content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import logging
def loadData(data_source, loc, run, indexes, ntry=0, __text__=None, __prog__=None):
"""
Loads the data from a remote source. Has hooks for progress bars.
"""
if __text__ is not None:
__text__.emit("Decoding File")
if data_source.getName() == "Local WRF-ARW":
url = d... | d06fd6fb6194dac63911a5b9c3ad267525098cd2 | 3,718 |
def comp_psip_skin(self, u):
"""psip_skin for skin effect computation
Parameters
----------
self : Conductor
An Conductor object
Returns
-------
None
"""
y = (1 / u) * (sinh(u) + sin(u)) / (cosh(u) + cos(u)) # p257 Pyrhonen
# y[u==0]=1
return y | 23fe18a13b56f38c49fd3ca14b557983064c65b3 | 3,719 |
import random
def homepage(var=random.randint(0, 1000)):
"""
The function returns the homepage html template.
"""
return render_template("index.html", var=var) | 17e9033b8abeaa990cd31008861e5c412e35d1d7 | 3,720 |
import numbers
def tier(value):
"""
A special function of ordinals which does not
correspond to any mathematically useful function.
Maps ordinals to small objects, effectively compressing the range.
Used to speed up comparisons when the operands are very different sizes.
In the current vers... | 851b36cf22c09d8f94168a0aa55292754451e351 | 3,721 |
from .models import Sequence
def get_next_value(
sequence_name="default",
initial_value=1,
reset_value=None,
*,
nowait=False,
using=None,
overrite=None,
):
"""
Return the next value for a given sequence.
"""
# Inner import because models cannot be imported before their app... | 0770c8d4a4bea732bacfe6b7eaa404546bb79699 | 3,722 |
def expected_shd(posterior, ground_truth):
"""Compute the Expected Structural Hamming Distance.
This function computes the Expected SHD between a posterior approximation
given as a collection of samples from the posterior, and the ground-truth
graph used in the original data generation process.
Pa... | 5e0daf39a13fc0a4cb7a4f5d0a9fe692fdae82db | 3,723 |
import json
def package_list_read(pkgpath):
"""Read package list"""
try:
with open(PACKAGE_LIST_FILE, 'r') as pkglistfile:
return json.loads(pkglistfile.read())
except Exception:
return [] | afb97afd20823563ecfda3b5c908f7ad70322868 | 3,724 |
import pandas
import types
def hpat_pandas_series_le(self, other, level=None, fill_value=None, axis=0):
"""
Pandas Series method :meth:`pandas.Series.le` implementation.
.. only:: developer
Test: python -m hpat.runtests hpat.tests.test_series.TestSeries.test_series_op8
Parameters
--------... | f2969e17dd79b71a033e3c84ffd82e3bf2448554 | 3,725 |
def map_view(request):
"""
Place to show off the new map view
"""
# Define view options
view_options = MVView(
projection='EPSG:4326',
center=[-100, 40],
zoom=3.5,
maxZoom=18,
minZoom=2
)
# Define drawing options
drawing_options = MVDraw(
... | 5d037262b2c93c538b5a5b6fe076ee04a9d9b5ee | 3,727 |
def decompose_jamo(compound):
"""Return a tuple of jamo character constituents of a compound.
Note: Non-compound characters are echoed back.
WARNING: Archaic jamo compounds will raise NotImplementedError.
"""
if len(compound) != 1:
raise TypeError("decompose_jamo() expects a single characte... | 56eb503b47a966d7f88750f7fdc1bcc55ba1aa1b | 3,728 |
from typing import Optional
def cp_in_drive(
source_id: str,
dest_title: Optional[str] = None,
parent_dir_id: Optional[str] = None,
) -> DiyGDriveFile:
"""Copy a specified file in Google Drive and return the created file."""
drive = create_diy_gdrive()
if dest_title is None:
dest_title... | 981cfa18da78a160447778cab5f3326f35dbfc59 | 3,729 |
def label_tuning(
text_embeddings,
text_labels,
label_embeddings,
n_steps: int,
reg_coefficient: float,
learning_rate: float,
dropout: float,
) -> np.ndarray:
"""
With N as number of examples, K as number of classes, k as embedding dimension.
