content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def remove_suboptimal_parses(parses: Parses, just_one: bool) -> Parses:
""" Return all parses that have same optimal cost. """
minimum = min(parse_cost(parse) for parse in parses)
minimal_parses = [parse for parse in parses if parse_cost(parse) == minimum]
if just_one:
return Parses([minimal_par... | c223229e73a5319bdb40ac58695aa6f5a8c0bb4b | 27,042 |
def local_ranking(results):
"""
Parameters
----------
results : list
Dataset with initial hand ranking and the global hand ranking.
Returns
-------
results : list
Dataset with the initial hand ranking and the game-local hand ranking
(from 0 - nplayers).
""... | 2be1ff269ad18ba9439d183f5899f5034927b5d7 | 27,043 |
def is_monotonic_increasing(bounds: np.ndarray) -> bool:
"""Check if int64 values are monotonically increasing."""
n = len(bounds)
if n < 2:
return True
prev = bounds[0]
for i in range(1, n):
cur = bounds[i]
if cur < prev:
return False
prev = cur
retur... | e745ce3825f4e052b2f62c7fdc23e66b5ee5d4d1 | 27,044 |
def parse(data):
"""
Takes binary data, detects the TLS message type, parses the info into a nice
Python object, which is what is returned.
"""
if data[0] == TLS_TYPE_HANDSHAKE:
obj = TlsHandshake()
obj.version = data[1:3]
obj.length = unpack(">H", data[3:5])[0]
if data[5] == TLS_TYPE_CLIENT_HELLO:
obj.... | 64698fde904d702181f4d8bacda648d9fbea68a7 | 27,045 |
def recoverSecretRanks_GPT(mod_rec, tok_rec, startingText, outInd, finishSentence=True):
"""
Function to calculate the secret ranks of GPT2 LM of a cover text given the cover text
"""
startingInd=tok_rec.encode(startingText)
endingInd=outInd[len(startingInd):]
secretTokensRec=[]
for i in ran... | be08520901b5c010d89a248814f96681265bb467 | 27,046 |
def threshold_strategies(random_state=None):
"""Plan (threshold):
- [x] aggregated features: (abs(mean - median) < 3dBm) || (2*stdev(x) < 8dBm)
- [x] histogram: x < 85dBm
- [ ] timeseries batch: p < 10**-3
"""
dummy = lambda: dummy_anomaly_injector(scaler=None, random_state=random_s... | d127a36d36360f6733e26538c37d3cbb47f199a4 | 27,047 |
import math
def ellipse_properties(x, y, w):
"""
Given a the (x,y) locations of the foci of the ellipse and the width return
the center of the ellipse, width, height, and angle relative to the x-axis.
:param double x: x-coordinates of the foci
:param double y: y-coordinates of the foci
:param... | 95864eac0feb9c34546eefed5ca158f330f88e3d | 27,048 |
def build_func(f, build_type):
"""
Custom decorator that is similar to the @conf decorator except that it is intended to mark
build functions specifically. All build functions must be decorated with this decorator
:param f: build method to bind
:type f: function
:parm build_type: The WAF build t... | e880b7d5a3c4ac79a3caff48f1a3f991ed321262 | 27,049 |
def getnumoflinesinblob(ext_blob):
"""
Get number of lines in blob
"""
ext, blob_id = ext_blob
return (ext, blob_id, int(getpipeoutput(['git cat-file blob %s' % blob_id, 'wc -l']).split()[0])) | ccc492cc66e046d73389f6822ad04cd943376f7b | 27,050 |
import requests
def fetch_data(full_query):
"""
Fetches data from the given url
"""
url = requests.get(full_query)
# Parse the json dat so it can be used as a normal dict
raw_data = url.json()
# It's a good practice to always close opened urls!
url.close()
return raw_data | 576b2548c1b89827e7586542e4d7e3f0cc89051d | 27,052 |
import http
def post(*args, **kwargs): # pragma: no cover
"""Make a post request. This method is needed for mocking."""
return http.post(*args, **kwargs) | d5c91da5f39ece36183a8265f74378a35f11c4c7 | 27,053 |
def shear_x(image: tf.Tensor, level: float, replace: int) -> tf.Tensor:
"""Equivalent of PIL Shearing in X dimension."""
# Shear parallel to x axis is a projective transform
# with a matrix form of:
# [1 level
# 0 1].
image = transform(
image=wrap(image), transforms=[1., level, 0., 0., 1., 0., 0., ... | 230fb5d346a966c4945b0bb39f336c1fddeb94fd | 27,054 |
def extract_const_string(data):
"""Extract const string information from a string
Warning: strings array seems to be practically indistinguishable from strings with ", ".
e.g.
