e5d3641bebcac069ac4d5a7bb42baafcbb | 40,086 |
def svn_client_checkout2(*args):
"""svn_client_checkout2(char const * URL, char const * path, svn_opt_revision_t peg_revision, svn_opt_revision_t revision, svn_boolean_t recurse, svn_boolean_t ignore_externals, svn_client_ctx_t ctx, apr_pool_t pool) -> svn_error_t"""
return _client.svn_client_checkout2(*args) | f0891b04e0eac9675e6912f105e8499ede218ef9 | 40,087 |
def sort_kv_pairs_by_value(d):
"""Turn a dict into a list of key-value pairs, sorted by value."""
return [
(k, v) for v, k in sorted([(v, k) for k, v in d.items()], reverse=True)
] | 58f3e40c4993a64f71212157fdd73ad82712fa44 | 40,088 |
import csv
def parsaCollettivi(file_collettivi):
""" Dato il csv genera lista di collettivi """
collettivi = []
with open(file_collettivi, 'r') as aulefile:
parsedCollettivi = csv.reader(aulefile, delimiter=';')
for row in parsedCollettivi:
flags = []
turni = []
... | 88c0e972232baae19862df3c3a6bc9324d94a501 | 40,089 |
def rk4(derivs, y0, t, *args, **kwargs):
"""
Integrate 1D or ND system of ODEs using 4-th order Runge-Kutta.
This is a toy implementation which may be useful if you find
yourself stranded on a system w/o scipy. Otherwise use
:func:`scipy.integrate`.
Args:
derivs: the derivative of the sys... | 3db3e7131525ff7b9decb554c99b67f9dc8a40dc | 40,090 |
def hexEncode(value):
"""Some replaces."""
if isinstance(value, unicode):
value = value.encode('ascii', 'backslashreplace')
return value | 06b4a4d1e6c8b3fff74fa6b2c0240b428f54eef6 | 40,091 |
import logging
def get_logger(name=None, level=None, stream=DEFAULT_STREAM,
clobber_root_handler=True, logger_factory=None,
wrapper_class=None):
"""Configure and return a logger with structlog and stdlib."""
_configure_logger(
logger_factory=logger_factory,
wrappe... | 4ed97ccb18096ae67dc37d957f6607a6de9ee3fc | 40,092 |
def log_likelihood(model,data) :
"""Return log10 (normalized) likelihood: P(3D astrometry | 3D phase space, Covariance)"""
functions = []
for s in data :
functions.append(imageLikelyhood(s))
images = getImages(model)
if(len(images)==len(functions)): # probably a very bad idea
re... | 5b74b3e6e503cb6f4a29a4db6a5574dd883bf806 | 40,093 |
def yices_division(t1, t2):
"""Returns the term (t1 / t2) from the given terms, or NULL_TERM if there's an error.
division(t1, t2):
t1 and t2 must be arithmetic terms
NOTE: Until Yices 2.5.0, t2 was required to be a non-zero constant.
This is no longer the case: t2 can be any arithmetic term.
... | 32daac08ea6b9004e68505a8db1843dd18027949 | 40,095 |
import string
def is_string_formatted(s, return_parsed_list=False):
""" check if a string has formatted characters (with curly braces) """
l = list(string.Formatter().parse(s))
if len(l) == 1 and l[0][0] == s:
is_formatted = False
else:
is_formatted = True
if return_parsed_list:
... | a47a698d1c53bbf4bfb88ec7aca9e1ed3b0958d5 | 40,096 |
def extract_number(img):
"""Get the image number only"""
img=img.split('.fits')
nimg=int(img[0][-4:])
return nimg | 693648b7ea11fe311da1c30485e69ed0a6aea774 | 40,097 |
def cv_score_table(res_sprm_cv):
"""
Internal function reorganizing sklearn GridSearchCV results to pandas table.
