content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def getFromLongestMatchingKey(object, listOfKeys, caseInsensitive=True):
"""
Function to take an object and a list of keys and return the value of the
longest matching key or None if no key matches.
:param object: The object with the keys.
:type object: dict
:param listOfKeys: A list of keys to... | 25271697197c5c16c2ad5ae7320fc452bc3c8205 | 44,500 |
def get_subscribers():
"""Get all global subs"""
return _SUBSCRIBERS | 03b080796a4688b039f0380ee3ba95202067aabe | 44,501 |
def python_version_is_greater_or_equal(major, minor=0, micro=0):
"""Alias for `~json_indent.pyversion.python_version_is_at_least()`:py:func:."""
return python_version_is_at_least(major, minor, micro) | d3a1b2680b13e20c439ae12cb334bec50f958d42 | 44,502 |
def parse_mimetype(mimetype):
"""Parses a MIME type into its components.
:param str mimetype: MIME type
:returns: 4 element tuple for MIME type, subtype, suffix and parameters
:rtype: tuple
Example:
>>> parse_mimetype('text/html; charset=utf-8')
('text', 'html', '', {'charset': 'utf-8'})
... | ae6136ecc9602a162853204642a443e904cac4b8 | 44,503 |
def generate_summary_movement_report(
movement_detail_report: pd.DataFrame,
) -> pd.DataFrame:
"""
Aggregate by source time for period statistics.
"""
summary_movement_report = movement_detail_report.groupby("source_time")[
[
"transportation_units",
"transportation_co... | e2ebc246486ef5de62d223d86ae12ab4dc8e7142 | 44,504 |
def object_key(obj):
"""Generate a checksum for a nested object or list."""
key = sha1()
if isinstance(obj, (list, set, tuple)):
for o in obj:
o = object_key(o)
if o is not None:
key.update(o)
elif isinstance(obj, dict):
for k, v in obj.items():
... | 7f503cf03d98f03a75dec53e289065ca6aec4c2b | 44,505 |
import numpy
def gfalternate_gotdataforgaps(data,data_alternate,alternate_info,mode="verbose"):
"""
Returns true if the alternate series has data where the composite series has gaps.
"""
return_code = True
ind = numpy.where((numpy.ma.getmaskarray(data)==True)&(numpy.ma.getmaskarray(data_alternate)... | 6bf3bdb84ceaf2a1a9e16efd9199b30774291281 | 44,506 |
def key_type(key):
"""String identifying if the key is a 'name' or an 'ID', or '' for None.
This is most useful when paired with key_id_or_name_as_string.
Args:
key: A datastore Key
Returns:
The type of the leaf identifier of the Key, 'ID', 'name', or ''.
"""
if key.id():
return 'ID'
elif k... | 8d055fc97313b7f613e5927d0f8f38d060a2cb2b | 44,507 |
def cvReadString(*args):
"""cvReadString(CvFileNode node, char default_value=None) -> char"""
return _cv.cvReadString(*args) | 25124e0ad0e1490ed3742d64f14cee4e43ec11e9 | 44,508 |
def compare_graph_properties(graph_properties):
"""
This function takes a dataframe of graph properties.
Each graph property is compared to other groups with the Mann-Whitney test.
Takes a pandas dataframe of graph properties with the following columns:
Network, Group, Network type, Conserved fract... | 2fd164bda1fe37e70efefbc9df75fc91b232f373 | 44,509 |
def _select_encoding(consumes, form=False):
"""
Given an OpenAPI 'consumes' list, return a single 'encoding' for CoreAPI.
"""
if form:
preference = [
'multipart/form-data',
'application/x-www-form-urlencoded',
'application/json'
]
else:
pre... | 81cac06c34f3df0d3c570ebcae90545a3a988fbc | 44,510 |
def execute_command(command: str, new_image: Image, threshold=True) -> Image:
""" __author__ = "Trong Nguyen"
Return a new image given a valid command, an image and if required,
a threshold value.
