content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def vectorsToRotMatrix(v1,v2):
"""
Given two points v1 and v2 in 3D space. Suppose furthermore that v2 is generated by v1
multiplied by a rotation matrix over the origin. We will determine this rotation matrix using this method
:rtype: float list
:return: Rotation matrix (unhomegenized) i... | 13a7348f84e69bc3337c0047e38443e839f74e33 | 37,827 |
def missing_impact(df: dd.DataFrame, bins: int) -> Intermediate:
"""
Calculate the data for visualizing the plot_missing(df).
This contains the missing spectrum, missing bar chart and missing heatmap.
"""
cols = df.columns.values
(nulldf,) = dask.persist(df.isnull())
nullity = nulldf.to_dask... | 44869403f21416f16341671e7d870cf4d2d01815 | 37,828 |
def svn_stream_write(stream, data):
"""svn_stream_write(svn_stream_t * stream, char const * data) -> svn_error_t"""
return _core.svn_stream_write(stream, data) | f35015ec517e77699db794ecedc93165bb5a0154 | 37,829 |
def build_word_dict(args, examples):
"""Return a dictionary from sentence words in
provided examples.
"""
word_dict = Dictionary()
for w in load_words(args, examples):
word_dict.add(w)
return word_dict | 1fa9d3906f16f00f89363acb487bb8c22eb5c0b1 | 37,830 |
def train_test_split(df, index,
split_by=None,
stratify_by=None,
test_split=0.1,
seed=None):
"""Split pandas dataframe into train and test splits. Options to split by
group (i.e. keep groups together) and stratify by label.
... | fe56f9897da4df4708b2b439ea8d2b027d01668e | 37,831 |
def get_data_ce_duals_active_all():
"""() -> list
Returns a list of all of the active ce cards in the database, sorted in ascending order by start date."""
query = (
f'''
SELECT active_product_nick, active_product_titles, CAST (CAST (active_product_prices AS text) AS money), active_product_... | 0d9af4d17059ae53c2d0a4fa40f5e007253f07c6 | 37,832 |
from typing import Optional
def _import_project_sections(nt_client, monday_client, nt_project_id, project, limits: dict):
"""Import monday lists as project sections"""
nt_api_sections = apis.ProjectSectionsApi(nt_client)
def _parse_timestamp(monday_timestamp: Optional[str]) -> Optional[models.TimestampNu... | a57a8a6a41b7ef333d45001859e9b199b3d7339a | 37,833 |
def evaluate_wos_layer(epoch_predicts, epoch_labels, vocab, threshold=0.5, top_k=None):
"""
:param epoch_labels: List[List[int]], ground truth, label id
:param epoch_predicts: List[List[Float]], predicted probability list
:param vocab: data_modules.Vocab object
:param threshold: Float, filter probab... | c3b3a47caab6d396e1c3531d7f5e4442e7e4dd33 | 37,834 |
def convert_weighted(array : np.array) :
"""
3D-array to 2D-array
(R^2 + G^2 + B^2) / (R+G+B)
"""
sqrd = array**2
sqrd = sqrd.sum(axis = -1)
norm = array.sum(axis = -1)
return np.nan_to_num(sqrd/norm, nan=0) | 794d2fae798aec538cc6d502d86c0cd524fdf889 | 37,835 |
def empty_init():
"""Returns True if trying to initialize an Interactionobseng
without any arguments fails."""
try:
BaseObservationEngine()
return True
except TypeError:
return False | 0d3a3f4b5e6addd818037b73edd5dc6ea37edd79 | 37,836 |
import signal
def smooth_column(args):
"""Low-level helper function for smoothing single column
Parameters
----------
args : tuple
Tuple containing data to smooth in 1d array,
smoothing kernel in 1d array, whether to
ignore nans, and data dtype
Returns
-------
... | ce3f62c01c2a6e14cf921c83b670dc08e94e2936 | 37,837 |
def check_all_H(structure):
"""
Parameters
----------
structure : Biopython protein structure object made with PDBParser().
Returns
-------
all_ligands : dataframe of all distances between each amino acid residue
and ligand from the protein structure.
