content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import math
def fnCalculate_Bistatic_Coordinates(a,B):
"""
Calculate the coordinates of the target in the bistatic plane
A,B,C = angles in the triangle
a,b,c = length of the side opposite the angle
Created: 22 April 2017
"""
u = a*math.cos(B);
v = a*math.sin(B);
return u,v | cc1dce6ef0506b987e42e3967cf36ea7b46a30d7 | 3,641,400 |
def _fn_lgamma_ ( self , b = 1 ) :
""" Gamma function: f = log(Gamma(ab))
>>> f =
>>> a = f.lgamma ( )
>>> a = f.lgamma ( b )
>>> a = lgamma ( f )
"""
return _fn_make_fun_ ( self ,
b ,
Os... | 62183327967840e26dfc009c2357de2c31171082 | 3,641,401 |
def convolve_smooth(x, win=10, mode="same"):
"""Smooth data using a given window size, in units of array elements, using
the numpy.convolve function."""
return np.convolve(x, np.ones((win,)), mode=mode) / win | b41edf8c0d58355e28b507a96b129c4720412a81 | 3,641,402 |
def _conditional(Xnew, feat, kern, f, *, full_cov=False, full_output_cov=False, q_sqrt=None, white=False, Lm=None):
"""
Multioutput conditional for an independent kernel and shared inducing features.
Same behaviour as conditional with non-multioutput kernels.
The covariance matrices used to calculate t... | 5158eb93f30fdac14bafb959e63cd8ad26fc45a7 | 3,641,403 |
import array
def descent(x0, fn, iterations=1000, gtol=10**(-6), bounds=None, limit=0, args=()):
"""A gradient descent optimisation solver.
Parameters
----------
x0 : array-like
n x 1 starting guess of x.
fn : obj
The objective function to minimise.
iterations : int
Ma... | ec132e7857cf4a941c54fc5db9085bdf013fb7a2 | 3,641,404 |
def count_teams_for_party(party_id: PartyID) -> int:
"""Return the number of orga teams for that party."""
return db.session \
.query(DbOrgaTeam) \
.filter_by(party_id=party_id) \
.count() | 07373325dd7d7ab21ef0cb1145d37b2d85292358 | 3,641,405 |
def num_series(datetime_series) -> pd.Series:
"""Return a datetime series with numeric values."""
return datetime_series(LENGTH) | 4d208bfbae5f3e7263663d06102aa0b290f4fd4e | 3,641,406 |
import re
def obtain_ranks(outputs, targets, mode=0):
"""
outputs : tensor of size (batch_size, 1), required_grad = False, model predictions
targets : tensor of size (batch_size, ), required_grad = False, labels
Assume to be of format [1, 0, ..., 0, 1, 0, ..., 0, ..., 0]
mode == 0: rank from ... | 72fc737d72fe0d6d3ff4e08a5a16acf05e0e88cb | 3,641,407 |
from typing import Dict
from typing import Any
def sample_a2c_params(trial: optuna.Trial) -> Dict[str, Any]:
"""
Sampler for A2C hyperparams.
"""
lr_schedule = trial.suggest_categorical("lr_schedule", ["linear", "constant"])
learning_rate = trial.suggest_loguniform("learning_rate", 1e-5, 1)
n_... | f9f966f3c41a32a15253ba612d94e1254a586e86 | 3,641,408 |
def location_parser(selected_variables, column):
"""
Parse the location variable by creating a list of tuples.
Remove the hyphen between the start/stop positions. Convert all elements to
integers and create a list of tuples.
Parameters:
selected_variables (dataframe): The dataframe contain... | 106f669269276c37652e92e62eb8c2c52dfe7637 | 3,641,409 |
import torch
import math
def get_qmf_bank(h, n_band):
"""
Modulates an input protoype filter into a bank of
cosine modulated filters
Parameters
----------
h: torch.Tensor
prototype filter
n_band: int
number of sub-bands
"""
k = torch.arange(n_band).reshape(-1, 1)
... | 87e8cf3b0d85a6717cce9dc09f7a0a3e3581e498 | 3,641,410 |
import math
def compare_one(col, cons_aa, aln_size, weights, aa_freqs, pseudo_size):
"""Compare column amino acid frequencies to overall via G-test."""
observed = count_col(col, weights, aa_freqs, pseudo_size)
G = 2 * sum(obsv * math.log(obsv / aa_freqs.get(aa, 0.0))
for aa, obsv in observ... | 910431062ac9ddef467d4818d3960385a2d4392b | 3,641,411 |
def open(uri, mode='a', eclass=_eclass.manifest):
"""Open a Blaze object via an `uri` (Uniform Resource Identifier).
