content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
async def post_user(ctx: Context, user: MemberOrUser) -> t.Optional[dict]:
"""
Create a new user in the database.
Used when an infraction needs to be applied on a user absent in the guild.
"""
log.trace(f"Attempting to add user {user.id} to the database.")
payload = {
'discriminator': ... | 25a6a710d7d94cc9837d9d67408a09fd6ff48596 | 4,066 |
from typing import List
def delete(ids: List = Body(...)):
"""
Deletes from an embeddings index. Returns list of ids deleted.
Args:
ids: list of ids to delete
Returns:
ids deleted
"""
try:
return application.get().delete(ids)
except ReadOnlyError as e:
ra... | 9075db7c7dd174b850d1d4acbe1cdb4001162b5d | 4,067 |
def main():
""" Simple Event Viewer """
events = None
try:
events = remote('127.0.0.1', EventOutServerPort, ssl=False, timeout=5)
while True:
event_data = ''
while True:
tmp = len(event_data)
event_data += events.recv(numb=8192, timeout=1).decode('latin-1')
if tmp == len(event_data):
bre... | d96500a3114785dbb408681e96d7ffb7a5c59d04 | 4,068 |
def fsi_acm_up_profiler_descending(vp1, vp2, vp3):
"""
Description:
Calculates the VEL3D Series A and L upwards velocity data product VELPTMN-VLU-DSC_L1
for the Falmouth Scientific (FSI) Acoustic Current Meter (ACM) mounted on a McLane
profiler.
Because of the orientation of th... | e176ff1b23bf4b5624cdc8a698d03c8d2ee1947a | 4,069 |
from typing import Tuple
def colour_name(colour: Tuple[int, int, int]) -> str:
"""Return the colour name associated with this colour value, or the empty
string if this colour value isn't in our colour list.
>>> colour_name((1, 128, 181))
'Pacific Point'
>>> colour_name(PACIFIC_POINT)
'Pacific... | e596bf802b8f168e6c8d9bd9b8e4113b61e7fd58 | 4,070 |
def score_fn(subj_score, comp_score):
"""
Generates the TextStim with the updated score values
Parameters
----------
subj_score : INT
The subjects score at the moment
comp_score : INT
The computer's score at the moment'
Returns
-------
score_stim : psychopy.visual.t... | 2d52b4c8d47543c6c1c98e5aa7feb8c3341ff7a4 | 4,071 |
def parse_write_beam(line):
"""
Write_beam (type -2)
If btype = −2, output particle phase-space coordinate information at given location V3(m)
into filename fort.Bmpstp with particle sample frequency Bnseg. Here, the maximum number
of phase- space files which can be output is 100. Here, 40 and ... | 7ce86ae39a51ea8d4636e37bea26edd3caae19e8 | 4,072 |
def get_tone(pinyin):
"""Renvoie le ton du pinyin saisi par l'utilisateur.
Args:
pinyin {str}:
l'entrée pinyin par l'utilisateur
Returns:
number/None :
Si pas None, la partie du ton du pinyin (chiffre)
"""
# Prenez le dernier chaine du pinyin
tone = pin... | fc0b02902053b3f2470acf952812573f5125c4cf | 4,073 |
def authIfV2(sydent, request, requireTermsAgreed=True):
"""For v2 APIs check that the request has a valid access token associated with it
:returns Account|None: The account object if there is correct auth, or None for v1 APIs
:raises MatrixRestError: If the request is v2 but could not be authed or the user... | 6c3f60df233cc030dfc3ec2658bd2a70c5a20aed | 4,074 |
def gen_rho(K):
"""The Ideal Soliton Distribution, we precompute
an array for speed
"""
return [1.0/K] + [1.0/(d*(d-1)) for d in range(2, K+1)] | 40382af047d0f2efba0eb6db17c28b92e47d3c92 | 4,075 |
import numpy as np
def assert_array_max_ulp(a, b, maxulp=1, dtype=None):
"""
Check that all items of arrays differ in at most N Units in the Last Place.
Parameters
----------
a, b : array_like
Input arrays to be compared.
maxulp : int, optional
The maximum number of units in t... | 8ca9698e5b213f753002535061b17aeb59f12e83 | 4,076 |
def Ambient_Switching(crop_PPFDmin, Trans, consumption):
"""
Inputs: consumption (returned from Light_Sel)
"""
#How much energy can you save if you switch off when ambient lighting is enough for plant needs?