"""
heteros = get_hetero... | db70d4d891c50ef97a3dc642e1f6d81068d8ef8e | 37,838 |
def get_example_jwt_auth_signer(**kwargs):
""" returns an example jwt_auth_signer instance. """
issuer = kwargs.get('issuer', 'egissuer')
key_id = kwargs.get('key_id', '%s/a' % issuer)
key = kwargs.get(
'private_key_pem', get_new_rsa_private_key_in_pem_format())
algorithm = kwargs.get('algor... | 33a40801a7492c23b08570f6204cedf4d8c02eb8 | 37,840 |
async def close_trades(ctx):
"""Ends free agency in the identified league."""
if ctx.author.id not in admin_ids:
return await ctx.send("This is an admin-only command.")
for l in leagues:
if l.get_channel() == ctx.channel.id:
league = l
break
else:
return a... | 3219057ba9e05da4e7fa66af963c4991a55b6e3e | 37,842 |
def generate_set_None(gen_dict, class_dict):
"""Generate the code for the _set_None method of the class
Parameters
----------
gen_dict : dict
Dict with key = class name and value = class dict (name, package, properties, methods...)
class_dict : dict
Dictionnary of the class to gene... | 457f6588e71b9ae66b1b23a768d13a0a38be0ed0 | 37,843 |
import xml
def unescape_ssml(text: str) -> str:
"""Unescapes XML control characters in SSML.
See:
https://console.bluemix.net/docs/services/text-to-speech/http.html#escape
We first unescape the text in case it already contains escaped control
characters.
"""
return xml.sax.s... | 4f58510cad608fc7e18ac4ab19cf5895206adfaa | 37,846 |
def descSetupInEipMode():
"""
Setting up an EIP/ELB enabled zone with netscaler provider
"""
zs = cloudstackConfiguration()
for l in range(1):
z = zone()
z.dns1 = "8.8.8.8"
z.dns2 = "8.8.4.4"
z.internaldns1 = "192.168.110.254"
z.internaldns2 = "192.168.110.25... | a77b650532b3187085df9a19f70879addb6629b5 | 37,847 |
async def send_expr(bot: NoneBot, ctx: Context_T,
expr: Expression_T, **kwargs):
"""Sending a expression message ignoring failure by default."""
return await send(bot, ctx, expression.render(expr, **kwargs)) | 0999f5d9c914c27029b0427f84089b5419432fbb | 37,848 |
def ssd_model_build():
"""create network"""
ssd = ssd_inception_v2(configs=config)
if config.feature_extractor_base_param != "":
ssd.init_parameters_data()
param_dict = load_checkpoint(config.feature_extractor_base_param)
load_param_into_net(ssd, param_dict)
return ssd | 1a4e412d7dafcb43333cda6d0966b2fc920f6b07 | 37,850 |
def last_update_import_id():
"""
For better filtering.
@return:
"""
last_run = app.session.query(func.max(ImportLog.import_id)).filter(ImportLog.status == STATUS_FINISHED).first()[0]
if last_run is None:
max_import_id = -1
else:
max_import_id = last_run
return max_import... | e4e402a6d82e4b98d63363530c4775f50a7ee9b2 | 37,851 |
def is_valid(value, cast_fn, expected_data_type, allow_none=False):
"""
Checks whether a value can be converted using the cast_fn function.
Args:
value: Value to be considered
cast_fn: Function used to determine the validity, should throw an
exception if it cannot
e... | ee1a2aca4ba7d437692f5025901f9bf94031434a | 37,852 |
import re
def get_kanji(seg_content: str) -> dict:
"""Split raw lesson content into individual character entries and process each one."""
ret = {}
entries = [entry for entry in re.split(KANJI, seg_content) if entry]
for kanji, desc in zip(entries[::2], entries[1::2]):
ret[kanji] = parse_kanji(... | 96fa6d48d3c0ac8b0e64f110987522f9656486aa | 37,853 |
def range_transformation(value: float, input_range: list, output_range: list = [-1, 1]):
"""Range transformation from [input_range[0], input_range[1]] to [output_range[0], output_range[1]]
Args:
value (float): variable
input_range (list): desired input variable range
output_range (list,... | 31fbddf575a896fa1ffba7c85857557c3df0337a | 37,854 |
def get_authen_roles():
"""
Get the authentication roles
Returns:
arr[str]: Array of associated roles
"""
return g.get(AUTHEN_ROLES, []) | a3ba9caa050491203626f60a273d0fa3f8f58a07 | 37,855 |
def _mkanchors(ws, hs, x_ctr, y_ctr):
"""
Given a vector of widths (ws) and heights (hs) around a center
(x_ctr, y_ctr), output a set of anchors (windows).
"""
ws = ws[:, np.newaxis]
hs = hs[:, np.newaxis]
anchors = np.hstack((x_ctr - 0.5 * (ws - 1),
y_ctr - 0.5 * (h... | 54e5cc05c34f970f9e725f8ecfd27043c700378c | 37,856 |
def explode(dataframe: DataFrame, col: str, new_col: str = None) -> DataFrame:
"""Explode a list in a cell to many rows in the dataframe
:param str col: name of the column to explode
:param str new_col: name of the new column to explode to, could be exploded column
"""
tmp_new_col = new_col if new_... | 54133354eddf42dad973c2e19a9bfc80f3763f08 | 37,857 |
def median_buffer_range(mag, magerr):
"""This function returns the ratio of points that are between plus or minus 10% of the
amplitude value over the mean
:param mag: the time-varying intensity of the lightcurve. Must be an array.
