content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def compute_mean_sem(df, key='fold_change'):
"""
Computes the mean and standard error of the fold-change given a
grouped pandas Series.
"""
# Compute the properties
mean_val = df[key].mean()
sem_val = df[key].std() / np.sqrt(len(df))
# Assemble the new pandas series and return.
samp... | ec628f966b2fe5d43261c37e44408d7a22fc6583 | 3,616,004 |
def main() -> int:
"""
Handle program invocation.
:returns: Exit code.
"""
logger.info('Initialising Database Connection')
db = ed_bgs.Database(config['database']['url'], logger)
ebgs = ed_bgs.EliteBGS(logger, db)
# return None
# Looping over monitored factions
for f in config['monitor_factions']:... | bb95137f110cd7fcb8acec2824e07310350d1d46 | 3,616,006 |
import xmlrpc
def stop_vm(client, session, vm, params):
"""Stop an existing virtual machine. It will fail if the virtual machine does
not exist."""
if vm['state'] is None:
return { 'failed': True, 'msg': NOT_EXISTS_ERR }
if vm['state'] in ('hold', 'stopped'):
return { 'changed': False,... | 39a04448f645c337f876a4d48edb8cb4c3cbbfbb | 3,616,007 |
import torch
def accuracy(predictions, labels):
"""
Evaluate accuracy from model predictions against ground truth labels.
"""
ind = torch.argmax(predictions, 1)
# provide labels only for samples, where prediction is available (during the training, not every samples prediction is returned for effic... | 484ba64b2239363daddd206e747f6c1456e236c9 | 3,616,008 |
def _quick_reap():
"""Reaps a task."""
data = _gen_request_data(
properties=dict(dimensions={u'OS': u'Windows-3.1.1'}))
request = task_request.make_request(data)
_result_summary = task_scheduler.schedule_request(request)
reaped_request, run_result = task_scheduler.bot_reap_task(
{'OS': 'Windows-3.... | 54e3c1793a2394ec97158e277fb803b7466fc150 | 3,616,009 |
from klab.bio.basics import residue_type_3to1_map
def read_and_calculate(workspace, pdb_paths):
"""
Calculate a variety of score and distance metrics for the given structures.
"""
# Parse the given restraints file. The restraints definitions are used to
# calculate the "restraint_dist" metric, w... | 568d9647200ee40868421c7e8a957213e045ebad | 3,616,010 |
from typing import Callable
def closure(func: Callable) -> Callable:
"""Wrap a method to eliminate the self keyword from its signature."""
# tried using @functools.wraps, but could not get it to work right
def wrapped(*args, **kwargs):
self = args[0]
if len(args) > 1:
args = a... | 79eaac9fc3f4df2cee66c444fef5f8feff18e5bb | 3,616,011 |
def dynamic_stub(end, group, cardinalities, pool):
"""Creates an face.DynamicStub.
Args:
end: A base.End.
group: The group identifier for all RPCs to be made with the created
face.DynamicStub.
cardinalities: A dict from method identifier to cardinality.Cardinality
value identifying the card... | 4f5e0660323071d8bff85fbaa0ebb9bcb837097b | 3,616,012 |
def get_issns_for_journal(nlm_id):
"""Get a list of the ISSN numbers for a journal given its NLM ID.
Structure of the XML output returned by the NLM Catalog query::
NLMCatalogRecordSet
NLMCatalogRecord
NlmUniqueID
DateCreated
DateRevised
DateAu... | 3c490d29066d6218ed21b72fd3f010c9ac7ca4d5 | 3,616,013 |
def encode(lng, lat, precision=10, bits_per_char=6):
"""Encode a lng/lat position as a geohash using a hilbert curve
This function encodes a lng/lat coordinate to a geohash of length `precision`
on a corresponding a hilbert curve. Each character encodes `bits_per_char` bits
per character (allowed are 2... | 090bffcd46ff26c2428e1fcfc1537da584f63196 | 3,616,014 |
def filter_form(context, *args, **kwargs):
"""Тег представления filter form как таблицы.
"""
filter_form = (args[0] if len(args) > 0
else kwargs.get('filter'))
if not filter_form:
filter_form = context.get('filter')
if filter_form is None:
raise TemplateSyntaxErr... | 50526302a9ea7d08e8818c92a68715313be4591b | 3,616,015 |
def test_lr_monitor_multi_lrs(tmpdir, logging_interval: str):
""" Test that learning rates are extracted and logged for multi lr schedulers. """
tutils.reset_seed()
class CustomBoringModel(BoringModel):
def training_step(self, batch, batch_idx, optimizer_idx):
return super().training_s... | 51e60dfaf745a0dedb6e492828daa7f0f6942839 | 3,616,016 |
def non_max_suppression_bbox(bboxes, confidences, img_size, verbose=False):
"""
high confidence detections suppress all overlapping detections (including
detections at other scales). Detections can partially overlap, but the
center of one detection can not be within another detection.