#Assume that when ambient is higher than max recommended PPFD, that the greenhouse is cloaked, allowin... | 5a8ab9d6eb0c6b3ddd7bb3f7efb1599b952aa345 | 4,077 |
from typing import Callable
def get_numerical_gradient(position: np.ndarray, function: Callable[[np.ndarray], float],
delta_magnitude: float = 1e-6) -> np.ndarray:
""" Returns the numerical derivative of an input function at the specified position."""
dimension = position.shape[0]
... | a439acd3934006e2b8f9188e3204e12ef3885ae5 | 4,078 |
def stable_point(r):
"""
repeat the process n times to
make sure we have reaches fixed points
"""
n = 1500
x = np.zeros(n)
x[0] = np.random.uniform(0, 0.5)
for i in range(n - 1):
x[i + 1] = f(x[i], r)
print(x[-200:])
return x[-200:] | 9d9c32abfb0fea74abb32ec8cebd8c76738669b1 | 4,080 |
def vary_on_headers(*headers):
"""
A view decorator that adds the specified headers to the Vary header of the
response. Usage:
@vary_on_headers('Cookie', 'Accept-language')
def index(request):
...
Note that the header names are not case-sensitive.
"""
def decorator(fu... | 9892ac00aa31b0e294f79b2d1539d6d79f3eaed7 | 4,081 |
def non_daemonic_process_pool_map(func, jobs, n_workers, timeout_per_job=None):
"""
function for calculating in parallel a function that may not be run
a in a regular pool (due to forking processes for example)
:param func: a function that accepts one input argument
:param jobs: a list of input arg... | 41fbdaae1e584839692eae4d5034ffd6828eb5c7 | 4,083 |
import random
import textwrap
from datetime import datetime
def result_list_handler(*args: list, **kwargs) -> str:
"""
Handles the main search result for each query. It checks whether there are any result for this qeury or not.
1. If there was results, then it sorts and decorates the them.
2 O... | c0fb0db46e3c47d24b06c290ba9d0129eb436edf | 4,084 |
def flip_mask(mask, x_flip, y_flip):
"""
Args:
mask: バイナリマスク
[height, width]
"""
mask = mask.copy()
if y_flip:
mask = np.flip(mask, axis=0)
if x_flip:
mask = np.flip(mask, axis=1)
return mask | d3d783fb3e5913448f4e9d06f1f96d89559a686c | 4,085 |
def sbn2journal(sbn_record, permalink_template="http://id.sbn.it/bid/%s"):
"""
Creates a `dbmodels.Journal` instance out of a dictionary with metadata.
:param record: the dictionary returned by `resolution.supporting_functions.enrich_metadata()`
:return: an instance of `dbmodels.Journal`
"""
bi... | 059b00aeb81dd1bdbc987f31c045b6eb5aedc3b3 | 4,086 |
def median(data):
"""Calculates the median value from |data|."""
data = sorted(data)
n = len(data)
if n % 2 == 1:
return data[n / 2]
else:
n2 = n / 2
return (data[n2 - 1] + data[n2]) / 2.0 | ad2b3f7eb3f5446c81c6c400bc16c7833e75c05c | 4,087 |
from typing import Optional
def split_text_by_length(text: str,
length: Optional[int] = None, # 方案一：length + delta
delta: Optional[int] = 30,
max_length: Optional[int] = None, # 方案二：直接确定长度上下限
min_length: Optional[int... | 60bf713a2cbe3eff85237d9637a303668a9f436b | 4,089 |
def _tfidf_fit_transform(vectors: np.ndarray):
""" Train TF-IDF (Term Frequency — Inverse Document Frequency)
Transformer & Extract TF-IDF features on training data
"""
transformer = TfidfTransformer()
features = transformer.fit_transform(vectors).toarray()
return features, transformer | c38aa629d11258291f306052ac0e4c9c2a474ebd | 4,090 |
from typing import List
def _is_missing_sites(spectra: List[XAS]):
"""
Determines if the collection of spectra are missing any indicies for the given element
"""
structure = spectra[0].structure
element = spectra[0].absorbing_element
# Find missing symmeterically inequivalent sites
symm_s... | 0ae7ad0622e8ec398306e05def214b0ad40fd90f | 4,091 |
def get_objects(params, meta):
"""
Retrieve a list of objects based on their upas.
params:
guids - list of string - KBase IDs (upas) to fetch
post_processing - object of post-query filters (see PostProcessing def at top of this module)
output:
objects - list of ObjectData - see t... | 17d38a1a5e09847700537076c0bfefdd55947682 | 4,092 |
def parseMidi(midifile):
"""Take a MIDI file and return the list Of Chords and Interval Vectors.
