content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def integrated_circular_gaussian(X=None, Y=None, sigma=0.8):
"""Create a circular Gaussian that is integrated over pixels
This is typically used for the model PSF,
working well with the default parameters.
Parameters
----------
X, Y: `numpy.ndarray`
The x,y-coordinates to evaluate the ... | 63201f6c37fba1e3750881cd692057c2bd5011b0 | 26,686 |
def nPairsToFracPairs(hd_obj, all_pairs_vs_rp, redshift_limit = 2):
"""
Function to convert the number of pairs into a fractional number density per shell
@redshift_limit :: the initial redshift limit set on the sample (needed for opening dir)
"""
num_pairs = all_pairs_vs_rp[1:] - all_pairs_vs_rp[:-... | d9d8f72d8f05cff4e984b43f4a22da406dfe1c05 | 26,687 |
def default_decode(events, mode='full'):
"""Decode a XigtCorpus element."""
event, elem = next(events)
root = elem # store root for later instantiation
while (event, elem.tag) not in [('start', 'igt'), ('end', 'xigt-corpus')]:
event, elem = next(events)
igts = None
if event == 'start' a... | 36e0b4b13cb357d74cee20623e5a71cf9a5dd02a | 26,689 |
def attention_guide(dec_lens, enc_lens, N, T, g, dtype=None):
"""Build that W matrix. shape(B, T_dec, T_enc)
W[i, n, t] = 1 - exp(-(n/dec_lens[i] - t/enc_lens[i])**2 / (2g**2))
See also:
Tachibana, Hideyuki, Katsuya Uenoyama, and Shunsuke Aihara. 2017. “Efficiently Trainable Text-to-Speech System Base... | 2af05dedb5260e52150d96b181fab063cd17efb8 | 26,690 |
def two_step_colormap(left_max, left, center='transparent', right=None, right_max=None, name='two-step'):
"""Colormap using lightness to extend range
Parameters
----------
left_max : matplotlib color
Left end of the colormap.
left : matplotlib color
Left middle of the colormap.
... | 226dfd9a9beaadf5a47167c6080cdb3ba8fa522f | 26,692 |
def _broadcast_arg(U, arg, argtype, name):
"""Broadcasts plotting option `arg` to all factors.
Args:
U : KTensor
arg : argument provided by the user
argtype : expected type for arg
name : name of the variable, used for error handling
Returns:
iterable version of arg... | 3a441b9156f7cf614b2ab2967159349252802bed | 26,693 |
import signal
def xkcd_line(x, y, xlim=None, ylim=None, mag=1.0, f1=30, f2=0.05, f3=15):
"""
Mimic a hand-drawn line from (x, y) data
Definition
----------
def xkcd_line(x, y, xlim=None, ylim=None, mag=1.0, f1=30, f2=0.05, f3=15):
Input
-----
x, y ... | ea36487d6e2f4f9d5d0bc9d5cea23459a5b8a5a4 | 26,695 |
def generate_mutation() -> str:
"""
Retrieve staged instances and generate the mutation query
"""
staged = Node._get_staged()
# localns = {x.__name__: x for x in Node._nodes}
# localns.update({"List": List, "Union": Union, "Tuple": Tuple})
# annotations = get_type_hints(Node, globalns=global... | 789e6042226ed25451d7055bc9b383b81fd10ddf | 26,696 |
from datetime import datetime
def start(fund: Fund, start_date: datetime) -> Fund:
"""
Starts the fund by setting the added USD and the market value of the manager
as the current market value. Meaning that at the beginning there is only
the manager's positions.
:param fund: The fund to start
:... | e7f4a273b4c48eb3f9e440f663fee45847df902a | 26,697 |
def _make_experiment(exp_id=1, path="./Results/Tmp/test_FiftyChain"):
"""
Each file specifying an experimental setup should contain a
make_experiment function which returns an instance of the Experiment
class with everything set up.
@param id: number used to seed the random number generators
@p... | 6cf51f8957e091175445b36aa1d6ee7b22465835 | 26,698 |
def find_largest_digit_helper(n, max_n=0):
"""
:param n: int,待判別整數
:param max_n: int,當下最大整數值
:return: int,回傳n中最大之 unit 整數
"""
# 特殊情況:已達最大值9，就不需再比了
if n == 0 or max_n == 9:
return max_n
else:
# 負值轉換為正值
if n < 0:
n *= -1
# 用餘數提出尾數
unit_n = n % 10
# 尾數比現在最大值
if unit_n > max_n:
max_n = unit_n
... | cd60a0cdb7cdfba6e2374a564bb39f1c95fe8931 | 26,699 |
def build_stats(loss, eval_result, time_callback):
"""Normalizes and returns dictionary of stats.
