content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Any
def build_get301_request(**kwargs: Any) -> HttpRequest:
"""Return 301 status code and redirect to /http/success/200.
See https://aka.ms/azsdk/python/protocol/quickstart for how to incorporate this request builder
into your code flow.
:return: Returns an :class:`~azure.core.res... | 2ef01a4c126890fd30fd3bc656036b92d2ef0408 | 20,434 |
def error_function_latticeparameters(varying_parameters_values_array,
varying_parameters_keys,
Miller_indices,
allparameters,
absolutespotsindices,
... | e1c3242855354ed82d2dd164a7ae16aa76cd5e22 | 20,435 |
def run_forward_model(z_in):
"""
Run forward model and return approximate measured values
"""
x_dummy[:prm.nn]=z_in
x_dummy[prm.nn:]=prm.compute_velocity(z_in,t0)
x_meas = H_meas.dot(x_dummy)
return x_meas | fd6bfbbacba59e08b2bb8c4588793b969cab4b60 | 20,436 |
def optimize(name: str, circuit: cirq.Circuit) -> cirq.Circuit:
"""Applies sycamore circuit decompositions/optimizations.
Args:
name: the name of the circuit for printing messages
circuit: the circuit to optimize_for_sycamore
"""
print(f'optimizing: {name}', flush=True)
start = time... | 07027dc2ad21e33ca2038cb40c3cbb2b529941e7 | 20,437 |
def download_sbr(destination=None):
"""Download an example of SBR+ Array and return the def path.
Examples files are downloaded to a persistent cache to avoid
re-downloading the same file twice.
Parameters
----------
destination : str, optional
Path where files will be downloaded. Opti... | 0b928977806b546325569dbf71e93e8b760868fa | 20,438 |
from typing import Tuple
from typing import Union
def isvalid_sequence(
level: str, time_series: Tuple[Union[HSScoring, CollegeScoring]]
) -> bool:
"""Checks if entire sequence is valid.
Args:
level: 'high school' or 'college' level for sequence analysis.
time_series: Tuple of sorted ... | 5e32906408540c504347c745113fc303ef0d989b | 20,439 |
def non_linear_relationships():
"""Plot logarithmic and exponential data along with correlation coefficients."""
# make subplots
fig, axes = plt.subplots(1, 2, figsize=(12, 3))
# plot logarithmic
log_x = np.linspace(0.01, 10)
log_y = np.log(log_x)
axes[0].scatter(log_x, log_y)
axes[0].s... | 86ce934aebc6b6f8e6b5c1826d9d26c408efc8df | 20,441 |
import io
def label_samples(annotation, atlas, atlas_info=None, tolerance=2):
"""
Matches all microarray samples in `annotation` to parcels in `atlas`
Attempts to place each sample provided in `annotation` into a parcel in
`atlas`, where the latter is a 3D niimg-like object that contains parcels
... | 65a3f83b031871a14b250df48c9edef3cdcce7ac | 20,442 |
def group_by(x, group_by_fields='Event', return_group_indices=False):
"""
Splits x into LIST of arrays, each array with rows that have same
group_by_fields values.
Gotchas:
Assumes x is sorted by group_by_fields (works in either order, reversed
or not)
Does NOT put in empty lists... | 12e8034556ca303a9ebd2ccaab83cbcc131b0bec | 20,443 |
def unlock_file(fd):
"""unlock file. """
try:
fcntl.flock(fd, fcntl.LOCK_UN)
return (True, 0)
except IOError, ex_value:
return (False, ex_value[0]) | 2c6ce071072fa45607ce284b0881af5df44b5e6d | 20,444 |
def DsseTrad(nodes_num, measurements, Gmatrix, Bmatrix, Yabs_matrix, Yphase_matrix):
"""
Traditional state estimator
It performs state estimation using rectangular node voltage state variables
and it is customized to work without PMU measurements
@param nodes_num: number of nodes of the grid
@p... | 9e662255875970fc8df38c29e728637e53a30db5 | 20,445 |
def _get_specs(layout, surfs, array_name, cbar_range, nvals=256):
"""Get array specifications.
Parameters
----------
layout : ndarray, shape = (n_rows, n_cols)
Array of surface keys in `surfs`. Specifies how window is arranged.
surfs : dict[str, BSPolyData]
Dictionary of surfaces.