The file is first parsed, midi or xml. Then with chordify and
PC-Set we compute a list of PC-chords and Interval Vectors.
"""
mfile = ms.converter.parse(midifile)
mChords = mfile.chordify()
chor... | 8c803c297eee5cc29a78d6c8b864a85e8bfd3d52 | 4,095 |
def get_similarity(s1, s2):
"""
Return similarity of both strings as a float between 0 and 1
"""
return SM(None, s1, s2).ratio() | 3964670a69a135fbc6837e9c68a2e7ac713d67dc | 4,096 |
from typing import Union
from typing import Sequence
from re import T
def concrete_values_from_iterable(
value: Value, ctx: CanAssignContext
) -> Union[None, Value, Sequence[Value]]:
"""Return the exact values that can be extracted from an iterable.
Three possible return types:
- ``None`` if the arg... | 3acdda92df4e27d4eecf39630570b90049580d6d | 4,097 |
def quat_conjugate(quat_a):
"""Create quatConjugate-node to conjugate a quaternion.
Args:
quat_a (NcNode or NcAttrs or str or list or tuple): Quaternion to
conjugate.
Returns:
NcNode: Instance with quatConjugate-node and output-attribute(s)
Example:
::
... | 2bff8b1e472ad2975ba96084843004ce86205f9f | 4,099 |
def askfont():
"""
Opens a :class:`FontChooser` toplevel to allow the user to select a font
:return: font tuple (family_name, size, \*options), :class:`~font.Font` object
"""
chooser = FontChooser()
chooser.wait_window()
return chooser.font | 8bce830a24d92be38c23ba09b6754f2e6cc6d161 | 4,100 |
def load_data(train_file, test_file):
"""
The method reads train and test data from their dataset files.
Then, it splits train data into features and labels.
Parameters
----------
train_file: directory of the file in which train data set is located
test_file: directory of the file in which ... | d830f4bcd3efe467a23cab0dfa4a3cdb4694559e | 4,101 |
def guide(batch_X, batch_y=None, num_obs_total=None):
"""Defines the probabilistic guide for z (variational approximation to posterior): q(z) ~ p(z|x)
"""
# we are interested in the posterior of w and intercept
# since this is a fairly simple model, we just initialize them according
# to our prior b... | 889f3224424496a4f001d81b046e1279ba0efe77 | 4,103 |
def get_reddit_tables():
"""Returns 12 reddit tables corresponding to 2016"""
reddit_2016_tables = []
temp = '`fh-bigquery.reddit_posts.2016_{}`'
for i in range(1, 10):
reddit_2016_tables.append(temp.format('0' + str(i)))
for i in range(10, 13):
reddit_2016_tables.append(temp.format(... | e590ab35becbe46aa220257f6629e54f720b3a13 | 4,105 |
def first_empty():
"""Return the lowest numbered workspace that is empty."""
workspaces = sorted(get_workspace_numbers(get_workspaces().keys()))
for i in range(len(workspaces)):
if workspaces[i] != i + 1:
return str(i + 1)
return str(len(workspaces) + 1) | f9c9f868570bbcc15a28097930d304b308ddf452 | 4,106 |
def get_local_tzone():
"""Get the current time zone on the local host"""
if localtime().tm_isdst:
if altzone < 0:
tzone = '+' + \
str(int(float(altzone) / 60 // 60)).rjust(2,
'0') + \
str(int(float(
... | dec1d9f9c5ecf937779de55a33397436841913bc | 4,108 |
def subscribers_tables_merge(tablename1: Tablename, tablename2: Tablename, csv_path=csvpath, verbose=True):
"""
Сводит таблицы, полученные загрузчиком, в одну. Может принимать pandas.DataFrame или имя группы, в этом
случае группа должна быть в списке групп, а соответствующий файл - в <csv_path>
"""
... | 56c5c80b57aa4103f1836f8b9a5ca7bbb67e25bc | 4,109 |
def get_current_offset(session):
"""
For backfilling only, this function works with the init container to look up
it's job_id so it can line that up with it's consumer group and offest so that
we can backfill up to a given point and then kill the worker afterwards.
"""
if settings.JOB_ID is None... | 97d0b0485005a709a047582667f56a79f636388d | 4,110 |
def get_params(p1, p2, L):
"""
Return the curve parameters 'a', 'p', 'q' as well as the integration
constant 'c', given the input parameters.
