content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def parseAreas(area):
"""Parse the strings into address. This function is highly customized and demonstrates the general steps for transforming raw covid cases data to a list of address searchable in Google Map.
Arguments:
area: raw data downloaded from a news app
Return:
l: a list of human-readabl... | f205fca1d0b76aa63839a7c00552a790110998e4 | 17,500 |
def is_valid_instruction(instr: int, cpu: Cpu = Cpu.M68000) -> bool:
"""Check if an instruction is valid for the specified CPU type"""
return bool(lib.m68k_is_valid_instruction(instr, cpu.value)) | ae528e503e24698507971334d33dc6abf0f4c39c | 17,501 |
import textwrap
import sys
def wrap_text(translations, linewrap=0):
"""Pretty print translations.
If linewrap is set to 0 disble line wrapping.
Parameters
----------
translations : list
List of word translations.
linewrap : int
Maximum line length before wrapping.
"""
... | adecfba77f017d4888fffda43c0466e9125b43ea | 17,502 |
def docker_available():
"""Check if Docker can be run."""
returncode = run.run(["docker", "images"], return_code=True)
return returncode == 0 | 43ce2c7f5cb16657b4607faa5eac61b20e539e53 | 17,503 |
from datetime import datetime
def is_bc(symbol):
"""
判断是否背驰
:param symbol:
:return:
"""
bars = get_kline(symbol, freq="30min", end_date=datetime.now(), count=1000)
c = CZSC(bars, get_signals=get_selector_signals)
factor_ = Factor(
name="背驰选股",
signals_any=[
... | 07dc2f01374f95544898375b8bc02b6128d70090 | 17,504 |
import time
import calendar
def IEEE2030_5Time(dt_obj, local=False):
""" Return a proper IEEE2030_5 TimeType object for the dt_obj passed in.
From IEEE 2030.5 spec:
TimeType Object (Int64)
Time is a signed 64 bit value representing the number of seconds
since 0... | fbb9466e927f1162226760efbe609bf3e779e163 | 17,505 |
def learning_rate_schedule(params, global_step):
"""Handles learning rate scaling, linear warmup, and learning rate decay.
Args:
params: A dictionary that defines hyperparameters of model.
global_step: A tensor representing current global step.
Returns:
A tensor representing current learning rate.
... | b88d67dd0d241d26bf183e90e3d3c215e0abd957 | 17,506 |
import logging
import os
import subprocess
def run(
command,
cwd=None,
capture_output=False,
input=None,
check=True,
**subprocess_run_kwargs
):
""" Wrapper for subprocess.run() that sets some sane defaults """
logging.info("Running {} in {}".format(" ".join(command), cwd or os.getcwd()... | 5595721fc28da8a87230a1d367cbc5c3bacdc779 | 17,507 |
def profile(step):
"""
Profiles a Pipeline step and save the results as HTML file in the project output
directory.
Usage:
@profile
def step(self):
pass
"""
@wraps(step)
def wrapper(*arg, **kwargs):
pipeline_instance = arg[0]
project = pipeline_in... | f300000a0471a2439ae951a2d33b8a03aa61b333 | 17,508 |
from modin.pandas.series import Series
def make_dataframe_wrapper(DataFrame):
"""
Prepares a "delivering wrapper" proxy class for DataFrame.
It makes DF.loc, DF.groupby() and other methods listed below deliver their
arguments to remote end by value.
"""
conn = get_connection()
class Obt... | a2d523f6e9cb9d23ae722195a091d8e2b68139cc | 17,509 |
def download_cmems_ts(lats, lons, t0, tf, variables, fn=None):
"""Subset CMEMS output using OpenDAP
:params:
lats = [south, north] limits of bbox
lons = [west, east] limits of bbox
t0 = datetime for start of time series
tf = datetime for end of time series
variables = li... | b97de3a7428d6e2b50ab36b28e47afe479c24042 | 17,510 |
def construct_gpu_info(statuses):
""" util for unit test case """
m = {}
for status in statuses:
m[status.minor] = status
m[status.uuid] = status
return m | b8b2f41799b863d2e22066005b901f17a610d858 | 17,511 |
def load_data_time_machine(batch_size, num_steps, use_random_iter=False,
max_tokens=10000):
"""Return the iterator and the vocabulary of the time machine dataset."""
data_iter = SeqDataLoader(batch_size, num_steps, use_random_iter,
max_tokens)
return ... | ed9d6b63c34cf9d1a750daabbdb81e03e467e939 | 17,512 |
def scan_paths(paths, only_detect, recursive, module_filter):
"""
Scans paths for known bots and dumps information from them
@rtype : dict
@param paths: list of paths to check for files
@param only_detect: only detect known bots, don't process configuration information
@param recursive: recursi... | f58216f1ed5955828738689fa67522a8cc0e497a | 17,513 |
def generate_masks(input_size, output_size=1, observed=None):
"""
Generates some basic input and output masks.
