content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def getInversePermutation(permutation):
"""Invert a given permutation vector.
:param list | tuple | np.ndarray permutation: Permutation vector to invert.
:return: Inverted permutation vector.
:rtype: list
"""
inverse = [0] * len(permutation)
for i, p in enumerate(permutation):
inve... | f8fe339f2b0a7fc8180252b99f3fce742f215a13 | 77,135 |
def number2latex(val, **kwargs):
""" Converts a number into a representation nicely displayed by latex """
if val.__class__.__name__ == 'Quantity':
# assume it is a pint quantity
if kwargs.pop('long_unit', False):
unit = "\\,{:L}".format(val.units)
else:
unit = "... | eddd772ff8c345a6925db820d523f9a9da7ed34f | 77,136 |
def Emojify_V2(input_shape, word_to_vec_map, word_to_index):
"""
Function creating the Emojify-v2 model's graph.
Arguments:
input_shape -- shape of the input, usually (max_len,)
word_to_vec_map -- dictionary mapping every word in a vocabulary into its 50-dimensional vector representation
wo... | b2e8181e54c18618450b13e1182d6d5ea1144b42 | 77,137 |
import logging
def create_logger():
"""
Creates a log in Stackdriver
"""
instance_name = get_hostname()
logname = '%s.log' % instance_name
logging_client = logging.Client()
logger = logging_client.logger(logname)
return logger | 9cef87ed4d1fecb93e398b0265b20ae97e55d93b | 77,138 |
def partitionByParentGeocode(block_nodes, num_partitions=None):
""" Partition an RDD of geonodes by parent geocode """
return block_nodes \
.map(lambda node: (node.parentGeocode, node)) \
.partitionBy(num_partitions, lambda k: int(k) if len(k)>0 else 0) \
.map(lambda d: (lambda parent_co... | 7792125722611c29e4e7af21e8d98ebfb4a81722 | 77,141 |
def get_minmax(g):
"""
Calculate the min and max of the Golly toroid coordinates.
"""
# get height and width
g_xspan = g.getwidth()
g_yspan = g.getheight()
# calculate min and max
g_xmin = - int(g_xspan / 2)
g_xmax = g_xspan + g_xmin
g_ymin = - int(g_yspan / 2)
g_ymax = g_yspan + g_ymin
#
retu... | 00563db83a538483b2b6d5d8f0be0617d2322ea6 | 77,142 |
def create_api():
"""return api object at startup"""
api = Api()
api.add_resource(Relay, '/')
return api | 7089df0e6a2be80b009b94320bb2c2263be684e8 | 77,143 |
import scipy
def _kolmogn(n, x, cdf=True):
"""Computes the CDF(or SF) for the two-sided Kolmogorov-Smirnov statistic.
x must be of type float, n of type integer.
Simard & L'Ecuyer (2011) [7].
"""
if np.isnan(n):
return n # Keep the same type of nan
if int(n) != n or n <= 0:
... | eaff5775f3d8d1aea192fff3653aed4094e78112 | 77,144 |
def apply_density_loss(rho, n, m, eta):
"""Applies loss to an input density matrix and traces out loss modes
rho: density matrix over lossy basis (including zero state)
n: number of photons
m: number of modes
eta: power loss (i.e. transmission = 1-eta; t=sqrt(1-eta))
Returns density matrix of sa... | 15942f984a46232d9b9720624a9bb382adc02fb4 | 77,146 |
from typing import Union
from typing import IO
from typing import AnyStr
from typing import List
def _flatsaxParse(fl: Union[FilePath, IO[AnyStr], str]) -> List["Flattenable"]:
"""
Perform a SAX parse of an XML document with the _ToStan class.
@param fl: The XML document to be parsed.
@return: a C{l... | f87526292681735ca4557e1ee57790690f959f9c | 77,147 |
def is_image(content_type):
"""is the given content_type string for an image?
Args:
content_type: string containing Content-Type HTTP header value
Returns:
Boolean
"""
return (str(content_type).count("image") > 0) | c69f163e09d8b68e179dd8765ef8401d988ac433 | 77,148 |
def eventLists():
# REPLICATED: utils/botHelperFunctions eventLists()
"""
Load defined event names
Returns
-------
searchEV : list of strings (event names)
Just grabs every event defined in the file in
(hardcoded) `keyEventDB` str varible
as of this, that file is listO... | b8e7eb6f069868558dc29f75b10b162c209ea2ce | 77,149 |
def lu_compact(A):
"""
This performs LU Decomposition on `A`
"""
assert A.shape[0] == A.shape[1]
U = A.astype(np.float64)
n = A.shape[0]
L = np.eye(n).astype(np.float64)
for k in range(n - 1):
for j in range(k + 1, n):
L[j, k] = U[j, k] / U[k, k]
U[j, k:... | ab76c19e4974d0e11036f37551c85f0addd2078c | 77,150 |
def mkcomboentry(prompt, row, table, options):
"""Create and return a combo entry within a gtk table."""
