content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import glob
def collect_factories(rootpath):
"""
Will collect (recursively) and return all factories found under given root path
"""
factories_collected = {} # <factory name> : <factory class>
factory_files = glob.glob(f"{rootpath}/**/factories.py", recursive=True)
for factory_file in factor... | 73563107e620d5c6d6419600ebf51bc267710cca | 3,615,432 |
def _get_hop_2_neighbours(graph, input_list: list, hop_n: int) -> list:
"""
Find hop_n neighbours of each item in input_list
:param graph: NetworkX graph object
:param input_list: Input list
:param hop_n: Hop hop_n
:return: hop_n hop neighbours of the input list's items
"""
full_list = ... | a51f1286aec2719b72665e35fec29d7d2b93b38e | 3,615,434 |
import asyncio
def create_worker(host='localhost', port=4730, loop=None):
"""XXX
:param host:
:param port:
:param loop:
:return:
"""
loop = loop or asyncio.get_event_loop()
conn = yield from create_connection(host=host, port=port, loop=loop)
return GearmanWorker(conn) | 8ee679baf652476f520df75b3dc4fa3bf6728031 | 3,615,435 |
import re
def prepare_template_data(fill_pairs):
"""
Prepares formatted data for filling template.
It produces mutliple variants of keys (key, Key, KEY) to control
format of filled template.
Args:
fill_pairs (iterable) of tuples (key, value)
Returns:
... | a6082093bcbe39ba429decd2735fb2797c6c11dd | 3,615,436 |
def get_tokens():
"""
Returns a tuple of tokens in the format {{site/property}} that will be used
to build the dictionary passed into execute
"""
return (SECURITY_ENABLED_KEY, KERBEROS_EXECUTABLE_SEARCH_PATHS_KEY, HIVE_PRINCIPAL_KEY, HIVE_PRINCIPAL_KEYTAB_KEY,
HIVE_USER_KEY, STACK_ROOT, LLAP_APP_NAM... | 6c05f16b3707d31af797fdb7bfc65fe8a1b78482 | 3,615,437 |
def largest_cc(mask):
""" Return the largest connected component of a 3D mask array.
Parameters
-----------
mask: 3D boolean array
3D array indicating a mask.
Returns
--------
mask: 3D boolean array
3D array indicating a mask, with only one connected component.
"""
... | 617d7a1474ab6b7a5a9ad6393c942cb874d49744 | 3,615,438 |
def _expand_to(
a: tp.Union[np.number, np.ndarray, Variable],
ndim_or_shape: tp.Union[int, tp.Tuple[int, ...]],
axis: tp.Union[None, int, tp.Tuple[int, ...]] = None,
keepdims: bool = False,
) -> tp.Union[np.ndarray, Variable]:
"""Return expanded array.
Parameters
----------
a : tp.Tuple... | fe1c979ba9c5c781edc4a525c0b87a13b0d39f8d | 3,615,439 |
def get_feedback_average(action):
"""returns the average feedback rating for the given action."""
return ActionFeedback.objects.filter(
action=action).aggregate(avg=Avg('rating'))['avg']
#query_set = get_action_feedback(action)
#total = 0
#for i in xrange(1, 6):
# total += query_set.... | f42125f7fdf7d3f8ee3ef97fe34fbb7f40567cb8 | 3,615,440 |
def display_method_to_choose_etfs(selected_method_choose_dates, all_etfs, etf_data, sl_obj):
"""
Generates various streamlit options for selecting which ETFs to display.
Parameters
----------
selected_method_choose_dates : list of str
Strings of the various methods of selecting ETFs.
al... | 6f2c65a5472b445dcdeb921d10c8c13397ef5d97 | 3,615,441 |
def cband():
"""Pre-define idealized critical band filter bank.
:return: idealized critical band filter bank
"""
return np.array(
[
0,
100,
200,
300,
400,
510,
630,
770,
920,
... | 1648adff3d9dce05be2f4879e34d4a6aa9acc8f2 | 3,615,443 |
def get_power_spectrum(array):
"""Calculate DFT and power spectrum from the given array.
:param array: a 2D array
:return: DFT array and the power spectrum
"""
fourier = np.fft.fft(array)
power = abs(fourier)**2
return fourier, power | 14066876f7b0d4925477e96301def89fc856b1b4 | 3,615,444 |
import scipy
def compute_intensity_features(im_label, im_intensity,
num_hist_bins=10, rprops=None):
"""
Calculates intensity features from an intensity image.
