content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import re
def remove_tags(text, which_ones=(), keep=(), encoding=None):
""" Remove HTML Tags only.
`which_ones` and `keep` are both tuples, there are four cases:
============== ============= ==========================================
``which_ones`` ``keep`` what it does
============== ==... | 3aa9bcab068c35245df022c7b09652a016d5070f | 0 |
def count_char(char, word):
"""Counts the characters in word"""
return word.count(char)
# If you want to do it manually try a for loop | 363222f4876c5a574a84fe14214760c505e920b0 | 1 |
def run_on_folder_evaluate_model(folder_path, n_imgs=-1, n_annotations=10):
"""
Runs the object detector on folder_path, classifying at most n_imgs images and manually asks the user if n_annotations crops are correctly classified
This is then used to compute the accuracy of the model
If all images are s... | 0c546194a76598d645cfc3cb7dc5fa1fc854aeca | 2 |
def get_sos_model(sample_narratives):
"""Return sample sos_model
"""
return {
'name': 'energy',
'description': "A system of systems model which encapsulates "
"the future supply and demand of energy for the UK",
'scenarios': [
'population'
]... | 885c251b8bbda2ebc5a950b083faed35c58f41cc | 3 |
from typing import Dict
from pathlib import Path
from typing import Tuple
import codecs
def generate_gallery_md(gallery_conf, mkdocs_conf) -> Dict[Path, Tuple[str, Dict[str, str]]]:
"""Generate the Main examples gallery reStructuredText
Start the mkdocs-gallery configuration and recursively scan the examples... | 766d6b371b6a2930c546ccc191a00c1eb3009dc1 | 4 |
from typing import Union
from typing import TextIO
from typing import List
import yaml
def load_all_yaml(stream: Union[str, TextIO], context: dict = None, template_env = None) -> List[AnyResource]:
"""Load kubernetes resource objects defined as YAML. See `from_dict` regarding how resource types are detected.
... | b3be3b7eb82987849657165e67603b3c701e69cc | 5 |
from typing import Optional
from typing import Dict
def parse_gridspec(s: str, grids: Optional[Dict[str, GridSpec]] = None) -> GridSpec:
"""
"africa_10"
"epsg:6936;10;9600"
"epsg:6936;-10x10;9600x9600"
"""
if grids is None:
grids = GRIDS
named_gs = grids.get(_norm_gridspec_name(s)... | 4c0cc7dc8237a8232a8fb8d86109172d92678535 | 6 |
def make_quantile_normalizer(dist):
"""Returns f(a) that converts to the quantile value in each col.
dist should be an array with bins equally spaced from 0 to 1, giving
the value in each bin (i.e. cumulative prob of f(x) at f(i/len(dist))
should be stored in dist[i]) -- can generate from distribution ... | 395314821be4349d0c5a3b13058db0d498b03ab5 | 7 |
def text():
"""
Route that allows user to send json with raw text of title and body. This
route expects a payload to be sent that contains:
{'title': "some text ...",
'body': "some text ....}
"""
# authenticate the request to make sure it is from a trusted party
verify_token(req... | 7bf4a602d603508894c8f86b2febc6d2a6e8e3c3 | 8 |
def RPL_ENDOFINFO(sender, receipient, message):
""" Reply Code 374 """
return "<" + sender + ">: " + message | 02fc0ef666caf7921e4f4a78a908686fd3dded17 | 10 |
def combined_score(data, side_effect_weights=None):
"""
Calculate a top-level score for each episode.
This is totally ad hoc. There are infinite ways to measure the
performance / safety tradeoff; this is just one pretty simple one.
Parameters
----------
data : dict
Keys should incl... | 9d0161f67de99f10e9d4900114ecf12462fac542 | 11 |
def volatile(func):
"""Wrapper for functions that manipulate the active database."""
def inner(self, *args, **kwargs):
ret = func(self, *args, **kwargs)
self.refresh()
self.modified_db = True
return ret
return inner | bbd8107ecc6a2b36e3677254d2b26f4ef77c3eb3 | 12 |
def input_risk_tolerance():
"""
This allows the user to enter and edit their risk tolerance.
"""
if g.logged_in is True:
if g.inputs is True:
risk_tolerance_id = m_session.query(model.User).filter_by(
id=g.user.id).first().risk_profile_id
risk_tolerance = ... | 09f9ae246beb8e9a9e901e141e11c29e594cb9c7 | 13 |
def check_context(model, sentence, company_name):
"""
Check if the company name in the sentence is actually a company name.
