content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Union
from typing import List
def count(obj: Union[int, List]) -> int:
"""Return the number of integers in obj.
>>> count(27)
1
>>> count([4, 1, 8])
3
>>> count([4])
1
>>> count([])
0
>>> count([4, [1, 2, 3], 8])
5
>>> count([1, [2, 3], [4, 5, [6, 7]... | d982b3096dc9c7776b32bab765e2a17769d128e9 | 37,100 |
def kmeans(x, n_clusters=20, random_state=42, **sklearnArg):
"""Given a set of different 1D functions (represented in matrix form where each row contains the function values on a given grid), this
method clusters those functions and tries to find typical function structures.
Args:
x (numpy matr... | 2671a7d40f339cc8e45c28381e65c8f8ceed474e | 37,101 |
def GetClientSecretFlag():
"""Anthos auth token client-secret flag, specifies the Client Secret is the shared secret between OIDC client application and OIDC provider."""
return base.Argument(
'--client-secret',
required=False,
help='Client Secret is the shared secret between OIDC client applicati... | 7d01e32208f51299e793359458ecef1da5e5bae6 | 37,102 |
def login(request):
"""
Fonction idantifiant les gens et/ou renvoyant le formulaire.
"""
message = None
form = None
topThree = []
if request.method == 'POST':
if request.session.test_cookie_worked():
request.session.delete_test_cookie()
form = LoginForm(reque... | 7e3dfe056e690c5830053a6e05f86b74e37e0fec | 37,103 |
def start_instance_pool(instance_pool_id: str,
configuration: Configuration = None,
secrets: Secrets = None) -> OCIResponse:
"""Start the given OCI Compute instances."""
client = oci_client(ComputeManagementClient, configuration, secrets,
... | 462f76cad9c9c7c7817ccaf6ed4715c7fb5caed1 | 37,104 |
def label_rank(label, scores, label_order) -> int:
"""
Add Labels based on Rank
:param label: Label to assign to item
:param scores: Score to rank item
:param label_order: Order of Labels
:return: Return Index
"""
loc = label_index(label, label_order)
if loc is None:
return ... | 06d5bb4d01f7b8194555f978be66ddb238b03360 | 37,105 |
def _single_quote_string(name: str) -> str: # pragma: no cover
"""Single quote a string to inject it into f-strings, since backslashes cannot be in double f-strings."""
return f"'{name}'" | 39868168862f3bd60d8da6168503cbc51fcbda84 | 37,106 |
import tempfile
import os
import yaml
def parse_override_config_and_write_file(namespace):
"""
Parse the command line for overriding the defaults and
create an override file.
"""
overrides = parse_override_config(namespace)
try:
tmp_dir = tempfile.mkdtemp()
override_config_file = os.path.join(tmp_... | 607466e20bbd5a64c14883e5515c19c04cc9e7ac | 37,107 |
def compute_rel_rois(num_rel, rois, relations):
"""
union subject boxes and object boxes given a set of rois and relations
"""
rel_rois = np.zeros([num_rel, 5])
for i, rel in enumerate(relations):
sub_im_i = rois[rel[0], 0]
obj_im_i = rois[rel[1], 0]
assert(sub_im_i == obj_im... | 4fcdf1fe57557a73c3da476e327f1632ea217d6d | 37,108 |
from pyparsing import (
srange, oneOf, Forward, Optional, Suppress, Word, ZeroOrMore,
dblQuotedString, pythonStyleComment
)
def from_gml(text):
"""
Return the list of graphs read from `text`, a string in GML format.
This function assumes that the input follows the GML specification,
p... | d223438d6b38d1b1c62c2e9a734a6a08b94e1721 | 37,109 |
import typing
from unittest.mock import patch
def parse(type_string: str, *, func=None):
"""Parse the given type string.
Args:
type_string (str): The type string to be parsed.
func (function): The function to which the type string belongs (optional).
This causes the t... | 485d0d5dd2edb63873464e3e02d67c202947d78b | 37,110 |
from threading import Thread
def run(data, inFile="", encrypt=False, method=3, aad="", key=config.KEY):
"""
Run encryption of decryption.
data: file name with extension
encrypt: False to decrypte
method: Block cyphering method
"""
if len(data) > 100000:
thread = Thread(target=wa... | 3884592005f72a2e2375da2698f37a61e7bc6aa3 | 37,111 |
def convert_str_version_number(version_str):
"""
Convert the version number as a integer for easy comparisons
:param version_str: str of the version number, e.g. '0.33'
:returns: tuple of ints representing the version str
"""
version_numbers = version_str.split('.')
if len(version_number... | b550b7d07d9b226800de261f792bf0995ac21738 | 37,112 |
import torch
def valid_simulation(_state, _params):
"""
AW - valid_simulation - return a binary variable per simulation indicating whether or not that simulation
satifies the desired policy outcome.
