content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from unittest.mock import Mock
async def test_10_request(requests_mock: Mock) -> None:
"""Test `async request()`."""
result = {"result": "the result"}
rpc = RestClient("http://test", "passkey", timeout=0.1)
def response(req: PreparedRequest, ctx: object) -> bytes: # pylint: disable=W0613
ass... | fa9e03d5b3f5a4f594db29eae057607f790e158c | 3,654,738 |
def entmax15(X, axis=-1, k=None):
"""1.5-entmax: normalizing sparse transform (a la softmax).
Solves the optimization problem:
max_p <x, p> - H_1.5(p) s.t. p >= 0, sum(p) == 1.
where H_1.5(p) is the Tsallis alpha-entropy with alpha=1.5.
Parameters
----------
X : paddle.Tensor
... | 08887ec5aff323077ea6ea99bf6bd2b83bb4cc19 | 3,654,739 |
def get_dependency_graph(node, targets=None):
"""Returns the dependent nodes and the edges for the passed in node.
:param str node: The node to get dependencies for.
:param list targets: A list with the modules that are used as targets.
:return: The dependency graph info.
:rtype: GraphInfo
"""... | 39667e034379477086062a9032f5007c12aba30e | 3,654,740 |
from pathlib import Path
def is_submodule_repo(p: Path) -> bool:
"""
"""
if p.is_file() and '.git/modules' in p.read_text():
return True
return False | 26675ee25e431778325081ec80d45ff3d72c2046 | 3,654,741 |
def shift_contig(df2, remove):
"""
The function append shifted fragment from
sort_cluster_seq function.
Parameters
----------
df2 : pandas DataFrame
DataFrame NRPS cluster fragment.
remove : list
List of cluster fragment, which should removed.
Returns
-------
df... | 7df891785fc58d818af5b423c7fdbc3c4382951f | 3,654,742 |
def _bocs_consistency_mapping(x):
"""
This is for the comparison with BOCS implementation
:param x:
:return:
"""
horizontal_ind = [0, 2, 4, 7, 9, 11, 14, 16, 18, 21, 22, 23]
vertical_ind = sorted([elm for elm in range(24) if elm not in horizontal_ind])
return x[horizontal_ind].reshape((I... | bd8fe5261e024f5d5cdf1a2d77229dd564d947bf | 3,654,744 |
def get_document(name, key):
"""Get document from Database"""
constructor = Constructor()
inst_coll = constructor.factory(kind='Collection', name=name)
inst_doc = Document(inst_coll)
doc = inst_doc.get_document(key)
return doc | acd4e8117c0002d323a4fad79704a33437481657 | 3,654,745 |
from datetime import datetime
import json
def predict() -> str:
"""predict the movie genres based on the request data"""
cur = db_connection.cursor()
try:
input_params = __process_input(request.data)
input_vec = vectorizer.transform(input_params)
prediction = classifier.predict(inp... | 0ae49a8ab05d1df1c0beb07f322262a7a7ac8ee2 | 3,654,746 |
def SignificanceWeights(serializer, decay):
"""Multiplies a binary mask with a symbol significance mask."""
def significance_weights(mask):
# (repr,) -> (batch, length, repr)
# significance = [0, 1, 2]
significance = serializer.significance_map
assert significance.shape[0] == mask.shape[2]
# sig... | 545ac45149b8653f502d2dd864f92a40ee5919cb | 3,654,747 |
def check_fun_inter_allocation(fun_inter, data, **kwargs):
"""Check allocation rules for fun_inter then returns objects if check"""
out = None
check_allocation_fun_inter = get_allocation_object(data, kwargs['xml_fun_inter_list'])
if check_allocation_fun_inter is None:
check_fe = check_fun_elem_d... | 61f17844953f3260a23aff35a2f090a028dd9212 | 3,654,748 |
from typing import Optional
def kernel_bw_lookup(
compute_device: str,
compute_kernel: str,
caching_ratio: Optional[float] = None,
) -> Optional[float]:
"""
Calculates the device bandwidth based on given compute device, compute kernel, and
caching ratio.
Args:
compute_kernel (str)... | efd70d5c2e5fc9295bccbfb05113474ac40ff1c9 | 3,654,749 |
def create_container(
container_image: str,
name: str = None,
volumes: t.List[str] = None,
) -> str:
"""Create a new working container from provided container image.
Args:
container_image (str): The container image to start from.
name (str, optional): The container name.
vol... | be50e84169e5d3df5dfd9730493d7daa9788049b | 3,654,751 |
def single_data_path(client, node_id):
"""
In order for a shrink to work, it should be on a single filesystem, as
shards cannot span filesystems. Return `True` if the node has a single
filesystem, and `False` otherwise.