:param model: the spacy model.
:param sentence: the sentence to be analysed.
:param company_name: the name of the company.
:return: True if the company name means a compan... | 993c27924844b7cd0c570a9ce5fa404ef6d29b97 | 15 |
def getItemSize(dataType):
"""
Gets the size of an object depending on its data type name
Args:
dataType (String): Data type of the object
Returns:
(Integer): Size of the object
"""
# If it's a vector 6, its size is 6
if dataType.startswith("VECTOR6"):
return 6
... | 2ab9c83bef56cd8dbe56c558d123e24c9da6eb0e | 16 |
def replace_symbol_to_no_symbol(pinyin):
"""把带声调字符替换为没有声调的字符"""
def _replace(match):
symbol = match.group(0) # 带声调的字符
# 去掉声调: a1 -> a
return RE_NUMBER.sub(r'', PHONETIC_SYMBOL_DICT[symbol])
# 替换拼音中的带声调字符
return RE_PHONETIC_SYMBOL.sub(_replace, pinyin) | a4c3d1a91fedf20016fb4c8b671326ad8cac008c | 17 |
from pyclustering.cluster.kmeans import kmeans
from pyclustering.cluster.center_initializer import kmeans_plusplus_initializer
from pyclustering.cluster.elbow import elbow
from pyclustering.cluster.kmeans import kmeans_visualizer
def elbow_kmeans_optimizer(X, k = None, kmin = 1, kmax = 5, visualize = True):
"""k-... | 53fe501367e85c3d345d0bebdfdccff17e8b93db | 18 |
import time
def FloatDateTime():
"""Returns datetime stamp in Miro's REV_DATETIME format as a float,
e.g. 20110731.123456"""
return float(time.strftime('%Y%m%d.%H%M%S', time.localtime())) | 115aef9104124774692af1ba62a48a5423b9dc2a | 19 |
def xyz_to_rgb(xyz):
"""
Convert tuple from the CIE XYZ color space to the sRGB color space.
Conversion is based on that the XYZ input uses an the D65 illuminate with a 2° observer angle.
https://en.wikipedia.org/wiki/Illuminant_D65
The inverse conversion matrix used was provided by Bruce Lindbloo... | 0c227f7d0ead08afdd0a3dd7946d45ad0cae011b | 20 |
import numbers
def _score(estimator, X_test, y_test, scorer, is_multimetric=False):
"""Compute the score(s) of an estimator on a given test set.
Will return a single float if is_multimetric is False and a dict of floats,
if is_multimetric is True
"""
if is_multimetric:
return _multimetric... | 1b3c136098e625968664518940769678d978aca4 | 21 |
import functools
def asynchronous(datastore=False, obj_store=False, log_store=False):
"""Wrap request handler methods with this decorator if they will require asynchronous
access to DynamoDB datastore or S3 object store for photo storage.
If datastore=True, then a DynamoDB client is available to the handler as... | 2bef0ba95993a4114ecb28b99a2952e2d269b54a | 22 |
def get_translatable_models():
"""
Get the translatable models according to django-modeltranslation
!! only use to migrate from django-modeltranslation !!
"""
_raise_if_not_django_modeltranslation()
return translator.get_registered_models() | b22ca513d3d29dfc7c2d3502cabdcf95e2e4bce9 | 23 |
def schedule_dense_arm_cpu(attrs, inputs, out_type, target):
"""dense arm cpu strategy"""
strategy = _op.OpStrategy()
isa = arm_isa.IsaAnalyzer(target)
if isa.has_dsp_support:
strategy.add_implementation(
wrap_compute_dense(topi.nn.dense),
wrap_topi_schedule(topi.arm_cpu.... | 45b800ceecc14dd62734159d05baa8273cc4c3ff | 24 |
def default_select(identifier, all_entry_points): # pylint: disable=inconsistent-return-statements
"""
Raise an exception when we have ambiguous entry points.
"""
if len(all_entry_points) == 0:
raise PluginMissingError(identifier)
elif len(all_entry_points) == 1:
return all_entry_... | 331ca0108f05e97fcbec95e40111ca6eb5aa835b | 25 |
import json
def read_prediction_dependencies(pred_file):
"""
Reads in the predictions from the parser's output file.
Returns: two String list with the predicted heads and dependency names, respectively.
