content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
def RunTransformix(command):
"""Run the transfomix transformation. You must be able to call transformix
from your command shell to use this. You must also have your transformation
parameter files set before running (see transformix parameter files).
Parameters
----------
command: string
Sent to the... | 01012ed8ff7d8fe807fc6dd6aa78e613868093ac | 3,613,000 |
import time
def timer(fcn):
"""Returns the runtime in ms of the function fcn"""
def wrapper(*args, **kwargs):
t0 = time.time_ns()
res = fcn(*args, **kwargs)
t = time.time_ns() - t0
print(f"{fcn.__name__}: {round(t * 10**-6, 1)} 'ms'")
return res
return wrapper | 9a76c7222f9f427abdde9194535acdf9880a2807 | 3,613,001 |
def read_landmarks(f_landmarks):
"""
Reads file containing landmarks for image list. Specifically,
<image name> x1 y1 ... xK yK is expected format.
:param f_landmarks: text file with image list and corresponding landmarks
:return: landmarks as type dictionary.
"""
landmarks_lut = {}
... | 9c4bf6b405f4fb49ace8badb4b3151cc457bbf84 | 3,613,002 |
def parse_char(ch):
"""
'A' or '\x41' or '0x41' or '41'
'\x00' or '0x00' or '00'
"""
if ch is None:
return None
if len(ch) == 1:
return ord(ch)
if ch[0:2] in ("0x", "\\x"):
ch = ch[2:]
if not ch:
raise ValueError("Empty char")
if len(ch) > 2:
r... | b3726d00839caf92b64d976ed447f8c1824efb9f | 3,613,003 |
def validate_parameters(self, parameters, task_id=None):
"""Validate parameters generated by the parameter parsing task
All validation should be done here - are there data restrictions?
Combinations that aren't allowed? etc.
Returns:
parameter dict with all keyword args required to load data.
... | 98e8e67d192dcc791c6585f76410bc516d88c4ae | 3,613,004 |
def Get_Entry():
"""
get the entry number of customers at every minute
"""
df['timestamp'] = df.index.time
time_spent = df.groupby(['weekday','customer_no'], as_index=False).agg({'timestamp':'min'})
time_spent.head()
entry = time_spent.groupby('timestamp').count() //5
entry['timestamp'] ... | e1760346b8b1852cfa0cb1a312d028d0a991b013 | 3,613,005 |
import copy
def load_detections_into_dataset(
dataset_name,
dataset_dicts,
det_file,
top_k_per_obj=1,
score_thr=0.0,
train_objs=None,
top_k_per_im=None,
):
"""Load test detections into the dataset.
Args:
dataset_name (str):
dataset_dicts (list[dict]): annotations i... | baae94a1a5c36f916a7319dcb1c9342cbca03cd9 | 3,613,006 |
def revert_version(request, revision_id):
"""Roll back the object saved in a Version to the previous Version"""
referer = request.META.get("HTTP_REFERER", "/")
revision_obj = Revision.objects.get(pk=revision_id)
revision_obj.revert() # revert all associated objects too
msg = "Rolled back revision %... | 70e7d541b2c700a88f0b718999acd4ca847b53a8 | 3,613,007 |
from typing import Optional
from typing import Tuple
def get_or_create_permission(
session: Session, name: str, description: Optional[str] = None
) -> Tuple[Optional[Permission], bool]:
"""Get a permission or create it if it doesn't already exist.
Returns:
(permission, is_new) tuple
"""
p... | 4a837f3ca9f5942368d75572b83de4f05e6d2c70 | 3,613,008 |
from typing import Any
def get_user_me(
db: Session = Depends(deps.get_db),
current_user: models.User = Depends(
deps.get_current_active_user
),
) -> Any:
"""
Get current user.
"""
if current_user is None:
raise exceptions.get_user_exception()
role = (
None
... | af61dc80820aaf2ce46b636b537413680976a6b0 | 3,613,009 |
import os
import time
def get_temp_dir(request):
"""
Action: If temporary directory does not exist, it is created. Then the temporary directory is returned
Returns: Temporary Directory
"""
if request.session.get('tmp_dir', None) is None:
tmp = os.path.join(gettempdir(), '{}'.format(hash(... | b4429066b9ffcdd60ed7b2a8398de086a16d18b8 | 3,613,010 |
import json
def trigger_oauth_expires_test(limit):
""" Test data for IFTTT trigger bunq_oauth_expires """
result = [{
"created_at": "2018-01-05T11:25:15+00:00",
"expires_at": "2018-01-05T11:25:15+00:00",
"meta": {
"id": "1",
"timestamp": "1515151515"
}
... | 6f0bf5ed1f2749bf67d9068ac9eb85cc6fd86e17 | 3,613,011 |
def translate_subset_type(subset_type):
"""Maps subset shortcut to full name.