:param _state: tensor (N x D): tensor of the state trajectory.
:return: tensor (N, ), bool: ten... | 6eb82ec744cbab353f649e63d54c0d95236f1699 | 37,113 |
def computeA(diameter):
"""Computes area of circle"""
radius = diameter / 2.0
return np.pi * (radius**2) | d78b596a3df0e82cf93b5e0318b9ba53c3dc1b6c | 37,114 |
def RemoveFromLinuxKernelCmdline(option):
"""
Remove 'option' to the kernel boot options of the grub configuration.
"""
if FindInLinuxKernelCmdline(option):
src = r'^(.*?' + MyDistro.grubKernelBootOptionsLine + r'.*?)(' + option + r')(.*?)("?)$'
rep = r'\1\3\4'
try:
R... | 798c803d3fb7d2ac9d525e8ea67e858c518e4e2d | 37,115 |
def get_maximum_weight(G, S, T):
"""
Given a networkx graph G and two subsets of vertices S and T, this method returns the maximum weight of an edge e,
having one endpoint in S and the other in T
:param G: A networkx graph
:param S: A subset of vertices in G
:param T: A subset of vertices in G
... | 8cb40045a303845b070760aad3c9d66815827a3d | 37,116 |
def create_volume_snapshot(session, cg_id, display_name, return_type=None,
**kwargs):
"""
Creates a new snapshot for the specified volume. Manually initiated
snapshots will fall under the "On Demand" snapshot policy.
:type session: zadarapy.session.Session
:param session... | caf9fdbdb5ddb26c3b271f3c568f3e49b5c5acd2 | 37,117 |
def parse_elem(elem):
"""Determine element type and dispatch to other parse functions."""
if len(elem) == 0:
return parse_text(elem)
if not elem[0].attrib:
return parse_list(elem)
if elem[0].get('Name') == 'Key':
return parse_key_value_dict(elem)
return parse_attrib_dict(elem... | c6195c8f8389b0ea93e8f48a827d0e212eb5aa42 | 37,118 |
from typing import Optional
def configured_version_for(artifact_name: str) -> Optional[str]:
"""Given the name of an artifact, retrieves the version of that
artifact from the current stack configuration. Returns `None` if
no version has been specified for that artifact.
In general, we will have versi... | 90e6bd5f09aa53ff33fefda5027c3b110d923578 | 37,119 |
def filtered_cumulative_sum(df, columns, latest_date, reference_column_name="covid_vacc_date"):
"""
This calculates cumulative sums for a dataframe, and when given a set of
characteristics as columns, produces a dictionary of dataframes.
Args:
df (Dataframe): pandas dataframe. At the very least... | 5bcb2d79fdfb2e8f26868ef3d411163b3d73f8e3 | 37,120 |
def handover_results():
"""
Endpoint to get a list of all the handover by release
This is using docstring for specifications
---
tags:
- handovers
operationId: handovers
parameters:
- name: release
in: query
type: string
description: get handover list for ... | a15b0b69b5ddf4654311d0940a37fac548c5dcf4 | 37,121 |
def safezip(*args):
"""make sure *args* are equal len before zipping"""
Nx = len(args[0])
for i, arg in enumerate(args[1:]):
if len(arg) != Nx:
raise ValueError(_safezip_msg % (Nx, i + 1, len(arg)))
return list(zip(*args)) | f8d2a1c3bbe33903b896e1dbf64ffd1c0804d849 | 37,122 |
from typing import Union
def chaid_to_graphviz(
tree: dict,
classes: Union[list, np.ndarray] = [],
classes_color: list = [],
round_pred: int = 2,
percent: bool = False,
vertical: bool = True,
node_style: dict = {},
arrow_style: dict = {},
leaf_style: dict = {},
**kwds,
):
"... | e48dc9611b9208b99daa631217320d644d02a769 | 37,123 |
import copy
def process_dataset(dataset, func):
"""Calculate things here using the dataset, then return
a dictionary containing names and values for each
calculated quantity."""
new_dataset = copy.copy(dataset)
del new_dataset["val"]
new_dataset.update(func(dataset))
return new_dataset | b38b2edd1abe9a990d8f524b78b38e8abadc7c55 | 37,124 |
def cosine_beta_schedule(timesteps, s = 0.008):
"""
cosine schedule
as proposed in https://openreview.net/forum?id=-NEXDKk8gZ
"""
steps = timesteps + 1
x = np.linspace(0, steps, steps)
alphas_cumprod = np.cos(((x / steps) + s) / (1 + s) * np.pi * 0.5) ** 2
alphas_cumprod = alphas_cumprod... | 703c78956b9d0e1ca00dbe2d1b3a7025aa955623 | 37,125 |
def _infinity(name):
"""
Create a single instance of an class with a given name.
