content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def piece_together_fourth(Dp, Wp):
"""
Take the skew and symmetric parts of a algorithmic tangent and piece them back together
"""
sym_id = 0.5*(np.einsum('ik,jl', np.eye(3), np.eye(3)) + np.einsum('jk,il', np.eye(3), np.eye(3)))
skew_id = 0.5*(np.einsum('ik,jl', np.eye(3), np.eye(3)) - np.einsum('jk,il', n... | fc386d688f0e571b3b184621885be100b5cd2306 | 3,625,005 |
def to_ragged_seq_set(data):
"""Convert dataset from mapping/array of sequences
to lists of mappings of sequences."""
# data is a dict
if is_mapping(data):
new_data = {}
for name, datum in data.items():
if not is_sequence_set(datum):
# all sequences must at le... | 5b8cce9846d861c564a23a77fe8a7ae03e3cdf8a | 3,625,006 |
def get_atoms_list(mmtf_dict):
"""Creates a list of atom dictionaries from a .mmtf dictionary by zipping
together some of its fields.
:param dict mmtf_dict: the .mmtf dictionary to read.
:rtype: ``list``"""
return [{
"x": x, "y": y, "z": z, "alt_loc": a or None, "bvalue": b, "occupancy": o,
... | 3b5f29362c077585ebc659b8d8a9ff5d60908ead | 3,625,007 |
import traceback
def register_augmentation(name):
"""Registers an augmentation.
This decorator allows vertview to instantiate an augmentation
from a configuration file. To use it, apply this decorator to an
AugmentationBase2D subclass, like this:
.. code-block:: python
@register_augmentation(... | 601ea1df05997ba46687d4e8e828be1254c3b29d | 3,625,008 |
def get_os_fingerprint(data):
"""
Get the most accurate OS fingerprint for the given Data object, if any.
:param data: Data object to query.
:type data: Data
:returns: Most accurate OS fingerprint.
If no fingerprint is found, returns None.
:rtype: OSFingerprint | None
"""
# Ge... | baca5b40cff177d8534f68d2334698852937caf2 | 3,625,009 |
def ring(symbols, domain, order=lex):
"""Construct a polynomial ring returning ``(ring, x_1, ..., x_n)``.
Parameters
==========
symbols : str, Symbol/Expr or sequence of str, Symbol/Expr (non-empty)
domain : :class:`~diofant.domains.domain.Domain` or coercible
order : :class:`~diofant.polys.po... | d26eaf26d2b4c87c5b6e70d87dbf0b4bae80aace | 3,625,010 |
def trimesh_swap_edge(mesh, u, v, allow_boundary=True):
"""Replace an edge of the mesh by an edge connecting the opposite
vertices of the adjacent faces.
Parameters
----------
mesh : :class:`compas.datastructures.Mesh`
Instance of mesh.
u : int
The key of one of the vertices of ... | 43f150bb52b1f4a9180f6c40a9d420fbe5e67e30 | 3,625,011 |
def perc_col_nans(col):
"""
Returns the percent of NaNs of a specific column in the dataset.
Parameters:
col (pandas Series): Column in the dataset
Returns:
col_perc_nans (float): Percent of NaNs in col
"""
col_perc_nans = count_col_nans(col) / len(col)
return... | 66db913b1299a280e867ff05bd8e438c25c03861 | 3,625,012 |
def get_string(key):
"""
Get localized string. First, try language as set in config. Then, try English locale. Else - raise an exception.
:param key: string name
:return: localized string
"""
lang = strings.get(Config.BOT_LANGUAGE)
if not lang:
if not strings.get("en"):
... | 90089fbe8bbbdfc0f1aa6560197489cbfb76f41a | 3,625,014 |
def prompt_vial_range():
"""Prompt user for first and last vial of run"""
first_ic_vial = int(input('First IC vial? '))
last_ic_vial = int(input('Last IC vial? '))
return first_ic_vial, last_ic_vial | bf5cf536c0aae3808bf16dd6d87a9d83bfbdab04 | 3,625,015 |
from collections import defaultdict
def getFollowupPhotometry(candidate, djangoRawObject = None, conn = None):
"""Use the query followupPhotometryQuery but organise the data for plotting"""
# We need to create a dictionary of filters which contain arrays of the data.
# It's messy to do this from scratch,... | d4f496360cdfde82f4dc81bb199374606929137f | 3,625,017 |
def generate_random_map(
size=6, p=0.7, num_pseudo_rewards=0, only_optimal_pseudo_rewards=True
):
"""Generates a random valid map (one that has a path from start to goal)
:param size: size of each side of the grid
:param p: probability that a tile is empty
:param num_pseudo_rewards: number of tiles ... | b50ce1575e0b8715b0ac4f271f3cf741e8a22b6f | 3,625,018 |
def approx_count_distinct(col, rsd=None):
"""Returns a new :class:`Column` for approximate distinct count of ``col``.
