content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def detect_version(conn):
"""
Detect the version of the database. This is typically done by reading the
contents of the ``configuration`` table, but before that was added we can
guess a couple of versions based on what tables exist (or don't). Returns
``None`` if the database appears uninitialized, ... | 6429dbb1e1767cf6fd93c3fd240ce095f1b50ef7 | 6,979 |
def nIonDotBHmodel2(z):
"""Ionization model 2 from BH2007: constant above z=6.
"""
return ((z < 6) * nIonDotLowz(z) +
(z >= 6) * nIonDotLowz(6)) | 438cdd69a229e445f8e313145e84ed11618ee2cb | 6,980 |
def answer(input):
"""
>>> answer("1234")
1234
"""
lines = input.split('\n')
for line in lines:
return int(line) | b9ce42d88a09976444563493a01741475dce67c5 | 6,981 |
def get_leading_states(contributions):
"""
Return state contributions, names as lists in descending order of contribution amount
:param contributions:
:return:
"""
contributions['state'] = contributions['clean_fips'].apply(get_state)
states = contributions.groupby('state')
state_sums = s... | 7028f87ad7b106e267104dddebc2fe42546d3cfd | 6,982 |
def contacts_per_person_normal_self_20():
"""
Real Name: b'contacts per person normal self 20'
Original Eqn: b'30'
Units: b'contact/Day'
Limits: (None, None)
Type: constant
b''
"""
return 30 | 4a240066b2aefd8af2e19f174632e1bf854bf7d3 | 6,983 |
def __compute_partition_gradient(data, fit_intercept=True):
"""
Compute hetero regression gradient for:
gradient = ∑d*x, where d is fore_gradient which differ from different algorithm
Parameters
----------
data: DTable, include fore_gradient and features
fit_intercept: bool, if model has int... | e987fc53b1f1ee8cc7a0ddbe83de23b1623b532e | 6,984 |
def calc_nsd(x, n=21):
"""
Estimate Noise Standard Deviation of Data.
Parameters
----------
x : 1d-ndarray
Input data.
n : int
Size of segment.
Returns
-------
result : float
Value of noise standard deviation.
"""
x_diff = np.diff(x, n=2)
x_frag ... | 23b0041fc1a9bde364828a0a94b12fc7292a391a | 6,985 |
def deflection_from_kappa_grid_adaptive(kappa_high_res, grid_spacing, low_res_factor, high_res_kernel_size):
"""
deflection angles on the convergence grid with adaptive FFT
the computation is performed as a convolution of the Green's function with the convergence map using FFT
The grid is returned in th... | cc71b9bd35c5e09e45815cf578870c481a03b8ed | 6,986 |
from params import pop_sizes
def remove_sus_from_Reff(strain, data_date):
"""
This removes the inferred susceptibility depletion from the Reff estimates out of EpyReff.
The inferred Reff = S(t) * Reff_1 where S(t) is the effect of susceptible depletion (i.e. a
factor between 0 and 1) and Reff_1 is t... | 9342896ff84507ecbe93b96a81b781ed6f8c336e | 6,987 |
def word2bytes(word, big_endian=False):
""" Converts a 32-bit word into a list of 4 byte values.
"""
return unpack_bytes(pack_word(word, big_endian)) | 9c208efc87bb830692771f3dacb1618a1d8d7da4 | 6,988 |
def statfcn(status, _id, _ret):
"""
Callback for libngspice to report simulation status like 'tran 5%'
"""
logger.warn(status.decode('ascii'))
return 0 | 344210160227ae76470f53eecd43c913b9dec495 | 6,989 |
def decode_eventdata(sensor_type, offset, eventdata, sdr):
"""Decode extra event data from an alert or log
Provide a textual summary of eventdata per descriptions in
Table 42-3 of the specification. This is for sensor specific
offset events only.
:param sensor_type: The sensor type number from th... | 7a90810657edd017b42f7f70a7a0c617435cb14f | 6,990 |
def about_incumbent(branch_df):
"""
number of incumbent updates
incumbent throughput: num_updates / num_nodes
max_improvement, min_improvement, avg_improvement
avg incumbent improvement / first incumbent value
max, min, avg distance between past incumbent updates
distance between last update... | 309dd09a6fcad58064e98c79536ca73256fe3ac2 | 6,992 |
from typing import List
def unique_chars(texts: List[str]) -> List[str]:
"""
Get a list of unique characters from list of text.