:param magerr: photometric error for the intensity. Must be an array... | 83b1eed561399916da58be96c2e8437a8669d2d8 | 37,858 |
def multiply(a, b):
"""Multiply simple numbers, vectors, and 2D matrices."""
is_a_num = is_number(a)
is_b_num = is_number(b)
is_a_vec = not is_a_num and is_number(a[0])
is_b_vec = not is_b_num and is_number(b[0])
is_a_mat = not is_a_num and not is_a_vec
is_b_mat = not is_b_num and not is_b_... | f4c9a6e29a24bfbd9dab940510f3b6c35d09c4a7 | 37,859 |
from typing import Tuple
from typing import List
def two_qubit_matrix_to_diagonal_and_operations(
q0: 'cirq.Qid',
q1: 'cirq.Qid',
mat: np.ndarray,
allow_partial_czs: bool = False,
atol: float = 1e-8,
clean_operations: bool = True,
) -> Tuple[np.ndarray, List['cirq.Operation']]:
"""Decompos... | 36bb1d8a31eeebf78619427e681c4c9784783d45 | 37,860 |
def log_f(theta):
"""log of unnormalized target probability density function"""
log_var = theta[0]
var = np.exp(log_var)
xx = theta[1:]
return -0.5*log_var**2 - (0.5/var)*np.dot(xx, xx) - 0.5*xx.size*log_var | a04ed631ae035101a04bb429c8e254f5fed0a59c | 37,861 |
from operator import or_
def search(database, search_params=None, limit=0, order_by='last_updated desc'):
"""
Searches for one or more resources in the database using the specified parameters.
Args:
database: The current database context.
limit: The maximum number of results to return.
... | d2ff639263310186e2362ce290fdeeb33d58242b | 37,862 |
def pd_series_to_instapost(timeseries:pd.core.series.Series, pathname:str, units:str, timezone:str)->dict:
"""
Args:
series: a pd.core.Series time series with a time stamp index
pathname: pathname the data is to be stored at
units: the units the data is in
... | 527d20d5cfe2e6bd02199ab2713c41fd291179ea | 37,863 |
def iou_batch(bb_test, bb_gt):
"""
From SORT: Computes IUO between two bboxes in the form [l,t,w,h]... | 75a3eaea8aeac8c57553cc961ffcd11f25d21ac3 | 37,864 |
from typing import Callable
from typing import Optional
def action_interaction_additive_reward_function(
context: np.ndarray,
action_context: np.ndarray,
action: np.ndarray,
base_reward_function: Callable[[np.ndarray, np.ndarray], np.ndarray],
action_interaction_weight_matrix: np.ndarray,
is_c... | 720b23fb2dd539dba29acf46f498ce46d7a0a77e | 37,865 |
def butter2d_lp(shape, f, n):
"""
Designs a lowpass 2D Butterworth filter.
Modified from Peirce JW (2009) Generating stimuli for neuroscience using
PsychoPy. Front. Neuroinform. 2:10.
doi:10.3389/neuro.11.010.2008.
Parameters
----------
shape : tuple
Size of the filter.
f :... | 6c4b7ccc14290b4be2e06e7c752eb2146f3023cf | 37,866 |
def run_model(network, nodes, demand_per_person_kw_peak, mg_gen_cost_per_kw, mg_cost_per_m2, cost_wire_per_m, grid_cost_per_m2):
"""
"""
# First calcaulte the off-grid cost for each unconnected settlement
for node in nodes:
if node[5] == 0:
node[7] = node[4]*demand_per_person_kw_pe... | 02b386363ac2b18bde7e5773da91109fd234353b | 37,867 |
def read_circuit(file):
"""
Read a Revlib circuit file and create a Qiskit circuit objetc
:param file: Revlib circuit file
:returns a Qiskit circuit object
"""
with open(file, mode="r") as file:
lines = []
begin = end = 0
variables = ''
for index, line in enum... | b8d5c126c867a7a63843c3baf6fb321dcba9aa3a | 37,868 |
def global_reconstruction_error(
X,
Y,
test_idx=None,
train_idx=None,
scaler=None,
estimator=None,
):
"""Computes the global reconstruction error using the source X
to reconstruct the features or samples of target Y based on a minimization
by linear regression:
.. math:: GRE... | cebeb31aea82a5258955523bd5eeb95e492d2eea | 37,869 |
def api_mobsfy(request):
"""POST - MobSFy API."""