The following is an array of two elements
const/4 v0, 0x1
new-array v0, v0, [Ljava/lang/String;
const/4 v1, 0x0
... | 70229ea1a6183218577244f185a5e37d170fe4be | 27,056 |
def choose_action(q, sx, so, epsilon):
"""
Choose action index for given state.
"""
# Get valid action indices
a_vindices = np.where((sx+so)==False)
a_tvindices = np.transpose(a_vindices)
q_max_index = tuple(a_tvindices[np.argmax(q[a_vindices])])
# Choose next action based on epsilon-g... | 626ccda15c24d983a060bdd6dd90a836c461b1ba | 27,057 |
def soliswets(function, sol, fitness, lower, upper, maxevals, delta):
""""
Implements the solis wets algorithm
"""
bias = zeros(delta.shape)
evals = 0
num_success = 0
num_failed = 0
dim = len(sol)
while evals < maxevals:
dif = uniform(0, delta, dim)
newsol = clip(so... | 19104e717af6701ce3d838d526059575306018cf | 27,059 |
def _get_precision_type(network_el):
"""Given a network element from a VRP-REP instance, returns its precision type:
floor, ceil, or decimals. If no such precision type is present, returns None.
"""
if 'decimals' in network_el:
return 'decimals'
if 'floor' in network_el:
return 'flo... | b3b451a26ec50ce5f2424ea7a3652123ae96321d | 27,060 |
import json
def user_list():
"""Retrieves a list of the users currently in the db.
Returns:
A json object with 'items' set to the list of users in the db.
"""
users_json = json.dumps(({'items': models.User.get_items_as_list_of_dict()}))
return flask.Response(ufo.XSSI_PREFIX + users_json, headers=ufo.JS... | b216b41b35b4b25c23ea2cc987ff4fe2b6464775 | 27,062 |
import hashlib
def md5_str(content):
"""
计算字符串的MD5值
:param content:输入字符串
:return:
"""
m = hashlib.md5(content.encode('utf-8'))
return m.hexdigest() | affe4742c2b44a60ef6dafa52d7a330594a70ed9 | 27,063 |
import requests
def hurun_rank(indicator: str = "百富榜", year: str = "2020") -> pd.DataFrame:
"""
胡润排行榜
http://www.hurun.net/CN/HuList/Index?num=3YwKs889SRIm
:param indicator: choice of {"百富榜", "富豪榜", "至尚优品"}
:type indicator: str
:param year: 指定年份; {"百富榜": "2015至今", "富豪榜": "2015至今", "至尚优品": "201... | d8540f3b7482f8f56f0ec40ac2592ef0cfae4035 | 27,064 |
def yamartino_method(a, axis=None):
"""This function calclates the standard devation along the
chosen axis of the array. This function has been writen to
calculate the mean of complex numbers correctly by taking
the standard devation of the argument & the
angle (exp(1j*theta) ). This uses the Yamart... | 1a313ac97495a0822de1f071191be08ec5b65269 | 27,065 |
def calc_half_fs_axis(total_points, fs):
""" Геренирует ось до половины частоты дискр. с числом
точек равным заданному
"""
freq_axis = arange(total_points)*fs/2/total_points # Hz до половины fs
return freq_axis | 35ef0482e3062d0af6f0e03e03e58e1c3cd33406 | 27,066 |
def fetch_weather():
""" select flight records for display """
sql = "select station, latitude,longitude,visibility,coalesce(nullif(windspeed,''),cast(0.0 as varchar)) as windspeed, coalesce(nullif(precipitation,''),cast(0.00 as varchar)) as precipitation from (select station_id AS station, info ->> 'Latitude' ... | 8ab9f20255a64cfdaa5bfd6ed9aa675ed76f2f5d | 27,067 |
def update_params(old_param, new_param, errors="raise"):
""" Update 'old_param' with 'new_param'
"""
# Copy old param
updated_param = old_param.copy()
for k,v in new_param.items():
if k in old_param:
updated_param[k] = v
else:
if errors=="raise":
... | 95de4e8e1278b07d2bd8ccc61af4e2dc43f87ca2 | 27,068 |
from datetime import datetime
def rng_name():
"""Generate random string for a username."""
name = "b{dt.second}{dt.microsecond}"
return name.format(dt=datetime.datetime.utcnow()) | 81be1b40770b08ec6b9adce0c3c9970ff1f3d442 | 27,070 |
def collections(id=None):
"""
Return Collections
Parameters
----------
id : STR, optional
The default is None, which returns all know collections.