Args:
loss: The final loss at training time.
eval_result: Output of the eval step. Assumes first value is eval_loss and
second value is accuracy_top_1.
time_callback: Time track... | cddde6bf9bd2797c94bc392be77f7be19a46271e | 26,700 |
import random
def random_resource_code2() -> str:
"""One random book name chosen at random. This fixture exists so
that we can have a separate book chosen in a two language document
request."""
book_ids = list(bible_books.BOOK_NAMES.keys())
return random.choice(book_ids) | 04ea455fa85eea32c2c7e9d7d3a3dc98759b937b | 26,701 |
def _to_str(value):
"""Helper function to make sure unicode values are converted to UTF-8.
Args:
value: String or Unicode text to convert to UTF-8.
Returns:
UTF-8 encoded string of `value`; otherwise `value` remains unchanged.
"""
if isinstance(value, unicode):
return value.encode('utf-8')
ret... | 46186757a475c2b5fa877e8fb62c32a27770e6b7 | 26,702 |
def get_loss(loss_name):
"""Get loss from LOSS_REGISTRY based on loss_name."""
if not loss_name in LOSS_REGISTRY:
raise Exception(NO_LOSS_ERR.format(
loss_name, LOSS_REGISTRY.keys()))
loss = LOSS_REGISTRY[loss_name]
return loss | d91bde7ce34e2d4fe38a5c86a93ba96d153eb7c1 | 26,703 |
def collate_fn(batch):
"""
Data collater.
Assumes each instance is a dict.
Applies different collation rules for each field.
Args:
batches: List of loaded elements via Dataset.__getitem__
"""
collated_batch = {}
# iterate over keys
for key in batch[0]:
try:
... | 718a6945d71a485fd4dbbbeaac374afbb9256621 | 26,704 |
def _rec_eval_in(g, a, v, i, j, K):
"""Recursive helper for :func:`dmp_eval_in`."""
if i == j:
return dmp_eval(g, a, v, K)
v, i = v - 1, i + 1
return dmp_strip([ _rec_eval_in(c, a, v, i, j, K) for c in g ], v) | 51fbd9a45b4e1722ef98a5ab543575980d56b66b | 26,705 |
def normalize(array):
"""
Normalize a 4 (or Nx4) element array/list/numpy.array for use as a quaternion
:param array: 4 or Nx4 element list/array
:returns: normalized array
:rtype: numpy array
"""
quat = np.array(array)
return np.squeeze(quat / np.sqrt(np.sum(quat * quat, axis=-1, keep... | 020b1fb9b1050192254274ac3d716e655a5ff003 | 26,706 |
def dose_class_baseline(dose_num, df_test, df_targets):
"""Calculate the PR- baseline for each dose treatment"""
dose_cpds_index = df_test[df_test['dose'] == dose_num].index
df_class_targets = df_targets.loc[dose_cpds_index].reset_index(drop = True)
class_baseline_score = calculate_baseline(df_class_targets)
... | 0e0178573fc3ccfb08c8f898d264efa84fd10962 | 26,707 |
def xrange(mn: int, mx: int = None) -> list:
"""Built-in range function, but actually gives you a range between mn and mx.
Range: range(5) -> [0, 1, 2, 3, 4]
XRange: xrange(5) -> [0, 1, 2, 3, 4, 5]"""
return list(range(0 if mx is None else mn, mn + 1 if mx is None else mx + 1)) | 4ab3059a51966cefd43008c4aa4c50cf42cb8fa2 | 26,708 |
def sous_tableaux(arr: list, n: int) -> list:
"""
Description:
Découper un tableau en sous-tableaux.
Paramètres:
arr: {list} -- Tableau à découper
n: {int} -- Nombre d'éléments par sous-tableau
Retourne:
{list} -- Liste de sous-tableaux
Exemple:
>>> sous_ta... | 4f0a627ea00beafb5b6bc77490e71631e8a55e28 | 26,710 |
def get_previous_tweets(date_entry):
"""Return details about previous Tweets. Namely, retrieve details
about the date_entry-th Tweets from 7 days ago, 30 days ago, and a
random number of days ago.
If a given Tweet does not exist, its corresponding entry in the
output will be empty.