>>> df.agg(approx_count_distinct(df.age).alias('c')).collect()
[Row(c=2)]
"""
sc = SparkContext._active_spark_context
if rsd is None:
jc = sc._jvm.functions.approx_count... | 7e7736db6c1ecf7d7b2476fd13f5698498aa3cff | 3,625,019 |
def private_mean(x, epsilon, sum_sensitivity):
"""
Computes a private mean with privacy budget epsilon using the given
sensitivity.
:param x: Vector over which the mean will be computed.
:param epsilon: The privacy budget.
:param sum_sensitivity: The sensitivity of the sum calculation.
:ret... | 3b400c17e1fa9b899d1b322291459724cd6cece8 | 3,625,021 |
from vtk import vtkImageData
def make_child_dataset(dataobject):
"""Creates a child dataset with the same size as the reference_dataset.
"""
new_child = vtkImageData()
new_child.CopyStructure(dataobject)
input_spacing = dataobject.GetSpacing()
# For a reconstruction we copy the X spacing from ... | a7e460f21564559f4731df76c978eac3a951dbe7 | 3,625,022 |
def calc_residuals(Amat,Bvec,coeffs,perconf=False):
"""Calculate residuals and other performance metrics"""
residuals = []
matmul = Bvec - Amat*coeffs
residuals = matmul*627.51
r2 = 1-sum(residuals**2)/sum((Bvec*627.51)**2)
rel_MAE = sum(abs(residuals))/sum(abs(Bvec*627.51))
if perconf:
... | fbeb72688f4e58dcca85b425be2ef0460a3cfcac | 3,625,023 |
def bucket_by_sequence_length(data_reader,
example_length_fn,
bucket_boundaries,
bucket_batch_sizes,
trainer_nums,
trainer_id):
"""Bucket entries in dataset by lengt... | 4adfe4f0780b4e97934b6715ab9227e3647a2592 | 3,625,024 |
from typing import Any
from typing import Dict
def get_overridable_parameters(config: Any) -> Dict[str, param.Parameter]:
"""
Get properties that are not constant, readonly or private (eg: prefixed with an underscore).
:param config: The model configuration
:return: A dictionary of parameter names an... | 9dbe89416d4dd0f232f3f714fc652bcb18ec80cc | 3,625,025 |
def compute_score(sent, sents):
"""Computes the average score of sent vs the other sentences (the result of
sent vs itself isn't counted because it's 1, and that's above
UPPER_BOUND)"""
if not len(sent):
return 0
return sum(compare_sents_bounded(sent, sent1) for sent1 in sents) / float(
... | ba3e0a16551daba922e87de6698f8e95494b01cd | 3,625,026 |
def computeCentroids(X, idx, K):
"""
returns the new centroids by
computing the means of the data points assigned to each centroid. It is
given a dataset X where each row is a single data point, a vector
idx of centroid assignments (i.e. each entry in range [1..K]) for each
example, and K, the n... | d21a5acd3ba481a9864a016dcfe79b629147f788 | 3,625,027 |
def async_track_time_interval_backoff(hass, action, intervals) -> CALLBACK_TYPE:
"""Add a listener that fires repetitively at every timedelta interval."""
if not iscoroutinefunction:
_LOGGER.error("Action needs to be a coroutine and return True/False")
return
if not isinstance(intervals, (l... | be7d3619b9ddc8336251fb50196a74ab9f58c36b | 3,625,028 |
import shlex
def grr_grep(line):
"""Greps for a given content of a specified file.
Args:
line: A string representing arguments passed to the magic command.
Returns:
A list of buffer references to the matched content.
Raises:
NoClientSelectedError: Client is not selected to perform this operatio... | 28c771f12d162e667009241cdba2f2e485736599 | 3,625,029 |
def convertMCFOSTdataToJy(data, wavelength, spatialUnit = 'arcsec', spatialResolution = None):
"""Convert data in MCFOST units into Jansky/pixel or Jansky/arcsec^2:
Input: data: 2D array, MCFOST-generated data.
wavelength: float, wavelength of the data to be converted in micron.
spatial... | 20e493989513e4e08e9211f7a6f7d606817aaa44 | 3,625,030 |
def defaults(dict=None):
"""
Adds a set of default values to the settings registry. These can and will be updated
by any settings modules in effect, such as the Settings Manager.
If dict is None, it'll return the current defaults.
