content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def productos_pos():
"""
Muestra las configuraciones para productos pos
"""
productos = db(db.maestro_pos).select()
return dict(productos=productos) | 87e80d5789f65df46c3178a9d83e575321b423a7 | 3,632,000 |
def _build_measurement_vectors(ppci):
"""
Building measurement vector z, pandapower to ppci measurement mapping and covariance matrix R
:param ppci: generated ppci which contains the measurement columns
:param branch_cols: number of columns in original ppci["branch"] without measurements
:param bus_... | b51be7da841ce5c54942834133d64263fcf29ff1 | 3,632,001 |
import zipfile
from io import StringIO
import numpy
import json
import pickle
def load(path):
"""Load data and reconstruct model."""
with zipfile.ZipFile(path,'r') as zf:
buf = StringIO.StringIO(zf.read('weights.npy'))
weights = numpy.load(buf)
config = json.loads(zf.read('config.json... | bee50593f16a534c16f9961e53aaf6a31b5bd3d1 | 3,632,002 |
def env(
a,
import_models=False,
c=None,
f=None,
dir='',
):
"""
Return web2py execution environment for application (a), controller (c),
function (f).
If import_models is True the exec all application models into the
environment.
"""
request = Request()
response ... | 3d78e71866eb1daf06e6e20e9437a0bf39210363 | 3,632,003 |
import copy
import hashlib
import json
def get_payload_hash(payload):
"""Return unique hash of HySDS job JSON payload."""
clean_payload = copy.deepcopy(payload)
for k in ('_disk_usage', '_sciflo_job_num', '_sciflo_wuid'):
if k in clean_payload:
del clean_payload[k]
return hashlib.... | e5122c85c3bfc358dda0404d029d06efbe2fefde | 3,632,004 |
def binStack(array, bins, id0=1):
"""
Bin a hyperstack according to a known list of frames per bin
@param array: input array to be binned, hyperstack or otherwise.
Binning occurs along the first axis
@type array: numpy.ndarray
@param bins: list of frames in each bin. Each index in bins is a... | 3367566a37e6328cd8af039e91a40d176b488617 | 3,632,005 |
import torch
def knn(A, B, k, distFcn):
"""
Returns the indices of the k-nearest neighbors of A in B
Parameters
----------
A : Tensor
a (N,F,) tensor
B : Tensor
a (M,F,) tensor
k : int
the number of neighbors to find
distFcn : callable
the distance func... | f9c3bac58ff3fcffe53bb9b2a25ffbcc57870ec9 | 3,632,006 |
def set_purpose(slack_client, channel, purpose):
"""
Set the purpose of a given channel.
"""
response = slack_client.api_call("channels.setPurpose",
purpose=purpose, channel=channel)
return response | 786a495b55300b955e2f7ec525117be75b251a07 | 3,632,007 |
import os
def generate_aes_key(size=256):
"""
Generates aes key with specified size
:param size: aes bits, default 256
:return: generated key bytes
"""
return os.urandom(int(size / 8)) | 604b626ae0996499c2d855ede91f70ded8f585cc | 3,632,008 |
def masked_minimum(data, mask, dim=1):
"""Computes the axis wise minimum over chosen elements.
Args:
data: 2-D float `Tensor` of size [n, m].
mask: 2-D boolean `Tensor` of size [n, m].
dim: The dimension over which to compute the minimum.
Returns:
masked_minimum: N-D `Tensor`.
The minimize... | 7629c1a2ba9c2089935a68354d748a80e1eff488 | 3,632,009 |
from typing import Tuple
import subprocess
import os
def spawn_node_process(output_dir: PathLike) -> Tuple[subprocess.Popen, str]:
"""
Spawn an rfbrowser node process, that can be shared between library instances.
Usage example:
rc = 1
background_process, port = spawn_node_process(ATEST_OUTPUT /... | cbdd9660060910b74f75803e1dfa0f6cacfbc25d | 3,632,010 |
import json
def decode_stderr_json(stderr):
""" return a list of decoded json messages in stderr """
# - check for blank input
if not stderr:
# - nothing to do
return list()
# - split the input (based on newlines) into list of json strings
output = list()
for line in stderr.spl... | d527730d8d9a77a1ec434ee6203c4e08433306c9 | 3,632,011 |
import collections
def hash_params(params):
"""
Construct a data structure of parameters that is hashable.
This requires changing any mutable data structures into immutable ones.
We chose a frozenset because role parameters have to be unique.