Args:
'text_embeddings': flo... | 83e4181c6600065bfb2cc98b4ca4957ea920ad7c | 3,730 |
def create_nan_filter(tensor):
"""Creates a layer which replace NaN's with zero's."""
return tf.where(tf.is_nan(tensor), tf.zeros_like(tensor), tensor) | 4e03c4c4c275430e5228e2d73b09e24f8c787e71 | 3,731 |
def requestor_is_superuser(requestor):
"""Return True if requestor is superuser."""
return getattr(requestor, "is_superuser", False) | 7b201601cf8a1911aff8271ff71b6d4d51f68f1a | 3,732 |
from typing import Dict
def process(business: Business, # pylint: disable=too-many-branches
filing: Dict,
filing_rec: Filing,
filing_meta: FilingMeta): # pylint: disable=too-many-branches
"""Process the incoming historic conversion filing."""
# Extract the filing informat... | 78f5033251cb90023c2e0c0ad064b92af5212e65 | 3,733 |
def est_const_bsl(bsl,starttime=None,endtime=None,intercept=False,val_tw=None):
"""Performs a linear regression (assuming the intercept at the origin).
The corresponding formula is tt-S*1/v-c = 0 in which tt is the travel
time of the acoustic signal in seconds and 1/v is the reciprocal of the
harmonic ... | 906119dcc66f4ab536d4a89c9c9b633bb6835058 | 3,734 |
def SeasonUPdate(temp):
""" Update appliance characteristics given the change in season
Parameters
----------
temp (obj): appliance set object for an individual season
Returns
----------
app_expected_load (float): expected load power in Watts
app_expected_dur (float): expected ... | 7fdfa932bedf2ac17490df6aaeedb547e1774c4d | 3,735 |
def pad_and_reshape(instr_spec, frame_length, F):
"""
:param instr_spec:
:param frame_length:
:param F:
:returns:
"""
spec_shape = tf.shape(instr_spec)
extension_row = tf.zeros((spec_shape[0], spec_shape[1], 1, spec_shape[-1]))
n_extra_row = (frame_length) // 2 + 1 - F
extension ... | 097bc2e8f58f1e947b8f69a6163d1c64d2197f9e | 3,736 |
def GetExclusiveStorageForNodes(cfg, node_uuids):
"""Return the exclusive storage flag for all the given nodes.
@type cfg: L{config.ConfigWriter}
@param cfg: cluster configuration
@type node_uuids: list or tuple
@param node_uuids: node UUIDs for which to read the flag
@rtype: dict
@return: mapping from n... | b93625bc2b865530bef0c648885f5615905e54c1 | 3,737 |
import csv
def get_read_data(file, dic, keys):
""" Assigns reads to labels"""
r = csv.reader(open(file))
lines = list(r)
vecs_forwards = []
labels_forwards = []
vecs_reverse = []
labels_reverse = []
for key in keys:
for i in dic[key]:
for j in lines:
... | 355c44cbf83ab9506755bda294723bfd1e8a15c1 | 3,738 |
def removeDuplicates(listToRemoveFrom: list[str]):
"""Given list, returns list without duplicates"""
listToReturn: list[str] = []
for item in listToRemoveFrom:
if item not in listToReturn:
listToReturn.append(item)
return listToReturn | 8265e7c560d552bd9e30c0a1140d6668abd1b4d6 | 3,739 |
def check_hms_angle(value):
"""
Validating function for angle sexagesimal representation in hours.
Used in the rich_validator
"""
if isinstance(value, list):
raise validate.ValidateError("expected value angle, found list")
match = hms_angle_re.match(value)
if not match:
raise... | bf1b6ec14cc131263913c331cb1d3cb9a06cdc76 | 3,740 |
def stats():
"""Retrives the count of each object type.
Returns:
JSON object with the number of objects by type."""
return jsonify({
"amenities": storage.count("Amenity"),
"cities": storage.count("City"),
"places": storage.count("Place"),
"reviews": storage.count("Re... | 31ebd630381fe33cdbff507a3d34497423dfd621 | 3,742 |
def addflux2pix(px,py,pixels,fmod):
"""Usage: pixels=addflux2pix(px,py,pixels,fmod)
Drizel Flux onto Pixels using a square PSF of pixel size unity
px,py are the pixel position (integers)
fmod is the flux calculated for (px,py) pixel
and it has the same length as px and py
pixels is the imag... | 808f99dac20cda962146fee8f2b9878a07804f9b | 3,743 |
def get_dea_landsat_vrt_dict(feat_list):
"""
this func is designed to take all releveant landsat bands
on the dea public database for each scene in stac query.
it results in a list of vrts for each band seperately and maps
them to a dict where band name is the key, list is the value pair.