:arg client: An :class:`elasticsearch.Elasticsearch` client object
:rtype:... | ae0b34f82acb6d12faf525f0270250cdf471a6f8 | 3,654,752 |
def sortorder(obj):
"""
Trys to smartly determine the sort order for this object ``obj``
"""
if hasattr(obj, 'last'):
return obj.last.timestamp()
if isinstance(obj, str):
# First assume pure numeric
try:
return float(obj)
except ValueError:
pa... | 674ee77a87ccd7a0bd89a88b88a2682926a1135e | 3,654,753 |
import json
import re
def get_more_details_of_post(post_url: str) -> json:
"""
:param post_url: the url of an imgur post
:return: Details like Virality-score, username etc in JSON format
"""
details = {}
try:
request = HTMLSession().get(post_url)
# some times, request isn't pr... | dd3d622c8a7e8f61daf24c2d0cc6752323d4693e | 3,654,754 |
import struct
import hmac
import hashlib
def subkey_public_pair_chain_code_pair(public_pair, chain_code_bytes, i):
"""
Yield info for a child node for this node.
public_pair:
base public pair
chain_code:
base chain code
i:
the index for this node.
Returns a pair (new_... | 8f31eb0ae3b063964ff46bcf6c78431d39d0e2ba | 3,654,755 |
from typing import Optional
def get_registry_description(metaprefix: str) -> Optional[str]:
"""Get the description for the registry, if available.
:param metaprefix: The metaprefix of the registry
:return: The description for the registry, if available, otherwise ``None``.
>>> get_registry_descripti... | 12b7aac7f880d6699ca85add1065eca49a06d278 | 3,654,756 |
import tqdm
def evaluate(model, valid_exe, valid_ds, valid_prog, dev_count, metric):
"""evaluate """
acc_loss = 0
acc_top1 = 0
cc = 0
for feed_dict in tqdm.tqdm(
multi_device(valid_ds.generator(), dev_count), desc='evaluating'):
if dev_count > 1:
loss, top1 = valid_... | 7b228e7cadd71ec1ac31436767b92c4dadb5ec53 | 3,654,757 |
def _get_rank(player):
"""Get the rank of a player"""
cursor = _DB.cursor()
try:
cursor.execute("SELECT score FROM scores WHERE player = ?", (player.lower(),))
rows = cursor.fetchall()
if not rows:
return 0
ps = rows[0][0]
cursor.execute("SELECT count(*) F... | e556b9fb75f6b40c8c1be8759255dfc5953a1e9a | 3,654,758 |
import pydoc
def spec(func):
"""return a string with Python function specification"""
doc = pydoc.plain(pydoc.render_doc(func))
return doc.splitlines()[2] | 00b96364f77141fedd7d50396946fd4e29cc5d02 | 3,654,760 |
import posixpath
def IsVirus(mi, log):
"""Test: a virus is any message with an attached executable
I've also noticed the viruses come in as wav and midi attachements
so I trigger on those as well.
This is a very paranoid detector, since someone might send me a
binary for valid reasons. I white-... | e30e91951ad49395d87bef07926cfdff4d15b3e2 | 3,654,763 |
def to_curl(request, compressed=False, verify=True):
"""
Returns string with curl command by provided request object
Parameters
----------
compressed : bool
If `True` then `--compressed` argument will be added to result
"""
parts = [
('curl', None),
('-X', request.me... | b462f62031f4fe757bb7a45b50ced9bc2ea6a9b5 | 3,654,764 |
def prox_trace_indicator(a, lamda):
"""Time-varying latent variable graphical lasso prox."""
es, Q = np.linalg.eigh(a)
xi = np.maximum(es - lamda, 0)
return np.linalg.multi_dot((Q, np.diag(xi), Q.T)) | 85d6cb26c7a35dbab771e0a9f9c8979fba90e680 | 3,654,765 |
def get_gamma_non_jitted(esys):
"""Get log gamma
Returns
-------
float[:]
"""
if isinstance(esys.species[0].logc, float):
v = np.empty(len(esys.species))
else:
v = np.empty(len(esys.species), dtype=object)
for i, sp in enumerate(esys.species):
v[i] = 10.0 ** (sp.... | f3d7f4b96676a10b7065196aac247006019da31e | 3,654,766 |
def active_matrices_from_extrinsic_euler_angles(
basis1, basis2, basis3, e, out=None):
"""Compute active rotation matrices from extrinsic Euler angles.
Parameters
----------
basis1 : int
Basis vector of first rotation. 0 corresponds to x axis, 1 to y axis,
and 2 to z axis.