"""
heads = []
deps = []
with open(pred_file, encoding="utf-8") as f:
for line... | c8280c861d998d0574fb831cd9738b733fd53388 | 26 |
def add_new_ingredient(w, ingredient_data):
"""Adds the ingredient into the database """
combobox_recipes = generate_CBR_names(w)
combobox_bottles = generate_CBB_names(w)
given_name_ingredient_data = DB_COMMANDER.get_ingredient_data(ingredient_data["ingredient_name"])
if given_name_ingredient_data:
... | ea0cbc371502d84223aeec5c18e2f19a020e229a | 27 |
def detect_entities(_inputs, corpus, threshold=None):
"""
Détecte les entités nommées sélectionnées dans le corpus donné en argument.
:param _inputs: paramètres d'entrainement du modèle
:param corpus: corpus à annoter
:param threshold: seuils de détection manuels. Si la probabilité d'une catégorie d... | 1d7dc2ef42a9961daee6260c9fb6b9b2f099e96f | 28 |
def request_video_count(blink):
"""Request total video count."""
url = "{}/api/v2/videos/count".format(blink.urls.base_url)
return http_get(blink, url) | d847d840892908a66f99fae95b91e78b8ddc7dcb | 29 |
def version():
"""Return a ST version. Return 0 if not running in ST."""
if not running_in_st():
return 0
return int(sublime.version()) | d4f51b0a91301a8cdadff126931e7f0e72b8c850 | 30 |
def get_intervention(action, time):
"""Return the intervention in the simulator required to take action."""
action_to_intervention_map = {
0: Intervention(time=time, epsilon_1=0.0, epsilon_2=0.0),
1: Intervention(time=time, epsilon_1=0.0, epsilon_2=0.3),
2: Intervention(time=time, epsilo... | 11c145efc3eb9e7bafc05943294232c161b59952 | 32 |
def draw_labeled_bboxes(img, labels):
"""
Draw the boxes around detected object.
"""
# Iterate through all detected cars
for car_number in range(1, labels[1]+1):
# Find pixels with each car_number label value
nonzero = (labels[0] == car_number).nonzero()
# Identify x and ... | 7bf9a3a5a54a41c49845408d5e04dc5de67eea6c | 33 |
def calc_diff(nh_cube, sh_cube, agg_method):
"""Calculate the difference metric"""
metric = nh_cube.copy()
metric.data = nh_cube.data - sh_cube.data
metric = rename_cube(metric, 'minus sh ' + agg_method)
return metric | 3eb62be75af265bd2fa7323c6c23e3735e1c87be | 35 |
def median_boxcar_filter(data, window_length=None, endpoints='reflect'):
"""
Creates median boxcar filter and deals with endpoints
Parameters
----------
data : numpy array
Data array
window_length: int
A scalar giving the size of the median filter window
endpoints : str
... | 1782998bad2ab02c628d8afbc456c1bea4c2533c | 36 |
import ray
import threading
def test_threaded_actor_api_thread_safe(shutdown_only):
"""Test if Ray APIs are thread safe
when they are used within threaded actor.
"""
ray.init(
num_cpus=8,
# from 1024 bytes, the return obj will go to the plasma store.
_system_config={"max_direct... | f3fd0d4c2621e69c348b734040c7bd49f1f1578b | 37 |
from typing import Optional
def build_template_context(
title: str, raw_head: Optional[str], raw_body: str
) -> Context:
"""Build the page context to insert into the outer template."""
head = _render_template(raw_head) if raw_head else None
body = _render_template(raw_body)
return {
'page... | 38bf538c0c979b6e0aaba1367458140028332385 | 38 |
def inf_set_stack_ldbl(*args):
"""
inf_set_stack_ldbl(_v=True) -> bool
"""
return _ida_ida.inf_set_stack_ldbl(*args) | 2b343bb66229f6ba5f834b3d543fcd75ad08875c | 39 |
def _get_self_compatibility_dict(package_name: str) -> dict:
"""Returns a dict containing self compatibility status and details.
Args:
package_name: the name of the package to check (e.g.
"google-cloud-storage").
Returns:
A dict containing the self compatibility status and deta... | ca29593d3d5941f576a2d033f5754902828a1138 | 40 |
def checksum_md5(filename):
"""Calculates the MD5 checksum of a file."""
amd5 = md5()
with open(filename, mode='rb') as f:
for chunk in iter(lambda: f.read(128 * amd5.block_size), b''):
amd5.update(chunk)
return amd5.hexdigest() | 80cd2bf43274ea060a4d5001d6a319fae59b1e94 | 41 |
def CleanGrant(grant):
"""Returns a "cleaned" grant by rounding properly the internal data.
This insures that 2 grants coming from 2 different sources are actually
identical, irrespective of the logging/storage precision used.