>>> execute_command("E", new_image, 10)
"""
functions = {"L": load, "S": save_as,
... | 54e87e4124ad05f21aeac99c5712da0863c8075a | 44,511 |
from sys import getsizeof
from typing import Mapping
import weakref
from typing import Container
def deep_getsizeof(o, ids):
"""Find the memory footprint of a Python object
This is a recursive function that rills down a Python object graph
like a dictionary holding nested ditionaries with lists of lists
... | 031f1da7931ab0df69aaa5eeb65a71534f126d49 | 44,512 |
def previous_prime(x):
"""前一个质数"""
if x <= 2:
return None
if x == 3:
return 2
if x % 2 == 0:
x -= 1
else:
x -= 2
while True:
if is_prime(x):
return x
else:
x -= 2 | 6ae7e33d55f3794da904db2040bea49a58eafb84 | 44,513 |
def other_classes(nb_classes, class_ind):
"""
Heper function that returns a list of class indices without one class
:param nb_classes: number of classes in total
:param class_ind: the class index to be omitted
:return: list of class indices without one class
"""
other_classes_list = list(ra... | 05b88e49827523508b14400aa83aa83dd48f2b2e | 44,514 |
def manage_frozen_objects():
"""
Manage objects that have been frozen due to being unsuitable for
preservation for time being
"""
return render_template(
"tabs/manage_frozen_objects/manage_frozen_objects.html"
) | b688fdf93b144a546215ea0206a580776e951b49 | 44,515 |
import os
import re
import warnings
def retrieve_datasets(source_path, countries_cities_dict, pollutants, years):
"""
Retrieve the selected EEA air pollution datasets from the local storage.
The EEA datasets are csv files.
Parameters
----------
source_path : str
Local path in which t... | b3ca939d3cc0d8220486cff00796655e398a08f3 | 44,516 |
def get_gvf(data_list, num_classes):
"""
The Goodness of Variance Fit (GVF) is found by taking the difference between the squared deviations
from the array mean (SDAM) and the squared deviations from the class means (SDCM), and dividing by the SDAM
"""
breaks = get_jenks_breaks(data_list, num_class... | 531454ece4102db986b8d37f21e666cad17412c8 | 44,517 |
def init_capacities(edges, transactions, amount_sat, verbose=False):
"""Initialize capacity map for path search"""
tx_targets = set(transactions["target"])
# init capacity dict
keys = list(zip(edges["src"], edges["trg"]))
is_trg = edges["trg"].apply(lambda x: x in tx_targets)
# [current_cap, tot... | cf1de4433c52d07ccd75f7ef39d2899974ec8517 | 44,518 |
import torch
import os
def train(net, dataloader, emb, caption, device, n_epoch=10, unfreeze_epoch=0, lr=1e-5,
verbose=True, ignore_bg=False, floss=F.l1_loss):
"""
:param net: neural network to be trained
:param dataloader: dataset
:param emb: embedding system (see embeddings)
:para... | 252918ffedf5f42ba36cce1d3f399f82e2995de8 | 44,519 |
def calculate_iou(gt, pr, form='pascal_voc') -> float:
"""Calculates the Intersection over Union.
Args:
gt: (np.ndarray[Union[int, float]]) coordinates of the ground-truth box
pr: (np.ndarray[Union[int, float]]) coordinates of the prdected box
form: (str) gt/pred coordinates format
... | c093fb8b36a87e2aad862d842e71f1f76b3dd791 | 44,520 |
import json
from datetime import datetime
def create_task(tenant_id='tenant_id'):
"""
Create a new task entry.
POST format:
{
"name": "My New Task",
"config": "\{\"task\": \"do something\"\}",
"agent_url": "swift://region-a.geo-1/mycontainer/myagent.py",
"email": "jeff.kramer@hp.com",
"interval": "300",... | 543213c5c370500b7076687901fcddbaa9da5ae9 | 44,521 |
from typing import Dict
from io import StringIO
def interpolate(s: str, registers: Dict) -> str:
"""
Interpolates variables in a string with values from a supplied dictionary of registers.
The parser is very lax and will not interpolate variables that don't exist, as users
may not be intending to int... | a877e455771e09bcca85455ffefe87c4622255f2 | 44,522 |
def login(user=None, verified=False, admin=False, overrides=None, return_field=None):
"""
Logs in user and returns the User object. If a user object is not specified,
one is randomly generated. The user object is force authenticated on the
DRF API client. If the return_field is specified it returns the ... | 7da1a5f50d10bce6cc4231cdb084e6a635d169a3 | 44,523 |
def retrieve_from_any(ecli, rootpath=None):
"""
Checks if it can find the xml document in the filesystem,
otherwise retrieves it from the web.