"""
if dict:
_defaults.update(dict)
else:
re... | 8b7423d0fdbbd522a01e04cd77e6aca863951e9a | 3,625,031 |
def send_email(email_subject, recipient, message, config = None):
"""Send an email using SendGrid."""
try:
config = current_app.config
except:
config = config
sender = sendgrid.SendGridClient(config['SENDGRID_API_KEY'])
email = sendgrid.Mail()
email.set_subject(email_subjec... | 18c20e086ddacc719898f2ad3e3a03f5c560d0fb | 3,625,033 |
import wsgiref
def simulate_request(app, method='GET', path='/', query_string=None,
headers=None, content_type=None, body=None, json=None,
file_wrapper=None, wsgierrors=None, params=None,
params_csv=False, protocol='http', host=helpers.DEFAULT_HOST,
... | 15950c9b880ac791454bd64becf176aec0ab4d99 | 3,625,035 |
def rcnn_encode(bboxes, targets):
"""
:param bboxes: (N, 4) bounding boxes of [x0, y0, x1, y1]
:param targets: (N, 4) target ground truth boxes of [x0, y0, x1, y1]
:return: deltas
"""
bw = bboxes[:, 2] - bboxes[:, 0] + 1.0
bh = bboxes[:, 3] - bboxes[:, 1] + 1.0
bx = bboxes[:, 0] + 0.5 *... | 919395705dd20e6872fac21ab8abf52a04ff8167 | 3,625,036 |
def mera_ansatz_parameters(num_qubits, depth, value):
"""Returns a Parameters object for the MERA Tensor network ansatz.
Args:
num_qubits : int
Number of qubits in the parameterized circuit.
depth : int [must equal log2(num_qubits)]
Number of "hyperlayers" in MERA netwo... | 8e491189527a95686c99a10da1527ec321c48036 | 3,625,039 |
def gaussianfilter(N, alpha, Ts, Fs):
"""
Generates a gaussian filter (FIR) impulse response.
Parameters
----------
N : int
Length of the filter in samples.
alpha: float
Roll off factor (Valid values are [0, 1]).
Ts : float
Symbol period in seconds.
... | 8f3ce2f3aa155dcf3163f6a252b98aa506137013 | 3,625,040 |
def minimal_copy(ds: Dataset) -> Dataset:
"""Make reduced copy with only the attributes needed for a QueryResult"""
res = Dataset()
for attr in chain.from_iterable(chain(req_elems.values(), opt_elems.values())):
val = getattr(ds, attr, None)
if val is not None:
setattr(res, attr,... | f0df04aa6e1a5447b7e6caf0a489cc89a7de9423 | 3,625,041 |
import numpy as np
import io
import torch
def read_txt_embeddings(logger, path):
"""
Reload pretrained embeddings from a text file.
"""
word2id = {}
vectors = []
# load pretrained embeddings
# _emb_dim_file = params.emb_dim
_emb_dim_file = 0
with io.open(path, 'r', encoding='utf-8', newline='\n', e... | 1d7cc0845488bb3bd37eef4ca0cdeff67787f6e8 | 3,625,042 |
def corrected_chance(clustering1, clustering2, measure='jaccard_index',
random_model='perm', norm_type='sum', n_samples=100):
"""
This function calculates the adjusted Similarity for one of six random
models.
.. note:: Clustering 2 is considered the gold-standard clustering for one... | 86505ed8eeb38decb551fa77cbec00b8ba9d16f1 | 3,625,043 |
def update_account():
"""Update account settings."""
form = AccountSettingsForm(request.form)
if form.validate():
if 'user_id' not in request.form:
return jsonify({'success': False,
'error': 'ID not found in edit!'})
edit_id = paranoid_clean(request.fo... | 247d60dbf333f7ed162b091c485e9bffe8418062 | 3,625,044 |
def make_weighted_loss(loss_fn, weight=1.0):
""" Adapts the given loss function by multiplying by a given constant.
Parameters
----------
loss_fn: a function to create the loss
weight: the value by which to weigh the loss.
Returns
-------
fn: The adapted loss
"""
def fn(*args, ... | bfe235e012cc134b98b5d995935327b11bba8651 | 3,625,045 |
def create_differences_matrix(rows, cols):
"""
Creates the central differences matrix A for an n by m shaped grid
"""
n = rows*cols
M = np.zeros((n,n))
for r in range(rows):
for c in range(cols):
i = r*cols + c
# Two inner diagonals
if c > 0: M[i-1,i] ... | ea199ed8fb3f33e4e059d5748d347a46dc78d7d7 | 3,625,046 |
def isvalid_corr(corrmat):
"""
Check if
1. corrmat is symmetric
2. off-diagonal values in [-1, 1]
3. diagonal values = 1
4. the matrix is positive semidefinite.