The function adds the cv score table to the object as cv_score_table_
"""
n_settings = len(res_sprm_cv.cv_results_['params'])
etas = [res_sprm_cv.cv_results_['para... | 8d139a8cfb5c2bfd625409fa319d3ff189f3afec | 40,098 |
def calc_aridity(prec, pet, water_year):
"""Calculates the aridity as described in Knoben et al (2018)"""
prec = prepare_data(prec, water_year=water_year)
pet = prepare_data(pet, water_year=water_year)
prec_pet = pd.concat([prec[0],pet.iloc[:,0:2]],axis=1)
prec_pet.columns = ["prec", "pet", "water_... | 661c5b76941abf14e2befa834d9e7d2fce8eb908 | 40,099 |
def group_reads_by_allele(allele_reads):
"""
Returns dictionary mapping each allele's nucleotide sequence to a list of
supporting AlleleRead objects.
"""
return groupby(allele_reads, lambda read: read.allele) | b7a18b40b45d0eeb5234b1f79f6b114bc109b64a | 40,101 |
from typing import Optional
from typing import MutableMapping
from typing import Any
def create_handler(
session: Optional[SessionProxy],
request: ResourceHandlerRequest,
callback_context: MutableMapping[str, Any], # pylint: disable=unused-argument
) -> ProgressEvent:
"""This function is triggered by... | 850f5c600fea75ac56ec4643888235a1ce5db836 | 40,102 |
import sqlite3
def get_buoy_metadata(db):
"""
Extracts the meta data from the buoy database.
Parameters
----------
db : str
Full path to the buoy data SQLite database.
Returns
-------
meta_info : list
List of dicts with keys based on the field names from the Stations
... | 0a985b57093661d768d09f90ff5b2e66d1ad24ca | 40,103 |
def get_dist_args(dist):
"""Probe a scipy.stats distribution (or JMCtools distribution) for its
required arguments"""
has_args = False
try:
fargs = dist.args
has_args = True
except AttributeError:
has_args = False
if not has_args:
try:
func_args = g... | af274ebfc4d1667bead06203c48111907f1f8d0f | 40,104 |
def MobileNetV2(
input_shape,
alpha=0.35,
include_top=True,
pooling=None,
classes=1000,
classifier_activation='softmax',
last_block_filters=None,
**kwargs
):
"""Instantiates the MobileNetV2 architecture.
.. seealso::
* `MobileNetV2: Inverted Residuals and Linear Bottlenecks <https://arxiv.org/... | 4eac36750d536cd4e98247c85271abf3dcf22e6f | 40,105 |
from typing import Collection
def update_menu_item_linked_object(menu_item, linked_object):
"""Assign new linked object to a menu item. Clear other links."""
menu_item.category = None
menu_item.collection = None
menu_item.page = None
if isinstance(linked_object, Category):
menu_item.categ... | 708c8af16a565d5093bf36a0b9ad65a12f6e57ac | 40,106 |
from datetime import datetime
def _get_creation_date():
"""作成時刻を返す"""
return datetime.utcnow().strftime('%Y-%m-%d-T%H:%M:%SZ') | a6725716361b0b37c35c62fe1f9600224d8d04f2 | 40,107 |
def _param_with_axes_sow_reduce_fn(x, y):
"""Reduction function for sow() calls.
Args:
x: Existing value, or () if there was none.
y: New axis names sown.
Returns:
New axis names.
Raises:
TypeError: If the newly sown value is not an AxisMetadata.
ValueError: If the newly sown axis names d... | 7f5ba0199c7ee8743c3bb6d6a4d9a0d2c7654221 | 40,108 |
def combine_similar_titles(extracted_strings):
"""Take a dictionary with titles and nested dicts with scores
and combine scores for titles which we decide are the same."""
# Iterate through each possible pair of title keys, including both
# permutations of each pair
for title_pair in permutation... | 4eaf64cbff8e6000ba41d8e6b8abcde737e06543 | 40,109 |
import operator
def rkLeavesByK(hmat):
"""Sort the Rk leaves by descending compression ratio.