Args:
subset_type (str): Subset shortcut.
Returns:
str: Subset full name.
"""
if subset_type == 'max':
model = 'best'
elif subset_type == 'random':
model = 'random'
elif subset_typ... | ff40e230c403818b55897ff96bee131d0c687096 | 3,613,012 |
def mid2aud(n_mid):
"""Return an audio segment from a mid file and build a wav meanwhile"""
m2a.FluidSynth().midi_to_audio(mid_dir + n_mid + '.mid',
wav_dir + n_mid + '.wav')
seg = AudioSegment.from_file(wav_dir + n_mid + '.wav')
return seg | f3573736541125dbb75439c038371e796a05ea02 | 3,613,013 |
import json
def lambda_handler(event, context):
"""
expected event:
{
"body-json" : {},
"params" : {
"path" : {},
"querystring" : {
"game" : "string"
},
"header" : {}
},
"stage-variables" : {
}
"""
if type(event) is not dict:
... | 2e20e4bd02bba3de2b3dc416bad58243357120a4 | 3,613,014 |
def open_file_on_worker(view):
"""Open the file on the worker process"""
service = cli.get_service()
if not service:
return None
service.open_on_worker(view.file_name(), view.substr(sublime.Region(0, view.size()))) | 4260a77791932ed95b1851411c06b06ccc7ccccf | 3,613,015 |
def solar_offset(geom: Geometry, precision: str = "h") -> timedelta:
"""
Given a geometry compute offset to add to UTC timestamp to get solar day right.
This only work when geometry is "local enough".
:param precision: one of ``'h'`` or ``'s'``, defaults to hour precision
"""
lon = mid_longitud... | afab5f060516584866a9c0d1c954ecadf4aa850b | 3,613,016 |
def bgr_to_y(image):
"""Convert a bgr image to grayscale.
:param image: an image denoted by a numpy array, which is HWC, and channels are in gbr
:type image: np.array
:return: the grayscale image
:rtype: np.array (with dtype np.float32), in range 0~255
"""
image = image.astype(np.float32) /... | d556f3e02a434be9283615e9ac833e9368d65df5 | 3,613,017 |
import email
def _create_email(
to_field="to_user@test1.com",
from_field="from_user@test2.com",
subject="This is a test email",
body="Almost empty text message",
attachment=None,
maintype=None,
subtype=None,
):
"""
Builds and returns an ``email.message.EmailMessage`` instance
w... | 7a918c4b49b7f68707e88a329bdde52eced01b46 | 3,613,018 |
def by_user_recipe_id(user_id, recipe_id):
""" Get Recipe owned by a user """
session = query_session.get_session()
return session.query(Recipe).filter(Recipe.id == recipe_id) \
.filter(Recipe.user_id == user_id) \
.first() | 26c6425982d62cd92f50a43f8690e81aef40b324 | 3,613,019 |
def Z_score(data):
"""
Z_score标准化
:param data:
:return:
"""
x, y, z = data.shape
def z_score(data):
return (data - np.mean(data)) / np.maximum(np.std(data), 1 / 256)
for i in range(z):
data[:, :, i] = z_score(data[:, :, i])
return data | 97c16a46209cee792e6fbfa6688b70d6b06e495f | 3,613,020 |
def torch_vad(sig, winLen=400, winSht=160, ener_thres=5.7,
mean_scale=0.5, prop_thres=0.12, frm_context=2,
twice_log_max_signed_int16=20.794354380710768,
eps=1.19209e-07):
""" Equivalent to KALDI's energy-based VAD implementation
(https://github.com/kaldi-asr/kaldi/... | 85b935c6842f82f411c7d1a0c967d8753cb38b29 | 3,613,021 |
async def create_sync_payload(dc, key):
"""Converts dictionary to JSON, encrypts it with provided public key (PEM)
and returns it as a Base64-encoded string.
"""
return await _run_async(_create_sync_payload, dc, key) | dec64b2a8f2bb81a6cc82a4c419adbf0f21bca3e | 3,613,022 |
import argparse
def arg_setup():
"""Sets up an argument parser and returns the arguments."""
parser = argparse.ArgumentParser(
description="run simulations of agents with wishful thinking")
parser.add_argument('scenario',
help="""the scenario to use (currently: sequenc... | 4a28bb0fa8925350d928b610b9b6bb62798aaf74 | 3,613,023 |
def graph_to_xarray(graph):
"""
Convert a hetnetpy.hetnet.Graph to an xarray.Dataset
"""
data_vars = dict()
for metaedge in graph.metagraph.get_edges(exclude_inverts=True):
data_array = metaedge_to_data_array(graph, metaedge)
name = metaedge.get_abbrev()
data_vars[name] = dat... | 3540f30651bb5b98dc18eb793574c7c5259d603c | 3,613,024 |
def get_shared_segments(poly1, poly2, bool_ret=False):
"""Returns the line segments in common to both polygons.
