content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
import itertools
def config_path(*args, **kwargs):
"""
Join multiple paths from configuration and always use config['path']['base'] as base path.
Use as follows:
```python
config_path('model.train')
```
:param args: Lists of keys to load.
:param kwargs: Keyword arguments. Cur... | c75ffafae583cb2ea9f9d4277c556c9dc4e815d7 | 3,632,300 |
def get_one_hot_predictions(tcdcn, x, dim):
"""
This method gets a model (tcdcn), passes x through it
and gets it's prediction, then it gets one_hot
matrix representation of the predictions. depending on whether
tcdcn is RCN or a structured model, x can be an image
(in the former case) and a one... | 27bf3ad70f77e726ba8484dec8770211907dfbd5 | 3,632,301 |
def run_multi_lsp(x, y, err, fts, fmin=0.1, fmax=150, k_band=1, m_base=1, mode='fast', dt_cut=365, k_term_base=0):
"""Run all methods of multiband gatspy Lomb-Scargle Periodogram.
Input
------
x, y, err, fts: phase, magnitudes/flux, error, filter list
fmin, fmax: minimum and maximum... | 28d0061499fe809f4cce770b8a23c66d8471f741 | 3,632,302 |
def render_tablet_screen():
"""
Serves the page for the tablet backend.
:return: The tablet html file.
"""
return app.send_static_file('tablet.html') | d82f1bf75438e05c4745a7eb7e25c2223f8e98cc | 3,632,303 |
def add_content(resp, param, value):
"""Adds content/body of the response.
ecocnt_html: html body,
ecocnt_css: css body,
ecocnt_js: js body,
ecocnt_img: img body,
ecocnt_vid: video body,
ecocnt_audio: audio body,
"""
if param == "ecocnt_html":
t = loader.get_template("echo/t... | 07bc2bc61d9901ab09b0badaef643622eb270754 | 3,632,304 |
def intersection_over_union(box1, box2):
"""Returns the IoU critera for pct of overlap area
box = (left, right, bot, top), same as matplotlib `extent` format
>>> box1 = (0, 1, 0, 1)
>>> box2 = (0, 2, 0, 2)
>>> print(intersection_over_union(box1, box2))
0.25
>>> print(intersection_over_union... | 4825de855bd12fcaaebbfa337fc0f6faa9482a74 | 3,632,305 |
def fpsol(nu,u):
"""
reads the vector normal and slip vector returning strike, rake, dip
"""
dip=np.arccos(-1*nu[2])
if nu[0] ==0. and nu[1] == 0.:
str=0.
else:
str=np.arctan2(-1*nu[0],nu[1])
sstr=np.sin(str)
cstr=np.cos(str)
sdip=np.sin(dip)
cdip=... | 735e99dc9b00c1d22c6a6976892ed709840cc007 | 3,632,306 |
def create_short_ticket(access_token, expire_seconds=2592000, scene_id=0):
"""
创建临时二维码
:param access_token: 微信access_token
:param expire_seconds: 二维码过期时间
:param scene_id: 场景值ID
:return:
"""
target_url = 'https://api.weixin.qq.com/cgi-bin/qrcode/create?access_token=%s' % access_token
... | 30dc627d5319d8145854b568ce8b7a8d4e4eba69 | 3,632,307 |
import os
def gen_compound(name, N=50, nP=10):
"""
(1) Alkane vs Alcohol
N: the #carbon atom in compound, ex: N=50 generates compounds of different length from 1 to 50 carbons
P: # of permutation to relabeling the vertex order for each generated compound
-----------------------------------... | b5b33b50ea9245669eb98f7f0f3c002dcf79e87e | 3,632,308 |
from datetime import datetime
import os
def build_youtube_search_request():
"""
Building a query based on the following API - https://developers.google.com/youtube/v3/docs/search/list
"""
video_search_params = {
"part": "id,snippet",
"type": "video",
"maxResults": 50,
"... | 4e79bcc8154f6384a371b236154d8eba7050c43c | 3,632,309 |
from qtpy.QtWidgets import QDesktopWidget # noqa
def get_screen_size():
"""Get **available** screen size/resolution."""
if mpl.get_backend().startswith('Qt'):
# Inspired by spyder/widgets/shortcutssummary.py
widget = QDesktopWidget()
sg = widget.availableGeometry(widget.primaryScreen(... | 9575fbf1874d6dcf22e0ebb5a771015dfa570847 | 3,632,310 |
def potential_bond_keys(mgrph):
""" neighboring radical sites of a molecular graph
"""
ridxs = radical_sites(mgrph)
return tuple(frozenset([ridx1, ridx2])
for ridx1, ridx2 in combinations(ridxs, 2)
if ridx2 in atom_neighborhood_indices(mgrph, ridx1)) | ccbff81075cab38b3bc96b39885f1873c733bd93 | 3,632,311 |
def convolve(signal,kernel):
"""
This applies a kernel to a signal through convolution and returns the result.
