content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Optional
def get_uuid_for_error(**kwargs) -> Optional[str]:
"""
Return the uuid for the derived dataset if it exists, and of the parent dataset otherwise.
"""
rslt = get_dataset_uuid(**kwargs)
if rslt is None:
rslt = get_parent_dataset_uuid(**kwargs)
return rslt | f3c6e4ec5f3189ef01fe9a8f9b5eac87b2e181b9 | 57,680 |
def mention_list_by_sentence_with_anaphora(a_obj, prev_obj, server):
"""
returns a list of lists of mentions, where the nth index of the list
corresponds to the nth sentence in obj:
[['Andrea', 'Dan'], ['Shane'], []]
this includes mentions via anaphora.
a_obj is the speechact to retrieve menti... | 3f7090bc0769b9bc2c1c8bfe2c7e08c88077fca7 | 57,681 |
def collect_table_keys(data, exclude):
"""
Resolve used fields per table
"""
table_keys = {}
for rule in data:
t = rule[OF_RECORD_ITEM.table]
for k in rule.keys():
if k not in exclude:
keys = table_keys.setdefault(t, set())
keys.add(k)
... | acb6b9548734c15ead2e9f08e430da68cd0577d5 | 57,683 |
def cross_product_matrices(vectors):
"""Return corresponding cross product matrices for an array of vectors
"""
length = vectors.shape[0]
result = np.tensordot(np.cross(vectors, unit_vectors(length, 3, 0)), np.array([1., 0., 0.]), axes=0) \
+ np.tensordot(np.cross(vectors, unit_vectors(len... | d12b5dca424bc56809c0e85adf20c71e453be4fc | 57,684 |
def format_docstring(usage: str, arg_list, kwarg_dict):
"""
Use argument lists to create Python docstring
"""
usage = usage.strip().strip("\"")
docstring = f'{usage}\n\n'
for arg in arg_list:
if not arg['input']:
continue
docstring += f"\t:param {arg['name']} {arg['t... | a68c0d03aaf851ffb039b722affbdc60f7d05c1c | 57,685 |
from pathlib import Path
import shutil
def temp_article_dir(temp_cwd: Path) -> Path:
"""Run the test from a temporary directory containing the
"tests/data/article" dataset.
"""
article_source_dir = Path(__file__).parent / "data" / "article"
for source_path in article_source_dir.iterdir():
... | 643b2c7f1183f19f263eaba0f3e930ac18fa6988 | 57,686 |
def load_states():
"""Loads the shapefile for states in the United States.
Returns
--------
data : DataFrame
DataFrame containing the shapefile for the United States.
"""
module_path = dirname(__file__)
df = gpd.read_file(join(module_path, 'cb_2018_us_state_500k/cb_2018_us_state_500... | 9f9fadb50781cfa3f783c07a3d9ea16bb3227203 | 57,687 |
def clamp_and_scale(img, bands, p, AOI):
"""
clip the upper range of an image based on percentile
This function is similar to ee.Image().clip() and ee.Image().unitScale(),
but operates on multiple bands with potentially different upper limits.
Parameters:
img (ee.Image): the image to modify
bands (... | 76081111644d4baa3ada4c93037d90ec21af1889 | 57,688 |
from typing import Union
from typing import List
import select
from operator import and_
def get_resources_for(guild_id: int, resource_type="role", session=db.open_session()) -> Union[List[db.Settings], None]:
"""
Searches db for resource in a guild that matches the setting name
:param guild_id: id of th... | af146ec17f71cd1c2cdefbb3beaad196ace80512 | 57,689 |
def rayleigh_k(x,k):
"""Rayleigh distribution parameterized by Fisher k parameter.
"""
return k*x * np.exp(-k*x**2/(2)) | 2dc84228eadb3dc1dc7d946335f02b4254530eda | 57,690 |
def _packaging_type(f):
"""Returns the packaging type used by the file f."""
