content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def getclasesbyid_(numid):
"""
Returns all defined clases by id [number]
"""
data = get_info_token()
user_ = data['User']
rol_ = data['Rol']
data_response = ''
if rol_ == 'Professor':
try:
bool_, data_response = getclassbyid_(data['User'],numid)
if bool_:
... | 75603f40621f51313863aa8977b71241a31c3d84 | 30,067 |
import json
def load_versions():
"""Load Bioversions data."""
with open(VERSIONS_PATH) as file:
return json.load(file) | e5e3b2a3dd4ae17fe6cf6b00700b33e9bc55e6b5 | 30,068 |
async def retrieve_document(document_id: str, collection: str) -> dict:
"""
:param document_id:
:param collection:
:return:
"""
document_filter = {"_id": ObjectId(document_id)}
if document := await greens.app.state.mongo_collection[collection].find_one(document_filter):
return await... | 4865acd4e553f651a68d694171c76d609eceff98 | 30,069 |
import requests
def get_kalliope_poststukken_uit(path, session, from_,
to=None,
dossier_types=None):
"""
Perform the API-call to get all poststukken-uit that are ready to be processed.
:param path: url of the api endpoint that we want to f... | 2976979bfcccd64939e56c2d0874f6d419028b62 | 30,070 |
import scipy
def lstsq_cholesky(
coefs: np.ndarray,
result: np.ndarray,
) -> np.ndarray:
"""Solve OLS problem using a Cholesky decomposition."""
left = coefs.T @ coefs
right = coefs.T @ result
return scipy.linalg.solve(left, right, assume_a="pos") | 08ec0988062daef04b55852d6673fb21031f9a87 | 30,072 |
import warnings
def _standardize(signals, demean=True, normalize=True, inplace=True,
verbose=False):
""" Center and norm a given signal (time is along first axis)
Attention: this will not center constant signals
but will replace these with colums of ones
... | f207af4e0e18f6f9f544a18ae89d0e86fd8ae493 | 30,075 |
def bbox_to_poly(bboxes: np.ndarray) -> np.ndarray:
"""
Expects bboxes in xyxy format. Turns each into a 1D array with 8 entries,
every consecutive pair being for one vertex (starting from top left and
going around clockwise)
Works with single bboxes (shape is (4, )) or multiple bboxes (shape is
... | 12a06d343ac5a1f4bd16168bf04dc7e9dfaff4ec | 30,076 |
def waypts_2_pwsplines(wp_traj, dt, degree=1, plot=False):
"""
Convert a sequence of multi-dimensional sparse waypoints
to a sequence of interpolated multi-dimensional waypoints via splines.
Parameters
----------
wp_traj: horizon * n_s, a sequence of waypoints.
dt: duration of 1 time step o... | b133159e19513fa80a282a71786e5976cad1ab9a | 30,077 |
def _bin_data(aa, bb, bins=10, verbose=False):
"""
If unbinned data has come in, do something smart
with it here.
Uses numpy.histogram for binning.
bins can be:
- int: number of bins
- list or array: bin boundaries, from min to max, half open on right,
like numpy, when bins=[1, 2, ... | a938cabaa2678a89cb1402d553041d409bfa4967 | 30,078 |
import logging
def initialize_logger(logger, logger_id, progress_bar=None, log_queue=None):
"""
Initialize logger for the :class:`pyro.infer.mcmc` module.
:param logger: logger instance.
:param str logger_id: identifier for the log record,
e.g. chain id in case of multiple samplers.
:para... | 4ea94d0bc1d6d9943cce2097f19256e3524d9521 | 30,079 |
def test_meta_plus_classmethod(namespaceable, namespace):
"""Test using a classmethod in a Namespace, while messing with metaclasses.
This might have been purely for coverage of some kind? I forget.
"""
class Meta(namespaceable, type(namespaceable)):
"""A throwaway test metaclass."""
wi... | 48ed58e8b4a0c68700ee8941087d015b76596c57 | 30,080 |
def EncodeConstants(const_dict):
"""the NPU requires that weights are compressed and bias/scales are 'encoded', both
of which are performed by this pass.
This pass modifies both the constant dict to contain the post-encoding values of the
constants and the IR to adjust buffer types/sizes/accesses so th... | 851e080bdf44e6de890fb87a1d2df1c0aefc0bf6 | 30,081 |
import collections
def count_tweet_shed_words_freq(tweet_text, ind_shed_word_dict, shed_word_ind_dict, shed_words_set):
"""
Count the frequency of selected Hedonometer words in tweet text.
param tweet_text: String of text field of tweet
return: dict of shed_word_ind to shed_word_freq mapping... | 129130f5b9def7320c6e3dd2d8ef82493d21eb8a | 30,082 |
def parse_date(text):
"""Return POSIX timestamp obtained from parsing date and time from given
date string.