If C{input_size} is an integer, the number of columns of the mask will be
that integer. If C{input_size} is a list or tuple, a mask with multiple channels
is created, which can be used with RGB images, f... | dee12176f72a158e9f39036981fa1dbd6be81817 | 17,514 |
import yaml
import logging
import sys
def parse_config_file(config):
"""
Load config file (primarily for endpoints)
"""
fail = False
with open(config, 'r') as fp:
content = yaml.load(fp.read())
if 'endpoints' not in content.keys():
return
for title, items in content['endpoi... | 2a9d4a47d5c5b8eea9fda0b33284a1c91bfc19b6 | 17,515 |
def average(time_array,height_array,data_array,height_bin_size=100,time_bin_size=3600):
"""
average: function that averages the radar signal by height and time
Args:
time_array: numpy 1d array with timestamps
height_array: numpy 1d array with height range
data_array: numpy 2d arra... | 710f4c8821cffe110511bda0dd3d4fd3052f33a9 | 17,516 |
def daily_report(api, space_name, charts, num_days=1, end_time=None):
"""Get a report of SLO Compliance for the previous day(s)
Returns: list of dicts of threshold breaches. Example Dict format:
{u'measure_time': 1478462400, u'value': 115.58158333333334}
:param api: An instance of sloc_report.LibratoA... | 86d25f5f2dd93a827f5f7b8cd44287f549921438 | 17,517 |
def new_pitch():
"""
route to new pitch form
:return:
"""
form = PitchForm()
if form.validate_on_submit():
title = form.title.data
pitch = form.pitch.data
category = form.category.data
fresh_pitch = Pitch(title=title, pitch_actual=pitch, category=category, user_... | a7724149a7e6b9d545559fef643dcc8fd2f5c731 | 17,518 |
def get_entity_bios(seq,id2label):
"""Gets entities from sequence.
note: BIOS
Args:
seq (list): sequence of labels.
Returns:
list: list of (chunk_type, chunk_start, chunk_end).
Example:
# >>> seq = ['B-PER', 'I-PER', 'O', 'S-LOC']
# >>> get_entity_bios(seq)
[[... | 25219d29ba8ecb2d44ca5a8245059432f3220d8d | 17,519 |
import torch
import copy
def early_stopping_train(model, X, Y_, x_test, y_test, param_niter=20001, param_delta=0.1):
"""Arguments:
- X: model inputs [NxD], type: torch.Tensor
- Y_: ground truth [Nx1], type: torch.Tensor
- param_niter: number of training iterations
- param_delta: learning rate
... | 83a8acdd24a4fde3db77184c3b4a99a1c1783349 | 17,520 |
def my_vtk_grid_props(vtk_reader):
"""
Get grid properties from vtk_reader instance.
Parameters
----------
vtk_reader: vtk Reader instance
vtk Reader containing information about a vtk-file.
Returns
----------
step_x : float
For regular grid, stepsize in x-direction.
... | 26ef8a51648ea487372ae06b54c8ccf953aeb414 | 17,521 |
def make_env(stack=True, scale_rew=True):
"""
Create an environment with some standard wrappers.
"""
env = grc.RemoteEnv('tmp/sock')
env = SonicDiscretizer(env)
if scale_rew:
env = RewardScaler(env)
env = WarpFrame(env)
if stack:
env = FrameStack(env, 4)
return env | 347376103fa00d4d43714f30097b0d129ef45f43 | 17,522 |
def plot_distr_cumsum(result, measure="degree", scale=['log', 'log'], figures=[], prefix="", show_std=True, show_figs=True, mode="safe", colors=('r', 'b')):
""" plots the cummulative distribution functions
special care has to be taken because averaging these is not trivial in comparison to e.g. degree
"""
... | 6b0a526cf8f09dd66ac7b0988c9445d57416be21 | 17,523 |
import socket
import sys
def recvall(sock, n, silent=False):
"""Helper function for recv_msg()."""
data = b''
while len(data) < n:
try:
packet = sock.recv(n - len(data))
if not packet:
return None
data += packet
except (socket.error, OSEr... | 0e5800929dfd2829fb922bbc0904a1ed893e79bf | 17,524 |
import sys
import os
def install_jenkins(dest_folder=".", fLOG=print, install=True, version=None):
"""
install `Jenkins <http://jenkins-ci.org/>`_ (only on Windows)
@param dest_folder where to download the setup
@param fLOG logging function
@param install ... | 7c67cc69f2fe3add7a97abbd8bb19451ee36fddd | 17,525 |
def state_space_model(A, z_t_minus_1, B, u_t_minus_1):
"""
Calculates the state at time t given the state at time t-1 and
the control inputs applied at time t-1
"""
state_estimate_t = (A @ z_t_minus_1) + (B @ u_t_minus_1)
return state_estimate_t | 0e04207028df8d4162c88aad6606e792ef618f5a | 17,526 |
def get_post(id , check_author=True):
"""Get a post and its author by id.