Parameters
----------
uri : str
Specifies the URI for the Blaze object. It can be a regular file too.
The URL scheme indicates the storage type:
* carray: Ch... | c0a5069f5d7f39c87aae5af361df86b6f4fc4189 | 3,641,412 |
def create_df(dic_in, cols, input_type):
"""
Convert JSON output from OpenSea API to pandas DataFrame
:param dic_in: JSON output from OpenSea API
:param cols: Keys in JSON output from OpenSea API
:param input_type: <TBD> save the columns with dictionaries as entries seperately
:return: Cleaned D... | 7b6a9445c956cc5d2850516d4c7dc2208b7391f7 | 3,641,413 |
def file_updated_at(file_id, db_cursor):
"""
Update the last time the file was checked
"""
db_cursor.execute(queries.file_updated_at, {'file_id': file_id})
db_cursor.execute(queries.insert_log, {'project_id': settings.project_id, 'file_id': file_id,
'log_ar... | bb0ec859c249b96e3ed066c3664e792100f5f23c | 3,641,414 |
def action_to_upper(action):
"""
action to upper receives an action in pddl_action_representation, and returns it in upper case.
:param action: A action in PddlActionRepresentation
:return: PddlActionRepresentation: The action in upper case
"""
if action:
action.name = action.name.uppe... | e9266ad79d60a58bf61d6ce81284fa2accbb0b8d | 3,641,415 |
from lvmspec.qa.qa_frame import QA_Frame
import os
def load_qa_frame(filename, frame=None, flavor=None):
""" Load an existing QA_Frame or generate one, as needed
Args:
filename: str
frame: Frame object, optional
flavor: str, optional
Type of QA_Frame
Returns:
... | 5c8b7d279d98ddb76c6ca54a53779d88d27dab3b | 3,641,416 |
from typing import Type
from typing import Dict
from typing import Any
def generate_model_example(model: Type["Model"], relation_map: Dict = None) -> Dict:
"""
Generates example to be included in schema in fastapi.
:param model: ormar.Model
:type model: Type["Model"]
:param relation_map: dict wit... | 1aafb069ff129453f9012de79d09c326224ceb5b | 3,641,417 |
def compare_folder(request):
""" Creates the compare folder path `dione-sr/tests/data/test_name/compare`.
"""
return get_test_path('compare', request) | b78bc261373d47bd3444c24c54c57a600a3855ad | 3,641,418 |
def _get_param_combinations(lists):
"""Recursive function which generates a list of all possible parameter values"""
if len(lists) == 1:
list_p_1 = [[e] for e in lists[0]]
return list_p_1
list_p_n_minus_1 = _get_param_combinations(lists[1:])
list_p_1 = [[e] for e in lists[0]]
list_... | b4903bea79aebeabf3123f03de986058a06a21f4 | 3,641,419 |
def system_mass_spring_dumper():
"""マスバネダンパ系の設計例"""
# define the system
m = 1.0
k = 1.0
c = 1.0
A = np.array([
[0.0, 1.0],
[-k/m, -c/m]
])
B = np.array([
[0],
[1/m]
])
C = np.eye(2)
D = np.zeros((2,1),dtype=float)
W = np.diag([1.0, 1.0])
... | 8a054753d7bbaa06b7217ce98d38074122d41f32 | 3,641,420 |
def explore_voxel(
start_pos: tuple,
masked_atlas: ma.MaskedArray,
*,
count: int = -1,
) -> int:
"""Explore a given voxel.
Ask Dimitri for more details.
Seems like this is a BFS until a voxel with a different value is
found or the maximal number of new voxels were seen.
Parameters... | d2f73562497a325a42a0322f3aba9be995809a24 | 3,641,421 |
import requests
def get_green_button_xml(
session: requests.Session, start_date: date, end_date: date
) -> str:
"""Download Green Button XML."""