Return None if no text given.
"""
if text:
return dateparser.parse(text).timestamp() | 6f089096cdd43eb2d0af1db6066e75a6ec6efb09 | 30,083 |
def format(table, field, fmt, **kwargs):
"""
Convenience function to format all values in the given `field` using the
`fmt` format string.
The ``where`` keyword argument can be given with a callable or expression
which is evaluated on each row and which should return True if the
conversion shou... | a66e351bca42f8e385d8859db720e86c7e6fac7c | 30,084 |
def colorbias(img, refcolor=np.array([1.,0,0])):
""" Compute Color Bias """
img_hsv = skimage.color.rgb2hsv(img)
refcolor = skimage.color.rgb2hsv(refcolor.reshape(1,1,3)) # to make it compatible
#dH = np.abs(np.sin((img_hsv[...,0] - refcolor[...,0])))
#dS = np.abs(img_hsv[...,1] - refcolor[...,1])
... | 5ab089fd7a72fe647e5da5c62380544b87c41739 | 30,085 |
import six
import numbers
import collections
def walk_json(e, dict_fct=i, list_fct=i, num_fct=i, str_fct=i, bool_fct=i, null_fct=i, not_found=not_found_default):
"""
Go throught a json and call each function accordingly of the element type
for each element, the value returned is used for the json output
... | d0c9f57180327b8fca218f3ba4f413b410c2a2da | 30,086 |
def colIm(z):
"""Returns a colour where log(Im(z)) is represented by hue.
This makes it easy to see where Im(z) converges to 0"""
h = np.log(z.imag)*pi
l = np.clip(0.5+0.05*z.real,0.1,0.9)
s = 1
c = hsl2rgb(h,s,l)
return c | 0ebefac4c7c5355ba735bfa46177b6f267f74cb9 | 30,087 |
def gsl_blas_zdotc(*args, **kwargs):
"""gsl_blas_zdotc(gsl_vector_complex const * X, gsl_vector_complex const * Y, gsl_complex * dotc) -> int"""
return _gslwrap.gsl_blas_zdotc(*args, **kwargs) | 953a9cd06d0f7a948d625acad9fd8ec8ce31249e | 30,088 |
def random_neighbour(vec,myid,n):
"""Generates a random binary vector that is 1-bit away (a unit Hamming distance)
Args:
vec (list or numpy.ndarray): An input vector
myid (int): An id of an agent of interest
n (int): Number of tasks allocated to a single agent
Returns:
list... | 816115c335e556815ff8ee20ae50ac9b9c9d6f22 | 30,089 |
import torch
def _degree_of_endstopping(model, block, image, weight_id0, weight_id1, weight_id2):
"""Passes image to model and records the activations of block. The
activations are normalized to be in [0, 1] and then summed over using
different weighted masks.
Parameters
----------
model : ... | 830e8fd5b008fb8d2a852f1f365d3da1ddc24075 | 30,090 |
def posts(parsed):
"""Calculates number of every type of post"""
num_t_post = 0
num_corner_post = 0
num_line_post = 0
num_end_post = 0
num_gate_posts = 0
for post in parsed.posts():
if not post.isRemoval:
if post.postType == 'tPost':
num_t_post += 1
... | e8c5905a38ab560f0dba595eecf67865efc27121 | 30,091 |
def _compute_populations(mvts: pd.DataFrame, label_col_name) -> dict:
"""
A private method that computes the population corresponding to each class label.
:param mvts: The dataframe who class population is of interest.
:param label_col_name: The column-name corresponding to the class labels in `mvts`.
... | d47b78d8f30f6cb15c9b98cb13d9fb7c883d62f1 | 30,092 |
def plot_avg_sum_capacity_comparison(
df: pd.DataFrame, port1: str, port2: str, vessel_type: str
) -> go.Figure:
"""
Returns a figure for the first chart on the Compare tab. It shows per day comparison between
average sum of capacity by applied conditions.
:param df: Pandas DataFrame, input data
... | 8551fac8720c3d8433a5242c8ea099626a5b6e0c | 30,093 |
def num_neighbours(lag=1):
"""
Calculate number of neigbour pixels for a given lag.
Parameters
----------
lag : int
Lag distance, defaults to 1.