"""
return grant._replace(latitude=round(grant.latitude, 6),
... | 648bb0a76f9a7cfe355ee8ffced324eb6ceb601e | 42 |
def OpenRegistryKey(hiveKey, key):
""" Opens a keyHandle for hiveKey and key, creating subkeys as necessary """
keyHandle = None
try:
curKey = ""
keyItems = key.split('\\')
for subKey in keyItems:
if curKey:
curKey = curKey + "\\" + subKey
else... | d7555a752a08ed0e7bfedbb77583aed9e5b26fe1 | 43 |
import multiprocessing
def eval_py(input_text: str):
"""Runs eval() on the input text on a seperate process and returns output or error.
How to timout on a function call ? https://stackoverflow.com/a/14924210/13523305
Return a value from multiprocess ? https://stackoverflow.com/a/10415215/13523305
"""... | 1058f2877e00370fa4600cf2bcfb334149347cba | 44 |
def trim(str):
"""Remove multiple spaces"""
return ' '.join(str.strip().split()) | ed98f521c1cea24552959aa334ffb0c314b9f112 | 45 |
def build_model_svr(model_keyvalue, inputs, encoder = None, context = None):
"""Builds model from, seal_functions, model params.
model_keyvalue: key identifying model
inputs: properly formatted encrypted inputs for model
encoder: SEAL encoder object
context: SEAL context object
"... | 0e36d94c5305aa55523d76d2f8afac17b9c7d9b0 | 46 |
def find_similar(collection):
""" Searches the collection for (probably) similar artist and returns
lists containing the "candidates". """
spellings = defaultdict(list)
for artist in collection:
spellings[normalize_artist(artist)].append(artist)
return [spellings[artist] for artist in ... | c11f93d0da7ff27f89c51d1d255d75e31c6c539f | 47 |
def vim_print(mse_ref, mse_values, x_name, ind_list=0, with_output=True,
single=True, partner_k=None):
"""Print Variable importance measure and create sorted output.
Parameters
----------
mse_ref : Numpy Float. Reference value of non-randomized x.
mse_values : Numpy array. MSE's for r... | 4c7eef9dc15d50b904dfe3df51586d77af70d776 | 48 |
def from_column_list(
col_names, col_types=None,
col_blobs=None, col_metadata=None
):
"""
Given a list of names, types, and optionally values, construct a Schema.
"""
if col_types is None:
col_types = [None] * len(col_names)
if col_metadata is None:
col_metadata = [None] * le... | 22fc57657bc144304ef0afbdd74acf9ed63faba0 | 49 |
import torch
def get_optimizer(lr):
"""
Specify an optimizer and its parameters.
Returns
-------
tuple(torch.optim.Optimizer, dict)
The optimizer class and the dictionary of kwargs that should
be passed in to the optimizer constructor.
"""
return (torch.optim.SGD,
... | 213090258414059f7a01bd40ecd7ef04158d60e5 | 50 |
def _from_list(data: any) -> dict:
"""Convert lists to indexed dictionaries.
:arg data: An ordered map.
:returns: An ordered map.
"""
if isinstance(data, list):
return dict([(str(i), _from_list(v)) for i, v in enumerate(data)])
if isinstance(data, dict):
return dict([(key, _fro... | 06c757276edbc013c4094872f4063077cec2c589 | 51 |
def parse_date(ses_date):
"""This parses a date string of the form YYYY-MM-DD and returns
the string, year, month, day and day of year."""
[yr,mn,dy] = ses_date.split('-')
year = int(yr)
month = int(mn)
day = int(dy[:2]) # strip of any a or b
DOY = day_of_year(year,month,day)
return ses_date,year,month,... | a8105f9f39869402863f14a1d68ff37a7f25ed74 | 52 |
import requests
import json
def get_access_token(consumer_key, consumer_secret):
"""
:return: auth token for mpesa api calls
"""
oauth_url = "https://api.safaricom.co.ke/oauth/v1/generate?grant_type=client_credentials"
response = requests.get(oauth_url, auth=HTTPBasicAuth(consumer_key, consumer_s... | 15d09439d0b6e135c4f87958fe116e686c38cca2 | 53 |
def create_feed_forward_dot_product_network(observation_spec, global_layers,
arm_layers):
"""Creates a dot product network with feedforward towers.
Args:
observation_spec: A nested tensor spec containing the specs for global as
well as per-arm observations.