Args:
... | a4b91b87f3cc897e720f745a1c0ad1097292774b | 26,711 |
def changed_cat_keys(dt):
"""Returns keys for categories, changed after specified time"""
return [root_category_key()] | fbc4d0380bb1deaf7f1214d526d1c623cceb4676 | 26,712 |
def create_client(CLIENT_ID, CLIENT_SECRET):
"""Creates Taboola Client object with the given ID and secret."""
client = TaboolaClient(CLIENT_ID, client_secret=CLIENT_SECRET)
return client | bea955f5d944e47f11c74ae97c5472dc3c512217 | 26,713 |
def set_values_at_of_var_above_X_lat_2_avg(lat_above2set=65, ds=None,
use_avg_at_lat=True, res='0.125x0.125',
var2set=None,
only_consider_water_boxes=True,
... | 6040523af84f5046af373de2aa22447e66aef181 | 26,714 |
def _plot_xkcd(plot_func, *args, **kwargs):
""" Plot with *plot_func*, *args* and **kwargs*, but in xkcd style. """
with plt.xkcd():
fig = plot_func(*args, **kwargs)
return fig | a4bc526c115c54f37c5171b82639adf0c0a3f888 | 26,716 |
import requests
def unfollow_user():
"""UnfollowUser"""
auth = request.headers
user = request.args.get('userId')
req = requests.post(
'/api/v1/IsAuthenticated',
{'id': auth['Authorization']}
)
req.json()
if req.authenticated:
cur = MY_SQL.connection.cursor()
... | 8e40b633b960070a4d433610f4f0d4e7f8b89a12 | 26,717 |
def isOverlaysEnabled():
"""Returns whether or not the current client's quality overlay
system is currently enabled.
Returns:
bool: True (1) if overlays are currently enabled.
"""
return False | d433b86b38bfa3c3ed28705888ef12710aaf4f96 | 26,718 |
def load_image(path, size=None, grayscale=False):
"""
Load the image from the given file-path and resize it
to the given size if not None.
"""
# Load the image using opencv
if not grayscale: # BGR format
image = cv2.imread(path)
else: # grayscale format
image = cv2.imread(... | 2d3d4a625a690800c2d5db8f8577e9c06a36001a | 26,719 |
def brent_min(f, bracket, fnvals=None, tolerance=1e-6, max_iterations=50):
"""\
Given a univariate function f and a tuple bracket=(x1,x2,x3) bracketing a minimum,
find a local minimum of f (with fn value) using Brent's method.
Optionally pass in the tuple fnvals=(f(x1),f(x2),f(x3)) as a parameter.
"""
x1, x2, x3 = b... | ef4010e00ca67d1751b7f8eea497afc59e76364c | 26,720 |
def best_validity(source):
"""
Retrieves best clustering result based on the relative validity metric
"""
# try:
cols = ['min_cluster_size', 'min_samples', 'validity_score', 'n_clusters']
df = pd.DataFrame(source, columns = cols)
df['validity_score'] = df['validity_score'].fillna(0)
bes... | ba830ccca8c9f62758ecd8655576efb58892cdbc | 26,721 |
import json
def normalize_cell_value(value):
"""Process value for writing into a cell.
Args:
value: any type of variable
Returns:
json serialized value if value is list or dict, else value
"""
if isinstance(value, dict) or isinstance(value, list):
return json.dumps(value)... | 8ef421814826c452cdb6528c0645133f48bd448a | 26,722 |
import numpy
def _ancestry2paths(A):
"""Convert edge x edge ancestry matrix to tip-to-tip path x edge
split metric matrix. The paths will be in the same triangular matrix order
as produced by distanceDictAndNamesTo1D, provided that the tips appear in
the correct order in A"""
tips = [i for i i... | 732ef3bbccff4696650c24a983fdbc338f1d8e24 | 26,723 |
def geometric_mean(x, axis=-1, check_for_greater_than_zero=True):
"""
Return the geometric mean of matrix x along axis, ignore NaNs.
Raise an exception if any element of x is zero or less.
"""
if (x <= 0).any() and check_for_greater_than_zero:
msg = 'All elements of x (except NaNs... | 485780f7766857333a240d059d2bb1c526d3f5a8 | 26,724 |
def mongodb():
"""
Simple form to get and set a note in MongoDB
"""
return None | a6de90429bb3ad3e23191e52e1b43484435747f9 | 26,725 |
def get_single_blog(url):
"""Получить блог по указанному url"""
blog = Blog.get_or_none(Blog.url == url)
if blog is None:
return errors.not_found()
user = get_user_from_request()
has_access = Blog.has_access(blog, user)
if not has_access:
return errors.no_access()
blog_dic... | b4a32278681af7eecbebc29ed06b88c7860a39c0 | 26,726 |
def test_section():
"""Returns a testing scope context to be used in 'with' statement
and captures testing code.