Returns
-------
int
Number of neighbours
"""
win_size = 2*lag + 1
neighbours = win_size**2 - (2*(lag-... | aca8c4e1fdac14cde111a7db2dd274767fc53d5a | 30,096 |
import requests
def get_solr_data_recommend(function, reader, rows=5, sort='entry_date', cutoff_days=5, top_n_reads=10):
"""
:param reader:
:param rows:
:param sort:
:param cutoff_days:
:param top_n_reads:
:return:
"""
query = '({function}(topn({topn}, reader:{reader}, {sort} desc... | b7dbf5fc2cd8772532ab98115369199e87e80a3c | 30,097 |
def normalize_key(key):
"""
Formata a chave para ser utilizada no json.
Args:
key (string): Campo coletado no scraping dos dados do MEC.
Returns:
Retorna a sttring formatada para ser utilizada no json.
"""
aux = key.strip(' :').replace(' ', '_').lower()
... | 1065bbbd4d6c435fe9db477ee0f7a047692eaf63 | 30,098 |
def line(p0=(0,0), p1=(1,0)):
"""
p0 p1
o-----------o
+--> u
"""
p0 = np.asarray(p0, dtype='d')
p1 = np.asarray(p1, dtype='d')
points = np.zeros((2,3), dtype='d')
points[0,:p0.size] = p0
points[1,:p1.size] = p1
knots = [0,0,1,1]
return NURBS([knots], points) | 0abf0688a2e7f84322f56b35796d75497f6f65c2 | 30,099 |
def superior():
"""a fixture for lake superior"""
superior = LakeFactory(lake_name="Lake Superior", abbrev="SU")
return superior | db21ff1ffbaf6be91dd8f0907083ee87bc4541de | 30,100 |
def hsv_mask(img, hue_mask, sat_mask, val_mask):
"""
Returns a binary image based on the mask thresholds
:param img: The image to mask
:param hue_mask: Tuple of (hue_min, hue_max)
:param sat_mask: Tuple of (sat_min, sat_max)
:param val_mask: Tuple of (val_min, val_max)
:return: Binary image ... | 194cb97b42850244b601653551d359b2c42caacd | 30,101 |
def convert_parameter_dict_to_presamples(parameters):
"""Convert a dictionary of named parameters to the form needed for ``parameter_presamples``.
``parameters`` should be a dictionary with names (as strings) as keys and Numpy arrays as values. All Numpy arrays should have the same shape.
Returns (numpy s... | f136c9c795ab4c7023e774866c061b19488cc81f | 30,102 |
def convert_to_rle(annotation, width, height):
"""Convert complex polygons to COCO RLE format.
Arguments:
annotation: a dictionary for an individual annotation in Darwin's format
Returns: an annotation in encrypted RLE format and a bounding box
@author Dinis Gokaydin <d.gokaydin@nationaldrones.... | a9562e95817585798164a91ef793841143329dd7 | 30,103 |
import socket
def getfqdn(name=None):
"""return (a) local IPv4 or v6 FQDN (Fully Qualified Domain Name)
if name is not given, returns local hostname
may raise socket.gaierror"""
return _getfqdn(socket.AF_UNSPEC, name) | cbebf1e3deda3a095996034b559af8f2ae4692c3 | 30,104 |
def create_answer_dict(elem, restrict_elem=None, checkbox=False):
"""
Construct dict with choices to fulfil form's div attribute
:param elem: ElemntTree element
:param restrict_elem: name of element which is not included in choice text
:param checkbox: boolean flag to work return data for checkbox ... | c87d5d22b3f779f4645263ae18febaa95984d614 | 30,105 |
def fasta(file_allname: str):
"""
需要传入file_allname的路径
:param file_allname:
:return: 返回fasta格式的序列list
"""
try:
# file_allname = input("输入你要分析出的文件,包括后缀名\n")
f = open(file_allname).read()
fasts = f.split(">")
fast_seq = []
index = 0
for fast in fasts:... | bbd03531a7d311c322fdbd66e401788fb6526120 | 30,106 |
def ask_version(version):
""" interact with user to determine what to do"""
upgrades = get_upgrades()
latest = get_latest(version, upgrades)
answer = False
if latest > version:
msg = "a new version (%s) is available. You have %s. Upgrade?" % (latest, version)
answer = True if raw_inp... | 1e6c7c87eeb4e222efd2b952e9d23b7c95275f85 | 30,107 |
def format_size(size):
"""
:param float size:
:rtype: str
"""
size = float(size)
unit = 'TB'
for current_unit in ['bytes', 'KB', 'MB', 'GB']:
if size < 1024:
unit = current_unit
break
size /= 1024
return '{0:.2f}'.format(size).rstrip('0').rstrip('... | 95470360fcc34df5a51a7cf354138413b41940aa | 30,108 |
def make_full_block_header_list(block_header):
"""Order all block header fields into a list."""