Checks that the id exists and optionally that the current user is
the author.
:param id: id of post to get
:param check_author: require the current user to be the author
:return: the post with author information
:rai... | a15ac3816d134f1dd89bf690c2f800e412d7219b | 17,527 |
def get_pixel(x, y):
"""Get the RGB value of a single pixel.
:param x: Horizontal position from 0 to 7
:param y: Veritcal position from 0 to 7
"""
global _pixel_map
return _pixel_map[y][x] | 47a77090683a5b8e7178b3c7d83ae5b1a090342f | 17,528 |
from typing import Callable
import re
def check_for_NAs(func: Callable) -> Callable:
"""
This decorator function checks whether the input string qualifies as an
NA. If it does it will return True immediately. Otherwise it will run
the function it decorates.
"""
def inner(string: str, *args, *... | e9336cca2e6cd69f81f6aef1d11dc259492774f8 | 17,529 |
from typing import Union
from typing import Callable
def integrateEP_w0_ode( w_init: np.ndarray, w0: Union[ Callable, np.ndarray ], w0prime: Union[ Callable, np.ndarray ],
B: np.ndarray, s: np.ndarray, s0: float = 0, ds: float = None,
R_init: np.ndarray = np.eye( 3 ), B... | 75a042b94ac46b7ecbb86e23abacde0d4034b9fe | 17,530 |
def change_coordinate_frame(keypoints, window, scope=None):
"""Changes coordinate frame of the keypoints to be relative to window's frame.
Given a window of the form [y_min, x_min, y_max, x_max], changes keypoint
coordinates from keypoints of shape [num_instances, num_keypoints, 2]
to be relative to this windo... | 2aa69a55d7f8177784afb41f50cd7ccfbffdbde3 | 17,531 |
import os
def eval_log_type(env_var_name):
"""get the log type from environment variable"""
ls_log = os.environ.get(env_var_name, '').lower().strip()
return ls_log if ls_log in LOG_LEVELS else False | 7d2711075b830fc5861961ed52714b58fd01b96b | 17,532 |
import random
def _get_name(filename: str) -> str:
"""
Function returns a random name (first or last)
from the filename given as the argument.
Internal function. Not to be imported.
"""
LINE_WIDTH: int = 20 + 1 # 1 for \n
with open(filename) as names:
try:
total_n... | 1b4cd75488c6bd1814340aee5669d1631318e77f | 17,533 |
def map_to_udm_section_associations(enrollments_df: DataFrame) -> DataFrame:
"""
Maps a DataFrame containing Canvas enrollments into the Ed-Fi LMS Unified Data
Model (UDM) format.
Parameters
----------
enrollments_df: DataFrame
Pandas DataFrame containing all Canvas enrollments
Ret... | 303223302e326854f7a19b2f3c9d0b626a2807bc | 17,534 |
def plot_electrodes(mris, grid, values=None, ref_label=None, functional=None):
"""
"""
surf = mris.get('pial', None)
if surf is None:
surf = mris.get('dura', None)
pos = grid['pos'].reshape(-1, 3)
norm = grid['norm'].reshape(-1, 3)
labels = grid['label'].reshape(-1)
right_or_le... | 0bcc5545c625675be080e6b70bf7a74d247ba1c9 | 17,535 |
from typing import Tuple
def _get_laplace_matrix(bcs: Boundaries) -> Tuple[np.ndarray, np.ndarray]:
"""get sparse matrix for laplace operator on a 1d Cartesian grid
Args:
bcs (:class:`~pde.grids.boundaries.axes.Boundaries`):
{ARG_BOUNDARIES_INSTANCE}
Returns:
tuple: A sparse ... | 80880c7fb1d54a7d4502e1096c2f2ade4d30ce21 | 17,536 |
import warnings
def column_or_1d(y, warn=False):
""" Ravel column or 1d numpy array, else raises an error
Parameters
----------
y : array-like
warn : boolean, default False
To control display of warnings.