"""
hv = p2 - p1
m = p1 + p2
def f_bind(a): return f(a, *hv, L)
def fprime_bind(a): return fprime(a, hv[0])
# Newton-Raphson algorithm to fin... | eae7d942b4272b3addc6c3f3912abc564e93f339 | 4,111 |
def _unpack(f):
"""to unpack arguments"""
def decorated(input):
if not isinstance(input, tuple):
input = (input,)
return f(*input)
return decorated | 245d425b45d9d7ef90239b791d6d65bcbd0433d5 | 4,112 |
from .ops.classes import WriteRichOp
from typing import Iterable
from functools import reduce
def chain_rich(iterable: Iterable['WriteRichOp']) -> 'WriteRichOp':
"""Take an `iterable` of `WriteRich` segments and combine them to produce a single WriteRich operation."""
return reduce(WriteRichOp.then, iterable... | fa75ab929fb01b9c68e58938aa04aebddc26f245 | 4,113 |
def sum_plot_chi2_curve(bin_num, sum_bin, r_mpc, ax=None, cov_type='bt', label=None,
xlabel=True, ylabel=True, show_bin=True, ref_sig=None):
"""Plot the chi2 curve."""
if ax is None:
fig = plt.figure(figsize=(6, 6))
fig.subplots_adjust(
left=0.165, bottom=0.13... | 6f0b7adf2daa98ecac9ff722eab9f6b748ef188b | 4,114 |
import dfim
import dfim.util
def compute_importance(model, sequences, tasks,
score_type='gradient_input',
find_scores_layer_idx=0,
target_layer_idx=-2,
reference_gc=0.46,
reference_shuffle_type=None,
... | a7ebe928f4e3b50d5c8735d438d28c034d5dfeb9 | 4,115 |
from typing import Iterable
def test_check_non_existing() -> None:
"""Test a check on a non-existing column."""
class Schema(pa.SchemaModel):
a: Series[int]
@pa.check("nope")
@classmethod
def int_column_lt_100(cls, series: pd.Series) -> Iterable[bool]:
return seri... | 473b0e1c4b4c785970bdc648e4290426524882c7 | 4,116 |
import requests
def fetch_url(url):
"""Fetches the specified URL.
:param url: The URL to fetch
:type url: string
:returns: The response object
"""
return requests.get(url) | 26198dbc4f7af306e7a09c86b59a7da1a4802241 | 4,117 |
def _nw_score_(s1, s2, insert=lambda c: -2,
delete=lambda c: -2,
substitute=lambda c1, c2: 2 if c1 == c2 else -1):
"""Compute Needleman Wunsch score for aligning two strings.
This algorithm basically performs the same operations as Needleman Wunsch
alignment, but is made more ... | 009c9eb4afec828adde53bddfd2a8b4d2a952c24 | 4,118 |
import pickle
import torch
import re
import warnings
from typing import Counter
from typing import OrderedDict
def load_gisaid_data(
*,
device="cpu",
min_region_size=50,
include={},
exclude={},
end_day=None,
columns_filename="results/usher.columns.pkl",
features_filename="results/usher... | eaa9c5b3735f291706ea783272b3372ad9e7937c | 4,119 |
def get_symbol_size(sym):
"""Get the size of a symbol"""
return sym["st_size"] | b2d39afe39542e7a4e1b4fed60acfc83e6a58677 | 4,120 |
def to_unnamed_recursive(sexpr, scheme):
"""Convert all named column references to unnamed column references."""
def convert(n):
if isinstance(n, NamedAttributeRef):
n = toUnnamed(n, scheme)
n.apply(convert)
return n
return convert(sexpr) | ffb58acb1cfbef654c5c936880961b8cc982ec01 | 4,122 |
def login_process():
"""Process login."""
email_address = request.form.get("email")
password = request.form.get("password")
user = User.query.filter_by(email_address=email_address).first()
if not user:
flash("Please try again!")
return redirect('/')
if user.password != passwor... | afee068b653e5f759329658e3614b0ce7ee2d405 | 4,123 |
def get_doc_translations(doctype, name):
"""
Returns a dict custom tailored for the document.