return make_short_block_header_list(block_header) + [
block_header.timestamp,
block_header.extraData,
] | 59bcfdd3cefd3a1b7a8dcaf063964eb27dbafd67 | 30,109 |
def rc_seq(seq=""):
"""Returns the reverse compliment sequence."""
rc_nt_ls = []
rc_dict = {
"a": "t",
"c": "g",
"t": "a",
"g": "c",
"n": "n",
"A": "T",
"C": "G",
"T": "A",
"G": "C",
"N": "N"
}
rc_nt_ls = [rc_dict[seq[i]... | 827877a76d4ffbe61e40e4f00641afa4277f3ff5 | 30,111 |
def descriptions(path, values):
"""Transform descriptions."""
if not values:
return
root = E.descriptions()
for value in values:
elem = E.description(
value['description'], descriptionType=value['descriptionType']
)
set_non_empty_attr(elem, '{xml}lang', value... | 34d570f0c2a97616833af5432ed5607413e2af9a | 30,112 |
from typing import Mapping
from typing import Union
from typing import Sequence
from typing import Optional
from typing import Any
def build_default_region_dataset(
metrics: Mapping[FieldName, Union[Sequence[float], TimeseriesLiteral]],
*,
region=DEFAULT_REGION,
start_date="2020-04-01",
static: Op... | 4c50876817b80ae412a193ba078b7948b7603322 | 30,113 |
def load_espnet_model(model_path):
"""Load an end-to-end model from ESPnet.
:param model_path: Path to the model.
:type model_path: str
:return: The model itself, mapping from subword to index,
and training arguments used.
:rtype: (torch.nn.Module, dict, dict)
"""
model, train_... | d9f001a64465547cf27c6d600939e57e9b8f1a19 | 30,115 |
from typing import Iterator
from typing import Union
from typing import Match
def full_match(nfa: NFA, text: Iterator[str]) -> Union[Match, None]:
"""
:param nfa: a NFA
:param text: a text to match against
:return: match or ``None``
"""
text_it = _peek(text, sof='', eof='')
curr_states_s... | 9cbb30633f648405e193f61f46b5e2dd80fffde0 | 30,116 |
def smiles_tokenizer(line, atoms=None):
"""
Tokenizes SMILES string atom-wise using regular expressions. While this
method is fast, it may lead to some mistakes: Sn may be considered as Tin
or as Sulfur with Nitrogen in aromatic cycle. Because of this, you should
specify a set of two-letter atoms ex... | c31916558fdbeda345a0667b43364f8bff504840 | 30,117 |
from typing import Set
def merge_parameter_sets(first: Set[ParameterDefinition], second: Set[ParameterDefinition]) -> Set[ParameterDefinition]:
"""
Given two sets of parameter definitions, coming from different dependencies for example, merge them into a single set
"""
result: Set[ParameterDefinition]... | 4b60ae17eb6e8b1ccd5149517c9d0ae809c33411 | 30,118 |
import struct
def build_udp_header(src_port, dst_port, length):
"""Builds a valid UDP header and returns it
Parameters:
- src_port: A uint16 which will be used as source port for the UDP
header
- dst_port: A uint16 which will be used as destination port for the
... | d110c19ff38f88bc892ecb52c8203e356a930bab | 30,120 |
def plot_confus_mat(y_true, y_pred, classes_on=None,
normalize='true',
linewidths=0.02, linecolor='grey',
figsize: tuple = (4, 3),
ax=None, fp=None,
**kwargs):
""" by default, normalized by row (true classes)
"""... | 59ef04547b4829d7c3c1049c93fab69faaa3b23d | 30,121 |
async def home():
"""
Home endpoint to redirect to docs.
"""
return RedirectResponse("/docs") | 1ebece9db1a86f54ec101037279087065aaa2f0a | 30,123 |
def robust_hist(x, ax=None, **kwargs):
"""
Wrapper function to `plt.hist` dropping values that are not finite
Returns:
Axes
"""
mask = np.isfinite(x)
ax = ax or plt.gca()
ax.hist(x[mask], **kwargs)
return ax | 32165e3e5cb796fe941bc0f177606dbc502c61ef | 30,124 |
def base36encode(number, alphabet='0123456789abcdefghijklmnopqrstuvxxyz'):
"""Convert positive integer to a base36 string."""
if not isinstance(number, (int, long)):
raise TypeError('number must be an integer')
# Special case for zero
if number == 0:
return alphabet[0]
base36 = ''
... | d670a047d210f1d452d2acde76dc47208be2f4bf | 30,126 |
def pipe(*args, **kwargs):
"""A source that builds a url.