... | ed4e95ce10859e976800fd88b6caceffd6ca09a2 | 54 |
import logging
def check_collisions(citekeys_df):
"""
Check for short_citekey hash collisions
"""
collision_df = citekeys_df[['standard_citekey', 'short_citekey']].drop_duplicates()
collision_df = collision_df[collision_df.short_citekey.duplicated(keep=False)]
if not collision_df.empty:
... | b01b53323f7885a7375ba78b50222bcbe9980498 | 55 |
def get_user(module, system):
"""Find a user by the user_name specified in the module"""
user = None
user_name = module.params['user_name']
try:
user = system.users.get(name=user_name)
except ObjectNotFound:
pass
return user | f674352998e444a184ab2a2a6a2caedc35611e49 | 56 |
def appointments(request):
"""Page for users to view upcoming appointments."""
appointments = Appointment.objects.filter(patient=request.user.patient)
context = {
'appointments': appointments
}
return render(request, 'patients/appointments.html', context) | ad7bab85db19f907631a8c9e25b65048abab7e6b | 57 |
def _SignedVarintDecoder(mask):
"""Like _VarintDecoder() but decodes signed values."""
local_ord = ord
def DecodeVarint(buffer, pos):
result = 0
shift = 0
while 1:
b = local_ord(buffer[pos])
result |= ((b & 0x7f) << shift)
pos += 1
if not (b & 0x80):
if result > 0x7fff... | de88a082cc90f6370674723173f4c75ee7025f27 | 58 |
def is_valid_msg_type(x):
"""
@return: True if the name is a syntatically legal message type name
@rtype: bool
"""
if not x or len(x) != len(x.strip()):
return False
base = base_msg_type(x)
if not roslib.names.is_legal_resource_name(base):
return False
# parse array indic... | ca6b6b2e62ffa26a795cbbccab01667a8ce9470e | 59 |
def get_ascii_matrix(img):
"""(Image) -> list of list of str\n
Takes an image and converts it into a list of list containing a string which maps to brightness
of each pixel of each row
"""
ascii_map = "`^\",:;Il!i~+_-?][}{1)(|\\/tfjrxnuvczXYUJCLQ0OZmwqpdbkhao*#MW&8%B@$"
brightness_matrix = get... | e8b6a160fc082a868267971937e56e2f6a1eb9e4 | 60 |
from typing import List
from typing import Dict
from typing import Any
def to_scene_agent_prediction_from_boxes_separate_color(
tracked_objects: TrackedObjects, color_vehicles: List[int], color_pedestrians: List[int], color_bikes: List[int]
) -> List[Dict[str, Any]]:
"""
Convert predicted observations int... | 728d471fbc15957c57f4b3a6da68bfffdbf875ac | 61 |
def stretch(snd_array, factor, window_size, h):
""" Stretches/shortens a sound, by some factor. """
phase = np.zeros(window_size)
hanning_window = np.hanning(window_size)
result = np.zeros( len(snd_array) /factor + window_size)
for i in np.arange(0, len(snd_array)-(window_size+h), h*factor):
... | aeb12b6da26de9630eec9ad84caf9f30bd6f1f71 | 62 |
def guess_encoding(text):
""" Given bytes, determine the character set encoding
@return: dict with encoding and confidence
"""
if not text: return {'confidence': 0, 'encoding': None}
enc = detect_charset(text)
cset = enc['encoding']
if cset.lower() == 'iso-8859-2':
# Anomoaly -- ch... | f58d652b7a77652ace1c27b315fc81ac82726a03 | 63 |
def is_edit_end_without_next(line, configs):
"""
Is the line indicates that 'edit' section ends without 'next' end marker
(special case)?
- config vdom
edit <name>
...
end
:param line: A str represents a line in configurations output
:param configs: A stack (list) holding c... | 0398fc86ee7911686bfdaa0cdf6431f53db1ccba | 64 |
def get_live_args(request, script=False, typed=False):
""" Get live args input by user | request --> [[str], [str]]"""
arg_string = list(request.form.values())[0]
if script:
return parse_command_line_args(arg_string)
if typed:
try:
all_args = parse_type_args(arg_string)
... | 9e56043760e9ac263a737166c796640170a6174c | 65 |
import codecs
import csv
def open_csv(path):
"""open_csv."""