You can provide a ICOS URI or DOI to filter for a specifict collection
Returns
-------
query : STR
A query, which can... | 0cd1704d2ac43f34d6e83a3f9e9ead39db390c2e | 27,071 |
def zmat_to_coords(zmat, keep_dummy=False, skip_undefined=False):
"""
Generate the cartesian coordinates from a zmat dict.
Considers the zmat atomic map so the returned coordinates is ordered correctly.
Most common isotopes assumed, if this is not the case, then isotopes should be reassigned to the xyz.... | 0859a549b611347b4e3d94e4f0965a8a550e198e | 27,073 |
def get_module_version(module_name: str) -> str:
"""Check module version. Raise exception when not found."""
version = None
if module_name == "onnxrt":
module_name = "onnx"
command = [
"python",
"-c",
f"import {module_name} as module; print(module.__version__)",
]
... | caadba47f46d96b0318cd90b0f85f8a2ca2275b0 | 27,074 |
def pd_images(foc_offsets=[0,0], xt_offsets = [0,0], yt_offsets = [0,0],
phase_zernikes=[0,0,0,0], amp_zernikes = [0], outer_diam=200, inner_diam=0, \
stage_pos=[0,-10,10], radians_per_um=None, NA=0.58, wavelength=0.633, sz=512, \
fresnel_focal_length=None, um_per_pix=6.0):
"""
Create a set of simu... | 71a7dd7206936541cc55d8909be7795261aeaefa | 27,075 |
def add_tickets(create_user, add_flights):
"""Fixture to add tickets"""
user = create_user(USER)
tickets = [{
"ticket_ref": "LOS29203SLC",
"paid": False,
"flight": add_flights[0],
"type": "ECO",
"seat_number": "E001",
"made_by": user,
}, {
"ticket... | 27f9ed9a5231c71e98a79632a97137b73831a0e0 | 27,076 |
def compute_depth_errors(gt, pred):
"""Computation of error metrics between predicted and ground truth depths
Args:
gt (N): ground truth depth
pred (N): predicted depth
"""
thresh = np.maximum((gt / pred), (pred / gt))
a1 = (thresh < 1.25).mean()
a2 = (thresh < 1.25 ** 2).mean()
... | a781d5a8c1e61b5562870d75124de64e05fe2789 | 27,077 |
def sanitize_bvals(bvals, target_bvals=[0, 1000, 2000, 3000]):
"""
Remove small variation in bvals and bring them to their closest target bvals
"""
for idx, bval in enumerate(bvals):
bvals[idx] = min(target_bvals, key=lambda x: abs(x - bval))
return bvals | a92b170748b5dbc64c4e62703a3c63103675b702 | 27,078 |
def fetch_engines():
"""
fetch_engines() : Fetches documents from Firestore collection as JSON
all_engines : Return all documents
"""
all_engines = []
for doc in engine_ref.stream():
engine = doc.to_dict()
engine["id"] = doc.id
all_engines.append(engine)
ret... | a79a623140209ed4e9e7cbea2d8944b3434f720a | 27,079 |
def isone(a: float) -> bool:
"""Work around with float precision issues"""
return np.isclose(a, 1.0, atol=1.0e-8, rtol=0.0) | ee44d5d7a9b00457e51501d8ce5680cd95726e3f | 27,080 |
def kerr(E=0, U=0, gs=None):
"""
Setup the Kerr nonlinear element
"""
model = scattering.Model(
omegas=[E]*1,
links=[],
U=[U])
if gs is None:
gs = (0.1, 0.1)
channels = []
channels.append(scattering.Channel(site=0, strength=gs[0]))
channels.append(scatte... | a94ecb4618405a2817267609008bc56ef97033b9 | 27,082 |
from typing import Dict
import requests
import logging
def get_estate_urls(last_estate_id: str) -> Dict:
"""Fetch urls of newly added estates
Args:
last_estate_id (str): estate_id of the most recent estate added (from last scrape)
Returns:
Dict: result dict in format {estate_id_1: {estat... | d93299002204edc9d26b3c77e2dff1f56f4b93d8 | 27,083 |
from datetime import datetime
def revert_transaction():
"""Revert a transaction."""
if not (current_user.is_admin or current_user.is_bartender):
flash("You don't have the rights to access this page.", 'danger')
return redirect(url_for('main.dashboard'))
transaction_id = request.args.get('... | 39f4fc0c6af9c58197c514d5d648e07da20558aa | 27,084 |
def is_number(s):
"""returns true if input can be converted to a float"""
try:
float(s)
return True
except ValueError:
return False | d9fc4411bbc5e5fd8d02b3c105a770e8859048e0 | 27,085 |
def bib_to_string(bibliography):
""" dict of dict -> str
Take a biblatex bibliography represented as a dictionary
and return a string representing it as a biblatex file.