Some magic is done at the edges so the result doesn't apprach zero:
1. extend the signal's edges with len(kernel)/2 duplicated values
2. perform the convolution ('same' mode)
... | 1eb31d9fdf2a6afa6ea08912f8b28f0ae4af64e6 | 3,632,312 |
def makemebv(gmat, meff):
"""Set up family-specific marker effects (GEBV)."""
qqq = np.zeros((gmat.shape))
for i in range(gmat.shape[0]):
for j in range(gmat.shape[1]):
if gmat[i, j] == 2:
qqq[i, j] = meff[j]*-1
elif gmat[i, j] == 1:
qqq[i, j] ... | 44cbcdeadbfee9b7e802e201ad589f9ebdcb11b3 | 3,632,313 |
from typing import Tuple
from typing import Optional
import io
import textwrap
from re import I
def _define_property_shape(
prop: intermediate.Property,
cls: intermediate.ClassUnion,
url_prefix: Stripped,
class_to_rdfs_range: rdf_shacl_common.ClassToRdfsRange,
constraints_by_property: infer_for_sc... | 29483d27548a7fbd208f820e8e0821e0b121132f | 3,632,314 |
def row2string(row, sep=', '):
"""Converts a one-dimensional numpy.ndarray, list or tuple to string
Args:
row: one-dimensional list, tuple, numpy.ndarray or similar
sep: string separator between elements
Returns:
string representation of a row
"""
return sep.join("{0}".form... | f81a2ec54b8c37285715cadca4458918962440b9 | 3,632,315 |
from sys import path
import time
import requests
import json
def download_profile_picture(user_id, discriminator, avatar_hash=None, cache_dir="cache", default_dir="default",
cert_file=None, game_name=None, game_version=None, game_url=None):
"""
Download a discord user's profile pi... | c68cc069a4666d6f693271971d94829e2bb963ae | 3,632,316 |
def apply_kNNO(Xs, Xt, ys=None, yt=None, scaling=True, k=10, contamination=0.1):
""" Apply kNNO.
k-distance is the distance of its k-th nearest neighbour in the dataset
KNNO ranks all instances in a dataset by their k-distance, with higher distances signifying
more anomalous instances
Parameter... | 6a90757063ff20dba11075508bce7038295920a1 | 3,632,317 |
import logging
def _tenant_update(name, new_name=None, description=None, default_datastore=None):
""" API to update a tenant """
logging.debug("_tenant_update: name=%s, new_name=%s, descrption=%s, default_datastore=%s",
name, new_name, description, default_datastore)
error_info, tenant =... | 87b9586b87868c3693b09a4127edc148c6d36bb0 | 3,632,318 |
from typing import Iterable
import os
def _clone_all(urls: Iterable[str], cwd: str):
"""Attempts to clone all urls, sequentially. If a repo is already present,
it is skipped. If any one clone fails (except for fails because the repo
is local), all cloned repos are removed
Args:
urls: HTTPS u... | 5a7c10de2fc8e1c4f77e9a7505315b62a94eb28e | 3,632,319 |
def build_aggregation(facet_name, facet_options, min_doc_count=0):
"""Specify an elasticsearch aggregation from schema facet configuration.
"""
exclude = []
if facet_name == 'type':
field = 'embedded.@type'
exclude = ['Item']
elif facet_name.startswith('audit'):
field = facet... | b8c3f337143a229401b9a41a8fde8903027cf67e | 3,632,320 |
def recover_marker_rbt(itf, tgt_mkr_name, cl_mkr_names, log=False):
"""
Recover the trajectory of a marker by rbt(rigid body transformation) using a group (cluster) markers.
The number of cluster marker names is fixed as 3.
This function extrapolates the target marker coordinates for the frames whe... | 598cd920494dac9e2847e9fdf7a0b1d66715957b | 3,632,321 |
def route_wrap_01_version(request_mapping: str):
"""
flask 路由映射包裹器
增加API_VERSION
:param request_mapping:
:return:
"""
return '{}/{}'.format(API_VERSION, request_mapping) | 0a3db2ed132c1f2233817a8154c5c1c87872d6dc | 3,632,322 |
def spawn(pool):
"""spawn a greenlet
it will be automatically killed after the test run
"""
return pool.spawn | fadea4b814e77f7fb26af27f0cc7bce1189a7dcf | 3,632,323 |
from typing import Any
import json
def from_json_util(json_str: str) -> Any:
"""Load an arbitrary datatype from its JSON representation.