... | 310208c5bd8db46d37635fa8e2fcd8422a753a1b | 20,446 |
def upper_camel_to_lower_camel(upper_camel: str) -> str:
"""convert upper camel case to lower camel case
Example:
CamelCase -> camelCase
:param upper_camel:
:return:
"""
return upper_camel[0].lower() + upper_camel[1:] | e731bbee45f5fc3d8e3e218837ccd36c00eff734 | 20,448 |
def get(isamAppliance, cert_dbase_id, check_mode=False, force=False):
"""
Get details of a certificate database
"""
return isamAppliance.invoke_get("Retrieving all current certificate database names",
"/isam/ssl_certificates/{0}/details".format(cert_dbase_id)) | 34ade7c42fcc1b1409b315f8748105ee99157986 | 20,449 |
def model_check(func):
"""Checks if the model is referenced as a valid model. If the model is
valid, the API will be ready to find the correct endpoint for the given
model.
:param func: The function to decorate
:type func: function
"""
def wrapper(*args, **kwargs):
model = None
... | 809d7659a721ad6dedf4a651dd1fdab1b1dbf51e | 20,450 |
def content_loss_func(sess, model):
"""Content loss function defined in the paper."""
def _content_loss(p, x):
# N is the number of filters at layer 1
N = p.shape[3]
# M is the height * width of the feature map at layer 1
M = p.shape[1] * p.shape[2]
return (1 / (4 * N * ... | 229866eaaf6021e7a078460dc29a6f0bfaa853bd | 20,451 |
import joblib
def Extract_from_DF_kmeans(dfdir,num,mode=True):
"""
PlaneDFを読み込んで、client_IP毎に該当index番号の羅列をそれぞれのtxtに書き出す
modeがFalseのときはシーケンスが既にあっても上書き作成
"""
flag = exists("Database/KMeans/km_full_"+dfdir+"_database_name")#namelistが存在するかどうか
if(flag and mode):return
plane_df =... | cb086c07024716022343c7e8eb5755f2de3695db | 20,452 |
from typing import Optional
def get_workspace(workspace_id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetWorkspaceResult:
"""
Resource schema for AWS::IoTTwinMaker::Workspace
:param str workspace_id: The ID of the workspace.
"""
__args__ = d... | 5c0970884be38923ae156511faf619fda725d004 | 20,453 |
import socket
def find_open_port():
"""
Use socket's built in ability to find an open port.
"""
sock = socket.socket()
sock.bind(('', 0))
host, port = sock.getsockname()
return port | 516540fd23259d0fe247e02c4058c5ed7f3ee3a8 | 20,454 |
import itertools
def split_list_round_robin(data: tp.Iterable, chunks_num: int) -> tp.List[list]:
"""Divide iterable into `chunks_num` lists"""
result = [[] for _ in range(chunks_num)]
chunk_indexes = itertools.cycle(i for i in range(chunks_num))
for item in data:
i = next(chunk_indexes)
... | a87322b2c6a3601cda6c949354e55c38e215289a | 20,455 |
def calc_Q_loss_FH_d_t(Q_T_H_FH_d_t, r_up):
"""温水床暖房の放熱損失
Args:
Q_T_H_FH_d_t(ndarray): 温水暖房の処理暖房負荷 [MJ/h]
r_up(ndarray): 当該住戸の温水床暖房の上面放熱率 [-]
Returns:
ndarray: 温水床暖房の放熱損失
"""
return hwfloor.get_Q_loss_rad(Q_T_H_rad=Q_T_H_FH_d_t, r_up=r_up) | 04ad561fa0090de2eb64d5514a28729da92af63c | 20,456 |
import random
def t06_ManyGetPuts(C, pks, crypto, server):
"""Many clients upload many files and their contents are checked."""
clients = [C("c" + str(n)) for n in range(10)]
kvs = [{} for _ in range(10)]
for _ in range(200):
i = random.randint(0, 9)
uuid1 = "%08x" % random.randint(... | 384aa2b03169da613b25d2da60cdd1ec007aeed5 | 20,458 |
def multi_lightness_function_plot(functions=None, **kwargs):
"""
Plots given *Lightness* functions.
Parameters
----------
functions : array_like, optional
*Lightness* functions to plot.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition su... | 18a4706d919c5b8822ff76a40dcd657028a6179b | 20,459 |
def delete_notification(request):
"""
Creates a Notification model based on uer input.