response = session.get(
f'https://myusage.torontohydro.com/cassandra/getfile/period/custom/start_date/{start_date:%m-%d-%Y}/to_date/{end_date:%m-%d-%Y}/f... | 2ed71202a40214b75007db7b16d5c1806ae35406 | 3,641,422 |
def calculateSecFromEpoch(date,hour):
"""
Calculates seconds from EPOCH
"""
months={
'01':'Jan',
'02':'Feb',
'03':'Mar',
'04':'Apr',
'05':'May',
'06':'Jun',
'07':'Jul',
'08':'Aug',
'09':'Sep',
'10':'Oct',
'11':'Nov',
'12':'Dec'
}
year=YEAR_PREFIX+date[0:2]
month=months[date[2:4]]
day=d... | 29adf78dbe795c70cb84f66b1dc249674869c417 | 3,641,423 |
def star_noise_simulation(Variance, Pk, nongaussian = False):
"""simulates star + noise signal, Pk is hyperprior on star variability and flat at high frequencies which is stationary noise"""
Pk_double = np.concatenate((Pk, Pk))
phases = np.random.uniform(0, 2 * np.pi, len(Pk))
nodes0 = np.sqrt(Pk_double... | 5ccc89f455b7347c11cac36abead172b352f7b9c | 3,641,424 |
from datetime import datetime
import time
def get_seq_num():
"""
Simple class for creating sequence numbers
Truncate epoch time to 7 digits which is about one month
"""
t = datetime.datetime.now()
mt = time.mktime(t.timetuple())
nextnum = int(mt)
retval = nextnum % 10000000
return ... | 34a2b3a7082d061987c7a0b67c91df040b86938c | 3,641,425 |
import logging
def get_packages_for_file_or_folder(source_file, source_folder):
"""
Collects all the files based on given parameters. Exactly one of the parameters has to be specified.
If source_file is given, it will return with a list containing source_file.
If source_folder is given, it will searc... | fc047dd10dfd18fc8efecb240d06aeb91686c0cb | 3,641,426 |
def sanitize_tag(tag: str) -> str:
"""Clean tag by replacing empty spaces with underscore.
Parameters
----------
tag: str
Returns
-------
str
Cleaned tag
Examples
--------
>>> sanitize_tag(" Machine Learning ")
"Machine_Learning"
"""
return tag.strip().rep... | 40ac78846f03e8b57b5660dd246c8a15fed8e008 | 3,641,427 |
def _vmf_normalize(kappa, dim):
"""Compute normalization constant using built-in numpy/scipy Bessel
approximations.
Works well on small kappa and mu.
"""
num = np.power(kappa, dim / 2.0 - 1.0)
if dim / 2.0 - 1.0 < 1e-15:
denom = np.power(2.0 * np.pi, dim / 2.0) * i0(kappa)
else:
... | 24d22469a572e7ff4b7e1c918fce7001731cec2a | 3,641,428 |
import urllib
def twitter_map():
"""
Gets all the required information and returns the start page or map with
people locations depending on input
"""
# get arguments from url
account = request.args.get('q')
count = request.args.get('count')
if account and count:
# create map a... | 54a37f91141e52d24f88214ea476a2f199c78674 | 3,641,429 |
def path_states(node):
"""The sequence of states to get to this node."""
if node in (cutoff, failure, None):
return []
return path_states(node.parent) + [node.state] | 21ed5eb98eca0113dd5f446066cd10df73665f10 | 3,641,430 |
def find_named_variables(mapping):
"""Find correspondance between variable and relation and its attribute."""
var_dictionary = dict()
for relation_instance in mapping.lhs:
for i, variable in enumerate(relation_instance.variables):
name = relation_instance.relation.name
field ... | 0b9a78ca94b25e7a91fe88f0f15f8a8d408cb2fd | 3,641,431 |
import urllib
def attribute_formatter(attribute):
""" translate non-alphabetic chars and 'spaces' to a URL applicable format
:param attribute: text string that may contain not url compatible chars (e.g. ' 무작위의')
:return: text string with riot API compatible url encoding (e.g. %20%EB%AC%B4%EC%9E%91%EC%9C%8... | 6c6745a5cea9a3f6bcee8cbcedb7a1493372dc96 | 3,641,432 |
from typing import NoReturn
import os
def feature_evaluation(X: pd.DataFrame, y: pd.Series,
output_path: str = ".") -> NoReturn:
"""
Create scatter plot between each feature and the response.
- Plot title specifies feature name
- Plot title specifies Pearson Correlation ... | ec2b5116a6cf23b41e0009e5a1ad810daf23bc5f | 3,641,433 |
import json
def maestro_splits():
"""
Get list of indices for each split. Stolen from my work on Perceptual
Evaluation of AMT Resynthesized.
Leve here for reference.
"""
d = asmd.Dataset().filter(datasets=['Maestro'])
maestro = json.load(open(MAESTRO_JSON))
train, validation, test = ... | 119b033d3fd507b77bbb3d16d993237f8658b5f5 | 3,641,434 |
def get_choice_selectivity(trials, perf, r):
"""
Compute d' for choice.
"""
N = r.shape[-1]
L = np.zeros(N)
L2 = np.zeros(N)
R = np.zeros(N)
R2 = np.zeros(N)
nL = 0
nR = 0
for n, trial in enumerate(trials):
if not perf.decisions[n]:
continue
... | f33593ad06bf3c54c950eda562a93e348320a5e1 | 3,641,435 |
def author_productivity(pub2author_df, colgroupby = 'AuthorId', colcountby = 'PublicationId', show_progress=False):
"""
Calculate the total number of publications for each author.