:param bboxes: Nx4 nump... | fc80d4e039a5658ba23cbc95c7e32297e71ff081 | 3,616,017 |
def inet_ntoa(i):
"""Convert an int to dotted quad."""
return '.'.join(map(str, [(i >> (3-j)*8) & 0xff for j in range(4)])) | b83a6b08118bcd7858cb588f53b71daaf31d358e | 3,616,018 |
def cleanup_string(string):
"""
>>> cleanup_string(u', Road - ')
u'road'
>>> cleanup_string(u',Lighting - ')
u'lighting'
>>> cleanup_string(u', Length - ')
u'length'
>>> cleanup_string(None)
''
>>> cleanup_string(' LIT ..')
'lit'
>>> cleanup_string('poor.')
'poor'
... | 5f9a369a52b798ff8c26bea56fbfe585b3612db0 | 3,616,019 |
def termConvection(t, y, schemeData):
"""
termConvection: approximate a convective term in an HJ PDE with upwinding.
[ ydot, stepBound, schemeData ] = termConvection(t, y, schemeData)
Computes an approximation of motion by a constant velocity field V(x,t)
for a Hamilton-Jacobi PDE (often calle... | 6954cef17beb6d1278dddfaf2ac3537efe42cf78 | 3,616,021 |
def is_field_allowed(name, field_filter=None):
"""
Check is field name is eligible for being split.
For example, '__str__' is not, but 'related__field' is.
"""
if field_filter in ["year", "month", "week", "day", "hour", "minute", "second"]:
return False
return isinstance(name, s... | 8be38b79bab3aeb49219155db0159cc143c38111 | 3,616,022 |
def build(help: dict) -> str:
"""Returns the formatted help string. See the GitHub page for info."""
global _cust_config
final_str = ""
terms = help["terms"]
if "config" in help:
_cust_config = help["config"]
else:
_cust_config = {}
# Terms
for term in terms:
if... | 2c7c89afed8b2e8dbbed49a2edcfadaf69ae4fa8 | 3,616,023 |
import logging
def setup_logger(level):
"""
Setup a logger for the REST handler
"""
logger = logging.getLogger('splunk.appserver.lookup_editor.rest_handler')
logger.propagate = False # Prevent the log messages from being duplicated in the python.log file
logger.setLevel(level)
log_file_p... | 4d0dff0da93d0a32520ebae1c0eaacde284ec179 | 3,616,024 |
from django.contrib.contenttypes import models
from django.contrib.auth import models as auth_models
def _makePermission(perm, model, app_label='editorialmanager'):
"""
Retrieves a Permission according to the given model and app_label.
"""
ct = models.ContentType.objects.get(model=model, app_label=ap... | a2219855a89aab4426a1597632dece89b8aa5afc | 3,616,025 |
def greater_equal(lhs, rhs):
"""Broadcasted elementwise test for (lhs >= rhs).
Parameters
----------
lhs : relay.Expr
The left hand side input data
rhs : relay.Expr
The right hand side input data
Returns
-------
result : relay.Expr
The computed result.
"""
... | 5b9eeab5fb9323a96895c3009cf15f947cb57910 | 3,616,026 |
from typing import List
from typing import Optional
from typing import Dict
def mergeVotingResult(vote: List[int], policevote: Optional[int] = None) -> Dict[int, float]:
"""
Count the vote result and the return the candidates with most votes
### Parameter
- vote: `List[int]`, the vote result
##... | 38649fc4e1c80d31375cce920b39387fd533b0b0 | 3,616,027 |
def get_avatar(burl, height):
""" xxx """
return_data = ''
uid = user_get_uid()
avatar_id = 0
connection = pymysql.connect(host=DB_SRV,
user=DB_USR,
password=DB_PWD,
db=DB_NAME,
... | 1cbbcd31adffb4c5c0d60a803ef65b793cf5cd40 | 3,616,029 |
def signup():
"""
Presents an anonymous user with the registration form and adds their info to the database.
Uses user.set_password() to hash their password (instead of storing it plaintext).
"""
if current_user.is_authenticated:
return redirect(url_for('index'))
form = RegistrationForm... | 76a9f449162f7bd1131ffab9e551f31529431f69 | 3,616,030 |
def read_bdf(iterable):
"""
Read a BDF-format font from the given source.
iterable should be an iterable that yields a string for each line of the
BDF file - for example, a list of strings, or a file-like object.