if f.basename.endswith(".aar"):
return "aar"
elif f.basename.endswith(".apk"):
return "apk"
elif f.basename.endswith(".jar"):
return "jar"
fail("Artifact has unknown packaging type: %s" % f.short_pat... | 2b8cee53091672bb317ecdf29b869b8b8eb73f3f | 57,691 |
def get_validator_keys(epoch, endpoint=_default_endpoint, timeout=_default_timeout) -> list:
"""
Get validator BLS keys in the committee for a particular epoch
Parameters
----------
epoch: :obj:`int`
epoch number
endpoint: :obj:`str`, optional
Endpoint to send request to
tim... | d3f579c75f5cc394c106eefc876dc78074ba798f | 57,692 |
from typing import Any
import time
import json
def read_json_with_timeout(path: str) -> Any:
"""Repeatedly tries to read a json object from the given path, waiting
until there is a trailing new line indicating that the write is complete
Args:
path (str): The path to read from
Raises:
... | 60f61da6e54fdba72f3a5f7300bcd6afd899b866 | 57,693 |
def create_model(model_name, pretrained=False, checkpoint_path=None, **kwargs):
"""Create a model
Almost entirely taken from timm https://github.com/rwightman/pytorch-image-models
Args:
model_name (str): name of model to instantiate
pretrained (bool): load pretrained ImageNet-1k weights if... | 4f3fc75346ad3657891f1460e88bcc45d575ba01 | 57,694 |
from datetime import datetime
def next_weekday(d, weekday):
"""
(datetime, string) -> datetime
returns the first ocurrence of the given weekday after the initial datetime d
"""
days_ahead = weekday - d.weekday()
if days_ahead <= 0:
days_ahead += 7
return d + datetime.timedelta(days... | 456e93f9332bc208e35080c05fcce8c31c329dd1 | 57,695 |
def get_compatibility_matrix(g: nx.Graph, attr_name: str):
"""
From Danai's heterophily paper
:param g:
:param attr_name:
:return:
"""
values = set(nx.get_node_attributes(g, attr_name).values())
mapping = {val: i for i, val in enumerate(values)}
print(mapping)
C = nx.attribute_mi... | 3f8a144278495191ffc861f1c431545255edc93f | 57,696 |
def async_api():
"""
获取异步任务列表
get req:
pass
"""
# q = {filters:[{}], order_by, single, limit, offset, group_by}
query = Async.query.t_query
pagin = gen_query(request.args.get('q', None), query, Async, db=db, per_page=settings.PER_PAGE, get_objects=True)
objects = []
for o in... | 1955bc0c3d27839a4d575779cede5807be110536 | 57,697 |
from operator import ne
def project(fld_a, fld_b):
""" project a along b (a dot b / magnitude(b)) """
# ax, ay, az = fld_a.component_views() # pylint: disable=W0612
# bx, by, bz = fld_b.component_views() # pylint: disable=W0612
# prod = ne.evaluate("(ax * bx) + (ay * by) + (az * bz)")
# mag = ne... | 5e6f0841896365ef41c180ec0239194e5bf4d632 | 57,699 |
def quote_dict(dct, tab):
"""
Recursively quotes dict values
:param dct:
:return:
"""
t = '\t' * tab
# The middle arg here is a newline if value is another dict, otherwise it's a space
dct_sring = '\n{0}'.format(t).join(
[
'%s:%s%s' % (
camelize(k... | bef0627e4fae06ad8cce395c695e72b42da01eb7 | 57,700 |
import types
def fit_state_preparation(create_u_func: types.FunctionType,
vdagger: qiskit.QuantumCircuit,
thetas: np.ndarray,
num_steps: int,
loss_func: types.FunctionType,
optimizer: type... | ec02609b2f6bd7eb20b61a22114399efac5d1873 | 57,701 |
def get_provider_driver(provider=None, region=None):
"""
Gets the specified libcloud driver
:param provider: Name of the driver
:rtype: `libcloud.compute.base.NodeDriver`
"""
provider_driver = config.AVAILABLE_CLOUD_REGIONS.get(provider, {}).get(region, None)
if not provider_driver:
... | d6260a86faa4c4f8d109418b5c95fb88bf2c27d6 | 57,702 |
def load_x_data_for_cnn(patient_name, keep_prob, input_x, sent_length, category_index, dropout_keep_prob):
"""Multiprocessing to fast speed"""
pool = Pool(processes=HP.read_data_thread_num)
generate_token_embedding_results = pool.map(generate_token_embedding, patient_name)
pool.close()
pool.join()
... | 9c00d03f040851d39aad2c38db06e5aa3e1d6194 | 57,704 |
def reshape(a, newshape, order='C'):
"""
Gives a new shape to a tensor without changing its data.
Parameters
----------
a : array_like
Tensor to be reshaped.