Parameters
----------
poly1 : libpysal.cg.Polygon
A Polygon.
poly2 : libpysal.cg.Polygon
A Polygon.
bool_ret : bool
Return only a ``bool``. Default is ``False`... | 7e3305b7d5c9bbade0a86d32c060c2f54bd05992 | 3,613,025 |
def get_latest_resources_asset(name):
"""
Searches through hazm's releases and find latest release that contains
resources.
Parameters
----------
name: str
The resource name
Returns
-------
asset: GitReleaseAsset
The resources asset
"""
g = Github()
repo... | ef9b3f450441cf2b6527b9ad6241cae59d3e472b | 3,613,026 |
def conv1x1_1bit(in_channels,
out_channels,
stride=1,
groups=1,
bias=False,
binarized=False):
"""
Convolution 1x1 layer with binarization.
Parameters:
----------
in_channels : int
Number of input channels.
... | a949c3b86f1331492e183528628a6ed2e13ff189 | 3,613,027 |
def get_vec_by_query(text):
"""提取文本向量
"""
token_ids, segment_ids = tokenizer.encode(text, max_length=maxlen)
# print("token_ids={},segment_ids={}".format(token_ids, segment_ids))
vec = encoder.predict([[token_ids], [segment_ids]])[0]
# print('vec size={}, element={}'.format(len(vec), vec[-1]))
... | 0f6f531344a79e169482975ebf35ac43304bcfad | 3,613,028 |
def serving_input_receiver_fn():
"""An input function for TensorFlow Serving."""
def _preprocess_image(image_bytes):
"""Preprocess a single raw image."""
image = tf.image.decode_jpeg(image_bytes, channels=IMG_CHANNEL)
image.set_shape((None, None, IMG_CHANNEL))
image = tf.image.r... | 47c6cc3056455a68be484fac114889943d04debe | 3,613,029 |
def _process_optimization_results(results, results_arguments):
"""Expand the solutions back to the original problems.
Args:
results (list):
list of dictionaries with the harmonized results objects.
results_arguments (list):
each element is a dictionary supplying the star... | 64a74f22d5391c88fb0fdccc3c7d610c4e67f928 | 3,613,030 |
def is_valid_continuous_partition_object(partition_object):
"""Tests whether a given object is a valid continuous partition object.
:param partition_object: The partition_object to evaluate
:return: Boolean
"""
if (partition_object is None) or ("weights" not in partition_object) or ("bins" not in pa... | b1576c909a9e09db35362aff1e00ef69cf33be02 | 3,613,031 |
def get(
hostname,
refresh_key,
authorization_host,
org_id,
sddc_id,
tier1,
nat,
verify_ssl=True,
cert=None,
cursor=None,
page_size=None,
sort_by=None,
sort_ascending=None,
):
"""
Retrieves nat rules for Given SDDC
CLI Example:
.. code-block:: bash
... | 2fac63ca341a3f6589444daeddad79ba99c832aa | 3,613,032 |
from typing import Optional
from typing import Callable
def add_fiber_array(
component: Component,
grating_coupler: Component = grating_coupler_te,
gc_port_name: str = "W0",
component_name: Optional[str] = None,
taper_factory: Callable = taper,
taper_length: float = 10.0,
get_route_factory... | de2a99ca12f28debc321a855b8adb894ba457672 | 3,613,033 |
def run(prefix, items, timestamp, delta, output_path=None, creation_dir=None, parent_dir_name="logs", silent=False, interactive=False):
""" collects log items and creates an archive with all collected items.
items is a list of instances of 'Item' subclasses (see the collectables submodule).