if 'identifier' not in request.POST:
return make_api_response(
{'error': 'Missing Parameters'}, 422)
resp = operations.mobsfy(request, True)
if resp['status'] == 'ok':
return make_api_response(resp, 200)
return make_api_re... | 306319f12e43cf57c3ab0757e964fae30cf17ed9 | 37,870 |
def numero_lista(df):
"""
Función destinada a obtener el número de lista de clases
:parameter: dataframe
:return:
numero de lista de clases
"""
# Selecciono la columna clase del dataframe y realizo unas modificaciones
df['clase'] = df['clase'].str.replace(
'[', '').str.replace(']... | 86523b6f9eae835de6dfc960e8930cf7659cb2a7 | 37,871 |
def Fingerprint(path, params):
"""Check for a Python app.
Args:
path: (str) Application path.
params: (ext_runtime.Params) Parameters passed through to the
fingerprinters.
Returns:
(PythonConfigurator or None) Returns a module if the path contains a
python app.
"""
log.info('Checking f... | 9fde55896fc98984ab90c6274f0f51b14d77e2a0 | 37,872 |
import numpy as np
def calc_spatialCorrHeightLev(varx,vary,levs,lons,weight,levelq):
"""
Calculates spatial correlation from pearson correlation coefficient for
grids over vertical height (17 pressure coordinate levels). Change the
weighting for different level correlations
Parameters
--... | 9645f5d92598250d75a484b0c5bf848073c3f5e8 | 37,874 |
def v_relative(v, met):
"""Estimates the relative air speed which combines the average air speed of
the space plus the relative air speed caused by the body movement. Vag is assumed to
be 0 for metabolic rates equal and lower than 1 met and otherwise equal to
Vag = 0.3 (M – 1) (m/s)
Parameters
... | 6dceae6ec076dc800d2aa3e80d7d491d94830580 | 37,875 |
def fully_qualified_name(entry):
"""
Calculates the fully qualified name for an entry by walking the path
to the root node.
Args:
entry: a BeautifulSoup Tag corresponding to an <entry ...> XML node,
or a <clone ...> XML node.
Raises:
ValueError: if entry does not correspond to one of the ... | 68119b640509cd972770f810b80ba1a2ad54f688 | 37,876 |
from pathlib import Path
def lab(
jupyter_lab: t.Tuple[BrowserContext, Path, int],
) -> t.Callable:
"""Provide function-scoped fixture leveraging longer lived fixtures."""
context, tmp, port = jupyter_lab
path = tmp / f"notebook-{uuid4()}.ipynb"
return lambda json_in: _lab(
json_in,
... | de906a24e494ac7dd056099ca925b82ac7eeb136 | 37,877 |
def load(env_name):
"""Loads the train and eval environments, as well as the obs_dim."""
# pylint: disable=invalid-name
kwargs = {}
if env_name == 'sawyer_push':
CLASS = SawyerPush
max_episode_steps = 150
elif env_name == 'sawyer_drawer':
CLASS = SawyerDrawer
max_episode_steps = 150
elif env... | 47f03f29d69f643ebd64040fa1d98607217fbb82 | 37,878 |
from typing import Iterable
from typing import Dict
def get_pkg_info(
package_name: str,
additional: Iterable[str] = ("pip", "flit", "pbr", "poetry", "setuptools", "wheel"),
) -> Dict[str, str]:
"""Return build and package dependencies as a dict."""
dist = distribution(package_name)
dependencies =... | 439b5058df1e421506ef6f23976cb64e48d555bc | 37,879 |
def sort_tasks_by_exec_time(tasks):
"""
Sort tasks in descending order by the execution time
Args:
tasks (list(Node)
Returns:
list(Node)
"""
n = len(tasks)
for i in range(n):
for j in range(0, n - i - 1):
if tasks[j].get_exec_time() < tasks[j+1].get_exe... | 44f24408803c851ae7f1dd021ec19f99efc3feda | 37,880 |
def csr_sort_indices(*args):
"""
csr_sort_indices(int n_row, int Ap, int Aj, signed char Ax)
csr_sort_indices(int n_row, int Ap, int Aj, unsigned char Ax)
csr_sort_indices(int n_row, int Ap, int Aj, short Ax)
csr_sort_indices(int n_row, int Ap, int Aj, unsigned short Ax)
csr_sort_indices(int n_r... | 06bf9c3c66e30d432e43e682e87da33665439b96 | 37,881 |
def rdkit_functional_group_label_features_generator(mol: Molecule) -> np.ndarray:
"""
Generates functional group label for a molecule in RDKit.
