content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import warnings
def _url_from_string(url):
"""
Generate actual tile url from tile provider definition or template url.
"""
if "tileX" in url and "tileY" in url:
warnings.warn(
"The url format using 'tileX', 'tileY', 'tileZ' as placeholders "
"is deprecated. Please use '... | f3d4393163e48a7949f3229c55ea8951411dcd63 | 3,639,400 |
import socket
def get_reverse_dns(ip_address: str) -> str:
"""Does a reverse DNS lookup and returns the first IP"""
try:
rev = socket.gethostbyaddr(ip_address)
if rev:
return rev[0]
return "" # noqa
except (socket.herror, socket.gaierror, TypeError, IndexError):
... | 58a27e25f7a9b11ab7dcddebeea743b7864f80f1 | 3,639,401 |
def abs_path(file_path):
"""
Returns the absolute path from the file that calls this function to file_path. Needed to access other files within aide_gui when initialized by aide.
Parameters
----------
file_path: String
The relative file path from the file that calls this function.
"""
... | 63e4a4b0c8fafb5920c78310fda90b119fd18104 | 3,639,402 |
def function(x: np.ndarray) -> float:
"""The ellipse function is x0^2 + 2 * x1^2 + 3 * x2^2 + ..."""
return np.linalg.norm(np.sqrt(np.arange(1, 1 + len(x))) * x) ** 2 | efe468177ff232d45d18385fa2744a9cf63739eb | 3,639,403 |
def replace_with_encoded_bits(one_hot_matrix, enum_val, add_value, last_col_index):
"""
Generate encoded bits for a categorical data value using one hot encoding.
:param one_hot_matrix: matrix representing the encoding of categorical data value to 1-hot encoding
:param enum_val: categorical data value,... | d5ee111d74071fdbaa3890b35a193aa9e24df745 | 3,639,404 |
def cosine_similarity(n_co_elements, n_first_element, n_second_element):
"""
Description
A function which returns the cosine similarity between two elements.
Arguments
:param n_co_elements: Number of co-elements.
:type n_co_elements: int
:param n_first_element: Size of the f... | ea35e47ecf3e77a95d535b0421afbe5f3a679817 | 3,639,405 |
def AddForwardEulerDynamicsConstraint(mp, A, B, x, u, xnext, dt):
"""
Add a dynamics constraint to the given Drake mathematical program mp, represinting
the euler dynamics:
xnext = x + (A*x + B*u)*dt,
where x, u, and xnext are symbolic variables.
"""
n = A.shape[0]
Aeq = np.hstack(... | e0070aa28b61833330706e3934cbfaa8eb1c1d1b | 3,639,406 |
import json
async def light_pure_rgb_msg_fixture(hass):
"""Return a mock MQTT msg with a pure rgb light actuator message."""
light_json = json.loads(
await hass.async_add_executor_job(load_fixture, "ozw/light_pure_rgb.json")
)
message = MQTTMessage(topic=light_json["topic"], payload=light_json... | 93156674ece713d6c9371f64840852a3d5d292b5 | 3,639,407 |
import csv
def make_header_names_thesaurus(header_names_thesaurus_file=HEADER_NAMES_THESAURUS_FILE):
"""
Get a dict mapping ideal domain-specific phrases to list of alternates.
Parameters
----------
header_names_thesaurus_file : str
Filepath.
Returns
-------
Dict of {'ideal phrase': ['alt_phrase0', 'alt_p... | 20f89be5dfbdf0feac5facddcaeeddb346d394a8 | 3,639,408 |
def split_train_valid_test(adata_here,
training_proportion=0.6,
validation_proportion=0.2,
test_proportion=0.2,
rng=None,copy_adata=False):
"""Split cells into training, validation and test
"""
... | ccff7c2b1372b74429bb6acb04df1dd66ad5c113 | 3,639,409 |
def get_stock_ledger_entries(previous_sle, operator=None,
order="desc", limit=None, for_update=False, debug=False, check_serial_no=True):
"""get stock ledger entries filtered by specific posting datetime conditions"""
conditions = " and timestamp(posting_date, posting_time) {0} timestamp(%(posting_date)s, %... | a25b1df6b692975c94f335e40d342617c3a95086 | 3,639,410 |
def index(request):
""" Main index. Editor view. """
# Render editor
body = render_to_string('editor.html', {})
data = {
'body': body
}
# Render page layout
return render(request, 'index.html', data) | bab60def7716ae11d328a95274d2ee7b6305dbaf | 3,639,411 |
def isUsdExt(ext):
""" Check if the given extension is an expected USD file extension.
