content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_all_elems_from_json(search_json: dict, search_key: str) -> list:
"""Returns values by key in all nested dicts.
Args:
search_json: Dictionary in which one needs to find all values by specific key.
search_key: Key for search.
Returns:
List of values stored in nested structure... | 6ab45e33962ccb5996b50d13e57626365c4ed78b | 32,256 |
def prFinalNodeName(q):
"""In : q (state : string)
Out: dot string (string)
Return dot string for generating final state (double circle)
"""
return dot_san_str(q) + '[shape=circle, peripheries=2];' | 8a4e5649ebeb0c68f2e1741fefd935c9a5f919bf | 32,258 |
import typing
from datetime import datetime
def decodeExifDateTime(value: str) -> typing.Optional[datetime.datetime]:
"""
utility fct to encode/decode
"""
try:
# return path.encode(sys.stdout.encoding, 'ignore').decode(sys.stdout.encoding)
d = datetime.datetime.strptime(value, '%Y:%m:%... | a1ce11305e8e486ad643530930368c47f1c073ef | 32,259 |
def parse(file: str) -> Env:
"""Parse an RLE file and create a user environment
Parameters
----------
file: str
Path to the RLE file.
Returns
-------
user_env: `dict` [str, `Any`]
User environment returned from ``user_env()``. It has these attributes:
``width``
... | cf0a884169b22f4781450c78a35b33ef43049d65 | 32,260 |
import six
def logger_has_handlers(logger):
"""
Check if given logger has at least 1 handler associated, return a boolean value.
Since Python 2 doesn't provide Logger.hasHandlers(), we have to perform the lookup by ourself.
"""
if six.PY3:
return logger.hasHandlers()
else:
c =... | dc0093dd25a41c997ca92759ccb9fa17ad265bdd | 32,261 |
import json
def query_parameters(prefix, arpnum, t_recs, keywords, redis=True):
"""Query keyword sequence from a header file.
Alternative design: replace prefix and arpnum with filepath.
"""
KEYWORDS = ['T_REC', 'AREA', 'USFLUXL', 'MEANGBL', 'R_VALUE']
if redis:
id = f'{prefix}{arpnum:06... | 84c0a43d6d045e3255478175697cbb0bfaac5da8 | 32,262 |
def x0_rand(mu3,xb,num_min):
"""
Randomly initialise the 5 protocol parameters using the specified bounds.
Parameters and bounds should be specified in the order {Px,pk1,pk2,mu1,mu2}.
Parameters
----------
mu3 : float
Intensity of pulse 3 (vacuum).
xb : float, array-like
Upp... | fcf32cd7367e7b78e48829f72523f50855ba563e | 32,264 |
def render_smiles_list(smiles_list):
"""
Format and return a SMILES string(s).
"""
# The string that will be returned to the template
result = r'<h3>Solvent SMILES:</h3>' + '\n'
result += r'<p>'
if len(smiles_list) == 1:
result += smiles_list[0]
else:
result += 'This is a... | f6207bb63452d1037c321874b8ed5248e89dc83e | 32,265 |
def get_config_id(kwargs=None, call=None):
"""
Returns a config_id for a given linode.
.. versionadded:: 2015.8.0
name
The name of the Linode for which to get the config_id. Can be used instead
of ``linode_id``.
linode_id
The ID of the Linode for which to get the config_id... | b66eda936157d0c6794289ed90acd681a5d31c02 | 32,266 |
def bunq_oauth_reauthorize():
""" Endpoint to reauthorize OAuth with bunq """
cookie = request.cookies.get('session')
if cookie is None or cookie != util.get_session_cookie():
return render_template("message.html", msgtype="danger", msg=\
"Invalid request: session cookie not set or not v... | 57708acb8e4c726640360bfb1263ede323571c15 | 32,267 |
from typing import List
from typing import Tuple
def extract_mealentries(meals: List[Meal]) -> List[Tuple]:
"""
Extract meal entries records from a sequence of myfitnesspal meals.
Args:
- meals (List[Meal]): A list with meal objects to extract data from
Returns:
- List[Tuple]: A list wit... | c7c043cee0b4af1253902080af67919cc9238d75 | 32,269 |
import math
def get_45point_spiralling_sphere_with_normal_zaxis_dist( num_of_spirals = 4, num_of_vertices = 45):
"""
A sphere of spiralling points. Each point is equally spaced on the x,y,z axes. The equal spacing is calculated by dividing the straight-line spiral distance by 45.