l = gtk.Label(prompt)
l.set_alignment(1.0, 0.5)
l.show()
table.attach(l, 0, 1, row, row+1, gtk.FILL, gtk.FILL, xpadding=5)
c = gtk.combo_box_new_text()
c.show()
for opt in options:
... | 09b60bce908ded14f0992dd6d62567643cc69e32 | 77,151 |
def _calcEndPointSep(fiberData, fidx):
""" * INTERNAL FUNCTION *
Calculates distance between end points
INPUT:
fiberData - fiber tree containing tractography information
fidx - fiber index
OUTPUT:
D - distance between end points
"""
endpt = fiberData.pts_per_fiber - 1
... | 360799ceb13412d3eddf75b84c74ee0b850c9f2e | 77,152 |
import numpy
def matrix_multiply(m1,m2):
"""
Multiplies the input matrices.
Inputs:
m1,m2: the input matrices
Returns:
result: matrix product of m1 and m2
in a list of floats
"""
product = numpy.matmul(m1,m2)
if type(product) == numpy.int64:
return float(pro... | 0447553f7fa7968cbb13fcaf7319391650377e49 | 77,153 |
def parse_and_append_solute_data(solute_data, solute_data_results, solute_estimator, solute_epi_unc_dict):
"""
Parse and append the `solute_data` to the `solute_data_results` dictionary.
If `solute_epi_unc_dict` is given, it is also parsed and appended to the `solute_data_results` dictionary.
It also re... | 04410d96139813b1a9c1a758796b33dc4a105a56 | 77,154 |
import base64
def read_encoded(filename: str) -> str:
"""Read a file and return the base64 encoding of its contents."""
with open(filename, 'rb') as infile:
return base64.b64encode(infile.read()).decode('utf-8') | 4d2c5c8f36b2ebe67a67714f6313a32d4d6bf005 | 77,155 |
def dihedral(a, b, c, d):
"""
Calculate the A - B - C - D dihedral angle in radians.
For collinear or close to collinear structures return a warning.
"""
collinear = 0
if abs(abs(angle(a, b, c)) - 180.) < 5. or abs(abs(angle(b, c, d)) - 180.) < 5.:
collinear = 1
b0 = a -... | de935d41deb4424df9193f3c27a93c8297155241 | 77,156 |
def entity_types(request):
"""View to display a list of all the entity types."""
entity_types = EntityTypeList.objects.all()
context_data = {'entity_types': entity_types}
return render(request, 'eats/view/entity_types.html', context_data) | fe9f573523cefc3c2e7c808c03d693b30ee6e3c4 | 77,157 |
def fetch_electricity(data_home=None, silent=True):
"""A day of electricity prices in New South Wales.
The data contains 45,312 items and 8 features. The goal is to predict whether the price of
electricity will go up or down at very frequent intervals.
Parameters:
data_home (str): The director... | 3152648c397a0b69c86a3969f7ddf32573e991ce | 77,158 |
import re
def strip_irc_colors(data):
"""Strip mirc colors from string. Expects data to be decoded."""
return re.sub('[\x02\x0F\x16\x1D\x1F]|\x03(\d{1,2}(,\d{1,2})?)?', '', data) | 2c4e480cc00e3704a0086522c8bb7409fca0af6e | 77,159 |
from typing import Optional
async def get_character_ids_from_class(profile: DestinyAccount, destiny_class: str) -> Optional[list[int]]:
"""Return the users character_ids that fit the given class or None"""
result = await profile.get_character_info()
if not result:
return
# loop through the ... | d8426b4b80154a3d49f464da702c2018ec3ebf6b | 77,160 |
def direct_unordered_attachments(t, m):
"""Enumerate the ways of directly attaching t unlabelled free nodes to l
unlabelled nodes."""
return IntegerPartitions.fixed_length_partitions(t+m, m) | 82abe1382c5adb59c2d2554cfaefa60e887906a3 | 77,161 |
def deeplift(score_func, X, batch_size=200,task_idx=0, num_refs_per_seq=10,reference="shuffled_ref",one_hot_func=None):
"""
Arguments:
score_func -- deepLIFT scoring function
X -- numpy array with shape (n_samples, 1, n_bases_in_sample,4) or list of FASTA sequences
batch_size -- numbe... | 4452e0127dea0d335384a200431dbe493f958fab | 77,162 |
from typing import List
def get_main_corpus() -> List[str]:
"""Returns the list of tweets (content as text) to consider as the main corpus"""
return list(set(get_text_from_all_tweets(city="Caracas"))) | a1b94404bd340a6513b912f9229c2db2e2f9f48f | 77,163 |
def get_labels(n_rows=15, seed=None):
"""
Generates a random vector of labels.