.. warning:: this does not handle unhashable scalars... | eb83122e2b1f7097917f1029e84f2053352127f4 | 3,632,012 |
def get_validate_result_form(tel_num, validate_code):
"""
Assemble form for get_validate_result
:param tel_num: Tel number
:param validate_code: Validate code from capcha image
:return: Param in dict
"""
post_data_dict = dict()
post_data_dict['source'] = 'wsyyt'
post_data_dict['telno... | 6340c97522a097c0cf96170e08466fb795e16dc3 | 3,632,013 |
def create_user():
"""Create a new user record."""
request = flask.request.get_json()
try:
# NOTE(jk0): We expect all of these keys to exist to be considered a
# valid user record. Ignore all others.
user = _lookup_user(request["userid"])
if user:
flask.abort(40... | 8d98667aba51172535768d6c57d9fc8f2e2e7821 | 3,632,014 |
def softmax_cross_entropy(logits, labels):
"""
Cross-entropy loss applied to softmax.
"""
one_hot = hk.one_hot(labels, logits.shape[-1])
return -jnp.sum(jax.nn.log_softmax(logits) * one_hot, axis=-1) | c0850fdebbf69629763e94c489ed0aaf67e67184 | 3,632,015 |
def get_category_detail(comp_id, cat_id):
"""Retrives information about the category and the reviews in it"""
json = [Category.query.filter_by(id=cat_id).filter_by(comp_id=comp_id).first_or_404().to_json()]
submissions = Submission.query.filter_by(comp_id=comp_id).all()
cat_submissions = []
for _, s... | d6b780a8d2c985f55a6500faf386c437669d0e9a | 3,632,016 |
def build_input_from_segments(persona, history, reply, vocab,
labels=False, with_eos=True):
"""
Build a sequence of input from 3 segments:
persona, history and last reply.
"""
bos, eos, speaker1, speaker2 = vocab[SPECIAL_TOKENS[:-1]]
sequence = [[bos] + list(chain(*... | 3b47bbc0fb7c666188f36a1e1df520d84327d336 | 3,632,017 |
from scipy.stats import norm
def dual_gaussian(x, amp1=1.0, mean1=0.0, std1=1.0, amp2=1.0, mean2=0.0, std2=1.0):
"""Sum of two Gaussians.
Parameters
----------
x : array
Function argument
amp1: float
Amplitude parameter of the first Gaussian
mean1: float
Mean parameter of th... | 6d46ffcfcfd0327d06ccc8c92157bd9f82813124 | 3,632,018 |
import os
def getFileInfoFromXML(thisfile):
""" Get the PFN from the XML """
pfn = thisfile.getElementsByTagName("pfn")[0].getAttribute("name")
# lfn will not be present in XML any longer, get it from the PFN - possible problem with LFN file name extensions
# lfn = thisfile.getElementsByTagName("lfn"... | 788080388a4c7984f8646a944eefa04a7ce22536 | 3,632,019 |
def get_district_info(request, code):
"""
Get district info by 'code'
"""
try:
district = District.objects.get(code=code)
child_districts = District.objects.filter(parent=district.code)
data = district_model2dict(district)
children = [district_model2dict(c) for c in child... | 57136fe7d77375b6d9c258b42bccf24e4c7a3750 | 3,632,020 |
def calculate_price(prices, concentrations):
"""
From a list of prices in $USD / kg and concentrations in mass %,
calculate the price of the formulation in $USD / kg
"""
# Normalise ingredient concentrations
concentrations = np.asarray(concentrations) / np.sum(concentrations)
# Calculate a... | 7131bb0aa5f9502f564e43eba76ee3b878041b22 | 3,632,021 |
def cos_convolve(evidence):
"""Take as input the classifier evidence for single trials in dictionary format
and return alligned evidence and evidence convolved with a cosine.
Input:
dictionary:
accuracy : ndarray
dimensions: time
matrix containing class predi... | cf292eb0af8d4f44a0d64c02b9a09e6b7d149eb9 | 3,632,022 |
from io import StringIO
def get_image_info(real_image_type, body):
""" only in webp, gif, png, jpeg, bmp
"""
image_fp = StringIO(body)
if real_image_type == 'webp':
data = image_fp.read()
width, height = decode.GetInfo(data)
image_pix_count = int(width) * int(height)
else:... | 9570de917deafdcaa2d2a2d208e40710bcb12d04 | 3,632,023 |
def estimate_ranks(layer):
""" Unfold the 2 modes of the Tensor the decomposition will
be performed on, and estimates the ranks of the matrices using VBMF
source: https://github.com/jacobgil/pytorch-tensor-decompositions/blob/master/decompositions.py
"""
weights = layer.weight.data
unfold_0 = ... | 3c4efeb5ad56a32ad3908657c013bfb153aaf01e | 3,632,024 |
def _add_batch_dim(img):
"""Many TF functions require NWHC input. Convert WHC image to NWHC of batch size 1."""