"""
print request.POST
# Notification's PK
Notification.objects.get(pk=int(request.POST["pk"])).delete()
return JsonResponse({}) | c4750bfbaa8184e64293517689671dbf717e6cd4 | 20,460 |
from dateutil import tz
def parse_query_value(query_str):
""" Return value for the query string """
try:
query_str = str(query_str).strip('"\' ')
if query_str == 'now':
d = Delorean(timezone=tz)
elif query_str.startswith('y'):
d = Delorean(Delorean(timezone=tz).... | ac9c6845871094d043eee7004214fdcecb20daec | 20,461 |
def build_model():
"""
Build the model
:return: the model
"""
model = keras.Sequential([
layers.Dense(64, activation='relu', input_shape=[len(train_dataset.keys())]),
layers.Dense(64, activation='relu'),
layers.Dense(1)
])
optimizer = tf.keras.optimizers.RMSprop(0.00... | b5e4b0a64e7d39a0c7b72c0380ef98d8eaf9cc01 | 20,462 |
def detect(stream):
"""Returns True if given stream is a readable excel file."""
try:
opendocument.load(BytesIO(stream))
return True
except:
pass | a9ef5361d9f6f5ae40767f40f12b89c3d53177a4 | 20,463 |
def new_default_channel():
"""Create new gRPC channel from settings."""
channel_url = urlparse(format_url(settings.SERVICE_BIND))
return Channel(host=channel_url.hostname, port=channel_url.port) | 4771306570213fa03cc5df08a0e8c9b216ecfd44 | 20,464 |
def iou(bbox1, bbox2):
"""
Calculates the intersection-over-union of two bounding boxes.
Args:
bbox1 (numpy.array, list of floats): bounding box in format x1,y1,x2,y2.
bbox2 (numpy.array, list of floats): bounding box in format x1,y1,x2,y2.
Returns:
int: intersection-over-onion o... | 7609bcc6eb39757240a22c28fc7c15f4024cd789 | 20,465 |
def get_version():
"""
Obtain the version of the ITU-R P.1511 recommendation currently being used.
Returns
-------
version: int
Version currently being used.
"""
return __model.__version__ | 4d36eacabebe74bfb18879ba64f190ceb1bbc22a | 20,466 |
import copy
def sample_filepaths(filepaths_in, filepaths_out, intensity):
"""
`filepaths_in` is a list of filepaths for in-set examples.
`filepaths_out` is a list of lists, where `filepaths_out[i]` is a list of
filepaths corresponding to the ith out-of-set class.
`intensity` is the number of i... | b20c1e1a019eaebc0eb7ea46b33c286b72da7af7 | 20,467 |
def makekey(s):
"""
enerates a bitcoin private key from a secret s
"""
return CBitcoinSecret.from_secret_bytes(sha256(s).digest()) | 51658c6426a78ae2e20752542bc579f5bb7ebc01 | 20,468 |
def shape_broadcast(shape1: tuple, shape2: tuple) -> tuple:
"""
Broadcast two shapes to create a new union shape.
Args:
shape1 (tuple) : first shape
shape2 (tuple) : second shape
Returns:
tuple : broadcasted shape
Raises:
IndexingError : if cannot broadcast
"""... | 4737332b371e0f16df3860d5c53e46718f68f30e | 20,469 |
import xxhash
def hash_array(kmer):
"""Return a hash of a numpy array."""
return xxhash.xxh32_intdigest(kmer.tobytes()) | 9761316333fdd9f28e74c4f1975adfca1909f54a | 20,470 |
def GenerateDiskTemplate(
lu, template_name, instance_uuid, primary_node_uuid, secondary_node_uuids,
disk_info, file_storage_dir, file_driver, base_index,
feedback_fn, full_disk_params):
"""Generate the entire disk layout for a given template type.
"""
vgname = lu.cfg.GetVGName()
disk_count = len(disk_in... | 87995b08d3579fc22a8db7c8408a9c29e47a8271 | 20,471 |
def check_pc_overlap(pc1, pc2, min_point_num):
"""
Check if the bounding boxes of the 2 given point clouds overlap
"""
b1 = get_pc_bbox(pc1)
b2 = get_pc_bbox(pc2)
b1_c = Polygon(b1)
b2_c = Polygon(b2)
inter_area = b1_c.intersection(b2_c).area
union_area = b1_c.area + b2_c.area - int... | 8caa07a42850d9ca2a4d298e9be91a44ac15f6a5 | 20,472 |
def apply_hypercube(cube: DataCube, context: dict) -> DataCube:
"""Reduce the time dimension for each tile and compute min, mean, max and sum for each pixel
over time.
Each raster tile in the udf data object will be reduced by time. Minimum, maximum, mean and sum are
computed for each pixel over time.