_lines = []
with codecs.open(path, encoding='utf8') as fs:
for line in csv.reader(fs):
if len(line) == 3:
_lines.append(line)
return _lines | 501ff4a2a1a242439c21d3131cecd407dcfa36af | 66 |
from typing import Union
from pathlib import Path
from typing import Dict
def parse_metadata(metadata_filepath: Union[str, Path]) -> Dict:
"""Parse the metadata file retreived from the BEACO2N site
Args:
metadata_filepath: Path of raw CSV metadata file
pipeline: Are we running as part of the ... | 321e9abb82172ee7d06423d2703ec2499aefbee9 | 67 |
def unit_norm(model,axis=0):
"""
Constrains the weights incident to each hidden unit to have unit norm.
Args:
axis (int):axis along which to calculate weight norms.
model : the model contains weights need to setting the constraints.
"""
def apply_constraint(t: Tensor):
w_d... | ffe517f2f883541d5d3736a2bb3263e6349ffe18 | 68 |
def responsive_units(spike_times, spike_clusters, event_times,
pre_time=[0.5, 0], post_time=[0, 0.5], alpha=0.05):
"""
Determine responsive neurons by doing a Wilcoxon Signed-Rank test between a baseline period
before a certain task event (e.g. stimulus onset) and a period after the tas... | 10493948d8fc710a95e1267b4543bc63cdebc661 | 69 |
def create_link(seconds, image_name, size):
"""
Function returns temporary link to the image
"""
token = signing.dumps([str(timezone.now() + timedelta(seconds=int(seconds))), image_name, size])
return settings.SERVER_PATH + reverse("image:dynamic-image", kwargs={"token": token}) | e0ede3b6a28e1bfa3a69d8019b0141cd85b77cce | 70 |
def read_one_hot_labels(filename):
"""Read topic labels from file in one-hot form
:param filename: name of input file
:return: topic labels (one-hot DataFrame, M x N)
"""
return pd.read_csv(filename, dtype=np.bool) | df6f0be241c8f5016ff66d02a54c899298055bd7 | 71 |
def make_randint_list(start, stop, length=10):
""" Makes a list of randomly generated integers
Args:
start: lowest integer to be generated randomly.
stop: highest integer to be generated randomly.
length: length of generated list.
Returns:
list of random numbers between sta... | 6ac9a20b9c5c87d9eff2b13a461cf266381961e2 | 72 |
def merge(intervals: list[list[int]]) -> list[list[int]]:
"""Generate a new schedule with non-overlapping intervals by merging intervals which overlap
Complexity:
n = len(intervals)
Time: O(nlogn) for the initial sort
Space: O(n) for the worst case of no overlapping intervals
... | 49a9d7d461ba67ec3b5f839331c2a13d9fc068d0 | 73 |
def df_drop_duplicates(df, ignore_key_pattern="time"):
"""
Drop duplicates from dataframe ignore columns with keys containing defined pattern.
:param df:
:param noinfo_key_pattern:
:return:
"""
ks = df_drop_keys_contains(df, ignore_key_pattern)
df = df.drop_duplicates(ks)
return d... | babd7be3ef66cef81a5a2192cf781afd2f96aca9 | 74 |
def get_mediawiki_flow_graph(limit, period):
"""
:type limit int
:type period int
:rtype: list[dict]
"""
# https://kibana5.wikia-inc.com/goto/e6ab16f694b625d5b87833ae794f5989
# goreplay is running in RES (check SJC logs only)
rows = ElasticsearchQuery(
es_host=ELASTICSEARCH_HOST,... | c82976c24d80f7784f32e36666f791fed4ada769 | 75 |
def bsplslib_Unperiodize(*args):
"""
:param UDirection:
:type UDirection: bool
:param Degree:
:type Degree: int
:param Mults:
:type Mults: TColStd_Array1OfInteger &
:param Knots:
:type Knots: TColStd_Array1OfReal &
:param Poles:
:type Poles: TColgp_Array2OfPnt
:param Weight... | 0fad8703881304c9d169feb4ce58f31b29d1703b | 76 |
def genomic_del3_abs_37(genomic_del3_37_loc):
"""Create test fixture absolute copy number variation"""
return {
"type": "AbsoluteCopyNumber",
"_id": "ga4gh:VAC.Pv9I4Dqk69w-tX0axaikVqid-pozxU74",
"subject": genomic_del3_37_loc,
"copies": {"type": "Number", "value": 2}
} | ed417f1b0eba79a5db717bd16ca79dd85c55c381 | 77 |
def get_configinfo(env):
"""Returns a list of dictionaries containing the `name` and `options`
of each configuration section. The value of `options` is a list of
dictionaries containing the `name`, `value` and `modified` state of
each configuration option. The `modified` value is True if the value
d... | c96b784f389af7c043977fbc1707840ef56a6486 | 79 |
def given_energy(n, ef_energy):
"""
Calculate and return the value of given energy using given values of the params
How to Use:
Give arguments for ef_energy and n parameters
*USE KEYWORD ARGUMENTS FOR EASY USE, OTHERWISE
IT'LL BE HARD TO UNDERSTAND AN... | 98095581bfaf4b8a6dbf59dce86b02e3f1fa6002 | 80 |
def sequence_sigmoid_cross_entropy(labels,
logits,
sequence_length,
average_across_batch=True,
average_across_timesteps=False,
average_across_cla... | 7eaea7dc8c416f0a37f0d6668ec175725f1fea04 | 81 |
import math
import torch
def stats(func):
"""Stats printing and exception handling decorator"""
def inner(*args):
try:
code, decoded, res = func(*args)
except ValueError as err:
print(err)
else:
if FORMATTING:
code_length = 0
... | 99e39e204238d09bd7275ac29089898ff3d22f6a | 82 |
import asyncio
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Unload a config entry."""