get_hwc(img) # validate dimensions
return tf.expand_dims(img, 0) | 53a995d6a1398f137abb69b38aa91b98257e50c3 | 3,632,025 |
def read_inventory_file(inventory):
"""
Read an inventory file, return the list of dicts
:param str inventory: The inventory file
:return list[dict, ..]: List of hostname and IP definitions
"""
log.info("Reading and validating inventory file")
inventory_hosts = load_json(inventory)
if no... | cff1d3c84b3617b12e4bee7b4726207d4d4747cd | 3,632,026 |
def ground_truth_to_word(ground_truth):
"""
Return the word string based on the input ground_truth
"""
try:
return ''.join([config.CHAR_VECTOR[np.argmax(arr)] for arr in ground_truth if np.argmax(arr) < len(config.CHAR_VECTOR)])
except Exception as ex:
print(ground_truth)
... | ae07266f34f01d605705d60e7c331cefb1fb845a | 3,632,027 |
import itertools
def build_dataframe(dimension_names, dimension_members, data_values,
null_values, sd_values):
"""Build a dataframe from dimensions and data.
Adds the cartesian product of dimension members plus the series of data.
Args:
dimension_names (list of string)
... | 1d5621d753466a69bd0bef4120c2c445e959bbb9 | 3,632,028 |
def fs_url_exists(fs_url):
"""
verifies for a valid fs url
:param fs_url: fs_url string
:return: boolean
"""
try:
fs.open_fs(fs_url)
except fs.errors.CreateFailed:
return False
return True | 98aad242d04b169e1a1e3204bf40e0b4ac9c4018 | 3,632,029 |
def _serialize_noise_model(config):
"""Traverse the dictionary looking for noise_model keys and apply
a transformation so it can be serialized.
Args:
config (dict): The dictionary to traverse
Returns:
dict: The transformed dictionary
"""
for k, v in config.items(... | f3453e174d5ba858b9eec678e7bc1574f74d50eb | 3,632,030 |
def create_app() -> falcon.API:
"""
Typical application factory style setup.
Returns:
falcon.API: The falcon API object.
"""
engine = create_engine("sqlite:///")
app = falcon.API(middleware=[DbSessionMiddleware(engine)])
app.add_route("/", ExampleResource())
return app | ab134f8d25644da01718a16e4887d023f5e0221f | 3,632,031 |
def show_tracker(secure=False):
"""
Output the analytics tracker code.
"""
google = getattr(settings, 'ANALYTICS', {})
if google:
analytics_code = google.get('ANALYTICS_CODE')
if analytics_code:
return {"analytics_code": analytics_code}
return {} | 32d30b031e979cf91165dba4872a93995289bbc4 | 3,632,032 |
from typing import Awaitable
import re
async def formatCommand(cls:"PhaazebotDiscord", Command:DiscordCommand, CommandContext:DiscordCommandContext, direct_call:bool=False) -> dict:
"""
This function is suppost to do everything.
It takes the placeholder in Command.content and replaces them with the wanted data.
... | 306e44d6b493c08140f24834d715669afb00477b | 3,632,033 |
def k8s_net_client(k8s_conf):
"""
Retrieves the kubernetes networking client
:param k8s_conf: the k8s configuration used to deploy the cluster
:return: a kubernetes.client.NetworkingV1Api instance
"""
logger.debug('Retrieving K8s networking API client')
return client.NetworkingV1Api(get_clie... | be57c7ba0558db35237b426dbfbc813b9f435ff4 | 3,632,034 |
import os
def sequential_name(folder, basename):
"""
Given a proposed name for a file (string 'basename') to be saved in a
folder (identified by its path in string 'folder'), produces a new
name to use that avoids overwriting other files - as long as their
names were made with this function, too.
"""
i... | 1a1afd78371da050ef6e44aa909d8c800f82ac21 | 3,632,035 |
def metric_max_over_ground_truths(metric_fn, predictions, ground_truths):
"""Take the average best score against all ground truth answers.
This is a bit different than SQuAD in that there are multiple answers
**and** predictions that we average over. For some situations (e.g., *top k*
beams or multiple human r... | 7c78fc1cca29bc9784a4e4687d794c1f2b6872c9 | 3,632,036 |
def parse_gsod_data(filename):
"""Parse Global Summary of the Day (GSOD) data from a comma separated
.txt file.