... | c2c3b7b90a48a37f5e172111ef13e8529a3a80c5 | 20,473 |
def dateIsBefore(year1, month1, day1, year2, month2, day2):
"""Returns True if year1-month1-day1 is before year2-month2-day2. Otherwise, returns False."""
if year1 < year2:
return True
if year1 == year2:
if month1 < month2:
return True
if month1 == month2:
if ... | 3ba19b6e57c8e51a86e590561331057a44885d10 | 20,474 |
def all_stat(x, stat_func=np.mean, upper_only=False, stat_offset=3):
"""
Generate a matrix that contains the value returned by stat_func for
all possible sub-windows of x[stat_offset:].
stat_func is any function that takes a sequence and returns a scalar.
if upper_only is False, values are added t... | 16ef240b33a477948ae99862bb21540a230a8a2f | 20,475 |
def PyCallable_Check(space, w_obj):
"""Determine if the object o is callable. Return 1 if the object is callable
and 0 otherwise. This function always succeeds."""
return int(space.is_true(space.callable(w_obj))) | e5b8ee9bbbdb0fe53d6fc7241d19f93f7ee8259a | 20,476 |
from typing import Callable
def _multiclass_metric_evaluator(metric_func: Callable[..., float], n_classes: int, y_test: np.ndarray,
y_pred: np.ndarray, **kwargs) -> float:
"""Calculate the average metric for multiclass classifiers."""
metric = 0
for label in range(n_class... | a8a61c7a2e3629ff69a6a2aefdb4565e903b82de | 20,477 |
def idxs_of_duplicates(lst):
""" Returns the indices of duplicate values.
"""
idxs_of = dict({})
dup_idxs = []
for idx, value in enumerate(lst):
idxs_of.setdefault(value, []).append(idx)
for idxs in idxs_of.values():
if len(idxs) > 1:
dup_idxs.extend(idxs)
return ... | adc8a0b0223ac78f0c8a6edd3d60acfaf7ca4c04 | 20,479 |
async def store_rekey(
handle: StoreHandle,
wrap_method: str = None,
pass_key: str = None,
) -> StoreHandle:
"""Replace the wrap key on a Store."""
return await do_call_async(
"askar_store_rekey",
handle,
encode_str(wrap_method and wrap_method.lower()),
encode_str(pas... | e7abb35147bd7b5be5aa37b6583571e5be8f144b | 20,480 |
import requests
def prepare_bitbucket_data(data, profile_data, team_name):
"""
Prepare bitbucket data by extracting information needed
if the data contains next page for this team/organisation continue to fetch the next
page until the last page
"""
next_page = False
link = None
profil... | a2fe54a4fd02e80b4bf4d41ff932e27b555afc5c | 20,481 |
def add(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.add <numpy.add>`.
See its docstring for more information.
"""
if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in add")
# C... | 7c35ea06f5bff91da283e3521185a6b9f1b55b32 | 20,482 |
def aslist(l):
"""Convenience function to wrap single items and lists, and return lists unchanged."""
if isinstance(l, list):
return l
else:
return [l] | 99ccef940229d806d27cb8e429da9c85c44fed07 | 20,483 |
def getKeyList(rootFile,pathSplit):
"""
Get the list of keys of the directory (rootFile,pathSplit),
if (rootFile,pathSplit) is not a directory then get the key in a list
"""
if isDirectory(rootFile,pathSplit):
changeDirectory(rootFile,pathSplit)
return ROOT.gDirectory.GetListOfKeys()... | 69d51a496ec77e00753518fee7ae8a0e5b9e7c9a | 20,485 |
from typing import Any
def query_from_json(query_json: Any,
client: cl.Client = None):
"""
The function converts a dictionary or json string of Query to a Query object.
:param query_json: A dictionary or json string that contains the keys of a Query.
:type query_json:... | 58d1b1f3efedf0b74a0136d1edd1da13bf16bf8c | 20,487 |
def fetch_validation_annotations():
""" Returns the validation annotations
Returns:
complete_annotations: array of annotation data - [n_annotations, 4]
row format is [T, X, Y, Z]
"""
ann_gen = _annotation_generator()
data = []
for annotation in ann_gen:
if annotation[0] in... | 1b9a8b86bbc005c79b152e1f59e653b7711e674f | 20,489 |
def enough_data(train_data, test_data, verbose=False):
"""Check if train and test sets have any elements."""
if train_data.empty:
if verbose:
print('Empty training data\n')
return False
if test_data.empty:
if verbose:
print('Empty testing data\n')
retu... | f11014d83379a5df84a67ee3b8f1e85b23c058f7 | 20,490 |
def calculate_tidal_offset(TIDE, GM, R, refell):
"""
Calculates the spherical harmonic offset for a tide system to change
from a tide free state where there is no permanent direct and
indirect tidal potentials
Arguments
---------
TIDE: output tidal system
R: average radius used ... | 278b27b2a1378cf0ccb44055a37baf9def7d6c6a | 20,492 |
def get_questions(set_id, default_txt=None):
"""Method to get set of questions list."""
try:
cache_key = 'question_list_%s' % (set_id)
cache_list = cache.get(cache_key)
if cache_list:
v_list = cache_list
print('FROM Cache %s' % (cache_key))
else:
... | 0153ab71caa705f7a4f2a07ce5ef210b02618dd4 | 20,493 |
def get_mms_operation(workspace, operation_id):
"""
Retrieve the operation payload from MMS.