Args:
item (dict): The entry to process
kwargs (dict): The keyword arguments passed to the wrapper
Kwargs:
conf (dict): The pipe configuration. Must contain the key 'base'. May
contain the keys 'params' or 'path'... | a9fca4149bca2ee50ffe5efcbb67c3066523cdf8 | 30,127 |
import six
def get_rotation(rotation):
"""
Return the text angle as float. The returned
angle is between 0 and 360 deg.
*rotation* may be 'horizontal', 'vertical', or a numeric value in degrees.
"""
try:
angle = float(rotation)
except (ValueError, TypeError):
isString = is... | 7ed0fd31f9a90ddb5743faa8e45e46f0d5cc08bd | 30,128 |
def checkWrite(request):
"""Check write"""
try:
_path = request.query_params.get("path")
_file = open(_path + "test.txt", "w")
_file.write("engine write test")
_file.close()
return HttpResponse(_path + "test.txt")
except ValueError as e:
return genericApiExce... | c3d196126c67cc9b8ba5482a4ebb7df778cd1d5e | 30,129 |
def most_seen_creators(event_kind=None, num=10):
"""
Returns a QuerySet of the Creators that are associated with the most Events.
"""
return Creator.objects.by_events(kind=event_kind)[:num] | 60d4865b56ea2d2ede8cad5123fbaa3f49e72bcd | 30,130 |
def read_lexicon():
"""
Returns the dict of {'word': string, 'score': int} represented by lexicon.txt
"""
return read_dict('resources/lexicon.txt') | 69cdf729aabfd42d4e02690cabcd91b1162598aa | 30,133 |
import tqdm
def show_erps(Ds, align_window, labels=None, show_sem=True, co_data=None,
**kwargs):
"""
Use plot ERPs on electrode_grid
Parameters
----------
Ds: list
list of D tensors (electrodes x time x trials)
align_window: tuple
time before and after stim in se... | 988a89af259387796e3735ce9526304591c09131 | 30,135 |
def insert_with_key_enumeration(agent, agent_data: list, results: dict):
"""
Checks if agent with the same name has stored data already in the given dict and enumerates in that case
:param agent: agent that produced data
:param agent_data: simulated data
:param results: dict to store data into
:... | d2d653dcff20836c4eaf8cf55b31b1a1209a4ddd | 30,136 |
def parse_condition_code(value, is_day: bool) -> str:
"""Convert WeatherAPI condition code to standard weather condition."""
if value is None:
return None
try:
condition_code = int(value)
if condition_code == 1000:
return ATTR_CONDITION_SUNNY if is_day else ATTR_CONDITI... | cd650a27b907f6d0ced7c05bd8aec5a316bf3b42 | 30,138 |
def min__to__s():
"""Convert minute to second"""
return '6.0E+1{kind}*{var}' | 2730af2cc79a6c4af6d1b18f79326623c0fd0289 | 30,139 |
import html
def home():
"""Home tab."""
icon = html.I(className="fas fa-home fa-lg", title="Home")
return html.Li(html.Span(icon), id="view-info", className="active") | f1771b014b3d0332965b4bb0d74038dfddda8c21 | 30,140 |
def score_per_term(base_t, mis_t, special_t, metric):
"""Computes three distinct similarity scores for each list of terms.
Parameters
----------
base_t, mismatch_t special_t: list of str
Lists of toponym terms identified as base, mismatch or frequent (special) respectively.
metric: str
... | 55e5b9b0d9feaa359ab0907b399eb37514dcfacd | 30,141 |
import bisect
def _eliminationOrder_OLD(gm, orderMethod=None, nExtra=-1, cutoff=inf, priority=None, target=None):
"""Find an elimination order for a graphical model
Args:
gm (GraphModel): A graphical model object
method (str): Heuristic method; one of {'minfill','wtminfill','minwidth','wtminwidth','random... | dfe770db099dc65bcba1afb8c2706005dd7bb81d | 30,142 |
import torch
def get_pretrain_data_loader(mode, pretrain_data_setting):
"""Get pre-training loader.
Args:
mode (str): either "train" or "valid".
pretrain_data_setting (dict, optional): pretrain dataset setting.