@param corrmat: numpy nxn ndarray
@return: CorrDiagnostics object ---> evaluates to True if corrmat is valid and False otherwi... | 6f2509daaf9901d3b35841bda08dd062d2b1caa1 | 3,625,047 |
def multi_JMI(X, y, is_disc, cost_vec, cost_param_vec,
num_features_to_select = None, random_seed = 123, num_cores = 1):
""" Cost-based JMI feature ranking with multiple penalization parameters.
Function to obtain the rankings associated to different cost parameters,
with the filter featu... | 8e0f641d89b07548fde555225ff9c2dad094e484 | 3,625,048 |
def arcsin(x):
"""
Compute the inverse sine of x.
Return the "principal value" (for a description of this, see
`numpy.arcsin`) of the inverse sine of `x`. For real `x` such that
`abs(x) <= 1`, this is a real number in the closed interval
:math:`[-\\pi/2, \\pi/2]`. Otherwise, the complex princi... | 6692bb51b5347ab77d2d12969a8fc98ccc43ac62 | 3,625,049 |
def run_queued(fn, params, processes=1, queued_params=None, logging_level=None):
"""
Same as run_function, but the function should be such that it accepts a
parameter queue and reads its inputs from there; params still contains
options for the function.
If logging_level is not None, a QueueHandler ... | bef4ae414bbe8787ef6c606c5391a49832aa0e90 | 3,625,050 |
import signal
def ExtractFrequencyTime(data, bands):
"""Computes the spectrogram of data, and the takes the sum of frequencies inside the band range.
"""
bands_results = {'all_spec':[], 'alpha':[], 'beta1':[], 'beta2':[], 'beta3':[]}
f, t, Sxx = signal.spectrogram(data,window = 'hamming', fs = 500,n... | 1ebf9e9a39d34d6a1657c6a2c440996e1ba88302 | 3,625,051 |
from typing import Any
from typing import List
def ensure_list(data: Any) -> List:
"""Ensure input is a list.
Parameters
----------
data: object
Returns
-------
list
"""
if data is None:
return []
if not isinstance(data, (list, tuple)):
return [data]
ret... | 58016feaf49d63255944fa615e7e2e1dac6dcc76 | 3,625,052 |
def decode_logistic_mixture(
targets, means, log_scales, logit_probs_softmax, # CDF
input_string):
"""
NOTE: This function uses either the CUDA or CPU backend, depending on the device of the input tensors.
NOTE: targets, means, log_scales, logit_probs_softmax must all be on the same device ... | 66ad78e22a538c788729bdbd1bb6a74a88d24be3 | 3,625,053 |
def _match_up_provided_args_with_field_defs(field_defs, args, kwargs):
"""
Returns a list of provided values, aligned with the field definitions. Missing values are represented using the NVP
(No Value Provided) token (as None can be a valid provided value).
"""
values = [NVP] * len(field_defs)
... | 440b218e3bde552a10890304278ef9604d8f988b | 3,625,054 |
def var_recode(TEDS_A_Imputed, user_target, TEDS_Af):
"""Recodes categorical variables present in the data.
Returns
A recoded data frame."""
# Identify the variable types
col_list = list(TEDS_A_Imputed.columns)
col_list_cat = [s for s in col_list if s != 'CASEID' and s != 'ADMY... | cc656e9a6840af4d95a6a114073459d815c533dc | 3,625,055 |
def get_cannonical(group):
"""
For each variant, that is unique combination of #CHROM, POS, REF, ALT, it keeps CANONICAL transcript annotations.
If more than consequence type is annotated, it keeps the most damaging or severe either if there is more than one
entry (row) per variant or either is coma-sep... | 31417a30fbfb7800dfdd46352ea9f9e5763be3e3 | 3,625,056 |
def get(blob_key):
"""Gets a `BlobInfo` record from blobstore.
Does the same as `BlobInfo.get`.
Args:
blob_key: The `BlobKey` of the record you want to retrieve.
Returns:
A `BlobInfo` instance that is associated with the provided key or a list
of `BlobInfo` instances if a list of keys was pro... | 03c3fe9da40c2986ccce19b62e99c07abe49cbd0 | 3,625,057 |
def init_split(df, featname, init_bins=100):
"""
对df下的featname特征进行分割, 最后返回中间的分割点刻度
为了保证所有值都有对应的区间, 取两个值之间的中值作为分割刻度
注意这里的分割方式不是等频等常用的方法, 仅仅是简单地找出分割点再进行融合最终进行分割
注意, 分出的箱刻度与是否闭区间无关, 这个点取决于用户,这个函数仅考虑分箱的个数
同时, 分箱多余的部分会进入最后一个箱, 如101个分100箱, 则最后一个箱有两个样本
Parameters:
----------
df: dataframe,... | 172f48bb019fd4cf4941b2ff0fefcb24709fe7a4 | 3,625,059 |
def dist_of_entity_k(adjacency_dict: dict, levels_dict: dict, c_k: dict, c_notk: dict) -> int:
"""
Performs the final iterations of the algorithm proposed in the Alternative Geographic Spine document to find
the "off spine entity distance" (OSED), which is the number of geounits that must be added or subtra... | 787466d3de923fa495d93794823c6b0d51c22f5b | 3,625,061 |
import tkinter
def repr_content_and_tags(text_widget: tkinter.Text) -> str:
"""Represent the content, indices and the tag starts and ends as a text table."""