"""
return type(name + "Type", (object, ), {
'__repr__': lambda self: "{0}.{1}".format(self.__module__, name),
'__str__': lambda self: name,
'__unicode__': lambda self: name,
})() | bd6cbda227e9d97938ab9ed7c2d2e97b95dc5080 | 37,126 |
def allocate_packs(packs,
tracks,
pack_refs,
num_silent_tracks):
"""Allocate tracks to channels and packs. This is intended to be used on a
subset of tracks referenced by an audioObject, or on all tracks if there is
no programme/content/object hierarc... | 05c1c0c99633904f8c38255410f0517c5dec8eb7 | 37,127 |
def edit_settings(request):
"""Edit user settings."""
user = request.user
if user.groups.filter(name='Mozillians').exists():
raise Http404
form = forms.EditSettingsForm(request.POST or None,
instance=user.userprofile)
if request.method == 'POST' and form.is... | 3a933ad9ded228bfccac92e6ab1ce9d2535d9fe2 | 37,128 |
def calculate_priority(priority_table_uri):
"""Create dictionary mapping each land-cover class to their priority weight.
Args:
priority_table_uri (str): path to priority csv table
Returns:
priority_dict (dict): land-cover and weights_matrix
"""
LOGGER.info("Creating land-cover prio... | 7e78ac80a388c7337f2ecd0b13e5149adee7c0d7 | 37,129 |
def create_virtual_cdrom_spec(client_factory,
datastore,
controller_key,
file_path,
cdrom_unit_number):
"""Builds spec for the creation of a new Virtual CDROM to the VM."""
config_spec = clien... | 8f62c70c432c368f0f94b3c1dc48f38d75093b07 | 37,130 |
def read_image_from_file(file_path: str) -> np.ndarray:
"""Read image data from a file and return as is."""
img = cv2.imread(file_path, cv2.IMREAD_UNCHANGED)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
return img | dccee146e26b4eb99ac02f392dc4769666dd2a98 | 37,131 |
def get_line(x, camera_id, camera_param):
"""Get line in world"""
# x: n * 2
x_tmp = np.concatenate((x, np.ones((len(x), 1)).astype(np.float32)), axis=1)
new_x = (x_tmp - camera_param[camera_id]['C']) * camera_param[camera_id]['FInv']
sample_num = len(new_x)
cam_origin = np.array([[0, 0, 0]... | 6467767026bcb556d83709c4b63d3b0e3eeba2ed | 37,132 |
def get_cca_data_as_matrices(data_set="train"):
""" Normalizes data and returns data and labels as separate lists.
Args:
data_set: data set to retrieve
Returns:
data: list of data vectors
labels: list of vectors
"""
X_scores, labels = CCA_reduction(data_set=data_set)
dat... | 6e580dd6738f46cb5fa0cb11e865538989a622ad | 37,133 |
def shard_query(query, shard_count):
""" Given a datastore.Query object and a number of shards, return a list of shards where each
shard is a pair of (low_key, high_key).
May return fewer than `shard_count` shards in cases where there aren't many entities.
"""
OVERSAMPLING_MULTIPLIER = 32 #... | 118ef5ba64a3ea58ba0676982062e3261ae4e2ed | 37,134 |
def get_bindings(keysToObtain=None):
"""Returns a dict struct with the direct input equivalent of the necessary elite keybindings"""
if keysToObtain is None:
keysToObtain = keys_to_obtain
direct_input_keys = {}
latest_bindings = get_latest_keybinds()
bindings_tree = parse(latest_bindings)
... | 284f6eb8eac18079ad2d3de050758a2cbe528380 | 37,135 |
def add_intercept(A):
"""
Adds an intercept (column of ones) to a supplied array A
such that the intercept is the first (leftmost) column
"""
n = A.shape[0]
intercept = ones(n).reshape(n, 1)
return hstack((intercept, A)) | 64149664398b153dcf2927a8d4543b3de0e4b8a3 | 37,136 |
from sys import path
import logging
def predict_adjacent_stop(departure_stop_num, arrival_stop_num, features, num_predictions):
"""
Predict the time to travel between two adjacent stops on the same route trip.
This method uses stop numbers and not stop IDs since stop IDs are not available
in the histo... | 1376da584f9aee4ffb9b7996df5932223c202bb1 | 37,137 |
def _cut_open_ended_intervals(intervals):
"""Keep only one open interval
If there are multiple open intervals keep only the latest open;
cut others so they no longer intersect each other.
