content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_package_attribute(name):
"""Retrieve package attributes from the package itself."""
with open("darwin/__init__.py") as init_file:
for line in init_file:
if line.startswith(name):
return eval(line.split("=")[-1]) | 33e7cdb53fffa844576e4e9387218b3ccbe6926d | 3,609,752 |
def legacy_redirect(id):
"""Redirect to the documents."""
error = {
"code": PIDDoesNotExistRESTError.code,
"description": PIDDoesNotExistRESTError.description,
}
try:
record = get_record_by_legacy_recid(Record, id)
except PIDDoesNotExistError:
return error
schema ... | 9e1716a3b978922954360334271c285a14d80708 | 3,609,753 |
def get_service(hass, config, discovery_info=None):
"""Get the Pushetta notification service."""
api_key = config[CONF_API_KEY]
channel_name = config[CONF_CHANNEL_NAME]
send_test_msg = config[CONF_SEND_TEST_MSG]
pushetta_service = PushettaNotificationService(
api_key, channel_name, send_tes... | 5ae13b5dc464d597b144632770067ca97dd173ae | 3,609,754 |
from typing import Optional
from typing import Dict
from typing import Any
import copy
def filter_end_events_per_object_type(ocel: OCEL, object_type: str, parameters: Optional[Dict[Any, Any]] = None) -> OCEL:
"""
Filters the events in which an object for the given object type terminates its lifecycle.
(E.... | 1cc42b4c362802516ea410b6856868c0cebf08ed | 3,609,755 |
import logging
def scrape_inverter():
""" Connect to the inverter and scrape the metrics """
client.connect()
if "sungrow-" in options['model']:
for i in bus["read"]:
if not load_registers("read", i["start"], int(i["range"])):
return False
for i in bus["holdin... | 9426618499ef6663ef62bfc5bd071fe21f6abc26 | 3,609,756 |
def call(cfg, clargs, cmds, **kwargs):
"""
IMPURE
Delegates work to appropriate `call_*` functions.
Parameters
----------
cfg: dict
Configuration dictionary.
clargs: Namespace
Command line arguments (normalized).
cmds: iter(tuple)
Iterator of commands to be passed to `subpro... | 098269efe7a3f20a15fd55b3d9aaa69cc288e772 | 3,609,757 |
import scipy
def plotPeaks(x, y, peaks, showPeaks=True, plotLabels=False, fig=10, plotScore=False, plotsmooth=True, plothalf=False, plotbottom=False, plotmarker='.-b'):
""" Plot detected peaks
Arguments
---------
x,y : numpy arrays
scandata
peaks : list
list of pe... | db8475879ec60cd0de7750927ec2710196ce3ed5 | 3,609,758 |
def connect(creds):
"""
Connect to cloudformation, with user-provided options.
:param region_creds: The region name and AWS credentials.
:type region_creds: kaws.config.AwsCreds or kaws.config.RegionAwsCreds
:rtype: boto.cloudformation.connection.CloudFormationConnection
Note: IAM cannot authenticate a user us... | b45794b343115f87daae68d38805ae602678ad30 | 3,609,759 |
import re
def isBaidu(url):
"""Return True if this url matches the pattern for Baidu searches"""
#Example: http://www.baidu.com/s?wd=mao+is+cool&rsv_bp=0&ch=&tn=baidu&bar=&rsv_spt=3&ie=utf-8
pattern = 'http://www.baidu.com/s\?wd=[\S+]+'
matches = re.match(pattern, url)
if matches != None:
return True... | b4c06154f1f4f2bd6a18bbcb08c2ce0b4d2cbbc9 | 3,609,760 |
def table_to_json(table):
""" returns a table as JSON """
if arcpyFound == False:
raise Exception("ArcPy is required to use this function")
return arcpy.RecordSet(table).JSON | 40eb4469853779144cb1a60df706bfeb21030a94 | 3,609,761 |
def epost_history_with_retries(qids, dbname, maxretries):
"""Entrez EPost for a batch of queryids.
qids - Collection of query IDs
dbname - target NCBI database
maxretries - maximum download attempts
Returns the generated history, as parsed by Entrez.read()
"""
trie... | 232bd19d3366e3a1c67a786c948d2deb67dc59a2 | 3,609,762 |
def cross_join(df1, df2):
"""
Return a dataframe that is a cross between dataframes
df1 and df2
ref: https://github.com/pydata/pandas/issues/5401
"""
if len(df1) == 0:
return df2
if len(df2) == 0:
return df1
# Add as lists so that the new index keeps the items in
#... | 5db6b7184e133f1bb2c7c63aff791292a4ad3dbf | 3,609,763 |
import FWCore.ParameterSet.Modules
def getModulesOfSequence(sequence):
""" returns the modules found in a sequence.