"""
np.random.seed(seed)
return np.random.randint(0, 2, size=(n_rows,)) | 4265c48e3dfb4dafc17358f772bc7a04d3c01ba2 | 77,164 |
def _rotate_mirror_do(im):
"""
Duplicate an np array (image) of shape (x, y, nb_channels) 8 times, in order
to have all the possible rotations and mirrors of that image that fits the
possible 90 degrees rotations.
It is the D_4 (D4) Dihedral group:
https://en.wikipedia.org/wiki/Dihedral_group
... | ffd88b473f120b9893add90031bfc4e841e60b2f | 77,165 |
def do_cavity_freq_sweep(cavity, localos, cavity_freq, acq_ctrl,
cavity_pm=10e6, freq_step=1e6, demod_freq=None,
delay=0.01, do_plots=True):
"""
Function which sweeps the cavity frequency around central value by pm_range
and measures using given acq_ctr, als... | 95a8bc3296f4b847343575cfd8123dc873f54212 | 77,166 |
import warnings
def normalize(av, vmin=0., vmax=1.):
"""
normalize an array to the range vmin/vmax
"""
if vmin == vmax:
return np.ones_like(av)*vmin
elif vmax < vmin:
warnings.warn("swapping vmin and vmax, because vmax < vmin.")
vmin, vmax = vmax, vmin
norm_one = (av -... | 4db466fdb00f01d6846c1e13f6bbc4fee21db4bc | 77,168 |
def PurgeWorkOrder(work_order_file: str, **kwargs):
"""
Simply resets an existing work order to status 0 by rewriting it
:param str work_order_file: file path to a work order file
:param kwargs: varios parameters taht all get ignored. Just there for compatiblity reasons
:return: True if file writing... | 1548b4bebc223b13221591ca9f5dd24b47ecf1a3 | 77,169 |
def normalised_ellipse_mask(ellipse):
"""Return a normalized copy of the supplied ellipse.
Here 'normalised' means that the rotation is as close to zero as possible.
Examples:
>>> normalised_ellipse_mask(
... ((1, 2), (100, 200), 90)
... )
((1, 2), (200, 100), 0)
""... | af5316ace76642667340a986f3d1c2d69934a333 | 77,170 |
def circular_velocity(k, a):
"""Circular velocity for a given body (k) and semimajor axis (a)."""
return circular_velocity_fast(k.to_value(u_km3s2), a.to_value(u.km)) * u_kms | d692ab405718a1edc98dfa02b2490b0ce8a8e09e | 77,171 |
import math
def format_bytes(size, precision=2, max_units=True, with_units=True):
"""
Returns a formatted byte size (e.g. "421.45 MB" or "421,451,273 bytes").
@param precision number of decimals to leave after converting to
maximum units
@param max_units whether to co... | c1671e5f131341e2823725c5c5e33c648c8a039e | 77,172 |
def line_distance(line1, line2, image_shape):
"""calculate a distance score between two lines"""
# find the intersection of line 1 with the edges of the image
line1_image = line_segment_within_image(line1, image_shape)
n_points = 10
sample_points = np.arange(0, n_points) / (n_points - 1.0)
l... | a59e4537c8278a4c2526312df049e224e1de9f85 | 77,173 |
from functools import reduce
def xor(*values):
"""An `exclusive or`_ operation on a list of values.
.. _exclusive or: https://en.wikipedia.org/wiki/Exclusive_or
:rtype: bool
:returns: ``True`` when an odd number of values are ``True`` or ``False`` when an even number of values are
``Tr... | d5dfbff2648f208dc192fd06da0c988c6bb9baaf | 77,174 |
def probability_of_sum(total:int, dice1, dice2):
"""
Brief:
Basic probability - Dice cast
Suppose a pair of fair 6-sided dice are thrown.
What is the probability that the sum of the rolls is 6? (Answer as a simple fraction of integers)
reference: https://statweb.stanford.edu/~susan/courses/s6... | b48e9db4dd40048d24a3dfb481406346076b7132 | 77,175 |
def get_source_with_id(result):
"""Return a document's `_source` field with its `_id` added.
Parameters
----------
result : dict
A document from a set of Elasticsearch search results.
Returns
-------
dict
The document's `_source` field updated with the doc's `_id`.
