content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import tqdm
def calc_curve_bootstrap(curve, metric, y, preds, n_bootstrap, seed=12345, stratified=True, alpha=95):
"""
Parameters
----------
curve : function
Function, which computes the curve.
metric : fucntion
Metric to compute, e.g. AUC for ROC curve or AP for PR curve
y : n... | 3ce7d2cacd9d09b8978db6514a112cfe5288ba6a | 3,610,200 |
import os
def connect(host=None, database=None, user=None, password=None, **kwargs):
"""Create a database connection."""
host = host or os.environ['PGHOST']
database = database or os.environ['PGDATABASE']
user = user or os.environ['PGUSER']
password = password or os.environ['PGPASSWORD']
ret... | a247940b8b18e69d85775d94bfee420ba32aad79 | 3,610,201 |
def to_b58_string(multihash):
"""
Convert the given multihash to a base58 encoded string
:param bytes multihash: multihash to base58 encode
:return: base58 encoded multihash string
:rtype: str
:raises: `TypeError`, if the `multihash` has incorrect type
"""
if not isinstance(multihash, b... | e85c83a622c3371b85f5dc716bbf1a415d03e349 | 3,610,202 |
import subprocess
import os
def run_in_docker(
command: str, docker_options="", capture_output=False, text=None
) -> subprocess.CompletedProcess:
"""Run command in Docker."""
command = command.strip()
print("+ ", command)
env = os.environ.copy()
env["PWD"] = cwd_for_docker_volume()
return ... | 5007dbcdd6de80ef6c2001521111b9f79305bdbf | 3,610,203 |
import logging
import os
import yaml
def get_logger(name, level=logging.INFO):
"""
Get a logger and load logging.yaml config file if exists
"""
# Set a basic level of logging
logging.basicConfig(level=level)
# Get the path to the logging config yaml
dir_py_file = os.path.dirname(os.path.r... | 09899272eff1ba937bb64cc2c1705c204147adea | 3,610,204 |
import urllib
def make_request(url: str) -> HTTPMessage:
"""
Send a get request to the url passed in and return
the headers in the response
Args:
url (str): url to send GET request to
Returns:
HTTPMessage: http response object
"""
with urllib.request.urlopen(url, timeout=3... | 11b628838b6cee5528761440e2b13de428f508e6 | 3,610,205 |
def poly0g_to_poly01(polygon, grid_side):
"""
[0, grid_side] coordinates to [0, 1].
Note: we add 0.5 to the vertices so that the points
lie in the middle of the cell.
"""
result = (polygon.astype(np.float32) + 0.5) / grid_side
return result | d3882be349bf09a5634de00ef12bef851d826075 | 3,610,206 |
def image_loader(path):
"""Image Loader helper function."""
return Image.open(path.rstrip("\n")).convert('RGB') | b6b989703771d6dd4ca8705044027fb71bcdcdb7 | 3,610,207 |
def retrieve_item(item_id):
"""
This is a stubbed method of retrieving a resource. It doesn't actually do anything.
"""
return {
"id": item_id,
"brand_name": "Clean Breathing",
"name": "Air Purifier",
"weight": 12.3,
} | eedeca7580bd74244c62da798ac19d6b815ba445 | 3,610,208 |
def max_drop_in_simulated_observation(
event_duration: int,
observation_size: int,
noise_sigma: float,
corr_array: np.ndarray) -> float:
"""Returns the maximum drop from a simulated observation.
An observation consisting only of correlated gaussian noise is
created and exhau... | 464f45adc3633ba87105f66dd4bc492c1241c500 | 3,610,209 |
def tau_of_N(microns, column, v0=0, temperature=20, width=1.0, velocity=0.0, orthopara=3):
"""
Return the optical depth of an H2 line as a function of wavelength...
(absorption)
"""
grounden = h2level_energy(0,0)
alllevelpop = np.sum([exp(-(h2level_energy(v,j)-grounden)/(k*temperature)) for v in... | 2d8c84188c802554be79660874a5f7cafafbcf6c | 3,610,210 |
def witness_dag_from_root(root, xsys, get_links=lambda y: map(lambda e: set({e}), y), strict=False):
"""Builds the witness DAG as in Englert (2014) from a sequence of 2-opt steps"""
# add a node for each edge in the initial tour with arbitrary timestamp {1,..,n}
_, y = xsys[root]
links = [find_next_li... | 20e7e905fadd383c8bf005bdd2b18a5ff32ca082 | 3,610,211 |
def create_instance(test_id, config, args):
"""
Invoked by TestExecutor class to create a test instance
@test_id - test index number
@config - test parameters from, config
@args - command line args
"""
return TestPeerReachability(test_id, config, args) | 5bfa04a20898fa2086656bd21a57a67d9d61a956 | 3,610,212 |
from typing import List
def get_graphs_np(graphs: GraphsTuple, indices=List[int]) -> GraphsTuple:
"""Gets a new graphstuple (numpy) based on a list of indices."""