:param mol: A molecule (i.e. either a SMILES string or an RDKit molecule).
:return: A 1D numpy array containing the RDKit 2D features.
"""
smiles = Che... | 15ea9e0255e18674f8aeb6dc20834f1c7aee1d7f | 37,882 |
def append(log: immutables.Map, after: model.Index, *entries: model.Entry) -> immutables.Map:
"""Append entries to `log` *after* the given index.
:param log: Log object to append entries to.
:param after: Log index after which entries will be appended.
:raises AppendError: If the operation is unsucces... | c9947284f8333910e2f00703ab0da43b7c9eb2a8 | 37,883 |
def get_ids(conn, sql_class, columns, data):
"""
Get row ids based on data and column_names.
This function returns only the first id per data point.
Be careful if the columns do not ensure uniqueness.
"""
return [
_get_data(
conn=conn,
sql_class=sql_class,
... | b36be7ef815b6d2b82e340ed44881f8117490d29 | 37,884 |
import requests
import re
def get_special_search_qnodes(search_term):
"""
Searches for the search_term and returns a list of candidates from the wikidata search api
"""
if search_term == '':
return []
url = "https://www.wikidata.org/w/api.php"
params = {
"action": "query",
... | fce3f0c7ebc34613e4e92162169a766e538897cf | 37,885 |
def custom(colors, bins=None, bin_method=BinMethod.quantiles):
"""Create a custom scheme.
Args:
colors (list of str): List of hex values for styling data
bins (int, optional): Number of bins to style by. If not given, the
number of colors will be used.
bin_method (str, optiona... | eb6f0726d3523e4937cb7615e74eb073025c144c | 37,886 |
def convert_vdot_to_time(vdot, distance):
"""Given a VDOT score, returns an approx time for a given distance."""
# Get equation parameters
c = VDOT_TO_TIME[VDOT_TO_TIME.Distance==distance].iloc[0].Intercept
m1 = VDOT_TO_TIME[VDOT_TO_TIME.Distance==distance].iloc[0].Coef1
m2 = VDOT_TO_TIME[VDOT_TO_TI... | bb4a3071b7a94e2e1486b37baf3aeff82fcb8a2f | 37,888 |
def exception_response(status_code, **kw):
"""Creates an HTTP exception based on a status code. Example::
raise exception_response(404) # raises an HTTPNotFound exception.
The values passed as ``kw`` are provided to the exception's constructor.
"""
exc = status_map[status_code](**kw)
retur... | 0efc1bdd3c6febd4976210bb2759fd50c8fce9db | 37,889 |
def _mask_iou(mask1: np.ndarray, mask2: np.ndarray) -> ScalarMetricValue:
"""Computes iou between two binary segmentation masks."""
return np.sum(mask1 & mask2) / np.sum(mask1 | mask2) | 6f781f3f9f0702613093432de67ea91179a5cd23 | 37,891 |
import re
def shorten_int_name(interface_name):
"""
Returns the Cisco shortened interface name from a full one.
If the full interface name is invalid, this will return None
"""
short = None
regex = "(\w{2}).*?(\d+(?:/\d+)?(?:/\d+)?)"
match = re.match(regex, interface_name)
... | 48a6f730c8d3d2f0abaec299385b5d558cf06a00 | 37,892 |
import re
def read_version():
"""Read version from the first line starting with digit
"""
regex = re.compile('^(?P<number>\d.*?) .*$')
with open('../CHANGELOG.rst') as f:
for line in f:
match = regex.match(line)
if match:
return match.group('number') | 7188470ab1a794b6e72a1fe8bcd804f7290be4a4 | 37,893 |
def version_to_semver(version):
""" Convert an SDK version string to an npm compatible semver
:param version: should be major[.minor]
:return: "major.minor.0"
"""
return "{}.{}.0".format(*parse_sdk_version(version)) | b1006b7dca79e6c19d3849dfef298cf08b7c7f29 | 37,894 |
def RefDefaults():
"""
Returns dictionary of default values for all properties. These are used
to provide defaults to fields that we do not want to automatically
calculate dimensions for
"""
return {
'phi': {
'min':-180,
'max':180... | e6e87fd7c3b3a05f83808bebb410a6d5c687d3d3 | 37,895 |
import json
def load_json(path: str):
"""
Load the contents of a json file into a python dictionary
"""
with open(path) as f:
content = json.load(f)
return content | b35ae26ca303347a98ea3dd3ca42370279d19a2a | 37,896 |
def repopulate(opt: Optimizer, selected_data: pd.DataFrame, target_size: int) -> Population:
"""
Create new generation.