timestamp and de... | 01368171994e097d7034bc9b31bd0c433d46d5e8 | 3,613,034 |
def get_instruments(instruments, level):
"""Returns a list of themis instruments for L2 data"""
if level == 'l1':
instr_list = ['bau', 'eff', 'efp', 'efw', 'esa', 'fbk', 'fff_16',
'fff_32', 'fff_64', 'ffp_16', 'ffp_32', 'ffp_64',
'ffw_16', 'ffw_32', 'ffw_64', ... | b797856b35f72eb34fa2d23a2e8d5ff7ade77516 | 3,613,035 |
def add_release(
target_name,
target_resource_group,
remote_url=None,
remote_branch=None,
remote_access_token=None,
vsts_account_name=None,
vsts_project_name=None,
registry_resource_id=None,
registry_name=None):
"""
Creates a build definiti... | 9365757705cd2244b754d9a3d31e71652e3e0d07 | 3,613,036 |
def connect():
"""initialize a connection to a mysql db on a local host server """
try:
return mysql.connect(
host="127.0.0.1",
port="3306",
user="root",
password=ROOT_PASSWORD
, auth_plugin='mysql_native_password',
database="sales"... | e44a386670720922488a6ee2556ac13966e90d82 | 3,613,037 |
def scatter(x, y, z, color=default_color, size=default_size,
size_selected=default_size_selected,
color_selected=default_color_selected, marker="diamond",
selection=None, grow_limits=True, **kwargs):
"""Plots many markers/symbols in 3d
:param x: {x}
:param y: {y}
:pa... | 872d90ff1dfffbe80db8eb53af1469f96297675f | 3,613,038 |
def create_openapi_spec(app: falcon.API) -> APISpec:
"""Creates an OpenAPI Spec for the Sustainerds API"""
spec = APISpec(
title="Sustainerds API",
version="1.0.0",
openapi_version="3.0.0",
plugins=[MarshmallowPlugin()],
)
return spec | 1b5db71cc6266fd108a5138df559802ccae92dda | 3,613,039 |
def trigger_oauth_expires_delete(identity):
""" Delete a specific trigger identity for trigger bunq_oauth_expires """
# We don't store trigger identities, so this call can be ignored
return "" | 355084d71efc7789335b7f0ca15e90165a2b5e26 | 3,613,040 |
def bibTex_abs_format_export_post():
"""
:return:
"""
results, status = export_post(request, 'BibTex Abs')
if status == 200:
maxauthor, keyformat, authorcutoff, journalformat = export_post_extras(request, 'BibTex Abs')
return return_bibTex_format_export(solr_data=results, include_ab... | 8d6a37504c8c5a51af2db18ce210e15f1d245b83 | 3,613,041 |
def ligands_rmsd_calculator(pdb_target, pdb_reference, resname="GRW"):
"""
:param pdb_target: problem pdb file
:param pdb_reference: reference pdb file
:param write2report: if True export results in a file
:param write2pdb: pdb file with the result of the superposition between "pdb_target" and "pdb... | 9cd18c0d6413fc18a6d558cdea4f98af3259acdf | 3,613,042 |
def knn_points_idx(p1, p2, K, sorted=False, version=-1):
"""
K-Nearest neighbors on point clouds.
Args:
p1: Tensor of shape (N, P1, D) giving a batch of point clouds, each
containing P1 points of dimension D.
p2: Tensor of shape (N, P2, D) giving a batch of point clouds, each
... | 8243f48bbe2c8c0c54f88d9fe04e6d541584e7be | 3,613,043 |
def modularity_individual(individual, graph: igraph.Graph):
"""
Decode an individual into a community membership vector and
calculates the modularity of the individual community set.
"""
members = decode(individual)
try:
return graph.modularity(members)
except igraph.InternalError as... | 9f9b8a341ad7012ac77d89316d01d74f8fa2f75a | 3,613,044 |
def api_get_challenge_detail(challengeID: int):
"""
查询挑战详情
{
"name":"名称",
"id":ID,
"description":描述,
"level":等级,
"hasFinished":是否完成
"problemsetList":[
{
"name":"名称",
"hasFinished":"是否完成",
"id":"ID"
... | 149c746dfcb1b593cea078dfa594557b54e6633a | 3,613,045 |
def superop2chi(superop: np.ndarray) -> np.ndarray:
"""
Converts a superoperator into a list of Kraus operators.
Operators with small norm may be excluded.
:param superop: a dim**2 by dim**2 superoperator
:return: a dim**2 by dim**2 process matrix
"""
return kraus2chi(superop2kraus(superop... | ab7c60b927225ba002011d8b6f02d5d82208c7cb | 3,613,046 |
def is_instation(stmt):
"""Check whether the statement is an 'instance' or
'instance-list' definition
"""
return is_instance(stmt) or is_instance_list(stmt) | 172d592c7bf2beca1a46cfa4b86206a1824032e3 | 3,613,047 |
def check_multigene(overlaps, min_overlap_bp=0, min_query_overlap=0, min_gene_overlap=.5):
"""
overlaps is a list of: (gene, overlap_bp, overlap_gene_ratio, overlap_query_ratio)
"""
if all(x[1]>=min_overlap_bp and x[2]>=min_gene_overlap and x[3]>=min_query_overlap for x in overlaps):
new_name = ... | 5f7c3ba7231939e2e54ce236a79025952d5e9a84 | 3,613,048 |
def unpickle():
"""Unpickle the bot token"""
with open('token.pickle', 'rb') as file:
token = pik(file)
return token | 3246a7da2d7257fa35cc6de78deabc726a1155e8 | 3,613,049 |
def calcInertiaTensor(coords):
""""Calculate inertia tensor from coords"""
coords = getCoords(coords)
center = calcCenter(coords)
coords = coords - center
return dot(coords.transpose(), coords) | a16376078bb85c8e18f455df08d741b07171e287 | 3,613,050 |
from typing import Optional
from typing import Set
from typing import Callable
def auto_eq(only: Optional[Set[str]] = None, exclude: Optional[Callable[[str], bool]] = None):
"""
Decorator.