The Out-of-proc SDK has a special JSON encoding strategy
to enable arbitrary datatypes to be serialized. This utility
loads a JSON with the assumption that it follo... | 5da695fb260b1df35dc91dfb8ef9026b04472d6a | 3,632,324 |
def min_row_dist_sum_idx(dists):
"""Find the index of the row with the minimum row distance sum
This should return the index of the row index with the least distance overall
to all other rows.
Args:
dists (np.array): must be square distance matrix
Returns:
int: index of row wit... | 7bddc4e58344e519a2bd928187db3a6b65e17118 | 3,632,325 |
def inline(text):
"""
Convert all newline characters to HTML entities:
This can be used to prevent Hypertag from indenting lines of `text` when rendering parent nodes,
and to safely insert `text` inside <pre>, <textarea>, or similar elements.
"""
return text.replace('\n', ' ') | 658f7e5adbf5747ea069fad8a9599e9bd499a381 | 3,632,326 |
def align_pos(xyz, test_crd, ref_crd, ind=None):
"""Translates a set of atoms such that two positions are coincident.
Parameters
----------
xyz : (N, 3) array_like
The atomic cartesian coordinates.
test_crd : (3,) array_like
Cartesian coordinates of the original position.
test_c... | ffa6001e20a4e4a1379e6a95139946aa91a5bdd0 | 3,632,327 |
from typing import Optional
from typing import Sequence
def get_orderable_db_instance(availability_zone_group: Optional[str] = None,
engine: Optional[str] = None,
engine_version: Optional[str] = None,
instance_class: Optional[st... | 6557de19d6c14d903d9f3058f7428ffe700633d0 | 3,632,328 |
def publish_channel_url():
"""open_channel_url: returns url to publish channel
Args: None
Returns: string url to publish channel
"""
return PUBLISH_CHANNEL_URL.format(domain=DOMAIN) | 7ba59e32746b9ffa9c9a46fd073cfbb1c3905e9f | 3,632,329 |
def hist_counts(df_acts=None, lst_acts=None, df_ac=None, y_scale="linear", idle=False,
figsize=None, color=None, file_path=None):
"""
Plot a bar chart displaying how often activities are occurring.
Parameters
----------
df_acts : pd.DataFrame, optional
recorded activities fr... | 4e9820d25bd2f33de8269f413fbce0b1898fd7fa | 3,632,330 |
def random_dense(shape, fortran):
"""Generate a random qutip Dense matrix of the given shape."""
return qutip.core.data.Dense(random_numpy_dense(shape, fortran)) | 869c8cd2972b40f82d73403ed5c54d170fe3dcb5 | 3,632,331 |
import torch
def bo_step(X, y, objective, bounds, GP=None, acquisition=None, q=1, state_dict=None, *GP_args,
**GP_kwargs):
"""
One iteration of Bayesian optimization:
1. Fit GP model using (X, y)
2. Create acquisition function
3. Optimize acquisition function to obtain cand... | e752091e5aaf3b42e3e8f21a21f0368485f60c25 | 3,632,332 |
def validate_inputs(input_data):
"""Check prediction inputs against schema."""
# set many=True to allow passing in a list
schema = InsuranceDataRequestSchema(strict=True, many=True)
errors = None
try:
schema.load(input_data)
except ValidationError as exc:
errors = exc.messages ... | e0faacabb729d191308bdf1d5710525b529d4793 | 3,632,333 |
def published_stats_list(request):
"""
List cumulative stats about projects published.
The request may specify the desired resource type
"""
resource_type = None
# Get the desired resource type if specified
if 'resource_type' in request.GET and request.GET['resource_type'] in ['0', '1']:
... | 308ef79fb6f51d192adb31849dd6bb75a46fe469 | 3,632,334 |
def get_entity(name):
"""Get an entity by the given name.
Args:
name (str): namespace.entity_name
Returns:
OntologyEntity: The entity with the given name.
"""
ns, n = name.split(".")
return _namespace_registry._get(ns)._get(n) | bd00058f8d3af4d29b35bcf0cc336f4c567baf8a | 3,632,335 |
def tst():
"""members page."""
return render_template('users/testing2.html') | 042463af7cc3742e78f744bc66ad09c3060ca877 | 3,632,336 |
def get_bq_col_type(col_type):
"""
Return correct SQL column type representation.
:param col_type: The type of column as defined in json schema files.
:return: A SQL column type compatible with BigQuery
"""
lower_col_type = col_type.lower()
if lower_col_type == 'integer':
return 'I... | 86cac08a04d804cc6addbeee86014f1aa6d35735 | 3,632,337 |
def _do_boundary_search(search_term):
"""
Execute full text search against all searchable boundary layers.