Note that a module can appear more than once.
"""
class Visitor:
#----------------------------------------
def __init__(self):
self.modules_found = []
... | 79fc93d5a5ea798db419b1156a596993d32b0f40 | 3,609,764 |
def client(clusterrole, namespace, kubeconfig, port, admin_client):
"""I have <clusterrole> permissions in <namespace>."""
needs_admin = namespace == 'all namespaces'
if needs_admin:
return admin_client
ensure_namespace(admin_client, namespace)
k8s_client = kubernetes.config.new_client_fro... | aed5faafc2cc194ed4a69a2d6815b5e4f5fa4b3b | 3,609,765 |
import numpy as np
def read_cnf_mols ( filename, with_v=False, quaternions=False ):
"""Read in molecular configuration."""
with open(filename,"r") as f:
n=int(f.readline()) # Number of atoms
box=float(f.readline()) # Simulation box length (assumed cubic)
revw=np.loadtxt(filename,... | f9ff9578d66d4f57740a10fae727202796b58cc6 | 3,609,766 |
from re import T
def multiply_series(*series) -> Series[T]:
"""
multiple addition
"""
if len(series) < 2:
return series[0]
return multiply_2series(series[0], multiply_series(*series[1:])) | 025adb3b0ce42170438a28d88010942d87935a27 | 3,609,767 |
def get_app_id(c, app_name):
"""
Retrieve app-id for a given app name (in full). Called from get_id, not for use as sub-task.
:return: False on error, True on not found (continue), or string with app uuid
"""
print(f'{CYAN}Retrieving app-id for {app_name}...{COL_END}')
response = c.config.contro... | 5be7a04a770fc927909ebc9d9eba6fff0524080f | 3,609,768 |
def lnL_EB(time: np.ndarray, flux: np.ndarray, sigma: float,
R_EB: float, EB_fluxratio: float, P_orb: float, inc: float,
a: float, R_s: float, u1: float, u2: float,
companion_fluxratio: float = 0.0,
companion_is_host: bool = False):
"""
Calculates the log likelihood o... | 9d17cbff17eefe29d271778b6c819f514026e374 | 3,609,769 |
def detect_burst(relevant_list, total_list):
""" Assume (num. of relevant docs, total num. docs) as the two input lists
returns state costs
"""
state_costs = [(0.0, 0.0)] # for the initial step
s = 2
R = sum(relevant_list)
D = sum(total_list)
p_0 = (1.0 * R) / D
p_1 = p_... | bf4d505d47eb0db2e2f32e254877391359ed408a | 3,609,770 |
def generate_inside_field(center, segment, n, max_features, min_features, feature_variance):
"""
Args:
"center" corresponds to the target instance to explain
Segment corresponds to the size of the hypersphere
n corresponds to the number of instances generated
feature_variance: Ar... | 2355631e9dc43b766c0420478f49629da0b29c9c | 3,609,771 |
import torch
def diversity_score(xyz, distance_type:str, **kwargs) -> torch.tensor.shape == [1]:
"""
:param xyz: [B, P, N, 3] tensor
:param distance_type: shape/part
:param kwargs: {downsample_type:None, npoint_per_part:10}
:return: [1] tensor of divs_score
"""
if distance_type == "shape":... | c04112b7dc8e0049ee318a118720bf7345ee7526 | 3,609,773 |
def find_left_element(sorted_data, right, comparator):
"""!
@brief Returns the element's index at the left side from the right border with the same value as the
last element in the range `sorted_data`.
@details The element at the right is considered as target to search. `sorted_data` must
... | 7edc5ba49da8dbcbdc45310331b68c8ebe0c4ee1 | 3,609,774 |
def CreateTestBudget(client):
"""Creates a budget to run tests with.
Args:
client: AdWordsClient client to obtain services from.
Returns:
int Budget ID
"""
budget_service = client.GetBudgetService(SERVER, VERSION, HTTP_PROXY)
budget = {
'name': 'Budget #%s' % Utils.GetUniqueName(),
'am... | 881095c68260a96195b3c97f4cf83f6a7d30e8f7 | 3,609,777 |
def logout():
"""Used to logout users"""
logout_user()
return redirect(url_for('home')) | 6e59dbb50b6813c67b0804e226dc1ce951d39daa | 3,609,778 |
def gaussian_kernel(x1: np.ndarray, x2: np.ndarray, sigma: int) -> np.ndarray:
"""
Compute the Gaussian kernel between x1 and x2.