Returns:
loader (torch.dataloader): a PyTorch dataloader with all input
d... | dc894eb5fb41cf49910568d01a749ebc93aded6d | 30,144 |
def do_simple_math(number1, number2, operator):
"""
Does simple math between two numbers and an operator
:param number1: The first number
:param number2: The second number
:param operator: The operator (string)
:return: Float
"""
ans = 0
if operator is "*":
ans = number1 * nu... | eb745f9c3f3c1e18de30cbe6c564d68c29e39ff4 | 30,145 |
def test_global_settings_data():
"""Ensure that GlobalSettingsData objects are properly initialized
per-thread"""
def check_initialized(index):
if index == 0:
sleep(0.1)
with pytest.raises(AttributeError):
_global_settings_data.testing_index # pylint: disable=W0104
... | bd1229bb9150b25c88be621d5af0f8da9cf7327d | 30,146 |
def set_client(client):
"""
Set the global HTTP client for sdk.
Returns previous client.
"""
global _global_client
previous = _global_client
_global_client = client
return previous | 9f29f5491cee42581fb2b0a22edd36a2297754b4 | 30,147 |
def readNetAddress(b, hasStamp):
"""
Reads an encoded NetAddress from b depending on the protocol version and
whether or not the timestamp is included per hasStamp. Some messages like
version do not include the timestamp.
Args:
b (ByteArray): The encoded NetAddress.
hasStamp (bool)... | 7d523c0465039008e0015c075e8282a1aacea000 | 30,148 |
def get_all_clouds(session, return_type=None, **kwargs):
"""
Retrieves details for all available storage clouds.
:type session: zadarapy.session.Session
:param session: A valid zadarapy.session.Session object.
:type return_type: str
:param return_type: If this is set to the string 'json', this... | 61029884408733398d8e2c3bb52c18ef4e9f83fc | 30,149 |
def _get_account_balances_by_regid(user_regid):
"""
returns uw_sws.models.Finance object for a given regid
"""
if user_regid is None:
return None
return get_account_balances_by_regid(user_regid) | 6c81ca23411a415d3551d856a44c44f6377ec1b9 | 30,150 |
def make_embed(msg_type='', title=None, icon=None, content=None,
msg_colour=None, guild=None, title_url=None,
thumbnail='', image='', fields=None, footer=None,
footer_icon=None, inline=False):
"""Returns a formatted discord embed object.
Define either a type or a co... | 5cdeb5862ffc525160361f760b5530e15d3258c1 | 30,153 |
import torch
def dynamic_stitch(indices, data):
"""
Args
indices: A list of at least 1 Tensor objects with type int32.
data: A list with the same length as indices of Tensor objects with
the same type.
Returns
A Tensor. Has the same type as data.
"""
dim_0 = in... | 6988b400ca1110187643eba932f00103f5f393b6 | 30,154 |
def snake(string):
"""snake_case"""
return "_".join(string.split()) | 6bf99dede918937ad59ec9be14ffade8fadb5794 | 30,155 |
def parse_standard_metadata():
"""
Gather the standard metadata information from Jenkins and the DBMS.
Returns
-------
The metadata obtained from Jenkins and the DBMS.
Warnings
--------
Underlying implementation is hacky right now.
"""
return {**_parse_jenkins_env_vars(), **_pa... | 535bc56eabbdc2d178b448951127adf37af217eb | 30,156 |
def match_all_args(ctx, node, func, args):
"""Call match_args multiple times to find all type errors.
Args:
ctx: The abstract context.
node: The current CFG node.
func: An abstract function
args: An Args object to match against func
Returns:
A tuple of (new_args, errors)
where new_args... | 88bd473876dd3a286c02330023555dab211336df | 30,158 |
import torch
def samples_from_cpprb(npsamples, device=None):
"""
Convert samples generated by cpprb.ReplayBuffer.sample() into
State, Action, rewards, State.
Return Samples object.
