content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def convert_shape_to_tensor(shape, name=None):
"""Convert a static shape to a tensor."""
if isinstance(shape, (tuple, list)) and not shape:
dtype = tf.dtypes.int32
else:
dtype = None
return tf.convert_to_tensor(shape, dtype=dtype, name=name) | abd5bfad082095c4f954fa6412b15f7dcb7a5fa8 | 61,660 |
from ezdxf.lldxf.validator import is_dxf_file, is_binary_dxf_file
from ezdxf.tools.codepage import is_supported_encoding
from ezdxf.lldxf.tagger import binary_tags_loader
from typing import Union
from pathlib import Path
def readfile(
filename: Union[str, "Path"],
encoding: str = None,
errors: str = "surr... | e398610ab0e8ceb1647399eb3db9bb07c358f6c0 | 61,661 |
def mock_subprocess_run(*args, **kwargs):
"""Mock calls to subprocess by routing them to the right mock"""
command = args[0][1]
if command == "show":
return mock_pip_show(*args, **kwargs)
elif command == "freeze":
return mock_pip_freeze(*args, **kwargs) | da7b24cef209c1d4d56e55609d3c318d9895d470 | 61,662 |
def kick(ips, tau):
"""Kick operator.
"""
ips.set_acc(ips)
if ips.include_pn_corrections:
return kick_pn(ips, tau)
return kick_n(ips, tau) | d47e826c0bb8f066fcae25e4ba871d38905f51b0 | 61,663 |
def replace_extension(filename, new_extension, add_to_end=False):
"""Replaces the extension in the filename with the new_extension."""
dot = filename.rfind(".")
if dot < 0 or filename[dot + 1:] == new_extension or add_to_end:
filename_base = filename
else:
filename_base = filename[:dot]
... | 75b04c37dffb3dd92f3fe12295b18efb52dfa2ef | 61,664 |
from bs4 import BeautifulSoup
def wrap_with_tag(html: str, document_wrapper_class: str) -> str:
"""
Wraps a string of HTML with a div using a given wrapper class
Args:
html (str): The HTML to be wrapped
document_wrapper_class(str): The class with which to wrap the HTML
Returns:
... | 075cf4ef818eb38f2b0a8a16c76fcc5cc11cdec9 | 61,665 |
def slave_entry(slave, programs, filesystems):
"""
Template tag {% slave_entry slave programms %} is used to display a single
slave.
Arguments
---------
slave: Slave object
programs: Array of programs
Returns
-------
A context which maps the slave object to slave an... | 7449eec9d906bfe74245cbdec2a76fd7a2fc8157 | 61,666 |
from dateutil import tz
import logging
def initialize_free(begin_datetime,end_datetime):
"""
initialize the free time
"""
#Generates the free time array every date from user defined time
ini_free = []
datetime_diff = end_datetime - begin_datetime
#Initialize the free date and time
free_end_datetime = arrow.... | a85e8058375baafb734852be02234c13c3eef415 | 61,667 |
def get_scatter_xy(x, y):
"""
Generate scatterplot with auxiliaries by given columns `x` and `y`.
The return is JSON in vega-lite schema.
"""
df = pd.DataFrame({"x": x, "y": y})
return get_scatter(df) | f782c5efb6a884b0be0816f49f50b31cb99eb0d4 | 61,668 |
def extractor(data, cell_type, conditions, cell_type_key="cell_type", condition_key="condition"):
"""
Returns a list of `data` files while filtering for a specific `cell_type`.
# Parameters
data: `~anndata.AnnData`
Annotated data matrix
cell_type: basestring
s... | 397ec9fa41ae6686e85754aac75c43fab19e817b | 61,669 |
def get_depth_to_slice(image_instance, depth='auto'):
"""
Parameters
----------
image_instance: ImageInstance
An image
depth: str|tuple
One of {'auto', 'time', 'zStack'} or a tuple containing {'time', 'zStack'} in any order. Which field to read for getting the depth.