Example::
with autograd.train_section():
y = model(x)
compute_gradient([y])
with autograd.test_section():
# testing, IO, gradient upda... | 6bcbc9aaaaeee5a9b5d8b6a3307f1fb69bf726ae | 26,727 |
from typing import Optional
import select
async def get_installation_owner(metadata_account_id: int,
mdb_conn: morcilla.core.Connection,
cache: Optional[aiomcache.Client],
) -> str:
"""Load the native user ID who in... | 925780ce87c14758cf98191cf39effcaf09a8aaa | 26,728 |
def get_cflags():
"""Get the cflag for compile python source code"""
flags = ['-I' + get_path('include'),
'-I' + get_path('platinclude')]
flags.extend(getvar('CFLAGS').split())
# Note: Extrat cflags not valid for cgo.
for not_go in ('-fwrapv', '-Wall'):
if not_go in flags:
... | f1c171d5a70127bda98a3ef7625c60336641ea1f | 26,729 |
import requests
def request_post_json(url, headers, data):
"""Makes a POST request and returns the JSON response"""
try:
response = requests.post(url, headers=headers, data=data, timeout=10)
if response.status_code == 201:
return response.json()
else:
error_mess... | 82d7ce423024ca1af8a7c513f3d689fbc77c591a | 26,730 |
import random
def get_rand_number(min_value, max_value):
"""
This function gets a random number from a uniform distribution between
the two input values [min_value, max_value] inclusively
Args:
- min_value (float)
- max_value (float)
Return:
- Random number between this range (float)
... | 0eec094d05b291c7c02207427685d36262e643e5 | 26,731 |
def read(string):
""" Given a single interval from a GFFv2 file, returns an Interval object.
Will return meta lines if they start with #, track, or browser. """
if string.startswith(metalines):
return interval(_is_meta=True, seqname=string)
values = []
cols = string.split(delimiter)
fo... | e4651216c9694935bc879c012b1fe74f529cb41d | 26,734 |
from typing import Union
from pathlib import Path
from typing import Dict
def average_results(results_path: Union[Path, str], split_on: str = " = ") -> Dict[str, float]:
"""
Average accuracy values from a file.
Parameters
----------
results_path : Union[Path, str]
The file to read results... | 28b896d567d6ef18662766a2da64c6bdb262f3d7 | 26,735 |
def dict_collection_only(method):
"""
Handles the behavior when a group is present on a clumper object.
"""
@wraps(method)
def wrapped(clumper, *args, **kwargs):
if not clumper.only_has_dictionaries:
non_dict = next(d for d in clumper if not isinstance(d, dict))
rais... | a84c3588942378157674e6862d2f1a8c785ba569 | 26,737 |
def country_name(country_id):
"""
Returns a country name
>>> country_name(198)
u'Spain'
"""
if country_id == '999':
#Added for internal call - ie flag/phone.png
return _('internal call').title()
try:
obj_country = Country.objects.get(id=country_id)
return obj... | fdb44061d795e42d9e312bc25f8335a41c91ca11 | 26,738 |
def KLdist(P,Q):
"""
KLDIST Kullbach-Leibler distance.
D = KLDIST(P,Q) calculates the Kullbach-Leibler distance (information
divergence) of the two input distributions.
"""
P2 = P[P*Q>0]
Q2 = Q[P*Q>0]
P2 = P2 / np.sum(P2)
Q2 = Q2 / np.sum(Q2)
D = np.sum(P2*np.log(P2/Q2))
... | 380796f3688c5ad8483ba50ddc940eb797e4a973 | 26,744 |
def homepage(request: HttpRequest) -> HttpResponse:
""" Render the home page of the application. """
context = make_context(request)
person = get_person(TARGET_NICK)
if not person:
return render(request, "404.html", status=404)
context["person"] = person
technology_set = person.technol... | 42f749a38543b456b603b5b7b923d5637ab84abe | 26,746 |
def _call_rmat(scale, num_edges, create_using, mg):
"""
Simplifies calling RMAT by requiring only specific args that are varied by
these tests and hard-coding all others.
"""
return rmat(scale=scale,
num_edges=num_edges,
a=0.1,
b=0.2,
c... | cf68a7e436919ad5296438708898eeb233112651 | 26,747 |
def value_loss(old_value):
"""value loss for ppo"""
def loss(y_true, y_pred):
vpredclipped = old_value + K.clip(y_pred - old_value, -LOSS_CLIPPING, LOSS_CLIPPING)
# Unclipped value
vf_losses1 = K.square(y_pred - y_true)
# Clipped value
vf_losses2 = K.square(vpredclipped -... | 0888a411be6fa7e41469d15a2798cbebda46db01 | 26,748 |
import torch
import warnings
def split_by_worker(urls):
"""Selects a subset of urls based on Torch get_worker_info.