Returns
-------
y : array
"""
shape = np.shape(y)
if len(s... | ef3a5bfe7a1ae07b925c1d9b897bce0eff29b275 | 17,537 |
def conv_tower(
inputs,
filters_init,
filters_end=None,
filters_mult=None,
divisible_by=1,
repeat=1,
**kwargs
):
"""Construct a reducing convolution block.
Args:
inputs: [batch_size, seq_length, features] input sequence
filters_init: Initial Conv1D filters
... | 82ff878423309e2963090a9569f14090a85d30e5 | 17,538 |
def edit_coach(request, coach_id):
""" Edit a coach's information """
if not request.user.is_superuser:
messages.error(request, 'Sorry, only the owners can do that.')
return redirect(reverse('home'))
coach = get_object_or_404(Coach, pk=coach_id)
if request.method == 'POST':
for... | ecaf07df3249d3349928b4e9da9c0524b27e603e | 17,539 |
import torch
def estimate_translation(S,
joints_2d,
focal_length=5000.,
img_size=224.,
use_all_joints=False,
rotation=None):
"""Find camera translation that brings 3D joints S closest to 2D... | 70b5cc75dc28919b6bb6cea70b49eae8ca593452 | 17,540 |
import random
def create_midterm_data(all_students):
"""
Create the midterm data set
Ten questions, two from each topic, a percentage of students did not
show up, use it as an example of merge
Rules:
- International students have a 10% drop out rate
- Performance changes by PROGRAM!
... | b1f946ebab616362113ada54a17cc3e857b33f98 | 17,541 |
def identify_outliers(x_vals, y_vals, obj_func, outlier_fraction=0.1):
"""Finds the indices of outliers in the provided data to prune for subsequent curve fitting
Args:
x_vals (np.array): the x values of the data being analyzed
y_vals (np.array): the y values of the data being analyzed
... | e1742747ac63b34c39d1e57cbc896b9df5af85e0 | 17,542 |
def GetTypeMapperFlag(messages):
"""Helper to get a choice flag from the commitment type enum."""
return arg_utils.ChoiceEnumMapper(
'--type',
messages.Commitment.TypeValueValuesEnum,
help_str=(
'Type of commitment. `memory-optimized` indicates that the '
'commitment is for mem... | f00e645a2dbfcae94a33fc5b016809f72e87c0a9 | 17,543 |
from typing import List
def gaussian_2Dclusters(n_clusters: int,
n_points: int,
means: List[float],
cov_matrices: List[float]):
"""
Creates a set of clustered data points, where the distribution within each
cluster is Gaussian.
P... | 9c950f9c5541c343a3a9a27dc3bff34be2006f8b | 17,544 |
def prepare_concepts_index(create=False):
"""
Creates the settings and mappings in Elasticsearch to support term search
"""
index_settings = {
"settings": {"analysis": {"analyzer": {"folding": {"tokenizer": "standard", "filter": ["lowercase", "asciifolding"]}}}},
"mappings": {
... | a33e7e6172c7a7c8577abab77cb467125e629e39 | 17,545 |
def pack_wrapper(module, att_feats, att_masks):
"""
for batch computation, pack sequences with different lenghth with explicit setting the batch size at each time step
"""
if att_masks is not None:
packed, inv_ix = sort_pack_padded_sequence(att_feats, att_masks.data.long().sum(1))
return... | ff5e02ac5977cf525a0e2f2a96714ff8a6cf1fe3 | 17,546 |
from sys import exc_info
def processor(preprocessed_data_id, param_id, param_constructor):
"""Dispatch the processor work"""
preprocessed_data = PreprocessedData(preprocessed_data_id)
params = param_constructor(param_id)
sp = StudyProcessor()
try:
process_out = sp(preprocessed_data, param... | 25c2771c1f627d8eb24b4e214e419ebab779352e | 17,547 |
def recommendation_inspiredby(film: str, limit: int=20) -> list:
"""Movie recommandations from the same inspiration with selected movie
Args:
film (str): URI of the selected movie
limit (int, optional): Maximum number of results to return. Defaults to 20.
Returns:
list: matching mo... | d70d6a30eabc5d1a5b5a7c3b0cebc28a9dcb0fa9 | 17,548 |
import string
def str2twixt(move):
""" Converts one move string to a twixt backend class move.