"""
result = []
query = _get_boundary_search_query(search_term)
with connection.cursor() as cursor:
wildcard_term = '%{}%'.format(search_term)
cursor.execute(query, {'term'... | b2cc74b7ba436c0c57bbb7505d964d79354a36f5 | 3,632,338 |
def prices(identifier, start_date=None, end_date=None, frequency='daily',
sort_order='desc'):
"""
Get historical stock market prices or indices.
Args:
identifier: Stock market symbol or index
start_date: Start date of prices (default no filter)
end_date: Last date (defaul... | 145d8ea607a1e374e205ef337345f7b9d6064479 | 3,632,339 |
import requests
import json
def verify_captcha(secret, response, remoteip=None):
"""
From https://developers.google.com/recaptcha/docs/verify:
secret: The shared key between your site and ReCAPTCHA.
response: The user response token provided by the reCAPTCHA to the user
and provide... | fbfaea5a388f5047322cdb05d0b37d7f445a2b17 | 3,632,340 |
def x1y1x2y2_to_xywh(x1y1x2y2):
"""Convert [x1 y1 x2 y2] box format to [x y w h] format."""
if isinstance(x1y1x2y2, (list, tuple)):
# Single box given as a list of coordinates
assert len(x1y1x2y2) == 4
ct_x, ct_y = (x1y1x2y2[3] + x1y1x2y2[1]) / 2, (x1y1x2y2[2] + x1y1x2y2[0]) / 2
... | b5535ace312ca2f790f4dcb66ed9e53223b90649 | 3,632,341 |
def col(loc, strg):
"""
Returns current column within a string, counting newlines as line separators.
The first column is number 1.
Note: the default parsing behavior is to expand tabs in the input string
before starting the parsing process. See
:class:`ParserElement.parseString` for more
... | 0dfc4387e391c4823939350ad19c60d106211a58 | 3,632,342 |
def create_model_fn(model_class, hparams, use_tpu=False):
"""Wraps model_class as an Estimator or TPUEstimator model_fn.
Args:
model_class: AstroModel or a subclass.
hparams: ConfigDict of configuration parameters for building the model.
use_tpu: If True, a TPUEstimator model_fn is returned. Otherwise ... | 83be600771b8e64c610db0d3d16fe10ba668fbd0 | 3,632,343 |
from typing import Any
def boolean(value: Any) -> bool:
"""Validate and coerce a boolean value."""
if isinstance(value, str):
value = value.lower()
if value in ("1", "true", "yes", "on", "enable"):
return True
if value in ("0", "false", "no", "off", "disable"):
... | 781dbb2e30448065d8dc65b42ab02914a3338b43 | 3,632,344 |
def unmap(data, count, inds, fill=0):
"""
Unmap a subset of item (data) back to the original set of items (of size count)
:param data: input data
:param count: the total count of data
:param inds: the selected indices of input data
:param fill: filled value
:return: unmaped data
"""
... | 3cc361650644275673e6340f8d6a216071b0c3c9 | 3,632,345 |
def processbundle(repo, unbundler, transactiongetter=None, op=None, source=b''):
"""This function process a bundle, apply effect to/from a repo
It iterates over each part then searches for and uses the proper handling
code to process the part. Parts are processed in order.
Unknown Mandatory part will ... | 4651bc64da5d48d992379301294c480f9d42cb0f | 3,632,346 |
def recursive_feature(G, f, n):
"""
G: iGraph graph with annotations
func: string containing function name
n: int, recursion level
Computes the given function recursively on each vertex
Current precondition: already have run the computation for G, func, n-1.
"""
retur... | 4516e85cddea50dc9a1f14448a7b950a0620e3f0 | 3,632,347 |
import unicodedata
def remove_accents(string):
"""
Removes unicode accents from a string, downgrading to the base character
"""
nfkd = unicodedata.normalize('NFKD', string)
return u"".join([c for c in nfkd if not unicodedata.combining(c)]) | 41c8e05aa8982c85cf5cf2135276cdb5e26fefec | 3,632,348 |
from typing import Optional
def __get_a0( # pylint: disable=invalid-name
n: int, a0: Optional[np.ndarray] = None
) -> np.ndarray:
"""
Returns initial parameters for fitting algorithm.
:param n: Number of parameters
:param a0: Initial parameters value. Optional
:return: nd.array
"""
i... | 80b5d974dd6187746215191cc1f4de1ae135b93e | 3,632,349 |
def convert_yaw_to_old_viewpoint(yaw):
""" we initially had viewpoint coordinates inverted
Example:
>>> import math
>>> TAU = 2 * math.pi
>>> old_viewpoint_labels = [
>>> ('left' , 0, 0.000 * TAU,),
>>> ('frontleft' , 45, 0.125 * TAU,),
>>> ... | 7659e15bf7f4693ac7c6223b8f4600450bc7f2fe | 3,632,350 |
import os
def uploadimages(path_list,client,csv_list):
"""Uploads images to imgur.