Args:
x1: The first vector.
x2: The second vector.
sigma: The sigma of the Gaussian function.
Returns:
The Gaussian kernel between x1 an... | 912f71fe3063b44b39f24886637d3e71cf1f0178 | 3,609,779 |
from datetime import datetime
def make_windows_timestamp_value_getter(value_name):
"""
return a function that fetches the value from the registry key
as a Windows timestamp.
"""
f = make_value_getter(value_name)
def _value_getter(key):
try:
return parse_windows_timestamp(... | 3ad16c5a76cc50a1b1e8632da95807ceb62dc179 | 3,609,780 |
def compute_area(c, target_layer):
"""
Compute area of the component on a given layer
"""
_print("Computing area ", c.name)
c.flatten()
# return c.area(by_spec=True)[layer]
polys_by_spec = c.get_polygons(by_spec=True)
_area = 0
for (layer, polys) in polys_by_spec.items():
_pr... | 89039cd084a51353c2b8b539c9580c38f416b24a | 3,609,781 |
import json
def admin_add_user(request):
"""
:param request:
:return:
"""
# Make sure user has permissions
# Get data
group_results = group.objects.filter(
is_deleted=False,
).values()
permission_set_results = permission_set.objects.filter(
is_deleted=False,
... | 8903f410b05c27a3d26a32f1943958dd7180cc88 | 3,609,783 |
def generate_flac_dirname(library_root, metadata):
"""Build the directory for a track's FLAC file.
:arg str library_root: the FLAC library directory
:arg dict metadata: the finalized metadata for a single track
:return: an absolute directory path
:rtype: :obj:`str`
"""
_log.call(library_ro... | 7e58d138ef98df8e08ca002f8920b5bc0a9a032c | 3,609,784 |
def NamedParameterNames(fn):
"""!
@brief Get names available to use as named parameters.
"""
try:
co = fn.__code__
except AttributeError:
return ()
return co.co_varnames[co.co_posonlyargcount:co.co_argcount+co.co_kwonlyargcount] | 6d62a5d10d02483ee288b765c7e63a060871d839 | 3,609,785 |
def create_and_validate_config(parsed_config: YAML = None) -> Config:
"""Run validation on config values."""
if parsed_config is None:
parsed_config = fetch_config_from_yaml()
# specify the data attribute from the strictyaml YAML type.
_config = Config(
app_config=AppConfig(**parsed_con... | ddb4eeb5a0b73d82cee49ca7fe652ba96d31b47e | 3,609,787 |
def optimizer():
"""
Get the optimizer to use for training
:return: optimizer object
"""
opt = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
return opt | ba1fbe6e59287f31423be28dfc33efd70a29e3d1 | 3,609,788 |
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Unload Trafikverket Weatherstation config entry."""
return await hass.config_entries.async_unload_platforms(entry, PLATFORMS) | 160038c53297a915087c591ed64e00f5d049a2cb | 3,609,789 |
from typing import List
from typing import Tuple
from typing import Any
def min_w_ind(lst: List) -> Tuple[int, Any]:
"""
Returns the min value and its index
:param lst: The list to get the max value in
:return: Min value and its index
"""
val = min(lst)
ind = lst.index(val)
return ind,... | d0da7d1ab1c762f1af2333de6e8b829f8218fd25 | 3,609,792 |
def run_transition():
"""
Transition execution/"stepping"
- run color change for long dimming periods
- runs the generated color dimming generators
:return: Execution verdict
"""
if None not in Data.FADE_OBJ:
try:
r = Data.FADE_OBJ[0].__next__()
g = Data.F... | ec9df50fa790384d570fbe8c2e4a30515defbecb | 3,609,793 |
def DatetimesRangeFieldWidget(field, request): # pylint: disable=invalid-name
"""Datetimes range widget factory"""
return FieldWidget(field, DatetimesRangeWidget(request)) | d389b5a8388813add654afe5084b24c8c75a2edd | 3,609,794 |
from typing import List
from typing import Dict
def get_company_news(
ticker: str,
s_start: str,
s_end: str,
) -> List[Dict]:
"""Get news from a company. [Source: Finnhub]
Parameters
----------
ticker : str
company ticker to look for news articles
s_start: str
date to ... | 8bbcadb8a1278203bb5c7e76a7a06f1bee4ce718 | 3,609,795 |
def count(iterable):
"""
Returns the number of items in `iterable`.
"""
return sum(1 for whatever in iterable) | a9bb4ac70cef36613372c1225202f97f70a642cf | 3,609,796 |
def scipy_rankdata(a):
"""
Ranks the data, dealing with ties appropriately.