node_indices = np.insert(np.cumsum(graphs.n_node), 0, 0)
node_slice = np.concatenate(
[np.arange(node_indices[i], node_indices[i + 1]) ... | 3b19af0f179749be6b3c1b3d743961baf616b4e9 | 3,610,213 |
def one_hot(Y, C):
"""
:param Y: -- shape of (1, number of examples)
:param C: -- number of classes of Y
:return:
Y_oh -- shape of (C, number of examples)
"""
m = Y.shape[1]
Y_oh = np.zeros((C, m))
for i in range(m):
Y_oh[Y[0,i],i] = 1
return Y_oh | a88d145033c1995d36031a5d176d1333f861ca48 | 3,610,214 |
import six
def parse_input_data(input_data, hdu_in=None):
"""
Parse input data to return a Numpy array and WCS object.
"""
if isinstance(input_data, six.string_types):
return parse_input_data(fits.open(input_data), hdu_in=hdu_in)
elif isinstance(input_data, HDUList):
if len(input_... | 5c1b4fc5dfa2b5a89242e62580f8d38b7c15952e | 3,610,215 |
import plotly.express as px
def _plotlyGraphCore(data: GraphData, title, legend):
"""Internal function for plotly graphing, users should call plotlyGraph() instead"""
try:
except ImportError:
raise ImportError("Plotly is required to use this graph. Install with `pip install plotly`")
sm =... | 0f6cf8fb052bda60c9235f96a37a9b481fee2ece | 3,610,216 |
def alg_to_song(algorithm, num_qubits=None,
num_samples=40, mapping=maps.default_map,
name="alg", tempo=100):
"""
Make a song from an algorithm. Markovian sample the algorithm, then map
to a Song object.
algorithm: list of Gate objects and/or string gates. Example:... | 09d55312a57438834afcb8406b6683819854dc68 | 3,610,217 |
from typing import Optional
from typing import Any
def encode_categorical_data_with_vocabulary(
train_data: np.ndarray,
test_data: Optional[np.ndarray] = None,
unknown_item_idx: int = 0,
) -> tuple[np.ndarray, Optional[np.ndarray], list[Any]]:
"""Encode the categorical data by using vocabulary mapping... | d89cb19df4bb1510e01db851caf865f947ce5fac | 3,610,218 |
def filter_sides(segmentation):
"""Remove hedges on left and right hand side.
Also remove anything from the edge of the hedge
to the closest edge of the image.
"""
ydim, xdim = segmentation.shape
mid_point = xdim // 2
for i in segmentation.identifiers:
region = segmentation.region_b... | 4d02903b4cadc39fb3461fdc13916cc7233ad39d | 3,610,219 |
from datetime import datetime
def log_file_name(extension):
"""
Create a file name in the logfiles directory, based on current data and time
Requires the computer to have an RTC or synched clock
"""
now = datetime.now()
# Linux
file_name = '%0.4d%0.2d%0.2d-%0.2d%0.2d%0.2d' % (now.year, now... | 795ab0623ee6a563cfc4e2531cd8745f0ff2fac3 | 3,610,220 |
def arc(data: bytes) -> int:
"""
Compute a CRC-16 checksum of data with the arc algorithm.
:param bytes data: The data to be computed
:return: The checksum
:rtype: int
:raises TypeError: if the data is not a bytes-like object
"""
_ensure_bytes(data)
return _crc_16_arc(data) | 1ce9de456d04b1a8b060a1cb83ffd1b457bdae86 | 3,610,221 |
def check_replication(master_vals, slave_vals, options):
"""Check replication among a master and a slave.
master_vals[in] Master connection in form: user:passwd@host:port:socket
or login-path:port:socket
slave_vals[in] Slave connection in form user:passwd@host:port:socket
... | dde3878a9afde2bd12209da20da5681fd64ba77c | 3,610,222 |
def _incremental_mean_and_var(X, last_mean, last_variance, last_sample_count):
"""
Note. Most of this script is taken from scikit-learn, except for the last line.