Parameters
----------
pub2author_df : DataFrame, default None, Optional
A DataFrame with the author2publication... | 15c56b22cc9d5014fe4dcfab8be37a9e4b0ef329 | 3,641,436 |
def smoothed_epmi(matrix, alpha=0.75):
"""
Performs smoothed epmi.
See smoothed_ppmi for more info.
Derived from this:
#(w,c) / #(TOT)
--------------
(#(w) / #(TOT)) * (#(c)^a / #(TOT)^a)
==>
#(w,c) / #(TOT)
--------------
(#(w) * #(c)^a) / #(TOT)^(a+1))
==>
#(w,c)
... | e2f72c4169aee2f394445f42e4835f1b55f347c9 | 3,641,437 |
import six
def encode(input, errors='strict'):
""" convert from unicode text (with possible UTF-16 surrogates) to wtf-8
encoded bytes. If this is a python narrow build this will actually
produce UTF-16 encoded unicode text (e.g. with surrogates).
"""
# method to convert surrogate pairs t... | 525199690f384304a72176bd1eaeeb1b9cb30880 | 3,641,438 |
def forgot_password(request, mobile=False):
"""Password reset form. This view sends an email with a reset link.
"""
if request.method == "POST":
form = PasswordResetForm(request.POST)
valid = form.is_valid()
if valid:
form.save(use_https=request.is_secure(),
... | ea27378253a7ed1b98cb91fd52fe724e79f35e26 | 3,641,439 |
def rotation_components(x, y, eps=1e-12, costh=None):
"""Components for the operator Rotation(x,y)
Together with `rotation_operator` achieves best memory complexity: O(N_batch * N_hidden)
Args:
x: a tensor from where we want to start
y: a tensor at which we want to finish
... | 79cec86425bce65ac92ce8cf9c720f98857d7e1a | 3,641,440 |
def erode(np_image_bin, struct_elem='rect', size=3):
"""Execute erode morphological operation on binaryzed image
Keyword argument:
np_image_bin -- binaryzed image
struct_elem:
cross - cross structural element
rect - rectangle structural element
circ -- cricle structural element(... | 4692b40555a8047d70ad8c4b33de636a0c6c87b0 | 3,641,441 |
from typing import Type
from typing import Union
from typing import Any
import inspect
def from_argparse_args(
cls: Type[ParseArgparserDataType], args: Union[Namespace, ArgumentParser], **kwargs: Any
) -> ParseArgparserDataType:
"""Create an instance from CLI arguments.
Eventually use varibles from OS env... | 8d418557437dfc8f2522f4681cf31b9e81065e54 | 3,641,442 |
def setup_counter_and_timer(nodemap):
"""
This function configures the camera to setup a Pulse Width Modulation signal using
Counter and Timer functionality. By default, the PWM signal will be set to run at
50hz, with a duty cycle of 70%.
:param nodemap: Device nodemap.
:type nodemap: INodeMap... | 9874b17ce49aca766504891bd9828aad1e075e21 | 3,641,443 |
def concat(l1, l2):
""" Join two possibly None lists """
if l1 is None:
return l2
if l2 is None:
return l1
return l1 + l2 | 9e87bead7eedc4c47f665808b9e0222437bc01b5 | 3,641,444 |
def get_model_data(n_samples=None, ratio=None):
"""
Provides train and validation data to train the model. If n_samples and
ratio are not None, it returns data according to the ratio between v1 and v2.
V1 is data comming from the original distribution of SIRD parameters, and
V2 is data comming from ... | 540706ca37decbf718fcedeef30beb235e98ded8 | 3,641,445 |
def skip():
""" Decorator for marking test function that should not be executed."""
def wrapper(fn):
fn.__status__ = "skip"
return fn
return wrapper | 0b966c306515073bfb52427b78c65822ee09a060 | 3,641,446 |
import os
def upload_original_to(instance, filename):
""" Return the path this file should be stored at. """
filename_base, filename_ext = os.path.splitext(filename)
filename_ext = filename_ext.lower()
origin_path = instance.release_agency_slug
if '--' in instance.release_agency_slug:
ag... | 5dede23726ecb1ef06b4de1fb29d96b1f909f980 | 3,641,447 |
def _GetThumbnailType(destination_id):
"""Returns the thumbnail type for the destination with the id."""
destination_type = _GetDestinationType(destination_id)
if destination_type == _DestinationType.HOTSPOT:
return _ThumbnailType.PRETTY_EARTH
else:
return _ThumbnailType.GEOMETRY_OUTLINE | 3452044aae2f9660084be46d840747089f271b1b | 3,641,448 |
async def postAsync(text: str, *, url: str = "auto", config: ConfigOptions = ConfigOptions(), timeout: float = 30.0,
retries: int = 3):
"""Alias function for AsyncHaste().post(...)"""