... | 50218d9ce2296e3c4952cc77fe64e30c19e03f77 | 3,654,767 |
def runQuery(scenarioID):
"""
Run a query that aquires the data from the lrs for one specific dialoguetrainer scenario
\n
:param scenarioID: The id of the scenario to request the data from \t
:type scenarioID: int \n
:returns: The data for that scenario or error \t
:rtype: [Dict<string, mixe... | 0f57a4468354680b315a65263593979149bdb186 | 3,654,769 |
def is_spaceafter_yes(line):
"""
SpaceAfter="Yes" extracted from line
"""
if line[-1] == "_":
return False
for ddd in line[MISC].split("|"):
kkk, vvv = ddd.split("=")
if kkk == "SpaceAfter":
return vvv == "Yes"
raise ValueError | 5693c8874ec9676bf19d9b1cb7ead5c1772a3f0b | 3,654,770 |
def linear_scheduler(optimizer, warmup_steps, training_steps, last_epoch=-1):
"""linear_scheduler with warmup from huggingface"""
def lr_lambda(current_step):
if current_step < warmup_steps:
return float(current_step) / float(max(1, warmup_steps))
return max(
0.0,
... | d9446ede5be0ed981ae00b0bccd494017057d834 | 3,654,771 |
from functools import reduce
import operator
from re import X
def MajorityVoteN(qubits,
nrounds,
prep=[],
meas_delay=1e-6,
add_cals=False,
calRepeats=2):
"""
Majority vote across multiple measurement results (same or dif... | 7bc3b6161d5224ed7adf9248b32b0bd283f50c70 | 3,654,772 |
def getRatios(vect1, vect2):
"""Assumes: vect1 and vect2 are equal length lists of numbers
Returns: a list containing the meaningful values of
vect1[i]/vect2[i]"""
ratios = []
for index in range(len(vect1)):
try:
ratios.append(vect1[index]/vect2[index])
excep... | e28f871986ab2b1b87cc3671b1c27ad14a0aadf8 | 3,654,773 |
def sampleset():
"""Return list with 50 positive and 10 negative samples"""
pos = [(0, i) for i in range(50)]
neg = [(1, i) for i in range(10)]
return pos + neg | 77e5a0ca3ad8757f0ded2aec9d73312a66ac9044 | 3,654,774 |
def recognize_emotion(name, mode, dataset):
"""
The main program for building the system. And we support following kinds of model:
1. Convolutional Neural Network (CNN)
2. Support Vector Machine (SVM)
3. Adaboost
4. Multilayer Perceptron (MLP)
Args:
... | eae092866f5190a637bbdb08c4ad7188b9cb88f3 | 3,654,775 |
def feedback(request):
"""
Feedback page. Here one can send feedback to improve the
website further.
"""
return render(request, "groundfloor/common/feedback.html", context = None) | 8dd9f8ae57ca49629820c58b54c7d98d705597bb | 3,654,776 |
from typing import Tuple
def fill_nodata_image(dataset: xr.Dataset) -> Tuple[np.ndarray, np.ndarray]:
"""
Interpolate no data values in image. If no mask was given, create all valid masks
:param dataset: Dataset image
:type dataset: xarray.Dataset containing :
- im : 2D (row,... | c245f0cbfbb79737fb85b9b8fb8381aad6373926 | 3,654,777 |
def find(value, a_list):
"""
TestCase for find
>>> find(26, [12,14])
True
>>> find(40, [14, 15, 16, 4, 6, 5])
False
>>> find(1, [1])
False
>>> find(1, [])
False
>>> find(4, [2, 3, 2])
True
"""
# 现将列表变为<value, index>字典
if a_list is None or len(a_list) < 2:
... | dd466a8ffa0c760ed0af9ad109b5f4e3b85a62db | 3,654,778 |
def transform_bbox(
bbox, source_epsg_code, target_epsg_code, all_coords=False
):
"""
Transform bbox from source_epsg_code to target_epsg_code,
if necessary
:returns np.array of shape 4 which represent the two coordinates:
left, bottom and right, top.
When `all_coords` is set to... | cd6938b2dfcc02fe9c2a323e2b60339de216dd26 | 3,654,779 |
def distance_metric(vector1, vector2):
""" Returns a score value using Jaccard distance
Args:
vector1 (np.array): first vector with minHash values
vector2 (np.array): second vector with minHash values
Returns:
float: Jaccard similarity
"""
return distance.pdist(np.array([ve... | e1acbc9eff7ee8bc78be0307acacbca9e9d69265 | 3,654,780 |
from datetime import datetime
def update_calendar(request):
"""
to update an entry to the academic calendar to be updated.
@param:
request - contains metadata about the requested page.