Parameters
----------
im_label : array_like
A labeled mask image wherein intensity of a pixel is th... | 9a064d70028417f83368083fc488939a17aa747f | 3,615,445 |
from pathlib import Path
from typing import Callable
from typing import Any
def readFileLines(filepath: Path, f: Callable[[str], Any] = str) -> list:
"""Reads the lines in a file
Args:
filepath (Path): The path of the file to be read.
f (Callable[[str], Any], optional): Transformation for the lines. ... | 21df2445f6132085d7da36276f371170ff0f2a4e | 3,615,446 |
def get_default(arr, idx, default_value):
"""get arr[idx] or return default_value
"""
try:
return arr[idx]
except IndexError:
return default_value | 038b943da7fa1d36038444880264160da8e031f4 | 3,615,447 |
def chat_words_conversion(text):
"""
converts common chat acronyms into it's fully spelled out phrase
"""
new_text = []
for w in text.split():
if w.upper() in chat_words_list:
new_text.append(chat_words_map_dict[w.upper()])
else:
new_text.append(w)
retur... | 5d97ce53a2103190ff0abb585e62923c0fad8f21 | 3,615,448 |
def second(xs):
"""
Returns the second element of a list, or None if the list is empty
"""
if not xs:
return None
return xs[1] | e5a915116d61e01842f86623aafcf6e2e6c8b5a3 | 3,615,449 |
import logging
def get_logger(module: str, file: str) -> logging.Logger:
"""Configure a file logger for use in a script.
Parameters
----------
module : str
The name of the module from which the logger is called
file : str
The name of the log file to which the logger will write
... | c9a68d216ca9a04ccb208dd546621e051dd37e36 | 3,615,450 |
def filled_grasp_grid(empty_grasp_grid, grid_file):
"""Return a GraspGrid instance filled from the grid_file."""
empty_grasp_grid.read(grid_file)
grid_file.close()
return empty_grasp_grid | 97ed623c09b9d42642a208451b004e5bec4910ed | 3,615,451 |
import warnings
def calculate_boot_stats(sample, rep, n="auto", level=0.95, estimator="mean", random_seed=None, pass_dist=False):
"""Calculates a bootstrapped confidence interval for a sample.
A bootstrapped confidence interval for the desired estimator for
the provided sample is calculated for a confide... | 354cf103105f3bc22decb3b27cbab694f7a7d9c9 | 3,615,452 |
import pickle
def get_camera_params():
"""
Return a default camera parameter matrix
"""
pickle_in = open("config.pickle", "rb")
data_dict = pickle.load(pickle_in)
return data_dict['mtx']
# return np.array([[800, 0, 320], [0, 800, 240], [0, 0, 1]]) | 51292054e8db77058ea37b2dbe06bf105183969b | 3,615,453 |
def _distributed_edge_access(g, edges, issue_remote_req, local_access):
"""A routine that fetches local edges from distributed graph.
The source and destination nodes of local edges are stored in the local
machine and others are stored on remote machines. This code will issue
remote access requests fir... | 1217fcce3a7b1256587298ec266627caa208c28b | 3,615,454 |
def check_letters():
"""
Check if all letters from input is in other string
"""
word = input("Give me a word: ").lower()
letters = input("Give letters to check for in word: ")
for l in letters:
if l not in word:
print("No match")
return 0
print("Match") | 4c419e5c3c70c383d06079ead7e105b38e6ca91e | 3,615,457 |
def case_json(ses):
""" returns a list of JSON fomratted output for case object """
return _get_case_json(ses, '/case') | 00447375c926521001f0b3039251a86ce6bc1336 | 3,615,458 |
def bernoulli_action_log_prob(logit, action):
"""Calculate the log p of an action with respect to a Bernoulli
distribution. Use logit rather than prob for numerical stability."""
if action == 0:
return F.logsigmoid(-logit)
else:
return F.logsigmoid(logit) | a1974fbe2d12fe878f875c5e1364cf3cc36d676c | 3,615,459 |
def get_1d_coords(p, i, j):
"""
Finds index of site in 1d chain from 2d lattics based on snake
decomposition, ie 1d coords on 2d lattice look like:
0, 1, 2, 3,
7, 6, 5, 4,
8, 8, 10, 11
Args:
p - dictionary that contains the relevant system parameters
i - row index... | 2852ec9d57c99f922380fc8b671bdd757e8decf4 | 3,615,460 |
def unpack_offset(msr_response):
"""
Extract the offset component of the response and unpack to voltage.