tbl = prettytable.PrettyTable()
tbl.field_names = ["Index", "Char", "Tag starts", "Tag ends"]
for index, character, tag_starts, tag_ends in en... | 534c1642d77f0229322a1065b237c65e6b0ccf5c | 3,625,062 |
def isotropic_twirl_state(X, d):
"""
Applies the twirling channel
X -> ∫ (U ⊗ conj(U))*X*(U ⊗ conj(U)).H dU
to the input operator X acting on two d-dimensional systems.
For d=2, this is equivalent to
X -> (1/24)*sum_i (c_i ⊗ conj(c_i))*X*(c_i ⊗ conj(c_i)).H
where the unitaries c... | 5ff32bb3b4c6b2671e9acb8d7963683bcc3c3261 | 3,625,064 |
from functools import reduce
def flatten_index(builder, index, const_shape):
"""Converts N-dimensional index into 1-dimensional one.
index is of a form ``(i0, i1, ... iN)``, where *i* is ValueRefs
holding individual dimension indices.
First dimension is considered to be variable. Given array shape
... | 2864701c5e3d0263d82fd585ad9d77c7c584ea2b | 3,625,065 |
def init_conds(MdiscI, P):
"""
Function to convert a disc mass from solar masses to grams and an initial spin
period in milliseconds into an angular frequency.
:param MdiscI: disc mass - solar masses
:param P: initial spin period - milliseconds
:return: an array containing the disc mass in grams and th... | 612411a3fad7f41309858f20e9aefad16904e16e | 3,625,066 |
from bs4 import BeautifulSoup
def fetch_feed() -> list[RenjiData]:
"""
Get news feed from renji.com
"""
logger.info("Start fetching info from renji.com ...")
res = urlopen("https://www.renji.com/default.php?mod=article&fid=38")
logger.info("Info fetched. Parsing ...")
soup = BeautifulSoup(... | 14cc274b17de03266626166592ae65e88bd54286 | 3,625,067 |
from typing import Optional
def get_me_ssh_key(key_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetMeSSHKeyResult:
"""
Use this data source to retrieve information about an SSH key.
## Example Usage
```python
import pulumi
import pul... | fe957f701869608e818092e22f08dcb0e6d8b27d | 3,625,068 |
import numpy
def gower_distance_numpy(point1, point2, max_range):
"""!
@brief Calculate Gower distance between two vectors using numpy.
@param[in] point1 (array_like): The first vector.
@param[in] point2 (array_like): The second vector.
@param[in] max_range (array_like): Max range in each data di... | b97c40cd62654172b0d502e35bbef8ce9e9175c5 | 3,625,069 |
def is_fix_only_distro(distro_name: str) -> bool:
"""
Does the given distro's security feed/db support vulnerability records before a fix is available?
:param distro_name:
:return: bool
"""
return distro_name in FIX_ONLY_DISTROS | 35eaf42b7111a3ddcec11dd351a7d00378607f86 | 3,625,070 |
def step_f(z: np.ndarray, scale: float, loc: float) -> np.ndarray:
"""
:param z: z-dimension
:param scale: width of step function, always 0
:param loc: position of step
:return: positioned step function
"""
new_z = z - loc
f = np.ones_like(new_z) * 0.5
f[new_z <= -scale] = 0
... | f94d0f18aa0805f6e0739927f88517c9e70a802a | 3,625,071 |
def build_SVM(X_train, y_train, kernel_):
"""
The function builds SVM
"""
scaler = StandardScaler()
X_train_std = scaler.fit_transform(X_train)
""" for i in range(1, 5):
svc = SVC(kernel=kernel_, random_state=0, gamma=i)
model = svc.fit(X_train_std, y_train.values.ravel())
... | a3ced31185a224b79366d44e3b2ce02f334f7ed6 | 3,625,072 |
def status(args: tuple[str]) -> list[res.Response]:
"""Batch `git status` command."""
return _call_git_use_case("status", args) | 855160c530f606535956b5decf766b32abdbeb4d | 3,625,073 |
def get_worker(project, object_id=None, global_id=None, user_id=None):
""" Gets the identified worker. Exactly one form of identification should be provided.