Args:
texts: List of sentences
Returns:
A sorted list of unique characters
"""
return sorted(set("".join(texts))) | 02bc9ce28498bd129fdb68c2f797d138ca584490 | 6,993 |
def adaptive_max_pool1d(input, output_size):
"""Apply the 1d adaptive max pooling to input.
Parameters
----------
input : dragon.vm.torch.Tensor
The input tensor.
output_size : Union[int, Sequence[int]]
The target output size.
Returns
-------
dragon.vm.torch.Tensor
... | 06556ea06ebe282bf24739d56ff016924a730c8b | 6,994 |
def get_return_nb(input_value, output_value):
"""Get return from input and output value."""
if input_value == 0:
if output_value == 0:
return 0.
return np.inf * np.sign(output_value)
return_value = (output_value - input_value) / input_value
if input_value < 0:
return_... | fe9ef59feb7b4e9797a74258ecbf890171f6df59 | 6,995 |
def get_rocauc(val,num_iterations):
""" Trains a logistic regression and calculates the roc auc
for classifying products as >=4 stars """
recalls = np.zeros(num_iterations)
precisions = np.zeros(num_iterations)
f1s = np.zeros(num_iterations)
roc_aucs = np.zeros(num_iterations)
factory = lr_wrapper(val,featur... | d2b2ceae240db6c3ce474d74aea1ebd4d1ed9830 | 6,996 |
import torch
def poly_edges_min_length(P, T, distFcn=norm):
"""
Returns the per polygon min edge length
Parameters
----------
P : Tensor
a (N, D,) points set tensor
T : LongTensor
a (M, T,) topology tensor
Returns
-------
Tensor
the (T, M,) min edge length... | efa68aa752d0f3c1efc29a846f06e006bd8bceb9 | 6,999 |
def softmax(x):
"""A softmax implementation."""
e_x = np.exp(x - np.max(x))
return e_x / e_x.sum(axis=0) | 3c8e38bf30304733e957cabab35f8fec1c5fba55 | 7,001 |
import logging
def get_cazy_class_fam_genbank_records(args, session, config_dict):
"""GenBank acc query results from the local CAZyme database for CAZyme from specific classes/fams
:param args: cmd-line argument parser
:param session: open SQLite db session
:param config_dict: dict, defines CAZy clas... | 3f2d8f65f811be1de6b839753242e51457f8e03e | 7,002 |
def assign_bias_ID(data, bias_params=None, bias_name='bias_ID', key_name=None, bias_model=None):
"""
Assign a value to each data point that determines which biases are applied to it.
parameters:
data: pointCollection.data instance
bias_parameters: a list of parameters, each unique combinati... | 8f2145b5efcd7b892b3f156e1e0c4ff59dac9d43 | 7,003 |
def check(s):
"""
:param s:str. the input of letters
:return: bool.
"""
if len(s) == 7 and len(s.split(' ')) == 4:
for unit in s.split(' '):
if unit.isalpha():
return True | 86e1270af299ba83b68d0dab9f8afc3fc5b7d7c5 | 7,004 |
def pyeval(*args):
"""
.. function:: pyeval(expression)
Evaluates with Python the expression/s given and returns the result
>>> sql("pyeval '1+1'")
pyeval('1+1')
-------------
2
>>> sql("select var('test')") # doctest: +NORMALIZE_WHITESPACE
Traceback (most recent call last):
.... | fa7febed8f25860eee497ce670dc9465526cbbc1 | 7,005 |
def with_hyperparameters(uri: Text):
"""Constructs an ImporterNode component that imports a `standard_artifacts.HyperParameters`
artifact to use for future runs.
Args:
uri (Text): Hyperparameter artifact's uri
Returns: ImporterNode
"""
return ImporterNode(
instance_name='with_h... | e06cc33d043e6abd4a9ee30648f72dcea2ad1814 | 7,007 |
def update_user_controller(user_repository_spy): # pylint: disable=W0621
"""montagem de update_user_controller utilizando spy"""
usecase = UpdateUser(user_repository_spy, PasswordHash())
controller = UpdateUserController(usecase)
return controller | 474c2bf42c932d71181bebbf7096cd628ba6956a | 7,008 |
def blockList2Matrix(l):
""" Converts a list of matrices into a corresponding big block-diagonal one. """
dims = [m.shape[0] for m in l]
s = sum(dims)
res = zeros((s, s))
index = 0
for i in range(len(l)):
d = dims[i]
m = l[i]
res[index:index + d, index:index + d] = m
... | b13a67cd203930ca2d88ec3cd6dae367b313ae94 | 7,009 |
def log_new_fit(new_fit, log_gplus, mode='residual'):
"""Log the successful refits of a spectrum.