>>> from undervolt import unpack_offset
>>> unpack_offset(0x0)
0.0
>>> unpack_offset(0x40000000000)
0.0
>>> unpack_offset(0x100f3400000)
-99.609375
"""
plane_index = int(m... | 408ba805fe92fbc0c7fd4498d2e16d6701180eb3 | 3,615,461 |
def check_early_stop(
perf_history,
minimum_length=20,
short_history=3,
long_history=5,
fail_function=np.less_equal):
"""
Determine whether to stop early. Using deepgaze criteria:
We determine this point by comparing the performance from
the last three epochs to ... | f730004bf4cbac1cfd12e260bdc8240193c4197d | 3,615,462 |
import math
def getAngle(v1,v2,prec=1E-6):
"""
Helper function to get angle between two vectors
inputs
--------
v1,v2 (list,list): two vectors
outputs
--------
angle (float, radians): angle between v1,v2
"""
return(math.acos((np.dot(v1,v2))/np.l... | 19e54f1bdd3b2ea95e77188eb383f98e6300d5ce | 3,615,463 |
def evaluate_cdr_hit(query, target, result={}, same_length=False):
"""
Compare query and target sequence positions in CDR3 and framework regions, return number of matches and % identity
If previous 'result' is provided, return (None, None) if an improvement has not been found.
"""
if same_lengt... | 1cc292c28ea5209f01cae9472cf20a13cf0864fa | 3,615,464 |
from typing import Sequence
import random
def make_burst_emitter(
center_xy: Point,
filenames_and_textures: Sequence[FilenameOrTexture],
particle_count: int,
particle_speed: float,
particle_lifetime_min: float,
particle_lifetime_max: float,
particle_scale: float... | 63a2b4cc0975f03711dc4824e8cdf431e3d61db6 | 3,615,465 |
import ctypes
def cusolverDnSsyevd_bufferSize(handle, jobz, uplo, n, a, lda, w):
"""
Calculate size of work buffer used by culsolverDnSsyevd.
References
----------
`cusolverDn<t>gebrd <http://docs.nvidia.com/cuda/cusolver/index.html#cuds-eigensolver-reference>`_
"""
lwork = ctypes.c_int(... | a16df1725e6db9471836bf517e7efa977c50fdf7 | 3,615,467 |
from typing import Dict
def get_github_repo_url(project_urls: Dict[str, str]) -> [str, None]:
"""
Get repo url for github.
:param project_urls: project urls to get github repo url from
:return: repo url if one is available, else None
"""
source_code_url = get_attribute(project_urls, ["Source ... | 358f35544c50ad65c7f276a2fdbdbf1abb91f039 | 3,615,468 |
import json
def abrir_freq(file):
"""
Abre o ficheiro json com o dicionário das frequências das regras.
:param file: ficheiro json
:return: dicionário com as frequências das regras no corpus.
"""
with open(file) as f:
freq_svo_dict = json.load(f)
return freq_svo_dict | b1cbb7c98146cf72390b511428d7734881f0b944 | 3,615,469 |
def update_user_phone():
"""
用户修改电话号码
"""
userid = g.userinfo.get("id")
requstsData = request.get_json()
phone = requstsData.get("phone")
code = requstsData.get("code")
if phone and code:
dbres = db.query("select id,code from tb_sms_log where phone = '{}' and status = '0' and c... | 1b7fb8763a35f9fc2e221e4c03788b3827bd7a67 | 3,615,470 |
import common.api as api
import base64
def file_update_complete_response( volume, reply ):
"""
Sign a protobuf ms_reply structure, using Syndicate's private key
"""
# sign each directory entry in the reply with the Syndicate key,
# so the MS attests to its index information
for ent_pb in reply.l... | 607b9fe4f155b39de72c5c8d9dafcd1ba8bfe7ce | 3,615,472 |
def destructure_decorated_lambda(tree):
"""Get the AST nodes for ([f, g, h], lambda) in f(g(h(lambda ...: ...)))
Input must be a tree for which ``is_decorated_lambda`` returns ``True``.
This returns **the original AST nodes**, to allow in-place transformations.
"""
def get(tree, lst):
if t... | 1c7a63fb7497a26f5a841556dbdb1114880c7388 | 3,615,473 |
from datetime import datetime
def get_data_type(v):
"""
Infers type from value. Returns tuple of (type, value)
"""
if isinstance(v, datetime.datetime):
return ("date", msecs_since_epoch(v))
elif isinstance(v, bool):
return ("boolean", str(v).lower())
elif isinstance(v, float):
... | 8e6d65ca328859e4b9c6a1493cf732e4a9b17c64 | 3,615,474 |
def replace_around(i, l, r, f_nones=True):
"""Replace the three elements centered at i with r."""
