content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def html_url(url: str, name: str = None, theme: str = "") -> str:
"""Create a HTML string for the URL and return it.
:param url: URL to set
:param name: Name of the URL, if None, use same as URL.
:param theme: "dark" or other theme.
:return: String with the correct formatting for URL
"""
i... | 74a0d3eabce4f0a53e699567e25c9d09924e3150 | 18,137 |
def get_logger_messages(loggers=[], after=0):
""" Returns messages for the specified loggers.
If given, limits the messages to those that occured after the given timestamp"""
if not isinstance(loggers, list):
loggers = [loggers]
return logger.get_logs(loggers, after) | d2c8ef6dc8f1ec0f4a5f7a1263b829f20e0dfa8b | 18,138 |
def __dir__():
"""IPython tab completion seems to respect this."""
return __all__ | d1b0fe35370412a6c0ca5d323417e4e3d1b3b603 | 18,139 |
def run_iterations(histogram_for_random_words,
histogram_for_text,
iterations):
"""Helper function for test_stochastic_sample (below).
Store the results of running the stochastic_sample function for 10,000
iterations in a histogram.
Param: histogram_for_ran... | 59bd4cefd03403eee241479df19f011915419f14 | 18,140 |
def GetFootSensors():
"""Get the foot sensor values"""
# Get The Left Foot Force Sensor Values
LFsrFL = memoryProxy.getData("Device/SubDeviceList/LFoot/FSR/FrontLeft/Sensor/Value")
LFsrFR = memoryProxy.getData("Device/SubDeviceList/LFoot/FSR/FrontRight/Sensor/Value")
LFsrBL = memoryProxy.getData("De... | 555c5cb1f6e68571848410096144a3184d22e28a | 18,141 |
def norm(x, y):
"""
Calculate the Euclidean Distance
:param x:
:param y:
:return:
"""
return tf.sqrt(tf.reduce_sum((x - y) ** 2)) | 67766f9e3c3a510a87eff6bdea7ddf9ec2504af3 | 18,142 |
def expand_key(keylist, value):
"""
Recursive method for converting into a nested dict
Splits keys containing '.', and converts into a nested dict
"""
if len(keylist) == 0:
return expand_value(value)
elif len(keylist) == 1:
key = '.'.join(keylist)
base = dict()
... | ac8b4bac9b686396d5d117149fb45b8bde2ac238 | 18,143 |
def _linear_sum_assignment(a, b):
"""
Given 1D arrays a and b, return the indices which specify the permutation of
b for which the element-wise distance between the two arrays is minimized.
Args:
a (array_like): 1D array.
b (array_like): 1D array.
Returns:
array_like: Indi... | eeecff894e8bf29de66fa2560b8fdadbf3970d6d | 18,144 |
def get_ingredients_for_slice_at_pos(pos, frame, pizza, constraints):
"""
Get the slice of pizza with its ingredients
:param pos:
:param frame:
:param pizza:
:param constraints:
:return:
"""
def _get_ingredients_for_slice_at_pos(_pos, _frame, _pizza, _max_rows, _max_cols):
if... | db1083695d6f9503b3005e57db47c15ac761a31d | 18,145 |
def merge_data_includes(tweets_data, tweets_include):
"""
Merges tweet object with other objects, i.e. media, places, users etc
"""
df_tweets_tmp = pd.DataFrame(tweets_data)
# Add key-values of a nested dictionary in df_tweets_tmp as new columns
df_tweets = flat_dict(df_tweets_tmp)
for ... | db8e8560bdb80bd4a57d4f0d69031e944511633f | 18,146 |
def stringify(context, mapping, thing):
"""Turn values into bytes by converting into text and concatenating them"""
if isinstance(thing, bytes):
return thing # retain localstr to be round-tripped
return b''.join(flatten(context, mapping, thing)) | c4c4503160cab3ff6a78e2fb724fd283011ce0e7 | 18,147 |
import logging
import json
def extract_from_json(json_str, verbose=False):
"""A helper function to extract data from KPTimes dataset in json format
:param: json_str: the json string
:param: verbose: bool, if logging the process of data processing
:returns: the articles and keywords for each article
... | b05120eee45a887cee5eac68febffe96fcf8d305 | 18,148 |
def split_data(data, split_ratio, data_type=DATA_TYPE_1):
"""
split data by type
"""
data_type_1 = data[data['LABEL'] == data_type]
data_type_2 = data[data['LABEL'] != data_type]
train_set = data.sample(frac=split_ratio, replace=False)
test_set = data[~data.index.isin(train_set.index)]
... | 2653ea65bbc6fa2c7c0db9ab29890f57d5254d3f | 18,149 |
def sparse_amplitude_prox(a_model, indices_target, counts_target, frame_dimensions, eps=0.5, lam=6e-1):
"""
Smooth truncated amplitude loss from Chang et al., Overlapping Domain Decomposition Methods for Ptychographic Imaging, (2020)
:param a_model: K x M1 x M2
:param indices_target: K... | 9a2b7c0deb2eba58cebd6f7b2198c659c1915711 | 18,151 |
from typing import Dict
from typing import Any
from typing import List
def schema_as_fieldlist(content_schema: Dict[str, Any], path: str = "") -> List[Any]:
"""Return a list of OpenAPI schema property descriptions."""