:return: The json encoded content of the reponse.
:rtype: dict
"""
response = make_mms_request(workspace, 'GET', '/operations/' + operation_id, None)
return response.json() | c88aca93803ab5075a217a10b7782ae791f168bc | 20,495 |
def _check_data_nan(data):
"""Ensure data compatibility for the series received by the smoother.
(Without checking for inf and nans).
Returns
-------
data : array
Checked input.
"""
data = np.asarray(data)
if np.prod(data.shape) == np.max(data.shape):
data = data.ravel... | 1cde49f2836405deb0c1328d5ce53c69ffbcb721 | 20,496 |
def function(row, args):
"""Execute a named function
function(arg, arg...)
@param row: the HXL data row
@param args: the arguments parsed (the first one is the function name)
@returns: the result of executing the function on the arguments
"""
f = FUNCTIONS.get(args[0])
if f:
retu... | 3b6e2e20c09c6cefebb4998d40376ff1b1aa63f2 | 20,497 |
def extract_rfc2822_addresses(text):
"""Returns a list of valid RFC2822 addresses
that can be found in ``source``, ignoring
malformed ones and non-ASCII ones.
"""
if not text: return []
candidates = address_pattern.findall(tools.ustr(text).encode('utf-8'))
return filter(try_coerce_asc... | b256bd585a30900e09a63f0cc29889044da8e0e0 | 20,499 |
def set_edge_font_size_mapping(table_column, table_column_values=None, sizes=None, mapping_type='c', default_size=None,
style_name=None, network=None, base_url=DEFAULT_BASE_URL):
"""Map table column values to sizes to set the edge size.
Args:
table_column (str): Name of C... | 7360f57d1e4921d58eaf5af4e57a6c5f636fefdb | 20,500 |
def compute_time_overlap(appointment1, appointment2):
"""
Compare two appointments on the same day
"""
assert appointment1.date_ == appointment2.date_
print("Checking for time overlap on \"{}\"...".
format(appointment1.date_))
print("Times to check: {}, {}".
format(appointmen... | c459ef52d78bc8dd094d5be9c9f4f035c4f9fcaa | 20,501 |
def set_up_prior(data, params):
"""
Function to create prior distribution from data
Parameters
----------
data: dict
catalog dictionary containing bin endpoints, log interim prior, and log
interim posteriors
params: dict
dictionary of parameter values for creation of pri... | eb75965b9425bbf9fe3a33b7f0c850e27e2d454a | 20,502 |
def is_nonincreasing(arr):
""" Returns true if the sequence is non-increasing. """
return all([x >= y for x, y in zip(arr, arr[1:])]) | 6d78ef5f68ca93767f3e204dfea2c2be8b3040af | 20,503 |
def restore_missing_features(nonmissing_X, missing_features):
"""Insert columns corresponding to missing features.
Parameters
----------
nonmissing_X : array-like, shape (n_samples, n_nonmissing)
Array containing data with missing features removed.
missing_features : array-like, shape (n_m... | 733fd72d36ea86269472949eaa12a306835578f9 | 20,504 |
def get_sample_type_from_recipe(recipe):
"""Retrieves sample type from recipe
Args:
recipe: Recipe of the project
Returns:
sample_type_mapping, dic: Sample type of the project
For Example:
{ TYPE: "RNA" } , { TYPE: "DNA" }, { TYPE: "WGS" }
"""
return find_mapping(recipe_type_mapping, recipe) | 57cef2f592d530ad15aed47cc51da4441430f3d2 | 20,505 |
import yaml
def _is_download_necessary(path, response):
"""Check whether a download is necessary.
There three criteria.