"""
... | 79009cc9fbcd085c8e95cf15f4271419d598d1ce | 3,744 |
def is_zh_l_bracket(uni_ch):
"""判断一个 unicode 是否是中文左括号。"""
if uni_ch == u'\uff08':
return True
else:
return False | 3ba18418005824a51de380c898726d050d464ec2 | 3,746 |
def petlink32_to_dynamic_projection_mMR(filename,n_packets,n_radial_bins,n_angles,n_sinograms,time_bins,n_axial,n_azimuthal,angles_axial,angles_azimuthal,size_u,size_v,n_u,n_v,span,n_segments,segments_sizes,michelogram_segments,michelogram_planes, status_callback):
"""Make dynamic compressed projection from list-mo... | 9764da2a2fb0c021274133fdd46661a44cf0dc31 | 3,747 |
from typing import Dict
def is_core_recipe(component: Dict) -> bool:
"""
Returns True if a recipe component contains a "Core Recipe"
preparation.
"""
preparations = component.get('recipeItem', {}).get('preparations') or []
return any(prep.get('id') == PreparationEnum.CORE_RECIPE.value for prep... | 451798c6f31297a80ac43db00243fb2dd85ced46 | 3,748 |
def build_estimator(output_dir, first_layer_size, num_layers, dropout,
learning_rate, save_checkpoints_steps):
"""Builds and returns a DNN Estimator, defined by input parameters.
Args:
output_dir: string, directory to save Estimator.
first_layer_size: int, size of first hidden layer of ... | 339e26fd910aa7412b8e2b66845718e440ccada6 | 3,749 |
import json
def importConfig():
"""設定ファイルの読み込み
Returns:
tuple:
str: interface,
str: alexa_remote_control.sh path
list: device list
"""
with open("config.json", "r", encoding="utf-8") as f:
config = json.load(f)
interface = config["interface"]
... | 84f8fc0deec4aebfe48209b01d1a35f7373d31e6 | 3,750 |
from typing import List
from typing import Dict
from typing import Any
def create_local_command(opts: Options, jobs: List[Dict[str, Any]], jobs_metadata: List[Options]) -> str:
"""Create a terminal command to run the jobs locally."""
cmd = ""
for meta, job in zip(jobs_metadata, jobs):
input_file =... | f5d23c1fb2271b44a323d1d17e9dda35df29fcd7 | 3,752 |
import time
def time_for_log() -> str:
"""Function that print the current time for bot prints"""
return time.strftime("%d/%m %H:%M:%S - ") | 0f964d5c827782ff8cc433e57bb3e78d0a7c7cba | 3,753 |
import math
def _is_int(n) -> bool:
"""
is_int 是判断给定数字 n 是否为整数，
在判断中 n 小于epsilon的小数部分将被忽略，
是则返回 True，否则 False
:param n: 待判断的数字
:return: True if n is A_ub integer, False else
"""
return (n - math.floor(n) < _epsilon) or (math.ceil(n) - n < _epsilon) | 076a82d245333890d6790f65a58e5507905ca68f | 3,754 |
def _cpp_het_stat(A, t_stop, rates, t_start=0. * pq.ms):
"""
Generate a Compound Poisson Process (CPP) with amplitude distribution
A and heterogeneous firing rates r=r[0], r[1], ..., r[-1].
Parameters
----------
A : np.ndarray
CPP's amplitude distribution. A[j] represents the probabilit... | adc00577e9a6cb1ff7f9e0313befe98c81332ab1 | 3,755 |
def return_bad_parameter_config() -> CloudSettings:
"""Return a wrongly configured cloud config class."""
CloudSettingsTest = CloudSettings( # noqa: N806
settings_order=[
"init_settings",
"aws_parameter_setting",
"file_secret_settings",
"env_settings",
... | 06f8af87873d571be9c5ae7fd2e563402e57b2d0 | 3,756 |
def update(isamAppliance, instance_id, id, filename=None, contents=None, check_mode=False, force=False):
"""
Update a file in the administration pages root
:param isamAppliance:
:param instance_id:
:param id:
:param name:
:param contents:
:param check_mode:
:param force:
:return:... | af0b95096638fb34af130623b0929c4394a1a845 | 3,757 |
def view_deflate_encoded_content():
"""Returns Deflate-encoded data.
---
tags:
- Response formats
produces:
- application/json
responses:
200:
description: Defalte-encoded data.