Handles both T1-style coordinates (e.g.: 'd5', 'f18'') as well as tsgf-
style coordinates (e.g.: 'fg', 'bi') as well as special strings
('swap' and 'resign'). It can handle letter in upper as well as lowerc... | fe1e644519f7d6fe7df2be8a38754ba230981a91 | 17,549 |
from datetime import datetime
import re
def celery_health_view(request):
"""Admin view that displays the celery configuration and health."""
if request.method == 'POST':
celery_health_task.delay(datetime.now())
messages.success(request, 'Health task created.')
return HttpResponseRedire... | 52f7fb76af5dc5557e22976b1930c19e6249f1cc | 17,550 |
def get_n_runs(slurm_array_file):
"""Reads the run.sh file to figure out how many conformers or rotors were meant to run
"""
with open(slurm_array_file, 'r') as f:
for line in f:
if 'SBATCH --array=' in line:
token = line.split('-')[-1]
n_runs = 1 + int(to... | 5574ef40ef87c9ec5d9bbf2abd7d80b62cead2ab | 17,551 |
def consume(pipeline, data, cleanup=None, **node_contexts):
"""Handles node contexts before/after calling pipeline.consume()
Note
----
It would have been better to subclass Pipeline and implement this logic
right before/after the core consume() call, but there is a bug in pickle
that prevents t... | b4d3df619600892fe02d418a19993af1f0715d84 | 17,552 |
def get_field_attribute(field):
"""
Format and return a whole attribute string
consists of attribute name in snake case and field type
"""
field_name = get_field_name(field.name.value)
field_type = get_field_type(field)
strawberry_type = get_strawberry_type(
field_name, field.descrip... | fbbe2dbdf6c5f0427365fbbb0d5f43df8bb74678 | 17,553 |
def shuffle_data(data):
"""
Shuffle the data
"""
rng_state = np.random.get_state()
for c, d in data.items():
np.random.set_state(rng_state)
np.random.shuffle(d)
data[c] = d
return data | 5a1fa1f81fbec54092c8d7b50ebf75f8edb526c7 | 17,554 |
def index(current_user=None):
""" Display home page """
return render_template('homepage.html', username=current_user['name'], \
logged_in=current_user['is_authenticated'], \
display_error=request.cookies.get('last_attempt_error') == 'True', \
login_banner=APP.config['LOGIN_BANNER']) | 287d8101ef318cb7ca308340e0d11ab157538450 | 17,555 |
import os
import pandas
def _read_data_file(data_path):
"""
Reads a data file into a :class:`pandas:pandas.DataFrame` object.
Parameters
----------
data_path : str
Path of the data file with extension. Supports ``.csv``, ``.xlsx``/``.xls``, ``.json``, and ``.xml``.
Returns
------... | 9ddfed58134a564ed63f712e305090ad6d9b6d41 | 17,556 |
def disable_admin_access(session, return_type=None, **kwargs):
"""
Disable Admin acccess
:type session: zadarapy.session.Session
:param session: A valid zadarapy.session.Session object. Required.
:type return_type: str
:param return_type: If this is set to the string 'json', this function
... | 5ac6c09ed3098f5b99baa2d5749d7b42a465e9f4 | 17,557 |
def _get_bbox_indices(x, y, bbox):
"""
Convert bbox values to array indices
:param x, y: arrays with the X, Y coordinates
:param bbox: minx, miny, maxx, maxy values
:return: bbox converted to array indices
"""
minx, miny, maxx, maxy = bbox
xindices, = np.where((x >= minx) & (x <= maxx))... | dd71f1852971dbd2d3026c1720f9f477b3093fc8 | 17,558 |
def skill_competencies():
"""
Called by S3OptionsFilter to provide the competency options for a
particular Skill Type
"""
table = s3db.hrm_skill
ttable = s3db.hrm_skill_type
rtable = s3db.hrm_competency_rating
query = (table.id == request.args[0]) & \
(table.skil... | 7edc87d20d36d25b05337365ed903126ef02742f | 17,559 |
def calc_field_changes(element, np_id):
"""
Walk up the tree of geo-locations, finding the new parents
These will be set onto all the museumobjects.
"""
fieldname = element._meta.concrete_model.museumobject_set.\
related.field.name
field_changes = {}
field_changes[fieldname] = e... | cba816488dcf10a774bc18b1b3f6498e1d8dc3d8 | 17,560 |
def index(request, _):
"""
路由请求
`` request `` 请求对象
"""
if request.method == 'GET' or request.method == 'get':
return index_page(request)
elif request.method == 'POST' or request.method == 'post':
return send_wxmsg(request)
else:
rsp = JsonResponse({'code': -1, 'erro... | 5006cf1e5cb23e49b17e9083fca66c7731f5559b | 17,561 |
def get_daisy_client():
"""Get Daisy client instance."""
