content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def create_covg_table(fname, table_data):
"""Add average CpG depth table to document."""
samps = sorted(
list(constants.SAMPLE_NAMES.keys()),
key=lambda d: constants.INTERLEAVE_ORDER[d],
reverse=False
)
data = format_covg_data(table_data)
with open(fname, 'a') as f:
... | 489559cd80fa8b2c731e9d49a26d693f345b92d9 | 69,128 |
def perform_plot(strain1, strain2, txtome):
"""
Plot the STP between two strains.
Params:
-------
strain1, strain2: str
Strains to plot
txtome: txtome
A transcriptome object that contains the data to plot.
Output:
-------
... | 90278169196d3ffadfa8aa2b837587c243612626 | 69,129 |
def _cosine_similarity(x, y, eps):
"""cosine similarity between two tensors"""
dotxy = jnp.sum(x * y, axis=1)
normx = jnp.linalg.norm(x, axis=1)
normy = jnp.linalg.norm(y, axis=1)
return jnp.abs(dotxy) / jnp.maximum(eps, normx * normy) | 12b93561df009c8320daaed42aff409ca646acd5 | 69,130 |
def build_df_per_id(trajectories):
"""Build one dataframe per id
Arguments:
trajectories: Dict mapping each id to a list of tuple (x,y,frame)
Returns:
df_per_id: dict mapping each id to a dataframe with its trajectory
Raises:
"""
df_per_id = {}
full_trajectories = add_nan_tra... | c27534b6a8b6b8e7a81015bc42cbc0279346f820 | 69,133 |
def int64_feature(values):
"""Returns a TF-Feature of int64s.
Args:
values: A scalar or list of values.
Returns:
A TF-Feature.
"""
if not isinstance(values, (tuple, list)):
values = [values]
return tf.train.Feature(int64_list=tf.train.Int64List(value=values)) | 01378bf614f3d289f2511c755f505bbaa8a99f1c | 69,134 |
def mul(mean1, var1, mean2, var2):
"""
Multiply Gaussian (mean1, var1) with (mean2, var2) and return the
results as a tuple (mean, var).
Strictly speaking the product of two Gaussian PDFs is a Gaussian
function, not Gaussian PDF. It is, however, proportional to a Gaussian
PDF, so it is safe to ... | 71844426a2b9f1d7466d85d8c6c1d2037626c7f5 | 69,135 |
def load_item(item_id: int):
"""
Load an item from item_template, convert it to a object of Class Item and return it
"""
if item_id <= 0 or not isinstance(item_id, int):
raise Exception("There is no such item with an ID that's 0 or negative!")
item_template_info: ItemTemplateSchema = sessio... | 0d31e007cf3bfed7f98c480bdef778350e461087 | 69,136 |
def revokeCloseBankAccount(request):
"""
정액제 해지신청을 취소합니다.
"""
try:
# 팝빌회원 사업자번호
CorpNum = settings.testCorpNum
# 팝빌회원 아이디
UserID = settings.testUserID
# [필수] 기관코드
# 산업은행-0002 / 기업은행-0003 / 국민은행-0004 /수협은행-0007 / 농협은행-0011 / 우리은행-0020
# SC은행-0023 ... | fb7cbdf564a3705776a9d81dc4b39a5ff2a8619e | 69,137 |
def download_post(client: Instaloader, post: Post) -> bool:
""" Downloads content and returns True """
client.download_post(post, post.owner_username)
return True | a3bfc7dd6344e2d31266ee2f113f245984c0dd5d | 69,138 |
def json_dumper(obj):
"""
Dumps generic objects to JSON. Useful to serialize ENV_CONFIG.