fields = []
if "properties" in content_schema:
required_fields = content_schema... | b691e74ac36a0f3904bd317acee9b9344a440cdb | 18,152 |
def shrink(filename):
"""
:param filename: str, the location of the picture
:return: img, the shrink picture
"""
img = SimpleImage(filename)
new_img = SimpleImage.blank((img.width+1) // 2, (img.height+1) // 2)
for x in range(0, img.width, 2):
for y in range(0, img.height, 2):
... | fad3778089b0d5f179f62fb2a40ec80fd3fe37d1 | 18,153 |
def eh_menor_que_essa_quantidade_de_caracters(palavra: str, quantidade: int) -> bool:
"""
Função para verificar se a string é menor que a quantidade de caracters informados
@param palavra: A palavra a ser verificada
@param quantidade: A quantidade de caracters que deseja verificar
@return: Retorna T... | 827469606b0b93b78b63686465decbbbc63b9673 | 18,154 |
import rasterstats as rs
def buffer_sampler(ds,geom,buffer,val='median',ret_gdf=False):
"""
sample values from raster at the given ICESat-2 points
using a buffer distance, and return median/mean or a full gdf ( if return gdf=True)
Inputs = rasterio dataset, Geodataframe containing points, buffer dista... | 8efde64c0ee49b11e484fd204cf70ae5ae322bf9 | 18,155 |
import re
def extract_int(str, start, end):
""" Returns the integer between start and end. """
val = extract_string(str, start, end)
if not val is None and re.match('^[0-9]{1,}$', val):
return int(val)
return None | ec08c15592ea7e7ab9e4a0f476a97ba2127dda85 | 18,156 |
import re
def get_pg_ann(diff, vol_num):
"""Extract pedurma page and put page annotation.
Args:
diff (str): diff text
vol_num (int): volume number
Returns:
str: page annotation
"""
pg_no_pattern = fr"{vol_num}\S*?(\d+)"
pg_pat = re.search(pg_no_pattern, diff)
try:... | d9ca1a760f411352d8bcbe094ac622f7dbd33d07 | 18,157 |
def check_diamond(structure):
"""
Utility function to check if the structure is fcc, bcc, hcp or diamond
Args:
structure (pyiron_atomistics.structure.atoms.Atoms): Atomistic Structure object to check
Returns:
bool: true if diamond else false
"""
cna_dict = structure.analyse.pys... | ae082d6921757163cce3ddccbca15bf70621a092 | 18,158 |
from typing import Optional
from typing import Union
from typing import Dict
from typing import Any
from typing import List
from typing import Tuple
def compute_correlation(
df: DataFrame,
x: Optional[str] = None,
y: Optional[str] = None,
*,
cfg: Union[Config, Dict[str, Any], None] = None,
dis... | a8fb7f4e6cf34d584aba8e8fa9a7a7703fad8bad | 18,159 |
def radix_sort(arr):
"""Sort list of numberes with radix sort."""
if len(arr) > 1:
buckets = [[] for x in range(10)]
lst = arr
output = []
t = 0
m = len(str(max(arr)))
while m > t:
for num in lst:
if len(str(num)) >= t + 1:
... | 517ab99483ac1c6cd18df11dc1dccb4c502cac39 | 18,160 |
def resampling(w, rs):
"""
Stratified resampling with "nograd_primitive" to ensure autograd
takes no derivatives through it.