Auto-adds a __hash__ function by hashing its attributes.
:param only: Only include these attributes
:param exclude: Exclude ... | 0278531c2b572754581310629f4c805e06cd8ee2 | 3,613,051 |
import tempfile
def AddLoggingParent(android_manifest, logging_parent_value):
"""Add logging parent as an additional <meta-data> tag.
Args:
android_manifest: A string representing AndroidManifest.xml
logging_parent_value: A string representing the logging
parent value.
Raises:
RuntimeError: I... | 6cd03b7dae970ea58a8493f3047ec77748724776 | 3,613,052 |
def replace_nans_binmean(d, by, aggreagation="mean"):
""""Replace each NaN value in `d` by the mean in each bin when grouping by `by`."""
return d.where(~np.isnan(d), mean_per_bin(d, by, aggreagation=aggreagation)) | 4d24e58c04ee44d90a5e9820fa942cf244c28059 | 3,613,053 |
from typing import Sequence
def repeatAndVarySequence(seq, poss, channels, names, args, iters):
"""
Repeat a sequence and vary part(s) of it. Returns a new sequence.
Given N specifications of M steps, N parameters are varied in M
steps.
Args:
seq (Sequence): The sequence to be repeated.
... | 481f8f2765398362757f88fa10a42dd81066e252 | 3,613,054 |
def conv_bn(inp, oup, stride):
"""
:param inp:
:param oup:
:param stride:
:return:
"""
return nn.Sequential(
nn.Conv2d(inp, oup, 3, stride, 1, bias=False),
nn.BatchNorm2d(oup),
#nn.ReLU6(inplace=True),
nn.ReLU(inplace=True)
) | cbe7326aba5d2d7508deebfcd531a5c2d593ce3e | 3,613,055 |
from re import T
def normalize(x, axis=-1, mean=None, variance=None, epsilon=1e-5):
"""Normalizes an array by subtracting mean and dividing by sqrt(var)."""
if mean is None:
mean = T.mean(x, axis, keepdims=True)
if variance is None:
# this definition is traditionally seen as less accurate ... | 2804df3370d92d32c13a87aaf647cd2a951f9087 | 3,613,056 |
def _get_restart_standard_names(restart_properties: RestartProperties = None):
"""Return a list of variable names needed for a smooth restart. By default uses
restart_properties from RESTART_PROPERTIES."""
if restart_properties is None:
restart_properties = RESTART_PROPERTIES
return_dict = {}
... | 8e45f22c7305160e29799a9480a9a35a9da81c82 | 3,613,057 |
import json
async def portfolio_style_report(folio_id, request, *,factor_code=""):
"""
:param folio_id:
:param request:
:return:
{
'T': 290,
'rolling_reg': [[{
'month': 7,
'day': 25,
'year': 2017
}, {
'crisk': [0.2244239767675... | 658ef0dd99fcdf4cad6652d3404bf43dae86df41 | 3,613,058 |
def flatten(l, types=(list, )):
"""
Given a list/tuple that potentially contains nested lists/tuples of arbitrary nesting,
flatten into a single dimension. In other words, turn [(5, 6, [8, 3]), 2, [2, 1, (3, 4)]]
into [5, 6, 8, 3, 2, 2, 1, 3, 4]
This is safe to call on something not a list/tuple -... | 5bdffb984fcd2614e4e71f19353b3d277dea368e | 3,613,059 |
def bitwise_or(rasters, extent_type="FirstOf", cellsize_type="FirstOf", astype=None):
"""
The BitwiseOr operation
The arguments for this function are as follows:
:param rasters: array of rasters. If a scalar is needed for the operation, the scalar can be a double or string
:param extent_type: one ... | ecaf7522c8943259d9b4d43b446cf77762c8de83 | 3,613,060 |
import scipy
import math
def Theory_Algebraic(N,Kappa,d) :
"""
Theoretical approximation for the algebraic connectivity
of periodic RGGs
Parameters
-----------
N : int
Network size
Kappa : float
Expected mean degree of the ensemble
d: int
Dimension of the embedding space
Returns
---------
Mu... | 3229d3bc0990207d70464ef33cf37f51debcfd00 | 3,613,061 |
def define_passes(ext_val):
"""
Overwrite function based depending on enum flag.