--- Original doc ---
Calculate mean update and a Youngs and Cramer variance update.
last_mean and last_variance are statistics compute... | 55eacfc7905eae1b2608314a651c25f2707a3ac7 | 3,610,223 |
def _calculate_expected_result(
dist_per_cell, numeric_values, numeric_values_scale, input_mask_float, logits_aggregation, config
):
"""
Calculates the expected result given cell and aggregation probabilities.
Args:
dist_per_cell (`tfp.distributions.Bernoulli`):
Cell selection distr... | b282c538b495989b6c4066b8f99d72fc4810845e | 3,610,224 |
def fit_unbinned(f_likelihood, data, start_guess, min_method=None, bounds=None):
"""
unbinned max likelihood fit to data with given likelihood func
"""
if method is None:
method="L-BFGS-B" # minimization method, see docs
result = minimize(
neg_log_like, # function to minimize
... | ac20d2fe30aae1922190fee7a38d204a1612a2ad | 3,610,225 |
def load_data(n_pca=3):
"""Data Loader
:param n_pca: number of pca components, defaults to 3
:type n_pca: int, optional
"""
path = f'../dataRBC/RBC_r28L_T100R100_pca{n_pca}_enc_data.txt.gz'
traj_data = pd.read_csv(path, header=None).values
traj_data = traj_data.reshape(-1, 200, n_pca)
... | e7e7c454da1aebb2af83f800e488cfab3296b110 | 3,610,226 |
import os
import pickle
def load_object(fname,zip=0,nofind=0,verbose=0):
"""Loads an object from disk. By default, this handles zipped files
and searches in the usual places for OCRopus. It also handles some
class names that have changed."""
if not nofind:
fname = ocropus_find_file(fname)
... | 10252b6c1348750b66c2a01a27df8f4e6aa9d660 | 3,610,227 |
def delete_attachment(self, request, form):
""" Delete a notice attachment. """
layout = Layout(self, request)
notice = self.linked_official_notices[0]
if notice.state == 'accepted' or notice.state == 'published':
if not request.is_secret(self):
request.message(
_("... | 6715c1079dfabd4e43e97a88ff4b5c75c563b00c | 3,610,228 |
def geoloc(ip_address: str) -> dict:
""" Return {'lat':, 'lon':} values for {ip_address} """
ip_details = method_ipinfo(ip_address)
return {'lat': ip_details['latitude'], 'lon': ip_details['longitude']} | 1f98d69dd9d239f27c85e490cc69d5a27aac9184 | 3,610,229 |
def TreeImportanceArray(reg):
"""Get important array if `reg` is tree regression."""
return reg.feature_importances_ | 59f3b0bcc9a4c60af71b62163e3e087137c64f49 | 3,610,230 |
def _get_test_stats_with_mi(feature_names):
"""Get stats proto for MI test."""
result = statistics_pb2.DatasetFeatureStatistics()
for feature_name in feature_names:
feature_proto = text_format.Parse(
"""
custom_stats {
name: "max_sklearn_adjusted_mutual_information"
... | d5ebdd6a55ca0af03b1076ecc5fd4741f296ec19 | 3,610,231 |
def ride(self: Client, riders_or_rides: str) -> RideProxy:
"""Delegates to a
:py:class:`mcipc.rcon.be.commands.ride.RideProxy`
"""
return RideProxy(self, 'ride', riders_or_rides) | 209f5804eaf7a6e566fd13acc484abf73802d47c | 3,610,232 |
def process_data(event_id, st, sampling_rate, pre_filt=(1.2, 2, 8, 10), water_level=100,
folder_name="default_folder", save_processed=True):
"""
Function to process the raw data stream
Args:
event_id (str): Event ID -> Ideally should be time stamp YYYY-MM-DDTHH:MM:SS.000
st ... | bf2b1f829bb0211d9d1729d8feb4534cb01b236e | 3,610,233 |
from typing import Any
from typing import Dict
def _check_headers(headers: Any) -> Dict:
"""Check headers format an validate content type.
:param headers: configured headers
:return Dict: request headers
"""
if headers is None:
headers = {}
if 'Content-Type' not in headers.keys():
... | f7dc965ffd740ea94ca3485f455cf6427ebc16d8 | 3,610,234 |
def average_test_disorder(data, test_classifier, target_classifier):
"""Given a list of points, a feature-test Classifier, and a Classifier
for determining the true classification of each point, computes and returns
the disorder of the feature-test stump."""
test_disorder = 0
test_classifications = ... | 555b55c58cfa956642d6b4f53afca07a999a33b1 | 3,610,235 |
import os
import glob
def test_snippets() -> bool:
"""Test all code snippets in *.snip files."""
here = os.getcwd()
fixture = CompilerFixture()
fail = False
for i in glob.glob(here + "/*.snip"):
print("=" * 20)
print(i)
try:
fixture.run_file(i)
except Ex... | 60c98bd13a1a24548493e5d1b39a07b7bb7a1b07 | 3,610,236 |
import signal
def seed_initial_offsets_peaks(y, noise, rect_area=500, prominence_knockdown_factor=0.03):
"""
Generate the locations of the seeds for the initial fit. Place a seed at each of the peaks.