Source: https://www7.ncdc.noaa.gov/CDO/cdoselect.cmd?datasetabbv=GSOD&countryabbv=&georegionabbv=
Format Specification: https://www7.ncdc.noaa.gov/CDO/GSOD_DESC.txt
Parameters:
... | 963444222e7627c25354ec6d0d891df4fee4fe8c | 3,632,037 |
def deserialize(xml):
""" Deserializes a Pubmed response into an article object."""
article = {}
root = ET.fromstring(xml)
article_el = root.find('.//PubmedArticle')
if article_el is None:
print('INFO: XML did not contain a Pubmed Article.')
return None
pmid_el = article_el.find('.//MedlineC... | 5cdb8c622f9155eaf36659bd9cab092e3adc4c44 | 3,632,038 |
def attSummaryDict(request, reqs, flist):
""" Return a dictionary summarizing the field values for the chosen most interesting fields """
sumd = {}
for req in reqs:
for f in flist:
if f in req and req[f]:
if not f in sumd: sumd[f] = {}
if not req[f] i... | bafbbe51555cb46c664d33ea31a0e36c56152fa9 | 3,632,039 |
def immutable_kwargs(
kwargs: tp.Dict[str, str]
) -> tp.Tuple[tp.Tuple[str, str], ...]:
"""
Convert str-typed kwargs into a hashable tuple.
"""
return tuple((k, v) for k, v in kwargs.items()) | 900e263e0a7928bfb2c65e3dc7f9c8e405014fb5 | 3,632,040 |
import os
def get_markings(catalogue_dir, cid, result):
"""
Take a directory of catalogue entries and extract the specific metadata related to CID
Add it to fields as defined in serene_metadata
"""
catalogue = load_markings(os.path.normpath(catalogue_dir))
catalogue_markings = catalogue[cid... | c4ad3863559e35b55993771d5b02ee274da9fea0 | 3,632,041 |
import numpy
def revise_max_intake(
max_intake, total_digestibility, energy_intake, energy_maintenance,
degr_protein_intake, protein_req, animal_type, CRD1, CRD2):
"""Calculate revised maximum intake from protein content of the diet.
When animals are unable to obtain enough protein from the d... | cfe61d2717fcf42104423499e1e1343873c905a0 | 3,632,042 |
from pegasusio.cylib.io import read_fcs
def load_fcs_file(input_fcs: str, genome: str = None) -> MultimodalData:
"""Load Cyto data from a FCS file, support v2.0, v3.0 and v3.1.
Parameters
----------
input_fcs : `str`
The FCS file.
genome : `str`, optional (default None)
The genom... | 232b849679c209863fdc3cc17ad1dc254ed23ab0 | 3,632,043 |
def ext_bottom_up_cut_rod(price, length):
""" bottom up implementation of cut rod memoized algorithm """
incomelst = [float("-Inf") for _ in range(length + 1)]
cutlst = [0 for _ in range(length + 1)]
# set zero income for zero length
incomelst[0] = 0
for j in range(1, length + 1):
income... | 7dd8c43afa9f71793d372b474963ff84d2ce607f | 3,632,044 |
def _build_config_dict(cfg_node):
"""
Updates the config dict provided from the given etcd node, which
should point at a config directory.
"""
config_dict = {}
for child in cfg_node.children:
key = child.key.rsplit("/").pop()
value = str(child.value)
config_dict[key] = va... | 567fca19a6e1890c881170200ba44fc262148948 | 3,632,045 |
import time
def stamp_to_ymd(timestamp):
"""
Caller sends a timestamp in seconds of epoch. Return string for
year month day of that time as YYYYMMDD' as used by url requests, as in
http://<fitsstore_server>/qaforgui/20130616
parameters: <float>, seconds of epochs.
return: <string>, YYYYM... | 2928e93a48f1a5c3abdddcb6285bed7b0cebb369 | 3,632,046 |
def ESMP_GridCreateCubedSphere(tilesize, regDecompPTile=None,
#decompFlagPTile=None, deLabelList=None,
staggerLocList=None, name=None):
"""
Preconditions: ESMP has been initialized.\n
Postconditions: An ESMP_Grid has been created.\n
Arguments... | 999d9b995671af9e410f73e29b2e1af8d79ad5a4 | 3,632,047 |
def extract_asymbox2(image,left_in,right_in, ycen=None, weight_image=None):
""" Extract the total flux within a variable window at many positions. This routine will accept an asymmetric/variable window
specified by the left_in and right_in traces. The ycen position is optional. If it is not provied, it is assu... | 34a7b2bf8ea79023f6847469ceafe376ef4d3fd0 | 3,632,048 |
import os
def exists(b, d, n):
"""Check if the folder specified by the given parameters exists"""
return os.path.isdir("../Output/B" +
str(b) + " D" + str(d) + " N" + str(n)) | b94f8bfb38351127e77fa9f19b706906d9805e82 | 3,632,049 |
def version() -> str:
"""版本号"""
return f'Version: {VERSION}' | df0dee3edebdaf24b52a9ad128b5198c89c779a5 | 3,632,050 |
import ctypes
def UnpackMessage(swig_obj_pointer, msg_name):
"""Unpack a SWIG-wrapped memory object into an AIO message.