Parameters
----------
new_fit : bool
If 'True', the spectrum was successfully refit.
log_gplus : list
Log of all previous successful refits of the spectrum.
mode : str ('positive_re... | 16761ca135efbdb9ee40a42cb8e9e1d62a5dc05e | 7,010 |
def prepare_hr_for_compromised_credentials(hits: list) -> str:
"""
Prepare human readable format for compromised credentials
:param hits: List of compromised credentials
:return: Human readable format of compromised credentials
"""
hr = []
for hit in hits:
source = hit.get('_source... | 846144700d3fe21628306de5aff72a77d2cc9864 | 7,011 |
def red_bg(text):
""" Adds a red background to the given text. """
return colorize(text, "\033[48;5;167m") | edc2741f3246de2c90c9722c4dbd2d813708fe90 | 7,012 |
def model_utils(decoy: Decoy) -> ModelUtils:
"""Get mock ModelUtils."""
return decoy.mock(cls=ModelUtils) | eb5d3eaf8f280086521209f62025e42fca7aec93 | 7,013 |
def getLeftTopOfTile(tilex, tiley):
"""Remember from the comments in the getStartingBoard() function that we have two sets of coordinates in this program. The first set are the pixel coordinates, which on the x-axis ranges from 0 to WINDOWWIDTH - 1, and the y-axis ranges from 0 to WINDOWHEIGHT - 1.
Lembrando... | fad5a9df02b05e76ba62013a49d77941b71f6f5f | 7,014 |
def count_str(text, sub, start=None, end=None):
"""
Computes the number of non-overlapping occurrences of substring ``sub`` in ``text[start:end]``.
Optional arguments start and end are interpreted as in slice notation.
:param text: The string to search
:type text: ``str``
:param ... | 1578f868a4f1a193ec9907494e4af613ca2a6d4d | 7,015 |
def tanh(x, out=None):
"""
Raises a ValueError if input cannot be rescaled to a dimensionless
quantity.
"""
if not isinstance(x, Quantity):
return np.tanh(x, out)
return Quantity(
np.tanh(x.rescale(dimensionless).magnitude, out),
dimensionless,
copy=False
) | 3d86565fb512bfe6f8034dd7436b65c1c322cde6 | 7,016 |
from typing import Optional
from typing import Sequence
from pathlib import Path
def epacems(
states: Optional[Sequence[str]] = None,
years: Optional[Sequence[int]] = None,
columns: Optional[Sequence[str]] = None,
epacems_path: Optional[Path] = None,
) -> dd.DataFrame:
"""Load EPA CEMS data from P... | 79213c5adb0b56a3c96335c0c7e5cb1faa734752 | 7,017 |
from typing import Optional
from typing import Tuple
import logging
def check_termination_criteria(
theta: Optional[float],
num_iterations: Optional[int]
) -> Tuple[float, int]:
"""
Check theta and number of iterations.
:param theta: Theta.
:param num_iterations: Number of iterations.... | 536cd70b8e8b04d828f0a4af1db96809ab607ff3 | 7,018 |
def verify_password(password, hash):
"""Verify if a hash was generated by the password specified.
:password: a string object (plaintext).
:hash: a string object.
:returns: True or False.
"""
method = get_hash_algorithm(flask.current_app.config['HASH_ALGORITHM'])
return method.verify(pass... | 484ad9f2debbd8856b9b7fbdd2a7588f9a279f62 | 7,020 |
import re
def _conversion_sample2v_from_meta(meta_data):
"""
Interpret the meta data to extract an array of conversion factors for each channel
so the output data is in Volts
Conversion factor is: int2volt / channelGain
For Lf/Ap interpret the gain string from metadata
For Nidq, repmat the gai... | e8cd2ea376bdb44ee999459ffcc28c4c4db39458 | 7,021 |
def read_split_csv(input_files, delimiter='\t', names=['src', 'dst'],
dtype=['int32', 'int32']):
"""
Read csv for large datasets which cannot be read directly by dask-cudf
read_csv due to memory requirements. This function takes large input
split into smaller files (number of input_fi... | cd1f2ccd487cf808af1de6a504bc0f6a3a8e34a1 | 7,022 |
def _gnurl( clientID ):
"""
Helper function to form URL to Gracenote_ API service.