- Translations with the following contexts are handled:
- doctype:name:docfield
- doctype:name
- doctype:docfield (Select fields only)
- 'Select' docfields will have a values dict which will have
trans... | e7fd896de3162452a77ab989670e61b01e8e35a2 | 4,124 |
def app(request):
"""
Default view for Person Authority App
"""
return direct_to_template(request,
'person_authority/app.html',
{'app':APP}) | 9e75c9cf381c69b19bfdf08c74b2e0dc2106822b | 4,126 |
def is_xbar(top, name):
"""Check if the given name is crossbar
"""
xbars = list(filter(lambda node: node["name"] == name, top["xbar"]))
if len(xbars) == 0:
return False, None
if len(xbars) > 1:
log.error("Matching crossbar {} is more than one.".format(name))
raise SystemExit... | 435b84a30f3f749f07d0cc6dfdd5e7f0c5343c4f | 4,127 |
def index():
""" Root URL response """
return "Reminder: return some useful information in json format about the service here", status.HTTP_200_OK | d8128c8ba8976238c1d68376eaa64a77d09ce525 | 4,128 |
def backproject(depth, K):
"""Backproject a depth map to a cloud map
depth: depth
----
organized cloud map: (H,W,3)
"""
H, W = depth.shape
X, Y = np.meshgrid(np.asarray(range(W)) - K[0, 2], np.asarray(range(H)) - K[1, 2])
return np.stack((X * depth / K[0, 0], Y * depth / K[1, 1], depth)... | 5433fd408932f48c238cad7e5e8d7b14ee7b00de | 4,129 |
from pathlib import Path
def get_parent_dir(os_path: str) -> str:
"""
Get the parent directory.
"""
return str(Path(os_path).parents[1]) | 3a6e518119e39bfbdb9381bc570ac772b88b1334 | 4,130 |
def parse_work_url(work_url):
"""Extract work id from work url
Args:
work_url (str): work url
Returns:
str: bdrc work id
"""
work_id = ""
if work_url:
work_url_parts = work_url.split("/")
work_id = work_url_parts[-1]
return work_id | 1e7f5e222a2f6c7d01cbcb7df556adf6dd33f7cf | 4,132 |
def room():
"""Create a Room instance for all tests to share."""
return Room({"x": 4, "y": 4, "z": 4}, savable=False) | f031faa1bf654ff32868b678f79c2af040926b44 | 4,133 |
import re
def searchLiteralLocation(a_string, patterns):
"""assumes a_string is a string, being searched in
assumes patterns is a list of strings, to be search for in a_string
returns a list of re span object, representing the found literal if it exists,
else returns an empty list"""
results = []
... | 0f751bae801eaee594216688551919ed61784187 | 4,134 |
def UIOSelector_Highlight(inUIOSelector):
"""
Highlight (draw outline) the element (in app) by the UIO selector.
:param inUIOSelector: UIOSelector - List of items, which contains condition attributes
:return:
"""
# Check the bitness
lSafeOtherProcess = UIOSelector_SafeOtherGet_Process(inUI... | 9ab5930396aa9813f09d858c4bb94adc2170f312 | 4,135 |
import torch
def completeMessage_BERT(mod, tok, ind, max_length=50):
"""
Sentence Completion of the secret text from BERT
"""
tokens_tensor = torch.tensor([ind])
outInd = mod.generate(tokens_tensor, max_length=50)
outText=tok.decode(outInd[0].tolist())
newText=outText[len(tok.decode(ind)):]
newText=n... | c2a47bbe90a9e5d222af0bbe5959c82d2ebd2cd3 | 4,136 |
def load_real_tcs():
""" Load real timecourses after djICA preprocessing """
try:
return sio.loadmat(REAL_TC_DIR)['Shat'][0]
except KeyError:
try:
return sio.loadmat(REAL_TC_DIR)['Shat_'][0]
except KeyError:
print("Incorrect key")
pass | 68b148e6fc6088d8ef9f90daf25e07609010d9fe | 4,138 |
def create_fsaverage_forward(epoch, **kwargs):
"""
A forward model is an estimation of the potential or field distribution for a known source
and for a known model of the head. Returns EEG forward operator with a downloaded template
MRI (fsaverage).
Parameters:
epoch: mne.epochs.Epochs
... | 34d72211babf23e41927ebe7df13c58bf6876e4d | 4,139 |
def midi_to_hz(notes):
"""Hello Part 6! You should add documentation to this function.
"""
return 440.0 * (2.0 ** ((np.asanyarray(notes) - 69.0) / 12.0)) | 7215126d25ff969a8aa187c7f49216ec7743a9e9 | 4,141 |
def bond_stereo_parities(chi, one_indexed=False):
""" Parse the bond stereo parities from the stereochemistry layers.
:param chi: ChI string
:type chi: str
:param one_indexed: Return indices in one-indexing?