Equal values are assigned a rank that is the average of the ranks that
would have been otherwise assigned to all of the values within that set.
Ranks begin at 1, not 0.
Parameters
----------
a : array_like
... | a3b3cd0e87550238ecc3d0be3b444091b5b864dd | 3,609,797 |
def _return_4roles(Z_com_deg, parti_coef):
"""private function for computing 4 roles"""
assert Z_com_deg.shape[0] == parti_coef.shape[0], ("Error, Z_com_deg {} \
should have same length as parti_coef {} ".format(Z_com_deg.shape[0],
parti_coef.sha... | 7e680891f07eabe5ee226227962acb50b2f1461a | 3,609,798 |
import torch
def xy_to_cxcy(xy):
"""
Convert bounding boxes from boundary coordinates (x_min, y_min, x_max, y_max) to center-size coordinates (c_x, c_y, w, h).
:param xy: bounding boxes in boundary coordinates, a tensor of size (n_boxes, 4)
:return: bounding boxes in center-size coordinates, a tensor... | 46eef5bb63c85a84050a57a2fb27618721b31eaa | 3,609,799 |
def delete_app_env(appname, envname):
"""Delete the specified environmental variable set"""
app = _get_app(appname)
deleted = app.remove_env_set(envname)
if not deleted:
abort(404, 'App `%s` has no env `%s`' % (app.name, envname))
return DEFAULT_RETURN_VALUE | c967ee5b8ffa3a66c97179c9386e27cd8f6bc7f7 | 3,609,800 |
def _angle(p,q,r):
"""
compute the positive angle formed by PQR
"""
return np.abs(get_angle_between(Ray(q,p),Ray(q,r))) | 1c0933c1cd8f7385be6942d57bca71b50ff9c3ce | 3,609,801 |
from typing import Sequence
def plotMatrix(matrix, title, xticklabels: Sequence[str], yticklabels: Sequence[str], xlabel: str, ylabel: str, normalize=True, figsize=(9,9),
titleAdd: str = None) -> matplotlib.figure.Figure:
"""
:param matrix: matrix whose data to plot, where matrix[i, j] will be rendere... | 868b884b27054129716e397b3a308cd870b5cd7f | 3,609,802 |
def _sample_flux_snr(distances, fwhm, plsc, n_injections, flux_min, flux_max,
nproc=10, random_seed=42, wavelengths=None, spectrum=None,
mode='median', scaling='temp-standard',
svd_mode='randsvd'):
"""
Sensible flux intervals depend on a combination... | cfd94d10870d599fd4c786aff87f600397debf44 | 3,609,803 |
def addBrightness(image, scale):
"""Adds Brightness to an image.
Parameters:
image (PIL.Image.Image) = The image to be modified.
Returns:
bright.enhance(1.1) = The modified image.
"""
#Use the pillow brightness method to add brightness
bright = ImageEnhan... | de91ca415f03a82c431b67e1fe059ea307362f21 | 3,609,804 |
import requests
import shutil
def download_log_simple():
"""
Download the log of job types that have a single console log
:return: 0 in case of success, -1 in case of an error
"""
response = requests.get("{}/job/{}/{}/consoleText".format(jenkins_url, job_name, build_id), stream=True,
... | 0630bec178113ef11c120ccef9142ab13d6e25d3 | 3,609,805 |
async def _compose(choice):
"""Figure out exactly what resource we're requesting and return the correct
class."""
nchoice = list(choice.keys())[0]
id = list(choice.values())[0]
if '_id' in nchoice:
nchoice = nchoice[:-3]
return ('/'.join([base_uri, nchoice, str(id), '']), nchoice) | c82afd7129068c6f80acb3d61e30031078c59c38 | 3,609,806 |
def validate(guess: str, solution: str) -> str:
"""Validates the user guess against the solution, coloring correct characters"""
return "".join([validate_char(i, guess, solution) for i in range(WORD_LENGTH)]) | 58af7fd7ba42bf591b9689f74e9f5007b5e70d0d | 3,609,807 |
def infection_rate_symptomatic_80x40():
"""
Real Name: b'infection rate symptomatic 80x40'
Original Eqn: b'Susceptible 40*Infected symptomatic 40x80*contact infectivity symptomatic 40x80*(self quarantine policy SWITCH self 40\\\\ * self quarantine policy 40+(1-self quarantine policy SWITCH self 40))/non con... | aca50b41f7241c1c357feee21048e0942e980545 | 3,609,808 |
import re
def input_text(frame_r: tk.Frame,
label_text: str,
text_width: int,
initial: str = None,
side_: constants = TOP,
side_label: constants = LEFT,
fmt: str = None):
"""テキストの入力ボックスを作成
Args:
frame_r (tkinter... | 57d4fb91627b24172991d28eac5e8182a100009e | 3,609,809 |
def plot_pca_variance(data):
"""Runs PCA on passed data and creates the plot figure to visualize the
variance corresponding to each component and returns finally the figure object.