Arguments:
path_list {list} -- [List of files at directory.]
client {ImgurClient} -- [ImgurClient we get from authentication.]
csv_list {list} -- [List of uploaded pictures.]
"""
#we create a da... | cdc798a60e38fea6e07325b7e50e2c11d80ee6aa | 3,632,351 |
def extract_lexical_features_test(nlp, tweet_list):
"""Provides tokenization, POS and dependency parsing
Args:
nlp (spaCy model): Language processing pipeline
"""
result = []
texts = (tweet for tweet in tweet_list)
for doc in nlp.pipe(texts, batch_size=10000, n_threads=3):
setti... | b0f87996558c4b2e1d77b59068e8ad259524a455 | 3,632,352 |
def get_hostname():
""" Return hostname. """
return tg.config.get('workbox.hostname') | 367dda60f71d169c6490913a3ee3f8befc83b738 | 3,632,353 |
import http
def geocode_location(api_key, loc):
"""Get a geocoded location from gooogle's geocoding api."""
try:
parsed_json = http.get_json(GEOCODING_URL, address=loc, key=api_key)
except IOError:
return None
return parsed_json | 95c820abc58a13cd57e662e78bfab8fceac5eadf | 3,632,354 |
def degree(f, *gens, **args):
"""
Return the degree of ``f`` in the given variable.
The degree of 0 is negative infinity.
Examples
========
>>> degree(x**2 + y*x + 1, gen=x)
2
>>> degree(x**2 + y*x + 1, gen=y)
1
>>> degree(0, x)
-inf
"""
allowed_flags(args, ['gen'... | a6b5e2ba9228ea1477234c0e16477dd603fb9598 | 3,632,355 |
from typing import Dict
def fit_model_sector(sector_corpus: Dict[DocId, Token]) -> sbmtm:
"""Fits the model taking the sector corpus data structure as an input
Args:
sector_corpus: a dict where keys are doc ids and
values are the tokenised descriptions
Returns:
The model
... | d025a0f4faac53b4b21486e159a0310c78dc72b8 | 3,632,356 |
def get_simulated_matches(path, met, sample_to_match, pop_var):
"""Selects initial conditions from cosmic data to match to star sample
Parameters
----------
path : `str`
path to cosmic data
met : `float`
metallicity of cosmic data file
sample_to_match : `DataFrame`
A d... | ecbb46f284f7b6748031b0907813deaad8967eba | 3,632,357 |
def _get_url_ext(url: str):
"""
>>> _get_url_ext('http://example.com/blog/feed')
'feed'
>>> _get_url_ext('http://example.com/blog/feed.xml')
'xml'
>>> no_error = _get_url_ext('http：//example.com')
"""
try:
url_path = urlparse(url).path.strip('/')
except ValueError:
re... | 61b94bd2c98686192a47ade9bb240bc4c58904c2 | 3,632,358 |
def connect_server():
"""Connect to azure cosmos DB.
Connet to azure cosmos DB.
Need to insert ID, DB name, table name, and key.
Args:
None
Returns:
clt(str): an instance for connecting to azure cosmos DB server
"""
clt = client.Client(
'wss://<YOURID>... | 1826b4676af381882710a8802392f7f1d4f2253e | 3,632,359 |
def checkCpuTime(sleeptime=0.2):
"""Check if cpu time works correctly"""
if checkCpuTime.passed:
return True
# First test that sleeping does not consume cputime
start1 = process_time()
sleep(sleeptime)
t1 = process_time() - start1
# secondly check by comparing to cpusleep (where we ... | 5b7db840f56b5eafdbfa857c470c316c257c9bac | 3,632,360 |
import logging
import os
import csv
def xmind_to_iwork_csv_file(xmind_file):
"""Convert XMind file to a iwork csv file"""
xmind_file = get_absolute_path(xmind_file)
logging.info('Start converting XMind file(%s) to iwork file...', xmind_file)
testcases = get_xmind_testcase_list(xmind_file)
filehea... | 56fd6f7cb6413bf25d7bf2200d6972765477a9c0 | 3,632,361 |
def load_ply(path):
"""
Loads a 3D mesh model from a PLY file.
:param path: A path to a PLY file.
:return: The loaded model given by a dictionary with items:
'pts' (nx3 ndarray), 'normals' (nx3 ndarray), 'colors' (nx3 ndarray),
'faces' (mx3 ndarray) - the latter three are optional.