"""
return jsonify(get_dict("origin", "headers", method=request.method, deflated=True)) | ff8d39f75a6cb526b3a61e85234e71efa174a208 | 3,758 |
def predict_from_word_vectors_matrix(tokens, matrix, nlp, POS="NOUN", top_number=constants.DEFAULT_TOP_ASSOCIATIONS):
"""
Make a prediction based on the word vectors
:param tokens:
:param matrix:
:param nlp:
:param POS:
:param top_number:
:return:
"""
vector_results = collect_wor... | 6a491e481238af932994bb8d383baca4da1ebd55 | 3,759 |
def blendImg(img_a, img_b, α=0.8, β=1., γ=0.):
"""
The result image is computed as follows:
img_a * α + img_b * β + γ
"""
return cv2.addWeighted(img_a, α, img_b, β, γ) | f60918ba424b0d59e9025c088c0f2c9a3f739fde | 3,762 |
def genoimc_dup4_loc():
"""Create genoimc dup4 sequence location"""
return {
"_id": "ga4gh:VSL.us51izImAQQWr-Hu6Q7HQm-vYvmb-jJo",
"sequence_id": "ga4gh:SQ.-A1QmD_MatoqxvgVxBLZTONHz9-c7nQo",
"interval": {
"type": "SequenceInterval",
"start": {
"valu... | 3ea1b39fed22487bebffc78d45cb493b7d7afa4a | 3,764 |
def compare_versions(a, b):
"""Return 0 if a == b, 1 if a > b, else -1."""
a, b = version_to_ints(a), version_to_ints(b)
for i in range(min(len(a), len(b))):
if a[i] > b[i]:
return 1
elif a[i] < b[i]:
return -1
return 0 | 0b22589164f7d3731edc34af97d306186e677371 | 3,765 |
def get_machine_action_data(machine_action_response):
"""Get machine raw response and returns the machine action info in context and human readable format.
Notes:
Machine action is a collection of actions you can apply on the machine, for more info
https://docs.microsoft.com/en-us/windows/sec... | 1e0ffc37d8d3b5662b64ec28cb850c6277b1bad2 | 3,766 |
import torch
def convolutionalize(modules, input_size):
"""
Recast `modules` into fully convolutional form.
The conversion transfers weights and infers kernel sizes from the
`input_size` and modules' action on it.
n.b. This only handles the conversion of linear/fully-connected modules,
altho... | 5693a17bac0f39538bfcada3280ce06ef91230a3 | 3,768 |
def is_unique2(s):
"""
Use a list and the int of the character will tell if that character has
already appeared once
"""
d = []
for t in s:
if d[int(t)]:
return False
d[int(t)] = True
return True | b1a1bdea8108690a0e227fd0b75f910bd6b99a07 | 3,769 |
import random
def uncomplete_tree_parallel(x:ATree, mode="full"):
""" Input is tuple (nl, fl, split)
Output is a randomly uncompleted tree,
every node annotated whether it's terminated and what actions are good at that node
"""
fl = x
fl.parent = None
add_descendants_ancestors... | f59e0f0279c9c439034116f769f51d60a924c4af | 3,770 |
def stations_by_river(stations):
"""Give a dictionary to hold the rivers name as keys and their corresponding stations' name as values"""
rivers_name = []
for i in stations:
if i.river not in rivers_name:
rivers_name.append(i.river)
elif i.river in rivers_name:
contin... | 66fd928415619d175b7069b8c3103a3f7d930aac | 3,771 |
def QA_SU_save_huobi(frequency):
"""
Save huobi kline "smart"
"""
if (frequency not in ["1d", "1day", "day"]):
return QA_SU_save_huobi_min(frequency)
else:
return QA_SU_save_huobi_day(frequency) | cdea45afe6d7e0b61dea517adb8fc484e8eafa38 | 3,772 |
def inverse(a):
"""
[description]
calculating the inverse of the number of characters,
we do this to be able to find our departure when we arrive.
this part will be used to decrypt the message received.