Args:
swig_obj_pointer: A SWIG-wrapped memory object pointing to the raw AIO
message payload.
msg_name: Name or short name of the message type.
Returns:
An AIO message s... | 2e445f5248ba023190298eec30e0e473804f3df5 | 3,632,051 |
def a2b_hashed_base58(s):
"""
If the passed string is hashed_base58, return the binary data.
Otherwise raises an EncodingError.
"""
data = a2b_base58(s)
data, the_hash = data[:-4], data[-4:]
if double_sha256(data)[:4] == the_hash:
return data
raise EncodingError("hashed base58 ha... | 82276533405e952f8f89cf3caefce6e653ab5694 | 3,632,052 |
def predict(theta, X):
""" computes the predictions for X using a threshold at 0.5
(i.e., if sigmoid(theta'*x) >= 0.5, predict 1)
"""
return np.array([1 if theta.dot(xi) >= 0.5 else 0 for xi in X]) | 3a80add19d08989f94cb3f9e4c058a37bd128f20 | 3,632,053 |
def not_contains(a, b):
"""Evaluates a does not contain b"""
result = False if b in a else True
return result | a0dc087049c8e93c1acdf0e59e3530a6ff8b54e5 | 3,632,054 |
def build_positional_encoding(cfg, default_args=None):
"""Builder for Position Encoding."""
return build_from_cfg(cfg, POSITIONAL_ENCODING, default_args) | 9db2eb7d88b5d4ceea0a9d62adc3239035a34cec | 3,632,055 |
def create_func_result_identifier(func, params_str, key=None, key_separator="__"):
"""
Creates a string of the following format:
If ``key`` is None:
``<FUNC_NAME><PARAMS_STR>``
If ``key`` is not None:
``<FUNC_NAME><PARAMS_STR>__key``
In both cases, ``<FUNC_NAME>`` represents the name of... | 6f3a7a6a8a94629dae7817403d78ef1f970ad5b2 | 3,632,056 |
def quat_to_euler(q):
"""
Converts a unit quaternion:
q = (w, x, y, z) = w + (x i, y j, z k)
into the aircraft Euler angles (roll, pitch, yaw) = (phi, th, psi).
"""
R00 = 1 - 2*q[2]**2 - 2*q[3]**2
R10 = 2*q[1]*q[2] + 2*q[3]*q[0]
if np.sqrt(R00**2 + R10**2) >= .000001:
phi = np... | 507e26d657a868bc136c901612ffba5dff62975d | 3,632,057 |
def idc_get_local_type_name(*args):
"""
idc_get_local_type_name(ordinal) -> char
"""
return _ida_typeinf.idc_get_local_type_name(*args) | c0921c70f0f42d913bbbe4e6d41a02a58660da0e | 3,632,058 |
import csv
def import_town(data_file):
"""
Reads town raster data from a CSV file.
Parameters
----------
data_file : str
Name of CSV raster data file to use for the town.
Returns
-------
town : list
List (cols) of lists (rows) representing raster data of the town.
... | b7749dfd4d698fddfe610c6a51c8ccc43c375cc2 | 3,632,059 |
def init_network():
"""신경망(neural network)에서 사용되는 가중치 행렬과 bias 행렬을 생성
교재 p.88
입력층: (x1, x2) -> 1x2 행렬
은닉층:
- 1st 은닉층: 뉴런 3개 (x @ W1 + b1)
- 2nd 은닉층: 뉴런 2개
출력층: (y1, y2) -> 1x2 행렬
W1, W2, W3, b1, b2, b3를 난수로 생성
1x2 2x3 3x2
"""
np.random.seed(1... | ddf727e651d46523f83d5d4e870c26e6bbc0b54c | 3,632,060 |
def reduce_detections(detections, detection_indices, img_w, img_h):
"""
Removes overlapping detections
Important note: Tensorflow detections are already sorted by detection score!