Returns
... | 44d7854db735d3ba077dc61f23a9cf771560748f | 61,670 |
def cfd(signal, fraction, delay=1, threshold=0):
"""Constant Fraction Discriminator
:param np.array signal: the input from the digitizer
:param float fraction: the fraction, from 0 to 1
:param float delay: the delay of the CFD
:param float threshold: the threshold
:return np.array edge_indices:... | 25308beffeb29211bd7d6f2f85e16bc621206c1e | 61,671 |
import json
def cluster_list_by_ids(realm):
""" this function returns the doc matching the cluster id """
cluster = Cluster(ES)
account = Account(ES)
account_email = json.loads(request.cookies.get('account'))["email"]
cluster_ids = request.args.getlist('ids[]')
if account.is_active_realm_mem... | 9bed8e1b98453d357ea9a406f05e41b8144d527f | 61,672 |
def dreadSkull(Z, p=None, Z0=None, ET=None):
"""
par_set['zoom'] = 0.4
Args:
Z: a real or complex number
p: a real of complex number
Returns:
Z: the result (complex)
p[0]
MATLAB:
Z = (-Z)^(-exp(Z^x)^(exp(Z^x)^(-exp(Z^x)^(exp(Z^x)^(-exp(Z^x)^(exp(Z^x)^(-... | 678e0b782a3fb55529ef4afcf35e1207facc5d14 | 61,673 |
def rescale_sound(snd_array, rescale):
"""Rescale the sound with the provided rescaling method (if supported).
Args:
snd_array (array): The array containing the sound data.
rescale ({'standardize', 'normalize', None}): Determines type of
rescaling to perform. 'standardize' will divide by the max valu... | ccb8f970d14da59b18eb74118260c33d48c1b7ba | 61,674 |
import logging
def count_total_molecules(filename: str) -> int:
"""Counts number of molecules in a file"""
logging.info("Counting total molecules in file %s", filename)
total = 0
ifs = oechem.oemolistream(filename)
mol = oechem.OEMol()
while oechem.OEReadMolecule(ifs, mol):
total += 1
... | ed376769e5468c8d8943e9ab370c69981df69363 | 61,675 |
from pathlib import Path
def get_and_mark_bundle_cache_version(bundle_base: str, *,
previously_bundled: bool) -> int:
"""
Check and return the bundle cache version.
The marker filename is `.bundle_cache_version`.
:param str bundle_base: The bundle directory
... | 74ab1584b60ffb77dbb3709d01ea4df00a448ea4 | 61,676 |
def order_details(order_id):
"""Shows details of an order.
arguments:
order_id - id of the order
Requires administrator privileges.
"""
order = Order.get_by_id(order_id)
return render_template('order/order_details.html', order=order) | 0b59f1ee859129343902c4ac8e326f56b823a680 | 61,677 |
def simulate_Poisson(intensity, region=(0, 1), seed=None):
"""
Provide points that are distributed by a uniform Poisson point process within the boundaries given by `region`.
Parameters
----------
intensity : int, float
The intensity (points per unit region measure) of the point process
... | 5d93a40bf032037e362d857f0bad8e56fec9c78f | 61,678 |
def mdown(context,text):
"""
Exported version of mdown.
"""
return _mdown(text) | 24efeee8241304335cce0b93421b84e5f5f32dba | 61,679 |
def sample_bernoulli(mean: np.ndarray) -> np.ndarray:
"""Samples from a bernoulli distribution with `mean`.
Args:
mean (np.ndarray): Mean of the bernoulli distribution.
Returns:
np.ndarray: Returns the drawn samples.
Example:
>>> # Sample from a bernoulli distribution with mea... | 9615c38c02f3cd941183bdbdeb187df80bc4d1b3 | 61,680 |
import torch
import test
def construct_and_train(name='last_model', dataset='cifar10', model='vgg', resume=False, epochs=100,
lr=0.1, batch_size=128, momentum=0.9, weight_decay=5e-4,
comp=False, noscale=False, memory=False, mnorm=False, mback=False, norm_ratio=False):
... | 8a75691fd8be9f4d1a35f7f307adb18079276e8c | 61,681 |
import click
def command(*args, **kwargs):
"""
A helper for decorating commands a-la `click.command`, but pulling the help string
from `<function>.__doc__` by default.
Also allows the use of custom arguments, which are stored on the command, as in
"adoc_examples".
"""
disable_opts = kwarg... | 929ac24a4c70e920fc0b238f6ccf98bed1750266 | 61,683 |
def haversine(lon1, lat1, lon2, lat2):
"""
Calculate the great circle distance between two points
on the earth (specified in decimal degrees).
Use of Euclidean distance in calculating geographical
distance is rarely, if ever, recommended.
"""
# convert decimal degrees to radians
lon1, la... | 34dc735d350bba7a33c47cf69d009a2022ee6af2 | 61,684 |
import asyncio
async def async_setup(hass, config):
"""Set up the Ais Files platform."""