"""
name = ""
pointSize = 0.0
resX = 0
resY = 0
comments = []
font = None
for line in iterabl... | cb0ae7f28060e702317184ae93d538bd10c1a77c | 3,616,031 |
def parallel_apply(df, group_list, f, num_cores, print_every_n=1000, **kwargs):
"""
A lightweight version of apply using the multiprocess library
:param df: the pandas dataframe that needs to be grouped
:param group_list: a list of variable names to group by
:param f: the function that operates on ... | d14e3d8a354121abf0dfe193eb1cfa2af89d65bd | 3,616,032 |
import requests
import socket
def _do_generate_runner(endpoint):
"""
Get the hostname or IP of the runner.
Will try to get the public host name from AWS metadata first, then from
reverse lookup, and then fall back to using the local hostname
:return: An ip address or a hostname
:rtype: str
... | 0d2f62f393270f12763e0635df38e6bf2e6c596b | 3,616,033 |
def vectorized_is_element(array, choices):
"""
Check if each element of ``array`` is in choices.
Parameters
----------
array : np.ndarray
choices : object
Object implementing __contains__.
Returns
-------
was_element : np.ndarray[bool]
Array indicating whether each ... | 03818826ea0d7a9bf48a6bfce204f591c96dea58 | 3,616,034 |
def what_am_I_from_prob(probabilities, no_of_guesses=5, true_class='', verbose=True):
"""Function to classify based on 'prob'ability layer inputs
probabilities: a vector of input probabilities
no_of_guesses: how many of the top probabilities do you want?
true_class: the real class name if known
outp... | f30692ea00d00dfb12c217751e18f40fde80a7a6 | 3,616,035 |
import typing
def _parse_term_from_lists(
term_list: typing.List, networks: NetworkStore = None
) -> Term:
"""Term is a list where the first element is either a valid functor or the keyword 'list'.
If the first element is list, then this term is a list, we parse recursively all its elements and return the... | 7d2bd73d4f63105e627613c47cea4a21c80ad5ff | 3,616,036 |
def create_urine_features(charts):
""" features of urine color and appearance"""
res = charts.loc[charts.label.str.lower().str.contains('urine', na=False),
['hadm_id', 'eventtime', 'admittime', 'label',
'value', 'valuenum', 'unitname']]
# clean the label column
res['labe... | 379a4707f5a773375e5f289287dd2cc0f4df2c60 | 3,616,037 |
def merge_user_settings(settings):
"""Return the default linter settings merged with the user's settings."""
user = settings.get('user', {})
default = settings.get('default', {})
if user:
tooltip_styles = default.get('tooltip_styles', {})
user_tooltip_styles = user.get('tooltip_styles',... | 969457f907d8431c9af6ef8a1b587575cb3ba681 | 3,616,038 |
def RSRS1(dataFame, Sbuy=1.0, Ssell=0.8):
"""斜率指标交易策略
"""
data = dataFame.copy()
data['flag'] = 0 # 买卖标记
data['position'] = 0 # 持仓标记
position = 0 # 是否持仓，持仓：1，不持仓：0
for i in range(1, data.shape[0] - 1):
# 开仓
if data.loc[i, 'beta'] > Sbuy and position == 0:
data... | a57d6199828b765ceb70d25fc61c4cc559a05580 | 3,616,039 |
def rgb2gray(rgb):
"""
Change RGB color image into grayscale in RGB representation using colorimetric (perceptual luminance-preserving) conversion
:param rgb: NumPy array of the RGB image
:return: NumPy array of grayscale image, same shape as input
"""
r, g, b = rgb[:, :, 0]/255, rgb[:, :, 1]/2... | 3c0b3a4ad1b2057b2b793569e629d36d7be27f7f | 3,616,041 |
import wave
def get_speech_features_from_file(filename,
num_features,
pad_to=8,
features_type='spectrogram',
window_size=20e-3,
window_stride=10e-3,... | bdb92866fa4014c9a1831e1138d1358a8b4d36c5 | 3,616,042 |
def health() -> dict:
"""
Root Get
"""
health = schemas.Health(
name=settings.PROJECT_NAME, api_version=__version__, model_version=model_version
)
return health.dict() | 65b059e44f929886576e9c181ffd8b3b785f17ba | 3,616,043 |
import copy
def site_response(sp, asig, linear=0, freqs=(0.5, 10), xi=0.03):
"""
Run seismic analysis of a soil profile - example based on:
http://opensees.berkeley.edu/wiki/index.php/Site_Response_Analysis_of_a_Layered_Soil_Column_(Total_Stress_Analysis)
Parameters
----------
sp: sfsimodels.... | 5cbbf8b980156ca579135620c81592950f6b7b41 | 3,616,044 |
from typing import Tuple
def _get_field_names(
schema_field_details: Tuple[Tuple[str, DataType], ...],
) -> Tuple[str, ...]:
"""Returns field names from schema fields."""