return await AsyncHaste().post(text, url=url, config=config, timeout=timeout, retries=retries) | bfa5460ac6f469c123eb1bef6e2430f2251809c9 | 3,641,449 |
from typing import OrderedDict
def gpu_load_acquisition_csv(acquisition_path, **kwargs):
""" Loads acquisition data
Returns
-------
GPU DataFrame
"""
chronometer = Chronometer.makeStarted()
cols = [
'loan_id', 'orig_channel', 'seller_name', 'orig_interest_rate', 'orig_upb', 'orig... | fdc2281a6bc31547f60c9c8d8585cdc1d101d88f | 3,641,450 |
def get_flows_src_dst_address_pairs(device, flow_monitor):
""" Gets flows under flow_monitor and returns source and destination address pairs
Args:
device ('obj'): Device to use
flow_monitor ('str'): Flow monitor name
Raises:
N/A
Returns:
[(... | 61ffbe3e0e81acf8c408df7b5ca0f8ff9519f87b | 3,641,451 |
def imthresh(im, thresh):
"""
Sets pixels in image below threshold value to 0
Args:
im (ndarray): image
thresh (float): threshold
Returns:
ndarray: thresholded image
"""
thresh_im = im.copy()
thresh_im[thresh_im < thresh] = 0
return thresh_im | 180dc1eba6320c21273e50e4cf7b3f28c786b839 | 3,641,452 |
import _winreg
def set_serv_parms(service, args):
""" Set the service command line parameters in Registry """
uargs = []
for arg in args:
uargs.append(unicoder(arg))
try:
key = _winreg.CreateKey(_winreg.HKEY_LOCAL_MACHINE, _SERVICE_KEY + service)
_winreg.SetValueEx(key, _SERV... | 90eb2ac8ea6e9a11b7ff8c266017fe027503f159 | 3,641,453 |
def isRenderNode():
# type: () -> bool
"""
Returns
-------
bool
"""
return flavor() == 'Render' | b0d5799f755c9c6a72f851ad325b4d8ddf3dec70 | 3,641,454 |
def test_clean_data_contains_instance_value():
"""
Test values from instances remain when not in data.
"""
data = {'first_name': 'John'}
fields = ['job_title', 'first_name']
class Job(object):
job_title = 'swamper'
first_name = ''
class Swamper(BaseSwamper):
def bui... | d2c310cfd760ddea7241ccb469ae7cffdaf373ea | 3,641,455 |
def wrap_application(app: App, wsgi: WSGICallable) -> WSGICallable:
"""Wrap a given WSGI callable in all active middleware."""
for middleware_instance in reversed(ACTIVE_MIDDLEWARES):
wsgi = middleware_instance(app, wsgi)
return wsgi | 09574d87e241c19cae30c2db29ee1ed4744a0c68 | 3,641,456 |
def cal_rpn(imgsize, featuresize, scale, gtboxes):
"""
Args:
imgsize: [h, w]
featuresize: the size of each output feature map, e.g. [19, 19]
scale: the scale factor of the base anchor to the feature map, e.g. [32, 32]
gtboxes: ground truth boxes in the image, shape of [N, 4].
... | 19178b125024d213808a497a005336678589588f | 3,641,457 |
def run(args):
"""This function is called by a user to recover or reset their primary
one-time-password secret. This is used, e.g. if a user has changed
their phone, or if they think the secret has been compromised, or
if they have lost the secret completely (in which case they will
need... | c81e533c7dead3fcda028ef85e566d290a85ec74 | 3,641,458 |
import time
def adjust_price(iteration, current_price, global_start, last_tx_time):
""" Function that decides to lower or increase the price, according to the
time of previous transaction and the progress in reaching TARGET in
TARGET_TIME.
Args:
iteration (int) - Number of previous suc... | f27f13e7b4a753d6b912ed1d795383f0d206b2ef | 3,641,459 |
import copy
def read_csv_batch(file: str, offset, cnt, **read_csv_params):
"""
Args:
file:
offset:
cnt:
read_csv_params:
Returns:
"""
read_csv_params = copy(read_csv_params)
if read_csv_params is None:
read_csv_params = {}
try:
usecols = ... | cc6699db5b9ecae9706d52768c8a1dcd084062ea | 3,641,460 |
def fault_ack_faults_by_dn(cookie, in_dns):
""" Auto-generated UCSC XML API Method. """
method = ExternalMethod("FaultAckFaultsByDn")
method.cookie = cookie
method.in_dns = in_dns
xml_request = method.to_xml(option=WriteXmlOption.DIRTY)
return xml_request | 532e925b560d02a0ed47d61f9aa721f55fc6b650 | 3,641,461 |
from typing import List
def provides(name=None, needs: List[str] = None):
"""A shortcut for defining a factory function that also needs dependencies
itself."""