newshape : int or tuple of ints
The new shape should be compatible with the original shape. If
an integer, then t... | cbbb2c187a83afb8c1c5eea4c32dfbdd9ca59831 | 57,705 |
def generate_RIP_behavior_graph(records):
"""
:param records:list of tuples (process, RIP, API_called)
:return: the graphs of API_calls of all subprocesses
"""
# Each subprocess is associated to one graph
# LIC stands for Last I Checked
forest_and_LIC = {} # forest_and_LIC = {subprocess : ... | 1bf4a63cd8ab7d0b3d6e03b08cc4989b20c24aae | 57,706 |
def render_mako_tostring_context(request, template_name, dictionary={}):
"""
Render mako tostring with RequestContext
"""
context_instance = get_context_processors_content(request)
return render_mako_tostring(template_name, dictionary=dictionary, context_instance=context_instance) | 0cad38e5e4c041014ff0675c607968af11beb3bf | 57,707 |
def test_pointer_indexing(pointer_value, type_p):
"""
>>> a = np.array([1, 2, 3, 4], dtype=np.float32)
>>> test_pointer_indexing(a.ctypes.data, float32.pointer())
(1.0, 2.0, 3.0, 4.0)
>>> a = np.array([1, 2, 3, 4], dtype=np.int64)
>>> test_pointer_indexing(a.ctypes.data, int64.pointer())
(1... | 21f87a5ec840e3fd789c9e1ca9382d96f451e1e5 | 57,708 |
def _update_centroids(current_centroids, current_weights, new_cluster_sums,
new_weights):
"""Computes a weighted combination of previous and new centroids.
Args:
current_centroids: A tensor whose rows represent the current centroids.
current_weights: A tensor of integer weights associ... | 09975fd6cd1bacdc51f50e910e3a5a6e6b83d07d | 57,709 |
def bound_precision(y_actual: pd.Series, y_predicted: pd.Series, n_to_check=5):
"""
Accepts two pandas series, and an integer n_to_check
Series are:
+ actual values
+ predicted values
Sorts each series by value from high to low, and cuts off each series at n_to_check
Determines how many hits... | 15f78aa2d1ec4d54b1cef88632782f8dff40dc4e | 57,710 |
import copy
def reduce_parallelism(typ, roles, values,calc_set):
"""
calculation_set_yambo ={'resources': {"num_machines": 8,"num_mpiprocs_per_machine": 32}, 'max_wallclock_seconds': 200,
'max_memory_kb': 1*92*1000000 , 'custom_scheduler_commands': u"#PBS -A XXXX" ,
' environme... | 1b8893cdb0d1e949b8013ffd20fb3a5a8b893bd9 | 57,711 |
import re
def clean_empty_sentences(df):
"""
Substitutes all the empty sentences with a customized sequence of characters
"""
return pd.DataFrame({
"sentence": df.sentence.apply(lambda x: re.sub("^ *$", "-", x)),
"label": df.label
}) | a9f6d5a331e76ffacd324cc0b77170095e5a8f6e | 57,712 |
def GetViewableStarredProjects(
cnxn, services, viewed_user_id, effective_ids, logged_in_user):
"""Returns a list of viewable starred projects."""
starred_project_ids = services.project_star.LookupStarredItemIDs(
cnxn, viewed_user_id)
projects = list(
services.project.GetProjects(cnxn, starred_pro... | 2b0ddc93d27131a0d91833f470b03f2cdd7658f3 | 57,713 |
from .units_utils import convert_units
def convert_g_per_liter_resin_to_cv(unitted_data, **kwargs):
""" To convert to volume in CV, divide by the product concentration in g/L.
"""
if "concentration" not in kwargs:
msg = "Trying to convert a volume in 'g per liter of resin' " \
"requ... | 004cd3cf4769f6a982c6853a3367f04470f4c8c0 | 57,714 |
from typing import Union
from typing import List
from typing import Tuple
def minimum_distances(
left_arr: Union[np.ndarray, List],
right_arr: Union[np.ndarray, List],
return_indices: bool = False) -> Union[np.ndarray, Tuple[np.ndarray, np.ndarray]]:
"""
Finds the minimum distance betw... | e90ad3cd5989a6740cc087d1f813f8b1cbf660a7 | 57,715 |
import torch
def manhattan_loss(X, mu_tilde):
"""
Computes the Manhattan loss.
Arguments:
X: array-like, shape=(batch_size, n_features)
Input batch matrix.
mu_tilde: array-like, shape=(batch_size, n_features)
Matrix in which each row represents the assigned mean vec... | 6a913bfdeb558b67684b66e1e1f067a198202474 | 57,716 |
import json
import traceback
def json_data_wrapper(method):
"""
Load JSON data from HTTP request bodies if possible
"""
if request.data:
try:
values = json.loads(request.data)
if values:
values.update(request.values.items())
request.values = values
except:
traceback.print_exc()
pass
retu... | f2253e40196c0310699fbbe2f11f0c200f5b42cd | 57,717 |
import functools
def forest_enabled(func):
"""
Decorator for validating that Forest is enabled for this study.
"""
@functools.wraps(func)
def wrapped(*args, **kwargs):
try:
study = Study.objects.get(id=kwargs.get("study_id", None))
except Study.DoesNotExist:
... | 0656ef67a0fd7bf4c927dae0a4199e15bc5a91e9 | 57,718 |
def test_run_command():
"""
.