"""
... | 289c0854bc3270dafab5689bc53d2507ff27c67c | 3,632,362 |
def parse_range(rng, dictvars={}):
"""Parse a string with an integer range and return a list of numbers, replacing special variables in dictvars."""
parts = rng.split('-')
if len(parts) not in [1, 2]:
raise ValueError("Bad range: '%s'" % (rng,))
parts = [int(i) if i not in dictvars else dictva... | 214109a71c84d06241e29cacaa052d9ce00302c5 | 3,632,363 |
from typing import Union
from typing import Iterable
from typing import List
from pathlib import Path
def relpaths(basepath: _path_t, pattern: Union[str, Iterable[_path_t]]) -> List[str]:
"""Convert a list of paths to relative paths
Parameters
----------
basepath : Union[str, Path]
Path to us... | 80c9febd541d8fd1ab190b2ef36e8929ee387b08 | 3,632,364 |
def binary_backtests_returns(
backtests: pd.DataFrame,
) -> pd.DataFrame:
"""
Converts a Horizon backtest data frame into a binary backtests of directions
"""
return backtests.diff().apply(np.sign).dropna() | 0355cd48620cbdbe54eb4ee48e82f7315f069263 | 3,632,365 |
def calculate_students_features_csv(entry_id, xmodule_instance_args):
"""
Compute student profile information for a course and upload the
CSV to an S3 bucket for download.
"""
# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
action_name = ugettex... | ccf8eae3b9732535c94381ba1909f36bce52556d | 3,632,366 |
def colorMap(value, name="jet", vmin=None, vmax=None):
"""Map a real value in range [vmin, vmax] to a (r,g,b) color scale.
:param value: scalar value to transform into a color
:type value: float, list
:param name: color map name
:type name: str, matplotlib.colors.LinearSegmentedColormap
:return:... | 8e444db6b3e04229dbf8b46cbe68ce6337032b01 | 3,632,367 |
def save_genre(row: dict):
"""Genre's control and save in data base."""
try:
result: Genres = session.query(Genres) \
.filter(Genres.name == row.get('genre_name')) \
.one()
return result
except MultipleResultsFound:
pri... | 0c7e26082816a2639cc4561a1e9ee5f2697a4175 | 3,632,368 |
def specializations(examples_so_far, h):
"""Specialize the hypothesis by adding AND operations to the disjunctions"""
hypotheses = []
for i, disj in enumerate(h):
for e in examples_so_far:
for k, v in e.items():
if k in disj or k == 'GOAL':
continue
... | 5f21edd18477c09d37a03026073c0120b6be41b9 | 3,632,369 |
def formulate_contingency(problem: LpProblem, numerical_circuit: OpfTimeCircuit, flow_f, ratings, LODF, monitor,
lodf_tolerance):
"""
:param problem:
:param numerical_circuit:
:param flow_f:
:param LODF:
:param monitor:
:return:
"""
nbr, nt = ratings.shape
... | ecc5deb3b689a5802341d48e81382d2d602f1ebc | 3,632,370 |
def max_pooling3d(inputs,
pool_size, strides,
padding='valid', data_format='channels_last',
name=None):
"""Max pooling layer for 3D inputs (e.g. volumes).
Arguments:
inputs: The tensor over which to pool. Must have rank 5.
pool_size: An integer or tuple... | 49756ea26e58549115408fbcb4ce179442a09942 | 3,632,371 |
def parareal_engine(x_0, U, num_iter, coarse_model="learned"):
"""Rolls out a trajectory using Parareal
Args:
x_0: Initial state
U: Control sequence
num_iter: Number of Parareal iterations to use for prediction
coarse_model: Learned/Analytical coarse model
Returns:
X: The corresponding state seq... | bd589650711d510fcffb2033dd5f7a501dc4e041 | 3,632,372 |
def plot_posterior_op(trace_values, ax, kde_plot, point_estimate, round_to,
alpha_level, ref_val, rope, text_size=16, **kwargs):
"""Artist to draw posterior."""
def format_as_percent(x, round_to=0):
return '{0:.{1:d}f}%'.format(100 * x, round_to)
def display_ref_val(ref_val):
... | 13d7d12dfac13f803fb08b49970471e4f97c7bff | 3,632,373 |
from operator import sub
from re import M
def change_theme(file: str, theme_name: str, logfile: str) -> bool:
"""
Change Oh My ZSH Theme
"""
if get_zsh_theme(file, logfile):
current_file = read_file_log(file, logfile)
current_theme = get_zsh_theme(file, logfile)[1]
new_theme = ... | 55438f7d93779417aff4dfa4170997269b200dca | 3,632,374 |
def check_tensor(data):
"""Ensure that data is a numpy 4D array."""
assert isinstance(data, np.ndarray)
if data.ndim == 2:
data = data[np.newaxis,np.newaxis,...]
elif data.ndim == 3:
data = data[np.newaxis,...]
elif data.ndim == 4:
pass
else:
raise RuntimeError('... | d641645e9a2c780d52c5e635859bdfcce61f86ab | 3,632,375 |
from typing import Type
from typing import Optional
def _find_first_ref(ref: Ref, message_type: Type[B]) -> Optional[B]:
""" Finds and returns (if exists) the first instance of the specified message type
within the specified Ref.