:param a: it is an Int
:return: x -> it is an Int
"""
x = 0
while a * x % 9... | 2893d2abda34e4573eb5d9602edc0f8e14246e09 | 3,774 |
from typing import Optional
from typing import Union
def currency_column_to_numeric(
df: pd.DataFrame,
column_name: str,
cleaning_style: Optional[str] = None,
cast_non_numeric: Optional[dict] = None,
fill_all_non_numeric: Optional[Union[float, int]] = None,
remove_non_numeric: bool = False,
) ... | e382752e5aff389872da69f42a3ec62785df336f | 3,775 |
async def subreddit_type_submissions(sub="wallstreetbets", kind="new"):
"""
"""
comments = []
articles = []
red = await reddit_instance()
subreddit = await red.subreddit(sub)
if kind == "hot":
submissions = subreddit.hot()
elif kind == "top":
submissions = subreddit.top()... | 9cc8655575ca8fd3729e220b0ee3fc8e45e4ed56 | 3,776 |
import typing
import json
def _get_bundle_manifest(
uuid: str,
replica: Replica,
version: typing.Optional[str],
*,
bucket: typing.Optional[str] = None) -> typing.Optional[dict]:
"""
Return the contents of the bundle manifest file from cloud storage, subject to the rules... | 7881e1514a9a645c1f7ee6479baa6e74bae4dabb | 3,778 |
def handler400(request, exception):
"""
This is a Django handler function for 400 Bad Request error
:param request: The Django Request object
:param exception: The exception caught
:return: The 400 error page
"""
context = get_base_context(request)
context.update({
'message': {
... | 0dc1b81ec86d675f348728863dfe07efbd936e8e | 3,779 |
def _gather_topk_beams(nested, score_or_log_prob, batch_size, beam_size):
"""Gather top beams from nested structure."""
_, topk_indexes = tf.nn.top_k(score_or_log_prob, k=beam_size)
return _gather_beams(nested, topk_indexes, batch_size, beam_size) | ebdaf391104a3f271a42549708f3e7adfaf8b0b0 | 3,781 |
import scipy
import numpy
def _traceinv_exact(K, B, C, matrix, gram, exponent):
"""
Finds traceinv directly for the purpose of comparison.
"""
# Exact solution of traceinv for band matrix
if B is not None:
if scipy.sparse.isspmatrix(K):
K_ = K.toarray()
B_ = B.toa... | 3637a5aa726ef1bf8489783c435c429b59422240 | 3,782 |
def create_feature_vector_of_mean_mfcc_for_song(song_file_path: str) -> ndarray:
"""
Takes in a file path to a song segment and returns a numpy array containing the mean mfcc values
:param song_file_path: str
:return: ndarray
"""
song_segment, sample_rate = librosa.load(song_file_path)
mfccs... | 8992feafd483bfe7b4af5e715ba1455884e1b710 | 3,783 |
def stations_highest_rel_level(stations, N):
"""Returns a list containing the names of the N stations
with the highest water level relative to the typical range"""
names = [] # create list for names
levels = [] # create list for levels
for i in range(len(stations)): # iterate through stat... | 780a03a424c9b2f0dedee2e93eb9bd27cc1fce36 | 3,784 |
def add_global_nodes_edges(g_nx : nx.Graph, feat_data: np.ndarray, adj_list: np.ndarray,
g_feat_data: np.ndarray, g_adj_list: np.ndarray):
"""
:param g_nx:
:param feat_data:
:param adj_list:
:param g_feat_data:
:param g_adj_list:
:return:
"""
feat_da... | 1097becfe88f05008541aaa6c3c074fcd5c3149a | 3,786 |
def get_data_collector_instance(args, config):
"""Get the instance of the data
:param args: arguments of the script
:type args: Namespace
:raises NotImplementedError: no data collector implemented for given data source
:return: instance of the specific data collector
:rtype: subclass of BaseDat... | 75fda1231e1489da4b0c10473c9f657b143047c1 | 3,788 |
def timeIntegration(params):
"""Sets up the parameters for time integration
:param params: Parameter dictionary of the model
:type params: dict
:return: Integrated activity variables of the model
:rtype: (numpy.ndarray,)
"""
dt = params["dt"] # Time step for the Euler intergration (ms)
... | 24d6702a92f82c6cc7fc1a337cd351b54c567e8b | 3,789 |
def is_role_user(session, user=None, group=None):
# type: (Session, User, Group) -> bool
"""
Takes in a User or a Group and returns a boolean indicating whether
that User/Group is a component of a service account.