:Parameters:
ext : `str`
:Returns:
If the file extension is a valid USD extension
:Rtype:
`bool`
"""
return ext.lstrip('.') in USD_EXTS | 5c2f7a48869c9ab4a94b4d8a84e892b76938e91a | 3,639,412 |
def _get_dflt_lexicon(a_pos, a_neg):
"""Generate default lexicon by putting in it terms from seed set.
@param a_pos - set of positive terms
@param a_neg - set of negative terms
@return list(3-tuple) - list of seed set terms with uniform scores and
polarities
"""
return [(w, POSITIVE, 1.... | b06a1f81629368447227a846ac3216220beaa77b | 3,639,413 |
import os
def process_dst_overwrite_args(src,
dst=None,
overwrite=True,
src_to_dst_func=None):
"""
Check when overwrite is not allowed, whether the destination exists.
"""
src = os.path.abspath(src)
if ds... | 201726c93ce918ff7bcf4d66cd0181ed62d1b061 | 3,639,414 |
def rct(target_t : Tensor, source_t : Tensor, target_mask_t : Tensor = None, source_mask_t : Tensor = None, mask_cutoff = 0.5) -> Tensor:
"""
Transfer color using rct method.
arguments
target_t Tensor( [N]CHW ) C==3 (BGR) float16|32
source_t Tensor( [N]CHW ) C==3 (BGR) float16|32
... | 87f350c3e8cef10ef2e3bc883457acf861ab064c | 3,639,415 |
def random_policy(num_actions):
"""
Returns a policy where all actions have equal probabilities, i.e., an uniform distribution.
"""
return np.zeros((num_actions,)) + 1 / num_actions | 9a95865cf3bc7634bc4bf033f343b5811ba40c9f | 3,639,416 |
def find_object(func, name, *args, **kwargs):
"""Locate an object by name or identifier
This function will use the `name` argumetn to attempt to
locate an object. It will first attempt to find the
object by identifier and if that fails, it will attempt
to find the object by name.
Since object... | 6ee8085d42883798c1f3ab5d0a7711af26b2b614 | 3,639,417 |
import os
def mkdir(path):
""" Make a directory, if the parent directory exists. """
path = abspath(path, fse.get_working().get_full_path())
parent_path, d = os.path.split(path)
parent = fse.find_dir(parent_path)
if parent:
entry = fse.create(name=d, parent=parent, depth=parent.depth+1, is_directory=True)
... | 6306e9fe3645b7db8cb478361186626fc294e4d5 | 3,639,418 |
import os
def _get_cognitive_services_client() -> ImageSearchClient:
"""Get the cognitive service client to run the searches against.
Ensure there is a COGNITIVE_KEY and COGNITIVE_ENDPOINT configured in your
app setting for the function, or your local.settings.json file when running
locally.
Ret... | f52a8a85a60401a5da2b7388fbd295954a54602a | 3,639,419 |
import os
def getZeroPadding(path):
"""Get original zero padding, so can be re-added."""
files = listVisibleFiles(path)
zero_padding = len(getNumSubString(os.path.splitext(files[0])[0]))
return zero_padding | 19b044027d4309c6b3977333958801802f287650 | 3,639,420 |
import logging
def weld_segments(gdf_line_net, gdf_line_gen, gdf_line_houses,
debug_plotting=False):
"""Weld continuous line segments together and cut loose ends.
This is a public function that recursively calls the internal function
weld_line_segments_(), until the problem cannot be si... | 913f5432fddaaf592ce8a4fa4a4a813fcd26c868 | 3,639,421 |
def CreateHSpline(points, multiple=False):
"""
Construct an H-spline from a sequence of interpolation points
Args:
points (IEnumerable<Point3d>): Points to interpolate
"""
url = "rhino/geometry/nurbscurve/createhspline-point3darray"
if multiple: url += "?multiple=true"
args = [point... | b5f7b2000dcce04a60087ab32956fa4701d1dadc | 3,639,422 |
def get_instance_embedding_loss(embedding,
instance_loss_type,
instance_labels,
crop_area,
crop_min_height,
num_samples=10,
simi... | ff1e08ea60f4c937fd44bec967eda37d6916ef00 | 3,639,423 |
def str_to_array(value):
"""
Check if value can be parsed to a tuple or and array.
Because Spark can handle tuples we will try to transform tuples to arrays
:param value:
:return:
"""
try:
if isinstance(literal_eval((value.encode('ascii', 'ignore')).decode("utf-8")), (list, tuple)):
... | d565021781a3c2c19c882073ddc6cbd24334b74a | 3,639,424 |
import inspect
def get_current_func_name():
"""for python version greater than equal to 2.7"""
return inspect.stack()[1][3] | 002d318bcab98639cab6c38317322f247a1ad0e0 | 3,639,425 |
def getParmNames(parmsDef):
"""Return a list of parm names in a model parm definition
parmsDef: list of tuples, each tuple is a list of parms and a time
constraint. Call with modelDict[modelname]['Parms].