Adapted from Leonsim's co... | 59173bdd28b513d0f039215ea7d713cd80d81b4e | 32,270 |
import re
import json
def parse_results(line):
"""Parses and logs event information from logcat."""
header = re.search(r'cr_PasswordChangeTest: (\[[\w|:| |#]+\])', line).group(1)
print(header)
credentials_count = re.search(r'Number of stored credentials: (\d+).', line)
if not credentials_count:
# Event... | 24cc928d945d2d4f16f394be68a8bb217c21b342 | 32,273 |
def bqwrapper(datai):
"""
Wraps the kdtree ball query for concurrent tree search.
"""
return kdtbq(datai, r=bw[0]) | 203e77e37ddb53b76366b0d376c37b63536da923 | 32,274 |
import re
def crawl_user_movies():
"""
@功能: 补充用户观看过的电影信息
@参数: 无
@返回: 电影信息
"""
user_df = pd.read_csv('douban_users.csv')
user_df = user_df.iloc[:, [1, 2, 3]]
user_movies = list(user_df['movie_id'].unique())
movies = [] # 储存电影
count = 1 # 日志参数
for i in user_movies:
... | 882fe56fc2fc5e22b6ad0ce518b7adaabd724cd2 | 32,275 |
import logging
def filter_by_shape(data: pd.DataFrame, geofence: Polygon) -> pd.DataFrame:
"""Remove trips outside of geofence. Filter by pickup and dropoff locations"""
logging.info('Filtering by bbox')
(min_lon, min_lat, max_lon, max_lat) = geofence.bounds
data = data[
(data.pickup_longitu... | fa98c85ea286921e9a986820a7a17e03e94181dc | 32,276 |
from ..core import cache as cache
def upload_collection(flask_app, filenames, runs, dataset_id, collection_id,
descriptions=None, cache=None):
""" Create new Predictors from TSV files
Args:
filenames list of (str): List of paths to TSVs
runs list of (int): List of run ids... | d6d16206716dae0e7e945d1cff95317454031e3e | 32,277 |
def get_filtered_metadata_list(metadata_list, strand):
""" Given a lis of exon junctions, remove the ones that redundantly cover a junction
Parameters
----------
metadata_list: List(Output_metadata),
strand: strand of the gene
Returns
-------
filtered_meetadata_list: List of metadata o... | dab3da34f435d7401dd5e76be2c9c032aea875c1 | 32,278 |
import functools
import traceback
def handle_exceptions(database, params, constraints, start_params, general_options):
"""Handle exceptions in the criterion function.
This decorator catches any exceptions raised inside the criterion function. If the
exception is a :class:`KeyboardInterrupt` or a :class:`... | 725cfc7d3c338e2a4dbd143fc558307cbb49e1cc | 32,279 |
def vector2angles(gaze_vector: np.ndarray):
"""
Transforms a gaze vector into the angles yaw and elevation/pitch.
:param gaze_vector: 3D unit gaze vector
:return: 2D gaze angles
"""
gaze_angles = np.empty((1, 2), dtype=np.float32)
gaze_angles[0, 0] = np.arctan(-gaze_vector[0]/-gaze_vector[2]... | b0db8e1f6cb9865e9563af5385f760699069013e | 32,280 |
def setup_train_test_idx(X, last_train_time_step, last_time_step, aggregated_timestamp_column='time_step'):
""" The aggregated_time_step_column needs to be a column with integer values, such as year, month or day """
split_timesteps = {}
split_timesteps['train'] = list(range(last_train_time_step + 1))
... | 256fbe66c0b27b651c8190101e5068f7e0542498 | 32,281 |
def get_targets_as_list(key_list):
"""Get everything as list
:param key_list: Target key list
:type key_list: `list`
:return: Values list
:rtype: `list`
"""
session = get_scoped_session()
values = []
for key in key_list:
values.append(get_all_targets(session, key))
retur... | bcd2ed48d685353a59c4545d1277589fa388b4a0 | 32,282 |
import re
def load_jmfd(jmfd_path):
"""Loads j-MFD as Pandas DataFrame.
Args:
jmfd_path (str): Path of J-MFD.
Raises:
JMFDFormatError: J-MFD format error.
Returns:
pandas.DataFrame: Pandas DataFrame of loaded j-MFD with word, existence of stem, foundation
... | 675370c9ce0ed37667ec347dc4a0af57ea5b20b3 | 32,283 |
def objectId(value):
"""objectId校验"""
if value and not ObjectId.is_valid(value):
raise ValueError('This is not valid objectId')
return value | 2e33950649fe95460e82102c1d6209a9173fa5fd | 32,285 |
def add_lists(list1, list2):
"""
Add corresponding values of two lists together. The lists should have the same number of elements.