@variables:
from_date - The starting date for the academic calendar event.
to_date - The en... | 804f3f0443d192c0c18a501c40808f2406596491 | 3,654,781 |
def get_section(entry: LogEntry) -> str:
"""returns the section of the request (/twiki/bin/edit/Main -> /twiki)"""
section = entry.request.split('/')[:2]
return '/'.join(section) | dee463b5a662846da01fc2ef8d1c72c5b582e7e5 | 3,654,782 |
def reverse_lookup(d, v):
"""
Reverse lookup all corresponding keys of a given value.
Return a lisy containing all the keys.
Raise and exception if the list is empty.
"""
l = []
for k in d:
if d[k] == v:
l.append(k)
if l == []:
raise ValueError
else:
... | d68f437aec47df964905779f99d58be84515fb72 | 3,654,783 |
def compile_channels_table(*, channels_meta, sources, detectors, wavelengths):
"""Compiles a NIRSChannelsTable given the details about the channels, sources,
detectors, and wavelengths.
"""
table = NIRSChannelsTable()
for channel_id, channel in channels_meta.items():
source_label = sources.l... | ac3099ef0440962b3fbfeec36f01ae92061b5693 | 3,654,784 |
from pathlib import Path
def cpe2pkg_tool():
"""Unsupported ecosystem CVE fixture."""
bin = Path(__file__).parent.parent / Path('tools/bin/cpe2pkg.jar')
if bin.exists():
return str(bin)
else:
raise RuntimeError('`cpe2pkg.jar` is not available, please run `make build-cpe2pkg once.`') | 7ad5489cd560f2820a5e77c46964514a5a34edc9 | 3,654,785 |
import threading
def spawn_thread(func, *args, **kwds):
"""
Utility function for creating and starting a daemonic thread.
"""
thr = threading.Thread(target=func, args=args, kwargs=kwds)
thr.setDaemon(True)
thr.start()
return thr | afaace7e02870390acb297106ac9d35c9a931a59 | 3,654,786 |
import uuid
def get_thread_replies(parent_id):
"""
Get all replies to a thread
If the thread does not exist, return an empty list
:param parent_id: Thread ID
:return: replies to thread
"""
assert type(parent_id) is uuid.UUID, """parent_id is not correct type"""
reply_query = Query()
... | 1b167dcc4ab09d50cda9feb478c8f1a4d0399e96 | 3,654,788 |
import torch
def compute_acc(pred, labels):
"""
Compute the accuracy of prediction given the labels.
"""
return (torch.argmax(pred, dim=1) == labels).float().sum() / len(pred) | 1b1ad83b9b4ae06f2bc80209e4e7339a421a39f3 | 3,654,789 |
async def read_update_status() -> str:
"""Read update status."""
return (
await cache.get(Config.update_status_id())
if await cache.exists(Config.update_status_id())
else "ready_to_update"
) | 0e80f7065665dbe1a41e59fe7c65904e58bb6d8f | 3,654,790 |
def PCopy (inFA, err):
"""
Make copy an GPUFArray
returns copy
* inFA = input Python GPUFArray
* err = Python Obit Error/message stack
"""
################################################################
# Checks
if not PIsA(inFA):
print("Actually ",inFA.__class_... | df1047dc143fb5f8d8f4fd88a2b1ebc0904620a2 | 3,654,792 |
def _get_statuses(policy_type_id, policy_instance_id):
"""
shared helper to get statuses for an instance
"""
_instance_is_valid(policy_type_id, policy_instance_id)
prefixes_for_handler = "{0}{1}.{2}.".format(HANDLER_PREFIX, policy_type_id, policy_instance_id)
return list(SDL.find_and_get(A1NS, p... | fdddc26d3c2b65834d4b047a5565894b0d965f9d | 3,654,793 |
def phase_lines(graph):
""" Determines the phase lines of a graph.
:param graph: Graph
:return: dictionary with node id : phase in cut.
"""
if has_cycles(graph):
raise ValueError("a cyclic graph will not have phaselines.")
phases = {n: 0 for n in graph.nodes()}
q = graph.nodes(in_deg... | 9f1aab9e487bd258c88b0f149bcf613341945879 | 3,654,794 |
def BCELossConfig(argument_parser):
"""
Set CLI arguments
:param argument_parser: argument parser
:type argument_parser: ```ArgumentParser```
:returns: argument_parser
:rtype: ```ArgumentParser```
"""
argument_parser.description = """Creates a criterion that measures the Binary Cross E... | d0108459bdad9b2f6fad438bff542624b482ef7d | 3,654,797 |
def gen_cities_avg(climate, multi_cities, years):
"""
Compute the average annual temperature over multiple cities.