Returns: List of string parameter names
Here's an example of how to remove unused parms f... | 785661200c388f23c5f38ae67e773a43fd8f57b3 | 3,639,426 |
def dict_merge(lft, rgt):
"""
Recursive dict merge.
Recursively merges dict's. not just simple lft['key'] = rgt['key'], if
both lft and rgt have a key who's value is a dict then dict_merge is
called on both values and the result stored in the returned dictionary.
"""
if not isinstance(rgt, ... | c939fed14ff10452663bc5a32247b21f6170897a | 3,639,427 |
def modified_zscore(x: np.ndarray) -> np.ndarray:
"""
Modified z-score transformation.
The modified z score might be more robust than the standard z-score because
it relies on the median for calculating the z-score. It is less influenced
by outliers when compared to the standard z-score.
Param... | 8f0933bf30ec55ba6305c9bd926437bb0715a938 | 3,639,428 |
def update_profile(email, username, name, bio, interest, picture=None):
"""更新 profile"""
db = get_db()
cursor = db.cursor()
# query user
user = get_user_by_email(email)
email = user['email']
profile_id = user['profile_id']
if profile_id is None:
# add profile
cursor.exe... | 0b13d81f9d36198d4660179eae7616d8f25ee37e | 3,639,429 |
import zlib
import marshal
def serialize(object):
"""
Serialize the data into bytes using marshal and zlib
Args:
object: a value
Returns:
Returns a bytes object containing compressed with zlib data.
"""
return zlib.compress(marshal.dumps(object, 2)) | 650cbc8937df5eae79960f744b69b8b12b623195 | 3,639,430 |
def logo_if(interp, expr, block, elseBlock=None):
"""
IF tf instructionlist
(IF tf instructionlist1 instructionlist2)
command. If the first input has the value TRUE, then IF runs
the second input. If the first input has the value FALSE, then
IF does nothing. (If given a third input, IF acts ... | 94f143f59fa02f059469f8f17a3ff11093110c84 | 3,639,431 |
import itertools
def select_model_general(
df,
grid_search,
target_col_name,
frequency,
partition_columns=None,
parallel_over_columns=None,
executor=None,
include_rules=None,
exclude_rules=None,
country_code_column=None,
output_path="",
persist_cv_results=False,
per... | 1c286b8cf922a50c1c1071aa0d0506b0cf102a6b | 3,639,432 |
def create_arma_sample(ar_order=1, ma_order=1, size=100):
"""Get a random ARMA sample.
Parameters
----------
ar_order, ma_order, size : int
Values for the desired AR order, MA order and sample size.
Returns
-------
An ARMA sample as a pandas Series.
"""
ar_coeff = np.linspa... | e859413cee0a20e51fc80aeffbb75b3ada83f010 | 3,639,433 |
def get_img(file_path, gray=False):
"""
获取输入图片
:param file_path: 图片文件位置
:param gray: 是否转换为灰度图
:return: img
"""
try:
img = Image.open(file_path)
if gray:
img = img.convert('L')
return img
except Exception:
print("不支持的图片格式")
return None | ac3ad78a1ce877905f550ebc43b7e9a6335fd762 | 3,639,434 |
from datetime import datetime
def working_days(days: int):
"""Return a list of N workingdays
Keyword arguments:
days -- days past
"""
dates = []
today = datetime.utcnow()
for i in range(days):
day = today - timedelta(days=i)
day = day.date()
dates.append(day)
... | 222002b53bcf536f7b31993a22424446fcce24cc | 3,639,435 |
def GetFile(message=None, title=None, directory=None, fileName=None,
allowsMultipleSelection=False, fileTypes=None):
"""
An get file dialog.
Optionally a `message`, `title`, `directory`, `fileName` and
`allowsMultipleSelection` can be provided.
::
from fontParts.ui import GetFi... | b81ba1e11764231c8c04164316e4ee55b0305044 | 3,639,436 |
def str_to_dtype(s):
"""Convert dtype string to numpy dtype."""
return eval('np.' + s) | e0ff793404af5a8022d260fde5878329abbac483 | 3,639,437 |
from typing import Callable
from typing import Tuple
def integrate_const(
f: Callable,
t_span: Tuple,
dt: float,
y0: np.ndarray,
method: str = 'runge_kutta4'
) -> Tuple[np.ndarray, np.ndarray]:
"""
A Python wrapper for Boost::odeint runge_kutta4 (the only one supported right now)
stepp... | e43479c829fd46e0f4cdd8c7918294577e91beed | 3,639,438 |
def cleanup(serialized):
"""
Remove all missing values. Sometimes its useful for object methods
to return missing value in order to not include that value in the
json format.