Args:
hmat: an instance of HMatrixStructure
Returns:
[(compression_ratio1, leaf1), ...]
"""
leaves = hmat.listRkLeaves()
ratio_leaves = [(x.k, x) for x in leaves]
ratio_leaves.sort(k... | 228eef2af7c422471744b1c92572d5e66f69166b | 40,110 |
def check_length(min_length: int,
max_length: int,
mode: str = 'and',
*args) -> bool:
"""
check items length is between min_length and max_length
:param min_length: minimum length
:param max_length: maximum length
:param mode: check mode, 'and': all... | f959619a466f62bf6ecfaf10e0fbb316652891e7 | 40,111 |
def _fix_estrs(estrs):
"""Add fitzpatrick colors, and remove emoji variation selectors.
1) The emoji ordering html page omits the skin color variants. Since
we want to display them, we have to add them. However, we don't add
them for sequences with multiple people, since we don't support
multiracial groups ... | 2e7ac8ac84d7a3afad796b607efb075e3ef8d087 | 40,112 |
from typing import Type
from re import T
from typing import Dict
def dict_to_df(desired_type: Type[T], dict_obj: Dict, logger: Logger, orient: str = None, **kwargs) -> pd.DataFrame:
"""
Helper method to convert a dictionary into a dataframe. It supports both simple key-value dicts as well as true
table di... | dad9f8f0630404641bc8316ab06c817d8df51c3a | 40,113 |
import html
def architecture_summary():
"""
Returns the text and image of architecture summary of the project.
"""
return html.Div(children=[
dcc.Markdown('''
# Project Architecture
This project uses MongoDB as the database. All data acquired are stored in raw form to t... | 6e5221c5cf3179760180242c583c4c0c1c3f1a8c | 40,114 |
def chunk_str(msg, sep=(" ", ".", ",", "(")):
"""
chunk_str will take a string and a tuple of separators and recursively
split the string into Chunk objects that record which separator was
used to split it.
:param msg: The string that we want to break apart.
:type msg: str
:param sep... | f1735fc8fda1a86eb3a3722c60764c3e40fc5041 | 40,115 |
def build_shared_head(cfg):
"""Build shared head of detector."""
return build(cfg, SHARED_HEADS) | ed82b32b8fab10120ac9a611d18ac0ebae43aa18 | 40,117 |
def check_csrf(func):
"""Checks/removes a csrf_token from request.session's list of valid tokens."""
def _wrapper(request, *args, **kw):
valid_csrf_tokens = request.session.get('csrf_tokens')
request_csrf_token = request.REQUEST.get('csrf_token')
# Special easter-egg to get around the csrf token.
#... | ee3d9b78528318750b08c191bfe0375c6dca95a9 | 40,118 |
from typing import Optional
def get_connection_monitor(connection_monitor_name: Optional[str] = None,
network_watcher_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> ... | 65829ab0b59914cc4dc71b7575641fab9e09959c | 40,119 |
def ssh(host, user, passwd, log=LOG):
"""SSH to any host.
"""
ssh = paramiko.SSHClient()
ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh.connect(host, username=user, password=passwd)
return ssh | 99b4a474c66e2fd9c9206698f47d8044e675ce5b | 40,120 |
def _filter_deps(filter, deps):
"""Filters dep targets based on tags."""
if not filter:
return deps
kept_deps = []
for dep in deps:
info = None
if TulsiSourcesAspectInfo in dep:
info = dep[TulsiSourcesAspectInfo].filtering_info
# Only attempt to filter targe... | a673c92c93bd43279e355da904ae495075a9027c | 40,121 |
import tokenize
def prepare_text_for_lda(text):
"""
:param text:
:return: list of filetered tokens
"""
tokens = tokenize(text)
tokens = [token for token in tokens if len(token) > 4]
tokens = [token for token in tokens if token not in stop_words_es]
tokens = [get_lemma(token) for token... | 819769632c1d96ade4ddfd6cde6c2b5ea51bb83d | 40,122 |
def make_grammar(description, whitespace=r'\s*'):
"""Convert a description to a grammar. Each line is a rule for a
non-terminal symbol; it looks like this:
Symbol => A1 A2 ... | B1 B2 ... | C1 C2 ...