Parameters
----------
list1: list
the first list to add
list2: list
the second list to add
Return
----------
output: list
... | e4efbc079a981caa4bcbff4452c8845a7e534195 | 32,286 |
def get_struc_first_offset(*args):
"""
get_struc_first_offset(sptr) -> ea_t
Get offset of first member.
@param sptr (C++: const struc_t *)
@return: BADADDR if memqty == 0
"""
return _ida_struct.get_struc_first_offset(*args) | f589dec791c3a81664b81573ea52f02d1c9a6b15 | 32,287 |
def export_gps_route( trip_id, trip_date, vehicle_id,
gtfs_error, offset_seconds,
gps_data ):
"""
Writes the given entry to the "tracked_routes" table. This table is used
to cache the results of finding and filtering only the valid routes as
represented in the GPS da... | fe1a4f4fb2c89c6634353748d5cdd49d82110e64 | 32,288 |
def optimize_solution(solution):
"""
Eliminate moves which have a full rotation (N % 4 = 0)
since full rotations don't have any effects in the cube
also if two consecutive moves are made in the same direction
this moves are mixed in one move
"""
i = 0
while i < len(soluti... | 4be6bf0e4200dbb629c37a9bdae8338ee32c262b | 32,289 |
from typing import Iterable
import resource
from typing import Optional
def secretsmanager_resource(
client: Client,
policies: Iterable[Policy] = None,
):
"""
Create Secrets Manager resource.
Parameters:
• client: Secrets Manager client object
• policies: security policies to apply to all... | ee2d880944065331aba0751bdfba2f82c3d7e2ac | 32,290 |
def lgbm_hyperband_classifier(numeric_features, categoric_features, learning_rate=0.08):
"""
Simple classification pipeline using hyperband to optimize lightgbm hyper-parameters
Parameters
----------
`numeric_features` : The list of numeric features
`categoric_features` : The list of categoric ... | 7c48373d1f40d7248a9d0f6a37c95281027aa1bd | 32,291 |
def GL(mu, wid, x, m = 0.5):
"""
Function to generate a 1D Gaussian-Lorentzian peak. The peak
is centered at pos, is wid wide (FWHM) and with blending parameter m.
Parameters
----------
mu: float
Peak center
wid: float
FWHM of Gaussian peak. FWHM is related to ... | d458eae3ad1ea31dcab021c798e9d7d02fa390ae | 32,292 |
def jp_(var,mask):
"""Value at j+1/2, no gradient across boundary"""
return div0((var*mask + np.roll(var*mask,-1,axis=0)),(mask+np.roll(mask,-1,axis=0))) | cc2aaf2e17bd0cbe3a211b26bc9d976298307f0d | 32,293 |
import re
def _solrize_date(date, date_type=''):
"""
Takes a date string like 2018/01/01 and returns an
integer suitable for querying the date field in a solr document.
"""
solr_date = "*"
if date:
date = date.strip()
start_year, end_year = fulltext_range()
if date_typ... | f309f784d79b46ed704ee1e631d7b4bdda7057f6 | 32,294 |
def read_file(filename):
"""
read filename and return its content
"""
in_fp = open(filename)
content = in_fp.read()
in_fp.close()
return content | c707a412b6099591daec3e70e9e2305fee6511f9 | 32,295 |
def delete_job(job_id):
"""Delete my job by Id
Upon success, marks job as 'aborted' if it must be suspended, and returns the deleted job with the appropriate status # noqa: E501
:param job_id: Id of the job that needs to be deleted
:type job_id: str
:rtype: Job
"""
job = q.fetch... | e8f02faa2a9336c93725739443b9007242b50b5c | 32,297 |
def service(appctx):
"""Service with files instance."""