:param ecli:
:param rootpath:
:return: xml element
"""
el = None
if rootpath is not None:
el = retrieve_xml_from_filesystem(ecli, r... | 37daf8adb654e941c1fdfd075470375860569759 | 44,524 |
def defineNodePositions(smax,pmin,fun,nodegap,L=200.):
"""
Loop through sections and determine optimal placement
of nodes in order to prevent vignetting/collisions
"""
#Loop through sections and construct node positions
N = len(smax)
rsec = []
rext = []
gap = L*3e-3+0.4 #.4 mm glass ... | 52a08fa1dc25d80ff5aff5e166eec8f9b396a257 | 44,525 |
import numexpr
def normalize_mi_ma(x, mi, ma, clip=True, eps=1e-20, dtype=np.float32): # dtype=np.float32
"""This function is adapted from Martin Weigert"""
if dtype is not None:
x = x.astype(dtype, copy=False)
mi = dtype(mi) if np.isscalar(mi) else mi.astype(dtype, copy=False)
ma = d... | c8a93fff58dfa9d288128278d2d894df82427122 | 44,526 |
def read_image(img_path):
"""Keep reading image until succeed.
This can avoid IOError incurred by heavy IO process."""
got_img = False
while not got_img:
try:
img = Image.open(img_path).convert('RGB')
got_img = True
except IOError:
print("IOError incur... | 26d0d0061d14e6916273a4fd418d5364ea1256ec | 44,527 |
def check_image_valid(im_source, im_search):
"""Check if the input images valid or not."""
if im_source is not None and im_source.any() and im_search is not None and im_search.any():
return True
else:
return False | d5bc706df271163b1857158820ee707a0229b83c | 44,528 |
def fabric_inband_net_create(module, inband_static_part):
"""
Method to create in-band network.
:param module: The Ansible module to fetch input parameters.
:param inband_static_part: It contains ip address of inband ip till third
octet.
:return: The output messages fo... | a44edd0e3998cd3ac622876a852d9e2aafa045e2 | 44,529 |
def create_match_apds_input_filenames(from_date, to_date, datestring):
""" Create the list of filenames for match_apt_trajectories.py. """
return [create_flights_filename(CPR_FR24, datestring),
create_apds_flights_filename(from_date, to_date),
create_events_filename(CPR_FR24, datestring)... | 118c214bfe1da657b2020ff4cc977cbef43266d5 | 44,530 |
def get_emoji_modifier_sequences(age=None):
"""Return map of modifier sequences to name, optionally limited to
those <= the provided age."""
_load_emoji_sequence_data()
return _age_map_select(_emoji_modifier_sequences, age) | ad3f48d2492caa24bcbc4d055a95a2d088921795 | 44,531 |
def update_taxes_with_shipping_lines(taxes, shipping_lines, shopify_settings):
"""Shipping lines represents the shipping details,
each such shipping detail consists of a list of tax_lines"""
for shipping_charge in shipping_lines:
if shipping_charge.get("price"):
taxes.append({
"charge_type": _("Actual"),
... | 21a30b6d9e83432b9772c70bce30cd722ccb10c5 | 44,532 |
from typing import List
def equal_accuracy(confusion_matrix_list: List[np.ndarray],
tolerance: float = 0.2,
label_index: int = 0) -> np.ndarray:
"""
Checks if accuracy difference of all grouping pairs is within tolerance.
.. note::
This function expects a list... | f7bd87ae947acd1496fd11b5c96b492d5af978eb | 44,533 |
def vm_snapshot_list_cb(result, task_id, vm_uuid=None, snap_ids=None):
"""
A callback function for DELETE api.vm.snapshot.views.vm_snapshot_list.
"""
snaps = Snapshot.objects.filter(id__in=snap_ids)
action = result['meta']['apiview']['method']
if result['returncode'] == 0:
vm = snaps[0]... | d57eb75d596a414ec77b4a3fe471c665b34f40b0 | 44,534 |
import array
import math
def fpart(x):
"""FRACTIONAL PART OF A REAL NUMBER"""
if type(x) in [array, list]:
if len(x) == 1:
x = x[0]
return math.modf(x)[0] | 03659c7b0ae133d226019141af59f4ec039c7dde | 44,535 |
import os
def get_mfp(path, recursive):
"""many,flat,prefix"""
path = normalize_path(path)
flat = not recursive
many = recursive
prefix = ""
if path[-2:] == "**":
many = True
flat = False
prefix = os.path.basename(path[:-2])
elif path[-1:] == "*":
many = True
flat = True
prefix =... | a34b315bb466c0374b40c0a32a84e5334b69a56e | 44,536 |
def BinomialNum(n, p):
"""Generate a binomially distributed random number with parameters n (int) and p (float)"""
assert type(n) == int, "n must be an integer"
assert n >= 1, "n must be greater than or equal to 1"
assert 0 < p < 1, "p must be between 0 and 1, exclusive"
return sum([BernoulliNum(p) for x in range(... | d96a49b07d9068e2c7352e241c515d6c5f2642b7 | 44,537 |
def graph_size_filter(graph, edge_weigths, node_sizes, min_size,
node_labels=None, relabel=False):
"""
"""
n_nodes = graph.numberOfNodes
if node_labels is None:
seeds = np.zeros(n_nodes, dtype='uint64')
assert n_nodes == len(node_sizes)
keep_nodes = node_si... | 8509d6f207bbd2ed8e676c2909b2daa2792a596e | 44,538 |
def prepare_arguments_deps(parser):
"""Parse arguments that belong to this verb.