Args:
climate: instance of Climate
multi_cities: the names of cities we want to average over (list of str)
years: the range of years of the yearly averaged temperature ... | 9609add6a1514d09b42e2494e56c84522d3cb364 | 3,654,798 |
def tangentVectorsOnSphere( points, northPole = np.array([0.0,0.0,1.0]) ):
"""
Acquire a basis for the tangent space at given points on the surface of the unit sphere.
:param points: N x 3 array of N points at which to acquire basis of tangent space.
:param northPole: 3 array of point correspondin... | bfa23a393ac4d1b38c6c2b19207520db1bd83e03 | 3,654,799 |
import tkinter
def _colorvar_patch_destroy(fn):
"""Internal function.\n
Deletes the traces if any when widget is destroy."""
def _patch(self):
"""Interanl function."""
if self._tclCommands is not None:
# Deletes the widget from the _all_traces_colorvar
# and delete... | d38380316932d8ff2fee8bed8b931b5567588774 | 3,654,800 |
def pres_from_hybrid(psfc, hya, hyb, p0=100000.):
"""Return pressure field on hybrid-sigma coordinates,
assuming formula is
p = a(k)*p0 + b(k)*ps.
"""
return hya*p0 + hyb*psfc | 4ebd90fb807ab9ea4c2b45d27da6f8b420c107f7 | 3,654,802 |
import urllib
def url_exist(file_url):
""" Check if an url exist
Parameters
----------
file_url : string
url of www location
Returns
-------
verdict : dtype=boolean
verdict if present
"""
try:
urllib.request.urlopen(file_url).code == 200
retu... | 717ee7073ab56e8611eb46f042ab7c18f2db0f33 | 3,654,803 |
from scipy import stats
def chi_square(observed, expected):
"""
Compute the chi square test
"""
# glen cowan pp61
temp = []
for (n, nu) in zip(observed, expected):
if nu != 0:
temp += [((n - nu) ** 2) / nu]
# compute p value
mychi = sum(temp)
p = stats.chi2.sf(... | 4b0577ec4e4b4dc6b99b00a54e78f1014b9cf93a | 3,654,804 |
def theta_8(p, q, h, phi, a, b):
"""Lower limit of integration for the case rho > a, rho > b."""
result = np.arctan(r_8(p, q, phi, a, b)/h)
return(result) | 913ceb462885fba93cbdb6bddaa5523c119821bc | 3,654,806 |
def collect_genewise(fst_file, file_name, gene_names, gene_to_fst):
"""take in the file name, opens it.
populates a dictionary to [gene] = fst
file_name = defaultdict(str)
FBgn0031208 500000 16 0.002 21.0 1:2=0.05752690
"""
file_name = file_name.split("_gene")[0]
f_in = open(fst_file, "r")
... | ea62da67a7084103859244bf7f192c2f4433124c | 3,654,807 |
import torch
def bbox_overlaps_batch(anchors, gt_boxes):
"""
:param anchors: (N, 4) ndarray of float
:param gt_boxes: (b, K, 5) ndarray of float
:return: (N, K) ndarray of overlap between boxes and query_boxes
"""
batch_size = gt_boxes.size(0)
if anchors.dim() == 2:
N = anchors... | cc5a88e6a1d5cd42b1827091cbee311e4f33bbb6 | 3,654,808 |
from typing import Tuple
from typing import Callable
from typing import Any
import re
def extract_curve_and_test(curve_names: str, name: str) -> Tuple[str, Callable[[Any], bool]]:
"""Return a curve and a test to apply for which of it's components to twist."""
twist_match = re.match(rf"(?P<curve>[{curve_names... | e4849ff7145bae0c2c900d0aa747ec7a14fb96ac | 3,654,809 |
import numpy
def psf_gaussian(psf_shape, psf_waist, psf_physical_size=1, psf_nphoton=2):
"""Return 3D gaussian approximation of PSF."""
def f(index):
s = psf_shape[index] // 2 * psf_physical_size
c = numpy.linspace(-s, s, psf_shape[index])
c *= c
c *= -2.0 / (psf_waist[index] ... | 77ccab6aaa141564751a0eafd13398f904673006 | 3,654,810 |
def get_employee_record(id_num):
"""Gets an employee's details if record exists.
Arguments:
id_num -- ID of employee record to fetch
"""
if not id_num in names or not id_num in cities:
return 'Error viewing record'
return f'{id_num} {names[id_num]} {cities[id_num]}' | 108b6e3482022e8e65e09bda1dd8a78ca7850cfe | 3,654,811 |
def list_aliases():
"""
Gets the list of aliases for the current account. An account has at most one alias.