1. If the file is missing, download it.
2. The following two checks depend on each other.
1. Some files have an entry in the header which specifies when the file was
... | 69cd2778fb6d4706ff88bd35c1b5c1abda9a39ba | 20,506 |
import hashlib
def hash64(s):
"""Вычисляет хеш - 8 символов (64 бита)
"""
hex = hashlib.sha1(s.encode("utf-8")).hexdigest()
return "{:x}".format(int(hex, 16) % (10 ** 8)) | e35a367eac938fdb66584b52e1e8da59582fdb9a | 20,507 |
def course_runs():
"""Fixture for a set of CourseRuns in the database"""
return CourseRunFactory.create_batch(3) | 1ffd4efe008e44f9e2828c9128acfe3cdafb5160 | 20,508 |
import json
def _response(data=None, status_code=None):
"""Build a mocked response for use with the requests library."""
response = MagicMock()
if data:
response.json = MagicMock(return_value=json.loads(data))
if status_code:
response.status_code = status_code
response.raise_for_st... | 0ccd38a954d28a4f010becc68319b49896323de0 | 20,509 |
def findtailthreshold(v, figpath=None):
"""
function [f,mns,sds,gmfit] = findtailthreshold(v,wantfig)
<v> is a vector of values
<wantfig> (optional) is whether to plot a diagnostic figure. Default: 1.
Fit a Gaussian Mixture Model (with n=2)
to the data and find the point that is greater t... | 8ef0c3267582d604621bd98fa7c81976b76b2c51 | 20,510 |
from typing import Optional
from typing import Dict
import asyncio
async def make_request_and_envelope_response(
app: web.Application,
method: str,
url: URL,
headers: Optional[Dict[str, str]] = None,
data: Optional[bytes] = None,
) -> web.Response:
"""
Helper to forward a request to the ca... | 22d18de671cc84d3471120273a7b0599fda26210 | 20,511 |
def get_provincial_miif_sets(munis):
"""
collect set of indicator values for each province, MIIF category and year
returns dict of the form {
'cash_coverage': {
'FS': {
'B1': {
'2015': [{'result': ...}]
}
}
}
}
"""
prov_sets = defaultdi... | a4484a40a30f8fe9e702735f6eccf78c395ea446 | 20,513 |
def create_kernel(radius=2, invert=False):
"""Define a kernel"""
if invert:
value = 0
k = np.ones((2*radius+1, 2*radius+1))
else:
value = 1
k = np.zeros((2*radius+1, 2*radius+1))
y,x = np.ogrid[-radius:radius+1, -radius:radius+1]
mask = x**2 ... | 33bbfa6141eb722180ffa9111555e4e00fbdac6a | 20,514 |
def edimax_get_power(ip_addr="192.168.178.137"):
"""
Quelle http://sun-watch.net/index.php/eigenverbrauch/ipschalter/edimax-protokoll/
"""
req = """<?xml version="1.0" encoding="UTF8"?><SMARTPLUG id="edimax"><CMD id="get">
<NOW_POWER><Device.System.Power.NowCurrent>
</Device.System.Power.No... | 9de1720f00ca4194b66f79048314bac1cac950ed | 20,515 |
import torch
def get_class_inst_data_params_n_optimizer(nr_classes, nr_instances, device):
"""Returns class and instance level data parameters and their corresponding optimizers.
Args:
nr_classes (int): number of classes in dataset.
nr_instances (int): number of instances in dataset.
... | f97e12b99a42f32bb3629df5567ca44477d71dc0 | 20,516 |
def inc(x):
""" Add one to the current value """
return x + 1 | c8f9a68fee2e8c1a1d66502ae99e42d6034b6b5c | 20,517 |
def regionError(df, C, R):
"""Detects if a selected region is not part of one of the selected countries
Parameters:
-----------
df : Pandas DataFrame
the original dataset
C : str list
list of selected countries
R : str list
list of selected regions
Returns
---... | 53e237bba7c1696d23b5f1e3c77d4b2d2a4c9390 | 20,518 |
def lherzolite():
"""
Elastic constants of lherzolite rock (GPa) from
Peselnick et al. (1974), in Voigt notation
- Abbreviation: ``'LHZ'``
Returns:
(tuple): tuple containing:
* C (np.ndarray): Elastic stiffness matrix (shape ``(6, 6)``)
* rho (float): Density (3270 ... | 4d7e16fcfc1732ee3a881d4b1c2d755bbd9035f3 | 20,519 |
def int_to_bit(x_int, nbits, base=2):
"""Turn x_int representing numbers into a bitwise (lower-endian) tensor."""
x_l = tf.expand_dims(x_int, axis=-1)
x_labels = []
for i in range(nbits):
x_labels.append(
tf.floormod(
tf.floordiv(tf.to_int32(x_l),
tf.to_int32(base... | a9529c737e058da664d31055aa85cc7e6179f585 | 20,520 |
def create_ldap_external_user_directory_config_content(server=None, roles=None, role_mappings=None, **kwargs):
"""Create LDAP external user directory configuration file content.