"""
# extra hacky, but works
try:
return obj.toJSON()
except:
try:
return obj.__dict__
except:
return str(obj) | 31d7ddcebb16bf437a18aa5584383f7ca5c83aed | 69,139 |
from typing import Counter
def apply_rules(
candidates: "list[Commit]",
advisory_record: AdvisoryRecord,
active_rules=["ALL"],
) -> "list[Commit]":
"""
This applies a set of hand-crafted rules and returns a dict in the following form:
commits_ruled[candidate] = ["explanation"]
where 'exp... | 2b11cbda939bfeab4b904b20c7d830f0e0f0d949 | 69,140 |
def get_paired_bams(align_bams, items):
"""Split aligned bams into tumor / normal pairs if this is a paired analysis.
Allows cases with only tumor BAMs to handle callers that can work without
normal BAMs or with normal VCF panels.
"""
tumor_bam, tumor_name, normal_bam, normal_name, normal_panel, tum... | 434d6c951d3e29d02d1bb1b0b594f7002e465775 | 69,141 |
def macroexpand(tree, module_name):
"""Expand the toplevel macros for the `tree`.
Load the macros from the given `module_name`, then expand the (top-level)
macros in `tree` until it stops changing.
"""
load_macros(module_name)
old = None
while old != tree:
old = tree
tree =... | e9954ddb5df6298532bdfd2861d20d43e24a4bbc | 69,142 |
def create_dimensions():
"""
This Function that will create all the dimensions for stroopwafel, a dimension is basically one of the variables you want to sample
Invoke the Dimension class to create objects for each variable. Look at the Dimension class definition in classes.py for more.
It takes the nam... | b7ad49793b1251489c8c066f8bc1b316343411b5 | 69,144 |
from typing import Tuple
from typing import Optional
def parse_trailing_comment(line: str) -> Tuple[str, Optional[str]]:
"""Split the line and return the extracted trailing comment."""
chunks = REGEX_QUOTE.split(line)
result = ""
while chunks:
text, *comment = REGEX_COMMENT.split(chunks.pop(0... | 339cc320d9242bcc2e0a0d929d51083059570716 | 69,145 |
from typing import List
import re
def get_dic(data)->List[float]:
""" """
new_data = [0,0,0,0]
for key, item in data.items():
if re.match(r"\b(elevation)\b", str(key), re.IGNORECASE):
new_data[0] = item.value
elif re.match(r"\b(thickness)\b", str(key), re.IGNORECASE):
... | 8d8adab78e739e364b7726f78a49403f5c9ae34a | 69,146 |
def make_header(in_files,args):
"""Make sam header given input file species and"""
#parse input barcode file and make list of individuals
in_files['header'] = 'location of header'
return in_files | 8a4a222391a462d0d6187080ed2eccc631526513 | 69,147 |
def accuracy(actual_y: list, predicted_y: list) -> float:
"""
Calculate the value of accuracy based-on predictions
:param actual_y:a list containing initial Y values generated by 'y_generator'
function
:param predicted_y: a list containing predicted Y values generated by
'predict_y_value... | 7082d0e5505fc58e9ba80883b63bec98f4632676 | 69,148 |
def send_messages(queue, messages):
"""
Send a batch of messages in a single request to an SQS queue.
This request may return overall success even when some messages were not sent.
The caller must inspect the Successful and Failed lists in the response and
resend any failed messages.
Usage is s... | 806bd30fb5efc9fef226ddb6c2d46ffe33402cbb | 69,149 |
def get_graph(network_data, vocab):
""" Build graph, treat all nodes as the same type
Parameters
----------
network_data: a dict
keys describing the edge types, values representing edges
vocab: a dict
mapping node IDs to node indices
Output
------
DGLHeteroGraph
... | b3bb88a8d7d3b3d102a38fec41bb57d3e9d45e73 | 69,150 |
def dict2columns(data, id_col=None):
"""Convert a dict-based object to two-column output.
Also make sure the id field is at top.
"""
if not data:
return ({}, {})
else:
if id_col is not None and id_col in data:
keys = [id_col]
[keys.append(key) for key in sort... | 24917339d53febc4239e21ebb8b39e487f45a370 | 69,151 |
def insertTimer (signal, type):
"""
- param signal a plugged input signal.