endpoint = conf.get('discoverd', 'daisy_url')
return daisy_client.Client(version=1, endpoint=endpoint) | 6ed0df1259672becfca3197f2d115a1c789306a1 | 17,562 |
from pathlib import Path
import multiprocessing
def intermediate_statistics(
scores, ground_truth, audio_durations, *,
segment_length=1., time_decimals=6, num_jobs=1,
):
"""
Args:
scores (dict, str, pathlib.Path): dict of SED score DataFrames
(cf. sed_scores_eval.utils.sco... | 5039bec8ceafed7952833aa2f39c5d44d0909790 | 17,563 |
def vnorm(v1):
"""vnorm(ConstSpiceDouble [3] v1) -> SpiceDouble"""
return _cspyce0.vnorm(v1) | 00016eaa6a765f564ce247c4126c4a360aa2b60d | 17,564 |
def mean_iou(y_true, y_pred):
"""F2 loss"""
prec = []
for t in np.arange(0.5, 1.0, 0.05):
y_pred_ = tf.to_int32(y_pred > t)
score, up_opt = tf.metrics.mean_iou(y_true, y_pred_, 2)
K.get_session().run(tf.local_variables_initializer())
with tf.control_dependencies([up_opt]):
... | a2503703bae7c8c83b42ac93406178bc4c52a675 | 17,565 |
def _encode_string_parts(value, encodings):
"""Convert a unicode string into a byte string using the given
list of encodings.
This is invoked if `encode_string` failed to encode `value` with a single
encoding. We try instead to use different encodings for different parts
of the string, using the enc... | 58f514ed7cbd9a6e2c10e6d8b22f32a32d71d6a7 | 17,566 |
import re
import os
def get_files(path, pattern):
"""
Recursively find all files rooted in <path> that match the regexp <pattern>
"""
L = []
if not path.endswith('/'): path += '/'
# base case: path is just a file
if (re.match(pattern, os.path.basename(path)) != None) and os.path.isfile(path):... | 0e71a8290b6d011eeebd75fc1b07ba5fb945521a | 17,567 |
def SocketHandler(qt):
""" `SocketHandler` wraps a websocket connection.
HTTP GET /ws
"""
class _handler(websocket.WebSocketHandler):
def check_origin(self, origin):
return True
def open(self):
qt.log("new socket open ...")
qt.register_socket(self... | 001f9dbee77560d4d5970fce731084b5a9cca7af | 17,568 |
from typing import Optional
def var_swap(asset: Asset, tenor: str, forward_start_date: Optional[str] = None,
*, source: str = None, real_time: bool = False) -> Series:
"""
Strike such that the price of an uncapped variance swap on the underlying index is zero at inception. If
forward start da... | 0991ff1fb889b14b6a3d3e850caa2364a4f4d044 | 17,569 |
def extract_flow_global_roi(flow_x, flow_y, box):
"""
create global roi cropped flow image (for numpy image)
image:
numpy array image
box:
list of [xmin, ymin, xmax, ymax]
"""
flow_x_roi = extract_global_roi(flow_x, box)
flow_y_roi = extract_global_roi(flow_y, box)
if flo... | 1b6d22d413693e978dc31cfbf1708c93d9256cf1 | 17,570 |
from unittest.mock import patch
def patch_shell(response=None, error=False):
"""Mock the `AdbDeviceTcpFake.shell` and `DeviceFake.shell` methods."""
def shell_success(self, cmd):
"""Mock the `AdbDeviceTcpFake.shell` and `DeviceFake.shell` methods when they are successful."""
self.shell_cmd = ... | cdf4df2bb383c4c8b49b59442550e2c73ca828aa | 17,571 |
def __setAdjacent_square__(self, pos):
"""
Sets all adjacencies in the map for a map with square tiles.
"""
self.__checkIndices__(pos)
i, j = pos; adjacent = []
# Function to filter out nonexistent cells.
def filterfn(p):
do_not_filter = 0 <= p[0] < self.__numrows__ and 0 <= p[1] < s... | ebdd3ee3d0104b5bd26cc48e07760de027615263 | 17,572 |
def model_definition_nested_events():
"""Test model for state- and parameter-dependent heavisides.
ODEs
----
d/dt x_1:
inflow_1 - decay_1 * x1
d/dt x_2:
- decay_2 * x_2
Events:
-------
event_1:
trigger: x_1 > inflow_1 / decay_2
bolus: [[ 0],
... | f42a5c7c01fd6f966ecec11b28c9620022dd7aaf | 17,573 |
async def address_balance_history(
request: Request,
address: Address,
token_id: TokenID = Query(None, description="Optional token id"),
timestamps: bool = Query(
False, description="Include timestamps in addition to block heights"
),
flat: bool | None = Query(True, description="Return d... | 2fcae2ab775611e51fd056e98928afbcb6bf1278 | 17,574 |
def load(as_pandas=None):
"""
Loads the Grunfeld data and returns a Dataset class.