Consider that the method matplotlib.pyplot.show is called inside this function
and the plot is showed if the regarding exec... | 22e03892aa47ef3bbb87c76c6cf5a2874f6fb7ee | 3,609,810 |
def on_volume_balance_vec(data_df, window=14):
"""
On Volume Balance (OBV).
:param data_df: Unstacked for one symbol only.
:param window: An integer number of days to look back.
:return: A pandas Series with the values of OBV for all the valid dates.
"""
obv_delta = data_df['Volume'] * np.si... | fba02e8c0416e2b0e5871a207fb20cc9b94f7852 | 3,609,813 |
def centroidCalculator(cell):
"""
Centroid is assumed to be roundish so the euclidean distance will always
be larger at that region than along protrusions.
"""
edt = distance_transform_edt(cell)
centroid = np.where(edt == np.max(edt))
centroid = [centroid[0][0], centroid[1][0]]
return ... | 0cdca26bed775e792bd761cb5aa484c633041d1f | 3,609,814 |
def is_ethernet_port(interface):
"""Judge whether it is ethernet port"""
ethernet_port = ['ge', '10ge', '25ge', '4x10ge', '40ge', '100ge', 'meth']
if_type = get_interface_type(interface)
if if_type in ethernet_port:
return True
return False | 668826ae07161ecd64714c065bd67adf9e9dd6e2 | 3,609,815 |
def parse_distribution(s):
"""
Parses the distribution from the given string
"""
segments = s.split(' ')
dist = segments[0]
args = segments[1:]
# Check to see if the given distribution is supported
if dist not in distributions.keys():
raise ValueError('Unsupported distribution %... | 0a7bcfaa6f7385e09bfc5e4de4474a2b02eb6048 | 3,609,817 |
def calculate_p_b(*args):
"""
Determines how difficult a text is according to the number of words that are, most likely, unknown to readers.
The other formulas we referred to based the score on the number of words and sentences only
"""
words_count, sentences_count, diff_words_count = args[0... | 420b8269390f50b163c89e97f95b27a282f6f829 | 3,609,819 |
def part1(entries: tuple) -> int:
"""part1 solver"""
card_key, door_key = entries
loop_size = 0
key = 1
while key not in (card_key, door_key):
loop_size += 1
key = (key * 7) % 20201227
if key == card_key:
return pow(door_key, loop_size, 20201227)
return pow(card_key,... | cb4e38704229c3a67a67d7ffd7d8a7e0d2d72628 | 3,609,820 |
def id_function(fixture_value):
"""Convert a param from the use_case fixture to a nicer name.
By default, the name (used in the test generated from the parameterized
fixture) will use the fixture name and a number.
Eg: test_foo[use_case0]
Providing explicit 'ids' (either as strings, or as a functi... | 3db81ccf652a82249f2455d695b563c12017b654 | 3,609,821 |
def application_create(request, name, redirect_uris, scopes=['all_info'],
client_type='confidential', description=None,
grant_type='authorization_code', **kwargs):
""" Registers a new consumer in the Keystone OAuth2 extension.
In FIWARE applications is the name OAu... | a36fec62ac062abd6a3fdf9d4fc109241646359b | 3,609,822 |
def create_spreadsheets_json(worksheet_title=None):
"""
create base parameters json for spreadsheets api call
"""
if worksheet_title is None:
raise ValueError('Missing worksheet_title parameter')
return {
"spreadsheet_key": SPREADSHEET_KEY,
"worksheet_title": worksheet_t... | 8177cb3749399b1ff367cc198d27aaed54e2d06e | 3,609,823 |
def constraint_configure_mentoring(model, tracks, v_tdh):
"""Configure the mentoring of onboarders appropriately."""