:return: The list of aliases for the account.
"""
try:
response = iam.meta.client.list_account_aliases()
aliases = response['AccountAliases']
if len(aliases) > 0:
... | 13fa5d4ded6811bbcbd6062cf7f690b08c41354e | 3,654,812 |
def MapToSingleIncrease(val):
"""
Need 30 minute values to be sequential for some of the tools(i.e. 1,2,3,4) so using a format
like 5,10,15,20 won't work.
"""
return val/5 | fe89d7ccb8bef511e2ad90a07ad0346c58ba894d | 3,654,813 |
def get_columns_for_table(instance, db, table):
""" Get a list of columns in a table
Args:
instance - a hostAddr object
db - a string which contains a name of a db
table - the name of the table to fetch columns
Returns
A list of columns
"""
conn = connect_mysql(instance)
cursor... | 567a7e3e6ebbf33cee3cb088e1725bd2b11edcef | 3,654,814 |
def registra_aluno(nome, ano_entrada, ano_nascimento, **misc):
"""Cria a entrada do registro de um aluno."""
registro = {'nome': nome,
'ano_entrada': ano_entrada,
'ano_nascimento': ano_nascimento}
for key in misc:
registro[key] = misc[key]
return registro | e56da99ec90de9ebca204ccc3c3f3555b9bbbc64 | 3,654,815 |
def create_small_table(small_dict):
"""
Create a small table using the keys of small_dict as headers. This is only
suitable for small dictionaries.
Args:
small_dict (dict): a result dictionary of only a few items.
Returns:
str: the table as a string.
"""
keys, values = tuple... | 08da78580fbf4cee8c30acb21ce7fa928a9c17b1 | 3,654,818 |
def get_normalized_list_for_every_month(variable_r, list_of_ranges_r, tags_r):
"""
:param variable_r: big list with all the data [sizes][months]
:param list_of_ranges_r: sorted list of range (sizes...Enormous, etc.)
:return: normalized list for each month (numbers are percentage respect to the total by... | 4a3b837e6bf254dbd3255a8ca0a5d103d34bd2a9 | 3,654,819 |
def mark_as_possible_cluster_member(g, possible_cluster_member, cluster, confidence, system, uri_ref=None):
"""
Mark an entity or event as a possible member of a cluster.
:param rdflib.graph.Graph g: The underlying RDF model
:param rdflib.term.URIRef possible_cluster_member: The entity or event to mark... | 851da7d12781723c7c2fb4bc13ac14172c890daf | 3,654,820 |
def twodcontourplot(tadata_nm, tadata_timedelay, tadata_z_corr):
"""
make contour plot
Args:
tadata_nm: wavelength array
tadata_timedelay: time delay array
tadata_z_corr: matrix of z values
"""
timedelayi, nmi = np.meshgrid(tadata_timedelay, tadata_nm)
# find the maxi... | 2e8850e1c8153c9c307ff785ddd1d1d127163190 | 3,654,821 |
def make_example_dags(module_path):
"""Loads DAGs from a module for test."""
dagbag = DagBag(module_path)
return dagbag.dags | ffc2fd47bbee7d2124da199d6b5101103500fbf2 | 3,654,822 |
def count_good_deals(df):
"""
7. Считает число прибыльных сделок
:param df: - датафрейм с колонкой '<DEAL_RESULT>'
:return: - число прибыльных сделок
"""
# http://stackoverflow.com/questions/27140860/count-occurrences-of-number-by-column-in-pandas-data-frame?rq=1
return (df['<DEAL_RESULT... | 1f3ef9b9e0f7924d45d5ce84a77938f19386b6bc | 3,654,823 |
import time
import itertools
import sh
def match_lines_by_hausdorff(target_features, match_features, distance_tolerance,
azimuth_tolerance=None, length_tolerance=0, match_features_sindex=None, match_fields=False,
match_stats=False, field_suffixes=('', '_match'), match_strings=None, constrain_target_features... | d9c08e8e156a525495a03e5e9d6881c33ecdf0a2 | 3,654,824 |
def create_anchors_3d_stride(grid_size,
voxel_size=[0.16, 0.16, 0.5],
coordinates_offsets=[0, -19.84, -2.5],
dtype=np.float32):
"""
Args:
feature_size: list [D, H, W](zyx)
sizes: [N, 3] list of list or array,... | 129e54a855bbacb2026eb08b5741ab70dd0374f4 | 3,654,828 |
def combined_roidb(imdb_names):
"""
Combine multiple roidbs
"""
def get_roidb(imdb_name):
imdb = get_imdb(imdb_name)
print('Loaded dataset `{:s}` for training'.format(imdb.name))
imdb.set_proposal_method("gt")
print('Set proposal method: {:s}'.format("gt"))
roidb... | 4660a6ffff11511c449629c9fdb7f5d566a886f9 | 3,654,829 |
from re import A
def render_locations_profile(list_id, item_id, resource, rfields, record):
"""
Custom dataList item renderer for Locations on the Profile Page
- UNUSED
@param list_id: the HTML ID of the list
@param item_id: the HTML ID of the item
@param resource: the S3R... | dbec0b41b16fa48996a735372bfb001b386c7300 | 3,654,830 |
def exception_log_and_respond(exception, logger, message, status_code):
"""Log an error and send jsonified respond."""