:param str clientID: the Gracenote_ client ID.
:returns: the lower level URL to the Gracenote_ API.
:rtype: str
"""
clientIDprefix = clientID.split('-')[0]
return 'https://c%s.web.cddbp.net/webapi/xml... | 6d1935c8b634459892e4ec03d129c791b1d8a06a | 7,023 |
def flatatt(attrs):
"""
Convert a dictionary of attributes to a single string.
The returned string will contain a leading space followed by key="value",
XML-style pairs. It is assumed that the keys do not need to be XML-escaped.
If the passed dictionary is empty, then return an empty string.
js... | 01d9ee3ec96b5a096758f60c2defe6c491d94817 | 7,024 |
def draw_bboxes(img,boxes,classes):
"""
Draw bounding boxes on top of an image
Args:
img : Array of image to be modified
boxes: An (N,4) array of boxes to draw, where N is the number of boxes.
classes: An (N,1) array of classes corresponding to each bounding box.
Outputs:
... | 6b60550206aaaa9e5033850c293e6c48a7b13e6d | 7,025 |
def markdown(context, template_path):
""" {% markdown 'terms-of-use.md' %} """
return mark_safe(get_markdown(context, template_path)[0]) | ea6cb711c1a669ad7efdf277baab82ea2a65ba9c | 7,026 |
def investorMasterGetSubaccAssetDetails(email, recvWindow=""):
"""# Query managed sub-account asset details（For Investor Master Account）
#### `GET /sapi/v1/managed-subaccount/asset (HMAC SHA256)`
### Weight:
1
### Parameters:
Name |Type |Mandatory |Description
--------|--------|--------|--------
email |STRING |... | 7d4f4c5cbd069144319268dcb7235926e55f85d8 | 7,027 |
def ema_indicator(close, n=12, fillna=False):
"""EMA
Exponential Moving Average via Pandas
Args:
close(pandas.Series): dataset 'Close' column.
n_fast(int): n period short-term.
fillna(bool): if True, fill nan values.
Returns:
pandas.Series: New feature generated.
"... | 9ddb20ddc6e0cc4b1f08a4e3347f719dbe84b55b | 7,028 |
def u_glob(U, elements, nodes, resolution_per_element=51):
"""
Compute (x, y) coordinates of a curve y = u(x), where u is a
finite element function: u(x) = sum_i of U_i*phi_i(x).
Method: Run through each element and compute cordinates
over the element.
"""
x_patches = []
u_patches = []
... | 2c9cabf97b9904d80043a0102c0ac8cd156388ae | 7,030 |
def keyring_rgw_create(**kwargs):
"""
Create rgw bootstrap keyring for cluster.
Args:
**kwargs: Arbitrary keyword arguments.
cluster_uuid : Set the cluster UUID. Defaults to value found in
ceph config file.
cluster_name : Set the cluster name. Defaults to "ce... | 077a3536a6e1ce2e762b14d8fb046617136fe941 | 7,031 |
import pandas
from datetime import datetime
def read_tm224_data(filename: str, folder: str = None) -> pandas.DataFrame:
"""
Read data stored by Lakeshore TM224 temperature monitor software.
Args:
filename: string
name of ".xls" file on disk
folder: string
location... | 430e5a64b5b572b721177c5adce7e222883e4512 | 7,032 |
import json
import logging
def load_keypoints2d_file(file_path, njoints=17):
"""load 2D keypoints from keypoint detection results.
Only one person is extracted from the results. If there are multiple
persons in the prediction results, we select the one with the highest
detection score.
Args:
file_path... | 3cf5c8f2c236b3883e983c74e1ac23c78d256b0d | 7,034 |
def utf8_bytes(string):
""" Convert 'string' to bytes using UTF-8. """
return bytes(string, 'UTF-8') | 8e5423d2b53e8d5fbeb07017ccd328236ef8bea5 | 7,035 |
def _get_value(session_browser, field):
"""Get an input field's value."""
return session_browser.evaluate_script('$("#id_%s").val()' % field) | 7ed2d130b83af7e6fdb6cce99efb44846820585a | 7,037 |
import functools
def standarize_ms(datas, val_index, max=(2^32 - 1)):
"""
Standarize milliseconds lapsed from Arduino reading.