"""
fittest_pop = Population(selected_data, opt.population.blueprint)
offspring_pop = make_new_generation(n=target_size,
parent_fitness_data... | 1ab2bbcee1f6f4b69aa2eba0fd4f1d48da770ba2 | 37,898 |
def DataframetolaTexTable(DF, alignment=None, fname=None,shade=False):
"""
Args:
df: pandas dataframe
alignment: python list of allignment of columns; default is ['c',..]; use ['c', 'p{4in}', 'c', 'c'] for wrapping
fname: path to save latex table
Returns:
object:
Returns... | 62be7748dbdce035b70468388d314c585696e275 | 37,899 |
def getinstructorData(courseIds):
"""
Gets and instructor object for the course id's given.
"""
instructorDict = {}
instructor = CourseInstructor.select().where(CourseInstructor.course << courseIds)
for i in instructor:
instructorDict.setdefault(i.course.id, []).append(i.user.firstName ... | 845c7cbc7a0eaa41072662d2669509c2b722ceb3 | 37,901 |
def convert_farenheit_to_celcius(temp):
"""Convert the temperature from Farenheit to Celcius scale.
:param float temp: The temperature in degrees Farenheit.
:returns: The temperature in degrees Celcius.
:rtype: float
"""
return (temp - 32) * 5 / 9 | a782550aa33641a719eb6b245d894248aeaa4985 | 37,902 |
def get_frequent_item(data):
"""
对于给定的字符串列表，找出其中出现次数最多的字符
参数
----
data: list[str]，字符串列表
返回
----
re: list[str]，出现次数最多的字符串
"""
_hash = word_count(data)
max_num = max(_hash.values())
return list(filter(lambda x: _hash[x] == max_num, _hash)) | 6cd1b6cd77e9855c6732614b3fbf2096ae1fcbfb | 37,905 |
def float_coords_(coords):
"""\
"""
return [float_recur(coord) for coord in coords] | c02fced6a0137a5bc933a81d0decc472f62faa62 | 37,906 |
def invt_sample_z(log_density, size=1, rng=None, **log_cdf_kwargs):
"""
Inverse transform sampling to generate "true" z values for simulation:
"""
if rng is None:
rng = np.random.default_rng()
zgrid, log_cdf = get_log_cdf(log_density, **log_cdf_kwargs)
cdf = np.exp(log_cdf)
interp_... | 7f7e1cb86aa04dc6b00d8d35f3c8cb8028e326ab | 37,909 |
from functools import reduce
import operator
def fsort(l, signed=True, reverse=False):
"""Sort a sequence of strings with one or more floating point number fields
in using the floating point value(s) (and intervening strings are treated
as normally done). Note that + and - preceding a number are included ... | 75b9b465bca0e5792a128682a8b31756779173c5 | 37,910 |
import re
def food_parse(db, query):
"""
returns a jsonable dict for the autocomplete js library we are using
for a text field used to select a food item
:param db:
:param query:
:return:
"""
parts = re.split("\s+", query)
parts = [lemmer.lemmatize(part) for part in parts]
db_... | ab55b9e1bbdf3a248c46316cdb8e69400fac9876 | 37,911 |
from typing import Union
from pathlib import Path
from typing import Optional
from typing import Tuple
import numpy
from typing import Dict
def read_gpop_hdf5(
path: Union[Path, str], interior_path: str, dof: Optional[int] = None
) -> Union[
Tuple[numpy.ndarray, Dict[int, numpy.ndarray], Dict[int, numpy.ndarr... | 286886a9866bc77b9ab5610c95ec248ceb4839d5 | 37,912 |
def invite(request):
"""
Simple view to send invitations to friends via mail. Making the invitation
system as a view, guarantees that no invitation will be monitored or saved
to the hard disk.
"""
if request.method == "POST":
mail_addr = request.POST['email_addr']
raw_addr_list ... | 14ba6ebd044710649f82c6d7b94b4b752d24bfae | 37,913 |
def cells():
"""Cells
From in 'Image manipulation and processing using Numpy and Scipy' section
2.6.6 Measuring object properties
<http://www.tp.umu.se/~nylen/fnm/pylect/advanced/image_processing/index.html>
No known copyright restrictions, released into the public domain.
"""
np.random.s... | 71a9fe2eda33585527b93710f97e76d6a9f8be10 | 37,915 |
import inspect
def jsonify_arg_input(arg):
"""Jsonify user input (in AssemblyPipeline `append` and `insert` methods)
into a standard step json."""
if isinstance(arg, RunnableArgument):
return arg.to_json()
# If a function object or name of a function is provided, we assume it
# does not ha... | ec5f04b42a410b8aea2ed9b01b5b506f1b9629ea | 37,916 |
def geodetic_to_ellipsoidal(lat: u.deg, lon: u.deg, height: u.m, ell):
"""Convert from geodetic to ellipsoidal-harmonic coordinates.