logger.error(message, exc_info=True)
return make_response(
message,
status_code,
dict(exception_type=type(exception).__name__, exception_message=str(exception)),
... | c784efd4b8adbbc463ff1d2a499ffd598253349d | 3,654,832 |
import re
def parse_cdhit_clusters(cluster_file):
"""
Parses cdhit output into three collections in a named tuple:
clusters: list of lists of gene ids.
reps: list of representative gene for each cluster
lookup: dict mapping from gene names to cluster index
In this setup, cluster ids are... | fe0634c1991f0bd687f8be675ff15cb3290c919c | 3,654,833 |
import torch
def evaluate(model: nn.Module, dataloader: DataLoader) -> Scores:
"""
Evaluate a model without gradient calculation
:param model: instance of a model
:param dataloader: dataloader to evaluate the model on
:return: tuple of (accuracy, loss) values
"""
score = 0
loss = 0
... | f23fbd72a24122b3a665f29918c52bbd5515d204 | 3,654,834 |
from operator import and_
def remote_judge_get_problem_info(problem_id: str, contest_id: int = -1, contest_problem_id: int = -1):
"""
{
"code":0,
"data":{
"isContest":"是否在比赛中",
"problemData":{
"title":"题目名",
"content":"题目内容",
... | aa7f8100bc7516659cf535e0fa7222b6f7b1a065 | 3,654,835 |
def can_write(obj, user):
"""
Takes article or related to article model.
Check if user can write article.
"""
return obj.can_write(user) | 9cb7cc046b63fb82670c4667abe169d6a1a279e4 | 3,654,836 |
def create_external_question(url: str, height: int) -> str:
"""Create XML for an MTurk ExternalQuestion."""
return unparse({
'ExternalQuestion': {
'@xmlns': 'http://mechanicalturk.amazonaws.com/AWSMechanicalTurkDataSchemas/2006-07-14/ExternalQuestion.xsd',
'ExternalURL': url,
... | d249e82225ab2c1546bd871c166e9b683622a15d | 3,654,837 |
def credentials_batch_account_key_secret_id(config):
# type: (dict) -> str
"""Get Batch account key KeyVault Secret Id
:param dict config: configuration object
:rtype: str
:return: keyvault secret id
"""
try:
secid = config[
'credentials']['batch']['account_key_keyvault_s... | 4e7cfb100c2d50ef13d47295ff0b5bb0e3351986 | 3,654,838 |
import re
def is_C2D(lname):
"""
"""
pattns = ['Conv2D']
return any([bool(re.match(t,lname)) for t in pattns]) | a12bfd9857543e568148659f782615b3f2de4b83 | 3,654,839 |
def encounter_media(instance, filename):
"""Return an upload file path for an encounter media attachment."""
if not instance.encounter.id:
instance.encounter.save()
return 'encounter/{0}/{1}'.format(instance.encounter.source_id, filename) | 79e4d8fae1d41edf362e99e6da11442a71565aa0 | 3,654,840 |
from datetime import datetime
def time_range_cutter_at_time(local,time_range,time_cut=(0,0,0)):
""" Given a range, return a list of DateTimes that match the time_cut
between start and end.
:param local: if False [default] use UTC datetime. If True use localtz
:param time_range: the TimeRa... | 57e851fb5b6ae8873dde5719dec668c25561f687 | 3,654,842 |
def _darknet_conv(
x: np.ndarray, filters: int, size: int, strides: int = 1, batch_norm: bool = True
) -> tf.Tensor:
"""create 1 layer with [padding], conv2d, [bn and relu]"""
if strides == 1:
padding = "same"
else:
x = ZeroPadding2D(((1, 0), (1, 0)))(x) # top left half-padding
... | f58153aa0c8af8df93289b872309f1c907941848 | 3,654,843 |
def _build_topic_to_consumer_topic_state_map(watermarks):
"""Builds a topic_to_consumer_topic_state_map from a kafka
get_topics_watermarks response"""
return {
topic: ConsumerTopicState({
partition: int((marks.highmark + marks.lowmark) / 2)
for partition, marks in watermarks_... | 78ef0710e4823031ad079313484dba0eacc37135 | 3,654,844 |
from typing import Optional
def elgamal_keypair_from_secret(a: ElementModQ) -> Optional[ElGamalKeyPair]:
"""
Given an ElGamal secret key (typically, a random number in [2,Q)), returns
an ElGamal keypair, consisting of the given secret key a and public key g^a.