"""... | be9b25ad65a8474aa41d3f927664abdb89a674d5 | 77,176 |
def kmeans_pc_clustering(hgt_anom, n_modes=20, n_clusters=4,
lat_name=None, lon_name=None,
time_name=None, **kwargs):
"""Perform k-means clustering of leading PCs.
Parameters
----------
hgt_anom : xarray DataArray
Array containing geopotential h... | 3df5c0be37da20d16c598bdcf75a9d755a617b15 | 77,177 |
def apply_x_frame(response):
"""Include X-frame header in http response to protect against clickhiJacking."""
response.headers["X-Frame-Options"] = "SAMEORIGIN"
return response | 3cc3b572eb64e856512fd8b41191f601bcbcc96c | 77,178 |
def coef_domain2(an1_mid, bn1_mid, an2_mid, bn2_mid, random_start=1, halfwidth0=1, pow=-1):
"""
return the parameter domain centered at the an1, bn1, an2, bn2
"""
domain1 = coef_domain(an1_mid, bn1_mid, random_start=random_start, halfwidth0=halfwidth0, pow=pow)
domain2 = coef_domain(an2_mid, bn2_mid... | 2b45e1b53d7597570af87544b6b27726e415bd21 | 77,179 |
def get_RoI_features(model, features, proposals, with_shared_fcs=False, only_cls_scores=False):
""" Extract features from either the RoI pooling layers or shared Fully-connected layers
or directly return the class_scores from the final class predictor itself.
Args:
model (nn.Module): The loaded dete... | 81c271f505be60e6662a50e4d03e569e59d623b1 | 77,180 |
import token
def get_node_output(cid,nid):
"""Get the latest node output."""
data={"api_token": token,
"api_email": user,
"c": "get_node_output",
"cid": cid,
"nid": nid}
resp = flowr.POST(headers = standard_headers, data=data)
# returns JSON formatted ... | d9db51f278ffacb9c067f46075aa0ec9c097e581 | 77,181 |
def create_rest_client(server, retry_multiplier, retry_max_exp, retry_stop, verbose):
"""
Create a RestClient with retry config set from command line options.
"""
if verbose:
log("Connecting to Entity Matching Server: {}".format(server))
retry_config = ClientWaitingConfiguration(retry_multip... | c1bee6f7abbdf8caff8ba5ef4ef8722b9786dd12 | 77,182 |
def multiply_probs(ln_pa, ln_pb):
"""
Returns the log probability of multiplied probabilities.
Pc = Pa * Pb => ln(Pc) = ln(Pa)+ln(Pb)
"""
return ln_pa+ln_pb | 5e541072c9aaf327536196ab4ffc9e3bf488ccf0 | 77,183 |
def tapping_XY(ref, pre_l1_tap_flat, pre_l0_tap_flat, prerr_l0_tap_flat, prerr_l0__, mode = 'm1'):
"""block_models.tapping_XY
Tap data from the sensorimotor data stream and build a supervised
training set of inputs X and targets Y suitable for machine
learning algorithms.
"""
# print "tapping p... | 8ec6bbcd2a0448d50c8a1d5564aaef7c9ff0ec1d | 77,185 |
def _Run(args, holder):
"""Issues requests necessary to list service attachments."""
client = holder.client
request_data = lister.ParseRegionalFlags(args, holder.resources)
list_implementation = lister.RegionalLister(
client, client.apitools_client.serviceAttachments)
return lister.Invoke(request_data... | e7714d6c4846e3410fb822cf902cccdf02b833f8 | 77,186 |
def update_user(uid, **kwargs): # pylint: disable=differing-param-doc
"""Updates an existing user account with the specified properties.
Args:
uid: A user ID string.
kwargs: A series of keyword arguments (optional).
Keyword Args:
display_name: The user's display name (optional). Ca... | 8a3f78186800f4e768cf9a7d622f3efdcfc133f6 | 77,187 |
def get_meta_data(**args):
"""
Get the meta data for a set of bibcodes
"""
data_dict = {}
# This information can be retrieved with one single Solr query
# (just an 'OR' query of a list of bibcodes)
bibcodes = [bibcode for (bibcode,score) in args['results']]
list = " OR ".join(map(lambda ... | 65f41d0d0cecae85d3e728069258b1045ce20c42 | 77,189 |
def test_data_fetch_relations(filter_id = "WIK_KET_Rioolgemaal"):
"""Test of related locations goed worden weggegooid."""