:type one_indexed: bool
:returns: A dictionary mapping bond keys on... | 02729db6888899a91e69a25dae81c06777b89182 | 4,142 |
def filter_camera_angle(places):
"""Filter camera angles for KiTTI Datasets"""
bool_in = np.logical_and((places[:, 1] < places[:, 0] - 0.27), (-places[:, 1] < places[:, 0] - 0.27))
# bool_in = np.logical_and((places[:, 1] < places[:, 0]), (-places[:, 1] < places[:, 0]))
return places[bool_in] | 417fccfbb240c5defc36b4ce465fe14333922b94 | 4,143 |
def neural_log_literal_function(identifier):
"""
A decorator for NeuralLog literal functions.
:param identifier: the identifier of the function
:type identifier: str
:return: the decorated function
:rtype: function
"""
return lambda x: registry(x, identifier, literal_functions) | 84651d58b7da677ee213d1ff4667dc3be702f243 | 4,144 |
def get_factors(n: int) -> list:
"""Returns the factors of a given integer.
"""
return [i for i in range(1, n+1) if n % i == 0] | c15a0e30e58597daf439facd3900c214831687f2 | 4,145 |
def fetch_tables():
""" Used by the frontend, returns a JSON list of all the tables including metadata. """
return jsonify([
{
"tab": "animeTables",
"name": "Anime",
"tables": [
{
"id": "englishAnimeSites",
"titl... | 5c07e7bc9f3366bc72e21dd5468edf57b6c448b3 | 4,146 |
def base_positive_warps():
"""
Get warp functions associated with domain (0,inf), scale 1.0
Warp function is defined as f(x) = log(exp(x)-1)
Returns
-------
Callable[torch.Tensor,torch.Tensor],
Callable[torch.Tensor,torch.Tensor],
Callable[torch.Tensor,torch.Tensor]
Function... | 389db769f55f7542a45e6acbbccf5760dc7b8c26 | 4,147 |
import re
import json
from datetime import datetime
def dev_work_create():
"""
Create work order.
:return:
"""
db_ins = current_user.dbs
audits = User.query.filter(User.role == 'audit')
form = WorkForm()
if form.validate_on_submit():
sql_content = form.sql_content.data
... | b11f840bbc6428696afabe7f2fe00b5d0b6ad7d1 | 4,148 |
def blur(x, mean=0.0, stddev=1.0):
"""
Resize to smaller size (AREA) and then resize to original size (BILINEAR)
"""
size = tf.shape(x)[:2]
downsample_factor = 1 + tf.math.abs(tf.random.normal([], mean=mean, stddev=stddev))
small_size = tf.to_int32(tf.to_float(size)/downsample_factor)
x = tf.image.resize_... | b0101a4b820beb84c627bef048bbafeb1d11cdea | 4,149 |
def improve(update, close, guess=1, max_updates=100):
"""Iteratively improve guess with update until close(guess) is true or
max_updates have been applied."""
k = 0
while not close(guess) and k < max_updates:
guess = update(guess)
k = k + 1
return guess | 3475c07a3e9a674661d90e116bfb91fa12344d63 | 4,150 |
def images_to_sequence(tensor):
"""Convert a batch of images into a batch of sequences.
Args:
tensor: a (num_images, height, width, depth) tensor
Returns:
(width, num_images*height, depth) sequence tensor
"""
num_image_batches, height, width, depth = _shape(tensor)
transposed = tf.transpose(tenso... | cc89ce931239b5335d5788bc6e9007e5186648bf | 4,151 |
from typing import Any
import logging
def transform_regions(regions: list[dict[str, Any]]) -> list[dict[str, Any]]:
"""
Transform aggregated region data for map
regions -- aggregated data from region pipeline
"""
records = []
for record in regions:
if "latitude" in record["_id"].keys(... | 599e58e3bd66159114d0dbf27b339c47134c29c3 | 4,152 |
def _file_to_import_exists(storage_client: storage.client.Client,
bucket_name: str, filename: str) -> bool:
"""Helper function that returns whether the given GCS file exists or not."""
storage_bucket = storage_client.get_bucket(bucket_name)
return storage.Blob(
bucket=storage_buc... | cb051aba0d5e787e85dbc0283aa439e3c17e819c | 4,153 |
from typing import Optional
from typing import List
from typing import Tuple
def get_relative_poses(
num_frames: int,
frames: np.ndarray,
selected_track_id: Optional[int],
agents: List[np.ndarray],
agent_from_world: np.ndarray,
current_agent_yaw: float,
) -> Tuple[np.ndarray, np.ndarray, np.nd... | e1dad983e5070310ce239615c98f85d8b09b9c45 | 4,155 |
import numpy
def read_mat_cplx_bin(fname):
"""
Reads a .bin file containing floating-point values (complex) saved by Koala
Parameters
----------
fname : string
Path to the file
Returns
-------
buffer : ndarray
An array containing the complex floating-point values read... | f2761f4cd7031dc16cb2f9903fd431bc7b4212d8 | 4,156 |
def DeleteDataBundle(**kwargs):
"""
Deletes a Data Bundle by ID.