return RecordService(ServiceWithFilesConfig) | 4902f8eae2c2c4200543a9c594f2abbc5163ec70 | 32,298 |
import json
import re
def get_sci_edus(filepath):
"""
load each sciedu
"""
with open(filepath, 'r') as fb:
train = json.loads(fb.read().encode('utf-8'))['root']
EDUs = []
sentenceNo = 1
sentenceID = 1
for edu_dict in train:
if edu_dict['id'] == 0:
continue
... | 0b8fd37dd8884e9e3f38f4bb671dff2df978f5b2 | 32,299 |
def vec_moderates(vec, minv, maxv, inclusive=1):
"""return a integer array where values inside bounds are 1, else 0
if inclusive, values will also be set if they equal a bound
return error code, new list
success: 0, list
error : 1, None"""
if not vec: return 1, None
i... | 65696ba3d4cb8c43e231a4aae1c8cef83351fb07 | 32,300 |
def SideInfo(version_index, channel_mode, raw_data=None):
"""SideInfo(version_index, channel_mode, raw_data) -> object
Return an object representing MPEG layer 3 side info, based on the given
parameters. The class of the object varies based on the MPEG version and
channel mode (only applicable fields are present, and... | af554b0b6ebc4c33846881b27c02fb648d82b5ca | 32,301 |
def datetimeConvertor(date, month, year, time, timezone):
"""
Converts raw date/time data into an object of datetime class.
"""
Date = date + "/" + monthnumberSwap(month) + "/" + year
Time = time + " " + timezone
return dt.datetime.strptime(Date + " " + Time, "%d/%m/%Y %H:%M:%S %z") | a83e873ee9b9aa1737fffc61c80aa9204305d3fb | 32,302 |
import pathlib
def dump_gone(aspect_store: dict, indent=False) -> bool:
"""Not too dry ..."""
return _dump(aspect_store, pathlib.Path('gone.json'), indent) | 14df4567d0ffc80f9764afa50c725bc1d178e031 | 32,303 |
def loss_fn(params, model, data):
"""
Description:
This is MSE loss function, again pay close attention to
function signature as this is the function which is going to be differentiated, so
params must be in its inputs. we do not need to vectorize this function as it is written
with batching co... | cddd29becee4ce047b086130c7ce8cea114cb914 | 32,304 |
import copy
def lufact(A):
"""
lufact(A)
Compute the LU factorization of square matrix A, returning the factors.
"""
n = A.shape[0]
L = eye(n) # puts ones on diagonal
U = copy(A)
# Gaussian elimination
for j in range(n-1):
for i in range(j+1,n):
L[i,j] = U[i,j] / U[j,j] # row multiplier
U[i,... | e04c20ede47019789e00dc375b84efa931fe2e1f | 32,305 |
def get_city(msg):
""" 提取消息中的地名
"""
# 对消息进行分词和词性标注
words = posseg.lcut(msg)
# 遍历 posseg.lcut 返回的列表
for word in words:
# 每个元素是一个 pair 对象，包含 word 和 flag 两个属性，分别表示词和词性
if word.flag == 'ns':
# ns 词性表示地名
return word.word
return None | 017f910090291fdc77cc22ce4bc3fc3699c2981b | 32,306 |
def get_cycle_time(string):
"""
Extract the cycle time text from the given string. None if not found.
"""
return _search_in_pattern(string, CYCLE_TIME_PATTERN, 1) | 6d41a9f4b04f90b4a5a8d7892398bc080d41e519 | 32,309 |
async def async_unload_entry(hass: HomeAssistant, config_entry: ConfigEntry) -> bool:
"""Unload a config entry."""
unload_ok = await hass.config_entries.async_unload_platforms(
config_entry, PLATFORMS
)
hass.data[DOMAIN].pop(config_entry.entry_id, None)
if not hass.data[DOMAIN]:
has... | 6e4bf924e6e04d03cc30de3a6d4b2f713dd05b32 | 32,310 |
from typing import Union
def get_scale_factor(unit: Union[str, float]) -> float:
"""
Get how many pts are in a unit.
:param unit: A unit accepted by fpdf.FPDF
:return: The number of points in that unit
:raises FPDFException
"""
if isinstance(unit, (int, float)):
return float(unit)
... | c95429436b96f883e5fcfe3b1680a9f35c5f27e3 | 32,312 |
def r2_score(y_true,y_pred):
"""Calculate the coefficient of determination."""
assert len(y_true)==len(y_pred)
rss = sum_square_residuals(y_true,y_pred)
tss = total_sum_squares(y_true)
return 1 - rss/tss | 7d2eba54db3d5682ec0ed22b5c09a65cf1e34e27 | 32,313 |
def give_name(fname):
"""
return name.csv
"""
if fname[:len( AUX_FILE) ] != AUX_FILE: # hide file
# renaming with correct extension
if fname[ -4: ]!= '.csv':
if fname.find('.') > -1:
fname = fname[: fname.find('.')]+'.csv'
else:
fname += '.csv'... | 55f6241b7a57d7611fe2db1731d909bb5b4186ac | 32,314 |
def categorize(document):
"""Categorize a document.