:param intervals: [Interval]
:return: processed intervals: [Interval]
"""
filtered_intervals = []
... | 1a4b5ae772a4a0bc092b1b61387c91dd32236b6d | 37,138 |
def get_content_type(obj):
"""
Returns the content type for ``obj``.
"""
return ContentType.objects.get_for_model(obj) | 71ee7ee109ce15f966446f7d86666c5737f80171 | 37,139 |
def spark_random_split(data, ratio=0.75, seed=42):
"""Spark random splitter.
Randomly split the data into several splits.
Args:
data (pyspark.sql.DataFrame): Spark DataFrame to be split.
ratio (float or list): Ratio for splitting data. If it is a single float number
it splits d... | 0a250f72e99ea81d2660d888276340a467e4af88 | 37,140 |
import os
def get_test_suite_kwargs(args):
"""Set and return test suite kwargs based on options."""
kwargs = vars(args)
del kwargs['verbose']
ydk_root = get_ydk_root()
default_profile = ydk_root + '/profiles/test/ydktest.json'
default_test_root = os.path.join(ydk_root, 'test', 'test-cases')
... | 8f1f5ea592b24f4be64fa7d333a9ccf4093fdd24 | 37,141 |
def unique_all(x: Array, /) -> UniqueAllResult:
"""
Array API compatible wrapper for :py:func:`np.unique <numpy.unique>`.
See its docstring for more information.
"""
values, indices, inverse_indices, counts = np.unique(
x._array,
return_counts=True,
return_index=True,
... | a6946861799c51a4499d94dc003316ecfbfb1802 | 37,142 |
def tail(filepath, n):
"""Similate Unix' tail -n, read in filepath, parse it into a list,
strip newlines and return a list of the last n lines"""
with open(filepath) as f:
file = f.read()
tail_result = file.split('\n')[-n:]
return tail_result | a91b1111c7943f9b9ac3e63032a43f3a18fbda59 | 37,143 |
import argparse
def parse_args():
"""
Parse the command line arguments and return an object representing the
command line (as returned by argparse's parse_args()).
Returns
-------
The commandline argparse namespace.
"""
parser = argparse.ArgumentParser(description='Utility for lis... | 3f58a22f11418c79479f28ee9b4fd7cb8832b77c | 37,144 |
def test_flag_robots(app, mock_user_ctx, request_headers, objects):
"""Test flag_robots preprocessor."""
def build_event(headers):
with app.test_request_context(headers=headers):
event = file_download_event_builder({}, app, objects[0])
return flag_robots(event)
assert build_even... | f5b5cd6698bdf99d6b1caff38c07c8f53ee75fb8 | 37,145 |
def plot_mean_and_CI(axes, mean, lb, ub, label, freqs, linestyle='-'):
""" Plot mean and confidence boundaries.
Args:
axes: plt.axes
mean: np.ndarray
lb: np.ndarray
ub: np.ndarray
label: string
freqs: list
linestyle: string
Returns: plt.axes
... | 77b7ecaa6dddae474495c0a65efafbf08717584c | 37,146 |
def messages(request):
""" Display some messages """
adjax.success(request, "This is your first success")
adjax.info(request, "This is your first info")
adjax.warning(request, "This is your first warning")
adjax.error(request, "This is your first error")
adjax.debug(request, "This is your first ... | a7a339712e905d109c19d73ab60059869b149b74 | 37,147 |
def locked(acquire, release):
"""Decorator taking two methods to acquire/release a lock as argument,
returning a decorator function which will call the inner method after
having called acquire(self) et will call release(self) afterwards.
"""
def decorator(f):
def wrapper(self, *args, **kwarg... | 92f8ae3b36375d14962997436bc1d210510b4cdb | 37,148 |
from api_x.zyt.evas.payment.config import PaymentScene
def app_checkout_entry_info(source, sn):
"""app支付info接口
deprecated之前只有lvye_skiing接入
"""
return redirect(config.HOST_URL + url_for('biz_entry.pay_info', sn=sn, payment_scene=PaymentScene.lvye_skiing)) | 27654aff3e1a178d97889d2f649bc4ba46bad256 | 37,149 |
def linreg(X, Y):
"""
Summary
Linear regression of y = ax + b
Usage
real, real, real = linreg(list, list)
Returns coefficients to the regression line "y=ax+b" from x[] and y[], and R^2 Value
"""
if len(X) != len(Y): raise ValueError("unequal length")
N = len(... | 379ec60fdbf33d9ea5c544cc04ecfd8257813c47 | 37,150 |
import torch
def _handle_row_wise_sharding_sharded_tensor(
input, world_size, weight, local_shard_t, bias, pg
):
"""
Entry-point function to handle the logic of row-wise sharding of weight
for Linear when the input is a sharded tensor. (Detailed explanations
of the logic can be found in the commen... | e5e709d7cc101adf1d31efbc3195136accbbc73d | 37,151 |
def put_tags(new_tag_list, cgx_dict):
"""
This function looks at a CloudGenix config object, and puts tags.