Args:
parser (argparser): Argument parser
Returns:
argparser: Parser that knows about our flags.
"""
parser.description = """ Manage dependencies for one or more packages in
a catkin workspace.... | a81760948787921c0bdaa6d34a34f688392f2a0f | 44,539 |
from typing import Optional
def bar(a: Optional[int], b: t.Optional[int]) -> int:
"""WHAT"""
return (a or 42) + (b or 0) | b2e43cb30c8af5fa8b03220ae0f7260084a5f9fd | 44,540 |
from functools import reduce
def checkarrays(f):
""" Similar to the @accepts decorator """
def new_f(*args, **kwd):
assert reduce(lambda x, y: x == y, map(np.shape, args))\
, """Array and Subarray must have same dimensions,
got %s and %s"""\
.replace(' ', '') % (ar... | 50c579f02cd99a84eb7c9e11a1daf63e652d7f52 | 44,541 |
from PCAfold import PCA
def outlier_detection(X, scaling, method='MULTIVARIATE TRIMMING', trimming_threshold=0.5, quantile_threshold=0.9899, verbose=False):
"""
Finds outliers in the original data set, :math:`\mathbf{X}`, and returns
indices of observations without outliers as well as indices of the outli... | d5d596616ab8ee838cfbf0c679f07a7bfbb06c32 | 44,542 |
import subprocess
import sys
import os
def read_coverage(chrom, cov=10, length=249250621, path="data/exacv2.chr{chrom}.cov.txt.gz"): #length may need to be fixed in the future, if new chromosome lengths are established in GRCh38 #or data/Panel.chr{chrom}.coverage.txt.gz for exacv1
"""
read ExAC coverage from ... | e5e2d3ac416c52f6529e7abaac3408ee64c93133 | 44,543 |
import typing
import math
def list_to_mathutils(values: typing.List[float], data_path: str) -> typing.Union[Vector, Quaternion, Euler]:
"""Transform a list to blender py object."""
target = get_target_property_name(data_path)
if target == 'delta_location':
return Vector(values) # TODO Should be ... | 04da3947be4fa82c67707d62bc8d092c6729252a | 44,544 |
def count_smileys(arr):
"""count valid smileys from an array, better reading"""
count = 0
eyes = ":;"
noses = "-~"
smiles = ")D"
for i in arr:
if len(list(i)) > 2:
if i[0] in eyes and i[1] in noses and i[2] in smiles:
count += 1
else:
if i[0] in eyes and i[1] in... | ebcd9147614b47a9911dfcb408bfd74c71de4203 | 44,545 |
def apply_mlrun(
model,
context: mlrun.MLClientCtx = None,
X_test=None,
y_test=None,
model_name=None,
generate_test_set=True,
**kwargs
):
"""
Wrap the given model with MLRun model, saving the model's attributes and methods while giving it mlrun's additional
features.
examples... | 8b84c7ea83d9c67a481afd423218150594ecaf4f | 44,546 |
def process_file(filename,word_to_id,cat_to_id,max_length=600):
"""
Args:
filename:train_filename or test_filename or val_filename
word_to_id:get from def read_vocab()
cat_to_id:get from def read_category()
max_length:allow max length of sentence
Returns:
x_pad: sequence data from preprocessing sentence ... | 0eca98da162000b1d86a707514eb4b4b13fa85ce | 44,547 |
def get_key_list(u_id: str, um_status: int) -> list:
"""
获取某个用户保存的友盟keys
:param u_id:
:param um_status:
:return:
"""
_filter: Q = Q(u_id=u_id) & Q(um_status=um_status)
return list(UmKey.objects.filter(_filter).values()) | 09d4808161994c4515588bf9b7761842ced490e0 | 44,548 |
def balanced_tree(ordered):
"""Create balanced binary tree from ordered collection"""
bt = BinaryTree()
add_range(bt, ordered, 0, len(ordered)-1)
return bt | 50fc5c843c581107df8b1db1d1bb8db74a0b5147 | 44,549 |
def tf_split(x, num_or_size_splits, axis=0, num=None, keep_dims=False):
"""Split feature map of high dimension into list of feature map of low dimension."""