tuple_values = data.filters.get_tuples([filter_id])
data.locations.fetch(tuple_values)
return "BER-HEE-KER" not in data.locations.df["locationId"] | d158c390b208397af4f2d556f04eed9952665276 | 77,190 |
def get_budget(args):
"""
Метод для получения данных о документах
:param args:
:return:
"""
provider = Provider()
answer = provider.get_budget(args)
return answer | 509a36cd157c54f794822a3155ea2701779fd89a | 77,193 |
def newton_dynamics(f, x0, steps, epsilon=0.01):
"""Just do Newtonian Hamiltonian dynamics, no momentum randomization and no MH reject."""
shape = x0.shape
xs = t.zeros((steps + 1,) + shape, dtype=x0.dtype)
vs = t.zeros((steps + 1,) + shape, dtype=x0.dtype)
v = t.randn_like(x0)
x = x0
xs[0],... | 309914c8562c607d5600128c7359bc8c702f5700 | 77,194 |
def model(inpt, num_actions, scope, reuse=False):
"""This model takes as input an observation and returns values of all actions."""
with tf.compat.v1.variable_scope(scope, reuse=reuse):
out = inpt
out = fully_connected(out, num_outputs=64, activation_fn=tf.nn.tanh)
out = fully_connected(... | e96390633eba58c5e36ec87d7d15e846f96e8cdc | 77,195 |
def get_height(image):
"""get_height(image) -> integer height of the image (number of rows).
Input image must be rectangular list of lists. The height is
taken to be the number of rows.
"""
return len(image) | 3aa94c4b2458d2a233f32ee10889e52566c04ecb | 77,196 |
import time
def th_C(tab, tab1, par, nthreads=-1, write=True, plot=False, **kwargs):
"""
Given two astropy data tables, cross-count pairs in angular space
All input parameters that control binning, column names, etc.
are passed in a single dictionary ``par``, which can be easily generated
wit... | 729ae4bf76968793452514c3776f87e00357337f | 77,198 |
def convert_predict_response_into_nparray(response, output_tensor_name):
"""
:param response:
:param output_tensor_name:
:return:
"""
dims = response.outputs[output_tensor_name].tensor_shape.dim
shape = tuple(d.size for d in dims)
return np.reshape(response.outputs[output_tensor_name].... | 648adfc2e30115791d56dda00246dfa2142aa194 | 77,200 |
import torch
def normalize_image_into_standard_form(img):
"""the input image should in gray x,y"""
img = (img-img.min())/(img.max()-img.min())
sz = [1,1]+ list(img.shape)
img_t = torch.Tensor(img)
img_t = img_t.view(sz)
return img_t | 8da901135cffc3cc36d5be969ee2e2f94f75f74e | 77,201 |
def is_power_of_two(n: int) -> bool:
"""
>>> is_power_of_two(1024)
True
>>> is_power_of_two(5)
False
"""
return n & (n - 1) == 0 | e56997fd768c5b6e74f179969b1681a1e0c33e78 | 77,202 |
def api_team_unlock_problems_and_contests(teamID: int):
"""
团队用户解锁团队题目和团队比赛和团队习题集
"""
user: User = db.session.query(User).filter_by(
id=session.get("uid", -1)).one_or_none()
if not user:
return make_response(-1, message="请登录")
team: Team = db.session.query(
Team.team_prob... | 2ec0deddd6d52d5f7178ddcebc1a625b9dd5d83b | 77,203 |
from typing import List
def normalize(
path: PathLike,
steps: int = 5,
chunk_size: int = 512,
threshold: float = 0.20,
cp_isolation: List[str] = None,
cp_exclusion: List[str] = None,
preemptive_behaviour: bool = True,
) -> CharsetMatch:
"""
Take a (text-based) file path and try to ... | a6f30fe16df7bf602f681b14a5e1b6a829cbad01 | 77,204 |
def _is_version_satisfied(specifier: str, sys_version) -> bool:
"""
SpecifierSet("") matches anything, no need to artificially
lock down versions at this point
@see https://warehouse.readthedocs.io/api-reference/json.html
@see https://packaging.pypa.io/en/latest/specifiers.html
"""
specifie... | 6ecc7854de41e28c50f7503ece2260638009cc62 | 77,206 |
from datetime import datetime
def run_typing_test(topics):
"""Measure typing speed and accuracy on the command line."""
paragraphs = lines_from_file('data/sample_paragraphs.txt')
def select(p): return True
if topics:
select = about(topics)
i = 0
while True:
reference = choose(p... | e6d1c74783b9ae2568a2fe9b77ca7b80bc5e473c | 77,207 |
def prepend(value, iterator):
"""
Prepend a single value in front of an iterator
"""
return chain([value], iterator) | e7118db2405094d36815f33911b1314c3511360d | 77,209 |
def ATL06_2_gdf(ATL_fn, dataset_dict, ancillary=False):
"""Wrap ATL_2_gdf with defaults for ATL_06."""
check_name = 'land_ice_segments'
return ATL_2_gdf(ATL_fn, dataset_dict, check_name=check_name,
ancillary=ancillary) | c16046d745f3241904fab63f2c710a3ba84fb601 | 77,211 |
def scenario_1(commodities) -> TScenario:
"""
Returns the setup for scenario 1 in ADR13.