"""
N = w.shape[0]
bins = np.cumsum(w)
ind = np.arange(N)
u = (ind + rs.rand(N))/N
return np.digitize(u, bins) | 2f3d6ae173d5e0ebdfe36cd1ab6595af7452c191 | 18,162 |
import torch
def integrated_bn(fms, bn):
"""iBN (integrated Batch Normalization) layer of SEPC."""
sizes = [p.shape[2:] for p in fms]
n, c = fms[0].shape[0], fms[0].shape[1]
fm = torch.cat([p.view(n, c, 1, -1) for p in fms], dim=-1)
fm = bn(fm)
fm = torch.split(fm, [s[0] * s[1] for s in sizes]... | bee6d8782b372c0fb3990eefa42d51c6acacc29b | 18,163 |
def get_RF_calculations(model, criteria, calculation=None, clus="whole", too_large=None,
sgonly=False, regionalonly=False):
"""
BREAK DOWN DATA FROM CALCULATION!
or really just go pickle
"""
print(f'{utils.time_now()} - Criteria: {criteria}, calculation: {calculation}, clus: {clus}, sgonly: {sgonly}... | 34b44b3a525bd7cee562a63d689fc21d5a5c2a4a | 18,164 |
from plugin.helpers import log_plugin_error
import importlib
import pkgutil
def get_modules(pkg, recursive: bool = False):
"""get all modules in a package"""
if not recursive:
return [importlib.import_module(name) for finder, name, ispkg in iter_namespace(pkg)]
context = {}
for loader, name,... | 96c48ae86a01defe054e5a4fc948c2f9cfb05660 | 18,166 |
def TransformOperationHttpStatus(r, undefined=''):
"""Returns the HTTP response code of an operation.
Args:
r: JSON-serializable object.
undefined: Returns this value if there is no response code.
Returns:
The HTTP response code of the operation in r.
"""
if resource_transform.GetKeyValue(r, 'st... | e840575ccbe468e6b3bc9d5dfb725751bd1a1464 | 18,167 |
import warnings
def split_record_fields(items, content_field, itemwise=False):
"""
This functionality has been moved to :func:`split_records()`, and this is just
a temporary alias for that other function. You should use it instead of this.
"""
warnings.warn(
"`split_record_fields()` has be... | 256efc34bced15c5694fac2a7c4c1003214a54c5 | 18,168 |
import scipy
import numpy
def prony(signal):
"""Estimates amplitudes and phases of a sparse signal using Prony's method.
Single-ancilla quantum phase estimation returns a signal
g(k)=sum (aj*exp(i*k*phij)), where aj and phij are the amplitudes
and corresponding eigenvalues of the unitary whose phases... | 50bbcd05b1e541144207762052de9de783089bad | 18,170 |
def _check_alignment(beh_events, alignment, candidates, candidates_set,
resync_i, check_i=None):
"""Check the alignment, account for misalignment accumulation."""
check_i = resync_i if check_i is None else check_i
beh_events = beh_events.copy() # don't modify original
events = np.z... | e4508e90f11bb5b10619d19066a5fb51c36365b3 | 18,171 |
def user_info():
"""
个人中心基本资料展示
1、尝试获取用户信息
user = g.user
2、如果用户未登录，重定向到项目首页
3、如果用户登录，获取用户信息
4、把用户信息传给模板
:return:
"""
user = g.user
if not user:
return redirect('/')
data = {
'user': user.to_dict()
}
return render_template('blogs/user.html', data=da... | cb8d9c2081c8a26a82a451ce0f4de22fc1a43845 | 18,172 |
def build_config_tests_list():
"""Build config tests list"""
names,_,_,_ = zip(*config_tests)
return names | df190ec4926af461f15145bc25314a397d0be52b | 18,173 |
def annotate_filter(**decargs):
"""Add input and output watermarks to filtered events."""
def decorator(func):
"""Annotate events with entry and/or exit timestamps."""
def wrapper(event, *args, **kwargs):
"""Add enter and exit annotations to the processed event."""
funcna... | e1ce16e46f17948bdb1eae3ac8e5884fe6553283 | 18,175 |
def cplot(*args,**kwargs):
"""
cplot - Plot on the current graphe
This is an "alias" to gcf().gca().plot()
"""
return(gcf().gca().plot(*args,**kwargs)) | b7725569d19520c0e85f3a48d30800c3822cdac2 | 18,176 |
from datetime import datetime
def need_to_flush_metrics(time_now):
"""Check if metrics need flushing, and update the timestamp of last flush.
Even though the caller of this function may not successfully flush the
metrics, we still update the last_flushed timestamp to prevent too much work
being done in user ... | a2f50927a61eecee9448661f87f08a99caa4a22c | 18,177 |
def create_instances_from_lists(x, y=None, name="data"):
"""
Allows the generation of an Instances object from a list of lists for X and a list for Y (optional).
All data must be numerical. Attributes can be converted to nominal with the
weka.filters.unsupervised.attribute.NumericToNominal filter.