where the right-hand side is one or more alternatives, separated by
the '|' sign. Each altern... | b390f8a75aa228490a9d4ddc6a0d24b6cf8b5633 | 40,123 |
from pathlib import Path
def repo_root() -> Path:
"""Repository root, 3 levels up from the resources root."""
return builtin_resources_root().parent.parent.parent | 5d156b90d9c60accc5ab55ba13495ac178a168c5 | 40,124 |
from typing import Optional
from typing import Sequence
def get_acl_token(accessor_id: Optional[str] = None,
description: Optional[str] = None,
local: Optional[bool] = None,
namespace: Optional[str] = None,
policies: Optional[Sequence[pulumi.Inpu... | db8255cebea93eb4ce02ef347e38785b41db471f | 40,125 |
def calc_code_churn(
repo: pygit2.Repository,
commit_a: pygit2.Commit,
commit_b: pygit2.Commit,
churn_config: tp.Optional[ChurnConfig] = None
) -> tp.Tuple[int, int, int]:
"""
Calculates churn between two commits.
Args:
repo: git repository
commit_a: base commit for diff cal... | 5297797d567c0b04283e7d68fa0070ba2cf7f8d8 | 40,126 |
def utf8_to_vyxal(code: str) -> str:
"""Turn UTF-8 characters into bytes according to the codepage"""
return "".join(chr(codepage.index(char)) for char in code) | 13590b17a821561e1baabfc01df0a2ba6997b505 | 40,127 |
def apply_chunk_id_maps(continuation_arr, chunk_id_maps):
""" Applies id maps to each set of continuations """
for (c_dict, id_map) in zip(continuation_arr.flat, chunk_id_maps.flat):
apply_id_map(c_dict, id_map)
return continuation_arr | d738e36a264a0b7a707203c01bbf13b952f1b8c8 | 40,128 |
def find_system_symbol(img, instruction_addr, sdk_info=None, cpu_name=None):
"""Finds a system symbol."""
img_cpu_name = get_cpu_name(img['cpu_type'], img['cpu_subtype'])
cpu_name = img_cpu_name or cpu_name
return DSymSymbol.objects.lookup_symbol(
instruction_addr=instruction_addr,
image... | 219e9fe30b5b15e3943ec56bec735395d5fd6a41 | 40,129 |
def check_processed_data(df,col_list,na_action):
""" Checks if provided dataframe consists of required columns and no missing values
"""
check_passed = True
# Check columns
df_cols = df.columns
if set(df_cols) != set(col_list):
check_passed = False
print('Column names mismatched... | fd26d00eabd9eb1dfd1f8bce01a3fb86582a740f | 40,130 |
def bezier_terms(n, t):
""" Bezier curve.
Return n+1 terms in list ()
"""
m_terms = list()
m_C = binomial_term
for i in range(n):
m_terms.append( m_C(n, i) * (1 - t)**(n - i) * t**i )
m_terms.append(t ** n)
return m_terms | b0891cb6fc848f971134367988f2cd85f3a624a5 | 40,131 |
def feed_conversation(samples, limit=5, threshold=.85):
"""helper function to feed result of classifier to Conversation module."""
try:
iter(samples)
assert not any(not isinstance(sub, tuple) for sub in samples)
except (AssertionError, TypeError) as e:
raise TypeError('samples must b... | 4c3d9b7c63e71790bb1a8445662754d48e31524f | 40,133 |
def _mount_config_map_op(config_map_name: str) -> OpFunc:
"""Mounts all key-value pairs found in the named Kubernetes ConfigMap.
All key-value pairs in the ConfigMap are mounted as environment variables.
Args:
config_map_name: The name of the ConfigMap resource.