return tuple(field[0] for field in schema_field_details) | 9e985b0a2619c24004e35f1ead6912a6fad91769 | 3,616,047 |
def strip_outer_matching_chars(s, outer_char):
"""
If a string has the same characters wrapped around it, remove them.
Make sure the pair match.
"""
s = s.strip()
if (s[0] == s[-1]) and s.startswith(outer_char):
return s[1:-1]
return s | b55d1f966a8b216dce2d4817117f350f639b9b83 | 3,616,048 |
def lr_schedule(step):
"""Linear scaling rule optimized for 90 epochs."""
steps_per_epoch = 30000 // FLAGS.batch_size
current_epoch = step / steps_per_epoch # type: float
lr = (1.0 * FLAGS.batch_size) / 32
boundaries = jnp.array((20, 40, 60)) * steps_per_epoch
values = jnp.array([1., 0.1, 0.01, 0.001]) * ... | f0579c77084e1092fc09b7a236b4bf4f848fc1cf | 3,616,050 |
def make_chunks(infos, **kwargs):
"""Generate chunks from note infos"""
return s.chunked(make_sound(infos, **kwargs)) | 1dc4ab1bccc3ed83e008efc45731df4cc532ad99 | 3,616,051 |
from pathlib import Path
def plot_traces_by_qu_unexp_sess(analyspar, sesspar, stimpar, extrapar,
quantpar, sess_info, trace_stats, figpar=None,
savedir=None, modif=False):
"""
plot_traces_by_qu_unexp_sess(analyspar, sesspar, stimpar, extrapar, ... | 7a1bfcf03b4468b58eff8d842ec82c5a508479db | 3,616,053 |
def to_cartesian(p, direction=1, axis='z'):
""" Converts a point given in (r, theta, z) coordinates to
cartesian coordinate system.
optionally, axis can be aligned with either cartesian axis x* or z and
rotation sense can be inverted with direction=-1
*when axis is 'x': theta goes from 0 at y-axis... | 9f171da66e66b1f7a580f0f22d9b5bc7c970cd95 | 3,616,054 |
def getLimits(locations, current, sortResults=True, verbose=False):
"""
Find the projections for each delta in the list of locations, relative to the current location.
Return only the dimensions that are relevant for current.
"""
limit = {}
for l in locations:
a, b = current.comm... | b8c62aecc2ce37fcaefd63544bd64ccba94f257b | 3,616,055 |
def mclag_ka_session_dep_check(ka, session_tmout):
"""Check if the MCLAG Keepalive timer and session timeout values are multiples of each other and keepalive is < session timeout value
"""
if not session_tmout >= ( 3 * ka):
return False, "MCLAG Keepalive:{} Session_timeout:{} values not satisfying ... | 3f3fd6a12711c0c290cdb0fbd68cfd1c743ef515 | 3,616,056 |
import struct
def pack(fmt, *args):
"""pack() is wrapper of struct.pack
"""
value = struct.pack(fmt, *args)
result = []
if isinstance(value, str):
# For Python2
for v in value:
result.append(ord(v))
return result
elif isinstance(value, bytes):
# F... | a9e4349debf9d9d9e088e8c02a9fc044b9a1897b | 3,616,057 |
def get_teacher_information(gid):
"""
Retrieve the team information for all teams in a group.
Args:
gid: the group id
Returns:
A list of team information
"""
group = get_group(gid=gid)
member_information = []
for tid in group["teachers"]:
team_information = api.... | c140fc2718f7bef1dd1367fd187b048e31304dfc | 3,616,058 |
def needs_owner(func):
"""Decorator to require the owner for the given function."""
@wraps(func)
def decorated_function(*args, **kwargs):
if args[0].chat.id != SETTINGS['owner']:
bot.reply_to(args[0], 'Sorry, you are not the owner of this bot')
return
return func(*ar... | 7cbecfb5901b0cab362f30017c615baac1dd9c57 | 3,616,059 |
def decompose_to_device(operation: cirq.Operation, atol: float = 1e-8) -> cirq.OP_TREE:
"""Decompose operation to ionq native operations.
Merges single qubit operations and decomposes two qubit operations
into CZ gates.