:param kwargs:
:return:
"""
data_bundle_id = kwargs['data_bundle_id']
del data_bundles[data_bundle_id]
return(kwargs, 200) | 88ded979e45beebe885eeb1890ce66ae367b1fd6 | 4,157 |
def determineactions(repo, deficiencies, sourcereqs, destreqs):
"""Determine upgrade actions that will be performed.
Given a list of improvements as returned by ``finddeficiencies`` and
``findoptimizations``, determine the list of upgrade actions that
will be performed.
The role of this function i... | 0ec771565560607e839ce87a65426e01d0276f36 | 4,158 |
def filter_ccfs(ccfs, sc_thresh, min_ccf):
"""
Remove noisy ccfs from irrelevant experiments
:param ccfs: 2d array
:param sc_thresh: int
number of sign changes expected
:param min_ccf: float
cutoff value for a ccf to be above the noise threshold
:return:
"""
if sc_thresh ... | 06941eaea7bc5dc25f261669532c66ac37cbb9ab | 4,159 |
def market_data(symbol, expirationDate, strike, optionType, info=None):
"""Gets option market data from information. Takes time to load pages."""
assert all(isinstance(i, str) for i in [symbol, expirationDate, strike, optionType])
return robin_stocks.options.get_option_market_data(symbol, expirationDate, strike, opt... | 153d15af1030be22fa6c97b8d68fdf2049ebc416 | 4,160 |
def get_documents_embeddings (y, embedder, column):
"""
Given a Dataframe containing study_id and a text column, return a numpy array of embeddings
The idea of this function is to prevent to embed two times the same text (for computation efficiency)
Parameters:
-----------
... | 9a748ef8b276d68a61d78c6fa567a40aae4fc222 | 4,161 |
def index(request):
"""view fonction de la page d'accueil
Render templates de la page d'accueil
"""
return render(request, "t_myapp/index.html") | b3cf3be5d3c2a286d5705281e35042ad19d0a050 | 4,162 |
def cidr_mask_to_subnet_mask(mask_num):
"""
掩码位数转换为点分掩码
:param mask_num: 掩码位数, 如 16
:return: 十进制点分ipv4地址
"""
return convert_to_ipv4(cidr_mask_to_ip_int(mask_num), stype='int') | 83556c856f68e82824fa1f3a34b4d629361081af | 4,163 |
def correlate(A,B,
rows=None,columns=None, mode_row='zero', mode_column='zero'):
"""Correlate A and B.
Input:
------
A,B : array
Input data.
columns : int
Do correlation at columns 0..columns, defaults to the number of columns in A.
rows : int
Do correlatio... | 88bfec52c318aaf119a6fac5cff731855f0a0d81 | 4,164 |
def getChrLenList(chrLenDict, c):
""" Given a chromosome length dictionary keyed on chromosome names and
a chromosome name (c) this returns a list of all the runtimes for a given
chromosome across all Step names.
"""
l = []
if c not in chrLenDict:
return l
for n in chrLenDict[c]:
... | aedf613484262ac5bd31baf384ade2eb35f3e1eb | 4,165 |
from typing import Optional
def query_sessions(user_id: Optional[int]) -> TList[Session]:
"""
Return all user's sessions
:param user_id: current user ID (None if user auth is disabled)
:return: list of session objects
"""
adb = get_data_file_db(user_id)
return [Session(db_session) for db... | c7449c7805f1ba0c425140603952215b67e3ce0e | 4,167 |
import torch
import math
def positionalencoding3d(d_model, dx, dy, dz):
"""
:param d_model: dimension of the model
:param height: height of the positions
:param width: width of the positions
:return: d_model*height*width position matrix
"""
# if d_model % 6 != 0:
# raise ValueError("... | 178dc3b86e3be0c9e799f5f0c658808f541f1eca | 4,168 |
def make_headers(context: TraceContext) -> Headers:
"""Creates dict with zipkin headers from supplied trace context.
"""
headers = {
TRACE_ID_HEADER: context.trace_id,
SPAN_ID_HEADER: context.span_id,
FLAGS_HEADER: '0',
SAMPLED_ID_HEADER: '1' if context.sampled else '0',
... | 474e3a57af1bda99585f7d140fbd0bb1d9bd18b2 | 4,169 |
def shiftRightUnsigned(col, numBits):
"""Unsigned shift the given value numBits right.