:param ext_val:
:return:
"""
if ext_val in [EXTENSIONS.CGINC, EXTENSIONS.GLSLINC, EXTENSIONS.SHADER]:
return format_write_cginc_first
elif ext_val in [EXTENSIONS.CS]:
return format_write_cs_first... | 3a1eba7e9983e60fcce74e243ce20e58dcea4e8b | 3,613,062 |
def get_path_prefix(path):
"""
gets path_prefixe given path
"""
temp_path=list(filter(None, path.split("/")))
j=0
path_prefix=[]
for node in temp_path:
path_prefix.append([node])
return path_prefix | 728c019d842c3b5bf7c6f6b8cebf13a1ad90bd41 | 3,613,063 |
from typing import Any
def test_pull_request_exists(monkeypatch: MonkeyPatch, branch: str) -> None:
"""It matches the branch in the process output."""
def stub(*args: Any, **kwargs: Any) -> Any:
return pretend.stub(stdout="topic")
with monkeypatch.context() as m:
m.setattr("subprocess.ru... | 2dc808e1127a7ec2fe4ca7506528e5a4819ae06a | 3,613,064 |
def classify_image(interpreter, image, top_k=1):
""" return a sorted array of classification results """
set_input_tensor(interpreter, image)
interpreter.invoke()
output_details = interpreter.get_output_details()[0]
output = np.squeeze(interpreter.get_tensor(output_details['index']))
# if model... | 212968b55e48517fec376b247cd09439545e0e14 | 3,613,065 |
import math
def occupancy_to_color(occupancy):
"""
Return corresponding color from blue to red spectrum
"""
# color = [255*(1-isoval), 255*(1-isoval), 255] # white to blue
# color = [255*isoval, 0, 255*(1-isoval)] # blue to red
color = "gray" + str(int(math.floor((1-occupancy)*100))).zfill(2)
if(color == "g... | 838a6025c473b51dab6c38c28f70ba7bafed3071 | 3,613,066 |
from typing import List
from typing import Tuple
from typing import Dict
def _simplify_cnots_triplets(
cnots: List[Tuple[int, int]], flip_control_and_target: bool
) -> Tuple[bool, List[Tuple[int, int]]]:
"""Simplifies CNOT pairs according to equation 11 of [4].
CNOT(i, j) @ CNOT(j, k) == CNOT(j, k) @ CNO... | bd624a19336b636adcbc852cd912de6dd0290167 | 3,613,067 |
def reshape(a):
"""Combine the last two dimensions of a numpy array"""
all_head_size = a.shape[-2] * a.shape[-1]
new_shape = a.shape[:-2] + (all_head_size,)
return a.reshape(new_shape) | 7381657c14b8b9245af2d85c1d1b7a0f5d40fff8 | 3,613,068 |
from typing import OrderedDict
import os
import json
def load_in_autotrack(trackDirPath, SCALE_FACTOR=1.0, TRACK_FILE_EXT="json"):
"""Load an predicted track"""
trackDict = OrderedDict()
frameDict = OrderedDict()
#count = 0
for x in os.listdir(trackDirPath):
path = os.path.join(trackDir... | 95b37a105c7862fb24f76e5aba3a2fb5d36a9bd6 | 3,613,069 |
import torch
def encode_selection(selection: SelectionNode, db: Database) -> EncodedSelection:
"""
Encoding is a vector of:
-------------------------------------------------------------------------------
| *col | *rel | *hist | *freq | onehot dtype | op one hot | operand encoding |
... | 831aecc8737a304f5f3375c39ca3c1834cc90559 | 3,613,070 |
def dict_keys(this):
"""
Return PyIterable for Dict keys.
"""
return mkiterable(this.getvalue().keys()) | 1e4575f109019e5314d53075987fcd1cf85c426d | 3,613,071 |
def EMA2(df, n):
"""
线性加权移动平均 WMA
Args:
df (pandas.DataFrame): Dataframe格式的K线序列
n (int): 线性加权移动平均的周期
Returns:
pandas.DataFrame: 返回的DataFrame包含1列, 是"ema2", 代表计算出来的线性加权移动平均线
Example::
# 获取 CFFEX.IF1903 合约的线性加权移动平均线
from tqsdk import TqApi, TqSim
fro... | d658d9813a55e26f22fb1dcb0490c94edee1b7d4 | 3,613,072 |
import random
def pusher(obj_scale=None,
obj_mass=None,
obj_damping=None,
object_pos=(0.45, -0.05, -0.275),
distr_scale=None,
axisangle=(0, 0, 1, 1.5),
distr_mass=None,
distr_damping=None,
goal_pos=(0.45, -0.05, -0.3230),
... | 10db02142bfdbf95a9c548e6e98bb1ece0f393ca | 3,613,073 |
def create_from_pairs(pairs):
"""
Build graph from `pairs` of words.