Parameters
----------
as_pandas : bool
Flag indicating whether to return pandas DataFrames and Series
or numpy recarrays and arrays. If True, returns pandas.
Returns
-------
Dataset
... | 183c37228619b835a36dc4a1cc1e1a7649fca6ec | 17,575 |
def rule_if_system(system_rule, non_system_rule, context):
"""Helper function to pick a rule based on system-ness of context.
This can be used (with functools.partial) to choose between two
rule names, based on whether or not the context has system
scope. Specifically if we will fail the parent of a ne... | 2149c2ffdd6afdd64f7d33a2de4c6a23b3143dee | 17,576 |
def find_inactive_ranges(note_sequence):
"""Returns ranges where no notes are active in the note_sequence."""
start_sequence = sorted(
note_sequence.notes, key=lambda note: note.start_time, reverse=True)
end_sequence = sorted(
note_sequence.notes, key=lambda note: note.end_time, reverse=True)
notes... | 8db86584908283385958c5f710fb36d95795f7b1 | 17,577 |
def is_connected(G):
"""Returns True if the graph is connected, False otherwise.
Parameters
----------
G : NetworkX Graph
An undirected graph.
Returns
-------
connected : bool
True if the graph is connected, false otherwise.
Raises
------
NetworkXNotImplemented:
... | 03a2602629db60565702bee044a1d70ba026a8aa | 17,578 |
import math
def show_result(img,
result,
skeleton=None,
kpt_score_thr=0.3,
bbox_color=None,
pose_kpt_color=None,
pose_limb_color=None,
radius=4,
thickness=1,
font_scale=0.5,
... | af90da2b30ff9891613654d70724162ce7b4d702 | 17,579 |
def D2(X, Y, Y2=None, YT=None):
""" Calculate the pointwise (squared) distance.
Arguments:
X: of shape (n_sample, n_feature).
Y: of shape (n_center, n_feature).
Y2: of shape (1, n_center).
YT: of shape (n_feature, n_center).
Returns:
pointwise distances (n_sample, n... | daa8940e939eb2806e043f9b4521bf8cd1aefd2e | 17,580 |
def read_table(path):
"""Lee un archivo tabular (CSV o XLSX) a una lista de diccionarios.
La extensión del archivo debe ser ".csv" o ".xlsx". En función de
ella se decidirá el método a usar para leerlo.
Si recibe una lista, comprueba que todos sus diccionarios tengan las
mismas claves y de ser así... | e2de4230f64cd45f3ff4caaa068c7df85c0c30df | 17,581 |
from typing import Dict
from typing import Any
from typing import cast
def spec_from_json_dict(
json_dict: Dict[str, Any]
) -> FieldSpec:
""" Turns a dictionary into the appropriate FieldSpec object.
:param dict json_dict: A dictionary with properties.
:raises InvalidSchemaError:
... | 9bf557364a7a17cea0c84c65ece5b1d0e3983b2f | 17,582 |
import scipy
def hyp_pfq(A, B, x, out=None, n=0):
"""
This function is decorated weirdly because its extra params are lists.
"""
out = np_hyp_pfq([a+n for a in A], [b+n for b in B], x, out)
with np.errstate(invalid='ignore'):
out *= np.prod([scipy.special.poch(a, n) for a in A])
ou... | f1d9e0454fa63d24b1a8a403bbae12e00b818bb2 | 17,583 |
from typing import Optional
from datetime import datetime
def create_new_token(
data: dict,
expires_delta: Optional[timedelta] = None,
page_only: bool = False):
"""Creates a token with the given permission and expiry"""
to_encode = data.copy()
if page_only:
expires = dateti... | 3a0a2aebc6b814850333a5d4f5db72b1396cf208 | 17,584 |
from pathlib import Path
from typing import Union
import re
def parse_json_year_date(year: Number, fullpath: Path) -> Union[Path, None]:
"""
Filtra os arquivos json por ano.
"""
if not isinstance(fullpath, Path):
raise TypeError("O parâmetro path deve do tipo Path.")
pattern_finder = re.se... | 1d482bf916c3574225fdc31e700fb570c47555b1 | 17,585 |
from malaya_speech.utils import describe_availability
def available_fastspeech2():
"""
List available FastSpeech2, Text to Mel models.
"""
return describe_availability(
_fastspeech2_availability,
text = '`husein` and `haqkiem` combined loss from training set',
) | b7fa7f6132eb478cf27068a4377688f8b3ec5c7b | 17,586 |
def solve(A, b, method='gauss', verbose=0, eps=1e-6, max_itration_times=100000, omega=1.9375):
"""
Solve equations in specified method.