if f_nones:
r = filter_nones(r)
return l[: max(i - 1, 0)] + r + l[i + 2 :] | 4e1c6b002714b07385f5f4871ca001aa956b3e06 | 3,615,475 |
def dictionariesToDataframe():
"""converts dictionaries on CSPP holdings to dataframes
return:
- [holdingsECB, holdingsECBDates]"""
matrixData = [] # 2D array with row per ISIN and columns for different data
for ISIN, dataInDictionary in dictionaryBondsECB.items():
item = [ISIN] + dat... | 8fa2afd551d337e52808cbecac4ec411cfb7360f | 3,615,476 |
def get_model_parameters(model):
"""Extract model arguments that were used during training"""
params = ModelParameters()
names = [layer.name for layer in model.layers]
params.num_codes = model.get_layer(name='embedding').input_dim-1
params.emb_weights = model.get_layer(name='embedding').get_weights... | b216b3d8f010d33f767e76252d1422ffa778b4df | 3,615,478 |
def transpone(l):
"""transpones a list of multiple lists
if the entrys do not have the same length, an empty string will be put in their place"""
nestedlist=[]
length=[]
transponedlist=[]
for i in range(len(l)):
length.append(len(l[i]))
for i in range(max(length)):
for j in... | 27d904910be743d4116fba5ba7479cfdc62ec18b | 3,615,479 |
def to_df(records_tree, event_name, instrument_name):
"""
Converts a `get_records_tree()[event][instrument]` to a pandas DataFrame
"""
# get instrument records
records = records_tree[event_name][instrument_name]
# build dataframe rows from records
acc = []
for s, entries in records.item... | 91805a4878eedeab3d5efdb1a4277966728543f3 | 3,615,480 |
def compare(value1, value2, comparison):
"""
Compare 2 values
"""
if isnum(value1) and isnum(value2):
comparison = comparison.lower()
if comparison == 'equals':
return value1 == value2
elif comparison == 'not equal':
return value1 != value2
elif co... | 49c6c3806224f864670f8078733d2baeea653792 | 3,615,481 |
def get_minsep_range(minseps, cap=None):
"""
Create ranged minseps from an ensemble of minsep entries
Args:
minseps (list): A list of minsep dictionaries
cap (tuple): Minimum-maximum caps
Returns:
minsep (dict): A minsep where values are minimum and maximum values
"""
... | e60392fa70f7f2b0989f4894ce90c7bd78aac7d2 | 3,615,482 |
def ga_exp(B, verbose = False):
"""
This is an expansion of the exponential of a general rotation and translation
Presented by R. Wareham (Applications of CGA)
B must be a general rotation object on the format $ \phi*P + t n_{\inf}} $
$P$ is a 2 blade in real space.
$$\phi \in \mathcal{... | 3abcadbcffe625bf473d28d5698fbf94e1d3318a | 3,615,483 |
import tqdm
def get_progress_bar(percentage, increment):
"""Get a progress bar string given a percentage."""
initial = percentage
total = 100
bar_format = generateProgressbar(
percentage) + "\n" + "{percentage:04.1f}%" + f"[{increment:+03.1f}]"
with tqdm(initial=initial, total=total, bar_... | 29957960090063903d1f231dd5f41532691dd05b | 3,615,484 |
def elsym(edgelen, order=1):
"""
Elementary symmetric polynomial of a given order
"""
l = len(edgelen)
if order == 0:
return 1
r = 0
for v in combinations(range(l), order):
r += np.product([edgelen[vv] for vv in v])
return r | 6939704c2bfcec935e762d23a1cb05f2cd8c593f | 3,615,485 |
def shorturl(request, key):
"""
Redirect the client.
"""
return redirect(get_object_or_404(ShortURL, pk=key).url) | 7f6700215f8cc60f5e090fa3ef1a3d4e7035ff6e | 3,615,486 |
import itertools
def group_by_day(list_all_objects):
"""
Recebe uma lista de objetos onde cada um deles possui um atributo tipo date e logo ordena eles por dia.
:param: list_all_objects: Register.objects.all(): django.db.models.query.QuerySet
:return: objects_day_ordered: [[objetos_do_dia_1][objetos_d... | 39feb54a2232e9e7a0965b72f2c6eb2509c7b610 | 3,615,487 |
def get_root_model(models):
""" Get a root model class from an iterator over `obj_tables.Model` classes
The root model is obtained by name, rather than from `core.Model`, because `models` may have
been obtained from `obj_tables` migration, which loads other versions of `wc_lang.core` in
private imports... | aabe0e445ff96036008eddc4c2127516554a4adc | 3,615,489 |
def datetime_to_iso(date, only_date=True):
""" Convert datetime format to ISO 8601 time format
This function converts a date in datetime instance, e.g. ``datetime.datetime(2017,9,14,0,0)`` to ISO format,
e.g. ``2017-09-14``
:param date: datetime instance to convert
:type date: datetime
:param ... | 676a7e65de2c9e4de60cfe8d832ab342aa46af4f | 3,615,490 |
def _copy_agave_agave(src_uri, dest_uri, agave):
"""
Copy Agave data using AgavePy Wrapper.