x_list = tf.split(x, num_or_size_splits, axis, num)
if not keep_dims:
x_list2 = [tf.squeeze(x_, axis) for x_ in x_list]
return x_list2... | 529f713c9fcd94599f4eb320d8529ed53f551f11 | 44,550 |
def stringify_edge_set(s: set):
""" Convert an agent-piece graph into a string, for display and testing """
return str(sorted([(agent.name(), piece) for (agent,piece) in s])) | 8d95fa4174a37bac1094a13449f92143993bdd23 | 44,551 |
def rholoc(A1: tn.Tensor, A2: tn.Tensor) -> tn.Tensor:
"""
-----A1-----A2-----
| |(3) |(4) |
| |
| |
| |(1) |(2) |
-----A1*----A2*-----
returned as a (1:2)x(3:4) matrix.
Assuming the appropriate Schmidt vectors have been contracted into the As,
np.trac... | c05735c17f0ca58f19388c691366c51c07d2f584 | 44,552 |
def _d(n, j, prec, sq23pi, sqrt8):
"""
Compute the sinh term in the outer sum of the HRR formula.
The constants sqrt(2/3*pi) and sqrt(8) must be precomputed.
"""
j = from_int(j)
pi = mpf_pi(prec)
a = mpf_div(sq23pi, j, prec)
b = mpf_sub(from_int(n), from_rational(1,24,prec), prec)
c ... | f2a37ee3df6dc2d5a1e615df88ef43e37031f872 | 44,553 |
def render_show_category_json(category_id):
"""
METHOD=GET.
Returns a JSON object of a specific category
"""
category = session.query(Category).filter_by(id=category_id).one()
items = session.query(Item).filter_by(category_id=category_id).all()
if category and items:
return jsonify(... | 29f14e41b91820c883d33539d71c96bbd9dbf047 | 44,554 |
def get_fully_qualified_class_name(cls):
"""Returns fully dot-qualified path of a class, e.g. `ludwig.models.trainer.TrainerConfig` given
`TrainerConfig`."""
return ".".join([cls.__module__, cls.__name__]) | dc3cbbb8be4503b562a381aa45842399a623971e | 44,555 |
import sys
def set_completed_todo(todo_id):
"""The route handler setting a todo item to completed.
Args:
todo_id: A str representing the id of the todo item that was completed
Returns:
Response: A json object signalling the update request was successful
"""
error = False
try... | 85bd8b15887b1716f73734f3207c626344ded86e | 44,556 |
import sys
def extARRAYPROC_ZIP(argu):
""" allow processing the data using multicore capabilities
This is a temporary method, as python cannot process using multicores within classes.
So we have to call a method from within the class to run multicores. you provide a
- ** parameters**, **types**, **r... | 273d732310c01c460d7700480c58de547d1a3f52 | 44,557 |
from typing import Union
def convert_bytes(bytes: int, unit: str = "Mi") -> Union[str, int]:
"""Converts a number of bytes to a string representation.
By default, the output is in MiB('Mi') format.
If unit is 'b', the output would be an integer value.
(e.g., convert_bytes(1024, 'b') -> 1024)
Onl... | dc38268c668e1b49718f167b5fc2767613d055b1 | 44,558 |
def global_settings(request):
"""
Expose various settings
"""
return {
'global_settings': {
'google_analytics_tracking_id': settings.GOOGLE_ANALYTICS_TRACKING_ID,
'IMIS_SSO_LOGIN_URL': settings.IMIS_SSO_LOGIN_URL,
'HELIX_LOGOUT_URL': settings.HELIX_LOGOUT_URL
... | 0f83b5000a8946d46fba244bdc67b5f2141ee0dc | 44,559 |
def index():
"""
The landing page of the site
:return: Returns a rendering of the landing page.
"""
form = Transaction(request.form)
return render_template("transaction.html", form=form) | e85ff39e1525b303604c815eea6b33d69290ac35 | 44,560 |
def determine_flow_unit(stock_unit: str, time_unit: str = "h"):
"""For example:
>>> determine_flow_unit("m³") # m³/h
>>> determine_flow_unit("kWh") # kW
"""
flow = to_preferred(ur.Quantity(stock_unit) / ur.Quantity(time_unit))
return "{:~P}".format(flow.units) | b359cba095f94101ac5c9ef1d6815897db33cff9 | 44,561 |
from typing import List
def handle_hosts(
actapi: act.api.Act, content: Text, hosts: List[Text]
) -> List[act.api.fact.Fact]:
"""handle the hosts part of a hybrid-analysis report"""
feeds_facts: List[act.api.fact.Fact] = []
for host in hosts:
(ip_type, ip) = act.api.helpers.ip_obj(host)
... | 14aee6fbe5eb2d51c8ae2349648f6f32573030e7 | 44,562 |
def parsevROps(payload, alert):
"""
Parse vROps JSON from alert webhook.