"""
# pylint: disable=too-few-public-methods,no-self-use
class FakeSession:
"""
Fake session
"""
command = None
def exec_command(self, command):
"""
.
"""
self.command = command
... | dd85e9cb3250c381ff7ff27c8ef64d714a50b561 | 57,719 |
def find_by_id(object_id, items):
""" Find an object given its ID from a list of items """
for item in items:
if object_id == item["id"]:
return item
raise Exception(f"Item with {object_id} not found") | 822bf82ea68bd94d0bb1ed2dd5db754aee9b0cba | 57,720 |
def spectral_analyze(dataset, timeindex = 0, bands = ['red', 'green','blue'], dims = ['x','y'], height = 500, width = 500, clims = None, norm = 'eq_hist', cmap=['black', 'white'], nodata = 1):
"""Interactivly visualize the spectral profile of single pixels in a multi-band xarray dataset
Description
-----... | 0c1e6cf36cf8d9d4a42dc6b2dd2b92c2c22480e8 | 57,721 |
def common_modulus_attack(modulus, exp1, exp2, msg1, msg2):
"""
Perform RSA Common Modulus Attack, given the modulus, two exponents
and two ciphertexts as integers.
Returns the plaintext as an integer.
"""
g, s, t = gmpy2.gcdext(exp1, exp2)
if g != 1:
print("Error: GCD of the two exp... | 1a4a20cc70f3f6bd1fa4c7ed8cf65ee31184b406 | 57,722 |
def big_h(u: np.array, v: np.array) -> np.array:
"""
The big h-function according to 139 of the specs.
Args:
u:
v:
Returns:
np.array
"""
left = (u + v + np.exp(-u - v)) / 2
diff = np.abs(u - v)
right = (diff + np.exp(-diff)) / 2
return left - right | 6f6873d3c9e4e229a9b38910f529da01ad57cb15 | 57,723 |
import json
def _get_results_table(df: pd.DataFrame, json_file: str = PATHWAY_NAMES):
"""Generate generic results table."""
with open(json_file) as f:
pathway_id_name_dict = json.load(f)
if 'pathway_id' in df:
df['Pathway'] = df.pathway_id.map(pathway_id_name_dict)
df['Database'] ... | a92baf686400e64fbad9ebcb253ea297fc373e50 | 57,724 |
def _getApplicationConfigObject(applicationname, createifneeded = True):
"""Return the application config object for the named application.
Throws exception if the application is not found.
Returns None if createifneeded is False and there isn't one yet."""
# Get the application deployment object for th... | aa2b9573913b9ed35ea7f74be02e3c6ef6961689 | 57,725 |
def getPixmap(page, matrix=None, colorspace=csRGB, clip=None, alpha=False, annots=True):
"""Create pixmap of page.
Args:
matrix: Matrix for transformation (default: Identity).
colorspace: (str/Colorspace) cmyk, rgb, gray - case ignored, default csRGB.
clip: (irect-like) restrict renderi... | 0968ebb22349a40d67892a805a6277bafd36288f | 57,726 |
def get_atom_int(atmstr: str) -> int:
""" Get atom number from atom label """
atom = atmstr.strip().lower()
atom = ATOM_LIST.index(atom) + 1
return atom | a3401776e543153599613101b47fe576bf11b612 | 57,727 |
import requests
import json
def create_snippet(data, baseurl, timeout, raw):
"""
Creates snippet with the given data on the haste server specified by the
baseurl and returns URL of the created snippet.
"""
try:
url = baseurl + "/documents"
response = requests.post(url, data.encode(... | eb34861909b61749ef2f29da16450a82dcc8d83e | 57,728 |
import json
def timeline():
"""Fake endpoint."""
with open('{}/examples/timeline3.json'.format(cwd), 'r') as timelinejson:
return jsonify(json.load(timelinejson))
return jsonify({}) | 5b42c906be66c0bc602e6de86646999b35c41470 | 57,729 |
import numpy
def apply_cnn_soundings_only(
model_object, sounding_matrix, num_examples_per_batch=100,
verbose=False, return_features=False, feature_layer_name=None):
"""Applies CNN to soundings only.
:param model_object: See doc for `apply_2d_or_3d_cnn`.
:param sounding_matrix: numpy arra... | 7e0b0dcce45457ea7e0fe6b420d046406ffe1c69 | 57,730 |
import torch
def fuse_epic_sliding_windows(maps_dict):
"""
Since different sliding windows have overlap, we desigin this function to fuse sliding windows.