Parameters
----------
lat : ~astropy.units.Quantity
Geodetic latitude.
lon : ~astropy.units.Quantity
Geodetic longitude.
height : ~astropy.units.Q... | ffaf011660c9a21908aa25e04c64e6aa9bd8d6f4 | 37,917 |
def enc_backbuffer(backbuffer):
"""Helper function for RLE compression, encodes a string of uncompressable data."""
compdata = []
if len(backbuffer) == 0:
return compdata
while len(backbuffer) > 128:
compdata.append(127)
compdata.extend(backbuffer[0:128])
backbuffer = bac... | 75e9860cd0a8563f3e5655b998b4d0dfa1658e9c | 37,918 |
def fourier_features(index, freq, order):
"""
`Reference`_: https://www.kaggle.com/ryanholbrook/seasonality
Example:
>>> # Compute Fourier features to the 4th order (8 new features) for a
>>> # series y with daily observations and annual seasonality:
>>> # fourier_features(y, freq=365.25, order... | 1568aa388889ca01e47f3eb63fbf19a92bdcc0e9 | 37,919 |
def read_range(read):
"""Creates a Range proto from the alignment of Read.
Args:
read: nucleus.genomics.v1.Read. The read to calculate the range for.
Returns:
A nucleus.genomics.v1.Range for read.
"""
start = read.alignment.position.position
end = start + cigar.alignment_length(read.alignment.ciga... | 4a0c4519cde59484d5aae3acd72d71e870fecc60 | 37,920 |
def _get_label_members(X, labels, cluster):
"""
Helper function to get samples of a specified cluster.
Args:
X (np.ndarray): ndarray with dimensions [n_samples, n_features]
data to check validity of clustering
labels (np.array): clustering assignments for data X
cluster ... | 95c9f4e898b0636d3e7b6151f6d336137200143c | 37,921 |
def create_balcony(bm, faces, prop):
"""Generate balcony geometry
"""
for f in faces:
if not valid_ngon(f):
popup_message("Balcony creation not supported for non-rectangular n-gon!", "Ngon Error")
return False
f.select = False
normal = f.normal.copy()
... | 80a1d98b8b5fd89d7f3f594edf6d51c358eb3551 | 37,922 |
def film_availability_keys():
"""
FilmAvailability definition
Optional keys: "id"
"""
return ["service", "displayName", "country", "url"] | 829ec5ea5492b58c19639f0f83245a88aedb6cc8 | 37,924 |
def get_label(scores):
""" Compute labels using score values.
Args:
scores: Score values for each detection.
Returns: Label for each detection.
"""
return tf.math.argmax(scores, axis=1) | abcd01c989f25d574236c19ffc6cafe2eb66257d | 37,925 |
def cm_step_summary(abf):
"""
Return a message displaying average stats
formatted like 'Cm = 34.56 +/- 3.21 pF'
"""
Ihs, Rms, Ras, Cms = cm_step_valuesBySweep(abf)
out = ""
out += "Ih = %.02f +/- %.02f pA\n" % (np.mean(Ihs), np.std(Ihs))
out += "Rm = %.02f +/- %.02f pA\n" % (np.mean(Rms)... | e4df5d9f524dfd450c05a407b6726ff75034638c | 37,926 |
from pathlib import Path
def check_arg_input_file(input_file: str) -> bool:
"""Return True of the input_file exists, raise an error otherwise.
:param input_file: the input file
:param input_format: the expected format of the input file
"""
path_input_file = Path(input_file)
if not path_input_... | df1f877be2afc1d37a008a551776a9adcc3f2b8a | 37,927 |
def V_tank_Reflux(Reflux_mass, tau, rho_Reflux_20, dzeta_reserve):
"""
Calculates the tank for waste.
Parameters
----------
Reflux_mass : float
The mass flowrate of Reflux, [kg/s]
tau : float
The time, [s]
rho_Reflux_20 : float
The destiny of waste for 20 degrees celc... | 3e1adc446bbe2dd936663af895c59222cd000a48 | 37,928 |
def angular_travel(angle_array):
"""
Takes in an array of angular change and returns the angles travelled. This is sensitive to changes in
direction, The angles travelled are returned as an array of stepwise values
"""
travelled = [0]
for a, angle in enumerate(angle_array):
travelled.app... | 0c9eca97614a38c7400796ae3930f18707bc948d | 37,930 |
def IR_50(cfg):
"""Constructs a ir-50 model.