Determine peak location from smoothed version of signal. Smooth signal by cross correlating it with rect.... | e7b4f572cedf5ef37e5bc0c3a6f724704c212f16 | 3,610,237 |
def ReadNetString(fp):
"""Reads a net string from the File object fp, returning the string in
unicode.
A net string has the format <len>:<str>,
where <len> is decimal of the length of <str>, and comma ends the string.
Returns:
The unicode string contained in the netstring, or '' if... | 9805367388fea261df94209482f3d496ef6e749b | 3,610,238 |
def to_str(obj):
"""Attempts to convert given object to a string object
"""
if not isinstance(obj, str) and PY3 and isinstance(obj, bytes):
obj = obj.decode('utf-8')
return obj if isinstance(obj, string_types) else str(obj) | 1123f73fff9b0eebe3a6d29f2768f0459e0d83f2 | 3,610,239 |
def get_middle_value(my_list):
"""Return the middle value from a list after sorting.
:param list my_list: List of sortable values"""
return sorted(my_list)[len(my_list) // 2]
"""Convert an integer resolution in base-pairs to a nicely formatted string.
:param int window_size: Integer resolution ... | 53e8724f1709429707766db45c34ebd0db62a686 | 3,610,240 |
import math
def ll2m(lat, lon):
"""Lat/lon to meters"""
x = lon * 20037508.34 / 180.0
y = math.log(math.tan((90.0 + lat) *
math.pi / 360.0)) / (math.pi / 180.0)
y = y * 20037508.34 / 180
return (x, y) | f998cb7af707d56c9dd6e7a26b8d165f392e07f3 | 3,610,241 |
def bilinterp(x, y, nx_tuple, ny_tuple, x_tuple, y_tuple, fxy):
"""
Bilinear interpolation: Given nx-tuple + 1 x-points,
ny-tuple + 1 y-points, x_tuple and y_tuple,
routine finds f(x, y) = fxy at (x, y) in (x_tuple, y_tuple).
Assumes x_tuple and y_tuple are increasing arrays.
"""... | ee6ffb312cb0a7af3cff524aa366e71f176158f8 | 3,610,242 |
def get_version():
"""Return version of the dynamic link library.
Wraps:
int DWGetVersion();"""
return _get_version() | a99b2c66124f14b04c476b888663ffd7b38a61ff | 3,610,243 |
def edu_plotter(func):
"""Decorator to apply to all plotting functions in OGGM-Edu.
Parameters
----------
func : function
the function or method to decorate
Returns
-------
the decorated function
"""
@wraps(func)
def context_wrapper(
*args,
sns_context=... | d44a63d1c62f5107eb9cbedd89b3c3634bc60a00 | 3,610,244 |
def load_sample_data(name):
"""
Load an example dataset from the GMT server.
The data are downloaded to a cache directory (usually ``~/.gmt/cache``) the
first time you invoke this function. Afterwards, it will load the data from
the cache. So you'll need an internet connection the first time around... | 73ffa2caa4106f97d88766214756fbf6347f4787 | 3,610,245 |
def rip_svgi(content: str, embed_styles: bool = False) -> str:
"""
Rips SVG content (single diagram) and scripts for interaction out of HTML
:param content: HTML page content in text format
:param embed_styles: If specified as True then mentioned styles would be downloaded and embedded into SVG
... | d5472b86be70e138128ff527f388a9b1ffa2602d | 3,610,246 |
def get_info(request):
"""
Obtiene
"""
info = "Backend"
if UserToken.get_headquar_id(request.session):
try:
sede = Headquar.objects.get(
id=UserToken.get_headquar_id(request.session))
info = "%s-%s" % (sede.enterprise.name, sede.name)
except:... | fbfdf8ce2a802af374b0004bb0e6029849c38b9d | 3,610,247 |
from typing import Sequence
def prune_by_lbh(seq_list: list, seq_length: int, q: Sequence, kim_reduction: float = 0.75,
keogh_reduction: float = 0.25):
"""
Prune the sequences based on LB_Kim and LB_Keogh lower bound. First the sequences are pruned using LB_Kim
reduction factor and then u... | c2ed7e88f9597e9f27ed1902fca858a35e028ff3 | 3,610,248 |
def keyDataIdsInit():
"""
Initializes the key data klasses. This function is called from the init
function and the application should not call it directly.