(optional)
TODO: Could tweak this paramter based on num of faces (2 ears, 1 of each class, per pers... | d774f88eaa91c79b6e9982520a836a4f5e1fb609 | 3,632,061 |
import os
def load_fiveplates_summary(platerun):
"""
"""
summary_file = paths.fiveplates_summary(platerun)
if summary_file.exists():
pass
else:
raise FileNotFoundError(os.fspath(summary_file))
return Table.read(os.fspath(summary_file), format='ascii') | 4abd9d534647546a793f796bd006e2ff19474a48 | 3,632,062 |
def make_connection():
"""Connection function to establish database connection. During development, the connection information will be
hard coded, however during actual deployment to AWS, the connection information will be retrieved from
other services eg aws secret manager etc.
Returns:
... | fa69c2752444cbee1d5630ee829bd5ebc4c0e0c5 | 3,632,063 |
import random
def a_noun(random=random, *args, **kwargs):
"""
Return a noun, but with an 'a' in front of it. Or an 'an', depending!
>>> mock_random.seed(0)
>>> a_noun(random=mock_random)
'an onion'
>>> a_noun(random=mock_random, capitalize=True)
'A Chimp'
>>> a_noun(random=mock_random... | 1eae1f7b445017d64fc17fe0364275d73ead1b87 | 3,632,064 |
def _tree_flatten_with_names(tree):
"""Populates tree_flatten with leaf names.
This function populates output of tree_flatten with leaf names, using a
custom traversal that produces names is provided. The custom traversal does
NOT have to traverse tree in the same order as jax, as we take care of
automatical... | 2878ece5d63d09d42d4b195706a4594b135ce849 | 3,632,065 |
def inhomogeneous_poisson_process(rate, as_array=False,
refractory_period=None):
"""
Returns a spike train whose spikes are a realization of an inhomogeneous
Poisson process with the given rate profile.
Parameters
----------
rate : neo.AnalogSignal
A `n... | 240b04f5e5ed316d911aad0ee690516982f123cd | 3,632,066 |
import re
def enumerate_quotes(filename, encoding="utf-8", empty_name="Inconnu"):
"""
Enumerates quote from a filename or a stream
@param filename filename or stream
@param encoding applicable only if filename
@param empty_name replces an empty author name
@r... | 51e3a406c05ab81ade918123ee4fba801fb9ef9e | 3,632,067 |
def _params_to_df(params: Parameters) -> DataFrame:
"""Convert lmfit.Parameters to pandas.DataFrame."""
return DataFrame(
[
(p.name, p.vary, p.value, p.stderr, p.min, p.max, p.brute_step, p.expr)
for p in params.values()
],
columns=(
"name",
... | 7485f43a474eef1ebb20ddb73bb411dad52cd918 | 3,632,068 |
def w(P, T, region = 0):
""" Speed of sound [m / s]"""
if region is 0:
region = idRegion(P, T)
if region is 1:
return region1.w(P, T)
elif region is 2:
return region2.w(P, T)
else:
return 0.000 | 7589c57071484d0f46e67a18bd125ad46edbe777 | 3,632,069 |
def WaitForOperation(api_version, response, asynchronous):
"""Handles waiting for the operation and printing information about it.
Args:
api_version: Cloud Domains API version to call.
response: Response from the API call
asynchronous: If true, do not wait for the operation
Returns:
The last inf... | 518e68421082bb3a2a90b38ae62c5be02f20d9fb | 3,632,070 |
from datetime import datetime
def generateVtBar(symbol, d):
"""生成K线"""
bar = VtBarData()
bar.symbol = symbol
bar.vtSymbol = symbol
bar.open = d['open']
bar.high = d['high']
bar.low = d['low']
bar.close = d['close']
bar.volume = d['volume']
bar.openInterest = d['open_oi']
... | d155bda31fba71f07af4d23d17fcaa09c6a277e4 | 3,632,071 |
def produce_validation_report(stages, jobs, validation_json, **kwargs):
"""Produce validation report inside CI pipeline.
@param stages: the GitLab CI stages to consider
@param jobs: the job names to consider
@param validation_json: local job path to validation JSON output
@return summary of valida... | bdcb0c87db61c78766bd3afddc1cd74737a43b51 | 3,632,072 |
def search_file(drive_service, num_of_responses, query):
"""
Search for files and store results of query in pd.DataFrame
"""
results = (
drive_service.files()
.list(
pageSize=num_of_responses,
q=query,
fields="nextPageToken, files(id, name, kind, expor... | b7bb340f0c1bb89bc76ecc420b473609a0bbbb2c | 3,632,073 |
from datetime import datetime
import numpy
def L6_summary_daily(ds,series_dict):
"""
Purpose:
Calculate the daily averages or sums of various quantities and write
them to a worksheet in an Excel workbook.