Args:
operation: `cirq.Operation` to decompose.
atol: absolute er... | f0b78287d44922482f81f59c1d8a202cf36167d3 | 3,616,060 |
def lucas(n):
""" compute the nth Lucas number """
a, b = 2, 1 # notice that all I had to change from fib were these values?
if n == 0:
return a
for _ in range(n - 1):
a, b = b, a + b
return b | 9d9404edf59690cafc49ba70d7dc776376d1f020 | 3,616,061 |
def do_map_eval(B, S, param, O, W = None, BGp = None):
""" This function evaluate the target function
given a output window set.
Args:
B: .
S: .
param: .
O: .
W: .
BGp: .
Returns: statTmp: .
"""
statTmp = {}
statTmp['W'] = np.array([])
statTmp['Xp'] =... | 1cf7ced27aac09a996b359936b28ad00b0fb7527 | 3,616,062 |
def transform_disturbances(draws, shocks_mean, shocks_cholesky):
"""Transform the standard normal deviates to the relevant distribution."""
draws_transformed = draws.dot(shocks_cholesky.T)
draws_transformed += shocks_mean
draws_transformed[:, :2] = np.clip(
np.exp(draws_transformed[:, :2]), 0.... | 532096f3710ebcf7259dfa8641152efc98db1660 | 3,616,063 |
import torch
def predict_one_scan_binary_class(rescaled_array, direction, checkpoint_path, array_info, batch_size=16, evaluate=False):
"""
:param array_info: stores information of the rescaled_array
:param rescaled_array: float32 array in shape [512, 512, 512, data_channel + enhanced_channel + semantic_ch... | 4b7fb388a1b557c4f2c13eeeea24989cfe9c29a2 | 3,616,064 |
def shuffle_batch(labeled_tensors,
batch_size,
num_threads=1,
capacity=32,
enqueue_many=False,
min_after_dequeue=0,
seed=None,
allow_smaller_final_batch=False,
name=None):
""... | 923f16f93e9107e8b2969c084751fb78e8f177fe | 3,616,065 |
from typing import Tuple
from typing import Union
def natural_keys(text: str) -> Tuple[Union[int, str], ...]:
"""
alist.sort(key=natural_keys) sorts in human order
:see: http://nedbatchelder.com/blog/200712/human_sorting.html
:see: http://stackoverflow.com/a/5967539/1391325
"""
return tuple(__atoi(c) for c in ... | d8c902ee7ee06fa33001e75f2c0fb87d83126175 | 3,616,066 |
def return_dict_of_attrs(obj):
"""
Returns dictionary of attributes of object that are not private or None,
and which top namespace is not sqlalchemy or wpipe.
Parameters
----------
obj
Input object.
Returns
-------
attrs : dict
Dictionary of attributes of obj.
... | 465abfd8ebb19d8dbfd5d8e6dd7cbb9099ad0b36 | 3,616,067 |
def BenefitSurg(t):
"""Surgery benefits"""
return SizeBenefitSurg(t) * PolsSurg(t) | 3376ae734d92b00b0bbb4ec6246e533f00bc88ce | 3,616,068 |
def _get_edge_attrs(edge_attrs, concat_qualifiers):
""" get edge attrs, returns for qualifiers always a list """
attrs = dict()
if "qualifiers" not in edge_attrs:
attrs["qualifiers"] = []
elif edge_attrs["qualifiers"] is None:
attrs["qualifiers"] = edge_attrs["qualifiers"]
if at... | 8500ae7c606041071264d980155fbada98ba870e | 3,616,069 |
def destroy_raid_bdev(client, name):
"""Destroy pooled device
Args:
name: raid bdev name
Returns:
None
"""
params = {'name': name}
return client.call('destroy_raid_bdev', params) | ef377fc024cd326ef3e496ffc94b10ef2076e1e2 | 3,616,070 |
def get_closest_point_index(pt, pts):
""" Closest point index of the pts from pt. """
distances = [rs.Distance(p, pt) for p in pts]
min_index = distances.index(min(distances))
return min_index | 5df14d648ead10e694323785625aa842a1ddd1ff | 3,616,071 |
def IFS(FS, T0=2 * np.pi, m_start=-4, m_stop=4, x_min=0, x_max=2 * np.pi, x_num=10):
"""Function to reconstruct (or check) the periodic function from the
obtained Fourier coefficients"""
m = np.arange(m_start, m_stop + 1)
m = np.reshape(m, (-1, m.size))