See the module-level docs for details on scenario setups.
"""
keys = ["9999_80_1", "9999.10_80_2"]
collection = create_collection(commodities, keys)
changes = [
CommodityChange(
col... | 8b71ec2bef5fcc096494366c587ad4d37f2b9fb6 | 77,212 |
def _GroupSymbolsByOffset(binary_filename):
"""Produce a map symbol name -> all symbol names at same offset.
Suffixes are stripped.
"""
symbol_infos = [
s._replace(name=RemoveSuffixes(s.name))
for s in symbol_extractor.SymbolInfosFromBinary(binary_filename)]
offset_map = symbol_extractor.GroupSym... | 8ec0b87ac2d31c1e89f515efa42b3a5e89def1b2 | 77,213 |
import bempp.api
from scipy.sparse import coo_matrix
import numpy as np
def p1_trace(fenics_space):
"""
Return the P1 trace operator.
This function returns a pair (space, trace_matrix),
where space is a Bempp space object and trace_matrix is the corresponding
matrix that maps the coefficients of ... | 5e58e76d14970c4f9828a9386b71d62c866865be | 77,214 |
def service_c_hours(request):
""" Renders the service chair way of viewing total service hours by brothers """
if not utils.verify_service_chair(request.user):
messages.error(request, "Service Chair Access Denied!")
return HttpResponseRedirect(reverse('dashboard:home'))
brothers = Brother.o... | 4f640e29d9a66deb5b179758952cf24ac831366a | 77,216 |
import requests
def event_ancestors(id='R-HSA-5673001'):
"""
The Reactome definition of events includes pathways and reactions.
Although events are organised in a hierarchical structure, a single event can be in more than one location,
i.e. a reaction can take part in different pathways while, in the ... | 35cb3944883ac97a8168ba4d8e1e5f908f094f0f | 77,218 |
def get_word_sentiment(word):
"""Return a sentiment representing the degree of positive or negative
feeling in the given word.
>>> sentiment_value(get_word_sentiment('good'))
0.875
>>> sentiment_value(get_word_sentiment('bad'))
-0.625
>>> sentiment_value(get_word_sentiment('winning'))
0... | 59d6f673eb6744bea78f2be82ae776e42a5c3dd3 | 77,220 |
def fit_spec():
"""Fit specification."""
data = dict(
a=1.0,
sig_a=2.0,
b=-3.0,
sig_b=4.0,
r2=5.0,
q=6.0,
chi2=7.0,
nu_chi=8,
exp_id=1,
idx=0,
mddp=9.0,
sig_mddp=9.1,
x1s=10.0,
sig_x1s=10.1,
x... | 93a348005c0b0ddd132fbe8e0d6923bb0fb25b3c | 77,223 |
from typing import Optional
from typing import Callable
from typing import Tuple
from typing import Dict
def make_params_and_inference_fn(
observation_size: int,
action_size: int,
normalize_observations: bool = False,
parametric_action_distribution_fn: Optional[Callable[[
int,
], distribut... | 807f95ce5865bdf77ff3361e642df39163dcdba5 | 77,224 |
def jsonify_dict(d, copy=True):
"""Make dictionary JSON serializable"""
if copy:
d = deepcopy(d)
for k, v in d.items():
if type(v) == np.ndarray:
d[k] = v.tolist()
elif type(v) == list:
d[k] = jsonify_list(v)
elif type(v) == dict:
d[k] = js... | 005b10fd8b0cae4a8af9b1d6e132fad95f6a6af7 | 77,225 |
def format_rows_to_columns(forecast_dict):
"""
Helper function to reformat list of courses from Student object's
self.plan (student_object.py) into a format appropriate for forecast.html
i.e. rows from student object will be converted into columns for forecast.html
"""
# these lists will contain the info for the ... | e7e5fc765641543130be4c103e77b73ed1e2b53e | 77,227 |
def psd_to_flux_density(E, f, Omega):
"""
Converting phase space density f to flux density S_nu. Returns frequency nu [GHz] and spectral irradiance S_nu = E^3/2./pi^2*f*Omega [Jy].