:param new_tag_list: List of tags to add if not already present.
:param cgx_dict: CloudGenix config dict, expects "tags" keys supported in root.
:return: CloudGenix config dict with added tags... | 70ff682995a17d2e27d4a4fabcb32c545bb7bcfe | 37,152 |
def perturb_actions(states, actions, perturbations, limits=None):
"""Create state-action pairs by perturbing the actions.
Parameters
----------
states : ndarray
An (N x n) array of states at which we want to generate state-action
pairs.
actions : ndarray
An (N x m) array of ... | 6a7152027004a4520057dcfaf82d1cde21f81dc2 | 37,153 |
import time
def median(image_set, size=None):
"""
Applies a median filter to the image set.
This function is a wrapper around scipy.ndimage.filters.median_filter
"""
if size is None:
print('Please set a filter size. Defaulting to size = 3.')
size = 3
print('Applying median f... | 3fd0c47ec3bafabbe93584c2c011e7245003ed48 | 37,154 |
def conditional_demographic_parity_ratio(labels, pred, attr, groups):
"""
Calculate conditional demographic parity by calculating the average
demographic parity ratio across bins defined by `groups`.
"""
ratios = []
for group in set(groups):
mask = groups == group
ratios.append... | 523a70684f303822f05d14874011a56741161e05 | 37,155 |
def calculate_ddx_G2(neighborindices, neighborpositions, eta, Rc, Rs, i, m, l):
"""
Calculates coordinate derivative of G2 symmetry function for atom at
index i and position Ri with respect to coordinate x_{l} of atom index
m.
Parameters
---------
neighborindices : list of int
List ... | affc094b6ecacb17c451989460bbde8c9939aadf | 37,156 |
def _correct_module_lettercase(module: str):
""" 修正模块的大小写.
示例:
'qtquick-window' -> 'QtQuick.Window'
'qtgraphicaleffects' -> 'QtGraphicalEffects
注意: 存在一些特殊情况:
'qt-labs-animation' -> 'Qt.labs.animation'
思路:
1. 我们需要把模块的名字按照词来拆分:
'qtgraphicaleff... | bb520055cf181b07cf39cef5adba33af60fab77f | 37,157 |
def normalize(x, axis=None, degree = 2, avoid_nans = False):
"""
Normalize array x.
:param x: An array
:param axis: Which axis to normalize along
:param degree: Degree of normalization (1 for L1-norm, 2 for L2-norm, etc)
:param avoid_nans: If, along an axis, there is a norm of zero, then normali... | 5b356936a6943f1490e6c8a6d6d93e3b2a8fb003 | 37,158 |
def get_default_curriculum_env_config(method, env_config=None):
"""Get default curriculum env config.
Args:
method: The method used in curriculum learning.
env_config: Optional. The env config. If None, use the default env
config file. Default, None.
Returns:
A curriculum env config.
"""
i... | cf2d7166ae66a8342f2e574bf921f5e27105afb5 | 37,159 |
import ctypes
def _get_libc():
"""Load the lib-C for unix systems."""
libc = _system_libraries.get("libc")
if libc is None:
libc_name = find_library("c")
if libc_name is None: # pragma: no cover
return None
libc = ctypes.CDLL(libc_name, mode=_RTLD_NOLOAD)
_syst... | 6e233d6e8af013d48e0751325f40ca9ef95d7d19 | 37,160 |
def try_multiple_dec_s3(func):
"""An S3 specific adapter to @try_multiple_dec
To decorate func to try multiple times after some sleep upon encountering
some intermittent error from S3
"""
return try_multiple_dec(
ntrials=4,
duration=2.,
increment_type... | 711c30c85cc5ca66484ddc27426afc1e151e86de | 37,161 |
def standardize_education_level(education_column):
"""This function aims at standardizing the education level. The column
has mixed types (ints and categories, with overlapping categories).
Args:
education_column (pd.Series): column in which we will replace the identified
matching values.