Args:
maps_dict (dict): {
"start_map": (tensor)
"end_map": (tensor)
"verb_map": (te... | 205ac18633fcfddd9ba9af6f7b82d89345bf96c3 | 57,731 |
def get_or_create_permission(codename, name=camel_or_snake_to_title):
"""
Get a Permission object from a permission name.
@:param codename: permission code name
@:param name: human-readable permissions name (str) or callable that takes codename as
argument and returns str
"""
u... | 6c6105f1d82a0b889e15623f6391e9227e540b01 | 57,732 |
import re
import copy
def get_params(group, content):
"""
check content validity in {% %} and return params list
token : eval(string) used to generate params.json
orgin: local variable name to be tuned
"""
token_list, origin_list = list(), list()
pattern = INIT + SCOPE + TAIL
param_lis... | c154ea153291496f2181dbb1f5eefdbc33f19cfb | 57,733 |
def server_interaction(client, hostname):
"""The server interaction function."""
prompt = 'fots@fotsies-ubuntu-testlab:~\$ '
# Start a client interaction using the paramiko-expect class
interact = paramikoe.SSHClientInteraction(client, timeout=10,
display=F... | 7c69b3a1ebd76d4c82205609d2e2fdbb2046627b | 57,736 |
import glob
import fcntl
import errno
import time
import csv
def write_monitoring_ts(start_time, np_t, values, quantiles, datatype, fname,
rewrite=False):
"""
writes time series of data
Parameters
----------
start_time : datetime object or array of date time objects
... | 693a3d4de4ff718c3b4e744f0e69eba3e7d8e896 | 57,737 |
def compile_deposit_script(payer_pubkey, payee_pubkey,
spend_secret_hash, expire_time):
""" Compile deposit transaction pay ot script.
Args:
payer_pubkey (str): Hex encoded public key in sec format.
payee_pubkey (str): Hex encoded public key in sec format.
spe... | 4aeb66857f4e848620e3fd00bf91ef59f32762d1 | 57,738 |
def get_error_rate(predictions):
"""
Returns the erro 0-1 classification prediction
Parameters
----------
predictions: pd df with columns 'pred_prob' and 'y'
"""
cutoff = 0.5
# get list of predicted probs and citaiton indicators
y_act = predictions['is_edge'].tolist()
y_pred = ... | a126436ed29a69b1cd9726f76024a11701e9d23b | 57,739 |
import tokenize
def build_model():
"""Build a machine learning pipeline
Args:
None
Returns:
cv: gridsearchcv object. Gridsearchcv object that transforms the data, creates the
model object and finds the optimal model parameters.
"""
pipeline = Pipeline([
('vect', C... | 3839bfea30f55bc812cce8d3a0b22915d9e339cd | 57,740 |
from typing import Sequence
def nan_calc_percentiles(
arr: np.ndarray,
percentiles: Sequence[float] = None,
axis=-1,
alpha=1.0,
beta=1.0,
copy=True,
) -> np.ndarray:
"""Convert the percentiles to quantiles and compute them using _nan_quantile."""
if percentiles is None:
percent... | 99db92753d33b87c88aac2beebda7fcb370615a4 | 57,741 |
def gaussian_tensor(x, axes, m, s, a, normalize=True):
"""Generally a 3-tensor where the axes represent the following: axis 1 is
the x-axis grid, axis 2 is the number of total functions (i.e. training
data) and axis 3 is the number of Gaussian functions one desires to sum
and normalize (if at all).
... | 156fc322d92535afff2a81dd82f7ee507d22d75d | 57,743 |
def logmon(nav, t, sat, cs, iu=None):
""" log variables for monitoring """
_, tow = gn.time2gpst(t)
if iu is None:
cpc = cs.cpc
prc = cs.prc
osr = cs.osr
else:
cpc = cs.cpc[iu, :]
prc = cs.prc[iu, :]
osr = cs.osr[iu, :]
if nav.loglevel >= 2:
n ... | 3385f9b9dd519cee8e9116f960b1f98b92fce2e1 | 57,744 |
def run(config_path, paths):
"""
The worker function that process the tiles.
Args:
config_path (str)
paths (Iterator)
"""
# load config
config = load_config(config_path)
# load model
model = load_model(config)
# update config path
config["loaders"]["test"]["fi... | d9818b48586023b938bf834160aa2d61737f60e9 | 57,745 |
def remove_stale_connectivity_entries():
"""
@rtype : boolean
"""
deletecursor = _db.cursor()
connectivitycursor = _db.cursor()
connectivitycursor.execute("SELECT StorageUUID FROM Connectivity")
connectivityresults = connectivitycursor.fetchall()
for connectivityrow in connectivityres... | 47938669e20543e5e20e2d44b4159c06d9278e7d | 57,746 |
def make_query_from_filter(sample_filter, require_meter=True):
"""Return a query dictionary based on the settings in the filter.