Accumulate weight for the edges that appear multiple time
"""
DG = nx.DiGraph()
for (n1, n2, w) in pairs:
if DG.has_edge(n1, n2):
DG.edge[n1][n2]['weight'] = w
else:
DG.add_edge(n1, n2, {... | 8cd39dcbfabbddfc737e533afa3ec72c2d64095f | 3,613,074 |
import tqdm
def loop(env, mind, interpreter=None, n_episodes=1, max_steps=-1, policy='deterministic', name="",
debug_mode=False, render_mode=False, train_mode=True, verbose=2, callbacks=None, **kwargs):
"""Conduct series of plies.
Args:
env (Environment): Environment to take actions in.
... | 78e07066e58ab3c60cbb94af23a9f2a4a6692891 | 3,613,075 |
def get_panelist_by_id(panelist_id: int):
"""Retrieve a panelist based on their ID"""
return panelists.get_panelist_by_id(panelist_id, database_connection) | 88ea2e420390fdf4972c1a8010905d8a7f33ff50 | 3,613,076 |
from apps.jsonapp import JSONApp
def main_json(config, in_metadata, out_metadata):
"""
Alternative main function
-------------
This function launches the app using configuration written in
two json files: config.json and input_metadata.json.
"""
# 1. Instantiate and launch the App
pri... | 9306c9877f0558f04b31693c0f1bd63422716b93 | 3,613,077 |
def new_figure_manager(*args, **kwargs):
"""Create a new figure manager instance."""
_warn_if_gui_out_of_main_thread()
return _backend_mod.new_figure_manager(*args, **kwargs) | bbef99f717cf2cb18622279c4b968d098505e75d | 3,613,078 |
def given(distribution: Series, **givens) -> Series:
"""
Condition the distribution on given and/or not-given values of the
variables.
:param distribution: The probability distribution to condition
e.g. P(A,B,C,D).
:param givens: Names and values of variables to condition o... | 2925671206004d4a3fc3fd4a4b782ff894a71cff | 3,613,079 |
def cosine_similiarity(vec_left, vec_right):
"""
余弦相似度
:param vec_left:
:param vec_right:
:return:
"""
num = np.dot(vec_left, vec_right)
denom = np.linalg.norm(vec_left) * np.linalg.norm(vec_right)
cos = -1 if denom == 0 else num / denom
return cos | a3eb01f3739f1faf4d1dd84c4260a755224e19a9 | 3,613,080 |
def albedo_diffuse_bubbly_ice(wavelengths, a, f, ni="p2016"):
"""compute diffuse albedo of pure ice without taking into account for the surface reflectance and
using the assymptotic radiative transfer theory
:param a: bubble radius (m)
:param f: is bubble fractional volume w/r to total volume (m3/m3).... | 91bf8a741c8c731fdc9113baa0372bac59f2d28a | 3,613,081 |
import argparse
def parse_arguments():
"""
Parse file arguments
"""
parser = argparse.ArgumentParser(description="Predict class for a given input image")
parser.add_argument('image_url', help="url for a test image")
return parser.parse_args() | d3f970c14474daa659c78542e709feb0f1e64794 | 3,613,082 |
def reflectance(*reference):
"""Reference to a factbase resource describing reflectance.
Parameters
----------
*reference : :obj:`str`
Keys pointing to the metadata object describing the resource within the
reflectance category in the layout file of a factbase.
Returns
-------
:obj:`Cube... | 782e169afa080cbccaf83863869cda84a9fa27d6 | 3,613,083 |
import six
def get_validator_or_converter(name):
"""
Get a validator or converter by name
"""
if name == 'unicode':
return six.text_type
try:
v = get_validator(name)
return v
except UnknownValidator:
pass
raise SchemingException('validator/converter not foun... | 1635469ff793f98f01665af53c246c9b0af63801 | 3,613,084 |
def _d_sellmeier(b, c, lambda0):
"""
Calculate the first derivative (wrt wavelength) of the Sellmeier equation.
This is a private method.
Args:
b : array of three Sellmeier Coefficients [--]
c : array of three Sellmeier Coefficients [microns**2]
lambda0 : wavelength in vacuum... | 1c3431f8c6b5ae7cd95e5f7ca74ff09004f5a6d6 | 3,613,085 |
def is_running():
"""
Check JDB process state
"""
return jdb_process is not None and jdb_process.poll() is None | aeafa3ca9f925e91eedb9e327f3389134b5ac974 | 3,613,086 |
def get_non_us_city(location: str) -> str:
"""
Deals with two types of non-US locations:
"New Delhi (India)" and "Perth, Western Australia (Australia)"
:param location: geo location of the person
:return city
:raises LocatorException: could not infer the city name
"""
sep_idx = location.... | a7b69a8937141f7bff288d19bb92e41beb3a98c5 | 3,613,087 |
def row_to_top(df, index):
"""Bring row to top
Parameters
----------
df: pandas.dataframe
Dataframe to copy
index: int
Index of row to bring to top
Returns
-------
df_cp: pandas.dataframe
Copy of dataframe with specified row at top
"""
df_cp = pd.concat... | 519af78bb1a77debf69f23d4b6b6218d3c6087bb | 3,613,088 |
def init_cache(cname):
"""
Wipes and initializes a cache dir for container name `cname`.