Examples::
>>> User(Serializable):
... def attributes():
... return ['id', 'name', 'bir... | 5e4bfd13408ec8272c4fc4e9a499349e13dd2798 | 3,639,439 |
from typing import Optional
from typing import List
async def discover_devices(
wave_devices: Optional[List[WaveDevice]] = None,
) -> List[WaveDevice]:
"""Discovers all valid, accessible Airthings Wave devices."""
wave_devices = wave_devices if isinstance(wave_devices, list) else []
device: BLEDevice... | 31b5a43b1be765ca4d67080f5a04d16477615fa6 | 3,639,440 |
import os
import pickle
def convert_examples_to_feats_lstm(examples, max_seq_length, glove_vocab, feat_file, language):
"""Loads a data file into a list of `InputBatch`s in glove+lstm manner"""
print("#examples", len(examples))
if os.path.exists(feat_file):
with open(feat_file, 'rb') as f:
... | 734fbac9f0e2f1b203424f5b495ceb3ba056c3ab | 3,639,441 |
import json
def PyValueToMessage(message_type, value):
"""Convert the given python value to a message of type message_type."""
return JsonToMessage(message_type, json.dumps(value)) | 576237ebbacb85ac4c51be8b5523f4f95cfcc019 | 3,639,442 |
from typing import Any
from typing import get_origin
def istype(obj: Any, annotation: type) -> bool:
"""Check if object is consistent with the annotation"""
if get_origin(annotation) is None:
if annotation is None:
return obj is None
return isinstance(obj, annotation)
else:
... | c1903ea2ec6c0b6b9006a38f7c0720c88987b706 | 3,639,443 |
import logging
import platform
def test_cand_gen(caplog):
"""Test extracting candidates from mentions from documents."""
caplog.set_level(logging.INFO)
if platform == "darwin":
logger.info("Using single core.")
PARALLEL = 1
else:
logger.info("Using two cores.")
PARALLE... | 44cf505a7eedef55e6322eafebfb92ad3b882697 | 3,639,444 |
def spending_from_savings(take_home_pay: float, savings: float) -> Decimal:
"""
Calculate your spending based on your take home pay and how much
you save. This is useful if you use what Paula Pant calls the anti-budget,
instead of tracking your spending in detail. This number can be used as
input fo... | da26cae052bd27efb11893440353d53e8b6aed89 | 3,639,445 |
import sys
def stdlib_public_names(module: str, *, version: str = None) -> set[str]:
"""
Return a set of public names of a stdlib module, in specific Python version.
If no version is given, default to the current version.
The `version` parameter takes argument of the form `3.9`, `4.7`, etc.
"""
... | 4a16226a58c58ef66ef4f439160cab72b4902ad0 | 3,639,446 |
def large_asymmetric_bulge(data):
"""
:param data: image data as array
:return: the width and location of the largest asymmetric bulge (if any) in the sequence
"""
# retrieve the lengths of the bars in the sequences (the counts) from the palindrome function
score, upper_half_counts, lower_half_c... | be7aef1cc6a2443de3ecff5099d6e28554544f7a | 3,639,447 |
import requests
def request(host, path, bearer_token, url_params):
"""Given a bearer token, send a GET request to the API.
Args:
host (str): The domain host of the API.
path (str): The path of the API after the domain.
bearer_token (str): OAuth bearer token, obtained using client_id an... | 8f322307bfc1cf48ff5e1a7e52df18e5c9dc7ddf | 3,639,448 |
def find_unique_distances(distance_ij: pd.Series) -> np.ndarray:
"""Finds the unique distances that define the neighbor groups.
:param distance_ij: A pandas ``Series`` of pairwise neighbor distances.
:return: An array of unique neighbor distances.
"""
unique_floats: np.ndarray = np.sort(distance_ij... | ca4d8252c4b79bd536a10a058ca5f75b9f39416e | 3,639,449 |
from typing import Dict
from typing import Any
def session(monkeypatch: pytest.MonkeyPatch) -> nox.Session:
"""Fixture for a Nox session."""
registry: Dict[str, Any] = {}
monkeypatch.setattr("nox.registry._REGISTRY", registry)
@nox.session(venv_backend="none")
def test(session: nox.Session) -> No... | 646403d4383c6e426d736bf55278e001db2a40e1 | 3,639,450 |
import yaml
def _load_yaml_with_clear_tag(stream):
"""Like yaml.safe_load(), but everything with a !clear tag before it
will be wrapped in ClearedValue()."""