Args:
npsamples (dict of nparrays):
Samples generated by cpprb.ReplayBuffer.sample()
devi... | 6775f0eee7544f35e04e6e6fd3096516411dc0e8 | 30,159 |
def generateKeys():
"""
generates and returns a dictionary containing the original columns names from the
LIDAR file as values and the currently used column names as corresponding keys
ws_1 : Speed Value.1
dir_1 : Direction Value.1
h_1 : Node RT01 Lidar Height
"""
keys = {"ws_0" :... | 9d0d55c3fdc32ddda46da4a9e876d4ce1ecde25d | 30,160 |
def process_line(line):
"""Return the syntax error points of line."""
stack = []
for c in line:
if c in '([{<':
stack.append(c)
elif c != closings[stack.pop()]:
return points[c]
return 0 | 4ab64c74d89f950cc6c87b7a91addeb29717d74a | 30,161 |
def get_uniprot_homologs(rev=False):
"""As above, but exclusively uniprot => mouse uniprot"""
homologs = {}
with open('data/corum_mouse_homologs.txt') as infile:
data = [line.strip().split('\t') for line in infile]
for line in data:
original = line[1].split('|')[1]
uniprot = line... | 969085375265b90b5501b4b86eaaed3e1c48795f | 30,162 |
import typing
def flatten(
value: list,
levels: typing.Optional[int] = None
) -> list:
"""Flatten a list.
.. code-block:: yaml
- vars:
new_list: "{{ [1, 2, [3, [4, 5, [6]], 7]] | flatten }}"
# -> [1, 2, 3, 4, 5, 6, 7]
To flatten only the top level, use the ``leve... | 569ccb15f140a517792bc6b5ea962537db0b31f8 | 30,163 |
def GetStage(messages):
"""Returns corresponding GoogleCloudFunctionsV2(alpha|beta)Stage."""
if messages is apis.GetMessagesModule(_API_NAME, _V2_ALPHA):
return messages.GoogleCloudFunctionsV2alphaStage
elif messages is apis.GetMessagesModule(_API_NAME, _V2_BETA):
return messages.GoogleCloudFunctionsV2bet... | 3bdb130cf78694b223bd555f6db20e1c687b5552 | 30,164 |
def get_general_case_info(adapter, institute_id=None, slice_query=None):
"""Return general information about cases
Args:
adapter(adapter.MongoAdapter)
institute_id(str)
slice_query(str): Query to filter cases to obtain statistics for.
Returns:
general(dict)
"""
g... | a5afc2244db59f7a3dd0da55dd4759a57af641a4 | 30,165 |
def _normalize_ids(arg, atoms={int, long, str, unicode, NewId}):
""" Normalizes the ids argument for ``browse`` (v7 and v8) to a tuple.
Various implementations were tested on the corpus of all browse() calls
performed during a full crawler run (after having installed all website_*
modules) and this one... | 1a7b930896a046357474000b8ebc598f70fbba76 | 30,166 |
def is_intersection(g, n):
"""
Determine if a node is an intersection
graph: 1 -->-- 2 -->-- 3
>>> is_intersection(g, 2)
False
graph:
1 -- 2 -- 3
|
4
>>> is_intersection(g, 2)
True
Parameters
----------
g : networkx DiGraph
n : node id
R... | 415e5154095cd78112ef029b6c4d62c36da0b3b8 | 30,167 |
def AxisRotation(p, ang, inplace=False, deg=True, axis='z'):
""" Rotates points p angle ang (in deg) about an axis """
axis = axis.lower()
# Copy original array to if not inplace
if not inplace:
p = p.copy()
# Convert angle to radians
if deg:
ang *= np.pi / 180
if axis == ... | 1df385b98edb69134849cb052380fb99261f96b2 | 30,168 |
from pathlib import Path
from typing import List
def get_dir_list(path: Path)->List[str]:
"""
Return directory list
"""
dir_list = []
paths = Path(path).glob("**/*")
for p in paths:
if p.is_dir():
dir_list.append(str(p))
return dir_list | a0fe0659ad0175364048be6ef96026584fa6f3ef | 30,169 |
import typing
def tokenize(data: typing.Union[str, typing.Sequence[str]]) -> list[str]:
"""break up string into tokens, tokens can be separated by commas or spaces
creates separate tokens for:
- "(" or "[" at beginning
- ")" or "]" at end
"""
# break into tokens
if isinstance(data, str):... | 832343067c8777aa386c0c87c2c4e8202a7cb88f | 30,170 |
def de_comma(string):
"""Remove any trailing commas
>>> de_comma(',fred,,') == ',fred'
True
"""
return string.rstrip(',') | 453d615c1fbbef5139d05d6e4510731c969d6a86 | 30,171 |
def MakeData(ea, flags, size, tid):
"""
Create a data item at the specified address
@param ea: linear address
@param flags: FF_BYTE..FF_PACKREAL
@param size: size of item in bytes
@param tid: for FF_STRU the structure id
@return: 1-ok, 0-failure
"""
return idaapi.do_data_ex(ea, fla... | ab890848784407bf0ee2864469a5c8874346c5ec | 30,172 |
def get_node_network_receive(cluster_id, ip, start, end, bk_biz_id=None):
"""获取网络数据
start, end单位为毫秒，和数据平台保持一致
数据单位KB/s
"""
step = (end - start) // 60
prom_query = f"""
max(rate(node_network_receive_bytes_total{{cluster_id="{cluster_id}",job="node-exporter", instance=~"{ ip }:9100"}}[5m])... | 9ba68d19c6ca959fd92020f50498d4aa14dfeb58 | 30,173 |
def verify_vrrpv3_summary(dut,**kwargs):
"""
Author: Raghukumar Rampur
email : raghukumar.thimmareddy@broadcom.com
:param dut:
:param interface:
:type string or list
:param vrid:
:type string or list
:param vip:
:type virtual-ip in string or list
:param state:
:type vrrp ... | b5d9ae54fc316cadfd8c4d067439b19ecac4c371 | 30,174 |
def attributes_restore(node):
"""Restore previously unlocked attributes to their default state.