# register services
@asyncio.coroutine
async def async_remove_file(call):
if "path" not in call.data:
return
await _async_remove_file(hass, call.data["path"])
@asyncio.coroutine
... | 69429f377e0c375b56527ded9d0d7623e4d8d3bf | 61,685 |
def _background(cmd, sockname="dtach"):
""" Run tasks in background
Make sure dtach is installed.
"""
return run('dtach -n `mktemp -u /tmp/%s.XXXX` %s' % (sockname, cmd)) | 05d4c6fcc83d1aaa2552c8594450c80bd47c3acc | 61,686 |
def isinrectbnd(x: int, y: int,
xmin: int, ymin: int,
xmax: int, ymax: int) -> bool:
"""Checks if the x and y values
lie within the rectangular area
defined by xmin, ymin and
xmax, ymax
Args:
x, y: (x,y) coordinates to test
xmin, ymin: min (x, ... | 3f67de8669a258a554a8754786579517a07bc321 | 61,687 |
def get_column_combinations(columns, k=5):
"""
Returns all possible combinations using k columns.
"""
results = combinations(columns, k)
return results | 0bab7b7d9377526d4ac98b6464d4e65435edd7a1 | 61,688 |
import binascii
def crc_srec(hexstr):
"""Calculate the CRC for given Motorola S-Record hexstring.
"""
crc = sum(bytearray(binascii.unhexlify(hexstr)))
crc &= 0xff
crc ^= 0xff
return crc | 835da45b3407e2fb32e8a715d465647ea9b86805 | 61,689 |
import torch
def get_masks(slen, lengths, causal, padding_mask=None):
"""
Generate hidden states mask, and optionally an attention mask.
"""
alen = torch.arange(slen, dtype=torch.long, device=lengths.device)
if padding_mask is not None:
mask = padding_mask
else:
assert lengths.... | 828dea2c33420a9e038e739e979d3c8ab211dfef | 61,690 |
def every_other(x, name=None):
"""Drops every other value from the tensor and returns a 1D tensor.
This is useful if you are running multiple inputs through a model tower
before splitting them and you want to line it up with some other data.
Args:
x: the target tensor.
name: the name for this op, defa... | 848d1050435ba014f627e372cdaea6b637667e35 | 61,691 |
def clock_in(client_id, employee_id, project_id=None):
"""
Clock in an employee.
Args:
client_id:
The ID of the client the employee works for.
employee_id:
The ID of the employee who is clocking in.
project_id:
The ID of the project the employee i... | f895328c624cf94c1e1929ec21770e69546ba174 | 61,694 |
def draw_region(img):
"""Driver function for the user to draw a rectangle
Parameters
----------
img : numpy.dnarray
image to draw a rectangle on
Returns
-------
array
coordinates of the rectangle the user has draw
"""
while True:
# displaying the image
... | f40a13f33e438de146d52ea1a8f9e71dec55e79a | 61,695 |
def tn_category_columns_builder(features):
"""Builds tensornet category feature columns."""
columns = {}
for slot in set(features):
columns[slot] = tn.feature_column.category_column(key=slot)
return columns | 74d166b31f4aa229d6340c852052a3bef4c202d7 | 61,696 |
def removepackages(pkgnames, forcedeletebundles=False, listfiles=False,
rebuildpkgdb=False, noremovereceipts=False,
noupdateapplepkgdb=False):
"""
Our main function, called by installer.py to remove items based on
receipt info.
"""
if pkgnames == []:
mun... | 7165d5d26ffce126d529104a589790878ac21693 | 61,698 |
def _estimate_sigma_kth(
X: np.ndarray, Y: np.ndarray, percent: float = 0.3
) -> np.ndarray:
"""Private function to compute kth percent sigma."""
# compute distance matrix
dists = pdist_squareform(X, Y)
# find the kth distance
sigma = kth_percent_distance(dists=dists, k=percent)
return sigm... | 6f3c93e521eb75af55a7d764caea7d99722356c3 | 61,699 |
def get_uploads_from_model(instance, attr):
"""Replaces attachment files from model to a given location,
returns list of opened files of dict {file:'file',date:date,name:'filename'}"""
ats = []
files = getattr(instance, attr)
for fl in files.all():
ats.append({"file": File(fl.file)... | 5de237811454c1c62634576dfdcd79bd51d13211 | 61,700 |
import pathlib
def check(root: pathlib.Path = pathlib.Path(".")):
"""Checks that all toml files parse and that values match the template value
types."""
possible_templates = list(root.glob("*.template.toml"))
if len(possible_templates) > 1:
raise ValueError("Only one template supported")
i... | 4ef6b98aa7306bf5db92d94b2deaa269f4ea7470 | 61,701 |
def remove_prefix(string: str, prefix: str):
"""
Removes a prefix from a string if present.