if not needs:
needs = []
def decorator(f):
decorated = _needs(*needs)(f)
set(name or f.__name__, decorated)
r... | e28e8d5690b7fa53907864c6d17e199a491ccada | 3,641,462 |
def clip_xyxy_to_image(x1, y1, x2, y2, height, width):
"""Clip coordinates to an image with the given height and width."""
x1 = np.minimum(width - 1.0, np.maximum(0.0, x1))
y1 = np.minimum(height - 1.0, np.maximum(0.0, y1))
x2 = np.minimum(width - 1.0, np.maximum(0.0, x2))
y2 = np.minimum(height - 1... | cf0fe5269afe2a5cbe94efb3221184f706fcb59d | 3,641,463 |
import re
def build_url(urlo, base, end, url_whitespace, url_case):
""" Build and return a valid url.
Parameters
----------
urlo A ParseResult object returned by urlparse
base base_url from config
end end_url from config
url_wh... | b6fa39062502a7d862b17cd079de3c4cfa3720c4 | 3,641,464 |
def AnomalyDicts(anomalies, v2=False):
"""Makes a list of dicts with properties of Anomaly entities."""
bisect_statuses = _GetBisectStatusDict(anomalies)
return [GetAnomalyDict(a, bisect_statuses.get(a.bug_id), v2)
for a in anomalies] | ffa8e0f93245f49e0857a19d4e154d47f3dd7f16 | 3,641,465 |
import re
def remove_links(txt: str):
"""
Remove weblinks from the text
"""
pattern = r'[-a-zA-Z0-9@:%._\+~#=]{1,256}\.[a-zA-Z0-9()]{1,6}\b([-a-zA-Z0-9()@:%_\+.~#?&//=]*)'
txt = re.sub(pattern, " ", txt)
txt = re.sub('http|https', " ", txt)
return txt | 4ccaae84d12ab47e70482d15100ba2e60ef476e8 | 3,641,466 |
def timefn(fn):
"""Times a function and stores the result in LOG variables"""
@wraps(fn)
def inside(*args, **kwargs):
start = timer()
result = fn(*args, **kwargs)
end = timer()
gv.TIME_LOG += f'Fn : {fn.__name__} - {end - start}\n'
return result
return inside | 8dddcd54489d2fb754d9c4de7bc1b084a10840e2 | 3,641,467 |
def get_tweet_stream(output_file, twitter_credentials):
"""
This function is given and returns a "stream" to listen to tweets and store them in output_file
To understand how this function works, check it against the code of twitter_streaming in part00_preclass
:param output_file: the file where the ret... | 71a336b71760ef74e14b6472cb8f2a8510d9acb3 | 3,641,468 |
def conv3d_3x3(filters,
stride=1,
padding=1,
kernel_initializer=None,
bias_initializer=None,
name=None):
"""3D convolution with padding."""
return keras.Sequential([
layers.ZeroPadding3D(padding),
layers.Conv3D(filters,
... | f8035b8be1bf82385c31aa0810e7addd8027b5cd | 3,641,469 |
def get_available_quests(user, num_quests):
"""Get the quests the user could participate in."""
quests = []
for quest in Quest.objects.exclude(questmember__user=user).order_by('priority'):
if quest.can_add_quest(user) and not quest.completed_quest(user):
quests.append(quest)
... | d1bdbe96dbd0b7fd5295ec43153249e7b93c7339 | 3,641,470 |
def height():
""" Default window height """
return get_default_height() | fab02ec1881d1c2ccda9f59e6a72d2990d815973 | 3,641,471 |
def no_adjust_tp_func_nb(c: AdjustTPContext, *args) -> float:
"""Placeholder function that returns the initial take-profit value."""
return c.curr_stop | 6896b72c20c79156c97ba09ba87a1947c7df04d6 | 3,641,472 |
def inverse_theoretical_laser_position(y, a, b, c):
"""
theoretical angular position of the wire in respect to the laser position
"""
return np.pi - a - np.arccos((b - y) / c) | 0ba87442954fd3bc832edec9adc082e1d2448347 | 3,641,473 |
def ad_roc(y_true, y_score):
""" Compute ROC-curve.