"""
# Get the body message, if it exists
body = _get_ref_body(ref)
... | 474ad2a2c874c6ae226475fc1e4b144fdd4f72a1 | 3,632,376 |
def verify_activation_token(*, uidb64, token):
"""
:param uidb64: (str) Base 64 of user PK.
:param token: (str) Hash.
:return: (bool) True if user verified, False otherwise.
"""
user_id = force_text(urlsafe_base64_decode(uidb64))
try:
user = User.objects.get(pk=user_id)
except ... | f184a85852906526434dc54b2e26491ad3dafc51 | 3,632,377 |
def softmax_loss_naive(W, X, y, reg):
"""
Softmax loss function, naive implementation (with loops)
Inputs have dimension D, there are C classes, and we operate on minibatches
of N examples.
Inputs:
- W: A numpy array of shape (D, C) containing weights.
- X: A numpy array of shape (N, D) containing a min... | f91d004eefd6e8c2bd7c151628a7aa809b2c40da | 3,632,378 |
def read_protein_from_file(file_pointer):
"""The algorithm Defining Secondary Structure of Proteins (DSSP) uses information on e.g. the
position of atoms and the hydrogen bonds of the molecule to determine the secondary structure
(helices, sheets...).
"""
dict_ = {}
_dssp_dict = {'L': 0, 'H': 1,... | 071a7b04b652261f83311e250e92884e95a4e818 | 3,632,379 |
def match(string, rule='IRI_reference'):
"""Convenience function for checking if `string` matches a specific rule.
Returns a match object or None::
>>> assert match('%C7X', 'pct_encoded') is None
>>> assert match('%C7', 'pct_encoded')
>>> assert match('%c7', 'pct_encoded')
"""
... | c6c2079786651bfaa1ba819251e1d51a276bf8cd | 3,632,380 |
from typing import List
def verify_td3(mrz: List[str]) -> bool:
"""Verify TD3 MRZ"""
if mrz[0][0] != "P":
return False
# if mrz[0][1]: # At the discretion of the issuing State or organization or "<"
# if mrz[0][2:5]: # ISSUING STATE OR ORGANIZATION
# if mrz[0][5:44]: # NAME
if calculat... | 13dca85d0f91cac9bbf759f8a5171e73ddfb4836 | 3,632,381 |
def compute_pwcca(acts1, acts2, epsilon=0.):
""" Computes projection weighting for weighting CCA coefficients
Args:
acts1: 2d numpy array, shaped (neurons, num_datapoints)
acts2: 2d numpy array, shaped (neurons, num_datapoints)
Returns:
Original cca coefficient mean and weighted mean
... | 17f0b6674cd1c45435eb73bc4e754543640543d6 | 3,632,382 |
def read_table(srm_file):
"""
Reads SRM compositional data from file.
For file format information, see:
http://latools.readthedocs.io/en/latest/users/configuration/srm-file.html
Parameters
----------
file : str
Path to SRM file.
Returns
-------
SRM compositions : panda... | 6ec87cab30162af55e3cce659b3ef7a205857595 | 3,632,383 |
def walker_method(for_class=object, methods_list=None):
"""A decorator to add something to the default walker methods,
selecting on class
"""
if methods_list is None: # handle early binding of defaults
methods_list = fallback_walker_method_list
def wrap(walker):
# wrap a walker wi... | b500f04510695e5cfd88590feaa75b27aee3b5b8 | 3,632,384 |
import pandas as pd
from IPython.display import display
def get_data(name_dataset='index',
verbose=True,
address="../datasets/",):
"""
This function is to load dataset from the git repository
:param name_dataset: name of dataset (str)
:param verbose:
:param address: url o... | fa518e744d43950ebcf65d00a5aa474d4fb36443 | 3,632,385 |
import torch
def copy_valid_indices(
acts, # type: torch.Tensor
target, # type: List[List[int]]
act_lens, # type: List[int]
valid_indices, # type: List[int]
):
# type: (...) -> (torch.Tensor, List[List[int]], List[int])
"""Copy the CTC inputs without the erroneous samples"""
if len(val... | 9eac2b7304ff5157ca13fae9d790af6c2b67d9c7 | 3,632,386 |
def is_odd(num: int) -> bool:
"""Is num odd?