Args:
session: the database session
user: a User object to check
... | 3d6b62b1708882b734031d737fa00f29ba9a9f95 | 3,790 |
def argCOM(y):
"""argCOM(y) returns the location of COM of y."""
idx = np.round(np.sum(y/np.sum(y)*np.arange(len(y))))
return int(idx) | 197ac25043b10575efb7405dba12c0d2e6f9976f | 3,791 |
def fringe(z, z1, z2, rad, a1):
"""
Approximation to the longitudinal profile of a multipole from a permanent magnet assembly.
see Wan et al. 2018 for definition and Enge functions paper (Enge 1964)
"""
zz1 = (z - z1) / (2 * rad / pc.pi)
zz2 = (z - z2) / (2 * rad / pc.pi)
fout = ( (1 / ... | b1d0138937d1c622809d6f559f17430e89259fed | 3,792 |
import random
def random_param_shift(vals, sigmas):
"""Add a random (normal) shift to a parameter set, for testing"""
assert len(vals) == len(sigmas)
shifts = [random.gauss(0, sd) for sd in sigmas]
newvals = [(x + y) for x, y in zip(vals, shifts)]
return newvals | 07430572c5051b7142499bcbdbc90de5abfcbd4d | 3,793 |
def compute_encrypted_request_hash(caller):
"""
This function will compute encrypted request Hash
:return: encrypted request hash
"""
first_string = get_parameter(caller.params_obj, "requesterNonce") or ""
worker_order_id = get_parameter(caller.params_obj, "workOrderId") or ""
worker_id = ge... | cf87c354df550b142030781e8b84ec1cb385489f | 3,794 |
def translate_line_test(string):
"""
Translates raw log line into sequence of integer representations for word tokens with sos and eos tokens.
:param string: Raw log line from auth_h.txt
:return: (list) Sequence of integer representations for word tokens with sos and eos tokens.
"""
data = strin... | d311eb9c6b398391724e868071d89f2f6c442912 | 3,795 |
def preprocess_signal(signal, sample_rate):
"""
Preprocess a signal for input into a model
Inputs:
signal: Numpy 1D array containing waveform to process
sample_rate: Sampling rate of the input signal
Returns:
spectrogram: STFT of the signal after resampling to 10kHz and adding
... | d2b6c5cb700ae877f7bf8bd4b5a772471e69a75d | 3,796 |
def get_frameheight():
"""return fixed height for extra panel
"""
return 120 | 3bd810eea77af15527d3c1df7ab0b788cfe90000 | 3,797 |
def default_heart_beat_interval() -> int:
"""
:return: in seconds
"""
return 60 | 58171c8fb5632aa2aa46de8138828cce2eaa4d33 | 3,798 |
import re
def email_valid(email):
"""test for valid email address
>>> email_valid('test@testco.com')
True
>>> email_valid('test@@testco.com')
False
>>> email_valid('test@testco')
False
"""
if email == '':
return True
email_re = re.compile(
r"(^[-!#$%&'*+/=?^_... | c76a621647595c741b1da71734a34372919e800f | 3,799 |
from typing import Any
def get_node_data(workspace: str, graph: str, table: str, node: str) -> Any:
"""Return the attributes associated with a node."""
return Workspace(workspace).graph(graph).node_attributes(table, node) | 0ac48d715fd31876b62d837d5b18b2ee75c791dd | 3,800 |
def siso_optional(fn, h_opt, scope=None, name=None):
"""Substitution module that determines to include or not the search
space returned by `fn`.
The hyperparameter takes boolean values (or equivalent integer zero and one
values). If the hyperparameter takes the value ``False``, the input is simply
... | 187a292c8dba59d5d4d7f67d54cdd087ee2b6582 | 3,801 |
def saconv3x3_block(in_channels,
out_channels,
stride=1,
pad=1,
**kwargs):
"""
3x3 version of the Split-Attention convolution block.
Parameters:
----------
in_channels : int
Number of input channels.
out_cha... | bda938d53bbb56a7035ae50125743e4eb9aa709b | 3,802 |
def add_hook(**_kwargs):
"""Creates and adds the import hook in sys.meta_path"""
hook = import_hook.create_hook(
transform_source=transform_source,
hook_name=__name__,
extensions=[".pyfr"],
)
return hook | 20c7e37aead055e32bfcb520a579b66069a3e26c | 3,803 |
def mul(n1, n2):
"""
multiply two numbers
"""
return n1 * n2 | c137432dd2e5c6d4dbded08546e3d54b98fe03df | 3,804 |
import torch
def pytorch_normalze(img):
"""
https://github.com/pytorch/vision/issues/223
return appr -1~1 RGB
"""
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])
img = normalize(torch.from_numpy(img))
return img.numpy(... | 7667d6fa3da69d89973bb804ad08a139ae7f3564 | 3,805 |
def get_nic_capacity(driver_info, ilo_fw):
"""Gets the FRU data to see if it is NIC data
Gets the FRU data in loop from 0-255 FRU Ids
and check if the returned data is NIC data. Couldn't
find any easy way to detect if it is NIC data. We should't be
hardcoding the FRU Id.