... | 310d72cb9fe5f65d85b19f9408e670426ebf7fdd | 18,179 |
def median_filter_(img, mask):
"""
Applies a median filer to all channels
"""
ims = []
for d in range(3):
img_conv_d = median_filter(img[:,:,d], size=(mask,mask))
ims.append(img_conv_d)
return np.stack(ims, axis=2).astype("uint8") | 2d7909b974572711901f84806009f237ecafaadf | 18,181 |
def replace_lines(inst, clean_lines, norm_lines):
"""
Given an instance and a list of clean lines and normal lines,
add a cleaned tier and normalized if they do not already exist,
otherwise, replace them.
:param inst:
:type inst: xigt.Igt
:param clean_lines:
:type clean_lines: list[dict... | 39f3fdcd40eafd32e071b54c9ab032104fba8c7c | 18,182 |
from pathlib import Path
def get_html(link: Link, path: Path) -> str:
"""
Try to find wget, singlefile and then dom files.
If none is found, download the url again.
"""
canonical = link.canonical_outputs()
abs_path = path.absolute()
sources = [canonical["singlefile_path"], canonical["wget_... | 3624e3df219cc7d6480747407ad7de3ec702813e | 18,183 |
def normalization(X,degree):
""" A scaling technique in which values
are shifted and rescaled so that they
end up ranging between 0 and 1.
It is also known as Min-Max scaling
----------------------------------------
degree: polynomial regression degree, or attribute/feature number
"""
... | 9cdef8b4b7e7a31523311ce6f4a668c6039ad2a1 | 18,184 |
def get_tags_from_match(child_span_0, child_span_1, tags):
"""
Given two entities spans,
check if both are within one of the tags span,
and return the first match or O
"""
match_tags = []
for k, v in tags.items():
parent_span = (v["start"], v["end"])
if parent_relation(child_... | c7ad037d2c40b6316006b4c7dda2fd9d02640f6e | 18,185 |
def _rfc822_escape(header):
"""Return a version of the string escaped for inclusion in an
RFC-822 header, by ensuring there are 8 spaces space after each newline.
"""
lines = header.split('\n')
header = ('\n' + 8 * ' ').join(lines)
return header | 1a3cd02b057742db00ed741c40947cf4e19d1a86 | 18,186 |
import socket
def getCgiBaseHref():
"""Return value for <cgiBaseHref/> configuration parameter."""
val = sciflo.utils.ScifloConfigParser().getParameter('cgiBaseHref')
if val is None:
val = "http://%s/sciflo/cgi-bin/" % socket.getfqdn()
return val | 62b5bc3d528c6db64ff8899c2847d2b0ecb4021d | 18,187 |
def dijkstra(gph: GraphState,
algo: AlgoState,
txt: VisText,
start: Square,
end: Square,
ignore_node: Square = None,
draw_best_path: bool = True,
visualize: bool = True) \
-> [dict, bool]:
"""Code for the dijkst... | cbc69734278e7ab4b0c609a1bfab5a9280bedee4 | 18,189 |
def nowIso8601():
"""
Returns time now in ISO 8601 format
use now(timezone.utc)
YYYY-MM-DDTHH:MM:SS.ffffff+HH:MM[:SS[.ffffff]]
.strftime('%Y-%m-%dT%H:%M:%S.%f%z')
'2020-08-22T17:50:09.988921+00:00'
Assumes TZ aware
For nanosecond use instead attotime or datatime64 in pandas or numpy
... | c5290e5a60f708f19d1cecf74c9cd927b4750ca3 | 18,191 |
def get_trip_data(tripdata_path, output_path, start=None, stop=None):
"""
Read raw tripdata csv and filter unnecessary info.
1 - Check if output path exists
2 - If output path does not exist
2.1 - Select columns ("pickup_datetime",
"passenger_coun... | 3aca0b89d1e747ae1ea3e5ea9f3fa0d63a5b9447 | 18,192 |
import urllib
def _qparams2url(qparams):
"""
parse qparams to make url segment
:param qparams:
:return: parsed url segment
"""
try:
if qparams == []:
return ""
assert len(qparams) == 4
num = len(qparams[0][1])
path=""
for i in range(num):
... | ac416dd0dac87210fef5aa1bea97a60c84df60cf | 18,193 |
import itertools
def confusion_matrix(y_pred: IntTensor,
y_true: IntTensor,
normalize: bool = True,
labels: IntTensor = None,
title: str = 'Confusion matrix',
cmap: str = 'Blues',
show: bool =... | 744642cde03696f6ecbccc6f702e3f9a3cb67451 | 18,194 |
def from_smiles(smiles: str) -> Molecule:
"""Load a molecule from SMILES."""