Args:
src_uri: Source URI parsed into dict with URIParser.
dest_uri: Destination URI parsed into dict with URIParser.
agave: dict that contains:
agave_wrapper: Agave wrapper objec... | 0dd5e5627cd4adc87b83b22cb63e5eda1f3dae11 | 3,615,491 |
def load(path_or_strm, container, **opts):
"""
:param path_or_strm: input config file path or file/file-like object
:param container: callble to make a container object
:param opts: keyword options passed to :class:`configobj.ConfigObj`
"""
return container(configobj.ConfigObj(path_or_strm, **op... | cccc2d780ab7d16996ac9b6658550773b307a4df | 3,615,493 |
import numpy
def default_unexpected(x):
"""Define unexpected values."""
large = 1.e3
small = -numpy.float('inf')
return (x is None) or x > large or x < small or numpy.isnan(x) | 4afe63f1969b568c691fcc4e4fbfa91ace53fdfb | 3,615,494 |
def predict_hot_pxl(sqr, model):
"""takes a numpy array (colour image) size 64x64 and a ML model,
returnes float number between 0 - 1 for hot pixel detection,
for 0 no hot pixel detected, 1 hot pixel detected"""
predict = model.predict(sqr.reshape(1,64,64,3))
y_pred = [i[0] for i in predict]
ret... | e533c2b27df280f0f62b2727b1dd960a828fdee0 | 3,615,495 |
import traceback
def write_to_file(file_name, dir_path, content):
"""
Rewrite or create and write to file.
Parameters:
file_name (string): file name
dir_path (string): root path which file contains
content (string): content to be written
... | b3ade139d6455f57e54d3ae03ab4988dc5718644 | 3,615,496 |
from typing import Tuple
from typing import Optional
from typing import Dict
def _build_meta_block(
payload_spec: PayloadSpec,
) -> Tuple[Optional[Block], Block, Dict]:
"""
Performs validations in the meta specification and returns o
Args:
payload_spec (dict): Payload specifications.
Ret... | 33ae726c2c73e964c8e157b00cb1a417446b7b9a | 3,615,497 |
def _unit_state_progress(uid, current, target):
"""
This method will ensure a unit state progression in sync with the state
model defined above. It will return a tuple: [new_state, passed_states]
where 'new_state' is either 'target' or 'current', depending which comes
later in the state model, and ... | 6549118b894a3f475200e08b74a4042f4b75c805 | 3,615,498 |
from typing import List
from datetime import datetime
def search(
bounds: List[float],
min_cloud: float = 0,
max_cloud: float = 100,
min_date='2013-01-01',
max_date=datetime.today(),
period: str = None,
period_qty: int = 1,
stac_collection_limit: int = 5... | a807308439d1ba3ce2a52890f7da43f2b6a831a4 | 3,615,499 |
import itk
def get_label_object_attributes(dataset, progress_callback=None):
"""Compute shape attributes of integer-labeled objects in a dataset. Returns
an ITK shape label map. An optional progress_callback function can be passed
in. This callback is expected to take one argument, a floating-point number... | bcf7e813492c94d132bd716f482c36709e540240 | 3,615,500 |
from aiida.orm import StructureData
def generate_structure():
"""Return a ``StructureData`` representing either bulk silicon or a water molecule."""
def _generate_structure(structure_id="Si"):
"""Return a ``StructureData`` representing bulk silicon or a snapshot of a single water molecule dynamics.
... | 7fc610d9dcb36e56953c98fcd4e067c6db33fd5b | 3,615,501 |
def get_lat_bin(lat, nbins=NBINS):
""" get latitude bin """
if lat < LATLIM[0]:
return 0
if lat > LATLIM[1]:
return nbins
return int((lat-LATLIM[0]) * nbins / (LATLIM[1]-LATLIM[0])) | cc6f67f0c9afb209416caa43b101c5a5174bfd43 | 3,615,502 |
def get_aff_trafo(xy0=None, xy1=None, theta=0, por=(0, 0), ax=None, patch=None):
"""
:param xy0: current position of the object, if not provided patch.get_xy() is used
:param xy1: desired position of the object
:param theta: rotation in degrees
:param por: point of rotation relative to the objects ... | 958249e940bf21cc10c68d2e2b7142d0fee62e15 | 3,615,503 |
from typing import Dict
from typing import Any
from typing import cast
def get_sig_alg(sig: key.Signature) -> Dict[str, Any]:
"""
Create `SignedDigestAlgorithm` structure.