loader = yaml.SafeLoader(stream)
loader.add_constructor('!clear', _cleared_value_constructor)
try:
return loader.get_single_data()
... | dec04cec96fae797250d1fb37491755ceaea399c | 3,639,451 |
def highlights(state_importance_df, exec_traces, budget, context_length, minimum_gap=0,
overlay_limit=0):
"""generate highlights summary"""
sorted_df = state_importance_df.sort_values(['importance'], ascending=False)
summary_states, summary_traces, state_trajectories = [], [], {}
seen_in... | 50c1dddaad88fa697f850380b215c2fb9e5f1a13 | 3,639,452 |
def draw_figure(canvas, figure, loc=(0, 0)):
"""
Draw a matplotlib figure onto a Tk grafica
loc: location of top-left corner of figure on grafica in pixels.
Inspired by matplotlib source: lib/matplotlib/backends/backend_tkagg.py
"""
figure_canvas_agg = FigureCanvasAgg(figure)
figure_canvas... | 02e4bc4a6cd475c63239170c0dae0648199c46b5 | 3,639,453 |
def find_struct(lines):
"""Finds structures in output data"""
struct = ''
name1 = ''
name2 = ''
seq1 = ''
seq2 = ''
result = []
for line in lines:
if line.startswith('; ========'):
break
if line.startswith('; ALIGNING'):
line = line.split()
... | b7f7e5c70fe0b1111f33e43a40bb9fdde4182b68 | 3,639,454 |
from typing import Callable
def chain(*fs: Callable) -> Callable:
"""
Compose given functions in reversed order.
Given functions f, g, the result of chain is chain(f, g) = g o f.
>>> def f(x: int) -> int:
... return x + 1
>>> def g(x: int) -> str:
... return str(x)
>>> chai... | 4956a955a760d5243988f8fc6fdb0303e3351704 | 3,639,455 |
def astra_fp_2d_fan(volume, angles, source_object, object_det):
"""
:param volume:
:param angles: degrees
:return:
"""
detector_size = volume.shape[1]
proj_geom = build_proj_geometry_fan_2d(detector_size, angles, source_object, object_det)
rec = astra_fp_2d(volume, proj_geom)
return... | 5114730387bd43585bb56a16e5e930491aa87fd2 | 3,639,456 |
from typing import Mapping
def get_remappings_prefix() -> Mapping[str, str]:
"""Get the remappings for xrefs based on the prefix.
.. note:: Doesn't take into account the semicolon `:`
"""
return _get_curated_registry()['remappings']['prefix'] | 02cb1bb1cfa4ffb177327442c6fb63c4fc3fa320 | 3,639,457 |
import json
def generate_schema():
""" schema generation from today filename dataset """
today = date.today().strftime("%d_%m_%Y")
complete_dataset = pd.read_csv(f"complete_dataset_{today}.csv")
json_schema = pd.io.json.build_table_schema(complete_dataset)
with open("json_schema_for_big_query.json... | 67dca17ddfae8f3530e8ced2a730c28657fa77ca | 3,639,458 |
def binary_truncated_sprt_with_llrs(llrs, labels, alpha, beta, order_sprt):
""" Used in run_truncated_sprt_with_llrs .
Args:
llrs: A Tensor with shape (batch, duration). LLRs (or scores) of all frames.
labels: A Tensor with shape (batch,).
alpha : A float.
beta: A float.
... | 4d4f67d1ad9407df1cf8bfdc0e4c5cf775fcc57b | 3,639,459 |
import time
def backoff(action, condition, max_attempts=40):
"""
Calls result = action() up to max_attempts times until condition(result) becomes true, with 30 s backoff. Returns a bool flag indicating whether condition(result) was met.
"""
timeout = 30
for attempt in range(max_attempts):
result = acti... | 93fe5ff9ee672073eb9eb4792572e41d4b4c3faa | 3,639,460 |
def get_file_info(repo, path):
"""we need change_count, last_change, nbr_committers."""
committers = []
last_change = None
nbr_changes = 0
for commit in repo.iter_commits(paths=path):
#print(dir(commit))
committers.append(commit.committer)
last_change = commit.committed_date... | 6ff99df399d35b79d0e2a5635b1e76e1f65fe0bd | 3,639,461 |
import requests
import urllib3
def retryable_session(session: requests.Session, retries: int = 8) -> requests.Session:
"""
Session with requests to allow for re-attempts at downloading missing data
:param session: Session to download with
:param retries: How many retries to attempt
:return: Sessio... | a57d2021077997ab14576df35b4e5ad9d281575e | 3,639,462 |
def apply_affine(x, y, z, affine):
""" Apply the affine matrix to the given coordinate.