Used as a shard selection function in Dataset."""
urls = [url for url in urls]
assert isinstance(urls, list)
worker_info = torch.utils.data.get_worker_info()
if worker_info i... | 1ddcf436fecc4359367b783f9c1c62fe84782468 | 26,749 |
def runge_kutta4(y, x, dx, f):
"""computes 4th order Runge-Kutta for dy/dx.
Parameters
----------
y : scalar
Initial/current value for y
x : scalar
Initial/current value for x
dx : scalar
difference in x (e.g. the time step)
f : ufunc(y,x)
Callable function ... | 0f79962a3bd7bbe49bd3ae3eff6d5496182fbea8 | 26,751 |
def genBinaryFileRDD(sc, path, numPartitions=None):
"""
Read files from a directory to a RDD.
:param sc: SparkContext.
:param path: str, path to files.
:param numPartition: int, number or partitions to use for reading files.
:return: RDD with a pair of key and value: (filePath: str, fileData: Bina... | 85ef3c657b932946424e2c32e58423509f07ceae | 26,752 |
import requests
def generate():
"""
Generate a classic image quote
:rtype: InspiroBotImageResponse
:return: The generated response
"""
try:
r = requests.get("{}?generate=true".format(url()))
except:
raise InsprioBotError("API request failed. Failed to connect")
if r.st... | bc9a49909d9191f922a5c781d9fc68c97de92456 | 26,753 |
import pickle
def inference_lstm(im_path, model_path, tok_path, max_cap_len=39):
"""
Perform inference using a model trained to predict LSTM.
"""
tok = pickle.load(open(tok_path, 'rb'))
model = load_model(
model_path,
custom_objects={'RepeatVector4D': RepeatVector4D})
encoder =... | 81cec1407b6227d7f65a697900467b16b2fce96e | 26,754 |
def iterative_proof_tree_bfs(rules_dict: RulesDict, root: int) -> Node:
"""Takes in a iterative pruned rules_dict and returns iterative proof
tree."""
root_node = Node(root)
queue = deque([root_node])
while queue:
v = queue.popleft()
rule = sorted(rules_dict[v.label])[0]
if n... | c7ce6f1e48f9ac04f68b94e07dbcb82162b2abba | 26,755 |
def get_host_buffer_init(arg_name, num_elem, host_data_type, host_init_val):
"""Get host code snippet: init host buffer"""
src = get_snippet("snippet/clHostBufferInit.txt")
src = src.replace("ARG_NAME", arg_name)
src = src.replace("NUM_ELEM", str(num_elem))
src = src.replace("HOST_DATA_TYPE", host_d... | 7f94d2727a3c6f861f5c6402c5c8d2211d32dd71 | 26,756 |
def get_setting(setting, override=None):
"""Get setting.
Get a setting from `muses` conf module, falling back to
the default.
If override is not None, it will be used instead of the setting.
:param setting: String with setting name
:param override: Value to use when no setting is available. D... | 7e4a05ee3b077023e04693a37d3cbeaaa6025d8d | 26,757 |
def extract_year_month_from_key(key):
"""
Given an AWS S3 `key` (str) for a file,
extract and return the year (int) and
month (int) specified in the key after
'ano=' and 'mes='.
"""
a_pos = key.find('ano=')
year = int(key[a_pos + 4:a_pos + 8])
m_pos = key.find('mes=')
month... | b52dc08d393900b54fca3a4939d351d5afe0ef3c | 26,758 |
def depolarize(p: float) -> DepolarizingChannel:
"""Returns a DepolarizingChannel with given probability of error.
This channel applies one of four disjoint possibilities: nothing (the
identity channel) or one of the three pauli gates. The disjoint
probabilities of the three gates are all the same, p /... | 247dd040844cdd3cd44336ca097b98fcf2f3cac3 | 26,759 |
import re
def verilog_to_circuit(
netlist,
name,
infer_module_name=False,
blackboxes=None,
warnings=False,
error_on_warning=False,
fast=False,
):
"""
Creates a new Circuit from a module inside Verilog code.
Parameters
----------
netlist: str
Verilog code.
... | 4dc8e59ff8bea29f32e64219e3c38ed7bfec4aef | 26,760 |
def load_all_channels(event_id=0):
"""Returns a 3-D dataset corresponding to all the electrodes for a single subject
and a single event. The first two columns of X give the spatial dimensions, and
the third dimension gives the time."""