:param filter: SampleFilter instance
:param require_meter: If true and the filter does not have a meter,
raise an error.
"""
q = {}
if samp... | 3ccea6e0253c159517f2f9d3379def00f97487e8 | 57,748 |
def wh_to_kwh(wh):
"""
Convert watt hours to kilowatt hours and round to two decimal places
:param wh: integer or decimal value
:return: two decimal spot kilowatt hours
"""
kw = float("{0:.2f}".format(wh / 1000.00))
return kw | 19488960a9c7a4d2fc748f4d897d082cfdaee2b8 | 57,749 |
def _irafstarfind_objparams(imgcutouts, kernel, sky=None):
"""
Find the parameters for each source as defined by IRAF's
``starfind``.
Parameters
----------
imgcutouts : list
A list of ``findstars._ImgCutout`` objects containing the image
cutout for each source.
kernel : ``f... | c34a07f9141fcc325bc77962fd29b9cd4efa3e4b | 57,750 |
def planck_energy_density(wavelength, temperature):
"""Spectral energy density according to Planck's law.
Uses the SI unit system, so the wavelength must be in meters (m) and the
temperature must be in Kelvin (K). Returns the spectral energy density form
of the Planck's law in Joule per cubic meter per ... | 758ee6ab7552e07ffc51eca436b433a2d11614ce | 57,751 |
import random
def get_background(dimensions: tuple[int, int], d_type: str = 'uint8', weights: tuple[int] = (1, 1, 1, 1, 1)) -> list:
"""
Generate a random background from one of 5 types
Blank background. Random Color
White Noise.
Random picture of a grid or cityscape
Procedurally generated li... | c4299dac551a0b8822934e25047efb7fa9344def | 57,752 |
def unbox_numpy_null(d):
"""
Reverses box_numpy_null, replacing null_numpy_value with None.
Recursively descends into a dictionary replacing None values.
"""
try:
return {k: unbox_numpy_null(v) for k, v in d.items()}
except Exception:
return None if is_null_numpy_value(d) else d | 84aa0bafc3df33819ec0a8a1d26d879ea9f21a42 | 57,753 |
def get_hms():
"""
'2019-06-28 14:47:48'
:return:
"""
hms = dt.datetime.today().strftime('%Y-%m-%d %H:%M:%S')
return str(hms) | 02871fafb61bc1448cdf29ca4a77f16fb4740712 | 57,754 |
def v4_add(matrix1, matrix2):
"""Add corresponding numbers in given 2-D matrices.
Removing the variable - row - altogether.
"""
combined = []
for row1, row2 in zip(matrix1, matrix2):
combined.append([
n + m
for n, m in zip(row1, row2)
])
return combined | 9c5408deb245d86b2f92fd74971a6a8ef0380023 | 57,755 |
import hashlib
import urllib
def gravatar_url(email: str, default_image="mp", size=None) -> str:
"""Creates a gravatar URL from the given e-mail address."""
if email is None:
return None
email = email.lower().strip().encode("utf-8")
url = "https://www.gravatar.com/avatar/"
url += hashlib... | 53aad42a55537736fd88377359b6ce09b20662de | 57,756 |
def isnumber(x):
"""Returns True, if x is a number (i.e. can be converted to float)."""
try:
float(x)
return True
except ValueError:
return False | 3e115928d8458d0034f032a56259e18be6c3383b | 57,757 |
from typing import Union
from typing import List
from typing import Tuple
def get_block_saturation_perf(
data: Union[pd.DataFrame, List],
col_to_use: str = None,
prev_sat_val: float = None,
window_len: int = None,
) -> Tuple[float, int, int]:
"""Calculates the saturation value, experiences to satu... | f3c597addd0b2de803a0fa5c04cd7e06835f12b4 | 57,758 |
def read_football(edgelist, community):
"""
Only takes the vertices in the community list,
since we don't know the ground truth not in the list
"""
# Two files concatenated with ','
# Create a iGraph with first file: Edge-list
G = ig.Graph.Read_Ed... | b4089d6ea3421b32afcd5c08b19f3ffbd7e105b0 | 57,759 |
def eh_posicao_livre (maze, conj_posicoes, posicao):
"""Esta funcao indica se uma posicao (o terceiro argumento dado, validado \
como tal) se encontra livre ao ser indicado um labirinto e um conjunto de \
posicoes (os dois primeiros argumentos, validados como tal)"""
if not (eh_posicao (posicao) and eh_labirint... | 68a889ab5f5ebcf5545ddc734f4820e12d00ace1 | 57,760 |
def delete_trunk(module, switch, switch_port, peer_switch):
"""
Method to delete a conflicting trunk on a switch.