return cdk.fromSMILES(smiles) | a5315eeb9ffadff16b90db32ca07714fe1573cda | 18,195 |
from typing import Dict
from typing import Any
def parse_template_config(template_config_data: Dict[str, Any]) -> EmailTemplateConfig:
"""
>>> from tests import doctest_utils
>>> convert_html_to_text = registration_settings.VERIFICATION_EMAIL_HTML_TO_TEXT_CONVERTER # noqa: E501
>>> parse_template_con... | adea58fd8e8a16ec4fd48ef68aa2ff1c6356bd0d | 18,196 |
import json
def stringify_message(message):
"""Return a JSON message that is alphabetically sorted by the key name
Args:
message
"""
return json.dumps(message, sort_keys=True, separators=(',', ':')) | ccd51481627449345ba70fbf45d8069deca0f064 | 18,197 |
import numpy as np
def compute_similarity_transform(X, Y, compute_optimal_scale=False):
"""
A port of MATLAB's `procrustes` function to Numpy.
Adapted from http://stackoverflow.com/a/18927641/1884420
Args
X: array NxM of targets, with N number of points and M point dimensionality
Y: a... | 10da3df241ec140de86b2307f9fc097b4f926407 | 18,198 |
def simplefenestration(idf, fsd, deletebsd=True, setto000=False):
"""convert a bsd (fenestrationsurface:detailed) into a simple
fenestrations"""
funcs = (window,
door,
glazeddoor,)
for func in funcs:
fenestration = func(idf, fsd, deletebsd=deletebsd, setto000=setto000)
i... | b72e73a22756e80981d308b54037510354a5d327 | 18,199 |
from typing import TextIO
from typing import Set
def observe_birds(observations_file: TextIO) -> Set[str]:
"""Return a set of the bird species listed in observations_file, which has one bird species per line.
>>> file = StringIO("bird 1\\nbird 2\\nbird 1\\n")
>>> birds = observe_birds(file)
>>> 'bird... | e3ea90e8da4488121ec1ae75c4aa116646db08f5 | 18,200 |
def convert_sheet(sheet, result_dict, is_enum_mode=False):
"""
转换单个sheet的数据
Args:
sheet: openpyxl.worksheet.worksheet.Worksheet
result_dict: [dict]结果都存在这里, key为data_name，value为sheet_result
is_enum_mode: [bool]是否为enum导表模式
Returns:
bool, 是否成功
"""
if is_enum_mode:
... | 284f470844b6722941d0e4725e4c23b1473b08df | 18,201 |
def bytes_to_int(b: bytes, order: str = 'big') -> int:
"""Convert bytes 'b' to an int."""
return int.from_bytes(b, order) | c959683787e03cc956b5abffc814f98cf4722397 | 18,203 |
def fit_model(params,param_names,lam_gal,galaxy,noise,gal_temp,
feii_tab,feii_options,
temp_list,temp_fft,npad,line_profile,fwhm_gal,velscale,npix,vsyst,run_dir,
fit_type,output_model):
"""
Constructs galaxy model by convolving templates with a LOSVD given by
a specified set of velocity parameters.
... | 44cd0bc61a4472c6a5c3c7b190ee5be96f4bdb1a | 18,204 |
import random
def generate_numbers():
"""
Function to generate 3 random digits to be guessed.
Generate 3 random in a list in order to be compare to the user's digits.
Return:
str_digits (Array): List with 3 random digits converted to String
"""
# List comprehension to generate num... | 8efd0f579a3a0b3dc5021cd762f9ad2f5774f6be | 18,205 |
def get_media():
"""Retrieves metadata for all of this server's uploaded media. Can use
the following query parameters:
* max: The maximum number of records to return
* page: The page of records
"""
error_on_unauthorized()
media = Upload.query.order_by(Upload.id)
total_num = media.cou... | 754417b47f5b9c28427b04ace88bf9ca5c9a5a47 | 18,206 |
def summate2(phasevec):
"""Calculate values b'(j^vec) for combining 2 phase vectors.
Parameter:
phasevec: tuple of two phasevectors
Example:
On input (([b_1(0),b_1(1),...,b_1(L-1)], L), ([b_2(0),b_2(1),...,b_2(L'-1)], L'))
give output [b_1(0)+b_2(0), b_1(0)+b_2(1),..., b_1(1)+b_2(0),...,b_1(L-... | 5150c2ee29a31438bf16104eaadeb85a01f54502 | 18,207 |
def makeTracker( path, args = (), kwargs = {} ):
"""retrieve an instantiated tracker and its associated code.
returns a tuple (code, tracker).