"""
string = ''
for entry in bibliography:
string += '\n@{}{{{},\n'.format(
bibliography[entry]['type'],
... | c8fc4247210f74309929fdf9b210cd6f1e2ece3f | 27,086 |
import io
def make_plot(z, figsize=(20, 20), scale=255 * 257,
wavelength=800, terrain=None,
nir_min=0.2, offset=3.5):
"""
Make a 3-D plot of image intensity as z-axis and RGB image as an underlay on the z=0 plane.
:param z: NIR intensities
:param figsize: size of the figure... | 1a4dde23a11b320e6564b6657a871a33ecb65eea | 27,087 |
def check_prio_and_sorted(node):
"""Check that a treap object fulfills the priority requirement and that its sorted correctly."""
if node is None:
return None # The root is empty
else:
if (node.left_node is None) and (node.right_node is None): # No children to compare with
... | 64100fd4ba9af699ab362d16f5bbf216effa2da5 | 27,088 |
import pickle
async def wait_for_msg(channel):
"""Wait for a message on the specified Redis channel"""
while await channel.wait_message():
pickled_msg = await channel.get()
return pickle.loads(pickled_msg) | dca398cb3adeb778458dd6be173a53cdd204bcb9 | 27,090 |
def abandoned_baby_bull(high, low, open_, close, periods = 10):
"""
Abandoned Baby Bull
Parameters
----------
high : `ndarray`
An array containing high prices.
low : `ndarray`
An array containing low prices.
open_ : `ndarray`
An array containing open prices.
clos... | 5fb0f2e3063e7b7aa03663d1e2d04d565ec8e885 | 27,091 |
def split_line_num(line):
"""Split each line into line number and remaining line text
Args:
line (str): Text of each line to split
Returns:
tuple consisting of:
line number (int): Line number split from the beginning of line
remaining text (str): Text for remainder ... | d232fd046ee60ac804fff032494c8c821456c294 | 27,092 |
def rad_to_arcmin(angle: float) -> float:
"""Convert radians to arcmins"""
return np.rad2deg(angle)*60 | c342286befd79a311edda18e8a7a2e978d8312ad | 27,093 |
def get_tile_prefix(rasterFileName):
"""
Returns 'rump' of raster file name, to be used as prefix for tile files.
rasterFileName is <date>_<time>_<sat. ID>_<product type>_<asset type>.tif(f)
where asset type can be any of ["AnalyticMS","AnalyticMS_SR","Visual","newVisual"]
The rump is defined as <da... | 15b517e5ba83b2cfb5f3b0014d800402c9683815 | 27,094 |
def get_indices_by_groups(dataset):
"""
Only use this to see F1-scores for how well we can recover the subgroups
"""
indices = []
for g in range(len(dataset.group_labels)):
indices.append(
np.where(dataset.targets_all['group_idx'] == g)[0]
)
return indices | 864aad8eef0339afd04cce34bee65f46c9fb030b | 27,095 |
def ranksumtest(x, y):
"""Calculates the rank sum statistics for the two input data sets
``x`` and ``y`` and returns z and p.
This method returns a slight difference compared to scipy.stats.ranksumtest
in the two-tailed p-value. Should be test drived...
Returns: z-value for first data set ``... | d01d0a56cf888983fa1b8358f2f6f0819ca824d9 | 27,096 |
def inchi_to_can(inchi, engine="openbabel"):
"""Convert InChI to canonical SMILES.
Parameters
----------
inchi : str
InChI string.
engine : str (default: "openbabel")
Molecular conversion engine ("openbabel" or "rdkit").
Returns
-------
str
Canonical SMILES.
... | 040d091f1cdbc1556fd60b9ee001953e1a382356 | 27,098 |
from typing import List
from re import T
def swap(arr: List[T],
i: int,
j: int) -> List[T]:
"""Swap two array elements.
:param arr:
:param i:
:param j:
:return:
"""
arr[i], arr[j] = arr[j], arr[i]
return arr | e34c983b816f255a8f0fb438c14b6c81468b38c6 | 27,099 |
def is_anno_end_marker(tag):
"""
Checks for the beginning of a new post
"""
text = tag.get_text()
m = anno_end_marker_regex.match(text)
if m:
return True
else:
return False | 28b7d216c38dabedaef33f4d71f9749e72344b65 | 27,100 |
async def fetch_and_parse(session, url):
"""
Parse a fatality page from a URL.
:param aiohttp.ClientSession session: aiohttp session
:param str url: detail page URL
:return: a dictionary representing a fatality.