info = load_waveform_data(eeg_data_file())
locs = load_channel_l... | 17dd6dfc196a3f88f4bf7f0128da1a0b027f9072 | 26,761 |
def parentheses_cleanup(xml):
"""Clean up where parentheses exist between paragraph an emphasis tags"""
# We want to treat None's as blank strings
def _str(x):
return x or ""
for em in xml.xpath("//P/*[position()=1 and name()='E']"):
par = em.getparent()
left, middle, right = _st... | b5a476cd6fd9b6a2ab691fcec63a33e6260d48f2 | 26,762 |
import numpy
def filter_atoms(coordinates, num_atoms=None, morphology="sphere"):
"""
Filter the atoms so that the crystal has a specific morphology with a given number of atoms
Params:
coordinates (array): The atom coordinates
num_atoms (int): The number of atoms
morphology (str):... | 9763f2c7b14a26d089bf58a4c7e82e2d4a0ae2bd | 26,763 |
def weekly():
"""The weekly status page."""
db = get_session(current_app)
#select id, user_id, created, strftime('%Y%W', created), date(created, 'weekday 1'), content from status order by 4, 2, 3;
return render_template(
'status/weekly.html',
week=request.args.get('week', None),
... | b5c1e5a8d981fb217492241e8ee140898d47b633 | 26,765 |
from typing import List
import pathlib
from typing import Sequence
def parse_source_files(
src_files: List[pathlib.Path],
platform_overrides: Sequence[str],
) -> List[LockSpecification]:
"""
Parse a sequence of dependency specifications from source files
Parameters
----------
src_files :
... | 47a6e66b56ca0d4acd60a6b388c9f58d0cccbb2c | 26,766 |
def delete_registry(
service_account_json, project_id, cloud_region, registry_id):
"""Deletes the specified registry."""
# [START iot_delete_registry]
print('Delete registry')
client = get_client(service_account_json)
registry_name = 'projects/{}/locations/{}/registries/{}'.format(
... | baa8cad0d324f2e564052822f9d17f45a581a397 | 26,767 |
def bundle(cls: type) -> Bundle:
""" # Bundle Definition Decorator
Converts a class-body full of Bundle-storable attributes (Signals, other Bundles) to an `hdl21.Bundle`.
Example Usage:
```python
import hdl21 as h
@h.bundle
class Diff:
p = h.Signal()
n = h.Signal()
... | bf1b68791dbdc5b6350d561db4d784ff92c0bbae | 26,768 |
import time
import calendar
def previousMidnight(when):
"""Given a time_t 'when', return the greatest time_t <= when that falls
on midnight, GMT."""
yyyy, MM, dd = time.gmtime(when)[0:3]
return calendar.timegm((yyyy, MM, dd, 0, 0, 0, 0, 0, 0)) | 0821eb46115a1e5b1489c4f4dbff78fab1d811b5 | 26,769 |
def compute_net_results(net, archname, test_data, df):
"""
For a given network, test on appropriate test data and return dataframes
with results and predictions (named obviously)
"""
pretrain_results = []
pretrain_predictions = []
tune_results = []
tune_predictions = []
for idx in r... | b971f269bbee7e48f75327e3b01d73c77ec1f06c | 26,770 |
def _distance_along_line(start, end, distance, dist_func, tol):
"""Point at a distance from start on the segment from start to end.
It doesn't matter which coordinate system start is given in, as long
as dist_func takes points in that coordinate system.
Parameters
----------
start : tuple
... | 2f168b068cc434fe9280e2cdf84ae3f0f93eb844 | 26,771 |
def exploits_listing(request,option=None):
"""
Generate the Exploit listing page.
:param request: Django request.
:type request: :class:`django.http.HttpRequest`
:param option: Action to take.
:type option: str of either 'jtlist', 'jtdelete', 'csv', or 'inline'.
:returns: :class:`django.htt... | 941ab4e3da6273f17f4a180aebe62d35f7133080 | 26,773 |
from typing import Sequence
from typing import Tuple
def find_command(tokens: Sequence[str]) -> Tuple[Command, Sequence[str]]:
"""Looks up a command based on tokens and returns the command if it was
found or None if it wasn't.."""
if len(tokens) >= 3 and tokens[1] == '=':
var_name = tokens[0]
... | 4b46b03f6dd0fb4a6cbcda855029d0a42958a49f | 26,774 |
def clean(df: pd.DataFrame, completelyInsideOtherBias: float = 0.7, filterCutoff: float = 0.65,
algo: str = "jaccard", readFromFile: bool = True, writeToFile: bool = True,
doBias: bool = True) -> pd.DataFrame:
"""Main function to completely clean a restaurant dataset.
Args:
df: a pa... | 6c7873958c61bab357abe1d099c57e681c265067 | 26,775 |
def create_list(value, sublist_nb, sublist_size):
"""
Create a list of len sublist_size, filled with sublist_nb sublists. Each sublist is filled with the value value
"""
out = []
tmp = []
for i in range(sublist_nb):
for j in range(sublist_size):
tmp.append(value)
out.... | 1ecf6c88390167584d1835430c359a7ed6d6b40b | 26,776 |
from datetime import datetime
import re
def parse_time(date_str: str) -> datetime:
"""
Parses out a string-formatted date into a well-structured datetime in UTC.