"""
entries = {
"user_directories": {
"ldap": {
}
}
}
entries["user_directories"]... | baaf3d7a02f2f4e18c3ccddb7f3ff4d5b379c1d4 | 20,521 |
def intersection(lst1, lst2):
"""!
\details Finds hashes that are common to both lists and stores their location in both documents
Finds similarity that is measured by
sim(A,B) = number of hashes in intersection of both hash sets divided by minimum of the number of hashes in lst1 and lst2
\param l... | 7288e523e743fda89596e56f217aac8c87899b50 | 20,522 |
def allrad2(F_nm, hull, N_sph=None, jobs_count=1):
"""Loudspeaker signals of All-Round Ambisonic Decoder 2.
Parameters
----------
F_nm : ((N_sph+1)**2, S) numpy.ndarray
Matrix of spherical harmonics coefficients of spherical function(S).
hull : LoudspeakerSetup
N_sph : int
Decod... | a34cfd7719c36dd8abf1313e3eca4aa2ce49477b | 20,523 |
def outfeed(token, xs):
"""Outfeeds value `xs` to the host. Experimental.
`token` is used to sequence infeed and outfeed effects.
"""
flat_xs, _ = pytree.flatten(xs)
return outfeed_p.bind(token, *flat_xs) | 1b4b8c289ebd5dbb90ddd7b565c98ea9ebaec038 | 20,525 |
def add_gaussian_noise(images: list, var: list, random_var: float=None, gauss_noise: list=None):
"""
Add gaussian noise to input images. If random_var and gauss_noise are given, use them to compute the final images.
Otherwise, compute random_var and gauss_noise.
:param images: list of images
:param ... | e453f1fda24ec428eb1e33aec87db9456fa015b2 | 20,526 |
def get_sso_backend():
"""
Return SingleSignOnBackend class instance.
"""
return get_backend_instance(cfg.CONF.auth.sso_backend) | 4c2a9b857006405f804826b1c096aa8d828d6e42 | 20,527 |
def conv_relu_pool_forward(x, w, b, conv_param, pool_param):
"""
Convenience layer that performs a convolution, a ReLU, and a pool.
Inputs:
- x: Input to the convolutional layer
- w, b, conv_param: Weights and parameters for the convolutional layer
- pool_param: Parameters for the pooling layer
Returns a tuple... | 20d5f3d4b30edd91ef54b53a7b09882b3e2ab9b8 | 20,528 |
def ConnectWithReader(readerName, mode):
""" ConnectWithReader """
hresult, hcontext = SCardEstablishContext(SCARD_SCOPE_USER)
if hresult != SCARD_S_SUCCESS:
raise EstablishContextException(hresult)
hresult, hcard, dwActiveProtocol = SCardConnect(hcontext, readerName,
mode, SCARD_PROTOC... | af7606fb9ad669185c7a655967d0193b59404fe1 | 20,529 |
def interpolate(points: type_alias.TensorLike,
weights: type_alias.TensorLike,
indices: type_alias.TensorLike,
normalize: bool = True,
allow_negative_weights: bool = False,
name: str = "weighted_interpolate") -> type_alias.TensorLike:
"""... | 13d49a570ac482a0b2b76ab0bb49bf7994df7204 | 20,530 |
def calcADPs(atom):
"""Calculate anisotropic displacement parameters (ADPs) from
anisotropic temperature factors (ATFs).
*atom* must have ATF values set for ADP calculation. ADPs are returned
as a tuple, i.e. (eigenvalues, eigenvectors)."""
linalg = importLA()
if not isinstance(atom, ... | 0a0a0db2ca99d4a3b754acb9cd22ec4659af948f | 20,531 |
def bitset(array, bits):
"""
To determine if the given bits are set in an array.
Input Parameters
----------------
array : array
A numpy array to search.
bits : list or array
A list or numpy array of bits to search.
Note that the "first" bit is denoted as zero,
w... | cbae61dabfbe0789ff349f12b0df43860db72df7 | 20,533 |
from typing import OrderedDict
def sample_gene_matrix(request, variant_annotation_version, samples, gene_list,
gene_count_type, highlight_gene_symbols=None):
""" highlight_gene_symbols - put these genes 1st """
# 19/07/18 - Plotly can't display a categorical color map. See: https://gith... | 70ed9387ebba73664efdf3c94fe08a67ed07acc9 | 20,535 |
import random
def normal218(startt,endt,money2,first,second,third,forth,fifth,sixth,seventh,zz1,zz2,bb1,bb2,bb3,aa1,aa2):
"""
for source and destination id generation
"""
"""
for type of banking work,label of fraud and type of fraud
"""
idvariz=random.choice(zz2)... | aec17f55306691395dc2797cf30e175e0cb5b9e8 | 20,537 |
from typing import List
def find_paths(root: TreeNode, required_sum: int) -> List[List[int]]:
"""
Time Complexity: O(N^2)
Space Complexity: O(N)
Parameters
----------
root : TreeNode
Input binary tree.
required_sum : int
Input number 'S'.