unload_ok = all(
await asyncio.gather(
*[
hass.config_entries.async_forward_entry_unload(entry, platform)
for platform in PLATFORMS
... | f44f9d9f3a566794547571563ae94ce433082d6d | 83 |
def get_ucp_worker_info():
"""Gets information on the current UCX worker, obtained from
`ucp_worker_print_info`.
"""
return _get_ctx().ucp_worker_info() | c40a0debcc769422b4cd8cd03018b57dd7efe224 | 84 |
from datetime import datetime
def check_can_collect_payment(id):
"""
Check if participant can collect payment this is true if :
- They have been signed up for a year
- They have never collected payment before or their last collection was more than 5 months ago
"""
select = "SELECT time_sign_up... | a057b6599bfd5417a17de1672b4ccf2023991e6e | 85 |
def plus_tensor(wx, wy, wz=np.array([0, 0, 1])):
"""Calculate the plus polarization tensor for some basis.c.f., eq. 2 of https://arxiv.org/pdf/1710.03794.pdf"""
e_plus = np.outer(wx, wx) - np.outer(wy, wy)
return e_plus | c5632dcfffa9990c8416b77ff0df728ae46c34bc | 86 |
import json
def duplicate_objects(dup_infos):
"""Duplicate an object with optional transformations.
Args:
dup_infos (list[dict]): A list of duplication infos.
Each info is a dictionary, containing the following data:
original (str): Name of the object to duplicate.
... | d8281eb6862cd7e022907bc479b03fc74cb3c78c | 87 |
def _list_data_objects(request, model, serializer):
"""a factory method for querying and receiving database objects"""
obj = model.objects.all()
ser = serializer(obj, many=True)
return Response(ser.data, status=status.HTTP_200_OK) | 80f43efdf1d09e73fda7be8ee5f8e37a163892f7 | 88 |
import configparser
def load_conf(file='./config', section='SYNTH_DATA'):
"""load configuration
Args:
file (str, optional): path to conf file. Defaults to './config'.
section (str, optional): name of section. Defaults to 'SYNTH_DATA'.
Returns:
[str]: params of configurat... | a30240e98d9fd1cdc1bc7746566fdb07b842a8dc | 89 |
import math
def distance(a, b):
"""
Computes a
:param a:
:param b:
:return:
"""
x = a[0] - b[0]
y = a[1] - b[1]
return math.sqrt(x ** 2 + y ** 2) | 60b637771cd215a4cf83761a142fb6fdeb84d96e | 90 |
def approve_pipelines_for_publishing(pipeline_ids): # noqa: E501
"""approve_pipelines_for_publishing
:param pipeline_ids: Array of pipeline IDs to be approved for publishing.
:type pipeline_ids: List[str]
:rtype: None
"""
pipe_exts: [ApiPipelineExtension] = load_data(ApiPipelineExtension)
... | e5ae4dfc0889fc95e3343a01111323eec43e1f93 | 91 |
def make_tokenizer_module(tokenizer):
"""tokenizer module"""
tokenizers = {}
cursors = {}
@ffi.callback("int(int, const char *const*, sqlite3_tokenizer **)")
def xcreate(argc, argv, ppTokenizer):
if hasattr(tokenizer, "__call__"):
args = [ffi.string(x).decode("utf-8") for x in a... | 73f38b71f15b286a95a195296c5c265ba2da87f9 | 92 |
def looping_call(interval, callable):
"""
Returns a greenlet running your callable in a loop and an Event you can set
to terminate the loop cleanly.