Usage:
L6_summary_daily(ds,series_dict)
where ds is an OzFluxQC data structure
... | d1f57bb364abd7c92b73eab2d9787f5893264a3c | 3,632,074 |
def check_eol(file, eol):
"""Check file EOL.
:param file: Path to file to check
:param eol: Expected End of Line
:return: Resulting error messages
:rtype: str
"""
error = ''
with open(file, 'rb') as open_file:
content = open_file.read()
if eol == '\n':
if b'\r\n' i... | 44bb060531c50ab5d072906414b8c948c9d6ecfa | 3,632,075 |
def pe44(limit=1500):
"""
>>> pe44()
(5482660, 7042750, 1560090, 2166, 1019)
"""
pents = [i * (3 * i - 1) >> 1 for i in range(1, limit << 1)]
ps = set(pents)
for i in range(limit):
p1 = pents[i]
for j in range(i + 1, (limit << 1) - 1):
p2 = pents[j]
di... | e41f513c518b502de0c47f3a70390f9df01a1868 | 3,632,076 |
import re
def text_cut(questions):
"""
This def will cut the text into words by jieba and del the stopwords then return the words,else return a string when
fail to find the stop_list.
:param questions: A list of text.
:return: A list of cut-words
Raises: FileNotFoundError: An error occurred se... | c7cc8e52265b6e7cbe222d899952ee2ddc13231d | 3,632,077 |
import logging
import sys
def mask_3D(hPa, sect, MBL=True, res='4x5', extra_mask=None,
M_all=False, use_multiply_method=True, trop_limit=False,
verbose=True, debug=False):
"""
Creates Maskes by pressure array (required shape: 72,46,47),
with conditions (lower and upper bounds) set... | b44124174b8c9ed82989d31f6b5a4ed6b43d73a0 | 3,632,078 |
def export_visible_cells(
self,
export_keyword="FLUXNUM",
visible_active_cells_value=1,
hidden_active_cells_value=0,
inactive_cells_value=0,
):
"""Export special properties for all visible cells.
Arguments:
export_keyword (string): The keyword to export.
Choices: 'FLUXNUM' o... | e7f03371a7c14385a2039ccb597e7e464f54b4f1 | 3,632,079 |
def sanitize_markdown(markdown_body):
"""
There are some symbols used in the markdown body, which when go through Markdown -> HTML
conversion, break. This does a global replace on markdown strings for these symbols.
"""
return markdown_body.replace(
# This is to solve the issue where <s> and... | adf21a9bbea1a95f0f4c0aca8d61ab6d69627074 | 3,632,080 |
def ProjectsInsightTypeInsightsService(api_version):
"""Returns the service class for the Project insights."""
client = RecommenderClient(api_version)
return client.projects_locations_insightTypes_insights | 7173907ad599fd4457050a2fb1d15d01d19098cf | 3,632,081 |
def get_course_dict(only_active=True):
""" Return a dictionary of courses.
By default only active courses.
key will be course ID.
courses[cid] = {id:, name:, title:}
"""
cdict = {}
reload_if_needed()
for course in COURSES:
if only_active:
if COURSES[cours... | 6e538b473224274c5ec7e8db17975c934e126c44 | 3,632,082 |
def _build_jinja2_expr_tmp(jinja2_exprs):
"""Build a template to evaluate jinja2 expressions."""
exprs = []
tmpls = []
for var, expr in jinja2_exprs.items():
tmpl = f"{var}: >-\n {{{{ {var} }}}}"
if tmpl not in tmpls:
tmpls.append(tmpl)
if expr.strip() not in exprs:
... | 3e5d944345316a40b7b8052f9b13801228607099 | 3,632,083 |
def create_blueprint(app):
"""Register blueprint routes on app."""
routes = app.config.get("APP_ROUTES")
blueprint = Blueprint(
"{{cookiecutter.package_name}}_records",
__name__,
template_folder="../templates",
)
# TODO: register your record views here.
# Register temp... | 28e8a6c1b54b2aeee4f901e110d9915c4f4f89f0 | 3,632,084 |
def normal(x, mu=0, sig=1):
""" Normal distribution log-likelihood.
:param x: *int, float, np.array.*
:param mu: (optional) *int, float, np.array.*
Location parameter of the normal distribution. Defaults to 0.