"""
obj, module, pathname, cls = makeObject( path, args, kwargs )
code = getCode( cls, pathname )
return code, obj | bc23e21bb53357bcf74e6194656cfbea4b24c218 | 18,209 |
from typing import Tuple
def get_anchor_generator(anchor_size: Tuple[tuple] = None, aspect_ratios: Tuple[tuple] = None):
"""Returns the anchor generator."""
if anchor_size is None:
anchor_size = ((16,), (32,), (64,), (128,))
if aspect_ratios is None:
aspect_ratios = ((0.5, 1.0, 2.0),) * le... | e9eef959c009062d5866558d00674c1afa033260 | 18,210 |
import torch
def tensor_to_longs(tensor: torch.Tensor) -> list:
"""converts an array of numerical values to a tensor of longs"""
assert tensor.dtype == torch.long
return tensor.detach().cpu().numpy() | ba1788be8e353936cfc3d604d940b78a96990fd4 | 18,211 |
def test_fixed(SNRs):
"""
Fixed (infinite T1) qubit.
"""
fidelities = []
numShots = 10000
dt = 1e-3
for SNR in SNRs:
fakeData = create_fake_data(SNR, dt, 1, numShots, T1=1e9)
signal = dt*np.sum(fakeData, axis=1)
fidelities.append(fidelity_est(signal))
return fidelities | 70ca68f475beed73a47722c719811544ae1bfccb | 18,212 |
def setup(app):
"""
Add the ``fica`` directive to the Sphinx app.
"""
app.add_directive("fica", FicaDirective)
return {
"version": __version__,
"parallel_read_safe": True,
"parallel_write_safe": True,
} | 996e568ab58634e64a845b34bf38082658b58889 | 18,213 |
from typing import Tuple
import torch
def get_binary_statistics(
outputs: Tensor, targets: Tensor, label: int = 1,
) -> Tuple[Tensor, Tensor, Tensor, Tensor, Tensor]:
"""
Computes the number of true negative, false positive,
false negative, true negative and support
for a binary classification pro... | e0c81b404f6da77f40c1e4f3810d699fdef1e6a4 | 18,214 |
def threshold_and_mask(min_normed_weight, W, Mc, coords): # =np.arange(Wc.shape[0])*stride + start):
"""Normalize the weights W, threshold to min_normed_weight and remove diagonal,
reduce DX and DY to the columns and rows still containing weights.
Returns
-------
coords : array_like
the in... | 78d361cf2125cd0d3ac1a3985933e39b09538b18 | 18,215 |
import csv
def readCGcsv(filename, levels):
""" Read a .csv file of a callgraph into a dictionary keyed by callgraph level. """
cgdict = {}
with open(filename, "r") as cgcsv:
cgreader = csv.DictReader(cgcsv)
for row in cgreader:
lvl = int(row['Level'])
if (lvl < l... | ec5dbc3d064a0cf784bfd764b996eb36677642a9 | 18,216 |
def use_colors(tones, i=None):
"""
Use specific color tones for plotting. If i is specified, this function returns a specific color from the corresponding color cycle
For custom color palettes generation check: http://colorbrewer2.org/#type=sequential&scheme=YlGnBu&n=8
Args:
tones : 'hot' or 'co... | e36cce208c89178af8199662edb336c2455bdc37 | 18,217 |
def fill_form(forms, form):
"""Fills a given form given a set or known forms.
:param forms: A set of known forms.
:param form: The form to fill.
:return: A mapping from form element IDs to suggested values for the form.
"""
forms = list(forms)
new_form = {}
def rec_fill_form(form, lab... | 3e6c1f623facb67602fa5e057080a08d0de9926d | 18,218 |
def integer_to_vector(x, options_per_element, n_elements, index_to_element):
"""Return a vector representing an action/state from a given integer.
Args:
x (int): the integer to convert.
n_options_per_element(int): number of options for each element in the vector.
n_elements (int): the n... | 2649359d6a62b047f70bfe72f8403e8343a231ab | 18,220 |
def samples_for_each_class(dataset_labels, task):
"""
Numbers of samples for each class in the task
Args:
dataset_labels Labels to count samples from
task Labels with in a task
Returns
"""
num_samples = np.zeros([len(task)], dtype=np.float32)
i = 0
for label ... | 96bc2c794fd955110864f59ddb96c5df1c33b8ed | 18,221 |
def requiredOneInGroup(col_name, group, dm, df, *args):
"""
If col_name is present in df, the group validation is satisfied.
If not, it still may be satisfied, but not by THIS col_name.
If col_name is missing, return col_name, else return None.
Later, we will validate to see if there is at least one... | de46a4ef2f3e45381644db41d617d8c4c0845877 | 18,222 |
def persist(session, obj, return_id=True):
"""
Use the session to store obj in database, then remove obj from session,
so that on a subsequent load from the database we get a clean instance.