Returns a dict.
"""
if (not 'alertId' in payload):
return alert
alert.update({
"hookName": "vRealize Operations Manager",
"AlertName": payload['alertName'] if ('alertName' in payload and payloa... | 8149dd87f26c0767692dcd79ab88a36e1f2e328b | 44,563 |
def as_chunks(l, num):
"""
:param list l:
:param int num: Size of split
:return: Split list
:rtype: list
"""
chunks = []
for i in range(0, len(l), num):
chunks.append(l[i:i + num])
return chunks | 6bf6a2efed8e4830447319dd1624e70463faaf41 | 44,564 |
def extract_average_values_roc(nb_random_realizations, fpr_list, tpr_list, auc_values):
"""This function extracts the average values for the ROC curve across the random realizations
Args:
nb_random_realizations (int): number of cross-validation runs that were performed
fpr_list (list... | 710a904ce50f6fd0f7c8b0cec1a44c72f4417041 | 44,565 |
def prepare_for_training(data, polynomial_degree=0, sinusoid_degree=0, normalize_data=True):
"""Prepare dataset for training on prediction."""
# Calculate the number of examples.
num_examples = data.shape[0]
# Prevent original data from being modified.
data_processed = np.copy(data)
# Normali... | c20ac524ed44bb9c1bff0943c85ec16251a6915a | 44,566 |
def z_curvature_stacks(z_fit_params, z_contour_stack):
"""
Calculates curvature, normal, and tangent vectors of contours on a given
image stack on z-slice
Iteratively steps through z_fit_params and z_contour_stack and calls
curvature_z_slice
Parameters
----------
z_fit_params : list
... | 8af26fb34a9a1d6b78adf6d2192c040504f0f355 | 44,567 |
import requests
def get_ec2_instance_ip():
"""Try to obtain the IP address of the current EC2 instance in AWS"""
try:
ip = requests.get('http://169.254.169.254/latest/meta-data/local-ipv4', timeout=0.01).text
except requests.exceptions.ConnectionError:
return None
return ip | b9b403124daba52236218d75225c537b450f283b | 44,568 |
import random
def e_greedy(options, e=0., reverse=False):
""" Epsilon-greedy algorithm for selecting sampled bandits
Parameters
----------
options : list
list of the bandits samples
e : float, default = 0
epsilon value between 0 and 1 that determines how random the chosen bandit i... | 648ceccf20ac19078557f8185f83c29c985f8ae8 | 44,569 |
from typing import Tuple
from typing import List
def get_all_serialization_annotations(
annotation: Annotation
) -> Tuple[Annotation, List[SerializationAnnotation]]:
"""Gets the type T of Annotation[T, SerializationAnnotation]
Args:
annotation (Any): The annotation
Returns:
Tuple... | a88818a33ec311fb39ad7d42ecd6abc3b651b062 | 44,570 |
def _name_to_agent_class(name: str):
"""
Convert agent name to class.
This adds "Agent" to the end of the name and uppercases the first letter
and the first letter appearing after each underscore (underscores are
removed).
:param name:
name of agent, e.g. local_human
:return:
... | 6ac0dbf4fb8ab90e592b85216be6d9c109a1310c | 44,571 |
def bin_search_recursive(array, what_to_find, left=0, right=None):
"""
Finds element in a sorted array using recursion.
:param list array: A sorted list of values.
:param what_to_find: An item to find.
:returns: Index of the searchable item or -1 if not found.
"""
right = right if right is... | 83ff4dbcd9cab179c5e83f73d5fdc7c5a6bca4d4 | 44,572 |
from typing import List
def extensions_to_glob_patterns(extensions: List) -> List[str]:
"""Generate a list of glob patterns from a list of extensions.
"""
patterns: List[str] = []
for ext in extensions:
pattern = ext.replace(".", "*.")
patterns.append(pattern)
return patterns | a04ed356bfa5db7c0210b86dff832d32bfef6dbf | 44,573 |
def is_classvar(t):
"""
>>> is_classvar(typing.ClassVar[int])
True
>>> is_classvar(int)
False
"""
return is_from_typing_module(t) and str(t).startswith("typing.ClassVar[") | 611092fa7c2f430aa755bbd667d40abcd7ccf693 | 44,574 |
from typing import Tuple
def get_reduced_powers(values: Tuple, power: int) -> Tuple[Expr, Symbol]:
"""
For a variable v only taking finitely many values v**n can be written as linear
combinations of powers < |values|. This function computes this linear combination.