Args:
string (`str`): The string to remove the prefix from.
prefix (`str`): The prefix to remove.
Returns:
The string without the prefix.
"""
return string[len(prefix) :] if stri... | 598e1b9b863d342e757e54cf94035da63e3ace1f | 61,702 |
import functools
def input_handling(func):
"""Decorator that handles input naming for interpolations."""
@functools.wraps(func)
def wrapper_input_handling(*args, **kwargs):
# unpack args
phi, theta, target_theta_levels, phi_dim, theta_dim, target_dim = args
# pop kwargs used for... | 9aa73218776d9ffa29d878036825c906fc428521 | 61,703 |
def get_params(opt_over, net, net_input, downsampler=None):
"""
Returns parameters that we want to optimize over.
:param opt_over: comma separated list, e.g. "net,input" or "net"
:param net: network
:param net_input: torch.Tensor that stores input `z`
:param downsampler:
:return:
"""
... | b8a3c26b5307c0ba584e3841a2d98f337c618bf8 | 61,705 |
def _top_k(distance_profile, k, exclusion_zone, option):
"""
Finds top k discords or motifs given an exclusion zone. The exclusion zone
acts as a buffer between a found index on the left and right hand side.
For example, if you set the exclusion zone to 4 and a motif or discord was
found at index ... | 922439992b77bf5852f37d8241c803fc04e05040 | 61,706 |
def coa_nonirrigated_cropland_fba_cleanup(fba, **kwargs):
"""
When using irrigated cropland, aggregate sectors to cropland and total ag land. Doing this because published values
for irrigated harvested cropland do not include the water use for vegetables, woody crops, berries.
:param fba:
:return:
... | 7e7495afef48fb7e772ecc92b76d22a82a6049c7 | 61,707 |
def write_tlv(data: dict):
"""Convert a dict to TLV8 bytes.
NB: This simple implementation assumes all values are bytes!
"""
tlv = b""
for key, value in data.items():
tag = bytes([int(key)])
length = len(value)
pos = 0
# A tag with length > 255 is added multiple tim... | e0da4f6374507e4f5b83b48826b7d7f31fd47dd5 | 61,708 |
import torch
def stensor(data, stable_dims=(), dtype=None, device=None,
requires_grad=False, pin_memory=False):
"""
Constructs a STensor from input data and a partition index placement
Args:
data: Initial data for the stensor. Can be a list, tuple,
NumPy ``ndarray``, scal... | 0c3307a94f341fa698e5b620b711089d5c9c3f4d | 61,709 |
def mulmat(X,Y):
"""
Multiplies a matrix X to a matrix Y
NOTE: Does no checks any matrix sizes.
Parameters
----------
X(list) : The X list as matrix
Y(list) : The Y list as matrix
Returns
-------
list : Result multiplied matrix X*Y
"""
result = matrix(len(X), len(Y[0])... | 887e7c7c7563abb636affb9c5634fb7f9a7fe0fe | 61,710 |
import math
def softplus(x):
"""Softplus activation function
Args:
x (float): input value
Returns:
float: output value
"""
try:
return math.log(1 + math.exp(x))
except OverflowError:
return 0 if x < 0 else 1 | 637f5bb5b504c2215e7213bbce06e937f13ea080 | 61,711 |
def _find_corners(cluster, cluster_type, n_fast=12, threshold_fast=0.1, method='suppression'):
"""
find 2 corners in the cluster
Method:
'farthest' from the center of mass
'largest' between all the corners
"""
# Find the corners with the corner_fast method
# Be sure there are no holes i... | 68f87879c0fe923cb7ca196b202bc97de65924d9 | 61,712 |
def is_admin(identity=None):
"""Returns True if |identity| (or current identity if None) is an admin.
Admins are identities belonging to 'administrators' group
(see model.ADMIN_GROUP). They have no relation to GAE notion of 'admin'.
See 'is_superuser' for asserting GAE-level admin access.