Returns : 0 on success or a negative value if an error occurs.
"""
return xmlsecmod.keyDataIdsInit() | a2f254c8b0655cea68f6a91092ac0b7697f99df2 | 3,610,249 |
import os
import click
def cli(drivername, mfname, devicetype, author):
""" Create sal driver staging from template """
templatedir = os.path.join(scriptdir, templates[devicetype][0])
destdir = os.path.join(scriptdir, "../../", templates[devicetype][1], drivername)
destdir = os.path.abspath(destdir)
... | 7321e77ad30472ed8b8420db132ced002cd3164b | 3,610,250 |
import numpy
def _image_to_ground_plane_perform(r_tgt_coa, r_dot_tgt_coa, arp_coa, varp_coa, gref, uZ):
"""
Parameters
----------
r_tgt_coa : numpy.ndarray
r_dot_tgt_coa : numpy.ndarray
arp_coa : numpy.ndarray
varp_coa : numpy.ndarray
gref : numpy.ndarray
uZ : numpy.ndarray
R... | d325471ce2f21562dfd38e536ce77eb215069349 | 3,610,251 |
def encode_string_text(text):
"""Replace special symbols with corresponding entities or magicwords."""
text = text.replace("<", "<")
text = text.replace(">", ">")
text = text.replace("[", "[")
text = text.replace("]", "]")
text = text.replace("{", "{")
text = text.replace(... | c7887934983efda3a0d1e06451ccd85cab529a30 | 3,610,252 |
def compute_input_planes(input_channels, merging_strategy, inputs, abs_nodes):
"""Compute the number of input planes."""
if len(inputs) == 0: # this is an input node
return input_channels
inplanes = 0
for i in inputs:
if merging_strategy == EdgeMerge.CAT:
inplanes += abs_nod... | a6f163a9891f77ba58e06905d3ed03fe9e7259eb | 3,610,253 |
def test_01_setup():
"""
sample init init attr, state, action space
:return:
"""
names = ['gender', 'age']
vals = {'gender': ['M', 'F', 'U'],
'age': ['0-19', '20-29', '30-39', '40-49', '50-59', '60-69', '70-*']}
attr_set = AttrSet(names, vals)
state_set = StateSet(['date', '... | ce487a5287859ea1502aea0090df90f5a0769036 | 3,610,254 |
def make_aware(value, timezone=None):
"""
Make a naive datetime.datetime in a given time zone aware.
:param value: datetime
:param timezone: timezone
:return: localized datetime in settings.TIMEZONE or timezone
"""
if timezone is None:
timezone = TIMEZONE
# Check that we won't... | 8012d14a84bf44f14454f5bf02f4ec93d31668cf | 3,610,255 |
from typing import Tuple
def parse_reflections_array(array: np.array) -> Tuple:
"""
Helper method for parsing reflections without exporting to ".CSV"
Parse an reflection array of GSASII defined as:
index explanation
0,1,2 h,k,l (float)
3 (int) multiplicity
4 (float) d-space, Å
5 (floa... | a20e11499b6baba9c6c6631441cd457a88bac5b9 | 3,610,256 |
def get_dbconn(db_dsn):
"""Connects to the MongoDB server and returns a database handler."""
def _ensure_indexes(db):
"""
Ensures that an index exists on specified collections.
Definitions:
index_by_collection = {
'collection_name': [
('field_name_1'... | f4b074547ce539865f17cee302feae0ca4bbd0d2 | 3,610,257 |
def _params_to_ints(qs):
"""Convert a (string) list of string ids to a list of integers"""
return [int(str_id) for str_id in qs.split(',')] | 7568eeb6cf28f1c8e696e2fab6e7a89dcbbc07fc | 3,610,258 |
import typing
import json
def _prepare_hyperparams(free_hyperparams: typing.Sequence, hyperparameter_values: typing.Dict) -> typing.Tuple[typing.Sequence, typing.Set[str]]:
"""
Values in ``hyperparameter_values`` should be serialized as JSON, as obtained by JSON-serializing
the output of hyper-parameter's... | 90a42428d33c6931622258691d92e82642dfa49e | 3,610,259 |
from typing import List
def est_croissante2(l : List[float]) -> bool:
""" ... cf. ci-dessus ...