:rtype: dict
"""
# Retrieve the page.
# page = await fetch_text(session... | 525bf965854a098507046b3408de5e73bcd4abc9 | 27,101 |
def wmt_diag_base():
"""Set of hyperparameters."""
hparams = iwslt_diag()
hparams.batch_size = 4096
hparams.num_hidden_layers = 6
hparams.hidden_size = 512
hparams.filter_size = 2048
hparams.num_heads = 8
# VAE-related flags.
hparams.latent_size = 512
hparams.n_posterior_layers = 4
hparams.n_decod... | 384820d2fadc13711968a666a6f4d7b1be0726c5 | 27,102 |
def K_axialbending(EA, EI_x, EI_y, x_C=0, y_C=0, theta_p=0):
"""
Axial bending problem. See KK for notations.
"""
H_xx = EI_x*cos(theta_p)**2 + EI_y*sin(theta_p)**2
H_yy = EI_x*sin(theta_p)**2 + EI_y*cos(theta_p)**2
H_xy = (EI_y-EI_x)*sin(theta_p)*cos(theta_p)
return np.array([
[EA ... | f187b35c5324a0aa46e5500a0f37aebbd2b7cc62 | 27,103 |
def get_closest_intersection_pt_dist(path1, path2):
"""Returns the manhattan distance from the start location to the closest
intersection point.
Args:
path1: the first path (list of consecutive (x,y) tuples)
path2: the secong path
Returns:
int of lowest manhattan distance ... | 07bbe3a2d5f817f28b4e077989a89a78747c676f | 27,104 |
def is_voiced_offset(c_offset):
"""
Is the offset a voiced consonant
"""
return c_offset in VOICED_LIST | 6dfad8859ba8992e2f05c9946e9ad7bf9428d181 | 27,105 |
def add_boundary_label(lbl, dtype=np.uint16):
"""
Find boundary labels for a labelled image.
Parameters
----------
lbl : array(int)
lbl is an integer label image (not binarized).
Returns
-------
res : array(int)
res is an integer label image with boundary encoded as 2.
... | 31bae32ad08c66a66b19379d30d6210ba2b61ada | 27,107 |
def kmax(array, k):
""" return k largest values of a float32 array """
I = np.zeros(k, dtype='int64')
D = np.zeros(k, dtype='float32')
ha = float_minheap_array_t()
ha.ids = swig_ptr(I)
ha.val = swig_ptr(D)
ha.nh = 1
ha.k = k
ha.heapify()
ha.addn(array.size, swig_ptr(array))
h... | 41037c924ae240636309f272b95a3c9dcfe10c5e | 27,108 |
def adcp_ins2earth(u, v, w, heading, pitch, roll, vertical):
"""
Description:
This function converts the Instrument Coordinate transformed velocity
profiles to the Earth coordinate system. The calculation is defined in
the Data Product Specification for Velocity Profile and Echo Intensi... | 0a51db6b5d6186c4f9208e4fa2425160e8c43925 | 27,109 |
import math
def strength(data,l):
"""
Returns the strength of earthquake as tuple (P(z),S(xy))
"""
# FFT
# https://momonoki2017.blogspot.com/2018/03/pythonfft-1-fft.html
# Fast Fourier Transform
# fx = np.fft.fft(data[0])
# fy = np.fft.fft(data[1])
# fz = np.fft.fft(data[2])
#... | 705b04644002c2cf826ca6a03838cab66ccea1f8 | 27,110 |
def humanize(tag, value):
"""Make the metadata value human-readable
:param tag: The key of the metadata value
:param value: The actual raw value
:return: Returns ``None`` or a human-readable version ``str``
:rtype: ``str`` or ``None``
"""
for formatter in find_humanizers(tag):
human... | 42a4e1506b4655a86607495790f555cc318b6d82 | 27,112 |
import itertools
def cartesian(sequences, dtype=None):
"""
Generate a cartesian product of input arrays.
Parameters
----------
sequences : list of array-like
1-D arrays to form the cartesian product of.
dtype : data-type, optional
Desired output data-type.
Returns
---... | 51e6031c568eee425f2ea86c16b472474ae499eb | 27,113 |
def nasa_date_to_iso(datestr):
"""Convert the day-number based NASA format to ISO.
Parameters
----------
datestr : str
Date string in the form Y-j
Returns
-------
Datestring in ISO standard yyyy-mm-ddTHH:MM:SS.MMMMMM
"""
date = dt.datetime.strptime(datestr, nasa_date_format... | d77114c874fdd41a220aae907ce7eabd6dd239bf | 27,114 |
def auto_label_color(labels):
"""
???+ note "Create a label->hex color mapping dict."