M = np.tile(m, (x_num, 1))
x = np.linspa... | 466a4e2c967ebda2a8a0ae6804b4427d695c3928 | 3,616,072 |
def get_calendar(username, base_url='https://github.com/'):
"""retrieves the github commit calendar data for a username"""
base_url = base_url + 'users/' + username
try:
url = base_url + '/contributions'
page = urllib2.urlopen(url)
except (urllib2.HTTPError,urllib2.URLError) as e... | d4c40371ed208046e97e79d92fb97c5a8e60c463 | 3,616,073 |
def stop_comm_msg_create(pid: int, ts: float) -> message.Message:
"""
create a message to stop the comm_handler
:param pid: agent pid
:type pid: int
:param ts: timestamp
:type ts: float
:return: stop communication handler message
:rtype: Message
"""
return message.Message(pid,... | c9d7c6361f276c1b8d54402aad713b05f17044ac | 3,616,074 |
def _normalize_data(data):
"""Turn entities in properties into entity ids"""
entities = data['layout']['entities']
for obj in entities:
schema = model.get(obj.get('schema'))
if schema is None:
raise InvalidData("Invalid schema %s" % obj.get('schema'))
properties = obj.get... | ff5f7de484f1483cc6ce2399d464d73724d3d8ee | 3,616,075 |
def conv2D_generative(inputs, filters, kernel_size=(1, 1),
padding="same", activation=None,
reuse=False, name="conv2D", strides=(1, 1),
dilation_rate=(1, 1), use_bias=True, mask=None,
bias_init=0.
):
""" 2D... | 515915d47c3715ccb60de909e07e10ed65fa60dd | 3,616,076 |
def FlattenList(list):
"""Flattens a list of lists."""
return [item for sublist in list for item in sublist] | 5ab33bd326d221449f9efc0da7ffa39eeedd3add | 3,616,077 |
def _build_state_value(django_request, user):
"""Composes the value for the 'state' parameter.
Packs the current request URI and an XSRF token into an opaque string that
can be passed to the authentication server via the 'state' parameter.
Meant to be similar to oauth2client.appengine._build_state_value.
A... | 4434c025065124f942f436ecf88f383d7cfe6c43 | 3,616,078 |
import sh
def commit(experiment_name, time):
"""
Try to commit repo exactly as it is when starting
the experiment for reproducibility.
"""
try:
sh.git.commit('-a',
m=f'"auto commit tracked '
f'files for new experiment: '
... | b62a32ddae3c53ce16f2931356493b683fa8794c | 3,616,079 |
import numpy
def angd2vec2d(ang: float) -> numpy.array:
"""Convert angle in degrees to a 2-d unit vector in the x-y plane."""
return ang2vecd(ang)[:2] | 03b9ff6f569a1745d6b7a3fb125e92b3eabc95b2 | 3,616,080 |
def pair_align(a, b):
"""
Accurate Registration.
:param a: Point cloud for previous frame.
:param b: Point cloud for current frame.
:return: The matrix.
"""
x = 0
return x | 033515d87b900a7790c4a461409138d420aa164d | 3,616,081 |
async def battery(request):
"""GET /api/battery
cf. https://docs.mistyrobotics.com/misty-ii/rest-api/api-reference/#getbatterylevel
"""
return web.json_response({
'status': 'Success',
'result': generate_batterylevel(),
}) | e1e404ca3cbae05bcf9db0e982fb906197edd05f | 3,616,082 |
def refresh_auth(action):
""" Uses the 'Authorization' block in the request header to return a fresh
token for a user. """
# first, drop GETs trying to do a refresh: we don't play that shit
if action == 'refresh' and flask.request.method == 'GET':
return utils.http_405
setattr(flask.reques... | 375ac68493ec725245647b252819cb7a295c4f48 | 3,616,083 |
from typing import Iterable
from typing import Type
from typing import Union
def apply_noise_to_gates(
circuit: Circuit,
noise: Iterable[Type[Noise]],
target_gates: Union[Iterable[Type[Gate]], np.ndarray],
target_qubits: QubitSet,
) -> Circuit:
"""Apply noise after target gates in target qubits.