"""
# Résultat
b : bool = True
# Indice courant
i : int = 0
while (i < len(l) - 1) and b:
b = l[i] < l[i + 1]
i = i + 1
return b | 74357fe91d42b3cb0d95e09346504b0701ab7164 | 3,610,260 |
def compose(f, g):
"""
Compose two filter f and g.
:param f: Outer filter function.
:type f: filter function.
:param g: Inner filter function.
:type g: filter function.
:return: lambda x: f(g(x))
:rtype: filter function.
"""
def filter_fn(df):
df = g(df)
if len... | d90cda63eb365219ce5f454265036c7d977da216 | 3,610,261 |
def Device(device_name):
"""Returns the taurus device for the given device name
It is a shortcut to::
import taurus.core.taurusmanager
manager = taurus.core.taurusmanager.TaurusManager()
factory = manager.getFactory()
device = factory.getDevice(device_name)
:param device_... | 834baf071ab408e9150cc803a317f151554950cb | 3,610,262 |
def load_data(self, name):
"""Load data given a data path.
This is a low level method that will search through the various
search paths until it's able to load a value. This is typically
only needed to load *non* model files (such as _endpoints and
_retry). If you need to load model files, you sho... | 94e75787fa72b91ea5e27e8cd076b36037044962 | 3,610,263 |
def stop_list_to_link_list(stop_list):
"""
[a, b, c, d] -> [(a,b), (b,c), (c,d)]
"""
return list(zip(stop_list[:-1], stop_list[1:])) | 49046e60664cd9c19ab55c1254684932d937531a | 3,610,264 |
from typing import Union
def compare(A: Mv, B: Mv) -> Union[Expr, int]:
"""
Determine if ``B = c*A`` where c is a scalar. If true return c
otherwise return 0.
"""
if isinstance(A, Mv) and isinstance(B, Mv):
Acoefs, Abases = metric.linear_expand(A.obj)
Bcoefs, Bbases = metric.linea... | 830dfaa97cf042278278b5c1aff8da77d5ee8f5a | 3,610,265 |
def get_enum_size(*args):
"""get_enum_size(enum_t id) -> size_t"""
return _idaapi.get_enum_size(*args) | 58024506d567e6d07d420233a16c1bd1e2f7750e | 3,610,266 |
def _martin_luther_king_holiday(year):
"""Martin Luther King's birthday (third Monday in January)"""
if year < 1983:
return None
for day in range(15, 22):
d = dt.date(year, 1, day)
if d.weekday()==0:
return d
raise Exception('Should never get there') | 06cfb37660a8b7034bad3cadc329bca84694acb6 | 3,610,267 |
def random_bivariate_anisotropic_Gaussian(kernel_size,
sigma_x_range,
sigma_y_range,
rotation_range,
noise_range=None,
... | add17263e4bc7c1b99bf55bf032e40cc093d7079 | 3,610,268 |
def validate_guess(number) -> str or None:
"""
:param number: the number to guess
:return: the valid guessed number or None if user gives up
"""
number_size = len(number)
while True:
guess = easygui.enterbox(f"Please guess the {number_size}-digit number: ")
if guess is None:
... | 41cfc02f97f33365389bd27dcd42d65c31ccdb57 | 3,610,269 |
def excel_radiosonde(request, form):
"""
Reads the radiosonde form and converts the data into a excel file
"""
start = form.cleaned_data['start_date_radiosonde']
end = form.cleaned_data['end_date_radiosonde']
time = form.cleaned_data['time_radiosonde']
fields = form.cleaned_data['fields... | 371736b8f6c0eb0b84a46bc4aa36060bf85b3db4 | 3,610,270 |
def compare_metrics(best_eval_result, current_eval_result):
"""Compares two evaluation results."""
return best_eval_result["exact_match"] < current_eval_result["exact_match"] | ce3880c2cc271d9c8c766a2dfbd95d31f5fb651c | 3,610,271 |
import importlib
def import_module(filename):
"""Import a module given a full path to the file."""
spec = importlib.util.spec_from_file_location("doc_filter", filename)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module | 924f19b96d98290dabfda1aef70cb7f67455f553 | 3,610,272 |
def set_target_bits(targs, sourcemask):
"""Apply bright source mask to targets, return desi_target array.
Parameters
----------
targs : :class:`recarray`
A recarray of targets as made by, e.g., :mod:`desitarget.cuts.select_targets`.
sourcemask : :class:`recarray`
A recarray containi... | 156a45e5c79a02321a3de05081ec429f5a4c325d | 3,610,273 |
def get_checksum_value(checksum):
"""
Return the checksum value.