"""
fpr, tpr, thresholds = sklearn.metrics.roc_curve(y_true, y_score, pos_label=1, drop_intermediate=False)
return fpr, tpr, thresholds | db161f7099aab4e1d266ab2b0c8aac0b96076a49 | 3,641,474 |
import time
import platform
import subprocess
def check_reachability(gateway):
# from https://stackoverflow.com/questions/2953462/pinging-servers-in-python
"""
Returns True if host (str) responds to a ping request.
Remember that a host may not respond to a ping (ICMP) request even if the host name is ... | 76580279cfc65f5a74015d63fb0eaccae9b8e141 | 3,641,475 |
import torch
def greedy_decoding(baseline_transformer, src_representations_batch, src_mask, trg_field_processor, max_target_tokens=100):
"""
Supports batch (decode multiple source sentences) greedy decoding.
Decoding could be further optimized to cache old token activations because they can't look ahead ... | dbdf636979f28ea09b261fd3947068d6e4e359ad | 3,641,476 |
def _parse_cell_type(cell_type_arg):
""" Convert the cell type representation to the expected JVM CellType object."""
def to_jvm(ct):
return _context_call('_parse_cell_type', ct)
if isinstance(cell_type_arg, str):
return to_jvm(cell_type_arg)
elif isinstance(cell_type_arg, CellType):
... | 1afa4b2ed28d08ebc3526b8462673e5aa7f8a47f | 3,641,477 |
def Ht(mu, q=None, t=None, pi=None):
"""
Returns the symmetric Macdonald polynomial using the Haiman,
Haglund, and Loehr formula.
Note that if both `q` and `t` are specified, then they must have the
same parent.
REFERENCE:
- J. Haglund, M. Haiman, N. Loehr.
*A combinatorial formula ... | d3a46458215417db0789d3601163e105c9712c75 | 3,641,478 |
def is_generic_alias_of(to_check, type_def):
"""
:param to_check: the type that is supposed to be a generic alias of ``type_def`` if this function returns ``True``.
:param type_def: the type that is supposed to be a generic version of ``to_check`` if this function returns \
``True``.
... | d09b255e9ff44a65565196dd6643564aea181433 | 3,641,479 |
def train_PCA(X,n_dims,model='pca'):
"""
name: train_PCA
Linear dimensionality reduction using Singular Value Decomposition of the
data to project it to a lower dimensional space.
It uses the LAPACK implementation of the full SVD or a randomized truncated
SVD by the method of Halko et al. 2009, ... | 1909d154d778864c2eba0819e43a2bbcb260edbf | 3,641,480 |
import os
def find_song(hash_dictionary, sample_dictionary, id_to_song):
"""
Run our song matching algorithm to find the song
:param hash_dictionary:
:param sample_dictionary:
:param id_to_song:
:return max_frequencies, max_frequencies_keys:
"""
offset_dictionary = dict()
for song_... | 73ec2b2783dddd00c7a744af732737f6e6bce8b2 | 3,641,481 |
def phedex_url(api=''):
"""Return Phedex URL for given API name"""
return 'https://cmsweb.cern.ch/phedex/datasvc/json/prod/%s' % api | a642cd138d9be4945dcbd924c7b5c9892de36baa | 3,641,482 |
import csv
def extract_emails(fname, email='Email Address',
outfile="emails_from_mailchimp.txt",
nofile=False, nolog=False, sort=True):
"""
Extract e-mail addresses from a CSV-exported MailChimp list.
:param fname: the input .csv file
:param email: the header of ... | 1b4e5f60eacd4843e1c9ba6a72c866c52b5bd8d9 | 3,641,483 |
def continuations(tree, *, syntax, expander, **kw):
"""[syntax, block] call/cc for Python.
This allows saving the control state and then jumping back later
(in principle, any time later). Some possible use cases:
- Tree traversal (possibly a cartesian product of multiple trees, with the
curr... | 333494e07462ee554701616c5069fa61c5f46841 | 3,641,484 |
import os
def get_autotune_level() -> int:
"""Get the autotune level.
Returns:
The autotune level.
"""
return int(os.environ.get("BAGUA_AUTOTUNE", 0)) | 661fc4a7580fffdc7eef18ff7eb22e56ece2b468 | 3,641,485 |
def DNA_dynamic_pressure(y, r, h, yunits='kT', dunits='m', opunits='kg/cm^2'):
"""Estimate peak pynamic overpressure at range r from a burst of yield y using the
the Defense Nuclear Agency 1kT standard free airburst overpressure, assuming an ideal
surface. Many real-world surfaces are not ideal (most, in the opinio... | ac56c9d72c516658384ac313c64ba7ed1235e0ea | 3,641,486 |
def revcumsum(U):
"""
Reverse cumulative sum for faster performance.