Returns:
An OpFunc for mounti... | 6c8193465f70ca34619a8a7c9f3debc534208f6e | 40,134 |
def make_tree(file_name):
"""Loads reStructuredText, outputs an lxml tree"""
rst = resource_string(__name__, file_name)
xml = rst2xml(rst)
return etree.fromstring(xml) | be71c99472ecf9fb8994390c090da4d21e26c144 | 40,135 |
import csv
def save_comments(name, token, nfrom = 0, toappend=[]):
"""
Args:
Takes a pagename, an API token, (optionally: an integer specifying
which # post to begin from, and a list to append comments to)
Out:
a list containing:
a list of of the comments it has i... | 210995010d6ee61dec45aaa3db17d1e43aad6c37 | 40,136 |
def point_inside_volume(p, ab1, ab2, eps = 0.01):
"""
Check if point p is inside the aabb volume
"""
ab1 = ab1.copy() - eps
ab2 = ab2.copy() + eps
if ab1[0] <= p[0] <= ab2[0] and \
ab1[1] <= p[1] <= ab2[1] and \
ab1[2] <= p[2] <= ab2[2]:
return True
else:
retu... | 9cdb6323343fdc23dae4b2c899927450c92cb7a2 | 40,137 |
def vgg_input_preprocess(image, max_dim=512, **kvargs):
""" apply appropriate VGG preprocessing to image, shape=(?,h,w,c)
should be same as `tf.keras.applications.vgg19.preprocess_input(rgb_data)/255.0`
NOTE:
- x_train from dataset will be dtype=tf.float32, domain=(0,1.) AFTER tf.image.convert_image_dtype(... | dec82416a3f91842280db82c0c62780ae628dde8 | 40,138 |
def ldns_rr_set_type(*args):
"""LDNS buffer."""
return _ldns.ldns_rr_set_type(*args) | a8223db4323693a46676292fd0d6065341254d05 | 40,139 |
def spline_jacobian(coordinates, force_coordinates, fudge=1e-5):
"""
Make the Jacobian matrix for the 2D biharmonic spline.
Follows [Sandwell1987]_.
Each column of the Jacobian is the Green's function for a single force
evaluated on all observation points.
Parameters
----------
coordi... | a997105a9b7d8ac025bde4d8b77e05199d21b0d7 | 40,140 |
def whip(innings_pitched: float, bb: int, h: int) -> float:
"""Calculate a baseball pitcher's WHIP.
WHIP = (BB + H) / IP
bb = Walks / Base on balls
h = hits
"""
WHIP = (bb + h) / innings(str(innings_pitched))
return round(float(WHIP), 2) | a28809aae63bab2b68f61bde2c84919e34b2998d | 40,141 |
def _determine_levels(index):
"""Determine the correct levels argument to groupby."""
if isinstance(index, (tuple, list)) and len(index) > 1:
return list(range(len(index)))
else:
return 0 | 2eaed820eb45ff17eb4911fe48670d2e3412fb41 | 40,142 |
def integerise(series):
"""
This duplicates functionality that exists in humanleague, rather than intorducing a package dependency solely for this function
"""
sumf = sum(series)
sumi = round(sumf)
# rescale series to nearest-integer sum
series = series * sumi / sumf
# get integer and fr... | a498c3fda42c7c02a3552ece93ea3d6c1996eacc | 40,143 |
def update_cluster_host_deployed_config(
cluster_id, host_id, user=None, session=None, **kwargs
):
"""Update clusterhost deployed config by cluster id and host id."""
clusterhost = _get_cluster_host(
cluster_id, host_id, session=session
)
return _update_clusterhost_deployed_config(
c... | 97ccffbded81262f42bab2349636f28db5416760 | 40,144 |
def make_ppo_runner(env, policy, num_runner_steps, gamma=0.99, lambda_=0.95,
num_epochs=3, num_minibatches=4):
""" Returns env runner for PPO """
transforms = [GAE(policy, gamma=gamma, lambda_=lambda_, normalize=False)]
if not policy.is_recurrent() and getattr(env.unwrapped, "nenvs", Non... | 9443dabb606457f8984900c35941dbf068dd9b2d | 40,145 |
def left_window_coords(win_size, original_left_bound):
"""
Returns a `tuple` `(new_start, new_end)` left of original bound describing a window of length `win_size` (see
note).