"""
use_labels = set(labels)
use_labels.discard(module_config.ABSTAIN_DECODED)
use_labels = sorted(use_labels, reverse=False)
assert len(use_labels) <= 20, "Too many labels to support (max at 20)"
pale... | 791de575e500bf2c2e0e1d56c390c59a2f62381c | 27,116 |
import re
def dedentString(text):
"""Dedent the docstring, so that docutils can correctly render it."""
dedent = min([len(match) for match in space_re.findall(text)] or [0])
return re.compile('\n {%i}' % dedent, re.M).sub('\n', text) | a384b0c9700a17a7ce621bca16175464192c9aee | 27,117 |
def preprocess(df):
"""Preprocess the DataFrame, replacing identifiable information"""
# Usernames: <USER_TOKEN>
username_pattern = r"(?<=\B|^)@\w{1,18}"
df.text = df.text.str.replace(username_pattern, "<USERNAME>")
# URLs: <URL_TOKEN>
url_pattern = (
r"https?://(?:[a-zA-Z]|[0-9]|[$-_@.&... | d592d9e56af9ec17dcebede31d458dfdc001c220 | 27,118 |
def mobilenetv3_large_w7d20(**kwargs):
"""
MobileNetV3 Small 224/0.35 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/model... | 550f8273dfe52c67b712f8cd12d1e916f7a917cc | 27,119 |
def random_forest_classifier(model, inputs, method="predict_proba"):
"""
Creates a SKAST expression corresponding to a given random forest classifier
"""
trees = [decision_tree(estimator.tree_, inputs, method="predict_proba", value_transform=lambda v: v/len(model.estimators_))
for estimator... | d13e28e05d01a2938116a1bac5ddbd64f7b5438c | 27,120 |
from cowbird.utils import get_settings as real_get_settings
import functools
def mock_get_settings(test):
"""
Decorator to mock :func:`cowbird.utils.get_settings` to allow retrieval of settings from :class:`DummyRequest`.
.. warning::
Only apply on test methods (not on class TestCase) to ensure t... | 8332d08846bcee6e9637f75c5c15fb763d9978a4 | 27,121 |
def _convert_to_interbatch_order(order: pd.Series,
batch: pd.Series) -> pd.Series:
"""
Convert the order values from a per-batch order to a interbatch order.
Parameters
----------
order: pandas.Series
order and batch must share the same index, size and be of... | 235e99d8a93ebeecde7bfe274b82fe32980288dd | 27,122 |
def CV_INIT_3X3_DELTAS(*args):
"""CV_INIT_3X3_DELTAS(double deltas, int step, int nch)"""
return _cv.CV_INIT_3X3_DELTAS(*args) | cbcbd6de2593d548c8e5bc02992d1df9a3d66460 | 27,123 |
def is_instance_cold_migrated_alarm(alarms, instance, guest_hb=False):
"""
Check if an instance cold-migrated alarm has been raised
"""
expected_alarm = {'alarm_id': fm_constants.FM_ALARM_ID_VM_COLD_MIGRATED,
'severity': fm_constants.FM_ALARM_SEVERITY_CRITICAL}
return _instanc... | 8b6db3498d09d4d538382507ffac249226a2912f | 27,124 |
def precision_macro(y_target, y_predicted):
"""
y_target: m x n 2D array. {0, 1}
real labels
y_predicted: m x n 2D array {0, 1}
prediction labels
m (y-axis): # of instances
n (x-axis): # of classes
"""
average = 'macro'
score = precision_score(y_target, y_predicted, ave... | 4038eb838f35da93b24301809e5f0c3d5c37e2c9 | 27,125 |
def layout(mat,widths=None,heights=None):
"""layout"""
ncol=len(mat[0])
nrow=len(mat)
arr=[]
list(map(lambda m: arr.extend(m),mat))
rscript='layout(matrix(c(%s), %d, %d, byrow = TRUE),' %(str(arr)[1:-1],nrow,ncol)
if widths:
rscript+='widths=c(%s),' %(str(widths)[1:-1])
if h... | 813fb351b4e09d4762255ecbbe6f9ee7e050efd0 | 27,126 |
def get_file_language(filename, text=None):
"""Get file language from filename"""
ext = osp.splitext(filename)[1]
if ext.startswith('.'):
ext = ext[1:] # file extension with leading dot
language = ext
if not ext:
if text is None:
text, _enc = encoding.read(filename)
... | 7cfcd49d94cc1c2246f03946cfea1c99b866f941 | 27,127 |
import re
def _get_output_name(fpattern,file_ind,ind):
""" Returns an output name for volumetric image
This function returns a file output name for the image volume
based on the names of the file names of the individual z-slices.