"""
return is_gr... | 0939eeea105c70ed5632e0e9b69243b4c3df4f76 | 61,713 |
def create_parser():
"""
:return:
"""
parser = ArgumentParser(add_help=True, parents=[get_parent_parser()])
parser.add_argument(
"--scenario_id",
help="The scenario ID. Required if " "no --scenario is specified.",
)
parser.add_argument(
"--scenario",
help="Th... | 9545faf73a4416bd4ac32d5e94de9c6b41ea2280 | 61,714 |
from typing import Optional
from typing import Any
def nested_get(dct: dict, *keys: str) -> Optional[Any]:
"""Multi-level get helper function."""
for key in keys:
dct = dct.get(key, {})
return dct if dct else None | cd881389157d67365793240e1e2e0b39f4bc1726 | 61,715 |
def data_preprocess(filename, mode='Train', training_data=None):
"""
:param filename: str, the filename to be read into pandas
:param mode: str, indicating the mode we are using (either Train or Test)
:param training_data: DataFrame, a 2D data structure that looks like an excel worksheet
:return: Tuple(data, label... | 115efaa45ff4abaf0d6a6b59eb7fa6fcdf28db82 | 61,716 |
from typing import Optional
from typing import Any
def scatter(
hist: BootstrapHistogram, ax: Optional[MplAxes] = None, **kwargs: Any
) -> Any: #
"""
Scatter plot of the bootstrap samples.
The scatter-point x-coordinate within a bin drawn from a uniform random distribution.
Parameters
-----... | a06ec1ef4b68108a85e31e41b9b1e139d515662d | 61,717 |
def get_ml_eng():
"""
Returns a started matlab engine.
The engine is started and set to the correct directory for Monocap. The
startup code for Monocap is then run to ensure all necessary files are
added to the path.
Returns
-------
eng : engine.matlabengine.MatlabEngine
... | 86856231111efef6d9fccc3d9fed6cb526d490ca | 61,718 |
def train_test_data(dataframe, target_variable_name, train_size=.8, random_state=42):
"""
Returns dataframes of training and test sets
Use this function if implementing cross validation with sklearn
:param dataframe: pandas.DataFrame
:param target_variable_name: str
:param train_size: float from... | 373494f59c1a68d8504fd13f8d028bdd478f37a2 | 61,719 |
def only_moto(request):
"""Return True if only moto ports are to be used for mock services."""
return request.config.option.only_moto | 1ab211925a411d4999a22e77d819da88b4477ed6 | 61,721 |
def get_nframes(video_name, last_frame, nframes = 10):
"""
Extracts nframes from video to create training batches.
:param video_name: absolute path to video
:param last_frame: frame of interest
:param nframes: number of frames to take
:return: array of size nframes x width x height x RGB, with ... | adb00d890a2c2c5e2d4fabe0e2d6dc25e18766ab | 61,722 |
def validate_permissions(
hass, minimum_permissions, token_path=DEFAULT_CACHE_PATH, filename=TOKEN_FILENAME
):
"""Validate the permissions."""
permissions = get_permissions(hass, token_path, filename)
if not permissions:
return False
for minimum_perm in minimum_permissions:
permissi... | ccbf14b17a78410f775ecd38d2a762bab5179271 | 61,724 |
def find(sub_str, target_str):
"""[summary]
字符串查找
Arguments:
sub_str {str} -- substring
target_str {str} -- target string
Returns:
bool -- if substring is found in target string
"""
return sub_str in target_str
# in operator用的是Boyer–Moore算法，最坏情况O(mn), 最好情况O(n/m)
... | d26e4ad79eaf913d81126d7647036b857de5ed6d | 61,725 |
def _source_step(func):
"""
Transform a iterator factory to a pipeline source
:Warning: The step ignores its in_queue and only writes to the out_queue.
:Parameters:
`func` : callable
iterator
:Return: New step class
:Rtype: ``type``
"""
class _SourceStep(AbstractStep):
... | dc8a6e53add8c24075a96a2a3e1b188f51903ae5 | 61,726 |
import math
def num_to_thaiword(number: int) -> str:
"""
This function convert number to Thai text
:param int number: an integer number to be converted to Thai text
:return: text representing the number in Thai
:rtype: str
:Example:
>>> from pythainlp.util import num_to_thaiword
... | 77e7021cfc36886b76af9c5ae93c0d4c40dfa005 | 61,727 |
def check_faces_in_caption(photo):
"""Checks if all faces are mentioned in the caption."""
comment = photo.comment
if photo.getfaces() and not comment:
return False
for face in photo.getfaces():
parts = face.split(" ")
# Look for the full name or just the first name.
if (... | eed03439df84a1ddd4cb7bcbb269af7c60adfcb5 | 61,729 |
def create_light_sensor():
"""
Create a new light sensor.
:return: New sensor object.