Parameters
----------
E : array of energy [eV]
f : p.s.d
Omega : the angle the source subtends [sr]
"""
... | fdd1540c68d7fcfa89234e5aa543dbc07d14d9ff | 77,228 |
def _maybe_replace_unmasked(ori, mask, reconstruction):
"""
Replace the unmasked parts of `reconstruction` with the respective parts from `ori` if configured in `FLAGS`.
"""
mask_b = np.array(mask, dtype=np.bool)
# if mask consists only of False, it means it is empty, in which case we don't want to... | 990faae0c048d28c30e2b122dc413aae6ec82faa | 77,230 |
async def bsgn_1(a):
"""Compute binary sign of a securely.
Binary sign of a (1 if a>=0 else -1) is obtained by securely computing
(u+v+w - u*v*w)/2 with u=(2a-1 | p), v=(2a+1 | p), and w=(2a+3 | p).
"""
stype = type(a)
await mpc.returnType(stype)
Zp = stype.field
p = Zp.modulus
lege... | 218e86dfc7ab3e40a0af91be72a6c6e80c18a8c5 | 77,233 |
def get_query_range(count: int, page: int):
"""Generate query for range of the search results
:type count: ``int``
:param count: Max amount of the search results
:type page: ``int``
:param page: Current page, depends on count
:return: A query range
:rtype: ``str``
"""
if page < 1:... | c29285c56eed77275d2ec28a45de148ce3b7f591 | 77,235 |
import json
def mock_md_fetch(monkeypatch):
"""Mock out the metadata-fetching implementation
Override _substitute_metadata so we can test `fetch_metadata' without network IO.
doctest.testmod does accept globals-setting parameters (`globs` & `extraglobs'), but they
haven't been as easy as just overwri... | b22c52e3038413744b5f0d219ad74a7c992b442c | 77,236 |
def T_stock(Q_plant, C, tubing_color, V_stock):
"""This function calculates the time after the experiment at which the
stock container will run out.
Parameters
----------
Q_plant : float
flow rate of the plant
C : float
desired concentration within the plant
tubing_color :... | b29278647eca96db0ecfb2c121cee9eb69183b15 | 77,237 |
def xT_surface(df, successful_shot_events, failed_shot_events, successful_pass_events, failed_pass_events, successful_dribble_events, failed_dribble_events, event_column_name, l=18, w=12, pitch_length=105, pitch_width=68, use_synthetic=0, df_synthetic=None):
"""
Iteratively calculates MxN xT value surface.
... | 16663a1f2c2bd6b3cbefdf0a31dc1d4f992db33e | 77,238 |
def svn_utf_cstring_to_utf8(*args):
"""svn_utf_cstring_to_utf8(char dest, char src, apr_pool_t pool) -> svn_error_t"""
return apply(_core.svn_utf_cstring_to_utf8, args) | c023085352dc7741b35377a540be642c83d7a20b | 77,239 |
def get_commits_master_url(repo_name):
""" Get GitHub API URL for latest commit to master """
return "%s/master" % get_commits_url(replace_special_chars(repo_name)) | b22d730892fbb65d80c6a80dde292dfbc8801e27 | 77,241 |
def Default(value: DefaultType) -> DefaultType:
"""
You shouldn't use this function directly.
It's used internally to recognize when a default value has been overwritten, even
if the overridden default value was truthy.
"""
return DefaultPlaceholder(value) | a02be19c566c2b41b58d32dee8cbe88e9934b413 | 77,243 |
import json
def get_deploy_durations_from_file(filename):
"""
filename: path to a file to be parsed for datetime data
The expected input is a paasta service log for the deploy events
The way I've been fetching them is by running 'internal logreader command' | grep deploy | grep event > filename
""... | 35bd78adf5a863604cd361a10d449199ece88b47 | 77,244 |
def chunkify(l, chunk_size):
"""Return list of evenly sized lists"""
book_chunks = []
for i in range(0, len(l), chunk_size):
book_chunks.append(l[i:i + chunk_size])
return book_chunks | d205d8a916582e86d736e1372a18d7dd173e4683 | 77,245 |
def resize(img, height=None, width=None):
"""resize the image
Args:
img (array): png image
height (int, optional): pixel. Defaults to None.
width (int, optional): pixel. Defaults to None.
Returns:
image: the raw image
"""
h, w = img.shape[0], img.shape[1]
if hei... | 05b47a3638fe5ef6d8298855a6b320e4f93888ad | 77,246 |
def get_abuse_categories(comment_body):
"""Returning the matching categories of abuse"""
cats = []
body = comment_body.lower()
for cat in sorted(cfg.CATEGORIES.keys()):
if cat in body:
# distinguish between the overlapping categories "spam"
# and "comment spam"
... | 362db333ea463ef1d22f1b0ae51bfb46f81e8b27 | 77,247 |
import re
def get_alphabet(sequences):
"""Retrieve alphabet of amino acids with modifications.