Parameters
----------
x: number or ndarray
The x coordinates
y: number or ndarray
The y coordinates
z: number or ndarray
The z coordinates
affi... | b940c98da65a61cd46d2ad85ec33c791619341a0 | 3,639,463 |
from scipy.ndimage import binary_dilation
def binary_dilation_circle(input, radius):
"""Dilate with disk of given radius.
Parameters
----------
input : array_like
Input array
radius : float
Dilation radius (pix)
Returns
-------
TODO
"""
structure = binary_disk... | c769b3aa652dc960cdd62dd19524d12f20e8b2bc | 3,639,464 |
def square_valid(board: Board, n: int, pawn_value: int, x: int, y: int) -> bool:
"""Check if the square at x and y is available to put a pawn on it."""
return (coordinates_within_board(n, x, y) and
square_playable(board, pawn_value, x, y)) | 725f65e64a8570e7483f103f0bf669cef3d7f1ef | 3,639,465 |
def epb2jd(epb):
""" Besselian epoch to Julian date.
:param epb: Besselian epoch.
:type epb: float
:returns: a tuple of two items:
* MJD zero-point, always 2400000.5 (float)
* modified Julian date (float).
.. seealso:: |MANUAL| page 76
"""
djm0 = _ct.c_double()
djm = ... | c5a9bcb422ab34ba0875d152cf8c39dda898e68b | 3,639,466 |
def one_hot_decision_function(y):
"""
Examples
--------
>>> y = [[0.1, 0.4, 0.5],
... [0.8, 0.1, 0.1],
... [0.2, 0.2, 0.6],
... [0.3, 0.4, 0.3]]
>>> one_hot_decision_function(y)
array([[ 0., 0., 1.],
[ 1., 0., 0.],
[ 0., 0., 1.],
... | a6eecff684ab926a46d746ca9c18e6b098308286 | 3,639,467 |
def combine_incomes(toshl_income, excel_income):
"""
Combines two data sources of incomes: toshl incomes and incomes from cashflow excel.
:param toshl_income: Preprocessed dataframe of toshl incomes (after cleaning and splitting)
:param excel_income: Raw excel income data
:return: Total income data
... | 31efb2d7b7420f3c71fcb12876cdc09d7ff748ec | 3,639,468 |
def generate_k(data_set, k):
"""
Given `data_set`, which is an array of arrays,
find the minimum and maximum for each coordinate, a range.
Generate `k` random points between the ranges.
Return an array of the random points within the ranges.
"""
centers = []
dimensions = len(data_set[0])
min_max = defaultdict(... | 1fd4eb6a825a0ca2b8e6b8200081ecfded351c7d | 3,639,469 |
import requests
def __ping_url(url: str) -> bool:
"""Check a link for rotting."""
try:
r = requests.head(url)
return r.status_code in (
requests.codes.ok,
requests.codes.created,
requests.codes.no_content,
requests.codes.not_modified,
)
... | e680cec006127bbe889dcab0291be3149f30d10e | 3,639,470 |
def get_all_list_data():
"""
Handles the GET request to '/get-all-list-data'.
:return: Json with all list data
"""
conn = get_db()
all_types = TypeDataAccess(conn).get_types(False)
all_tags = TagDataAccess(conn).get_tags()
all_groups = ResearchGroupDataAccess(conn).get_research_groups(F... | 4a4a942e054d301f936ae7993b04aff6c554f91c | 3,639,471 |
def truncate_range(data, percMin=0.25, percMax=99.75, discard_zeros=True):
"""Truncate too low and too high values.
Parameters
----------
data : np.ndarray
Image to be truncated.
percMin : float
Percentile minimum.
percMax : float
Percentile maximum.
discard_zeros : ... | c9f56e593255ae6261b6f709b725cc952accc884 | 3,639,472 |
def obtain_dcdb_to_drugbank(biana_cnx, unification_protocol, output_pickle_file):
"""
Obtain a dictionary {dcdb : drugbank}
"""
up_table = return_unification_protocol_table(biana_cnx, unification_protocol)
query = ('''SELECT DC.value, DB.value FROM externalEntityDCDB_drugID DC, {} U1, {} U2, exter... | 02b9d5b6ddb29974d551123e7bb12a7a6aca3ca4 | 3,639,473 |
def duo_username(user):
""" Return the Duo username for user. """
return user.username | 92b2bfd5f6f3027787db493880139a8564597946 | 3,639,474 |
import random
def random_number_list(data=[]):
""" Add random number between 0 and 9 (both inclusive) to a list """
for i in range( 0, list_length ):
# append a random int to the data list
data.append( random.randint(0, 10))
return data | 5a04409a40e1e65216579056f95024269da1fc5a | 3,639,475 |
def _matrix_method_reshape(df: pd.DataFrame) -> pd.DataFrame:
"""
Reshape df for matrix method and deal with missing values.