"""
temp = build.Light()
temp.current_value = float(input("\n" + Lang["< Insert current value >"] + "\n\n>>"))
clear()
temp.sampling_freq = float(input("\n" + Lang["< Insert sampling frequency >"] + "\n... | 52a2f9316401c62215e55f8f9249c84ae9bfde9a | 61,731 |
def prcs_blast_rslts_xml(filepath, args):
"""
Processes the blast results stored in an xml file and then scrapes online
databases for ec numbers.
:param filepath: The filepath of the blast results xml file.
:param args: A python dictionary of command line arguments
:return: The results of ... | 5fa2365a99f50bdce6a5f5a5f3a6cfed4e5b8dc6 | 61,732 |
from typing import Any
from typing import IO
from typing import List
from re import A
import abc
def wait(*l: Fiber[Any, Any, Any]) -> IO[R, E, List[Result[R, A]]]:
"""
Wait until these Fibers finish. Return the list of Result
in the same order.
:param l:
:return:
"""
if len(l) == 1 and is... | 205130d88643f29b3bd7f6d8b6609fd18700aa4d | 61,736 |
def mp_move_files(multiprocessing_pool_vars):
""" Moves the file as given with multiprocessing_pool_vars (iterable)
multiprocessing_pool_vars: [filename, from_dir, to_dir]
:param multiprocessing_pool_vars:
:returns: list
"""
filename = multiprocessing_pool_vars[0]
from_dir = multiprocessing_... | d8bf3fbd1cd77aff75a259ee311ab1a29ca6ab7b | 61,737 |
import json
def add ( data ):
"""Process JSON string to add to data set"""
if util_json_bad(data):
raise BadJsonError(data)
return
t = json.loads(data, strict=False)
name = t["dataset"]
keys = t["keys"]
values = t["values"]
if util_key_bad(keys):
raise BadKey... | 9182f0cfa77231b02d4f7f70e68c8989c73d7fed | 61,738 |
def LfromS(seq):
"""
Compute Schroder function value L from a given sequence.
This performs the calculation by plodding through the algorithm given in
the paper. Humans can easily recognize the relation between elements of S
and length of runs of 0s or 1s in the binary representation of L. Knowing
that, the... | 6adf8c0b6f8e12d7e6a79efcb38c628ef0b29031 | 61,739 |
import numpy
def negative_binary_f_two(func, c, x, y):
"""Test negative values as input to func as second argument."""
x = x + (-4)
z = func(c, x)
z = numpy.clip(z, 0, 63).astype(numpy.int32) + y
return z | aec636cbf7c8733ce5584381d8be5bd25cf7d167 | 61,740 |
def prop_test(data, prop_0, alternative = 'equal', alpha = 0.05):
"""
This function is used to implement the prop_test
Input params:
data (dataframe of boolean): dataframe restricted to the specified column to evaluate
prop_0 (float) : values of the alternative testing
... | 5b0094d6cf53e4709fe379196a6c8a80670d4d45 | 61,743 |
from re import T
def task():
""" RESTful CRUD controller """
tablename = "project_task"
table = s3db[tablename]
# Custom Method to add Comments
s3mgr.model.set_method(module, resourcename,
method="discuss",
action=discuss)
statuses = resp... | b6c4e613a042cebc029023f309e0b55df5b45525 | 61,744 |
def interpret_where_clause(
interpreter, speaker, where_d, memory_type="ReferenceObject", ignore_self=False
):
"""
where_d is a sentence (nested dict/list) of the recursive form
COMPARATOR, TRIPLE, or {CONJUNCTION, [where_clauses]}
where each CONJUCTION is either "AND", "OR", or "NOT"
"""
... | 3f8e24ffe3cb44fe9c96d7535c1b9ee381979210 | 61,746 |
def generate_point():
"""
X: [tRexX,tRexY,speed,obsX,obsY]
Y: [passReward,jumpReward]
"""
X = np.array([
np.random.normal(23,1), # tRex X
np.random.uniform(0,90), # tRex Y
np.random.uniform(6,12), # speed
np.random.uniform(-50,700), # obs1 X
np.rando... | 13a8482247e0b1f58f8fb7dce317c2ade9e9f04b | 61,747 |
import torch
def nms (boxes, nms_thresh):
""" None Max Separetion """
if len (boxes) == 0:
return boxes
det_confs = torch.zeros (len (boxes))
for i in range (len (boxes)):
det_confs [i] = 1 - boxes [i][4]
_, sortIds = torch.sort (det_confs)
out_boxes = []
for i in range (... | 6d2d152a87f5f595a541ca03d870e8a89de671db | 61,748 |
def _compute_coords(shape, xyz_resolution=1, origin='center'):
"""Returns the real_coordinates of an image with the given shape
at the given resolution as a single numpy array of shape (*shape, len(shape))."""