"""
return U.flip(dims=[0]).cumsum(dim=0).flip(dims=[0]) | da147820073f5be9d00b137e48a28d726516dcd0 | 3,641,487 |
def http_trace_parser_hook(request):
"""
Retrieves the propagation context out of the request. Uses the honeycomb header, with W3C header as fallback.
"""
honeycomb_header_value = honeycomb.http_trace_parser_hook(request)
w3c_header_value = w3c.http_trace_parser_hook(request)
if honeycomb_header... | 7c97ed82f22357d3867e8a504a30f3a857837bcf | 3,641,488 |
import torch
def format_attn(attention_tuples: tuple):
"""
Input: N tuples (N = layer num)
Each tuple item is Tensor of shape
Batch x num heads x from x to
Output: Tensor of shape layer x from x to
(averaged over heads)
"""
# Combine tuples into large Tensor, then avg
return tor... | 8d25d081992099835a21cdbefb406f378350f983 | 3,641,489 |
def fit_gaussian2d(img, coords, boxsize, plot=False,
fwhm_min=1.7, fwhm_max=30, pos_delta_max=1.7):
"""
Calculate the FWHM of an objected located at the pixel
coordinates in the image. The FWHM will be estimated
from a cutout with the specified boxsize.
Parameters
------... | c3e69f93fdf84c7f895f9cb01adf3e6a0aa3001d | 3,641,490 |
def _ensure_aware(series, tz_local):
"""Convert naive datetimes to timezone-aware, or return them as-is.
Args:
tz_local (str, pytz.timezone, dateutil.tz.tzfile):
Time zone for time which timestamps will be converted to.
If the series already has local timezone info, it is returned as-is.
""... | fbb99be365a47507ae676fc90601d13cfa46832b | 3,641,491 |
import os
import pickle
def one_mask(df, mask_type, sample_type, data, logger=None):
""" return a vector of booleans from the lower triangle of a matching-matrix based on 'mask_type'
:param df: pandas.DataFrame with samples as columns
:param str mask_type: A list of strings to specify matching masks, or ... | cdb0305f716c9d0b9e1ab2c1e89f8dfbeb6d5504 | 3,641,492 |
def compute_epsilon(steps):
"""Computes epsilon value for given hyperparameters."""
if FLAGS.noise_multiplier == 0.0:
return float('inf')
orders = [1 + x / 10. for x in range(1, 100)] + list(range(12, 64))
sampling_probability = FLAGS.batch_size / NB_TRAIN
rdp = compute_rdp(q=sampling_probability,
... | 8c998fdcafaac3c99a87b4020ae6959e64170d36 | 3,641,493 |
def extract_tumblr_posts(client, nb_requests, search_query, before, delta_limit):
"""Extract Tumblr posts with a given emotion.
Parameters:
client: Authenticated Tumblr client with the pytumblr package.
nb_requests: Number of API request.
search_query: Emotion to search for.
... | bff51bcdc945244a47a88d32139749dddf25f0cf | 3,641,494 |
def total_curtailment_expression_rule(mod, g, tmp):
"""
**Expression Name**: GenVar_Total_Curtailment_MW
**Defined Over**: GEN_VAR_OPR_TMPS
Available energy that was not delivered
There's an adjustment for subhourly reserve provision:
1) if downward reserves are provided, they will be called up... | 9a1466dbbbc945b30c1df04dc86a2134b3d0659a | 3,641,495 |
def transpose(m):
"""Compute the inverse of `m`
Args:
m (Matrix3):
Returns:
Matrix3: the inverse
"""
return Matrix3(m[0], m[3], m[6],
m[1], m[4], m[7],
m[2], m[5], m[8]) | 843a4b9d52f7c15772957b7abe05ef8c32c8370b | 3,641,496 |
def reverse_string(string):
"""Solution to exercise C-4.16.
Write a short recursive Python function that takes a character string s and
outputs its reverse. For example, the reverse of "pots&pans" would be
"snap&stop".
"""
n = len(string)
def recurse(idx):
if idx == 0:
... | 6d4472fb9c042939020e8b819b4c9b705afd1e60 | 3,641,497 |
def result_to_df(model, data,
path: str = None,
prediction: str = 'prediction',
residual: str = 'residual') -> pd.DataFrame:
"""Create result data frame.
Args:
model (Union[NodeModel, StagewiseModel]): Model instance.
data (MRData): Data object... | 8b089569d628a0f89381240a133b21ae926da7f9 | 3,641,498 |
import re
def auto(frmt, minV = None, maxV = None):
"""
Generating regular expressions for integer, real, date and time.
:param format: format similar to C printf function (description below)
:param min: optional minimum value
:param max: optional maximum value
:return: regular expression for... | a160b2c49baf875adb0a7949b8ea0e0e92dc936a | 3,641,499 |
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