... | 1299ce4eaa2ad8f5993767d41883d44af1855ee4 | 3,616,084 |
def load_info(path = defaults._default_info_path, verbose = False):
"""
:param path:
:param verbose:
:return:
"""
if verbose: print(path)
i = classes.InfoClass()
i.load(path)
return i | 582c17e473267b0124ac09a79c0cb9bc9fa9f97a | 3,616,085 |
import numbers
def mlevel(level):
"""Convert level name/int to log level. Borrowed from celery, with <3"""
if level and not isinstance(level, numbers.Integral):
return LOG_LEVELS[level.upper()]
return level | 143f5f4610034d372a55a8a6c1a8c7f4e3ee6a0e | 3,616,087 |
from datetime import datetime
from typing import Dict
from typing import Any
def get_legislation_introduced_since(since_date: datetime) -> Dict[str, Any]:
"""See: http://wslwebservices.leg.wa.gov/legislationservice.asmx?op=GetLegislationIntroducedSince"""
argdict: Dict[str, Any] = dict(sinceDate=since_date)
... | 1d6cb1d0eb1fa01c4305dca422b7fdb22ac18520 | 3,616,090 |
import io
def extern(decorated):
"""
A decorator gadget that generates a Rust extern {} block
Usage:
properties.name = "my::rust::extern"
@extern
function(generator, outfile, ...):
outfile.write("contents inside generated extern block")
Generates:
extern ... | d42470dd962c2b92e03b199872726b10b0a8f7d7 | 3,616,092 |
def make_exp_vocab(exp_dic):
"""
Returns a dictionary that maps words to indices.
"""
exp_vdict = {'<EOS>': 0}
exp_vdict[''] = 1
exp_id = 2
for qid in exp_dic.keys():
exp_strings = exp_dic[qid]
for exp_str in exp_strings:
exp_list = ActivityDataProvider.seq_to_lis... | a496f4bf0e5ef2692f7f904e9dd4c905dc2e7826 | 3,616,093 |
def load_frames(folder_name, offset=0, desired_fps=3, max_frames=40):
"""
:param folder_name: Filename with a gif
:param offset: How many frames into the gif we want to start at
:param desired_fps: How many fps we'll sample from the image
:return: [T, h, w, 3] GIF
"""
coll = ImageCollection(... | 46c41f393cfc73581ef89ba0d4204f0a96a8b303 | 3,616,094 |
from typing import Tuple
from typing import Union
def _verify_data_shape(data, shape, path=None) -> Tuple[bool, Union[str, None]]:
"""
_verify_data_shape(
{'data': []},
{'data': list}
) == (True, None)
_verify_data_shape(
{'data': ''},
{'data': list}
) == (False, '.data')
... | 3e76362938146972d96e34a22373b43dca23381b | 3,616,095 |
def MultipleComparisons(trends, kys, aplha = 0.10, MCmethod="fdr_by"):
"""
Takes the results of an existing trend detection aproach and modifies them to
account for multiple comparisons.
args
trends: list
list of numpy arrays containing results of trend analysis
kys: list
list of what is in results
y... | 9c4a74c9ffe319b3a4058a9252ff5f64de71d048 | 3,616,096 |
def view_questions_default_page():
"""View all tests, for default test page"""
questions = Question.select()
return questions | 8fdf5849bd9536d076f6ffc7f6aa9cc65eb61685 | 3,616,098 |
import random
def chooseAxes(numBits):
"""Return Alice and Bob's randomly chosen mstment axes for the specified
number of qubits in the E91 protocol:
A chooses from (0, pi/4, pi/2) with equal probability,
B chooses from (pi/4, pi/2, 3pi/4) with equal probability.
"""
choicesA ... | 76ae98d9dd4d590d84e2194a3ae0c6bd91ae9838 | 3,616,100 |
import time
def newCommentUri(secs=None):
"""this is essentially a bnode, but a real URI is easier to work with"""
if secs is None:
secs = time.time()
return URIRef("http://bigasterisk.com/comment/%r" % secs) | 00f384ec0c7fe2151ce7a112e9eefddefcfc5407 | 3,616,101 |
def non_max_suppression(dets, threshold):
"""执行non-maximum suppression并返回保留的boxes的索引.
dets:(x1、y1、x2、y2,scores)
threshold: Float型. 用于过滤IoU的阈值.
"""
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
# 每一个检测框的面积
areas = (x2 - x1 + 1) * (y2 - y1... | fdd4917e85641def1b13d6764a3d880b271721a4 | 3,616,103 |
from windspharm.xarray import VectorWind
def wind_rot_div(u, v, truncation=None, const=None):
"""Split the wind field into divergent and zonal mean and eddy rotational components."""
vec = VectorWind(u, v, rsphere=const.rplanet_m)
div_cmpnt_u, div_cmpnt_v, rot_cmpnt_u, rot_cmpnt_v = vec.helmholtz(truncat... | a45ea9f5807d6756dd9b770d9e3e33bd8b03c0f5 | 3,616,105 |
def blank_image(width=1024, height=1024, background=BG_COLOR):
"""
It creates a blank image of the given background color
"""
img = np.full((height, width, MONOCHROME), background, np.uint8)
return img | aa96b09e2233b8371321df3837278488399d9332 | 3,616,106 |
def pretrained_embedding_layer(word_to_vec_map, word_to_index):
"""
Creates a Keras Embedding() layer and loads in pre-trained GloVe 50-dimensional vectors.