# If agent is on, he/she to be paired with exactly 1 mentor:
for d in range(num_days):
for h in agents_onb:
model.Add(
sum(v_mentors.loc[(d, h)].values.tol... | 69c97ee94bf040ce853d25e5c5cf6184e33e0418 | 3,609,825 |
def _parts_span_selector(pspec):
"""
Selector for `System`Span` part specification
"""
if len(pspec.leaves) > 3:
raise MessageException("Part", "span", pspec)
start = 1
stop = None
step = 1
if len(pspec.leaves) > 0:
start = pspec.leaves[0].get_int_value()
if len(pspec... | 0144c5aeb31225a5ed46a5e95a3c4d2c0c7f970f | 3,609,826 |
def selection(triple, variables):
"""Apply selection on a RDF triple"""
bindings = set()
if variables[0] is not None:
bindings.add((variables[0], triple[0]))
if variables[1] is not None:
bindings.add((variables[1], triple[1]))
if variables[2] is not None:
bindings.add((variab... | 7f237f271d7c980e5ece21eacde671ee0f8a1d05 | 3,609,827 |
from typing import Type
from pydantic import BaseModel # noqa: E0611
from typing import List
def schema_factory(
schema_cls: Type[BaseModel],
name: str = "",
excludes: List[str] = ["id", "created_at", "updated_at"],
) -> Type[BaseModel]:
"""
Is used to create a CreateSchema which does not contain... | 729971dc3c2bbab4926da8acd5690678152d666d | 3,609,828 |
def daily_std_error(merged_data):
"""Calculates daily seasonal standard error of the timeseries data in a DataFrame
Parameters
----------
merged_data: DataFrame
A pandas DataFrame with a datetime index and columns containing float type values.
Returns
-------
DataFrame
A p... | 11b5f72ff1a68425cd17d7638590290f5ac883d8 | 3,609,829 |
def bruteforce(model, c, max_iter=1000):
"""
Generiere Zufallsdaten, bis diese eine Klasse maximieren oder die maximale Anzahl an Iterationen verbraucht ist.
"""
shape = (1,) + model.input_shape[1:]
for i in range(max_iter):
image = np.random.random(shape)
prediction = model.predict(... | ccf6d4b899237511b5799c5682de5387108122ab | 3,609,830 |
def process_logic(op):
"""
Parse the binary operation binary expression.
Convert operator to fabric of AST-classes 'AndBexp' / 'OrBexp'.
"""
if op == '&&':
return lambda l, r: AndBexp(l, r)
elif op == '||' or op == '!!':
return lambda l, r: OrBexp(l, r)
else:
raise Ru... | 4f1b5af939b3909ea25bdb95cdffa1da44fd1fc5 | 3,609,831 |
def _build_chef_properties(env, config_file):
"""
Build python object representation of the Chef-solo node.json file from
node_extra.json in config dir and the fabric environment.
"""
json_properties = _parse_json(config_file)
return build_properties(env, "chef", json_properties) | 0c012c55895597abcd4c82cadd43113dacdb5e68 | 3,609,832 |
def bond_vector(xi, xi_neig, box_length):
""" Determine the normalized bond vector between atoms i and j.
"""
bond = xi - nearest_atom_image(xi_neig, xi, box_length)
bond /= np.linalg.norm(bond)
return bond | 13211c0bfd63971edad8f5839cdbe320d901b572 | 3,609,833 |
def get_activation_fn(name, framework="tf"):
"""Returns a framework specific activation function, given a name string.
Args:
name (str): One of "relu" (default), "tanh", or "linear".
framework (str): One of "tf" or "torch".
Returns:
A framework-specific activtion function. e.g. tf.... | 51306d72aa3f1d05111929c841befdd8807318a7 | 3,609,834 |
def rolling_weighted_triangle_conv(values, weights, window_size):
"""Smoothes the data with a window and given the weights
Original algorithm: stackoverflow.com/a/46232913/1257075
Returns:
Smoothed values
Args:
values: data to smoothen
weights: weights for each data point
window_s... | fec4c0bd655d774a5ff138a801edd2a465a2c319 | 3,609,835 |
def par(q):
"""Parameterize using t^3 + t, where t is the polar angle."""
t = np.arctan2(q[1], q[0])
# A simple diffeomorphism from R^1 -> R^1.
return t**3 + t | 9d37a105a66cc9908284a1501fa89fc5c75f3541 | 3,609,836 |
def tanimoto_sparse(str1, str2):
"""!
Calculate the tanimoto coefficient for a pair of sparse vectors
@param str1 str: String of 1s and 0s representing the first compound fingerprint
@param str2 str: String of 1s and 0s representing the second compound fingerprint
@return Returns float
"""
n... | 2a7a6e7c585ceb3aaaa4dfed7e98b01f151e7c06 | 3,609,837 |
import itertools
import time
def perform_experiment(relax: bool, spring_constant: Vector, random_strength: Vector, seed: Vector):
"""
A function that takes potential values of parameters and returns a dataframe with experiment results
for all possible combinations of these parameters.