:param project:
:param object_id: The worker's OBJECTID.
:param global_id: The worker's GlobalID.
:param user_id: The worker'... | bff455591f48c7a45f387364c13b1d6e70c5196d | 3,625,074 |
import xml
import re
def xml_to_string(elem, pretty=False):
"""
Returns a string from an xml tree.
"""
try:
if elem is not None:
if PY2:
xml_str = ElementTree.tostring(elem, encoding='utf-8')
else:
xml_str = ElementTree.tostring(elem, enc... | 55d385a55d8cc998470b19286460267d24ddd26a | 3,625,075 |
from typing import Type
from typing import Optional
from typing import List
def build_config(
config_file: str,
task_cls: Type[GeneralizedRCNNTask],
opts: Optional[List[str]] = None,
) -> CfgNode:
"""Build config node from config file
Args:
config_file: Path to a D2go config file
o... | 5387bf56461c3ad1c71bf25592abd5c77ab4b43c | 3,625,076 |
def get_learner(config_args, train_loader, val_loader, test_loader, start_epoch, device):
"""
Return a new instance of model
"""
# Available models
learners_factory = {
"default": DefaultLearner,
"selfconfid": SelfConfidLearner,
"oodconfid": OODConfidLearner,
}
... | 71e566ac47f78598d9ea3e9a79bb0f3c5f9e0276 | 3,625,079 |
def localHomologyMultiproc(
k, cplx, numProcs, localSimplices=None, iterate=True, rankOnly=False
):
"""Compute local homology relative to the star over a list of simplices in parallel"""
if localSimplices is None:
localSimplices = []
for ki in range(k + 1):
localSimplices += ksi... | de3998fc755b8c002e960bf0cfd5b28ec9150426 | 3,625,080 |
def text_repr(diffs):
"""
Helper function to dump xml elements into plain string form for the sake of comparison.
It also get rid of all attributes in xml elements if any.
"""
return {change_type:[etree.tostring(elem.attrib.clear() or elem).decode('utf-8') for elem in elems]
for change_t... | 9e9e2b6b4fff642bb82278642b9c6ea02d0519b3 | 3,625,081 |
import json
def search_nlucell():
"""Search NluCell 搜索问答节点
Get：返回所有问答节点
POST：返回所有包含搜索关键词的问答节点
"""
data = {
'skb': database.skb,
'result': []
}
state = {
'success' : 0,
'message' : "请先选择知识库再搜索节点"
}
if not database.skb:
return json.dumps(state)... | 7a398ce5dddf9e6f2f5fe82b475eef7eba32b2cb | 3,625,083 |
def generate_gate_swap_mat() -> np.ndarray:
"""Return the Hilbert-Schmidt representation matrix for a SWAP gate with respect to the orthonormal Hermitian matrix basis with the normalized identity matrix as the 0th element.
The result is a 16 times 16 real matrix.
Parameters
----------
Returns
... | df86f8ef3c2e4321695a87822a063ebee5c4f27c | 3,625,084 |
def can_register(extra, password_meta):
"""
:param extra: {str: any?}, additional fields that the user will fill out when registering such as gender and birth.
:param password_meta: {'count': int, 'count_number': int, 'count_uppercase': int, 'count_lowercase': int,
'count_special'... | a6ba8cc6fc4a4180bbbceb9a8ae14b07d7dad809 | 3,625,086 |
def cross_entropy(output, target):
"""Calculate Cross-entropy loss."""
return F.cross_entropy(input=output, target=target) | e836dd4d0dbae597932aa3265a92776b7a032ccb | 3,625,087 |
def plate_to_genesift_sequencing_order_spreadsheet(plate, output_file,
sample_name_function,
well_filter=None,
direction='row'):
"""Generate an excel spreadsheet f... | bd317bd535bfa1e465ee0e0df6a020d299e83789 | 3,625,088 |
def hours_of_daylight(date, axis=23.44, latitude=39.87):
"""Compute the hours of daylight for the given date"""
#date = datetime.strptime(start_time, "%Y-%m-%d")
diff = date - pd.datetime(2000, 12, 21)
day = diff.total_seconds() / 24. / 3600
day %= 365.25
m = 1. - np.tan(np.radians(latitude... | 390cd02b805686a824b8e1bfa8641d1adeb01e9d | 3,625,089 |
def reject(p, xs):
"""The complement of filter.