Categorizes a document into the following categories
[business, entertainment, politics, sport, tech].
Takes a string object as input and returns a string object.
"""
doc = clean(document)
vector = doc2vec_model.infer_vector(doc.split(' '... | a085e08e7e8b7ff31e68a536e973b5131540e481 | 32,315 |
def delete_intent(token, aiid, intent_name):
"""Delete an Intent"""
return fetch_api(
'/intent/{aiid}?intent_name={intent_name}',
token=token,
aiid=aiid,
intent_name=intent_name,
method='delete'
) | 198ed90b176c2f08c3c681dfbb5deea52cfbcfa4 | 32,316 |
def report_all(df_select):
"""
report all values to a defined template
"""
if len(df_select) == 0:
report_all = 'No similar events were reported on in online media'
else:
report_all = """
Similar events were reported on in online media.
Below we provide a tabulated s... | d0e5f06416a467d7578f4748725301638b33d1bb | 32,317 |
import urllib
def get_filename_from_headers(response):
"""Extract filename from content-disposition headers if available."""
content_disposition = response.headers.get("content-disposition", None)
if not content_disposition:
return None
entries = content_disposition.split(";")
name_entry... | d4c54c3d19d72f2813e2d1d4afde567d0db0e1af | 32,318 |
def names(as_object=False, p5_connection=None):
"""
Syntax: ArchiveIndex names
Description: Returns the list of names of archive indexes.
Return Values:
-On Success: a list of names. If no archive indexes are configured,
the command returns the string "<empty>"
"""
met... | 1b1d00d70730b79ccab25e5ca101f752ad49cc1c | 32,319 |
def regionvit_base_w14_224(pretrained=False, progress=True, **kwargs):
"""
Constructs the RegionViT-Base-w14-224 model.
.. note::
RegionViT-Base-w14-224 model from `"RegionViT: Regional-to-Local Attention for Vision Transformers" <https://arxiv.org/pdf/2106.02689.pdf>`_.
The required input ... | 63983c4fe9cb5ed74e43e1c40b501f50fbaead56 | 32,320 |
import collections
def create_executor_list(suites):
"""
Looks up what other resmoke suites run the tests specified in the suites
parameter. Returns a dict keyed by suite name / executor, value is tests
to run under that executor.
"""
memberships = collections.defaultdict(list)
test_membe... | c9150b14ba086d9284acb2abdcd4592e7803a432 | 32,321 |
def calculate_great_circle(args):
"""one step of the great circle calculation"""
lon1,lat1,lon2,lat2 = args
radius = 3956.0
x = np.pi/180.0
a,b = (90.0-lat1)*(x),(90.0-lat2)*(x)
theta = (lon2-lon1)*(x)
c = np.arccos((np.cos(a)*np.cos(b)) +
(np.sin(a)*np.sin(b)*np.co... | f0832b984382b2cd2879c40ab1249d68aacddd69 | 32,322 |
def divide(x,y):
"""div x from y"""
return x/y | 74adba33dfd3db2102f80a757024696308928e38 | 32,323 |
def execute(compile_state: CompileState, string: StringResource) -> NullResource:
""" Executes the string at runtime and returns Null"""
compile_state.ir.append(CommandNode(string.static_value))
return NullResource() | 4785d9a527982eb723d120f47af2915b6b830795 | 32,324 |
import torch
def fakeLabels(lth):
"""
lth (int): no of labels required
"""
label=torch.tensor([])
for i in range(lth):
arr=np.zeros(c_dims)
arr[0]=1
np.random.shuffle(arr)
label=torch.cat((label,torch.tensor(arr).float().unsqueeze(0)),dim=0)
return label | a2ffb4a7ff3b71bc789181130bc6042ff184ac9c | 32,325 |
def load_canadian_senators(**kwargs):
"""
A history of Canadian senators in office.::
Size: (933,10)
Example:
Name Abbott, John Joseph Caldwell
Political Affiliation at Appointment Liberal-Conservative
Pro... | 42ae6a455d3bed11275d211646ee6acd2da505b6 | 32,326 |
def _get_md5(filename):
"""Return the MD5 checksum of the passed file"""
data = open(filename, "rb").read()
r = md5(data)
return r.hexdigest() | c86943841a1f8f8e296d82818c668c197f824373 | 32,327 |
def implements(numpy_func_string, func_type):
"""Register an __array_function__/__array_ufunc__ implementation for Quantity
objects.