Supports any of the following formats:
- hh:mm
In this format, we treat the value of the hh section to be 24hr format.
I... | 6009342d1e9c1c3f9b255758adf685e4fe7ca2f0 | 26,778 |
def gen_r_cr():
"""
Generate the R-Cr table.
"""
r_cr = [0] * 256
for i in range(256):
r_cr[i] = int(1.40199 * (i - 128))
return r_cr | 43e014bb62c40d038c5fbd124e834e98e9edb5e3 | 26,779 |
def fallible_to_exec_result_or_raise(
fallible_result: FallibleProcessResult, description: ProductDescription
) -> ProcessResult:
"""Converts a FallibleProcessResult to a ProcessResult or raises an error."""
if fallible_result.exit_code == 0:
return ProcessResult(
stdout=fallible_result... | 6b46a78897f0fcbd10e4a0c9b733f1834f638af0 | 26,780 |
def tf_pose_to_coords(tf_pose):
"""Convert TransformStamped to Coordinates
Parameters
----------
tf_pose : geometry_msgs.msg.Transform or geometry_msgs.msg.TransformStamped
transform pose.
Returns
-------
ret : skrobot.coordinates.Coordinates
converted coordinates.
"""
... | 3bfaf7d566e90c9ac0c0d8a34060497e2c0c0f78 | 26,781 |
def make_graph_indep_graphnet_functions(units,
node_or_core_input_size,
node_or_core_output_size = None,
edge_input_size = None,
edge_output_size = None,
global_input_size = None,
global_output_size = None,
aggregation_function = 'mean',
**kwargs):
"... | 63694e7765896d0b369b65d4362edca29b6592d0 | 26,782 |
import typing
def is_generic(t):
"""
Checks if t is a subclass of typing.Generic. The implementation is done per
Python version, as the typing module has changed over time.
Args:
t (type):
Returns:
bool
"""
# Python 3.6, 3.5
if hasattr(typing, "GenericMeta"):
... | b085d7799ffe034b4bdeccea250d36f4ff372aea | 26,783 |
def getGpsTime(dt):
"""_getGpsTime returns gps time (seconds since midnight Sat/Sun) for a datetime
"""
total = 0
days = (dt.weekday()+ 1) % 7 # this makes Sunday = 0, Monday = 1, etc.
total += days*3600*24
total += dt.hour * 3600
total += dt.minute * 60
total += dt.second
return(tot... | 16caa558741d8d65b4b058cf48a591ca09f82234 | 26,784 |
from re import T
def make_support_transforms():
"""
Transforms for support images during inference stage.
For transforms of support images during training, please visit dataset.py and dataset_fewshot.py
"""
normalize = T.Compose([
T.ToTensor(),
T.Normalize([0.485, 0.456, 0.406], [... | 38d17b780fc8faf6a77074c53ef36733feb1f756 | 26,785 |
def single_label_normal_score(y_pred, y_gold):
"""
this function will computer the score by simple compare exact or not
Example 1:
y_pred=[1,2,3]
y_gold=[2,2,3]
score is 2/3
Example 2:
it can also compute the score same way but for each label
y_pred=[1,2,3,2,3]
y_gold=[2,2,3,1,3... | 3f906aca6cc5280b932c2dc0a73bfcedad63bd65 | 26,786 |
def get_tuning_curves(
spike_times: np.ndarray,
variable_values: np.ndarray,
bins: np.ndarray,
n_frames_sample=10000,
n_repeats: int = 10,
sample_frac: float = 0.4,
) -> dict:
"""
Get tuning curves of firing rate wrt variables.
Spike times and variable values are both in mill... | ecdc4a71cc5a65dbb51dd69ef7a710c8ff596fec | 26,787 |
def get_custom_feeds_ip_list(client: PrismaCloudComputeClient) -> CommandResults:
"""
Get all the BlackListed IP addresses in the system.
Implement the command 'prisma-cloud-compute-custom-feeds-ip-list'
Args:
client (PrismaCloudComputeClient): prisma-cloud-compute client.
Returns:
... | bcaf44dcefe0fda10943b29cae5e9ba72e561e27 | 26,789 |
import logging
def setup_new_file_handler(logger_name, log_level, log_filename, formatter, filter=None):
"""
Sets up new file handler for given logger
:param logger_name: name of logger to which filelogger is added
:param log_level: logging level
:param log_filename: path to log file
:param fo... | 1ffd48250d17232eea94f13dd52628993ea04c2e | 26,791 |
import hashlib
def _gen_version(fields):
"""Looks at BotGroupConfig fields and derives a digest that summarizes them.