"""
if sig.meta.algorithm == key.AsymmetricAlgorithm.RSA:
return get_sig_alg_rsa(cast(rsa.RsaSignature, sig))
if sig.... | 02a244ff0a8c67027a29c827e4101598a19fa455 | 3,615,504 |
def descendants(node, lst=None):
"""Return a list of all the descendants beneath a node"""
if lst is None:
lst = []
for child in node.children:
lst.append(child)
descendants(child, lst=lst)
return lst | 5fe6fb9d9fbfd63bbeb161fdbe1d0e54d20edf9e | 3,615,506 |
def read_uncompressed_dataset(file):
""" Get a file path and return the uncompressed dataset"""
try:
return pd.read_pickle(file)
except:
try:
return pd.read_csv(file)
except:
print("%s cannot be read" % file)
return | 61accb9fa81e59b4b1324c40b567a5ce4e718fa6 | 3,615,508 |
def _run_reformulator_eval(questions, annotations, reformulator_instance,
environment_fn, batch_size):
"""Runs eval with just the reformulator, using greedy decoding."""
f1s = []
for (questions_batch, annotations_batch) in batch(questions, annotations,
... | 0ba54ac97a0f33bf7a0c77c968036c01d946ea3e | 3,615,509 |
def _get_single_node_name_from_collection(meta_graph_def, collection_key):
"""Obtain a node name that is the single element of a collection."""
if collection_key not in meta_graph_def.collection_def:
return None
collection = meta_graph_def.collection_def[collection_key]
if not collection.node_list.value:
... | 160ddf3f178f69fe31cfa8301516395f46ee6740 | 3,615,510 |
def test_create_plots_create_matrix_deletion_raw_count():
"""
"""
#ref_seq, total_dels, total_ins, cov = crispr_count_indels._count_indels("15_dels_ladder_for_matrix.fasta")
ref_seq, ref_seq_id = count_indels._get_ref_seq("15_dels_ladder_for_matrix.fasta")
cov = count_indels._get_coverage("15_d... | 473d86545ff3669279e7e5aed65b0fe920eef48c | 3,615,511 |
def wire_mutual_inductance(wire_i, wire_j, ref):
# di0: float, dj0: float, dij: float, rw0: float):
"""Inductance between wire i and wire j, with reference wire 0.
Uses widely separated assumption, di0/rw > 4
"""
if type(ref) == Wire:
rw0 = ref.radius
di0 = wire_i.distance_to(ref)
... | 484027eca8864a4d66e78988d4f2580fbf12644b | 3,615,512 |
from typing import Any
from typing import Tuple
def parl_to_kaldi_test_pairs(request: Any) -> Tuple[str, str]:
"""Return an embedded statement from the above list using given index."""
index: int = request.param
return parl_to_kaldi_pairs[index] | 5b830e2daf852358bafe2caf365438a3cd1301d0 | 3,615,515 |
def global_pairwise_align_protein(seq1, seq2, gap_open_penalty=11,
gap_extend_penalty=1,
substitution_matrix=None,
penalize_terminal_gaps=False):
"""Globally align pair of protein seqs or alignments with Needleman-... | b2494fb60f5735eae0aa9d1eda0185884f905d92 | 3,615,516 |
import requests
def client(api_client):
"""Returns HttpClient instance with retrying feature skipped."""
api_client = api_client(disable_retry_status_list={503, 404})
# This won't work with Httpx but will save us about 10 mins for this test alone
api_client.session = requests.Session()
return api_... | 615756a81fd243d4d7495bafca4538e19775f7b4 | 3,615,517 |
def create_elem_dict(row):
"""
Create new element dictionary from row with metadata common to all
nodes/ways/relations.
"""
elem = {
'id': row.id,
'version': row.version,
'userId': row.user_id,
'userName': row.user_name,
'timestamp': row.timestamp,
'ta... | d97b712cd4b0bc6e79f5aa09f212491d715f1c69 | 3,615,518 |
from typing import Dict
from typing import Any
from typing import Tuple
from typing import Optional
def source_ip_and_reverse_dns(
message: Dict[str, Any]) -> Tuple[Optional[str], Optional[str]]:
"""
Extract the source IP and reverse DNS information from a canary request.
"""
reverse_dns, sour... | df2a9b6c4a177073fc019e88c33234f4d6124ccb | 3,615,519 |
import typing
def spark_flatMap(func: typing.Callable[[pyspark.rdd.RDD], pyspark.rdd.RDD]=default_function(1)):
"""Spark's flatMap
:param Callable func: The function to apply.
:input RDD data: The RDD to convert.
:output RDD result: The resulting RDD.