Parameters
... | 7d6b89993f8df97a0424077569d443598d31bd89 | 3,609,838 |
from bs4 import BeautifulSoup
import codecs
def get_saml_response(html):
"""
Parse SAMLResponse from Shibboleth page
>>> get_saml_response('<input name="a"/>')
>>> get_saml_response('<body xmlns="bla"><form><input name="SAMLResponse" value="eG1s"/></form></body>')
'xml'
"""
soup = Beauti... | 24800c318f7f5f6000c6652d15421c68a97a04a6 | 3,609,839 |
def _is_namespace_visible(context, namespace):
"""Return true if namespace is visible in this context"""
if context.is_admin:
return True
if namespace.get('visibility', '') == 'public':
return True
if namespace['owner'] is None:
return True
if context.owner is not None:
... | 4f3119684681aa2f3c34a62e1674aaa58d26105e | 3,609,840 |
def create_quantum_model():
"""Create a QNN model circuit and readout operation to go along with it."""
data_qubits = cirq.GridQubit.rect(4, 4) # a 4x4 grid.
readout = cirq.GridQubit(-1, -1) # a single qubit at [-1,-1]
circuit = cirq.Circuit()
# Prepare the readout qubit.
circuit.a... | 3574dec302b4a3c0b5bf3767ff66936af2eaaf70 | 3,609,841 |
def get_aa_subseq_df(sg_designs, aa_seq_df, width, id_cols,
transcript_base_col='Transcript Base',
target_transcript_col='Target Transcript',
aa_index_col='AA Index'):
"""Get the amino acid subsequences for a design dataframe
:param sg_designs: Dat... | 181b16fd9887ffe41fea9bbefafa02e0a3e6e557 | 3,609,842 |
def _exception_to_dict(exception):
"""Convert exception to an error object to be sent as response to APIs."""
return {"error": {"type": type(exception).__name__,
"message": exception}} | 4abb81516b604bdfd2f6360a1272556b0b6f6932 | 3,609,843 |
import torch
from typing import List
def get_depth_prediction(
depth_logits: torch.Tensor,
use_dgc_scaling: bool,
camera_matrix: torch.Tensor = None,
real_camera_height: torch.Tensor = None,
panoptic_seg: torch.Tensor = None,
road_class_id: int = -1,
depth_filter_class_ids: List[int] = Non... | 8839c1873c0fd6cd04bc9add7e9cb16b1bfb87af | 3,609,844 |
from typing import Optional
def sync_wait_and_get_s3_object(
uri: Optional[str]=None,
bucket: Optional[str]=None,
key: Optional[str]=None,
sess: Optional[boto3.session.Session]=None,
region_name: Optional[str]=None,
max_wait_seconds: float=DEFAULT_S3_OBJECT_WAIT_TIMEOUT_SECONDS, # ... | 57379f99ce4add147a1570d6e419f1dab47a330b | 3,609,845 |
def read_ceps_test(test_file):
"""
Reads the MFCC features from disk and
returns them in a numpy array.
"""
X = []
y = []
ceps = np.load(test_file)
num_ceps = len(ceps)
X.append(np.mean(ceps[int(num_ceps / 10):int(num_ceps * 9 / 10)], axis=0))
return np.array(X), np.array... | c235d222e610d17f5302cc467867f6989891da3b | 3,609,847 |
def dict_to_object(dictionary):
"""
parse a dictionary and return a dynamic object
:param dictionary: dict
:return: dynamic_object
"""
obj = DynamicClass()
for key in dictionary:
setattr(obj, key, dictionary[key])
return obj | 31135f58545c000a7ee64d71a7938222028d63e6 | 3,609,848 |
import torch
def batchify(fn, chunk):
"""
Constructs a version of 'fn' that applies to smaller batches.
"""
if chunk is None:
return fn
def ret(inputs):
return torch.cat([fn(inputs[i:i + chunk]) for i in range(0, inputs.shape[0], chunk)], 0)
return ret | 4629520fb5aef3a6e280e2eaee30e39baad51f98 | 3,609,849 |
def log_loss(y, p):
""" Compute the log loss by tensorflow from binary truth and predicted score
Parameters
----------
y:
The binary truth: 0 or 1
p:
The predicted score in [0, 1]
Returns
-------
the value of the log loss
"""
return -( y*log(p) + (1-y)*log(1-p) ... | 2e8d02b3a1a1542f5be24df0c0e3ffdbc860e206 | 3,609,850 |
def cleanstrings(df, columns, stringmaps, unmapped=None, simplify=True):
"""Consolidate freeform strings in several dataframe columns.