Note: Only takes height for one circulation of ms from Arduino.
datas:
List of data readings
val_index:
Index of ms value in reading data entry
max:
... | 84bf498ff3c88b3415433fa9d5be7b6865b3216b | 7,042 |
def corr_bias(x_data, y_data, yerr, pdz1_x, pdz1_y, pdz2_x, pdz2_y):
"""
Given a correlation measurement and associated PDZs, generate a model and
fit as a bias to the measurement. Return:
1) the model [unbiased] (x and y float arrays)
2) best fit bias (float)
3) the bias PDF (x ... | 255e1c5a67551deb19b91d247f5a913541d8f1da | 7,043 |
def confidence_ellipse(
x=None, y=None, cov=None, ax=None, n_std=3.0, facecolor="none", **kwargs
):
"""
Create a plot of the covariance confidence ellipse of `x` and `y`
Parameters
----------
x, y : array_like, shape (n, )
Input data.
cov : array_like, shape (2, 2)
covarianc... | 3965012ccdd1f6b71af4f169b812c384446ed76d | 7,044 |
from typing import List
def adapted_fields(type) -> List[Attribute]:
"""Return the attrs format of `fields()` for attrs and dataclasses."""
if is_dataclass(type):
return [
Attribute(
attr.name,
attr.default
if attr.default is not MISSING
... | cc6a799e06715cbd4e3219ea42aaeff2e4924613 | 7,046 |
from typing import get_args
def get_parms():
"""
Use get_args to get the args, and return a dictionary of the args ready for
use in pump software.
@see get_args()
:return: dict: parms
"""
parms = {}
args = get_args()
for name, val in vars(args).items():
if val is not None:... | 6ebdbee656fd216e5d8c66025029aa2d58641831 | 7,047 |
def make_led_sample(n_samples=200, irrelevant=0, random_state=None):
"""Generate random samples from the 7-segment problem.
Parameters
----------
n_samples : int, optional (default=200)
The number of samples to generate.
irrelevant : int, optional (default=0)
The number of irreleva... | 7dab2595c0118ca2f08a99ded22047be164f1648 | 7,049 |
def handle_source_authorization_exception(e):
""" Error handler: the data source requires authorisation
This will be triggered when opening a private HDX dataset before
the user has supplied their authorisation token.
@param e: the exception being handled
"""
if e.message:
flask.flash(e.... | e2c736b301e229d61874bb3cfad13b86dc93e1d1 | 7,050 |
def findcosmu(re0, rp0, sublat, latc, lon): # considers latc to be plaentocentric latitudes, but sublat to be planetographic
"""Takes the equitorial and polar radius of Jupiter (re0, rp0 respectively), the sub-latitude of Jupiter, latitude and
longitude (both in radians) to determine the "cos(mu)" of the ... | 677adffb6f00e9e1119a71a660ee81d2893d4ef1 | 7,051 |
def RMS_energy(frames):
"""Computes the RMS energy of frames"""
f = frames.flatten()
return N.sqrt(N.mean(f * f)) | 10d366e771f629c6efda2faf1f752363dca63b0a | 7,052 |
import urllib
def is_blacklisted_url(url):
"""
Return whether the URL blacklisted or not.
Using BLACKLIST_URLS methods against the URLs.
:param url: url string
:return: True if URL is blacklisted, else False
"""
url = urllib.parse.urlparse(url).netloc
for method in WHITELIST_URL:
... | 8a987c0bbce01d18da67b047aed0e680ce5fc661 | 7,053 |
def heading(yaw):
"""A helper function to getnerate quaternions from yaws."""
q = euler2quat(0.0, 0.0, yaw)
quat = Quaternion()
quat.w = q[0]
quat.x = q[1]
quat.y = q[2]
quat.z = q[3]
return quat | fcd05575257ef6cdc084cb2fde309aa48b5a2fb5 | 7,054 |
def check_login_required(view_func):
"""
A decorator that checks whether login is required on this installation
and, if so, checks if the user is logged in. If login is required and
the user is not logged in, they're redirected to the login link.
"""
def _check(*args, **kwargs):
siteconf... | 9f0b44f630a24649d87af0bd604a41b7b5b885de | 7,055 |
def Str(*args):
"""(s1, s2, ...) -> match s1 or s2 or ..."""
if len(args) == 1:
return Str1(args[0])
return Expression.Alt(tuple(map(Str, args))) | 41aece71a6a774db58028add5d60d8c9fed42dd3 | 7,056 |
def image_noise_gaussian(image):
"""
Adds Gaussian noise to the provided image
"""
float_img = image.astype(np.float)
gauss = np.random.normal(0.0, 4.0, (IMG_SIZE, IMG_SIZE, IMG_CHANNELS))
gauss = gauss.reshape(IMG_SIZE, IMG_SIZE, IMG_CHANNELS).astype(np.float)
result = float_img + gauss
... | 0e5f5a83f7017d48e083a35bcb22cdf50ebb1006 | 7,057 |
from re import T
def argsort(x: T.FloatTensor, axis: int = None) -> T.LongTensor:
"""
Get the indices of a sorted tensor.