"""
cache = abspath('.tmptest/test-kraken-integration/{cname}/cache'.format(cname=cname))
if os.path.exists(cache):
subprocess.check_call(['rm', '-rf', cache])
os.makedirs(cache)
os.chmod(cache, ... | 0f1b4a035b0a44e065a60ba9cce4699113f0dd9e | 3,613,089 |
def encodeMask(M):
"""
Encode binary mask M using run-length encoding.
:param M (bool 2D array) : binary mask to encode
:return: R (object RLE) : run-length encoding of binary mask
"""
[h, w] = M.shape
M = M.flatten(order='F')
N = len(M)
counts_list = []
pos = 0
# counts
counts_list.append(1)
diffs ... | bafe9ba42701d85fa3a572e86d0846a15fda067f | 3,613,090 |
def flatten_model_graph(ir_model: Model):
"""
Flatten the subgraph into root graph.
"""
def _flatten(graph: Graph):
"""
flatten this graph
"""
model = graph.model
node_to_remove = []
for node in graph.hidden_nodes:
node_graph = model.graphs.ge... | ebe7a0c1519914de3088b65481f3368457dbbe1b | 3,613,091 |
def get_cache():
"""returns the cache"""
return _cache | bb73c2f143bc2595085e63c028330b254f495464 | 3,613,092 |
def parse_message(message, nodata=False):
"""Parse df message from bytearray.
@message - message data
@nodata - do not load data
@return - [binary header, metadata, binary data]
"""
header = read_machine_header(message)
h_len = __get_machine_header_length(header)
meta_raw = message[h_l... | 9fbd2744e3c91e6db6ede20fd5bb50c84dbdc2e5 | 3,613,093 |
def reblock_array(df, nblocks, weights=None):
"""
Reblock df into nblocks new blocks
:param df: data to reblock
:type df: numpy array-like
:param nblocks: number of resulting blocks
:type nblocks: int
:param weights: weights used to average data
:type weights: array
:return: reblock... | 24adfe10ba1fbef5b7efb3d006a8e81be89d3f7a | 3,613,094 |
def B_measure(D, Cm, verbose=False):
"""
Computes the B measure for each network edge with infinite distance, thus not existing in the original Distance graph.
The formal definition is as follow:
.. math::
b_{ij} = <d_{ik}> / d_{ij}^m
b_{ji} = <d_{jk}> / d_{ij}^m
which is the average distance of all edges t... | 075ec0e4a3c50bd48cd8684317f63915c5eacc63 | 3,613,095 |
from typing import List
def get_medias() -> List[Media]:
"""
Retrieve the list of medias to be processed into folders
:return: the list of medias to process
"""
files = []
for folder in config['input']['folders']:
files += scan_folder(folder)
files.sort()
medias = []
for ... | c6a42cacc2c517e410a51ddccc99217beac70377 | 3,613,096 |
def count_paths_recursive(graph, node_val, target):
"""A more conventional recursive function (not a recursive generator)"""
if node_val >= target:
return 1
total = 0
for next_node in graph[node_val]:
total += count_paths_recursive(graph, next_node, target)
return total | be2aba80ed7dc734fb30f3b8b1a675d97e73c860 | 3,613,097 |
import re
def check_valency(mol):
"""
Checks that no atoms in the mol have exceeded their possible
valency
:return: True if no valency issues, False otherwise
"""
try:
Chem.SanitizeMol(mol, sanitizeOps=Chem.SanitizeFlags.SANITIZE_PROPERTIES)
return True, None
except ValueEr... | ebcbcb31b89aae27066f841495d2aa4930a74e04 | 3,613,098 |
import time
import yaml
def ensure_pod(ctx):
"""创建configmap"""
name = "kubectld-%s-u%s" % (ctx["source_cluster_id"], ctx["username_slug"])
name = name.lower()
k8s_client = K8SClient(ctx)
try:
pod = k8s_client.v1.read_namespaced_pod(name, namespace=constants.NAMESPACE)
if pod.stat... | a14dd0896e661d00ca088cdbf5a45e16ef47bd78 | 3,613,099 |
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