The values ought be passed as a sort... | edb4977ec5ee84129f35b1d8bafed59ad948b3f0 | 44,575 |
def detect_cross_pnt(arr, thr, way='up', gap=1):
"""
detect the data rise/down point, returns the index of the
point right above the threshold.
arguments:
- arr: data array (1d)
- thr: threshold (scale)
key arguments:
- way: either be "up" or "down", for data rise/ data down respective... | 0cf5db8f78cb0ee81174a7d662551c095480de97 | 44,576 |
def check_resource(drink_ingredients):
"""Checks whether the ingredients in the machine enough to make the drink"""
for items in resources:
if drink_ingredients[items] > resources[items]:
print(f"Sorry there's not enough {items}!")
return False
return True | ecd869d4f09032e57d151ec6816fc2b08dce41b8 | 44,577 |
def handler(event, context):
"""
https://docs.aws.amazon.com/lambda/latest/dg/with-scheduled-events.html
"""
print(event, context)
publisher.handle(event, context)
return {} | 049029afedc796f86fd2b82637464e724d722bf9 | 44,578 |
from typing import Union
from typing import Mapping
def extract_image(
inputs: Union[jnp.ndarray, Mapping[str, jnp.ndarray]]
) -> jnp.ndarray:
"""Extracts a tensor with key `image` or `x_image` if it is a dict, otherwise returns the inputs."""
if isinstance(inputs, dict):
if "image" in inputs:
retur... | 2a4ecc20c861532736a4725fbe5a19b53847a53e | 44,579 |
def drop_duplicate_cols(df: pd.DataFrame) -> pd.DataFrame:
"""Remove duplicated colulms from a df
# https://stackoverflow.com/questions/14984119/python-pandas-remove-duplicate-columns/40435354#40435354
Args:
df (pd.DataFrame): df with duplicated column names
Returns:
pd.DataFrame: df ... | 3b5ffa67b363e59271a5c6392fec0365c2034daf | 44,580 |
def find_sources(indegrees: dict) -> deque:
"""Find sources (nodes that have 0 inbound edges).
Args:
indegrees (dict): A dictionary where the key is a graph node \
and the value is the number of inbound edges.
Returns:
deque: A deque containing source nodes.
"""
sources = d... | f31c67eedebe9d15aa65fbbcc1b36cf52c4eccc7 | 44,581 |
def stretch_audio(x, rate, window_size=512):
"""Stretch the audio speech using spectrogram.
Args:
x (numpy.ndarray): Input waveform.
rate (float): Rate of stretching.
window_size (int, optional): Window size for stft. Defaults to 512.
Returns:
numpy.ndarray: The stretched a... | cd07aca4db84eb8934510afd6770b439289bc264 | 44,582 |
async def email_subscribe_confirm(token, hood=Depends(get_hood_unauthorized)):
"""Confirm a new subscriber and add them to the database.
:param token: encrypted JSON token, holds the email of the subscriber.
:param hood: Hood the Email bot belongs to.
:return: Returns status code 200 after adding the s... | 441ec97f6534749fb6a006a443326f56ebe75f8f | 44,583 |
def pairing_gen(email_addresses):
"""This function generates the final pairings and outputs an alphabetically sorted pandas dataframe with all
elements in both columns """
pairing_1 = []
pairing_2 = []
for first_member, second_member in grouper(email_addresses, 2, SUBSTITUTE):
pairing_1.appe... | 5efa2b3a7f6de73c2c117dd3e7a0407e8ce52e57 | 44,584 |
import torch
def get_joint_loss(data_dict, device, config, weights,
detection=True, caption=True, reference=True, use_lang_classifier=True, num_ground_epoch=50):
""" Loss functions
Args:
data_dict: dict
config: dataset config instance
reference: flag (False/True)
Returns:
... | 66d5358286b20dc2e4efa5ed71bea298c4a5eeca | 44,585 |
def specr_model(fn, a,b,c1,c2,d,e):
"""
Description:
------------
Theoretical model for spectral ratio. Preferred model is
determined by the values of d & e and they are user-defined.