All variables are kept the same as in the original filename,
but the... | 8ce392acab2984b5012d8de7a0aa205f9a5e5e3b | 27,128 |
import re
def MatchNameComponent(key, name_list, case_sensitive=True):
"""Try to match a name against a list.
This function will try to match a name like test1 against a list
like C{['test1.example.com', 'test2.example.com', ...]}. Against
this list, I{'test1'} as well as I{'test1.example'} will match, but
... | ad522feba9cabb3407e3b8e1e8c221f3e9800e16 | 27,129 |
import requests
def news_api():
"""Uses news API and returns a dictionary containing news """
news_base_url = "https://newsapi.org/v2/top-headlines?"
news_api_key = keys["news"]
country = location["country"]
news_url = news_base_url + "country=" + country + "&apiKey=" + news_api_key
n_api = re... | 45e8a9d42d64066e2259fc95727d52e6b5bdfc9e | 27,130 |
def compress(mesh, engine_name="draco"):
""" Compress mesh data.
Args:
mesh (:class:`Mesh`): Input mesh.
engine_name (``string``): Valid engines are:
* ``draco``: `Google's Draco engine <https://google.github.io/draco/>`_
[#]_
Returns:
A binary string rep... | 67d8ec030d006f6720bacffad7bacd0c36b9df42 | 27,131 |
import configparser
def get_hotkey_next(config: configparser.RawConfigParser):
"""
获取热键：下一个桌面背景
"""
return __get_hotkey(config, 'Hotkey', 'hk_next') | 3af499c01778a1defb0a440d042538885d829398 | 27,133 |
def get_soup(url):
""" Returns beautiful soup object of given url.
get_soup(str) -> object(?)
"""
req = urllib2.Request(url)
response = urllib2.urlopen(req)
html = response.read()
soup = bs4(html)
return soup | 8d0bb43ae1d404cef5a3873dfd089b88461bf9fd | 27,135 |
def internal_server_error(error):
""" Handles unexpected server error with 500_SERVER_ERROR """
message = error.message or str(error)
app.logger.info(message)
return make_response(jsonify(status=500, error='Internal Server Error', message=message), 500) | 8e80a4502a4656a1ccdb2c720177090dd7bcf53a | 27,136 |
import math
def diffsnorms(A, S, V, n_iter=20):
"""
2-norm accuracy of a Schur decomp. of a matrix.
Computes an estimate snorm of the spectral norm (the operator norm
induced by the Euclidean vector norm) of A-VSV', using n_iter
iterations of the power method started with a random vector;
n_i... | 2f446a08c6ff5d8377cca22ffcd1570c68f46748 | 27,137 |
from typing import Iterator
from typing import Tuple
def data_selection(workload: spec.Workload,
input_queue: Iterator[Tuple[spec.Tensor, spec.Tensor]],
optimizer_state: spec.OptimizerState,
current_param_container: spec.ParameterContainer,
h... | 6daa0950e5ce82da081b71a01572dc29374f17f8 | 27,138 |
def graph_cases_factory(selenium):
"""
:type selenium: selenium.webdriver.remote.webdriver.WebDriver
:rtype: callable
:return: Constructor method to create a graph cases factory with a custom
host.
"""
return lambda host: GraphCaseFactory(selenium=selenium, host=host) | b41b02c148b340c07859e707cbaf4810db3b6004 | 27,139 |
def clean_scene_from_file(file_name):
"""
Args:
file_name: The name of the input sequence file
Returns:
Name of the scene used in the sequence file
"""
scene = scenename_from_file(file_name)
print('Scene: ', scene)
mesh_file = SCENE_PATH + scene + '/10M_clean.ply'
return ... | cd706c900ca3e3fce6736ce5c4288cce6079b3e0 | 27,140 |
def _non_overlapping_chunks(seq, size):
"""
This function takes an input sequence and produces chunks of chosen size
that strictly do not overlap. This is a much faster implemetnation than
_overlapping_chunks and should be preferred if running on very large seq.
Parameters
----------
seq : ... | 15b5d2b4a7d8df9785ccc02b5369a3f162704e9e | 27,141 |
import logging
def Compute_Error(X_data, pinn, K, mu, Lf, deltamean, epsilon, ndim) :
"""
Function to determine error for input data X_data
:param array X_data: input data for PINN
:param PINN pinn: PINN under investigation
:param float K: key parameter for using trapezoidal rule and estimating t... | 0789d7c52c96aed5cb40aa45c44c4df09f5cffaf | 27,143 |
import itertools
def sort_fiducials(qr_a, qr_b):
"""Sort 2d fiducial markers in a consistent ordering based on their relative positions.