:param module: The Ansible module to fetch input parameters.
:param switch: Name of the local switch.
:param switch_port: The l3-port which is part of conflicting trunk for l3.
:para... | 72dfc4a128f291fbaf0379c5dae2a76d22dda143 | 57,761 |
def julio (string, number):
"""
I like this program.
"""
alpha_cod = ""
codificated = ""
i = 0
position = 0
alpha = "ABCDEFGHIKLMNOPQRSTVX"
while i < len(alpha):
if i + number >= len(alpha) or i + number <= -1:
alpha_cod = alpha_cod + alpha [(i + number) % len(al... | 676b6f12ddf5897171cc809de2275ec4972fa4a0 | 57,762 |
def rgb_rendering_of_mask(pred_img, writing_path=None):
"""
Returns a segmentation mask in red and blue display
:param pred_img: segmented image - 3-class mask
:param save_mask: Boolean: whether or not to save the returned mask
:param writing_path: string: path where to save the mask if save_mask=Tr... | d780af5d18921669daa67d4841faf1d99961280f | 57,763 |
from typing import Iterable
def iscontainer(*items):
"""
Checks whether all the provided items are containers (i.e of class list,
dict, tuple, etc...)
"""
return all(isinstance(i, Iterable) and not isinstance(i, basestring)
for i in items) | 7e40d20bd32187a7bbd74a1635b27460f07e0ea2 | 57,765 |
def createGUI():
"""Creates the, well, GUI!"""
root = Tk()
root.title("Xovich")
root.geometry("500x325")
xovich = Main(root)
return xovich | 55fa9e76b158a593d36eed21a39473de6433b617 | 57,766 |
import torch
def recall_at_k_batch_torch(X_pred, heldout_batch, k=100):
"""
Recall@k for predictions [B, I] and ground-truth [B, I].
"""
batch_users = X_pred.shape[0]
_, topk_indices = torch.topk(X_pred, k, dim=1, sorted=False) # [B, K]
X_pred_binary = torch.zeros_like(X_pred)
if torch.cu... | 580305c0ed43a22e8cf64bee23e3e207516e9e2a | 57,767 |
def write_binary(path, contents):
"""Open file, write binary, and close.
Args:
path (str or py.path.Local): Path of file to write to
contents (bytes): New contents
Returns:
py.path.local: `filename` as :class:`py.path.Local`
"""
p = py_path(path)
p.write_binary(contents... | 988b48d6a7c06567af83f3462df2060cf2c202b3 | 57,768 |
def move(action):
"""Takes the player's input and performs the transformation"""
global climb
#If the person asks for help they will be displayed a list of possible commands
if action == "help" or action == "h":
print("""A list of possible commands (not case sensitive):
Cardinal Directions (... | f6852aa5f4e05ee14038691bd6b69ef0346a65ea | 57,769 |
def core_version():
"""Return the SODAR Core version"""
return projectroles.__version__ | 19bd2fdeaf9066a47d4fa0759e3efcaa9f5b34f8 | 57,770 |
def api_error_generator():
"""
API error dict generator for Flask-restful
Some are just standard from werkzeug.exceptions, others are custom defined above.
:return:
"""
api_errors = {
"BadRequest": {"status": 400, "error": "Invalid syntax in request"},
"NoJSON": {"status": 400, ... | 53dbb9afd3b2c412590a24b225eda58e72e98dd8 | 57,771 |
import math
def angle(vec, units, vec2=[0,0,1]):
""" Angle between vectors (with z by default) """
if units=='degrees': return math.acos( dot( unit(vec), unit(vec2) ) )*180.0/math.pi
elif units=='radians': return math.acos( dot( unit(vec), unit(vec2) ) )
else: print('\nSpecify valid angle unit ("deg... | ce88b5d0fa20ad309f496620eb5956cd0efd19b8 | 57,772 |
import numbers
def scale_tensor(tensor, scale):
"""
Safely scale a tensor without increasing its ``.size()``.
"""
if is_identically_zero(tensor) or is_identically_one(scale):
return tensor
result = tensor * scale
if not isinstance(result, numbers.Number) and result.shape != tensor.shap... | a97734bb077234b21cb71eb74b4bec3f2c4d6835 | 57,773 |
def split_data(x, y, ratio, seed=10):
"""split the dataset based on the split ratio."""