Input:
-----------------
fn --> freqeuncy bins
a --> fc main event
b --> fc egf
... | 1355ba14569cb87ebe6d8f937db81db89fc8c952 | 44,586 |
import re
def get_operation_id_groups(expression):
"""Takes an operator expression from an .mmcif transformation dict, and
works out what transformation IDs it is referring to. For example, (1,2,3)
becomes [[1, 2, 3]], (1-3)(8-11,17) becomes [[1, 2, 3], [8, 9, 10, 11, 17]],
and so on.
:param str ... | 8ec6fdca5209de1d658a2ae938fc840e9d1b0c23 | 44,587 |
from typing import Optional
def is_plus(char: Optional[str]) -> bool:
"""Check if character is a plus symbol."""
return char == PLUS | 9a9a1141f87150ec621e283362a1831eb0bb8288 | 44,588 |
def mrt_alert_msg(mrt_line, direction, stations, public_bus, mrt_shuttle, mrt_shuttle_dir):
"""
Message that will be sent if there is an MRT alert/breakdown/delay
:param mrt_line: "DTL/NSL/EWL..."
:param direction: "Both"/specific MRT station name("Jurong East")
:param stations: "NS17, NS16, NS15, N... | df03473dab23748f42bfe9fc8bc0fe9a80fc7c74 | 44,589 |
import re
def normalize(contentData):
"""
The primary normalization and de-obfuscation function. Runs various checks and changes as necessary.
Args:
contentData: Script content
Returns:
contentData: Normalized / De-Obfuscated content
"""
# Passes modificationFlag to each fun... | 5bd34668e536aaf4d497f517fe5fde2197796baa | 44,590 |
def clusters_tournament(ptree, labels):
"""A cluster 'wins' if some node inside the cluster is the ascendant
of another node in the other cluster"""
L = np.max(labels) + 1
T = np.zeros((L, L), dtype=int)
for i, m in enumerate(ptree.match):
li = labels[i]
if li != -1:
for ... | 8ccf7ad28e58c44c7f12051bded48136fe7598c5 | 44,591 |
from datetime import datetime
import requests
from bs4 import BeautifulSoup
def _load_quebec(start_date=datetime(2020, 1, 1), end_date=datetime.today(), verbose=True):
"""
Parameters:
- `start_date`
datetime object, the date of the earliest news release to be retrieved. By default, only ... | 295b723a4e7ab6d36c540e1910e954b0efd439bd | 44,592 |
def batch_to_model_inputs(batch, aux, prog, diag, forcing, constants):
"""Prepare batch for input into model
This function reshapes the inputs from (batch, time, feat) to (time, z, x,
y) and includes the constants
"""
batch = merge(batch, constants)
def redim(val, num):
if num == 1:
... | b0268c72499823bad747fb30e4be8d091c3060d6 | 44,593 |
def is_envvar(buff, pos):
""":return: start, end, pos or None, None, None tuple."""
try:
while buff[pos] in ' \t':
pos += 1
start = pos
while True:
if buff[pos] in '\0"\'()- \t\n':
return None, None, None
if buff[pos] == '=':
... | ee424577dd91a7d7011996c5f185f15855e1d2f5 | 44,594 |
def application():
"""Create an application."""
return flaked.Application() | 067fc7e8763678b1ba3387f95f8b90fc3f1075bd | 44,595 |
from bs4 import BeautifulSoup
def urlscraper(url: str, pattern: str, regex:bool=False) -> list:
"""urlscraper is a simple method to scrape information from a url based on a given string pattern
:param url: the url to run pattern against
:param pattern: the string representation of the pattern
:param ... | a1788fb1e6d98d1fb65dd3bdb617bf9a22f0a053 | 44,596 |
def load_model(filename):
"""
Return a model stored within a file.
This routine is for specialized model descriptions not defined by script.
If the filename does not contain a model of the appropriate type (e.g.,
because the extension is incorrect), then return None.
No need to load pickles o... | 2be8d79119538c31606dfccffd8560aa82dc4e7a | 44,597 |
def climb_stairs(stairs):
#
"""You are climbing a stair case. It takes n steps to reach to the top.
Each time you can either climb 1 or 2 steps. In how many distinct ways can
you climb to the top?
Example:
Input: 2
Output: 2
3
1 1 1
1 2
2 1
"""
... | c32a05ab1013b769c2d040a00c622605d7893398 | 44,598 |
def measure_nearest_neighbor_performance(accuracy_label, encoder,
family_accessions, batch_size,
train_samples, shuffle_seed,
sample_random_state):
"""Measures nearest neighbor classification p... | defbc8a86978062997fb6bacb912c014ede6fbf0 | 44,599 |
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