In general, when we find fiducials in an image, we don't expect them to be
returned in a consistent order. Additionally, the image coordinate may be
rotated from... | daa96f12ef2e94fed86970979e4d140f8a3fa3d5 | 27,144 |
from pathlib import Path
import jinja2
def form_render(path: str, **kwargs) -> str:
""" Just jinja2 """
file_text = Path(path).read_text()
template = jinja2.Template(file_text)
return template.render(**kwargs) | b5da5afdedcac922c164f644eabeae5f038f9169 | 27,145 |
def _names(fg, bg):
"""3/4 bit encoding part
c.f. https://en.wikipedia.org/wiki/ANSI_escape_code#3.2F4_bit
Parameters:
"""
if not (fg is None or fg in _FOREGROUNDS):
raise ValueError('Invalid color name fg = "{}"'.format(fg))
if not (bg is None or bg in _BACKGROUNDS):
raise Va... | 50e4dfe9aa56c1f3fc7622c468045b26da9b4175 | 27,146 |
def preprocess(code):
"""Preprocess a code by removing comments, version and merging includes."""
if code:
#code = remove_comments(code)
code = merge_includes(code)
return code | b4ecbf28fa2043559b744e7351f268a2ba1e8200 | 27,147 |
import types
def _from_schemas_get_model(
stay_within_model: bool, schemas: _oa_types.Schemas, schema: _oa_types.Schema
) -> types.ModelArtifacts:
"""
Get artifacts for a model.
Assume the schema is valid.
Args:
schema: The schema of the model to get artifacts for.
schemas: All d... | 0c5166c6baaabda64795729554b7bb3444a902c9 | 27,148 |
def solution2(inp):
"""Solves the second part of the challenge"""
return "done" | 8e20e1a81911b3f2e54fac058df8a44e54945af0 | 27,149 |
import math
def juld_to_grdt(juld: JulianDay) -> GregorianDateTime:
"""ユリウス通日をグレゴリオ曆の日時に變換する."""
A = math.floor(juld.julian_day + 68569.5)
B = juld.julian_day + 0.5
a = math.floor(A / 36524.25)
b = A - math.floor(36524.25 * a + 0.75)
c = math.floor((b + 1) / 365.25025)
d = b - math.floor(3... | 94559bbec7fef45e6c7f6d8594d20c8039b58672 | 27,150 |
def users_all(request):
"""
Returns name + surname and email of all users
Note: This type of function can only be justified
when considering the current circumstances:
An *INTERNAL* file sharing app (used by staff)
Hence, all names and emails may be fetched be other
authenticated users
... | 53302d074ee1bbbc1156ffa2f94da4f834e9cb3c | 27,151 |
def _resolve_categorical_entities(request, responder):
"""
This function retrieves all categorical entities as listed below and filters
the knowledge base using these entities as filters. The final search object
containing the shortlisted employee data is returned back to the calling function.
"""
... | d6671d030699df1b0400b1d478dc98f86be06c29 | 27,152 |
def filter_c13(df):
""" Filter predicted formulas with 13C.
Returns filtered df and n excluded """
shape_i = df.shape[0]
df = df[df['C13'] == 0]
df = df.reset_index(drop=True)
shape_f = df.shape[0]
n_excluded = shape_i - shape_f
return df, n_excluded | 4f0d3eb6c9de7c07bc2e3f285ad5502bb6d6dd06 | 27,153 |
import random
import gzip
def getContent(url):
"""
此函数用于抓取返回403禁止访问的网页
"""
random_header = random.choice(HEARDERS)
"""
对于Request中的第二个参数headers，它是字典型参数，所以在传入时
也可以直接将个字典传入，字典中就是下面元组的键值对应
"""
req = Request(url)
req.add_header("User-Agent", random_header)
req.add_header("Ho... | da396d664fb23737ea2d87b6548521948adad709 | 27,154 |
def neighbour(x,y,image):
"""Return 8-neighbours of image point P1(x,y), in a clockwise order"""
img = image.copy()
x_1, y_1, x1, y1 = x-1, y-1, x+1, y+1;
return [img[x_1][y], img[x_1][y1], img[x][y1], img[x1][y1], img[x1][y], img[x1][y_1], img[x][y_1], img[x_1][y_1]] | 8e645f7634d089a0e65335f6ea3363d4ed66235b | 27,155 |
def deconv2d(x, kernel, output_shape, strides=(1, 1),
border_mode='valid',
dim_ordering='default',
image_shape=None, filter_shape=None):
"""2D deconvolution (i.e. transposed convolution).
# Arguments
x: input tensor.
kernel: kernel tensor.
output_s... | d1ed452b627764f0f08c669e4bea749886ebd0a6 | 27,157 |
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