The given checksum might either be a standard ad32 or md5 string, or a dictionary with the format
{ checksum_type: value } as defined in the `FileSpec` class. This function extracts the checksum value from this
dictionary (or immediate... | bc5a3a506a53970217a32fc0be79378e85787c18 | 3,610,274 |
def construct_bibfile_data(*paths):
"""
List of data corresponding to individual bib files
:param pathlib.Path *paths: Path to file possibly containing BibTeX data.
:rtype: list
"""
bibs = [reffile_factory(path) for path in paths]
return bibs | 7b0ddfd615e8cb54ce905d52a756e689824454a1 | 3,610,275 |
def check_shell_pipes(cmd):
"""
Determine whether a command appears to contain shell pipes.
:param str cmd: Command to investigate.
:return bool: Whether the command appears to contain shell pipes.
"""
return "|" in strip_braced_txt(cmd) | ad91661727e42fef6c95428b524c0178e23642ec | 3,610,276 |
from typing import Dict
import requests
from bs4 import BeautifulSoup
import re
def scrap_allrecipes_recipe(url: str) -> Dict:
"""This function scraps a recipe of Allrecipes, given its URL,
and prepare a JSON file to index in Elasticsearch.
:param url: the URL of the recipe
:return: the recipe as a J... | 0c060ba40e784b7dad6ab2af40dd6f0aa4600173 | 3,610,277 |
def waitTargetUpdate(omni_robot, timeout):
"""
Wait for target updating
:param omni_robot: (OmniRobot)
:param timeout: (time to wait for updating)
"""
omni_robot.target_pos_changed = True
time = 0.0 # second
while time < timeout and not rospy.is_shutdown():
if not omni_robot.tar... | c9be8516640667a758ef1a3fc62b881fc4bedec3 | 3,610,278 |
def known_references(request):
"""
List all known references witht he option of removing the contact date
"""
user = request.user
if 'remove_known_ref' in request.POST and \
request.POST['remove_known_ref'].isdigit():
try:
application = CredentialApplication.objects.get(
... | e22424641306f0020006f233cfea2b169a4c17c6 | 3,610,279 |
def get_plugin():
"""Return the filter."""
return IpynbFilter | 991dead0a95e97526736e3cf06bd76138be46cf2 | 3,610,280 |
from typing import Collection
from typing import Tuple
import os
import tempfile
import logging
import shutil
import subprocess
import shlex
def run_gliph(fname: str, cutoff: int = 0) -> Collection[Tuple[str]]:
"""
Run gliph. Note that we copy the fname into the current directory to make
working with GLIP... | b4411f809d12275219fbb24f200b57ff0aef0b7d | 3,610,281 |
import sys
def main_loop(snake_list, cherry_list):
"""
Main loop of the game. This function returns only if snake collision occured.
"""
while True:
# capture events
for event in pygame.event.get():
if event.type == pygame.QUIT:
# happens when user tries to... | 8f99e460b88616c34213e649485c2705bfc5a351 | 3,610,282 |
def __ensure_paragraphs(text):
""" Checks if paragraph break in text else adds it and returns """
if "\n\n" in text:
# Paragraph break detected just return it
return text
# If not detected add it ourselves
new_text = "\n\n".join(__cut_text(text, length=500))
return new_text | 5b79021021c4a89bc12901ac12c29257e16d3409 | 3,610,283 |
def main(path, task, representation):
"""
:param path: str specifying path to dataset.
:param task: str specifying the task. Always e_iso_pi in the case of the human performance comparison
:param representation: str specifying the molecular representation. One of ['fingerprints, 'fragments', 'fragprints... | 732f96bc4697ce11f3665584799c608b8c0096ae | 3,610,284 |
from typing import Any
def vectorized_loss_and_aux(task_family: tasks_base.TaskFamily,
learned_opt: lopt_base.LearnedOptimizer,
theta: lopt_base.MetaParams, inner_opt_state: Any,
task_param: Any, key: PRNGKey,
... | 760366cc22a5b3c962f3598cc707771d284f3d66 | 3,610,285 |
def region_of_interest(img, vertices):
"""
区域选择
Only keeps the region of the image defined by the polygon
formed from `vertices`. The rest of the image is set to black.
"""
# defining a blank mask to start with
mask = np.zeros_like(img)
# defining a 3 channel or 1 channel color to fill... | a0b3741b135a9a9c2356b6b63061ee784c0a6b98 | 3,610,286 |
def segformer_b5(pretrained=False, progress=True, num_classes=150):
"""Create a SegFormer-B5 model.