Arguments:
word_to_vec_map -- dictionary mapping words to their GloVe vector representation.
word_to_index -- dictionary mapping from words to... | ecc973587aaa08cbe5d5b10c582c38374b992de9 | 3,616,108 |
async def update_request(connection: Connection, old_key: str, new_key: str, json: str) -> int:
"""
returns amount of entries updated
"""
return await connection.execute(
"""
update
requests.requests
set
id = :new_key,
body = :json,
... | a67b31ed409be5cdd6269409e9d355c2d763bf80 | 3,616,110 |
from datetime import datetime
def _prepare_transactions(response, telegram_id, mcc_codes):
"""Parse response from monobank API and return formatted transaction."""
transactions = []
costs_converter = 100.0
for transaction in response:
transactions.append((
transaction["id"],
... | 0794c0761e7232bf517dd867f4d8bab252b2c708 | 3,616,111 |
import torch
def get_gaps(o : Tensor, forward : bool = True, backward : bool = True,
nearest : bool = True, normalize : bool = True):
"""Number of sequence steps from previous, to next and/or to nearest real value along the
last dimension of 3D arrays or tensors"""
_gaps = []
if forward ... | d0b7938687433b2307fd121db07b9cdb09c1f07b | 3,616,112 |
def DoubleCast(value):
"""Explicitly cast a value to type Double."""
if istype(value, Double):
return value
return UPlus(value) | bbef5bfc39c0be1a1ec7572f941596e513adbda9 | 3,616,113 |
def _find_datapoints(sheet, row, col):
"""Return start and stop points for adsorption and desorption."""
rowc = 1
# Check for adsorption branch
if sheet.cell(row + rowc, col).value == 'ADS':
ads_start_row = row + rowc + 1
ads_final_row = ads_start_row
point = sheet.cell(ads_final_r... | 38f0f0d9706c7ed7d3171e1b1c02161af618a4e0 | 3,616,115 |
from typing import Tuple
from typing import List
def _read_dvxrel2_flag(data: bytes, n0: int,
i0: int, i1: int,
size: int,
ints: np.ndarray) -> Tuple[List[int], List[str]]:
"""reads the DVxREL2 flag table"""
flag = ints[i0+10]
#print(int... | 2e8e6f58d01a3bfda7030186b392850fa3cb6c83 | 3,616,116 |
def patient_list(request):
"""Accepts a request to return a list of all patients from the backing data
store. Used for synching the mobile client.
Warning: This can return a significant amount of patient data.
Request parameters:
username
a valid username
password
... | b76ee242902f91e4f31c0a940196b5bf5ed298ca | 3,616,118 |
def create_dict_playlists_playlistids(p_list, pid_list):
""" Create a dictionary of playlists and playlist ids """
playlists_and_playlist_ids = {}
for i in range(len(p_list)):
playlists_and_playlist_ids[p_list[i]] = pid_list[i]
return playlists_and_playlist_ids | 173850ed85b3dc774ddea14674e22e701991c807 | 3,616,119 |
from datetime import datetime
def create_bot(market, strategy, resolution, start, end, verbose, percent, automatic, btc):
"""Will create a new bot instance."""
bot = Cointrader(market=market, strategy=strategy, resolution=resolution, start=start, end=end, automatic=automatic,
percent=perc... | 82efbc617094ab07b5d9f151e1c63dec12b1a404 | 3,616,120 |
def money_manager(manager):
"""
Patches a model manager's get_queryset method so that each QuerySet it returns
is able to work on money fields.
This allow users of django-money to use other managers while still doing
money queries.
"""
# Need to dynamically subclass to add our behaviour, an... | e73b4d2a513f836c333a673e499f9cf3daacc8ce | 3,616,122 |
def get_address():# check_author=True):
"""Get a address and user by id.
Checks that the id exists and optionally that the current user is
the author.
:param id: id of address to get
:return: the address
:raise 404: if a address with the given id doesn't exist
"""
success = True
uid... | 44851e91940f4f190be4764bfcf84b713278e06b | 3,616,123 |
def round(sdf: np.float, radius: np.float) -> np.float:
"""
Rounds a shape
:param sdf: pre-calculated SDF
:param radius: radius
:return: SDF
"""
return sdf - radius | b440d3a9dbe5f78988605efb024af5c9e311150b | 3,616,124 |
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