:param driver_info: Co... | cc20e1b35a47bec1242ed5dba60da8473527ca4f | 3,806 |
import re
def isValidInifileKeyName(key):
""" Check that this key name is valid to be used in inifiles, and to be used as a python property name on a q or i object """
return re.match("^[\w_]+$", key) | 9e68b987d6ac9af3c40e053c2347b01f737f0665 | 3,807 |
def installed_pkgs():
"""
Return the list of installed packages on the machine
Returns:
list: List of installed packages
CLI Example:
.. code-block:: bash
salt '*' macpackage.installed_pkgs
"""
cmd = "pkgutil --pkgs"
return __salt__["cmd.run"](cmd).split("\n") | b9a66600327ea8eb0ec63745cacd8509a0f757d9 | 3,808 |
import math
def extract_feature(audio, sr=44100):
"""
extract feature like below:
sig:
rmse:
silence:
harmonic:
pitch:
audio: audio file or audio list
return feature_list: np of [n_samples, n_features]
"""
feature_list = []
y = []
if isinstance(audio, str):
... | d4eca914605bc87c57dbaf846a9a01d79a953c56 | 3,809 |
from typing import OrderedDict
import six
def BuildPartialUpdate(clear, remove_keys, set_entries, field_mask_prefix,
entry_cls, env_builder):
"""Builds the field mask and patch environment for an environment update.
Follows the environments update semantic which applies operations
in an ... | 320c589cd45dcec9a3ebba4b295075e23ef805ed | 3,811 |
def create_schema_usb():
"""Create schema usb."""
return vol.Schema(CONFIG_SCHEMA_USB) | e543a5950788ad629ed3986cc7a6c5a58931a478 | 3,813 |
def _build_field_queries(filters):
"""
Builds field queries.
Same as _build_field_query but expects a dict of field/values and returns a list of queries.
"""
return [
_build_field_query(field, value)
for field, value in filters.items()
] | 9b1241cce6c421a79cd5ea26dd134d5fd93d6fde | 3,814 |
def bycode(ent, group):
"""
Get the data with the given group code from an entity.
Arguments:
ent: An iterable of (group, data) tuples.
group: Group code that you want to retrieve.
Returns:
The data for the given group code. Can be a list of items if the group
code occu... | c5b92f2bbd1cd5bc383a1102ccf54031222d82c3 | 3,815 |
from typing import List
from typing import Tuple
def get_midi_programs(midi: MidiFile) -> List[Tuple[int, bool]]:
""" Returns the list of programs of the tracks of a MIDI, deeping the
same order. It returns it as a list of tuples (program, is_drum).
:param midi: the MIDI object to extract tracks programs... | 7249baa46b80b8b42400068edacf5ce9e829c71f | 3,817 |
def is_depth_wise_conv(module):
"""Determine Conv2d."""
if hasattr(module, "groups"):
return module.groups != 1 and module.in_channels == module.out_channels
elif hasattr(module, "group"):
return module.group != 1 and module.in_channels == module.out_channels | 27127f54edbf8d0653cab6c7dbfb1448f33ecab4 | 3,818 |
def list_all_routed():
"""
List all the notifications that have been routed to any repository, limited by the parameters supplied
in the URL.
See the API documentation for more details.
:return: a list of notifications appropriate to the parameters
"""
return _list_request() | d67141d6fa5908d99292d898a5a77df3e80d47aa | 3,819 |
def Lstart(gridname='BLANK', tag='BLANK', ex_name='BLANK'):
"""
This adds more run-specific entries to Ldir.
"""
# put top level information from input into a dict
Ldir['gridname'] = gridname
Ldir['tag'] = tag
Ldir['ex_name'] = ex_name
# and add a few more things
Ldir['gtag'] = gridn... | 92d992c3a7eba7bbba9146018060bca7844d4a78 | 3,822 |
def rfe_w2(x, y, p, classifier):
"""RFE algorithm, where the ranking criteria is w^2,
described in [Guyon02]_. `classifier` must be an linear classifier
with learn() and w() methods.