"""
def decorator(func):
if func_type == "function":
HANDLED_FUNCTIONS[numpy_func_string] = func
elif func_type == "ufunc":
HANDL... | ec0d843798c4c047d98cd9a76bcd862c3d5339e8 | 32,328 |
def r2(data1, data2):
"""Return the r-squared difference between data1 and data2.
Parameters
----------
data1 : 1D array
data2 : 1D array
Returns
-------
output: scalar (float)
difference in the input data
"""
ss_res = 0.0
ss_tot = 0.0
mean = sum(data1) / l... | d42c06a5ad4448e74fcb1f61fa1eed1478f58048 | 32,329 |
from typing import IO
def fio_color_hist_fio(image_fio):
"""Generate a fileIO with the color histogram of an image fileIO
:param image_fio: input image in fileIO format
:type image_fio: fileIO
:return: color histogram of the input image in fileIO format
:rtype: fileIO
"""
image_fio.seek(0... | 13c10cce5dc9bfa17d19a4b2f486fb7b34bcb176 | 32,330 |
def lattice2d_fixed_env():
"""Lattice2DEnv with a fixed sequence"""
seq = 'HHHH'
return Lattice2DEnv(seq) | 664b6b411a47018c460b09909ccb29c033bae2e5 | 32,332 |
import time
import logging
def expected_full(
clr,
view_df=None,
smooth_cis=False,
aggregate_smoothed=False,
smooth_sigma=0.1,
aggregate_trans=False,
expected_column_name="expected",
ignore_diags=2,
clr_weight_name='weight',
chunksize=10_... | 5f387c71f059cd942ff1ff4b6cdb6a59e91ef85b | 32,333 |
def nmgy2abmag(flux, flux_ivar=None):
"""
Conversion from nanomaggies to AB mag as used in the DECALS survey
flux_ivar= Inverse variance oF DECAM_FLUX (1/nanomaggies^2)
"""
lenf = len(flux)
if lenf > 1:
ii = np.where(flux>0)
mag = 99.99 + np.zeros_like(flux)
mag[ii] = 22.... | 5f65a06049955b4ddfe235d6fc12ae5726089b0f | 32,334 |
def rnn_decoder(dec_input, init_state, cell, infer, dnn_hidden_units, num_feat):
"""Decoder for RNN cell.
Given list of LSTM hidden units and list of LSTM dropout output keep
probabilities.
Args:
dec_input: List of tf.float64 current batch size by number of features
matrix tensors input to the decod... | 215691ac8b3191da46d01a17fd37e2be08174640 | 32,335 |
import torch
def l1_loss(pre, gt):
""" L1 loss
"""
return torch.nn.functional.l1_loss(pre, gt) | c552224b3a48f9cde201db9d0b2ee08cd6335861 | 32,336 |
def run_tnscope(align_bams, items, ref_file, assoc_files,
region=None, out_file=None):
"""Call variants with Sentieon's TNscope somatic caller.
"""
if out_file is None:
out_file = "%s-variants.vcf.gz" % utils.splitext_plus(align_bams[0])[0]
if not utils.file_exists(out_file)... | a7e82dc94a9166bde47ad43dab2c778b2f7945d6 | 32,337 |
def get_product(product_id):
"""
Read a single Product
This endpoint will return a product based on it's id
"""
app.logger.info("Request for product with id: %s", product_id)
product = Product.find(product_id)
if not product:
raise NotFound("product with id '{}' was not found.".forma... | e9ee42be5f586aa0bbe08dfa5edefbd3b0bbc5d7 | 32,338 |
import re
import string
def aips_bintable_fortran_fields_to_dtype_conversion(aips_type):
"""Given AIPS fortran format of binary table (BT) fields, returns
corresponding numpy dtype format and shape. Examples:
4J => array of 4 32bit integers,
E(4,32) => two dimensional array with 4 columns and 32 rows.... | 772bd75ff2af92cede5e5dac555662c9d97c544a | 32,339 |
def account_list():
"""获取账户列表"""
rps = {}
rps["status"] = True
account_list = query_account_list(db)
if account_list:
rps["data"] = account_list
else:
rps["status"] = False
rps["data"] = "账户列表为空"
return jsonify(rps) | 3ab704e96cbf2c6548bf39f51a7f8c6f77352b6c | 32,340 |
def sample_points_in_range(min_range, max_range, origin, directions, n_points):
"""Sample uniformly depth planes in a depth range set to [min_range,
max_range]
Arguments
---------
min_range: int, The minimum depth range
max_range: int, The maximum depth range
origin: tensor(shape=(4, 1),... | 6cc33a77e58a573315caf51b907cd881029e7ea1 | 32,341 |
from typing import Counter
def normalize(vectorOrCounter):
"""
normalize a vector or counter by dividing each value by the sum of all values
"""
normalizedCounter = Counter()
if type(vectorOrCounter) == type(normalizedCounter):
counter = vectorOrCounter
total = float(counter.totalC... | 8d4cb0f8be4e7c6eeaba6b49d5a84b024f2c91b9 | 32,342 |
def IsStringInt(string_to_check):
"""Checks whether or not the given string can be converted to an int."""