"""
def inner(data: pyspark.rdd.RDD) -> R... | 9f7d6fa9a18d844f6e0d140063ab0dc5684217a6 | 3,615,520 |
def fCO2_to_CO2(fCO2, Ks):
"""
Calculate CO2 from fCO2
"""
return fCO2 * Ks.K0 | 2b71b46147291e7fffb99d51d0acb59ea4cd0c69 | 3,615,521 |
def summary_stats(tile_summary):
"""
Obtain various stats about the slide tiles.
Args:
tile_summary: TileSummary object.
Returns:
Various stats about the slide tiles as a string.
"""
return "Original Dimensions: %dx%d\n" % (tile_summary.orig_w, tile_summary.orig_h) + \
"Original Tile Siz... | 8e36e9b10ec721cd567eccb54c9afecad13f2eea | 3,615,523 |
def soundnet5_model_params(model_filename=None, num_classes=None, scope='SoundNet'):
"""
Load model parameters from Torch file.
"""
def retrieve_if_not_none(local_net, layer_num, var_name): return None if local_net is None else \
local_net['modules'][layer_num][var_name]
def transpose_if_n... | 305e06bbadb67b9beab060c1763e68423c64b393 | 3,615,524 |
def landsat457_cloud_mask_func(img):
"""Apply basic ACCA cloud mask to a daily Landsat 4, 5, or 7 image"""
cloud_mask = ee.Algorithms.Landsat.simpleCloudScore(img).\
select(['cloud']).lt(ee.Image.constant(50))
return img.mask(cloud_mask.mask(cloud_mask)) | 50b01ef70f41be0788952c5e0ca2a55c8b6ccff5 | 3,615,525 |
def check_if_in_team(api, team_id, person):
""" Checks if a person is in a given team
:param api: CiscoSparkAPI instance to query Spark with.
:param team_id: The ID of the team to check for
:param person: The person to check against the team
"""
team_memberships = api.team_memberships.list(te... | b20a5ee41485b2dd397c7dd23407ef95d0f34e4a | 3,615,526 |
def handle_public_events(iterable):
"""Report private repositories being made public, and new releases."""
lines = []
unused = iterable
# Private -> Public Transitions
events, unused = partition_type('PublicEvent', unused)
for event in events:
tmpl = 'made {} public'
lines.appen... | 7608bbf011729c2bf78a9c5a62e5061760aa50ae | 3,615,527 |
def generate_sub_tetrahedrons(a, b, c, d):
"""
Generate sub-tetrahedrons.
Returns tuple of tetrahedrons.
ARGUMENTS: a, b, c, d - vertices of tetrahedron
"""
sub_tetra = []
sub_tetra.append((a, midpoint(a, b), midpoint(a, c), midpoint(a, d)))
sub_tetra.append((midpoint(a, b), b, midpoin... | 9f4a379092d62162109da199589393f2a02ccab1 | 3,615,528 |
def ExtractMemoryDumpIds(trace_builder):
"""Get a list with the ids of 'GlobalMemoryDump' events found in a trace.
Args:
trace_builder: A TraceDataBuilder object; trace data is extracted from it
and the builder itself is cleaned up.
"""
event_ids = _SerializeAndProcessTrace(
trace_builder, _GET... | 4a102b4d897fceeb63a493bc5799e22f7d0f044c | 3,615,529 |
from azure.mgmt.keyvault import KeyVaultManagementClient
import re
def get_vm_format_secret(secrets, certificate_store=None):
"""
Format secrets to be used in `az vm create --secrets`
:param dict secrets: array of secrets to be formatted
:param str certificate_store: certificate store the secret will ... | 5f97ae86c07250864012f869bd718fb3513b6a8e | 3,615,530 |
import builtins
def instance(type_cls, cls):
""" Decorator for creating a typeclass instance.
Examples:
>>> from abc import ABC, abstractmethod
>>> from pycats import typeclass, instance
>>>
>>> @typeclass
... class Functor(ABC):
...
... @abstractme... | acd655661d2106e18004f7c22f6c8395287a20d4 | 3,615,531 |
def get_inputs(seq_len: int) -> tensorflow.Tensor:
"""Get input layers.
See: https://arxiv.org/pdf/1810.04805.pdf
Args
seq_len: Length of the sequence or None.
"""
names = ['Token', 'Segment']
# , 'Masked']
return [
keras.layers.Input(
shape=(None,),
... | 3742ff634a7b46e17e19d509ea20dcac79660060 | 3,615,532 |
def replace_self_attention_layer_with_sparse_self_attention_layer(
config,
layers,
# SparsityConfig parameters needs to be set accordingly
sparsity_config=SparsityConfig(num_heads=4)):
"""This function replaces the self attention layers in attention layer with sparse self attention.