This digest is going to be sent to the bot in /handshake, and bot would
include it in its state (and thus send it with each /poll). If server detects
that the bot is using older version of th... | 0052c655ca355182d0e962e37ae046f63d1a5066 | 26,792 |
import logging
def get_callee_account(global_state, callee_address, dynamic_loader):
"""
Gets the callees account from the global_state
:param global_state: state to look in
:param callee_address: address of the callee
:param dynamic_loader: dynamic loader to use
:return: Account belonging to ... | 28a95b2155b1f72a2683ac7c7029d1d5739305f3 | 26,794 |
from typing import Iterable
def get_products_with_summaries() -> Iterable[ProductWithSummary]:
"""
The list of products that we have generated reports for.
"""
index_products = {p.name: p for p in STORE.all_dataset_types()}
products = [
(index_products[product_name], get_product_summary(pr... | 0d9e23fecfebd66ba251bc62b750e2d43b20c7fa | 26,795 |
def _round_to_4(v):
"""Rounds up for aligning to the 4-byte word boundary."""
return (v + 3) & ~3 | c79736b4fe9e6e447b59d9ab033181317e0b80de | 26,797 |
def bool_like(value, name, optional=False, strict=False):
"""
Convert to bool or raise if not bool_like
Parameters
----------
value : object
Value to verify
name : str
Variable name for exceptions
optional : bool
Flag indicating whether None is allowed
strict : b... | 42d16ae228140a0be719fbd238bdc25dafc1cb64 | 26,799 |
def process_2d_sawtooth(data, period, samplerate, resolution, width, verbose=0, start_zero=True, fig=None):
""" Extract a 2D image from a double sawtooth signal
Args:
data (numpy array): measured trace
period (float): period of the full signal
samplerate (float): sample rate of the acqu... | f7b212d54637e04294cda336e154910eb718b3e5 | 26,800 |
def lower_threshold_projection(projection, thresh=1e3):
"""
An ugly but effective work around to get a higher-resolution curvature
of the great-circle paths. This is useful when plotting the great-circle
paths in a relatively small region.
Parameters
----------
projection : class
... | 165c657f1ec875f23df21ef412135e27e9e443c6 | 26,801 |
def post_benchmark(name, kwargs=None):
"""
Postprocess benchmark
"""
if kwargs is None:
kwargs = {}
post = benchmarks[name].post
return post(**kwargs) | 900f60435ae31e8ec09312f23ab9f98a723d22af | 26,802 |
def tag_view_pagination_counts(request,hc,urls,tag_with_items):
"""
retrieve the pagination counts for a tag
"""
hc.browser.get(urls['https_authority'])
try:
po = hc.catalog.load_pageobject('TagsPage')
po.goto_page()
po.search_for_content([tag_with_items])
po = hc.... | 7130ffdbb2b8f90fadf1a159d15726012511ddee | 26,803 |
def arts_docserver_role(name, rawtext, text, lineno, inliner, options=None,
content=None):
"""Create a link to ARTS docserver.
Parameters:
name (str): The role name used in the document.
rawtext (str): The entire markup snippet, with role.
text (str): The text ma... | 8f20cc4adb9f7fa17514116fe984562d9f0174f3 | 26,804 |
def arima_model(splits, arima_order, graph=False):
"""
Evaluate an ARIMA model for a given order (p,d,q) and also forecast the next one time step.
Split data in train and test. Train the model using t = (1, ..., t) and predict next time step (t+1).
Then add (t+1) value from test dataset to history and f... | 07ca1349e5ebe02793fbf798cbd4e5ce20128a74 | 26,805 |
import ctypes
def srfscc(srfstr, bodyid):
"""
Translate a surface string, together with a body ID code, to the
corresponding surface ID code. The input surface string may
contain a name or an integer ID code.
https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/srfscc_c.html
:... | 9f32b6929c2fd5d482db5f79f4b00f1fe41b114b | 26,806 |
import json
import requests
def pr_comment(
message: str,
repo: str = None,
issue: int = None,
token=None,
server=None,
gitlab=False,
):
"""push comment message to Git system PR/issue
:param message: test message
:param repo: repo name (org/repo)
:param issue: pull-req... | 7115ec59fca36459a15e07906ce5c58b305bcfdc | 26,807 |
from typing import Sequence
def windowed_run_count_1d(arr: Sequence[bool], window: int) -> int:
"""Return the number of consecutive true values in array for runs at least as long as given duration.
Parameters
----------
arr : Sequence[bool]
Input array (bool).
window : int
Minimum dur... | ff7b18380cd77ad046fc5d5aa678e7393c72d495 | 26,810 |
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