>>> df = spark.createDataFrame([(-42,)], ['a'])
>>> df.select(shiftRightUnsigned('a', 1).alias('r')).collect()
[Row(r=9223372036854775787)]
"""
sc = SparkContext._active_spark_context
jc = sc._jvm.functio... | 342d08644c56c2cce5e02f0d3d0ddd9df0b2f173 | 4,170 |
def scalar_sub(x: Number, y: Number) -> Number:
"""Implement `scalar_sub`."""
_assert_scalar(x, y)
return x - y | 74c9d44eaaabb1bfeea012b4ec1503e37d7c9f8b | 4,171 |
def predict_attack(h1,h2,h3,h4,h5,h6,h7,h8,h9,h10,h11,h12,h13):
"""
Parameters:
-name:h1
in:query
type:number
required=True
-name:h5
in:query
type:number
required:True
-name:h4
in:query
type:number
required:True
-name:h8
... | 907f6b52c3b1c24a409b8b7ebc157412bd67777d | 4,172 |
def _check_varrlist_integrity(vlist):
"""Return true if shapes and datatypes are the same"""
shape = vlist[0].data.shape
datatype = vlist[0].data.dtype
for v in vlist:
if v.data.shape != shape:
raise(Exception("Data shapes don't match"))
if v.data.dtype != datatype:
... | 1b6fedd1222757c0bc92490be85d8030ee877842 | 4,173 |
def subclassfactory(fact_method):
"""fact_method takes the same args as init and returns the subclass appropriate to those args
that subclass may in turn override the same factory method and choose amoung it's subclasses.
If this factory method isn't overridden in the subclass an object of that class is ini... | eb0b8227276ed7499d21d9998ec08fb830d89642 | 4,174 |
def simulate_var1(x_tnow, b, mu, sigma2, m_, *, j_=1000, nu=10**9,
init_value=True):
"""For details, see here.
Parameters
----------
x_tnow : array, shape(n_, )
b : array, shape(n_,n_)
mu : array, shape(n_, )
sigma2 : array, shape(n_,n_)
m_ : int
... | 66bf82052e933e14d16e82738d36a4c96b51ca43 | 4,175 |
from typing import Optional
def is_drom(insee_city: Optional[str] = None, insee_region: Optional[str] = None) -> bool:
"""
Est-ce que le code INSEE de la ville ou de la région correspond à un DROM ?
Args:
insee_city: Code INSEE de la ville
insee_region: Code INSEE de la région
Return... | 7a33516eb31c5ff7800eb6dc663d76d5e2c445cb | 4,176 |
import math
def pack_rows(rows, bitdepth):
"""Yield packed rows that are a byte array.
Each byte is packed with the values from several pixels.
"""
assert bitdepth < 8
assert 8 % bitdepth == 0
# samples per byte
spb = int(8 / bitdepth)
def make_byte(block):
"""Take a block o... | e0b8a4701adf1757a558475e2ea5830a3d53ab2a | 4,177 |
def reset_user_pwd(username: str) -> int:
"""
:param username: 用户名
:return: 结果代码: 1: 成功, 0: 失败
"""
return update_user_info(username=username, args={
'password': '12345678'
}) | a9703bb82913b47e9b59ba36cd9257323cbfeec2 | 4,178 |
def location_engineering(df: pd.DataFrame) -> pd.DataFrame:
"""Call the `location_dict()` function to get the location dictionary and the
`location_dataframe()` one to add the location dictionary info to the DataFrame.
Parameters
----------
df :
The dataframe to work with.
Returns
... | cca3e1724da08ffcb895aa9fc323ebaf380760e4 | 4,179 |
import re
def extract_energyxtb(logfile=None):
"""
Extracts xtb energies from xtb logfile using regex matching.
Args:
logfile (str): Specifies logfile to pull energy from
Returns:
energy (list[float]): List of floats containing the energy in each step
"""
re_energy = re.comp... | 075f9d48d3bcc9f6bd12aa791cc4d0444299dd74 | 4,180 |
def make_transaction_frame(transactions):
"""
Formats a transaction DataFrame.
Parameters
----------
transactions : pd.DataFrame
Contains improperly formatted transactional data.
Returns
-------
df : pd.DataFrame
Daily transaction volume and dollar ammount.
- S... | ab8feafb1a441fddf574ebd12a7720a7c4d7398b | 4,182 |
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