axes = _compute_axes(shape, xyz_resolution, origin)
meshes = np.meshgrid(*axes, indexing='i... | 7d460c7ed6a5c292eb732be4e9d2a58c2298d16b | 61,749 |
def read_db_config(filename=CONFIG_FILE, section=DBTYPE):
""" Read database configuration file and return a dictionary object
:param filename: name of the configuration file
:param section: section of database configuration
:return: a dictionary of configuration parameters
"""
# create parser an... | e6a2837f2d11389e6f2680041f73de0fa17dc5af | 61,750 |
import requests
def send_message_to_telegram(msg='hi'):
"""in: str, out: str"""
METHOD_NAME = 'sendMessage'
for my_id in TELEGRAM_ID_LIST:
data_to_send = {
'chat_id': my_id,
'text': msg
}
header = {
'Content-Type': 'application/x-www-form-urlen... | 5818d863b5abd8bc3640c135528320953c74ea3e | 61,751 |
import json
def get_track_info(item_id):
"""
A function that gets track name information from item id
:param item_id: the item id to find
:return: the String type name of track
"""
f = open(str(dir_path) + r"/metadata/json/track.json", encoding="utf-8")
data = json.load(f)
try:
... | 1a444ae09dc3a9966039f9a226a4d9630e7c207d | 61,753 |
from typing import Dict
from typing import Any
def find_class(klass, dictionary: Dict[str, Any]):
"""
Given a dictionary, find the best-fit class among the subclasses
of the supplied class.
"""
dictionary_keys = key_strings_from_dict(dictionary)
classes = all_visible_subclasses(klass)
clas... | 9c6736467aec269f83033cc3da2e457e1ff094a1 | 61,754 |
def get_text_channel(
guild: discord.Guild, *text_channel_names: str
) -> discord.TextChannel:
"""
Get the first text_channel found in @names or raise an Exception.
"""
for name in text_channel_names:
text_channel = discord.utils.get(guild.text_channels, name=name)
if text_channel:
... | b3ae871d341608a10c6c70fb3da907e4fb56797a | 61,755 |
def use_snippets(document, position):
"""
Determine if it's necessary to return snippets in code completions.
This returns `False` if a completion is being requested on an import
statement, `True` otherwise.
"""
line = position['line']
lines = document.source.split('\n', line)
act_lines... | 1cf60c6979e374a478d69802b9c89c68de635033 | 61,757 |
import random
def contest(other):
"""contests human ability"""
return random.randint(1, 20) > round(other.advantage / 5) | a87cc2ffc7d01f493d99b3808735f7954847caaa | 61,758 |
def rs(hass):
"""Return CommandCover instance."""
return cmd_rs.CommandCover(
hass,
"foo",
"command_open",
"command_close",
"command_stop",
"command_state",
None,
) | 04e7e846a019dd4b47fb93ac12b857013713043a | 61,759 |
def _preprocess_arguments(domain, funcs, config):
""" Preprocess domain arguments and configuration file. """
# Preprocess config argument
converted_cp_to_euclidean = False
if isinstance(config, str):
config = load_config_file(config)
if domain is None:
domain = config.domain
# The function
if con... | a2193d83d2301e240ac35c6276e9cffc77600913 | 61,760 |
def load_simulated_gaussian(partition='complete', **kwargs):
"""
Synthetic data with a Gaussian (non-linear) log-risk function.
For more information, see [#katzman1]_ as well as the accompanying README.
Parameters
----------
partition: string
Partition of the data to load.
... | 1fdb49ee518a94b3d1f0dbb0ad9aff740a865439 | 61,761 |
def encode_target(target):
"""Apply one-hot-encoding to encode target values.
Author: Jernej Vivod (vivod.jernej@gmail.com)
Args:
target (numpy.ndarray): target variable values.
Returns:
numpy.ndarray: one-hot-encoded target variable values.
"""
# Encode data using one-hot-e... | 4e07eec0f8210bd686ea390f04c1e276abfad7fd | 61,764 |
def build_auth_args(request):
"""
组装认证信息
"""
# auth_args 用于ESB身份校验
auth_args = {}
if request is None:
return auth_args
ignore_fields = ["rtx"]
for key, value in get_oath_cookies_params().items():
if value in request.COOKIES and key not in ignore_fields:
auth_... | b15ccdd81d2d23ffa196d074ac391344b22e9561 | 61,766 |
def check_mean_greater(alpha, N, mean, n):
"""
H0: m <= m_0
H1: m > m_0,
where m_0 = N.mean
Returns True if H0 is rejected in favor of H1, and False if cannot reject H0.