"""
session.add(obj)
session.flush()
obj_id = obj.id if return_id else None # save this before obj i... | a308931f418616417d10d3115b0f370352778533 | 18,223 |
from unittest.mock import patch
def test_bittrex_query_asset_movement_int_transaction_id(bittrex):
"""Test that if an integer is returned for bittrex transaction id we handle it properly
Bittrex deposit withdrawals SHOULD NOT return an integer for transaction id
according to their docs https://bittrex.gi... | 83e3ce3d8f82b159191c6b9068b54321d06bfa9a | 18,224 |
from operator import sub
def masker(mask, val):
"""Enforce the defined bits in the <mask> on <val>."""
ones = sub(r"[^1]", "0", mask)
val |= int(ones,2)
zeros = sub(r"[^0]", "1", mask)
val &= int(zeros,2)
return val | 68b3edd542b295ca7aade0eb9829e310e4c0ed2d | 18,226 |
def ct_lt_u32(val_a, val_b):
"""
Returns 1 if val_a < val_b, 0 otherwise. Constant time.
:type val_a: int
:type val_b: int
:param val_a: an unsigned integer representable as a 32 bit value
:param val_b: an unsigned integer representable as a 32 bit value
:rtype: int
"""
val_a &= 0xf... | 6816fd1e9633c0c3035d68ac657f3cb917f24527 | 18,227 |
import typing
async def is_banned(ctx: Context, user: typing.Union[discord.Member, discord.User]) -> bool:
"""Returns true if user is in guild's ban list."""
bans = await ctx.guild.bans()
for entry in bans:
if entry.user.id == user.id:
return True
return False | 2807e2d9a296afb360efe9abf9618e0ebe19e796 | 18,228 |
from typing import List
def _create_transformation_vectors_for_pixel_offsets(
detector_group: h5py.Group, wrapper: nx.NexusWrapper
) -> List[QVector3D]:
"""
Construct a transformation (as a QVector3D) for each pixel offset
"""
x_offsets = wrapper.get_field_value(detector_group, "x_pixel_offset")
... | 1504193d1a7731740a607f77c94a810561142c57 | 18,229 |
import random
def buildIterator(spec_name, param_spec, global_state, random_selection=False):
"""
:param param_spec: argument specification
:param random_selection: produce a continuous stream of random selections
:return: a iterator function to construct an iterator over possible values
"""
i... | d86d2af9499117614a11796c17eeccba16149092 | 18,230 |
def outlier_removal_mean(dataframe, colname, low_cut, high_cut):
"""Replace outliers with the mean on dataframe[colname]"""
col = dataframe[colname]
col_numerics = col.loc[
col.apply(
lambda x: isinstance(x, (int, float))
and (x >= low_cut and x <= high_cut)
)
]... | 03d40bb8098d4313e468d5b4a929756354a7732c | 18,232 |
def non_repeating(value, counts, q):
"""Finds the first non-repeating string in a stream.
Args:
value (str): Latest string received in the string
counts (dict): Dictionary of strings containing the counts to determine if string is repeated
q (Queue): Container for all strings in stream ... | fc5ec025cffa0d7230d814d3677ae640cd652349 | 18,233 |
def auth_optional(request):
"""
view method for path '/sso/auth_optional'
Return
200 reponse: authenticated and authorized
204 response: not authenticated
403 reponse: authenticated,but not authorized
"""
res = _auth(request)
if res:
#authenticated, but can be aut... | 06416fdce6a652ca0cdc169c48219e685c13cdad | 18,234 |
def is_pip_main_available():
"""Return if the main pip function is available. Call get_pip_main before calling this function."""
return PIP_MAIN_FUNC is not None | 3d4243bb4336fbc9eb9e93b2a1cf9ec4cc129c03 | 18,235 |
import torch
def energy_target(flattened_bbox_targets, pos_bbox_targets,
pos_indices, r, max_energy):
"""Calculate energy targets based on deep watershed paper.
Args:
flattened_bbox_targets (torch.Tensor): The flattened bbox targets.
pos_bbox_targets (torch.Tensor): Bounding... | 84bed4cc1a8bf11be778b7e79524707a49482b39 | 18,236 |
def dashtable(df):
"""
Convert df to appropriate format for dash datatable
PARAMETERS
----------
df: pd.DataFrame,
OUTPUT
----------
dash_cols: list containg columns for dashtable
df: dataframe for dashtable
drop_dict: dict containg dropdown list for dashtable
"""
... | 39897244f81a5c6ac0595aac7cb219f59d6c5739 | 18,237 |
def other_identifiers_to_metax(identifiers_list):
"""Convert other identifiers to comply with Metax schema.