... | 8a8cc237b8123a5c48b52a918d5e8d5de660ce4b | 37,162 |
def neutral_key_state(game: Game):
""" Logic to execute when no relevant key is pressed. Returns updated neutral_count """
player = game.player
previous_orientation = player.orientation
if player.is_moving_up():
player.reset_speed()
player.orientation = DIRECTIONS.get(0)
game.sc... | 4f2a7542385e5e575dcb46e5be5b02987b528743 | 37,163 |
def reshape_from_matrix(output_tensor, orig_shape_list):
"""Reshapes a rank 2 tensor back to its original rank >= 2 tensor."""
if len(orig_shape_list) == 2:
return output_tensor
output_shape = get_shape_list(output_tensor)
# output_shape = tf.shape(output_tensor)
orig_dims = orig_shape_list[0:-1]
widt... | de9344c0cf09cdd0a3f33db39fcb1b7a72fe00e5 | 37,164 |
def compute_unconstrained_optimization_weights(cov, mean, market_return, rfr, market_var, l=None):
"""
"""
# risk aversion
if l is None:
l = (market_return - rfr) / market_var
return np.dot(np.linalg.inv(l*cov), mean) | 0a11d920db8bb28e13484d3138a33b7233103327 | 37,165 |
import os
def get_coordinates_partition_path(coordinates_dir: str,
partition_type: utils.PartitionType) -> str:
"""Gets the path to the coordinates for the provided partition file.
Args:
coordinates_dir: A directory containing coordinates files.
partiti... | 2aee18e77eeaf85fe552be622e8370f924b1077b | 37,166 |
def setup_animation(tracks, step_interval):
"""
Set up data structures and a matplotlib FuncAnimation instance for
animating a list of track DataFrames.
:param tracks: list of track DataFrames
:param step_interval: step interval for animation (e.g., '15S')
:return: FuncAnimation instance
"""... | 8e296f35395f2a815309b3a15c43933a41791f90 | 37,167 |
def eval_standard(ner_model, examples, label=None):
""" Evaluates the model using the standard evaluation metrics
If label parameter is not defined, the scores will be calculated for the whole document,
otherwise it will calculate the scores for the selected label only
Parametres
-------------
... | 68e2d372369a69fb3bee5f0dde767873021347ae | 37,168 |
def calc_E_G_C_hs_d_t():
"""冷房設備機器のガス消費量（MJ/h）(23b)を計算する
Args:
Returns:
ndarray: 冷房設備機器のガス消費量（MJ/h）
"""
return calc_E_G_C_hs_MR_d_t() + calc_E_G_C_hs_OR_d_t() | c9eff01fd51590850d8c2f01aae90c04315eb4d7 | 37,169 |
def Keplerian1D_neg(x, mass=1., v0=0., r0=0.):
"""Computes the keplerian velocity at requested distances.
Args:
x (array_like):
Distances to the central object.
mass (float, optional):
Mass of the central object.
v0 (float, optional):
Velocity offset ... | edbb693de44d73420c9874efa4366a7ea39c4ecb | 37,170 |
import os
def process_modules_csv(drcty):
""" Separate out MFG from model and append these columns to base data
frame """
dp = os.path.join(os.getcwd(), drcty)
fp = os.path.join(dp, 'CEC Modules.csv')
df = pd.read_csv(fp, index_col=0, skiprows=[1,2])
names = list(df.index.values)
mfgs... | 405c4d185ed829ce6619147804ac19a0da85b487 | 37,171 |
def create_sample_table(word_count):
""" Create negative sample table for vocabulary, words with
higher frequency will have higher occurrences in table.
"""
table = []
frequency = np.power(np.array(word_count), 0.75)
sum_frequency = sum(frequency)
ratio = frequency / sum_frequency
co... | 9c8c1e05d2d493b4c8ace51772effa776c732e61 | 37,172 |
from typing import Dict
import torch
def create_supervised_evaluator(
model: nn.Module, metrics: Dict, device, dtype,
output_transform=lambda x, y, y_pred: (y_pred, y,)):
"""
Factory function for creating an evaluator for supervised models.
Args:
model (`torch.nn.Module`): the model to tr... | 56def95b6491b16ca15ae386f3d58d2798433e36 | 37,173 |
import logging
def post(activity: dict, collection_id=None, **kwargs):
"""Celery task to deal with data post processing."""
execution = execution_from_collection(activity, collection_id=collection_id, activity_type=post.__name__)
collection = execution.activity.collection
scene_id = activity['scenei... | bdef84b97d6fe4883f24953a990bd5dd7b610f89 | 37,174 |
import functools
import operator
def feed_forward_cnn_small_categorical_fun(action_space, config, observations):
"""Small cnn network with categorical output."""