For sparsity... | 381b7c876a90ff2d6f135db4fd92ba3b4114aa94 | 3,615,533 |
def mape(y_true: pd.Series, y_pred: pd.Series) -> float:
"""Compute Mean Absolute Percentage Error (MAPE)
Args:
y_true (pd.Series): actual values
y_pred (pd.Series): predict values
Returns:
float: mape value
"""
return np.mean(np.abs((y_true - y_pred) / y_true)) * 100 | a1959cd422db225ec0ddd77fc47ca55c78a686d9 | 3,615,534 |
def list_mutations(context):
"""
:type context: Context
"""
assert context.mutation_id == ALL
mutate(context)
return context.performed_mutation_ids | a78ba96202c910df057d86dac13cc549b6951e06 | 3,615,535 |
from typing import Optional
import json
async def make_keyboard_from_json(query: str, message: Message) -> Optional[Message]:
"""
Запрос в конструктор из json формата
:param query: JSON запрос
:param message: Объект сообщения пользователя
"""
try:
data = json.loads(query)
retur... | 7f4b9fd01776b486c450e8515ae38e8854530202 | 3,615,537 |
def group_per_category(bkgs):
"""
Groups a flat list of datasets into sublists with the same category
E.g. [ ttjet, ttjet, ttjet, qcd, qcd ] --> [ [ttjet, ttjet, ttjet], [qcd, qcd] ]
"""
cats = list(set(bkg.get_category() for bkg in bkgs))
cats.sort()
return [ [ b for b in bkgs if b.get_cate... | c331456b1b3066f667c94e6ed7d00c8421ec2160 | 3,615,538 |
def subtract_params(param_list_left: list, param_list_right: list):
"""Subtract two lists of parameters
:param param_list_left: list of numpy arrays
:param param_list_right: list of numpy arrays
:return: list of numpy arrays
"""
return [x - y for x, y in zip(param_list_left, param_list_right)] | f8563cae337af0e30621428103afa10bde614e93 | 3,615,539 |
def rebin_or(newbins, oldbins, oldvalues):
"""Deprecated as of 2015-02-15. Use rebin instead."""
return rebin(newbins, oldbins, oldvalues, method='or') | d58c3334f2789c1d01f618e78ff5a519a9c88c4d | 3,615,540 |
from typing import List
def mkrefpath(r:DRef, items:List[str]=[])->RefPath:
""" Construct a [RefPath](#pylightnix.types.RefPath) out of a reference `ref`
and a path within the stage's realization """
assert_valid_dref(r)
return [str(r)]+items | 04a1b10478d71d0751898d69e521119549102d62 | 3,615,542 |
import re
def resize(url, width):
"""
Return a url to a resized version of the given image at the url -- only
works for files hosted on your MEDIA_ROOT --- CACHE THIS HEAVILY
"""
width = int(width)
regex = get_media_url_regex()
# check to see if the url is one we can handle, othe... | 0ddaed81e450d00e4c76682c4c059b1155f0e975 | 3,615,543 |
async def me(
request: Request,
scopedTo: ScopedTo = ScopedTo(
[UserScope.admin, UserScope.auditor, UserScope.guardian, UserScope.voter]
),
) -> UserInfo:
"""
Get user info for the current logged in user.
"""
token_data = scopedTo(request)
if token_data.username is None:
... | a4ff28f2eccaf36383894e9af103d67c752aa7c1 | 3,615,544 |
def crop_center(image):
"""Returns a cropped square image."""
shape = image.shape
new_shape = min(shape[1], shape[2])
offset_y = max(shape[1] - shape[2], 0) // 2
offset_x = max(shape[2] - shape[1], 0) // 2
image = tf.image.crop_to_bounding_box(
image, offset_y, offset_x, new_shape, new_s... | bf069a5388ec40f8c07671cf514bb88442674cbd | 3,615,545 |
def load_video(video_data, *, config=VideoLoaderConfig()):
"""Load a video into the database"""
video_id = video_data.pop("video_id")
platform = video_data.pop("platform")
topics_data = video_data.pop("topics", None)
offered_bys_data = video_data.pop("offered_by", None)
with transaction.atomic(... | 93d18d2d8bb067e85747641478555d21d1fe2148 | 3,615,546 |
from typing import Union
async def is_float(obj: Union[Message, CallbackQuery]) -> bool:
"""
Checks if message text can be converted to float
:return: True if so
"""
obj = await _to_message(obj)
return obj.text and obj.text.isnumeric() | 55fe1160431027f0c9546023ad5760455e3c632b | 3,615,547 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.