Note: Converts any new value less than `1` to `1`.
:param win_size: size of window to the left.
:param original_left_b... | 80d1c96ab2f9de650b50dbde04acfdb455824f78 | 40,146 |
def _get_forms_to_modify(domain, modified_forms, modified_cases, is_deletion):
"""Used on user.retire() and user.unretire()
Returns a list of IDs of forms which only modify the cases passed in and
which aren't already listed in `modified_forms`.
"""
form_ids_to_modify = set()
for case_id in mod... | 4c907c12a79a7eedb29b4b52461dcdc0c2d8602a | 40,147 |
def build_post_required_integer_header_request(
**kwargs # type: Any
):
# type: (...) -> HttpRequest
"""Test explicitly required integer. Please put a header 'headerParameter' => null and the client
library should throw before the request is sent.
See https://aka.ms/azsdk/python/protocol/quickstar... | ba9fe7629c798311fb9670db3092f5a72d9a9717 | 40,148 |
def mask2rle(img: np.ndarray):
"""
img: numpy array, 1 - mask, 0 - background
Returns run length as string formated
"""
pixels = img.copy().flatten()
pixels = np.concatenate([[0], pixels, [0]])
runs = np.where(pixels[1:] != pixels[:-1])[0] + 1
runs[1::2] -= runs[::2]
return ' '.join(... | be053cd777f30a610121cae80cf97b15014504a3 | 40,149 |
def make_mask(df: pd.DataFrame, image_name: str="img.jpg", shape: tuple=(256, 1600)):
"""
Create mask based on df, image name and shape.
"""
encoded_masks = df.loc[df["im_id"] == image_name, "EncodedPixels"]
masks = np.zeros((shape[0], shape[1], 4), dtype=np.float32)
for idx, label in enumerate... | 7902d5bc5a7a3c5e7d124f698b94548742e37fdf | 40,150 |
from typing import List
from typing import Dict
def parse_filters(tokens: List[str]) -> Dict[str, str]:
"""Parses a filter description, like 'filter-for', 'refcounty', '42'."""
ret: Dict[str, str] = {}
filter_for = False
for index, value in enumerate(tokens):
if value == "filter-for":
... | 6b659342761e11311bfa3aa1962067e3e83a809d | 40,151 |
def format_val(v):
"""Takes in float and formats as str with 1 decimal place
:v: float
:returns: str
"""
return '{:.1f}%'.format(v) | 932ca312a573a7e69aa12e032d7b062ac22f3709 | 40,152 |
def _can_cast(type1, type2):
"""NOT_RPYTHON: operates on BaseType subclasses"""
return casting_table[type1.num][type2.num] | 03e8602528b26c2c5a61fc56af0ef79c82a9ecf2 | 40,153 |
def concat(layers):
"""
Args:
layers (list(layer)): a list of layers
"""
return (
np.concatenate([l[0] for l in layers]),
np.concatenate([l[1] for l in layers])
) | b07eda38b6974a208f2756b04fc7f92ca5853da4 | 40,154 |
import struct
def array_to_bytes(arr: np.ndarray):
"""
Dumps a numpy array into a raw byte string.
:param arr: A numpy array.
:return: A `bytes` string.
"""
shape = arr.shape
ndim = arr.ndim
ret = struct.pack('i', ndim) + struct.pack('i' * ndim, *shape) + arr.tobytes(order='C')
ret... | fa623658aa73d0f5486771f497c9ce159ea89ca6 | 40,155 |
def count_parameters(model):
"""
number of model parameters to update
"""
return sum(p.numel() for p in model.parameters() if p.requires_grad) | 3f739da845f483fdd489afabd9da12340b0f44a9 | 40,156 |
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