We first drop columns which contain all missing values, transpose
the dataframe and then fill the remaining missing values with zero,
to deal with missing items in some period... | 64989a6c61d1d891a3190cc1f6a36c98cf562775 | 3,639,476 |
import glob
import os
import csv
def orbitrap(file_path):
"""Import Orbitrap data from XCalibur export. Designed for scan by scan Orbitrap data.
Original export of example data performed by Cech lab @ UNCG. Example data in MS_data external in Cech directory
"""
headers = ["scan", "rt", "mz", "drift", ... | 3d627faac3988451e5dd8287dfe8487c2efc3897 | 3,639,477 |
import warnings
def sim_bursty_oscillator(T, Fs, freq, prob_enter_burst=.1,
prob_leave_burst=.1, cycle_features=None,
return_cycle_df=False):
"""Simulate a band-pass filtered signal with 1/f^2
Input suggestions: f_range=(2,None), Fs=1000, N=1001
Paramet... | ea408f91f6160114f0077bd441ea049f848d2da1 | 3,639,478 |
def visualize_percent_diff(df):
"""Creates a visualization of difference in percentage of tweets of a topic
across the entire US and returns the mean sentiment felt about the
topic across the entire US
Parameters:
-----------
df: pd.DataFrame
dataframe containing all tweets. Must conta... | d3f3404e5695a0191580f3df20eaf4c824d3e436 | 3,639,479 |
import six
import inspect
def basic_compare(first, second, strict=False):
"""
Comparison used for custom match functions,
can do pattern matching, function evaluation or simple equality.
Returns traceback if something goes wrong.
"""
try:
if is_regex(second):
i... | ee16806fd78f46c2bcf01a5263f6d0210c22f32a | 3,639,480 |
def parse_line(line,):
"""Return a list of 2-tuples of the possible atomic valences for a given line from
the APS defining sheet."""
possap = []
for valence, entry in enumerate(line[4:]):
if entry != "*":
possap.append((valence, int(entry)))
return possap | d27ed66cb35084c9927cae8658d7ea8a421c69a4 | 3,639,481 |
def first_order_moments(X, min_words=3):
"""First-Order Moments
Generate first order Moment of document-word frequency matrix.
Parameters
----------
X : array-like or sparse matrix, shape=(n_samples, n_features)
Matrix of Document-word frequency. `n_samples` is the
number of do... | b3105e50a3cf69b3dda62dfc07764ae8539ebc8f | 3,639,482 |
from datetime import datetime
def dashboard():
"""Получить статистику по сайту"""
user = get_user_from_request()
if not user.is_admin:
return errors.no_access()
users = User.select().count()
d = datetime.datetime.now() - datetime.timedelta(days=7)
active_users = User.select().where(... | 05363fd27ee6980258b7ea015a81e644799c5baa | 3,639,483 |
def dct(f, axis=-1):
"""
Compute the Discrete Cosine Transform over the specified axis.
:param f: The input array.
:param axis: Axis along which the DCT is computed. The default is over the last axis.
:return c: The computed DCT.
"""
# Size of the input along the specified axis.
... | 3e6cd65a3088d948fb81f61c25b2f590facb8351 | 3,639,484 |
from pathlib import Path
def get_create_data_dir():
"""Get the data directory.
When the directory does not exist it is created.
"""
# Calculate the dataset data dir
data_dir = Path(get_data_dir()).expanduser()
dataset = _dataset_settings['name']
dataset_dir = data_dir / dataset
# Ens... | 8fd7631504ab7b926f1f6b533d0fdabaa8cad592 | 3,639,485 |
def interpolate_bezier(points, steps=100, **kwargs):
"""Generates an array of waypoints which lie on a 2D Bezier curve described by n (x, y) points. The trajectory is
guaranteed to include the start and end points though only on (x, y, z) axes.
The curve generated is of the nth degree, where n = len(points... | 403d8f6242947bc240920ea15ae6c0d72ec2d547 | 3,639,486 |
def _EAMS(track, Xmin=0.55, i0=12):
"""
Early-Age Main Sequence. Without this, the low-mass tracks do not
reach an EEP past the ZAMS before 15 Gyr.
"""
i_EAMS = _IorT_AMS(track, Xmin, i0)
return i_EAMS | 4cde6c1e598366bbaf25ab98d2ec14b9f5a34d86 | 3,639,487 |
import uuid
def neighboring_pairs(dataset, text_key='text', reuse_sentences=True):
"""Create a dataset consisting of neighboring sentence pairs.