try:
int(string_to_check)
return True
except ValueError:
return False | 75d83ce78fca205457d4e4325bca80306f248e08 | 32,343 |
import torch
import math
def build_ewc_posterior(data_handlers, mnet, device, config, shared, logger,
writer, num_trained, task_id=None):
"""Build a normal posterior after having trained using EWC.
The posterior is constructed as described in function :func:`test`.
Args:
... | dd04d235a36516ea600eec154f5a8952ee6ea889 | 32,345 |
def get_roc_curve(y_gold_standard,y_predicted):
"""
Computes the Receiver Operating Characteristic.
Keyword arguments:
y_gold_standard -- Expected labels.
y_predicted -- Predicted labels
"""
return roc_curve(y_gold_standard, y_predicted) | b522ee6566004ec97781585be0ed8946e8f2889e | 32,346 |
def get_image_unixtime2(ibs, gid_list):
""" alias for get_image_unixtime_asfloat """
return ibs.get_image_unixtime_asfloat(gid_list) | 2c5fb29359d7a1128fab693d8321d48c8dda782b | 32,347 |
def create_sql_query(mogrify, data_set_id, user_query):
"""
Creates a sql query and a funtion which transforms the output into a list
of dictionaries with correct field names.
>>> from tests.support.test_helpers import mock_mogrify
>>> query, fn = create_sql_query(mock_mogrify, 'some-collection', Q... | ac56dd8b89da7554111f4e285eb9511fbdef5ced | 32,348 |
def patch_hass():
"""
Patch the Hass API and returns a tuple of:
- The patched functions (as Dict)
- A callback to un-patch all functions
"""
class MockInfo:
"""Holds information about a function that will be mocked"""
def __init__(self, object_to_patch, function_name, autospec=F... | 400bb38ca7f00da3b1a28bc1ab5c2408be2931c9 | 32,349 |
def compute_coherence_values(dictionary, corpus, texts, limit, start=2, step=3):
"""
Compute c_v coherence for various number of topics
Parameters:
----------
dictionary : Gensim dictionary
corpus : Gensim corpus
texts : List of input texts
limit : Max num of topics
Returns:
----... | 009f637b7ff1d92514711ca5566f2c2c7ee307b0 | 32,350 |
def parallax_angle(sc, **kw) -> DEG:
"""Compute parallax angle from skycoord.
Parameters
----------
sc: SkyCoord
** warning: check if skycoord frame centered on Earth
Returns
-------
p: deg
parallax angle
"""
return np.arctan(1 * AU / sc.spherical.distance) | 0d84a98cae93828d1166008fe3d654668a4a178e | 32,351 |
def formatting_dates(dates_list):
""" Formatting of both the start and end dates of a historical period.
dates = [period_start_date, period_end_date]"""
new_dates = dates_list
# Change all "BCE" into "BC":
for index1 in range(len(new_dates)):
if " BCE" not in new_dates[index1]:
... | 174617ad0a97c895187f8c1abe7e6eb53f59da6f | 32,352 |
from datetime import datetime
def exp_days_f(cppm_class, current_user):
"""
User's password expiration and check force change password function.
1. Calculates days to expiry password for particular user
2. Checks change password force checkbox.
Returns:
exp_days: Number of days unt... | e0f014fe4813dd70fd733aa2ed2fa4f06105c2f0 | 32,353 |
def isinteger(x):
"""
determine if a string can be converted to an integer
"""
try:
a = int(x)
except ValueError:
return False
except TypeError:
return False
else:
return True | b39530a79c39f0937a42335587f30bed26c6ce0a | 32,354 |
import hashlib
def _get_hash(x):
"""Generate a hash from a string, or dictionary."""