If axis=None this flattens x.
Args:
x: A tensor:
axis: The axis of interest.
Returns:
tensor (of ints): indices of sorted tensor
"""
if axis ... | 57e2e4d8c5a870c4ea382a02e19d0451dbe90704 | 7,058 |
def dirPickledSize(obj,exclude=[]):
"""For each attribute of obj (excluding those specified and those that start with '__'),
compute the size using getPickledSize(obj) and return as a pandas Series of KBs"""
return pd.Series({o:getPickledSize(getattr(obj, o))/1024. for o in dir(obj) if not np.any([o[:2]=='_... | d27b404f8c637aa7dd230126d3dbe9112240112c | 7,059 |
from typing import Any
def audit_log() -> Any:
"""
List all events related to the connected member.
"""
if "member_id" not in session:
abort(404)
return render_template(
"audit_log.html",
full_audit_log=fetch_audit_log(session["member_id"]),
) | a5c95ac9c7e55212f8e308a9bf141468dc3a7626 | 7,060 |
def load_comparisonXL(method, evaluate="train", dropna=True):
"""Load comparison table."""
if evaluate == "test":
e = "['Test']"
elif evaluate == "in bag":
e = "['In Bag']"
elif evaluate == "out of bag":
e = "['Out of Bag']"
else:
e = "['Train']"
# Import methods... | 56ff4d8c74ec88fc8b2f245706b7cf039334a76f | 7,061 |
def verify_user_password(user: User, password: str) -> bool:
"""Verify User's password with the one that was given on login page."""
return pwd_context.verify(password, user.password) | 43b25118e5ef3b89622acd7aa3276a1b18352674 | 7,062 |
def __valid_ddb_response_q(response):
"""private function to validate a given DynamoDB query response."""
if 'ResponseMetadata' in response:
if 'HTTPStatusCode' in response['ResponseMetadata']:
if response['ResponseMetadata']['HTTPStatusCode'] == 200:
return True
return F... | f4e71c4f5d058ba20013b3a405ffeff637e03ae8 | 7,063 |
def GetPipelineResultsPathInGCS(artifacts_path):
"""Gets a full Cloud Storage path to a pipeline results YAML file.
Args:
artifacts_path: string, the full Cloud Storage path to the folder containing
pipeline artifacts, e.g. 'gs://my-bucket/artifacts'.
Returns:
A string representing the full Cloud ... | 83b7c15f00679ff201c9a8b155102f36bb8e685c | 7,064 |
def Pnm_p(n, m, x):
"""Eq:II.77 """
return lpmn(m, n, x)[1][-1, -1] | 027cb169263853ede6d29a6760da981d30ef950b | 7,065 |
def _remove_empty_subspace(subspaces, n_clusters, m, P, centers, labels, scatter_matrices):
"""
Check if after rotation and rearranging the dimensionalities a empty subspaces occurs. Empty subspaces will be
removed for the next iteration. Therefore all necessary lists will be updated.
:param subspaces: ... | 473a509860b9708ee217f4f7b0a2718d1a3a7d7e | 7,066 |
def _get_citekeys_action(elem, doc):
"""
Panflute action to extract citationId from all Citations in the AST.
"""
if not isinstance(elem, pf.Citation):
return None
manuscript_citekeys = global_variables["manuscript_citekeys"]
manuscript_citekeys.append(elem.id)
return None | 74dec7a972f38c34040dc430b0c130b2a76784c2 | 7,067 |
def average_gradients(tower_grads):
"""Calculate the average gradient for each shared variable across all towers.
Note that this function provides a synchronization point across all towers.
Args:
tower_grads: List of lists of (gradient, variable) tuples. The outer list
is over individual gra... | da85dee074f5bb15a13ea3d2c2fe105469c1ee90 | 7,068 |
def compute_neighbours_probability_matrix(n_matrix, src, d_matrix, sigma_neigh):
"""Compute neighbours' probability matrix.