Acts as a transducer if a transformer is given in list position. Filterable
objects include plain objects or any object that has a filter method such
as Array"""
return filter(complement(p), xs) | a2556ab9d4514dfb18a513938960211473a508a9 | 3,625,090 |
from typing import OrderedDict
def filter_excluded_fields(fields, Meta, exclude_dump_only):
"""Filter fields that should be ignored in the OpenAPI spec
:param dict fields: A dictionary of of fields name field object pairs
:param Meta: the schema's Meta class
:param bool exclude_dump_only: whether to ... | a39a7665052cde0ba9f694696a57f2b1f6ca0603 | 3,625,092 |
def parse_xmpp_addresses(text):
"""."""
xmpp_addresses = ioc_grammars.xmpp_address.searchString(text)
return _listify(xmpp_addresses) | 36e5567e43bf48674787130a10bc77a69d9dcd54 | 3,625,093 |
def login_user():
""" This route handles user login """
user_info = request.get_json()
user_instance = UserModel.query.filter_by(email=user_info["email"]).first()
if not user_instance:
return {
"message": "Your email or password is not correct",
"status": "failed",
... | de93dc48865c75ae96a43f7cc9534ac64aba443e | 3,625,094 |
from typing import Any
def test_email(
email_to: EmailStr,
current_user: models.User = Depends(deps.get_current_active_superuser),
) -> Any:
"""
Test emails.
"""
send_test_email(email_to=email_to)
return {"msg": f"Test email sent to {email_to}"} | 13e7bcb0e96ae11c910619f4a4f161738c10ac6f | 3,625,095 |
def euclidean_distance(vects):
"""Compute Euclidean Distance between two vectors.
Euclidean distance is defined as the length of a line
segment between the two points.
d(p,q) = √ [Σ(qi – pi)^2]
Args:
vects : vectors
Returns:
euclidean distance between vects.
"""
x, y ... | f48eac6ff7adaefee700fe48f60cd614655ac704 | 3,625,096 |
def process_typedef(line):
"""处理类型定义"""
content = line.split(' ')
type_ = type_dict[content[1]]
keyword = content[2]
if '[' in keyword:
i = keyword.index('[')
keyword = keyword[:i]
else:
keyword = keyword.replace('\n', '') # 删除行末分号
keyword = keyword.replace('\r'... | e36f0f6298e2cdf7edc1d843c3fbaae7aa428a97 | 3,625,097 |
def findNearestNeighbourPixel(img, seg, i, j, segSize, fourConnected):
"""
For the (i, j) pixel, choose which of the neighbouring
pixels is the most similar, spectrally.
Returns tuple (ii, jj) of the row and column of the most
spectrally similar neighbour, which is also in a
clump of size... | e205652d7b39c922a203162f3cdc58672347b938 | 3,625,098 |
import json
def _load_json_as_list(path: str) -> list:
"""Load json file and convert it into list.
:param path: path to json file
:type path: str
:return: dict
:rtype: dict
"""
with open(path, "r") as json_data:
data = json.load(json_data)
if isinstance(data, list):
re... | d7aa301a830a826937522dc9c737bf84bf6f4f9a | 3,625,099 |
def flavor_create(context, values, projects=None):
"""Create a new instance type. In order to pass in extra specs,
the values dict should contain a 'extra_specs' key/value pair:
{'extra_specs' : {'k1': 'v1', 'k2': 'v2', ...}}
"""
specs = values.get('extra_specs')
specs_refs = []
if specs:
... | 0250bd710c182a99dd270c535b90688062db5734 | 3,625,100 |
from typing import Any
def dictlike(var: Any) -> Boolean:
"""
Determine whether or not var is dict-like (Can
contain dict-like items).
:param var: Any variable to check
:return: Boolean
"""
try:
var.items()
return True
except (TypeError, AttributeError):
return False | 5e2a16c4f76112892556de840d4ff8821f98aedd | 3,625,101 |
def plot_vehicle_tri(ax, coords, yaw, color=(0, 0, 1, 0.5), zorder=None):
"""Plot a marker representing a vehicle (either ground truth or
estimate)"""
vertices = [
[0, 0],
[0.77, -0.5],
[0, 0.5],
[-0.77, -0.5]
]
tri = patches.Polygon(
vertices, closed=True, fa... | 5adc6da320972630aa4277ca49525cc615568464 | 3,625,102 |
def PatchDword(ea, value):
"""
Change value of a double word
@param ea: linear address
@param value: new value of the double word
@return: 1 if successful, 0 if not
"""
return idaapi.patch_long(ea, value) | 4ed7fee3fae16d0026f616bd725db60341652f77 | 3,625,103 |
import re
def _addquotes(vistr: str) -> str:
"""Add quotes to '=attribute' attributes"""
vistr = re.subn(r'=(?!")(.*?)([\s>])', _quote, vistr)[0]
return vistr | 63ebe29ef8d78450fc8592646f8042710c78371c | 3,625,105 |
from typing import List
def readFile(filename: str) -> List[str]:
"""
Reads a file and returns a list of the data
"""
try:
with open(filename, "r") as fp:
return fp.readlines()
except:
raise Exception(f"Failed to open {filename}") | a5817ab563b83d5cf4999290d10a14a0b68954b6 | 3,625,107 |
def calculate_residuals(df, fit, names):
"""Calculates residuals values by comparing values in df and in fit.