"""
ev = Event()
def loop(interval, callable):
while not ev.wait(timeout=interval):
callable()
return gevent.spawn(loop, in... | 0df2a822c2eb56b8479224b0463bf9a2ad34f1e7 | 93 |
def rsquared_adj(r, nobs, df_res, has_constant=True):
"""
Compute the adjusted R^2, coefficient of determination.
Args:
r (float): rsquared value
nobs (int): number of observations the model was fit on
df_res (int): degrees of freedom of the residuals (nobs - number of model params... | 8d466437db7ec9de9bc7ee1d9d50a3355479209d | 94 |
def metadata_factory(repo, json=False, **kwargs):
"""
This generates a layout you would expect for metadata storage with files.
:type json: bool
:param json: if True, will return string instead.
"""
output = {
"baseline_filename": None,
"crontab": "0 0 * * *",
"exclude_r... | 8dc0cd4cb5aa194c915146efbe0a743b5047561d | 95 |
from typing import Optional
from typing import Sequence
def inpand(clip: vs.VideoNode, sw: int, sh: Optional[int] = None, mode: XxpandMode = XxpandMode.RECTANGLE,
thr: Optional[int] = None, planes: int | Sequence[int] | None = None) -> vs.VideoNode:
"""
Calls std.Minimum in order to shrink each pix... | 67d05b2ef31fdc3b544d063a571d39a1c1a3ecf8 | 96 |
def _extract_aggregate_functions(before_aggregate):
"""Converts `before_aggregate` to aggregation functions.
Args:
before_aggregate: The first result of splitting `after_broadcast` on
`intrinsic_defs.FEDERATED_AGGREGATE`.
Returns:
`zero`, `accumulate`, `merge` and `report` as specified by
`can... | 22aff3c077b94c5eae8841448c2a55bbfa311487 | 97 |
def _make_system(A, M, x0, b):
"""Make a linear system Ax = b
Args:
A (cupy.ndarray or cupyx.scipy.sparse.spmatrix or
cupyx.scipy.sparse.LinearOperator): sparse or dense matrix.
M (cupy.ndarray or cupyx.scipy.sparse.spmatrix or
cupyx.scipy.sparse.LinearOperator): precond... | 37d877dc8522a476c1ff0be34db01fe8d711dbb7 | 98 |
from typing import List
def merge_intersecting_segments(segments: List[Segment]) -> List[Segment]:
"""
Merges intersecting segments from the list.
"""
sorted_by_start = sorted(segments, key=lambda segment: segment.start)
merged = []
for segment in sorted_by_start:
if not merged:
... | e18498d9a9695b2c5796fb6e006f375541f704c7 | 99 |
def change_log_root_key():
"""Root key of an entity group with change log."""
# Bump ID to rebuild the change log from *History entities.
return ndb.Key('AuthDBLog', 'v1') | 465ab46b7e884d7f5e217861d6c451c491e04f07 | 100 |
import numpy
def load_file(filename):
"""Loads a TESS *spoc* FITS file and returns TIME, PDCSAP_FLUX"""
hdu = fits.open(filename)
time = hdu[1].data['TIME']
flux = hdu[1].data['PDCSAP_FLUX']
flux[flux == 0] = numpy.nan
return time, flux | 50c777903b26c658c828346af53e3a659d1eb46b | 101 |
def create_insight_id_extension(
insight_id_value: str, insight_system: str
) -> Extension:
"""Creates an extension for an insight-id with a valueIdentifier
The insight id extension is defined in the IG at:
https://alvearie.io/alvearie-fhir-ig/StructureDefinition-insight-id.html
Args:
... | 72b000cdc3903308ca8692c815e562511fd50b91 | 102 |
def ReadNotifyResponseHeader(payload_size, data_type, data_count, sid, ioid):
"""
Construct a ``MessageHeader`` for a ReadNotifyResponse command.
Read value of a channel. Sent over TCP.
Parameters
----------
payload_size : integer
Size of DBR formatted data in payload.
data_type ... | 5d088416f5fca6e0aeb3ef1f965ca7c00d8a6c90 | 103 |
def substitute_T5_cols(c, cols, nlu_identifier=True):
"""
rename cols with base name either <t5> or if not unique <t5_<task>>
"""
new_cols = {}
new_base_name = 't5' if nlu_identifier=='UNIQUE' else f't5_{nlu_identifier}'
for col in cols :
if '_results' in col : new_cols[col] = n... | 2820706faff786011abbd896551026c65bb0d848 | 104 |
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