Parameters
-----------
n_matrix : :py:class:`~numpy.ndarray` of :py:class:`~int`, shape (n_verts, n_neigh_max)
The sets of neighbours.
src : :py:class:`~numpy.ndarray... | 2651ad650697266d7e0db5fdc55e176334fc3cb8 | 7,069 |
def ar_cosmap(inmap):
"""
Get the cosine map and off-limb pixel map using WCS.
Generate a map of the solar disk that is 1 at disk center and goes radially outward as the cos(angle to LOS), which
is = 2 at 60 degrees from LOS.
Other outputs:
- rrdeg: gives degrees from disk center
- offlimb: ... | 4365b0ef1134f117e5bc3396239cc1ba174f5009 | 7,070 |
def as_array(request: SubRequest) -> bool:
"""
Boolean fixture to support ExtensionDtype _from_sequence method testing.
"""
b = request.param
assert isinstance(b, bool)
return b | 7a8b627769b8955ad4162a30be5ddc9b0ee76723 | 7,071 |
def gram_matrix(x):
"""Create the gram matrix of x."""
b, c, h, w = x.shape
phi = x.view(b, c, h * w)
return phi.bmm(phi.transpose(1, 2)) / (c * h * w) | 11de97b67f3f8ecb7d7d009de16c1a5d153ab8ff | 7,072 |
def open_file(path, mode):
"""
Attempts to open file at path.
Tried up to max_attempts times because of intermittent permission errors on Windows
"""
max_attempts = 100
f = None
for _ in range(max_attempts):
try:
f = open(path, mode)
except PermissionError:
... | 9217a1b66b2bb30895fe445fa4a50b5da5466391 | 7,074 |
import requests
import json
def get_sts_token(current_refresh_token):
"""
Retrieves an authentication token.
:param current_refresh_token: Refresh token retrieved from a previous authentication, used to retrieve a
subsequent access token. If not provided (i.e. on the initial authenticati... | b41c6658a4eb218771d6e908411ba3b54e4e13f3 | 7,075 |
async def device_climate_fan(device_climate_mock):
"""Test thermostat with fan device."""
return await device_climate_mock(CLIMATE_FAN) | 1143adceacb610d18e1a26df4e24f715eb68917f | 7,076 |
def make_training_config(args):
""" Create training config by parsing args from command line and YAML config file, filling the rest with default values.
Args
args : Arguments parsed from command line.
Returns
config : Dictionary containing training configuration.
"""
# Parse the configuration file.
config = {... | 1902e0999336249a7feda1f0aa415f7d148a16ee | 7,077 |
from typing import Tuple
def _crown_relu_relaxer(inp: Bound) -> Tuple[LinFun, LinFun]:
"""Obtain the parameters of a linear ReLU relaxation as in CROWN.
This relaxes the ReLU with the adaptive choice of lower bounds as described
for CROWN-ada in https://arxiv.org/abs/1811.00866.
Args:
inp: Input to the ... | 7e43e973adb65089a2eb35665c219911fc409446 | 7,078 |
import torch
import time
def run_single_measurement(model_name, produce_model, run_model, teardown, inp, criterion, extra_params, use_dtr, use_profiling):
"""
This function initializes a model and performs
a single measurement of the model on the given input.
While it might seem most reasonable to in... | a3765a88ccb10b3f0322f11f8205ecfdb7f98f38 | 7,079 |
def make_noise(fid, snr, decibels=True):
"""Given a synthetic FID, generate an array of normally distributed
complex noise with zero mean and a variance that abides by the desired
SNR.
Parameters
----------
fid : numpy.ndarray
Noiseless FID.
snr : float
The signal-to-noise ... | 823c9fee2c1a696a38b6a27406f51a27185460c1 | 7,080 |
def viterbi(prob_matrix):
""" find the most likely sequence of labels using the viterbi algorithm on prob_matrix """
TINY = 1e-6 # to avoid NaNs in logs
# if prob_matrix is 1D, make it 2D
if len(np.shape(prob_matrix)) == 1:
prob_matrix = [prob_matrix]
length = len(prob_... | 50b28dcf7cedc75adb4a41cb9ccf2152af5f4b8f | 7,081 |
def slsn_constraint(parameters):
"""
Place constraints on the magnetar rotational energy being larger than the total output energy,
and the that nebula phase does not begin till at least a 100 days.