Arguments:
df (pandas.DataFrame):
Holds the data to be fitted. Either concentrations vs time
or charge passed vs time depending on the situation.
fit (numpy.nda... | 5b597dd8ff83241993bee8cae27e6f85c43b1959 | 3,625,108 |
def ted():
"""
When A POST request with json data is made to this uri,
Read the example from the json, predict probability and
send it with a response
"""
# Get decision score for our example that came with the request
data = flask.request.json
print(data)
X = data#["example"])
#... | 11a20ecb7ba60d3debea53cf5b52b76454436c32 | 3,625,109 |
import yaml
def yaml_load(source, loader=yaml.Loader):
"""
Wrap PyYaml's loader so we can extend it to suit our needs.
Load all strings as unicode: http://stackoverflow.com/a/2967461/3609487.
"""
def construct_yaml_str(self, node):
"""Override the default string handling function to alwa... | dbf8f52b159b1f563322a1474a4a14733b741143 | 3,625,110 |
def _item_to_instance(iterator, instance_pb):
"""Convert an instance protobuf to the native object.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type instance_pb: :class:`~google.spanner.admin.instance.v1.Instance`
:param... | 75fceba9caec7fa37d2ef674dca2296a71b4532f | 3,625,111 |
def get_trunc_hour_time(obstime):
"""Truncate obstime to nearest hour"""
return((int(obstime)/3600) * 3600) | 8379aafc76c1987f537ea294c7def73ad32f1b23 | 3,625,113 |
import re
def normalize_package_name(python_package_name):
"""
Normalize Python package name to be used as Debian package name.
:param python_package_name:
The name of a Python package as found on PyPI (a string).
:returns:
The normalized name (a string).
>>> from py2deb impor... | 47a850c601e64b570470a339769742d8f3732e28 | 3,625,114 |
def resolve_all(x):
"""Recursively resolves the given object and all the internals.
Make sure there is no indirect reference within the nested object.
This procedure might be slow.
"""
while isinstance(x, PDFObjRef):
x = x.resolve()
if isinstance(x, list):
x = [ resolve_all(... | 28e3903b679f842fd8f104780ddb08379f65cfaf | 3,625,115 |
def logout():
"""View of logout"""
logout_user()
flash('Administrator Logged out')
return redirect(url_for('main.index')) | 85b8df3f281641b823d7a6765316832f96f5202e | 3,625,116 |
import tqdm
def create_data_language(
text, vocabulary, window_size=2, fill_strategy="zeros", verbose=False
):
"""Create a supervised dataset for the characte/-lever language model.
Parameters
----------
text : str
Some text.
vocabulary : list
Unique list of supported characte... | 2da866ac637d4658c17e69d722c8a9db52987983 | 3,625,117 |
import dateutil
def format_datetime(value, datetime_format="medium"):
"""Converts a datetime str to a format that is understood by the db.
Args:
value: A str representing a datetime
datetime_format: A str representing the desired format of the returned
datetime, accepted values ar... | f526ddf89f030b66aa7e2567b1cc301c98100096 | 3,625,118 |
import csv
def getDialect(filename):
"""Get the dialect of the given csv file."""
with open(filename, 'rb') as csvfile:
dialect = csv.Sniffer().sniff(csvfile.read(1024))
return dialect | 0169c9058a46ba265768ef405cd525cc2d1a132b | 3,625,119 |
def sort_list(source, target):
"""
This function is used to sort the source and target list on the
basis of key found in the source and target list.
:param source:
:param target:
:return:
"""
# Check the above keys are exist in the dictionary
if len(source) > 0:
tmp_key = is_... | 3344f83e21e31c1cf3145e1ba5334bc9a0d5216b | 3,625,120 |
def get_audio_source(input=None, **kwargs):
"""
Create and return an AudioSource from input.
Parameters
----------
input : str, bytes, "-" or None (default)
source to read audio data from. If `str`, it should be a path to a valid
audio file. If `bytes`, it is used as raw audio data.... | e046b79bd9bafd2c8a23614834dc1533e0ceb3da | 3,625,121 |
def delete_prtg_device(prtg_single_device_obj):
"""
deletes the host at PRTG WITHOUT confirmation
"""
result = prtg_single_device_obj.delete(confirm=False)
return result | 4cb9b2a35294f0c56a62a7dbd220ab2ada81a15d | 3,625,122 |
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