Arguments:
identifiers_list (list): List of other identifiers from frontend.
Returns:
list: List of other identifiers that comply to Metax schema.
"""
other_identifiers = []... | 986c98d5a557fb4fb75ed940d3f39a9a0ec93527 | 18,238 |
def enforce_excel_cell_string_limit(long_string, limit):
"""
Trims a long string. This function aims to address a limitation of CSV
files, where very long strings which exceed the char cell limit of Excel
cause weird artifacts to happen when saving to CSV.
"""
trimmed_string = ''
... | 9b8bcf4590dc73425c304c8d778ae51d3e3f0bf3 | 18,239 |
def gaussian_blur(image: np.ndarray, sigma_min: float, sigma_max: float) -> np.ndarray:
"""
Blurs an image using a Gaussian filter.
Args:
image: Input image array.
sigma_min: Lower bound of Gaussian kernel standard deviation range.
sigma_max: Upper bound of Gaussian kernel standard ... | 2fd31d016e4961c6980770e8dd113ae7ad45a6ed | 18,240 |
def get_number_of_pcs_in_pool(pool):
"""
Retrun number of pcs in a pool
"""
pc_count = Computer.objects.filter(pool=pool).count()
return pc_count | 812de24ad2cbc738a10258f8252ca531ef72e904 | 18,241 |
from typing import List
def get_used_http_ports() -> List[int]:
"""Returns list of ports, used by http servers in existing configs."""
return [rc.http_port for rc in get_run_configs().values()] | 12982ff4d5b2327c06fef1cf874b871e2eee08c1 | 18,243 |
import io
def get_img_from_fig(fig, dpi=180, color_cvt_flag=cv2.COLOR_BGR2RGB) -> np.ndarray:
"""Make numpy array from mpl fig
Parameters
----------
fig : plt.Figure
Matplotlib figure, usually the result of plt.imshow()
dpi : int, optional
Dots per inches of the image to save. Note... | dde9f35b78df436b30d4f9452b9964c93f924252 | 18,244 |
def split_data_by_target(data, target, num_data_per_target):
"""
Args:
data: np.array [num_data, *data_dims]
target: np.array [num_data, num_targets]
target[i] is a one hot
num_data_per_target: int
Returns:
result_data: np.array [num_data_per_target * num_targets... | d4425753b4d9892d2c593ec8e58e75bae0005c3d | 18,245 |
def top_mutations(mutated_scores, initial_score, top_results=10):
"""Generate list of n mutations that improve localization probability
Takes in the pd.DataFrame of predictions for mutated sequences and the
probability of the initial sequence. After substracting the initial value
from the values of the... | f574bf7f7569e3024a42866873c5bb589ff02095 | 18,246 |
def npmat4_to_pdmat4(npmat4):
"""
# updated from cvtMat4
convert numpy.2darray to LMatrix4 defined in Panda3d
:param npmat3: a 3x3 numpy ndarray
:param npvec3: a 1x3 numpy ndarray
:return: a LMatrix3f object, see panda3d
author: weiwei
date: 20170322
"""
return Mat4(npmat4[0, 0],... | 7b58014d5d354aefac84786212b6ca190a983e48 | 18,247 |
import requests
def is_at_NWRC(url):
"""
Checks that were on the NWRC network
"""
try:
r = requests.get(url)
code = r.status_code
except Exception as e:
code = 404
return code==200 | b909a9087940eb70b569ea6c686ff394e84a6ed9 | 18,248 |
import torch
def lmo(x,radius):
"""Returns v with norm(v, self.p) <= r minimizing v*x"""
shape = x.shape
if len(shape) == 4:
v = torch.zeros_like(x)
for first_dim in range(shape[0]):
for second_dim in range(shape[1]):
inner_x = x[first_dim][second_dim]
... | 24bda333cdd64df9a0b4fa603211036bbdad7200 | 18,249 |
def _transform_index(index, func):
"""
Apply function to all values found in index.
This includes transforming multiindex entries separately.
"""
if isinstance(index, MultiIndex):
items = [tuple(func(y) for y in x) for x in index]
return MultiIndex.from_tuples(items, names=index.na... | c642dd9330032ed784224b7ede6ee299b6d3ed67 | 18,250 |
def extractQualiTeaTranslations(item):
"""
# 'QualiTeaTranslations'
"""
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp or vol or frag) or 'preview' in item['title'].lower():
return None
if 'Harry Potter and the Rise of the Ordinary Person' in item['tags']:
return None
i... | 446b7f7598e118222c033bbfce074fa02340fd8e | 18,251 |
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