:param num: number to check.
:type num: int
:returns: True if num is odd.
:rtype: bool
:raises: ``TypeError`` if num is not an int.
"""
if not isinstance(num, int):
raise TypeError("{} is not an int".format(num))
return num % 2 ==... | 0e5781596a99909e58583859948332c3afb06fb0 | 3,632,387 |
def cross_entropy_loss(y_hat, y):
"""
Cross entropy loss
y_hat: predict y after softmax, shape:(M,d), M is the #of samples
y: shape(M,d)
"""
loss = np.mean(np.sum(- y * np.log(y_hat), axis=-1))
dy = y_hat - y
return loss, dy | 81f6dc61d0ed9d9e5eac4a41042679b3ea01167d | 3,632,388 |
import string
def string_list(resource_name, encoding='utf-8'):
"""Package resource wrapper for obtaining resource contents as list of
strings.
The function uses the 'string' method and splits the resulting string
in lines.
Params:
resource_name: Relative path to the resource in the pack... | 88e7103056e38020670a74a19bfeee90326e7d38 | 3,632,389 |
import os
def get_plugin_names():
""" Get the list of names of registered plugins.
"""
pluginlist = []
# Read
if os.path.isfile(regfile):
with open(regfile, 'rb') as f:
pluginlist = f.read().decode().splitlines()
# Clean
pluginlist = [line.strip() for line in pluginlist... | b86908b2789598f1bd46249ab31f9d1990a87d68 | 3,632,390 |
from typing import Optional
def rpc_get_name() -> Optional[str]:
"""Retrieve the JsonRpc id name."""
global _RpcName
return _RpcName | 2b7d7e9b37b00281b0791e446e5ad4bacee78c4b | 3,632,391 |
def _epd_platform_from_raw_spec(raw_spec):
""" Create an EPDPlatform instance from the metadata info returned by
parse_rawspec.
if no platform is defined ('platform' and 'osdist' set to None), then
None is returned.
"""
platform = raw_spec[_TAG_PLATFORM]
osdist = raw_spec[_TAG_OSDIST]
i... | b6757206e6753441478629519531b0ec5adfc83a | 3,632,392 |
def index(request):
"""The home page for Distance Tracker."""
if request.user.is_authenticated:
today = date.today()
cur_week = today.isocalendar()[1]
cur_month = today.month
cur_year = today.year
exercises_week = Exercise.objects.filter(owner=request.user,
... | 279f6e7c1cb9f2821ebee7b138c7b8b22e60768e | 3,632,393 |
import runpy
import imp
def mod_from_file(mod_name, path):
"""Runs the Python code at path, returns a new module with the resulting globals"""
attrs = runpy.run_path(path, run_name=mod_name)
mod = imp.new_module(mod_name)
mod.__dict__.update(attrs)
return mod | 3ea8109d912582555b76816f55fbb632ba82f189 | 3,632,394 |
def interpolation(x0: float, y0: float, x1: float, y1: float, x: float) -> float:
"""
Performs interpolation.
Parameters
----------
x0 : float.
The coordinate of the first point on the x axis.
y0 : float.
The coordinate of the first point on the y axis.
x1 : float.
T... | f8fc96c6dc6c2eeeeceb22f92b32023f3873fe3e | 3,632,395 |
def do2ptblinding(unblindedfile, cosmfile, inifor2pt, outftag = 'bl', seed='blinded'):
"""
Given unblinded data file, computes and applies blinding factors.
Factors are computed doing [shift cosm 2pt fn]/[ref cosm 2pt fn]
where cosm parameters are taken from pregenerated
cosmfile, and the shifted c... | 64f1cc3d684f18f6cd0443a4333167aba6585054 | 3,632,396 |
import collections
def product_counter_v3(products):
"""Get count of products in descending order."""
return collections.Counter(products) | 22c57d50dc36d3235e6b8b642a4add95c9266687 | 3,632,397 |
def remove_noise(line,minsize=8):
"""Remove small pixels from an image."""
if minsize==0: return line
bin = (line>0.5*np.amax(line))
labels,n = ndimage.label(bin)
sums = ndimage.sum(bin,labels,range(n+1))
sums = sums[labels]
good = np.minimum(bin,1-(sums>0)*(sums<minsize))
return good | 1e19fad38a081db35ac31e3e19d224f4cb8e7d59 | 3,632,398 |
import textwrap
def _ParseFormatDocString(printer):
"""Parses the doc string for printer.
Args:
printer: The doc string will be parsed from this resource format printer.
Returns:
A (description, attributes) tuple:
description - The format description.
attributes - A list of (name, descript... | f5aaffb91cbedbc1b6e0da64cdfb3ff4adfa684e | 3,632,399 |
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