:param sig: (optional) *int, float.*
Standard deviatio... | fc88fd34b4c5e5be835c1d29b2f8f38b7f1f21b9 | 3,632,085 |
import optparse
import platform
def parse_args(args):
"""
Parse arguments
"""
parser = optparse.OptionParser()
parser.add_option('--os', default=platform.system().lower(),
help='Set the target os (default %default)')
parser.add_option('--cc', default='gcc',
... | 04d5c4c4168f04c2e4ec9de39a3a6c44a9c131e4 | 3,632,086 |
def BitmapFromImage(image):
"""
A compatibility wrapper for the wx.Bitmap(wx.Image) constructor
"""
return Bitmap(image) | 4593506342bfd8b3f1bb3e6077031291a8eb87aa | 3,632,087 |
def load_coco_name(path):
"""Load labels from coco.name
"""
coco = {}
with open(path, 'rt') as file:
for index, label in enumerate(file):
coco[index] = label.strip()
return coco | 2da456b7c2879ec5725172280dacbcaaacd86bfc | 3,632,088 |
def qsat(T, p) :
"""
Saturation vapour pressure.
Derived variable name: qsat
Parameters
----------
T : numpy array or xarray DataArray
Temperature. (K)
p : numpy array or xarray DataArray
Pressure (Pa).
Returns
-------
qs : numpy array or xarray DataArray
... | 2e257dade4531e49f813b3fb96b71f0298819509 | 3,632,089 |
def extract_features(df, action):
"""
提取特征
:param df: DataFrame 样本(训练和测试)
:param action: str action
:return:
x: DataFrame 特征
y: Series 标签
"""
# 特征-训练每个任务都需要初始化
DENSE_FEATURE_COLUMNS = ['videoplayseconds']
# 1,特征处理
# dense
df.fillna(value={f: 0.0 for f in DEN... | af648a66146d1af34777c85417745c55e95f0122 | 3,632,090 |
def quick_sort(input_list):
"""Quick sort."""
if not isinstance(input_list, (list, tuple)):
raise ValueError('input takes list/tuple only')
if isinstance(input_list, (tuple)):
input_list = list(input_list)
if not all(isinstance(val, (int, float)) for val in input_list):
raise V... | 41224487ab352dc88ebd39007a02cf2fe2993651 | 3,632,091 |
from typing import List
def validate_execution_order(relations: List[RelationDescription], keep_going=False):
"""
Make sure we can build an execution order.
We'll catch an exception and set a flag if the keep_going option is true.
"""
try:
ordered_relations = etl.relation.order_by_depende... | 773303496c3a0ac62e195ea62622e4605acb19fc | 3,632,092 |
def now():
"""Returns a java.util.Date object that represents the current time
according to the local system clock.
Returns:
Date: A new date, set to the current date and time.
"""
return Date() | 4d32130ed1af12370012186084b270dde6fdd986 | 3,632,093 |
def create_session_factory(session_id_store, backend_store, *, loop=None):
"""Creates new session factory.
Create new session factory from two storage:
session_id_store and backend_store.
"""
return _SessionFactory(session_id_store=session_id_store,
backend_store=backend_... | c8f302af26894e16f5a24aa9ca460400746fed06 | 3,632,094 |
import os
async def get_mnemonic(strict=False):
"""Attempt to gather a mnemonic from one of the available sources
First, if a mnemonic is defined in the env, use that.
Next, check the config file for the secret
If no mnemonic can be found, optionally raise an Exception
Args:
strict ... | b0056eb251c4426ab252ceb1a628a7ef3e057ab9 | 3,632,095 |
def process(callable_, *args, **kwargs):
"""
Submit a callable to a background process.
Return an proxy object for the future return value.
NOTE: Use only, if you really need control over the type of background execution.
"""
return _submit(callable_, 'cpu', *args, **kwargs) | ac596fef8e72f1ba65450928aba9ea173764d564 | 3,632,096 |
def encode_entities(string):
""" Encodes HTML entities in the given string ("<" => "<").
For example, to display "<em>hello</em>" in a browser,
we need to pass "<em>hello</em>" (otherwise "hello" in italic is displayed).
"""
if isinstance(string, basestring):
string = ... | 949d76b25ff65020b3b560a0fd984107c13d1bfb | 3,632,097 |
import os
def load_node_handle(fname, mode="r"):
"""
Read a conduit file node handle. Does not read into memory.
"""
if os.path.exists(fname):
options = conduit.Node()
options["mode"] = mode
handle = conduit.relay.io.IOHandle()
handle.open(fname, options=options)
... | dce4c6aa262e6ae27ea0804959459dbeb20348eb | 3,632,098 |
async def upload_data_generation_file(
background_tasks: BackgroundTasks,
doc: UploadFile = File(...),
current_user: User = Depends(auth.get_current_user_and_bot)
):
"""
Uploads document for training data generation and triggers event for intent creation
"""
TrainingDataGenerationProcessor.i... | 742f61a13491f2fe84301d3bcd9c5f5ee18e3df0 | 3,632,099 |
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