:param A: coefficient matrix of the equations
:param b: vector
:param method: the way to solve equations
:param verbose: whether show the running information
... | 50c7cdc5a2c8b146a062c028c4cb684c0b7efc2f | 17,587 |
def returns_unknown():
"""Tuples are a not-supported type."""
return 1, 2, 3 | 9fc003c890b4e053362c684b1a5f0dfca59bbe42 | 17,588 |
def get_user(
cmd,
app_id: str,
token: str,
assignee: str,
api_version: str,
central_dns_suffix=CENTRAL_ENDPOINT,
) -> User:
"""
Get information for the specified user.
Args:
cmd: command passed into az
app_id: name of app (used for forming request URL)
token... | cc387259c97ebfecadd5d82dc6acf8f970d19478 | 17,589 |
import subprocess
def run_test(
bess_addr,
ptfdir,
trex_server_addr=None,
extra_args=(),
):
"""
Runs PTF tests included in provided directory.
"""
# create a dummy interface for PTF
if not create_dummy_interface() or not set_up_interfaces([DUMMY_IFACE_NAME]):
return False
... | c1a41561a0d6f37b8f5693dbaa8a1fc2799e0786 | 17,590 |
def get(fg, bg=None, attribute = 0):
"""
Return string with ANSI escape code for set text colors
fg: html code or color index for text color
attribute: use Attribute class variables
"""
if type(fg) is str:
bg = bg if bg else "#000000"
return by_hex(fg, bg, attribute=attribute)
... | 16ee7ea3bd5c66c415a6466632cee1c5b337696b | 17,591 |
def get_Qi(Q,i,const_ij,m):
"""
Aim:
----
Equalising two polynomials where one is obtained by a SOS
decomposition in the canonical basis and the other one is expressed
in the Laguerre basis.
Parameters
----------
Q : matrix for the SOS decomposition
i : integer
... | a54313c8763777840c4a018dedb2fe6363e09d55 | 17,592 |
import os
def run_openlego(analyze_mdao_definitions, cmdows_dir=None, initial_file_path=None,
data_folder=None, run_type='test', approx_totals=False, driver_debug_print=False):
# type: (Union[int, list, str], Optional[str], Optional[str], Optional[str], Optional[str], Optional[bool], Optional[boo... | b198f9dfbbf051a3b119a1c4fa8002f3c2e8183a | 17,593 |
def strToBool(s):
"""
Converts string s to a boolean
"""
assert type(s) == str or type(s) == unicode
b_dict = {'true': True, 'false': False, 'yes': True, 'no': False}
return b_dict[s.lower()] | 84e59429523e6e59a90739b0f1b160fa9e84bdc8 | 17,594 |
import json
def publish_to_sns(topic_name, message, region=None):
"""
Post a message to an SNS topic
"""
AWS = AWSCachedClient(region) # cached client object
partition = None
if region:
partition = partition_from_region(region)
else:
partition = 'aws'
region = 'us... | 5a3c35c0367873e2c0b3c79a176b7c384d2b74ed | 17,595 |
import os
def bandpass_voxels(realigned_file, bandpass_freqs, sample_period=None):
"""
Performs ideal bandpass filtering on each voxel time-series.
Parameters
----------
realigned_file : string
Path of a realigned nifti file.
bandpass_freqs : tuple
Tuple containing the ban... | 0792647b7faa1beaa517d99f448d554168401446 | 17,596 |
from typing import List
from typing import Tuple
def get_subset(
classes: List,
train_data,
train_labels,
val_data,
val_labels,
test_data,
test_labels,
) -> Tuple:
"""
creates a binary subset of training, validation, and testing set using the specified list of classes to select
... | 8857b7f5c4563692b3236b68889201bd3a28507e | 17,597 |
def to_xyzw(matrix):
"""Convenience/readibility function to bring spatial (trailing) axis to start.
Args:
matrix (...x4 array): Input matrix.
Returns:
4x... array
"""
return np.rollaxis(matrix, -1) | 7c74b9bd6dc271db4a5dd925bbcfec4eef7ca791 | 17,598 |
import numpy
def do_3d_pooling(feature_matrix, stride_length_px=2,
pooling_type_string=MAX_POOLING_TYPE_STRING):
"""Pools 3-D feature maps.
:param feature_matrix: Input feature maps (numpy array). Dimensions must be
M x N x H x C or 1 x M x N x H x C.
:param stride_length_px: S... | 180ceae7364dcd1dd55d23a00389d0c3bb43cc38 | 17,599 |
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