.. [Guyon02] I Guyon, J Weston, S Barnhill and V Vapnik. Gene Selection for Cancer Classification using Support... | 9176ee36c1180ab862b23be9d9a09584abea50ca | 3,823 |
from typing import List
def compress_timeline(timeline: List, salt: bytes) -> List:
"""
Compress the verbose Twitter feed into a small one. Just keep the useful elements.
The images are downloaded per-request.
Args:
timeline (List): The Twitter timeline.
salt (bytes): The salt to appl... | aff1364714d7e83685ab2257167fcd8bc7e10436 | 3,824 |
def createFinalCompactedData(compacted_data,elevations):
"""
This function creates a dataframe that combines the RGB data and the elevations data
into a dataframe that can be used for analysis
Parameters
----------
compacted_data : list of compacted data returned from condensePixels.
elevat... | 0d8b6a5e10504c32988e05e7450ebcf077305949 | 3,825 |
def get_sorted_nodes_edges(bpmn_graph):
"""
Assure an ordering as-constant-as-possible
Parameters
--------------
bpmn_graph
BPMN graph
Returns
--------------
nodes
List of nodes of the BPMN graph
edges
List of edges of the BPMN graph
"""
graph = bpmn... | 879d7e8e3e5e4e9a8db3fc01622b96dde2b7af25 | 3,826 |
from typing import Optional
from typing import Dict
from typing import Any
def list_commits(
access_key: str,
url: str,
owner: str,
dataset: str,
*,
revision: Optional[str] = None,
offset: Optional[int] = None,
limit: Optional[int] = None,
) -> Dict[str, Any]:
"""Execute the OpenAP... | be3899be0b77de069c7d32ca39aaec2039fe89e4 | 3,827 |
import heapq
def dijkstra(graph, start, end=None):
"""
Find shortest paths from the start vertex to all
vertices nearer than or equal to the end.
The input graph G is assumed to have the following
representation: A vertex can be any object that can
be used as an index into a dictionary. G is... | b2a1ee983534c0a4af36ae7e3490c3b66949609b | 3,828 |
def tournament_selection(pop, size):
""" tournament selection
individual eliminate one another until desired breeding size is reached
"""
participants = [ind for ind in pop.population]
breeding = []
# could implement different rounds here
# but I think that's almost the same as calling tour... | 78bebc2de25d0744f3f8dabd67f70136d5f020b5 | 3,830 |
import math
def bond_number(r_max, sigma, rho_l, g):
""" calculates the Bond number for the largest droplet according to
Cha, H.; Vahabi, H.; Wu, A.; Chavan, S.; Kim, M.-K.; Sett, S.; Bosch, S. A.; Wang, W.; Kota, A. K.; Miljkovic, N.
Dropwise Condensation on Solid Hydrophilic Surfaces. Science Advances 2... | 2098a762dd7c2e80ff4a570304acf7cfbdbba2e5 | 3,831 |
def spatial_conv(inputs,
conv_type,
kernel,
filters,
stride,
is_training,
activation_fn='relu',
data_format='channels_last'):
"""Performs 1x1 conv followed by 2d or depthwise conv.
Args:
input... | e87820eaa5b8ed13157fe0790c4e09b1bc546a0d | 3,832 |
async def timeron(websocket, battleID):
"""Start the timer on a Metronome Battle.
"""
return await websocket.send(f'{battleID}|/timer on') | f1601694e2c37d41adcc3983aa535347dc13db71 | 3,833 |
import numpy
def to_unit_vector(this_vector):
""" Convert a numpy vector to a unit vector
Arguments:
this_vector: a (3,) numpy array
Returns:
new_vector: a (3,) array with the same direction but unit length
"""
norm = numpy.linalg.norm(this_vector)
assert norm > 0.0, "vector ... | ae46bf536b8a67a1be1e98ae051eebf1f8696e37 | 3,834 |
import base64
def decode(msg):
""" Convert data per pubsub protocol / data format
Args:
msg: The msg from Google Cloud
Returns:
data: The msg data as a string
"""
if 'data' in msg:
data = base64.b64decode(msg['data']).decode('utf-8')
return data | 32e85b3f0c18f3d15ecb0779825941024da75909 | 3,835 |
def pivot_longer_by_humidity_and_temperature(df: pd.DataFrame) -> pd.DataFrame:
"""
Reshapes the dataframe by collapsing all of the temperature and humidity
columns into an temperature, humidity, and location column
Parameters
----------
df : pd.DataFrame
The cleaned and renamed datafra... | d60b92b523c31b3f7db799f58a42bd9ca810d258 | 3,836 |
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