:param object N: distribution.
"""
assert(0 < alpha < 1.0) # significance level
assert(n > 0) # sample size
... | 9af7f75716b82067230c88a76b40b731e19449cd | 61,768 |
def list_even(obj):
"""
Return a list of all even integers in obj,
or sublists of obj, if obj is a list. If obj is an even
integer, return a list containing obj. Otherwise return
en empty list.
@param int|list obj: possibly nested list of ints, or int
@rtype: list[int]
>>> list_even(... | 8b94f8983f9c8d19163de875089697f6cdab8114 | 61,769 |
def get_output_data_file(given_filename, run_directory, application_name):
"""
Get the csv file where results will be written. This method checks
if the user defined a custom filename. If not, it returns the default.
Important: if the file exists, it will be overwritten.
:param given_filename: the f... | bab5f5410d138aebb8a065201665b35edb1bcbb0 | 61,770 |
def encrypt(backup: str, password: str) -> str:
"""Encrypts a database backup
Pararameters:\n
backup (str): name of the database backup
password (str): encrypting password
Returns:\n
str: cryptogram of the encryption
None: an error ocurred
"""
... | a3b0db8db360a2bb99af7aa4cdc727f4293be7e5 | 61,771 |
def operator_as_argument(statement):
"""This looks at various possible fixes when the bad token is an operator.
The following cases are considered:
1. operator instead of comma
2. operator instead of equal sign
"""
if not statement.bad_token.is_operator() or statement.prev_token == "def":
... | 95ec70aff8c27f626b258ad0d21d9fecfa6347d4 | 61,772 |
async def api_req_add(req: Request, data: Body, authorized: bool = Depends(verify_token)):
"""Добавить данные в бд"""
if authorized:
try:
return {"status_code": 200, "result": DB._add_data(authorized, data)}
except:
raise HTTPException(status_code=500, detail="Ошибка серв... | 794a8c17889ef55d0e4ba10e080e1e2911f50acc | 61,773 |
async def infer_Jinv(self, engine, x):
"""Infer the return type of primitive `Jinv`."""
return await compute_jinv_type(x) | 498fa68608aa5e0655c84bdf305af75e7565b531 | 61,774 |
from typing import Sequence
def count_increases_pairwise(readings: Sequence[int]) -> int:
"""Count the number of times a reading increases."""
counter = 0
for previous_reading, current_reading in iterate_window(readings, 2):
if current_reading > previous_reading:
counter += 1
ret... | 1ec02d072d5c654f684403cab10058dc6f42bc53 | 61,776 |
def load_repository_url() -> str:
"""Return repository URL."""
return load_repository().remote().url.split(".git")[0] | 38c62540dc8e765f2aaec59764a29beacc11eaaa | 61,777 |
def calibrate_box(bbox, reg):
"""校准box
参数：
bbox:pnet生成的box
reg:rnet生成的box偏移值
返回值：
调整后的box是针对原图的绝对坐标
"""
bbox_c = bbox.copy()
w = bbox[:, 2] - bbox[:, 0] + 1
w = np.expand_dims(w, 1)
h = bbox[:, 3] - bbox[:, 1] + 1
h = np.expand_dims(h, 1)
reg_m = np.hstack([w,... | 9829a856cd1c0bbf4becd9436e423384e40b8c35 | 61,778 |
import random
def get_random_testcases(input_directory, max_testcases):
"""Returns list of |max_testcases| testcases."""
testcases_list = get_testcases(input_directory)
return random.SystemRandom().sample(testcases_list, max_testcases) | 3f1736bbea946372f20b6b26cdb8a2ab1ca39f95 | 61,779 |
def ppo_sharpe_port(cov=None, pre=None, as_dense=True):
""" Max Sharpe ratio portfolio using cov-implied returns
:param cov: Covariance matrix
:param pre: Precision matrix
:param as_dense: If false, will return weights in dict formet
:return: np.array of weights
"""
return pp... | 2712ba9a61a3005963c60352f00455cb00200c56 | 61,780 |
def constraints_from_table(table, power_spectrum, boxlen):
"""Load a table containing constraints and convert it into a list of
Constraint objects. Also needs the power spectrum of the CRF that you're
going to build, because it needs to determine the spectral parameters.
Finally, we need the boxsize (i... | de9930b7e108717a944637f0b8e2ef6b627c3d4a | 61,782 |
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