The input examples should have a key text_key associated with a tf.string
value.
The output examples have keys 'first' and 'second'.
We only take sentence pairs... | 815b04be745344e3a527c1eb07d22fd31bfffd94 | 3,639,488 |
def decode(tokenizer, token):
"""decodes the tokens to the answer with a given tokenizer"""
answer_tokens = tokenizer.convert_ids_to_tokens(
token, skip_special_tokens=True)
return tokenizer.convert_tokens_to_string(answer_tokens) | 4bbb58a6a0ed0d33411f9beee35ad0f2fb43698f | 3,639,489 |
def davis_jaccard_measure(fg_mask, gt_mask):
""" Compute region similarity as the Jaccard Index.
:param fg_mask: (ndarray): binary segmentation map.
:param gt_mask: (ndarray): binary annotation map.
:return: jaccard (float): region similarity
"""
gt_mask = gt_mask.astype(np.bool)
fg_mask =... | 96e6c47cd3b8d71206f9cf903b3827840803cf10 | 3,639,490 |
def extract_logits(logits = None, seq_pos = None):
"""
Args
logits: Tensor(batch_size,seq_length,vocab_size) e.g.(8,1024,50257)
seq_pos: list(batch_size)
Return:
output_logits: Tensor(batch_size,1,vocab_size) extract the Specified logit according to the seq_pos list .
"""
... | 008931ca8677461de947d7a365521e1e72c53866 | 3,639,491 |
import subprocess
def CollectSONAME(args):
"""Replaces: readelf -d $sofile | grep SONAME"""
toc = ''
readelf = subprocess.Popen(wrapper_utils.CommandToRun(
[args.readelf, '-d', args.sofile]),
stdout=subprocess.PIPE,
bufsize=-1,
... | dda042430ec1acfb82f6622e0d3786f6be44f2f4 | 3,639,492 |
def padRect(rect, padTop, padBottom, padLeft, padRight, bounds, clipExcess = True):
"""
Pads a rectangle by the specified values on each individual side,
ensuring the padded rectangle falls within the specified bounds.
The input rectangle, bounds, and return value are all a tuple of (x,y,w,h).
"""
# Unpack th... | 032cafd373b59b725b8e2e28ba91e263ccae6e12 | 3,639,493 |
def gcs_csv_to_table(full_table_id: str, remote_csv_path: str) -> Table:
"""
Insert CSV from Google Storage to BigQuery Table.
:param full_table_id: Full ID of a Google BigQuery table.
:type full_table_id: str
:param remote_csv_path: Path to uploaded CSV.
:type remote_csv_path: str
:returns... | bb0713848249e2eb4e6b89db652152c6485af0ee | 3,639,494 |
import argparse
def _get_client(args: argparse.Namespace) -> NodeClient:
"""Returns a pycspr client instance.
"""
return NodeClient(NodeConnectionInfo(
host=args.node_host,
port_sse=args.node_port_sse
)) | 0eff36345d99c50a6d8298021b9f875dd17a2afe | 3,639,495 |
import math
def turn_xyz_into_llh(x,y,z,system):
"""Convert 3D Cartesian x,y,z into Lat, Long and Height
See http://www.ordnancesurvey.co.uk/gps/docs/convertingcoordinates3D.pdf"""
a = abe_values[system][0]
b = abe_values[system][1]
e2 = abe_values[system][2]
p = math.sqrt(x*x + y*y)
long = math.atan(... | 304facd429083032e611f2f9aca09b298a40a48b | 3,639,496 |
def _TileGrad(op, grad):
"""Sum reduces grad along the tiled dimensions."""
input_shape = array_ops.shape(op.inputs[0])
# We interleave multiples and input_shape to get split_shape,
# reshape grad to split_shape, and reduce along all even
# dimensions (the tiled dimensions) to get the result
# with shape in... | 21294667ac3a31082cc2a3d09120330ce3ec1564 | 3,639,497 |
def obj_spatial_error_sum_and_naturalness_jac(s, data):
""" jacobian of error function. It is a combination of analytic solution
for motion primitive model and numerical solution for kinematic error
"""
# Extract relevant parameters from data tuple.
# Note other parameters are used for calli... | e0f57a88e3b490abc8eb9dbc636701c4a06ffc05 | 3,639,498 |
from datetime import datetime
def today():
"""Ritorna il giorno di oggi in formato YYYYMMDD"""
today = datetime.date.today()
return today.strftime("%Y%m%d") | fdf9c83153667fb3324f31893bf3721566dea4d3 | 3,639,499 |
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