"""
secret_key_int = a
if secret_... | 35de350b6bb434e1bb3d2c52d90f9a96be72dc1f | 3,654,845 |
def current_default_thread_limiter():
"""Get the default `~trio.CapacityLimiter` used by
`trio.to_thread.run_sync`.
The most common reason to call this would be if you want to modify its
:attr:`~trio.CapacityLimiter.total_tokens` attribute.
"""
try:
limiter = _limiter_local.get()
e... | 7abec5d74b9cfdaa663fd432587ea19440b7132f | 3,654,846 |
import copy
def _mask_board(board):
"""
A function that copies the inputted board replaces all ships with empty coordinates to mask them.
:param board: a 2D numpy array containing a string representation of the board. All ships should be visible.
:return: a 2D numpy array containing a string represent... | c6832c90ac96d61563e37482773abf627d92a05a | 3,654,847 |
def remove_head_id(ref, hyp):
"""Assumes that the ID is the begin token of the string which is common
in Kaldi but not in Sphinx."""
ref_id = ref[0]
hyp_id = hyp[0]
if ref_id != hyp_id:
print('Reference and hypothesis IDs do not match! '
'ref="{}" hyp="{}"\n'
'Fil... | 210798e8a02f555f70a1d9f2de9ce098dd0669fb | 3,654,849 |
def convert_image_np(inp):
"""Convert a Tensor to numpy image."""
inp = inp.numpy().transpose((1, 2, 0))
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
inp = std * inp + mean
inp = np.clip(inp, 0, 1)
return inp | 446feda40cc6698b5cbc80c3b14fa3212ef2800b | 3,654,850 |
def get_miner_day_list():
"""
存储提供者每天的miner数据
:return:
"""
miner_no = request.form.get("miner_no")
date = request.form.get("date")
data = MinerService.get_miner_day_list(miner_no, date)
return response_json(data) | 4fd523e8855ba498a1d694e532d27c863e7f9407 | 3,654,851 |
def get_notebook_logs(experiment_id, operator_id):
"""
Get logs from a Experiment notebook.
Parameters
----------
experiment_id : str
operator_id : str
Returns
-------
dict or None
Operator's notebook logs. Or None when the notebook file is not found.
"""
notebook =... | d98865cdbca25839bb6010ab5e726fd35d162ada | 3,654,852 |
from typing import Callable
def modify_env2(
function: Callable[[_UpdatedType], _SecondType],
) -> Kinded[Callable[
[Kind2[_Reader2Kind, _FirstType, _SecondType]],
Kind2[_Reader2Kind, _FirstType, _UpdatedType],
]]:
"""
Modifies the second type argument of a ``ReaderBased2``.
In other words, i... | 5ed2c5deaaa376e4884f31e3ba08d3b2839cc1a5 | 3,654,853 |
def model_trees(z, quantiles, normed=False,
dbhfile='c:\\projects\\MLM_Hyde\\Data\\hyde_runkolukusarjat.txt',
plot=False,
biomass_function='marklund'):
"""
reads runkolukusarjat from Hyde and creates lad-profiles for pine, spruce and decid.
Args:
z - g... | ba3c1ea345031a8b5434e1dd4f005b1c2c1e74ce | 3,654,854 |
def inject_general_timeline():
"""This function injects the function object 'Tweet.get_general_timeline'
into the application context so that 'get_general_timeline' can be accessed
in Jinja2 templates.
"""
return dict(get_general_timeline=Tweet.get_general_timeline) | 56b395da0facda561061c8f63eb3eb26c07f3605 | 3,654,855 |
def get_vaccinated_model(model, area=None):
"""Get all states that can be vaccinated or recovered (by area).
Parameters
----------
model : amici.model
Amici model which should be evaluated.
areas : list
List of area names as strings.
Returns
-------
states : list
... | c03a9d048abb08561463b1975ffec663f24267b3 | 3,654,857 |
from datetime import datetime
def MicrosecondsToDatetime(microseconds):
"""Returns a datetime given the number of microseconds, or None."""
if microseconds:
return datetime.utcfromtimestamp(float(microseconds) / 1000000)
return None | 69fd3dc3b8d1a97e7a64037cabe988365b2c6e63 | 3,654,858 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.