if isinstance(x, dict):
x = tuple(sorted(pair for pair in x.items()))
return hashlib.md5(bytes(repr(x), "utf-8")).hexdigest() | c47f96c1e7bfc5fd9e7952b471516fbf40470799 | 32,357 |
def wrap_arr(arr, wrapLow=-90.0, wrapHigh=90.0):
"""Wrap the values in an array (e.g., angles)."""
rng = wrapHigh - wrapLow
arr = ((arr-wrapLow) % rng) + wrapLow
return arr | e07e8916ec060aa327c9c112a2e5232b9155186b | 32,358 |
def task_fail_slack_alert(context):
"""
Callback task that can be used in DAG to alert of failure task completion
Args:
context (dict): Context variable passed in from Airflow
Returns:
None: Calls the SlackWebhookOperator execute method internally
"""
if ENV != "data":
re... | 392d5f3b1df21d8dbe239e700b7ea0bd1d44c49f | 32,359 |
def largest_negative_number(seq_seq):
"""
Returns the largest NEGATIVE number in the given sequence of
sequences of numbers. Returns None if there are no negative numbers
in the sequence of sequences.
For example, if the given argument is:
[(30, -5, 8, -20),
(100, -2.6, 88, -40, -... | b7326b3101d29fcc0b8f5921eede18a748af71b7 | 32,360 |
def align_quaternion_frames(target_skeleton, frames):
"""align quaternions for blending
src: http://physicsforgames.blogspot.de/2010/02/quaternions.html
"""
ref_frame = None
new_frames = []
for frame in frames:
if ref_frame is None:
ref_frame = frame
else:
... | 7c8d6f4bacfb3581dc023504b94d2fba66c5e875 | 32,361 |
import math
def do_round(precision=0, method='common'):
"""
Round the number to a given precision. The first
parameter specifies the precision (default is ``0``), the
second the rounding method:
- ``'common'`` rounds either up or down
- ``'ceil'`` always rounds up
- ``'floor'`` always rou... | 3e2b4c6c842ca5c3f60951559a815f27cc8edd19 | 32,362 |
import torch
def scale_invariant_signal_distortion_ratio(preds: Tensor, target: Tensor, zero_mean: bool = False) -> Tensor:
"""Calculates Scale-invariant signal-to-distortion ratio (SI-SDR) metric. The SI-SDR value is in general
considered an overall measure of how good a source sound.
Args:
pred... | 2ec9e4d3cbd0046940974f8d7bae32e230da63ed | 32,363 |
import json
from datetime import datetime
def is_token_valid():
"""Check whether the stored token is still valid.
:returns: A bool.
"""
try:
with open('/tmp/tngcli.txt', 'r') as file:
for line in file:
payload = json.loads(line)
except:
return Fal... | 2574245a38a02bdba7b2fee8f5dff807b128316f | 32,364 |
def DB_getQanswer(question):
"""
Calls the function in the database that gets the question answer to the
input question.
"""
return DB.get_question_answer(question) | 8afb32f1e8b39d3ff89b3c9fe02a314099a416ef | 32,365 |
def _state_senate_slide_preview(slug):
"""
Preview a state slide outside of the stack.
"""
context = make_context()
resp = _state_senate_slide(slug)
if resp.status_code == 200:
context['body'] = resp.data
return render_template('slide_preview.html', **context)
else:
... | c9139df85745feca150fd22591e85165969952de | 32,366 |
def tensor_network_tt_einsum(inputs, states, output_size, rank_vals, bias, bias_start=0.0):
# print("Using Einsum Tensor-Train decomposition.")
"""tensor train decomposition for the full tenosr """
num_orders = len(rank_vals)+1#alpha_1 to alpha_{K-1}
num_lags = len(states)
batch_size = tf.shape(in... | b9cabf2e76e3b18d73d53968b4578bedc3d7bb7e | 32,367 |
from .observable.case import case_
from typing import Callable
from typing import Mapping
from typing import Optional
from typing import Union
def case(
mapper: Callable[[], _TKey],
sources: Mapping[_TKey, Observable[_T]],
default_source: Optional[Union[Observable[_T], "Future[_T]"]] = None,
) -> Observab... | 3ecc790a3e6e7e30e4f0a34e06dbfc9e2875388c | 32,368 |
from typing import Tuple
import json
def group_to_stats(request, project_id) -> Tuple:
"""
Combining the same actions for grouping data for chart
"""
filters = json.loads(request.query_params.get('filters', '{}')) # date time, issue type, method
group_by = request.query_params.get('groupBy', 'hou... | 7a27fa180fd0e1bf059d11bd7995cdea0a85c6cf | 32,369 |
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