:param parameters: dictionary of parameters
:return: converted_parameters dictionary where the viola... | 9fd4cc37c783aa1afdc816edbc88c45132fb4026 | 7,082 |
def grover_circuit(n,o,iter):
"""Grover Search Algorithm
:param n: Number of qubits (not including ancilla)
:param o: Oracle int to find
:return qc: Qiskit circuit
"""
def apply_hadamard(qc, qubits,a=None) -> None:
"""Apply a H-gate to 'qubits' in qc"""
for q in qubits:
... | fac61eda28a249e333dabd46c7d404603141c07c | 7,083 |
def reference_cluster(envs, in_path):
"""
Return set of all env in_paths referencing or
referenced by given in_path.
>>> cluster = sorted(reference_cluster([
... {'in_path': 'base', 'refs': []},
... {'in_path': 'test', 'refs': ['base']},
... {'in_path': 'local', 'refs': ['test']... | 6398705dfb63c30de62b2eb900d88612e5144774 | 7,084 |
def scheme_apply(procedure, args, env):
"""Apply Scheme PROCEDURE to argument values ARGS in environment ENV."""
if isinstance(procedure, PrimitiveProcedure):
return apply_primitive(procedure, args, env)
elif isinstance(procedure, UserDefinedProcedure):
new_env = make_call_frame(procedure, a... | 14879f29a5e8c3c5b7d4d41be35730eb66dbdc66 | 7,085 |
def _validate_num_clusters(num_clusters, initial_centers, num_rows):
"""
Validate the combination of the `num_clusters` and `initial_centers`
parameters in the Kmeans model create function. If the combination is
valid, determine and return the correct number of clusters.
Parameters
----------
... | 67d0be234a97c33eb742c70e8d6bb30be4608ab2 | 7,086 |
import mimetypes
def urlinline(filename, mime=None):
"""
Load the file at "filename" and convert it into a data URI with the
given MIME type, or a guessed MIME type if no type is provided.
Base-64 encodes the data.
"""
infile = open(filename, 'rb')
text = infile.read()
infile.close()
... | 4b8035944a7a25d5b3ce3bc8a8fbd0a4dd424447 | 7,087 |
def star_rating(new_rating=None, prev_rating=None):
"""
Generates the query to update the product's star ratings. Inc method is
from https://docs.mongodb.com/manual/reference/operator/update/inc/
"""
add_file = {
1: {"one_star": 1},
2: {"two_stars": 1},
3: {"three_stars": 1},... | e50f8271dbbb8c2722729cce6a8f036c851c4e95 | 7,089 |
def check_encoder(value: EncoderArg) -> EncoderFactory:
"""Checks value and returns EncoderFactory object.
Returns:
d3rlpy.encoders.EncoderFactory: encoder factory object.
"""
if isinstance(value, EncoderFactory):
return value
if isinstance(value, str):
return create_encode... | 5e23b483df8fbe190f1ac6ccf743bc783728adf8 | 7,090 |
import pathlib
def allowed_task_name(name: str) -> bool:
"""Determine whether a task, which is a 'non-core-OSCAL activity/directory is allowed.
args:
name: the task name which is assumed may take the form of a relative path for task/subtasks.
Returns:
Whether the task name is allowed or ... | 231d7a98f5d6b7059f5517283ec3bed35264050e | 7,091 |
def get_ignored_classes(uppercase, lowercase, digit):
"""
get tuple of ignored classes based on selected classes
:param
uppercase: whether to keep uppercase classes
:param
lowercase: whether to keep lowercase classes
:param
digit: whether to keep digit classes
:return:
... | 2a2380f4f984feb42ce1de912739fd395a8422bd | 7,092 |
import torch
def unscaled_prediction_rmse(model, input_tensor, label_tensor, scalar, loading_length=0, return_loading_error=False,
device=None):
"""
Prediction RMSE.
:param model: model
:param input_tensor: input tensor
:param label_tensor: label tensor
:param sc... | ea7b0e2c2fd022cc7bcb466057feacf5a1fbaa00 | 7,093 |
import copy
def __copyList__(fromList, initialValues = None):
"""
Returns a copy of the provided list. Initial values must either be a single value, or
a list of exactly the same size as the provided list.
"""
if __isListType__(fromList) is False:
raise ValueError('The provided value to co... | 9f126a10795132b5d2ddaeef552c6e5abd8680ba | 7,094 |
import re
def build_or_pattern(patterns, escape=False):
"""Build a or pattern string from a list of possible patterns
"""
or_pattern = []
for pattern in patterns:
if not or_pattern:
or_pattern.append('(?:')
else:
or_pattern.append('|')
or_pattern.append(... | 225cc20504a85342694e14ea76b9bf3ed8b6d11b | 7,095 |
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