obs_shape = common_layers.shape_list(observations)
x = tf.reshape(observations, [-1] + obs_shape[2:])
with tf.variable_scope("network_parameters"):
... | bdd25c95c30d66976dc1d84b596ebc08cab4abad | 37,175 |
def check_next_in_request(request):
"""
Проверяет наличие слова 'next' в объекте запроса request методе POST
:param request:
:return:
"""
return True if 'next' in request.POST else False | b70ba54fa32234798b842ffcb24834fdcd95c827 | 37,176 |
from typing import List
from typing import Callable
def build_data_pipeline(
chain: List[Callable], kwargs: DataFuncKwargs, args_mut: DataFuncArgsMut
):
"""
Higher order function
:param chain: array of callable
:param **kwargs: any kwargs you like
"""
for call in chain:
# note: ret... | 252d7aa1a5238a770a589623bddeb36fa8d21bd7 | 37,177 |
import tokenize
def tokenize_by_word(text, deacc):
"""Tokenize input text. Before tokenizing transforms text to lower case and removes accentuation and acronyms set
:const:`~gensim.summarization.textcleaner.AB_ACRONYM_LETTERS`.
Parameters
----------
text : str
Given text.
Returns
... | eab6b61f178b6a388a5f5357e0f31c818ca74750 | 37,178 |
def overlap_slices(large_array_shape, small_array_shape, position):
"""
Modified version of `~astropy.nddata.utils.overlap_slices`.
Get slices for the overlapping part of a small and a large array.
Given a certain position of the center of the small array, with
respect to the large array, tuples o... | ef86928b3ef619f209247bb72e2e391d14d541c4 | 37,179 |
import torch
def mrr(scores: torch.Tensor) -> np.float:
""" Tested | Accepts one (n,) tensor """
ranks = (torch.argsort(scores, dim=0) == 0).nonzero()[0]
recirank = 1.0 / (ranks + 1).float()
return recirank.detach().cpu().numpy().item() | 33f185d0465bd6bf89a933d3a849e49414e7e423 | 37,180 |
import os
import subprocess
import logging
def write_to_raveler(sps, sp_to_segment, segment_to_body, directory, gray=None,
raveler_dir='/usr/local/raveler-hdf', nproc_contours=16,
body_annot=None):
"""Output a segmentation to Raveler format.
Arguments:
- sps: ... | 95c063139addc53be505932050ba1fc4bd7b6528 | 37,181 |
import numpy
def rotmat(x, origin=(0, 0, 0), upvector=(0, 0, 1)):
"""
Given a position vector x, find the rotation matrix to r,h,v coordinates.
"""
x = numpy.asarray(x) - numpy.asarray(origin)
nr = x / numpy.sqrt((x * x).sum())
nh = numpy.cross(upvector, nr)
if all(nh == 0.0):
nh =... | 519d7aaa15dd48bb31aed0059c01f365f4e8118b | 37,182 |
def curry(func):
"""Curry a function, but keep the docstring
Args:
func: a function to curry
Returns:
a curried function
>>> def add(a, b):
... '''Add stuff'''
... return a + b
>>> curry(add)(1)(2)
3
>>> print(curry(add).__doc__)
Add stuff
"""
retur... | 7fed40c2794496a78ff629f1e391206ab5c3b241 | 37,183 |
def score_func(house_data, venue_data):
"""Function for calculating location-based score of a house.
Function gets a house and venues within 1 km radius of that house,
calculates each venue's influential score on that house with dividing
venue's check-in count with the distance.
With that division,... | d1f3f5596316cfb958edf9672fcbc9665f53fa9c | 37,184 |
def bold(s):
"""Return the string bold.
Source: http://stackoverflow.com/a/16264094/2570866
:param s:
:type s: str
:return:
:rtype: str
"""
return r'\textbf{' + s + '}' | f7b791ea59852f5ab268ff67535c2f4b26d0f078 | 37,185 |
def train(
n_layer,
init_scale=1,
scale_upper_bound=128,
accum_upper_bound=4096,
method="approx_range",
update_per_n_iteration=1,
warmup_attr_ratio=None,
warmup_n_epoch=None,
n_class=10,
manual_seed=0,
train_batch=128,
device=-1,
learnrate=0.1,
):
""" Train functi... | 3bcb26a2ffc23b4af97e8fa78fcc5ee86a27649e | 37,186 |
def verify_access_key(key):
"""
Confirm that the access key is valid.
:param str key: Access key string.
"""
try:
access_key = models.AccessKey.objects.get(key=key)
except models.AccessKey.DoesNotExist:
return None
return access_key | 682e644fe420d17142d89c734e976db91bfce3c9 | 37,187 |
def send_sns_message(sns_client, payload, sns_topic_arn):
"""Publishes the message to sns.