Returns
-------
all_p... | 71cd37db1be97015173748e8d2142601e306552b | 20,539 |
import time
import requests
import json
def macro_bank_switzerland_interest_rate():
"""
瑞士央行利率决议报告, 数据区间从20080313-至今
https://datacenter.jin10.com/reportType/dc_switzerland_interest_rate_decision
https://cdn.jin10.com/dc/reports/dc_switzerland_interest_rate_decision_all.js?v=1578582240
:return: 瑞士央... | 14eb2ce7dc85e0611a8d55147172256ed8a2c71e | 20,540 |
def create_dataframe(message):
"""Create Pandas DataFrame from CSV."""
dropdowns = []
df = pd.DataFrame()
if message != "":
df = pd.read_csv(message)
df = df.sample(n = 50, random_state = 2) # reducing Data Load Running on Heroku Free !!!!
if len(df) == 0:
return pd.D... | c0d764ed47cba31d0129d1c61e645065ba2e99b5 | 20,541 |
def load_model(path):
"""
This function ...
:param path:
:return:
"""
# Get the first line of the file
with open(path, 'r') as f: first_line = f.readline()
# Create the appropriate model
if "SersicModel" in first_line: return SersicModel.from_file(path)
elif "ExponentialDiskMo... | 425113abe09b1de1efa1d5cf1ca2df4d999886c2 | 20,542 |
import functools
def add_metaclass(metaclass):
"""
Class decorator for creating a class with a metaclass.
Borrowed from `six` module.
"""
@functools.wraps(metaclass)
def wrapper(cls):
orig_vars = cls.__dict__.copy()
slots = orig_vars.get('__slots__')
if slots is not Non... | f6ee3feef418d5bff4f0495fdbfc98c9a8f48665 | 20,543 |
import torch
def max_pool_nd_inverse(layer, relevance_in : torch.Tensor, indices : torch.Tensor = None,
max : bool = False) -> torch.Tensor :
"""
Inversion of LogSoftmax layer
Arguments
---------
relevance : torch.Tensor
Input relavance
indices : torch.Ten... | ae3ad1b2a3791063c90568f0c954d3de6f3985f8 | 20,544 |
def aroon_up(close, n=25, fillna=False):
"""Aroon Indicator (AI)
Identify when trends are likely to change direction (uptrend).
Aroon Up - ((N - Days Since N-day High) / N) x 100
https://www.investopedia.com/terms/a/aroon.asp
Args:
close(pandas.Series): dataset 'Close' column.
n(... | 2a44c15b06e9a1d2facaa800a186b780fc226717 | 20,545 |
def triangulate(points):
""" triangulate the plane for operation and visualization
"""
num_points = len(points)
indices = np.arange(num_points, dtype=np.int)
segments = np.vstack((indices, np.roll(indices, -1))).T
tri = pymesh.triangle()
tri.points = np.array(points)
tri.segments = seg... | d18a7d171715217b59056337c86bf5b49609b664 | 20,548 |
def immutable():
""" Get group 1. """
allowed_values = {'NumberOfPenguins', 'NumberOfSharks'}
return ImmutableDict(allowed_values) | 851853b54b106cbc3ee621119a863a7b2862e8d5 | 20,549 |
def test_plot_colors_sizes_proj(data, region):
"""
Plot the data using z as sizes and colors with a projection.
"""
fig = Figure()
fig.coast(region=region, projection="M15c", frame="af", water="skyblue")
fig.plot(
x=data[:, 0],
y=data[:, 1],
color=data[:, 2],
size... | 4a9f2727d046d91445504d8f147fcef95a261cb5 | 20,550 |
def predict_to_score(predicts, num_class):
"""
Checked: the last is for 0
===
Example: score=1.2, num_class=3 (for 0-2)
(0.8, 0.2, 0.0) * (1, 2, 0)
:param predicts:
:param num_class:
:return:
"""
scores = 0.
i = 0
while i < num_class:
scores += i * ... | ee4038583404f31bed42bed4eaf6d0c25684c0de | 20,551 |
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