Args:
pretrained: Download backbone weights pretrained on ImageNet data if true.
progress: Display the download progress of pretrained weights if true.
num_classes: Number of output class... | 39bc9c36fd26a49856848d8ba08076a0a9205334 | 3,610,287 |
def expand_codes(df=None,
codes=None,
cols=None,
sep=None,
codebook=None,
hyphen=True,
star=True,
colon=True,
regex=None,
del_dot=False,
case_sensitiv... | e2e6132cf94a6b19c9d6294c36ffc8fa412401a0 | 3,610,288 |
import math
def compute_roce(fpr, preds, real):
"""
Calculate the ROC enrichment (ROCE) score - i.e., the y value divided by
the x value on an ROC curve, at a fixed predetermined x value (i.e.
a fixed false positive rate).
Args:
fpr (float): pre-set false positive rate
preds (np.ar... | 89190c89b4faa0d2025da578b06ba94906e7bfe8 | 3,610,289 |
import os
def create_local_path(*relative_path, cache=LOCAL_CACHE) -> str:
"""
Create path in local OS - if not exist, create make directory to the root
:param relative_path: path relative to 'base_path'
:param cache: initial part of local path to be be joined with
:return: a full path in local ... | cb25184dd6911d1e88a168eefc4a2b75a4bf17d7 | 3,610,290 |
def segmentPlaneIntersection(s0 = "const Dim<3>::Vector&",
s1 = "const Dim<3>::Vector&",
point = "const Dim<3>::Vector&",
normal = "const Dim<3>::Vector&",
tol = ("const double", "1.0e-8")):
"""Inters... | eb68974937de575702069565fc3ee34dfadf89cc | 3,610,291 |
def subplots(nrows=1, ncols=1, figsize=None, xlabel=None, ylabel=None):
"""
Creates subplots from matplotlib.
Args:
nrows (int):
ncols (int):
figsize (tuple[int, int]):
xlabel (str):
ylabel (str):
Returns:
fig (matplotlib.figure.Figure): the matplotlib f... | fa78a962364dc3cb7f9807e42a9c458a17e75f42 | 3,610,292 |
def get_host_data(root):
"""Traverses the xml tree and build lists of scan information
and returns a list of lists.
"""
host_data = []
hosts = root.findall('host')
for host in hosts:
addr_info = []
# Ignore hosts that are not 'up'
if not host.findall('status')[0].attrib[... | 6f4967da12edd496df613b210083745c5c137578 | 3,610,293 |
import concurrent
def with_progress_bar(target):
"""
Adapted from ipywidgets progress bar example
:param target: Function to run. Function must take progress bar as argument.
:return: None
Try it out with::
a = []
def work(progress):
total = 3
for i in ran... | 0d814c035363c14cff98de798781129b42a2858a | 3,610,294 |
def incident_beam(*, source_chopper: sc.Variable,
sample_position: sc.Variable) -> sc.Variable:
"""
Compute the incident beam vector from the source chopper position vector,
instead of the source_position vector.
"""
return sample_position - source_chopper.value['position'].data | 2f6b5502e336ed02b4c733808bb446f5e0310689 | 3,610,295 |
import math
def arrhenius (A: float, E: float, T: float, R: float = R) -> float:
"""
Args:
A: Pre-exponential (frequency) factor.
ValueError raised if not > 0.
E: Activation energy.
T: Temperature in Kelvins.
ValueError raised if not >= 0.
R: Universal g... | 8f5d43bb659070fed34274db36fb9e5ec79343d1 | 3,610,296 |
def xoai_contributor(source, *args, **kwargs):
"""
CZ:
EN:
"""
value = []
for person_role in source:
role = person_role["@name"]
field = person_role["element"]["field"]
if isinstance(field, list):
for person in field:
value.append(
... | a17ab90aee1326c66cdc546b726666b86039cc3f | 3,610,297 |
def http_endpoint(
flask_entity,
flask_rule,
method: HttpMethod = HttpMethod.GET,
returns_json_response: bool = True,
):
"""
Decorator factory used to easily register a Transiter HTTP endpoint.
:param flask_entity: either the Flask app or a Flask blueprint
:param flask_rule: the URL rel... | a33c4a24466ce8ebaa96e243714ae045ce1f22fa | 3,610,298 |
from typing import Any
from typing import List
import torch
def all_gather_cuda(data: Any) -> List[bytes]:
"""
Run all_gather on arbitrary picklable data (not necessarily tensors)
Args:
data: any picklable object
Returns:
list[data]: list of data gathered from each rank
"""
world_size = global_world_size()
... | 763c64ee2f5efe129be1a292acb81461ba395bf5 | 3,610,299 |
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