Arguments:
sns_client (client): The boto3 client for SQS
payload (dict): the payload to post to SNS
sns_topic_arn (string): the arn for the SNS topic
"""
dumped_payload = get_escaped_json... | 0398ebf26314a2efe532b072dd2c9696a188644d | 37,188 |
def filter_first_altloc(atoms, altloc_ids):
"""
Filter all atoms, that have the first *altloc* ID appearing in a
residue.
Structure files (PDB, PDBx, MMTF) allow for duplicate atom records,
in case a residue is found in multiple alternate locations
(*altloc*).
This function is used to r... | baa8e0b3588523d4af194091bd161873fdebaa4f | 37,189 |
import scipy
import numpy
def dlqr(A, B, Q, R, optimal_cost_function=False):
"""Solves for the optimal lqr controller.
x(n+1) = A * x(n) + B * u(n)
J = sum(0, inf, x.T * Q * x + u.T * R * u)
"""
# P = (A.T * P * A) - (A.T * P * B * numpy.linalg.inv(R + B.T * P *B) * (A.T * P.T * B).T + Q
# 0.5... | 17149079f1eae11f07184170c4a91a46fa2787bb | 37,190 |
def add_single_scale_rpn_losses(model):
"""Add losses for a single scale RPN model (i.e., no FPN)."""
# Spatially narrow the full-sized RPN label arrays to match the feature map
# shape
model.net.SpatialNarrowAs(
['rpn_labels_int32_wide', 'rpn_cls_logits'], 'rpn_labels_int32'
)
if cfg.T... | 367917906613f688f68d629063a6a80ea05ceafe | 37,191 |
def product(data):
"""
Generate the product for the entries specified by the data.
"""
return "tRNA-{aa} ({anticodon})".format(
aa=data["metadata"]["isotype"],
anticodon=data["metadata"]["anticodon"],
) | 5f347cfa1fd7d7030fb1b1a5d2e88eb664c831ae | 37,192 |
def _pad_image(image, factor=2):
"""Enlarges the image canvas, filling new pixels with colors at the edge.
:param image: An RGB image
:param factor:
A scalar representing the factor in which the canvas is to be enlarged.
A factor of 2 will double the canvas, a factor of 1 will keep it
... | de45488de1b8de449d4c9ba8db9e7b1572f5d88c | 37,193 |
def change_multi_asset_mode(self, multiAssetsMargin: str, **kwargs):
"""
|
| **Change Multi-Assets Mode (TRADE)**
| *Change user's Multi-Assets mode (Multi-Assets Mode or Single-Asset Mode) on Every symbol*
:API endpoint: ``POST /fapi/v1/multiAssetsMargin``
:API doc: https://binance-docs.github... | 03935ac6efb09b9a4e5923f9aab8ef1edfca5426 | 37,194 |
import base64
def get_image_data(docx_file_path, image_name):
"""
Return base 64 encoded data for the image_name that is stored in the
docx_file_path.
"""
with ZipFile(docx_file_path) as f:
images = [
e for e in f.infolist()
if e.filename == 'word/media/%s' % image_... | 77776dfc43c8a31c371b9ec87f4fcdedda8c0441 | 37,195 |
async def get_a_user(user_id):
"""
Get a single user
---
/api/users/{user_id}:
get:
summary: Buscar um usuário pelo ID
security:
- APIKeyHeader: []
tags:
- User
parameters:
- in: path
name: user_id
required: true
schema:
... | 48fe262763872d0f394bdb9bb9a3ed553cae7ee2 | 37,196 |
def extract_string_from_tensor(input_ids: Tensor, mode="single",config = None, tokenizer = None):
"""
Args:
input_ids(Tensor): input tensor of sequence index. Shape: (self.batchsize,self.seq_length)
mode(str): "pair","single"and "CBT", "pair" for tasks with paired inputs, such ... | 91eb9f11b338592d365e062312ad70f5d0ab5ce8 | 37,197 |
async def create_deliverer_keyboard(
customer_tg_id,
button_text: str,
callback_action: str,
) -> InlineKeyboardMarkup:
"""Creates a keyboard for delivery man."""
keyboard = [
[
InlineKeyboardButton(
text=button_text,
callback_data=f'{callback_acti... | 71f15a2b061f235a12f3a211732054718d45c76b | 37,198 |
def get_trial_id():
"""Trial id for the corresponding trial of this Trainable.
For function API use only. Do not call this method in the Class API. Use
`self.trial_id` instead.
"""
_session = get_session()
return _session.trial_id | 69c40d2a5d3541e0568ddcbfddf65fc848801097 | 37,199 |
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