"""
input_size = cfg.INPUT.SIZE_TRAIN
model = Backbone(input_size, 50,cfg.MODEL.BACKBONE.BACKBONE_OUT_CHANNELS, 'ir')
return model | fef1dce13a8c4d50e669551b6b561ef1d9014007 | 37,932 |
def writeNetfile2(G, fname):
"""
write net file from G (networkx)
Parameters
----------
G: a neteworkx object
Returns
-------
file
"""
nZones = ''
nNodes = str(len(G.nodes()))
nLinks = str(len(G.edges()))
header = "<NUMBER OF ZONES> " + nZones + "\n<NUMBER OF NODES> " + nNodes + "\n<FIRS... | ea4b914c2169d3d3cc92a51c84ffcf89fe4bfd4e | 37,933 |
import torch
def attention_aggregator(embedding_lists, weights, embed_dim=0) -> torch.Tensor:
"""
Returns a weighted sum of embeddings
:param embedding_lists: list of n tensors of shape (l, K) embedding tensors (l can vary)
:param weights: list of n tensors of shape (l,) weights (l can... | 88fe01d8baea23321593bf88fd522eb0ef379be9 | 37,934 |
def _calculate_application_risk(module):
"""
Function to calculate Software risk due to application type. This
function uses a similar approach as RL-TR-92-52 for baseline fault
density estimates. The baseline application is Process Control
software. Every other application is ranked relative to ... | 703aaf086aecf717be5c13694a8f1dae9f70a86c | 37,935 |
def test():
""" Eventually this could become a convenience command for calling the
other test commands quickly with just test -x.
"""
return test_all() | 8a1bb5d89aa73f0236de0316b38c02ea17ae18cd | 37,936 |
def RK(A,b,k=100, random_state=None):
"""
Function that runs k iterations of randomized Kaczmarz iterations (with uniform sampling).
Parameters
----------
A : NumPy array
The measurement matrix (size m x n).
b : NumPy array
The measurement vector (size m x 1).
k : int_, opti... | 375acf10f277ff7533b0b45058a836c46328deea | 37,941 |
def run_k_means(reduced_text: str, k: int, dataframe: pd.DataFrame)->None:
""" create dataframe column for k means cluster """
kmeans = KMeans(n_clusters=k, random_state=42)
y_pred = kmeans.fit_predict(reduced_text)
dataframe['y_pred'] = y_pred
return y_pred | 08fbf8cb54bc74d410f674924cc13bc82e376578 | 37,942 |
from typing import List
from typing import Tuple
def split_blank_line(
lines: List[str], line_offset: int = 0
) -> Tuple[List[str], List[str]]:
"""Split leading blank line from lines if one exists
Args:
lines: The lines to evaluate.
line_offset (optional): The offset into the overall docu... | c70cf05111ec17c12797b5d94a547db0b4d3427c | 37,943 |
from typing import Union
import requests
import json
def get_page_list_by_page(base_url: str, api_token: str, page_path: str, limit:Union[int, None]=None) -> dict:
"""
get page list under the specified page path
"""
req_url = '{}{}'.format(base_url, '/_api/pages.list')
limit = 1e10 if limit is Non... | dbf70ac34187748e9f6dbfc4296df738c98819b6 | 37,944 |
def erode_edges(mask, erosion_width):
"""Erode edge of objects to prevent them from touching
Args:
mask: uniquely labeled instance mask
erosion_width: integer value for pixel width to erode edges
Returns:
mask where each instance has had the edges eroded
"""
if erosion_widt... | 35a32f14b8ca9c54d090fe0e77e4108f02f8fe4b | 37,945 |
import re
def load_keel_file(path):
"""Load a keel dataset format.
Parameters
----------
path : str
The filepath of the keel dataset format.
Returns
-------
keel_dataset: KeelDataset
The keel dataset format loaded.
"""
handle = open(path)
try:
... | 55849a706cdc8a3790501f694329ac73dbe1cb0d | 37,946 |
import torch
def searchsorted2d(a, b):
"""
Searches a sorted 2D array along the second axis. Basically performs a vectorized digitize. Solution provided here:
https://stackoverflow.com/questions/40588403/vectorized-searchsorted-numpy.
:param a: The array to take the elements from
:type a: torch.Te... | f46cf6217e7ec85ba0a27df8474b64bebc552759 | 37,948 |
def bytesToBits(numBytes):
"""
Converts number of bytes to bits.
:param numBytes: The n number of bytes to convert.
:returns: Number of bits.
"""
return numBytes * 8 | 6dc14c9d9f5829337e826c63a7772ea8d3c6962c | 37,949 |
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