Parameters
----------
sequences : ar-like
peptide sequences.
Returns
-------
List with modification strings.
"""
return np.unique(
re.findall("-OH|H-|[a-z0-9]+[A-Z]|[A-Z... | 0faeca97418a3cf2c3bb1a8c03e6743cc16917a6 | 77,248 |
def createRequestWithFuture():
"""
Creates a `Request` and populates the `future` field in the same way
the `BulkRequestManager` populates it when the request is placed.
"""
req = Request('http://127.0.0.1:40506', 'test')
req.future = injectResultTimestampFn(Future())
return req | 50744ed213ddd88a6da99e15e035b19e67e98654 | 77,249 |
from typing import Optional
import torch
def isposinf(x: DNDarray, out: Optional[DNDarray] = None):
"""
Test if each element of `x` is positive infinite, return result as a boolean :class:`~heat.core.dndarray.DNDarray`.
Parameters
----------
x : DNDarray
Input tensor
out : DNDarra... | a542de41e3784c80b10418e5562aad846c614e0e | 77,250 |
def verifyScoutFlags(logger):
"""Checks that all of the configuration flags are set correctly
Args:
logger (logger): (elementals) logger
Return Value:
True iff all configuration flags are set to a valid value, False otherwise
"""
global config_flags
if config_bitness is None:
... | 61bc6761b29c567ac7eb04167437dcf153667afb | 77,251 |
def decodeJSONFitterSteps(fitter : Fitter, dct):
"""
Function for passing as decoder to Fitter.decodeSettingsJSON().
Constructs scaffold objects from their JSON object encoding.
Used as object_hook argument to json.loads as a lambda function
to pass fitter:
lambda dct: decodeJSONFitterSteps(fitt... | 4f789852f0bd00693259247a53bd0dceb6388ba4 | 77,252 |
def update_playlist(playlist, client=default):
"""
Save given playlist data into the API. Metadata are fully replaced by
the ones set on given playlist.
Args:
playlist (dict): The playlist dict to update.
Returns:
dict: Updated playlist.
"""
return raw.put(
"data/pl... | 6fbdad36314d2d6417bc33021c7fc4730d65e714 | 77,253 |
def hbdet_bias_plot(start_date, end_date):
"""Return a <div> element with a weather downtime plot.
The plot shows the downtime for the period between start_date (inclusive) and end_date (exclusive).
Params:
-------
start_date: date
Earliest date to include in the plot.
end_date: date
... | b10d54a088800bd1a3d67d2f5b144f5607eda213 | 77,254 |
import vagrant
def check_vagrant_plugins_installed() -> CheckLevels:
"""
Error if `vagrant-vbguest` is not installed.
"""
# We import Vagrant here instead of at the top of the file because, if
# the Vagrant executable is not found, a warning is logged.
#
# We want to avoid that warning for... | 8c081d366e0fed78c919f9b1f4a4d96504685204 | 77,256 |
def remember(function):
"""
A decorator caching the result of a method.
"""
memo = {}
def wrapper(*args):
if args in memo:
return memo[args]
else:
rv = function(*args)
memo[args] = rv
return rv
def _reset(args):
if not arg... | a6e9e745e9b8b95fd4dd934ee436b6dcb4bb242b | 77,258 |
def get_worker_cpu_usage():
"""[summary] this endpoint retrieves the average CPU user per minute for the past 30 minutes.
Returns:
[type] -- [description] this endpoints return a json object
{
isSuccess: boolean indicating if the action is successful,
timestamps: list of... | c9283ddffc458dc1b21edf5c79a20e14bdeacab9 | 77,259 |
def success(parsed_args):
"""
:param :py:class:`argparse.Namespace` parsed_args:
:return: Nowcast system message type
:rtype: str
"""
logger.info(
f"NEMO nowcast-agrif run for "
f'{parsed_args.run_date.format("YYYY-MM-DD")} '
f"queued on {parsed_args.host_name}"
)
... | 026e1bed8efc995aba417c5d03b82bf274505290 | 77,260 |
def nancov(X):
"""
Generates a covariance matrix excluding nan-components.
Parameters
---------------
X : :class:`numpy.ndarray`
Input array for which to derive a covariance matrix.
Returns
-------
:class:`numpy.ndarray`
"""
# tried and true - simply excludes samples
... | 7ba961dab9d7f02b41c7bda805f72e3b55e4d6ee | 77,261 |
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