This function will consolidate freeform strings found in `columns` into
simplified categories, as defined by `stringmaps`. This is useful when
a field contains many dif... | f9fd09efd5f27b19ef275dfc4ff62aa18a4bbbf0 | 3,609,851 |
import datasets
import torch
def get_tst_loader(
data_dir: str,
batch_size: int,
shuffle: bool = True,
num_workers: int = 4,
pin_memory: bool = False,
):
"""
Utility function for loading and returning a multi-process
test iterator over the CIFAR-100 dataset.
If using CUDA, num_work... | ed6bf3a4cab0717e6f2de6c2caa4b40e05d9ee9b | 3,609,852 |
def _any_none(*args):
"""Returns a boolean indicating if any argument is None"""
for arg in args:
if arg is None:
return True
return False | fadb9330fc1f4ffca2cf0105d8513d0be0d5fae1 | 3,609,853 |
def precision(judged_data):
"""
Our relevance judgments are on a graded scale of 0-3, where scores of 1-3 are considered
relevant, and less than 1 is irrelevant. We compute precision of the result set based on
this quanitization.
Args:
judged_data (pandas.DataFrame): A DataFrame with at a m... | 6d4c4ee7793625e4590c01120318afe33cba0b0c | 3,609,854 |
def filter_cycles(cycle_list, **filters):
"""Puts cycles through filters to meet specific requirements.
cycle_list is a list of tuples where the first item is an intake and
the second action is a placement or drop.
filters are the specifications that certain data points inside the
cycles must fit t... | 1abdcf76365cbaced4ac1dcfff96a91282c38370 | 3,609,855 |
def ansi_escape(text):
"""
Replace characters with a special meaning.
"""
return text.replace('\x1b', '?').replace('\b', '?') | 86ff3e7cfce8fcc17e826896e32c28e0d30ee83c | 3,609,856 |
def ajax_get_commandes(request):
"""
This view comes before the feature of sending mass mails to customers. It goes up the number of customers selected by status.
"""
if request.method == 'POST':
try:
event = request.POST.get('event').split(',') if request.POST.get('event').split(',... | 9953c6bff7dd1b5476ee0a17e57f208d1a234bbd | 3,609,857 |
def global_counter() -> int:
""" A really dumb global counter.
This is useful for giving output files a unique number, so if we run the
same command multiple times we can keep their output separate.
"""
global _global_counter
_global_counter += 1
return _global_counter | 8771b81f459ab116998e6927c8e2d0d71676ac0f | 3,609,858 |
def _GetAndroidVersionFromMetadata(metadata):
"""Return the Android version from metadata; None if is does not exist.
In Android PFQ, Android version is set to metadata in master
(MasterSlaveLKGMSyncStage).
"""
version_dict = metadata.GetDict().get('version', {})
return version_dict.get('android') | e1d1ed9d0bbf2f65d646c11007739f6b5a9b78ec | 3,609,859 |
from functools import reduce
def get_in(d, t, default=None):
"""
look up if you can get a tuple of values from a nested dictionary,
each item in the tuple a deeper layer
example: get_in({1: {2: 3}}, (1, 2)) -> 3
example: get_in({1: {2: 3}}, (2, 3)) -> {}
"""
result = reduce(lambda d, t: d... | f92e6c94e3485f4b02a8487f832064de7a42eba5 | 3,609,860 |
def divisible_by_five(n: int) -> bool:
"""Return True if an integer is divisible by 5, and false otherwise."""
if n % 5 > 0:
return False
return True | e4cd2adf7067000f10aa655bb9fd819e525527d2 | 3,609,861 |
def get_imaging_root_data_dir() -> str:
"""
get_imaging_root_data_dir() -> str
Retrieve the root data directory - e.g. containing all subject/sessions data
:return: a string for full path to the root data directory
"""
return _linking_module.get_imaging_root_data_dir() | 9a697c7665de45ba235d3584898799c77e91591d | 3,609,863 |
from typing import Union
from typing import List
def _input_is_valid(
dataset: np.ndarray, predictive_model: object, as_probabilistic: bool,
categorical_indices: Union[None, List[Index]],
class_names: Union[None, List[str]], classes_number: Union[None, int],
feature_names: Union[None, ... | 38f473129ce0ead9831024351f2b084c68f60bd6 | 3,609,864 |
def cvPtr1D(*args):
"""cvPtr1D(CvArr arr, int idx0, int type=None) -> uchar"""
return _cv.cvPtr1D(*args) | db40872eed3bda3a859ccc11838a3ea0a65d4a2d | 3,609,865 |
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