# set seed
np.random.seed(seed)
# generate random indices
num_row = len(y)
indices = np.random.permutation(num_row)
index_split = int(np.floor(ratio * num_row))
index_tr = indices[: index_split]
i... | 229716e4cab06ecafdfbc685158f6f0bd4b1594d | 57,775 |
def validate_with_model(model, type_checks=None, ignore=None,
ignore_missing=None, disallow=None):
"""
Decorator which will check the contents of the of the json
request against a model for:
* missing fields which are required
* values which don't match their type(s)... | 352a2332ccb35f3193979225b5ebfe633a319012 | 57,776 |
def run_validators():
""" Run all test validators """
# First, add the validator direcotry to the python path to allow
# modules to be loaded by pylint
# We also add the jenkins/test directory so that github_helpers can be properly loaded.
pypath = os.getenv("PYTHONPATH", "")
tools_test_path = O... | d5ddecbcb5edee8a189c8dc178251995c42e752b | 57,777 |
def widthHeightDividedBy(image, value):
"""Divides width and height of an image by a given value."""
w, h = image.shape[:2]
return int(w/value), int(h/value) | 78bbe60c43a1bbf362c98125bfddc080cf568861 | 57,778 |
import time
import site
def _get_hazard(
ensemble: gm_data.Ensemble,
station_name: str,
im: IM,
exceedance: float,
ix: int,
n_stations: int,
):
"""Computes the ensemble hazard curve for the specific station"""
start_time = time.time()
site_info = site.get_site_from_name(ensemble, s... | 6c43223b52385d1d08157d6655c9655608027b63 | 57,779 |
def analytical_pulse_energy(q, ekev):
"""
Estimate of analytical_pulse_energy from electron bunch charge and radiation energy
:param q: electron bunch charge [nC]
:param ekev: radiation energy [keV]
:return P: pulse energy [J]
"""
P = 19*q/ekev
return P/1e3 | d81ddafcc41e0e8619922dce0583bf19579112bc | 57,782 |
def batch_parallel(map_fn, devices, **kwargs):
"""
Parallelize map_fn across devices.
:param map_fn: function that takes kwargs and returns a tuple of tensors
:param devices: A list of devices to parallelize over
:param kwargs: kwargs of input to map, will be split along axis 0.
:return: The ou... | 0f0fb6da8553b73d8aeaebaec076b34af4571523 | 57,783 |
def plot_airfoil(air_df):
"""Plot an airfoil
Parameters
-----------
air_df : pd.Dataframe
Pandas Dataframe containing x- and y-coordinates of airfoil data.
"""
line, = plt.plot(air_df.x, air_df.y)
plt.axis('equal')
return line | 2b5c87acd54f8680a50a7e894b1a9658e631cecd | 57,784 |
def get_file_date(tree):
"""
Get publication date from dta file xml tree.
:param tree: the xml tree
:return: int, the publication date
"""
date = tree.find("{http://www.dspin.de/data/metadata}MetaData/{http://www.dspin.de/data/metadata}source/{http://www.clarin.eu/cmd/}CMD/{http://www.clar... | 64b0e43b9926d94f1cec066af5bf58ecc10d5044 | 57,785 |
import string
import random
def random_string(string_length=10):
"""
Generate a random string of fixed length
:param string_length:
:return:
"""
letters = string.ascii_lowercase
data = ""
for character in range(string_length):
data += random.choice(letters)
return data | 54600929a4250612ac6dda904778950a767bd654 | 57,786 |
def format_version(version):
"""Converts a version specified as a list of integers to a string.
e.g. [1, 2, 3] -> '1.2.3'
Args:
version: ([int, ...]) Version as a list of integers.
Returns:
(str) Stringified version.
"""
return '.'.join(str(x) for x in version) | fa85b122ce6fed4919ec87ad29847b0997493806 | 57,788 |
def find_keys_for_target(keys_left, keys_right, target):
"""
Finds a (left, right) pair of default rule keys in the respective keys dictionaries
for the given target
"""
print("Searching for the specified build target...")
print(target)
target_pattern = '"' + target + '"'
criteria = [
... | 35686f69e36da76d6514e138579a4ecb5f21d3d9 | 57,789 |
def padded_cross_entropy_loss(logits, labels, masks, smoothing=0.05, vocab_size=256):
"""Calculate cross entropy loss while ignoring padding.
Args:
logits: Tensor of size [batch_size, length_logits, vocab_size]
labels: Tensor of size [batch_size, length_labels]
masks: Tensor of size [batch_size, length_... | c29ea2f99e6485cd052ea1fb8bc868908cb91908 | 57,791 |
def get_open_title(win, message_id, oms):
"""Build title for File Open / Save dialog
"""
what = get_text(win, message_id)
if oms:
what = ' - '.join((what, oms))
return what | 52e33e1c1d583f0fcf0050c1795440faa3d8c40f | 57,792 |
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