Args:
node (str): Node to restore attributes
Returns:
bool: False if attribute doesn't exists else True
"""
attr_name = "attributes_state"
base_attr = "{}.{}".format(node, attr_nam... | 8c598518d7df1bcc88cbbb3c48d34fecd41b0487 | 30,175 |
import pickle
def get_actual_data(base, n_run, log_path, subfolders):
"""
:param base: the sub folder name right before the _DATE_InstanceNumber
:param n_run: the INSTANCE number in the subfolder name
:param log_path: path to the main log folder containing all the runs of an experiment (e.g. ../data/C... | b9f76b14b90e3c187e19bcd0b8bbbfe865518fe7 | 30,176 |
def secs_to_str(secs):
"""Given number of seconds returns, e.g., `02h 29m 39s`"""
units = (('s', 60), ('m', 60), ('h', 24), ('d', 7))
out = []
rem = secs
for (unit, cycle) in units:
out.append((rem % cycle, unit))
rem = int(rem / cycle)
if not rem:
break
if re... | 0918fd72fbaaa0adf8fe75bcb1ef39b4e9aba75b | 30,177 |
def shuffle(xsets, ysets, seed=None):
"""Shuffle two datasets harmonically
Args:
x, y: datasets, both of them should have same length
Return:
(shuffled_x, shuffled_y): tuple including shuffled x and y
"""
if len(xsets) != len(ysets):
raise ValueError
np.random.seed(seed=s... | 0d07fa7b1d556a5af0bb4f3d174326c756d3d6a7 | 30,178 |
import math
def get_CL_parameters(file_pointer, class_10_100_1000):
""" Function to predict cluster count and mean size by means of clustering
Args:
file_pointer: string with a file path
Returns
tuple with(
clusters: predicted number of clusters
log_me... | 498bf2e3b6a1e70808b159e2b630d9cdb8cebc40 | 30,179 |
def _nanclean(cube, rejectratio=0.25, boxsz=1):
"""
Detects NaN values in cube and removes them by replacing them with an
interpolation of the nearest neighbors in the data cube. The positions in
the cube are retained in nancube for later remasking.
"""
logger.info('Cleaning NaN values in the c... | 154bf994161a932505101ccbe921792e2d3c9f3b | 30,180 |
import json
def parseData(filePath):
"""
Tries to import JSON JobShop PRO file to program
:return machineList itinerariesList
"""
machinesList = []
itinerariesList = []
with open(filePath, 'r', encoding="utf8") as inputfile: # read file from path
importedData = json.loads(inputf... | b02471737e320eb35c4c9626c11737952455f18e | 30,181 |
def curve_fit_log(xdata, ydata, sigma):
"""Fit data to a power law with weights according to a log scale"""
# Weights according to a log scale
# Apply fscalex
xdata_log = np.log10(xdata)
# Apply fscaley
ydata_log = np.log10(ydata)
sigma_log = np.log10(sigma)
# Fit linear
popt_lo... | f00484c2e520e8060d7cb29ea503170c2e6ff07d | 30,182 |
def get_computed_response_text_value(response):
"""
extract the text message from the Dialogflow response, fallback: None
"""
try:
if len(response.query_result.fulfillment_text):
return response.query_result.fulfillment_text
elif len(response.query_result.fulfillment_mes... | fa7410ac4b0ef2c0dea59b0e9d001a7893a56479 | 30,183 |
def tmpdir_factory(request):
"""Return a :class:`_pytest.tmpdir.TempdirFactory` instance for the test session.
"""
return request.config._tmpdirhandler | cb506efaef55275d30755fc010d130f61b331215 | 30,184 |
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