- return an Timer entity.
"""
assert signal.isPlugged()
Timer = getTimerType (type)
timer = Timer ("timer_of_" + signal.name)
other = signal.getPlugged()
plug(other, timer.sin)
plug(timer.sout, signal)
... | 3f1671647ac7842fd32e0b1b107069371f4e4cdd | 69,152 |
def resolve_int_list_arg(arg):
"""Resolve a CLI argument as a list of integers"""
if arg is None:
return None
if isinstance(arg, int):
return [arg]
if isinstance(arg, str):
return [int(arg)]
if isinstance(arg, tuple):
# Interpret as range (ignore any other items in tu... | 5201d191946c69e10253e476341ab70c76b3a67d | 69,153 |
def divide_by_two(a):
"""Return a / 2.
"""
return a / 2.0 | f7c71a468f91892d327d7e9745934f6f4760deeb | 69,155 |
import csv
def read_ensembl_genes(fpath, source, name):
"""
:param fpath:
:param source: content of ensemblSource file; contains transcript type info, e.g., protein coding
:param name: content of ensemblToGeneName file; contains gene symbol/name info
:return:
"""
fieldnames = ['bin', 'name... | 820bbb02dec86da382137ad7eddb52ee596a02a6 | 69,156 |
def SystemYChanged():
"""(read-only) Flag that indicates if elements of the System Y have been changed by recent activity."""
return lib.Solution_Get_SystemYChanged() != 0 | 04195262f03ef6df39caf4f56c95fb117f0e279f | 69,157 |
def groupwise_normalise(gs):
"""
Normalises each group of GeoSeries
:param gs: GeoSeries
:return: normalised GeoSeries
"""
return gs.groupby(level=0).apply(lambda x: x / x.sum()) | e0c87701658481ccea01828c75244b7a1043ee29 | 69,158 |
def dnn_batch_normalization_train(inputs, gamma, beta, mode='per-activation',
epsilon=1e-4, running_average_factor=0.1,
running_mean=None, running_var=None):
"""
Performs batch normalization of the given inputs, using the mean and
variance ... | 853f5a2c130ff4aa6b319b40a456817d982a2332 | 69,159 |
from typing import Dict
def component_io_to_rest_obj(io_dict: Dict):
"""Component inputs/outputs entity to rest object."""
rest_component_io = {}
for name, port in io_dict.items():
rest_component_io[name] = port._to_rest_object()
return rest_component_io | 03c3b5fc0033c3488a1190db89e8361483fc765d | 69,161 |
def delta(net: ann.NeuralNetwork,
sample: Sample,
error_function_deriv: List[Mapping[Tuple(Sample,
ann.NeuralNetwork
),
float]
... | 3f8b411750f7b3266eaaef814e21eaba36cf68ec | 69,162 |
def PolynomialJac(mu, *u):
"""The derivative matrix of the polynomial model."""
jac = -np.array([(1 - mu) ** (l + 1) for l in range(len(u))]).transpose()
return jac | 495dd55004b8014ef7ee2499ba79188eaee48707 | 69,163 |
import struct
def b58decode(v, length=None):
""" decode v into a string of len bytes."""
if isinstance(v, bytes):
v = v.decode()
for c in v:
if c not in __b58chars:
raise ValueError("invalid Base58 string")
long_value = 0
for (i, c) in enumerate(v[::-1]):
long... | 496b70440346b4545371b9293ff50e7c1e05300d | 69,164 |
def transformRemoveXmlTagsC14NId():
"""
The 'remove xml tags' transform id (used before base64 transforms)
(http://www.w3.org/TR/xmldsig-core/sec-Base-64).
Returns : 'remove xml tags' transform id.
"""
return TransformId(_obj=xmlsecmod.transformRemoveXmlTagsC14NId()) | 856dd18d4e04e3b9e94d911a02f564b3561dccf1 | 69,165 |
def correlation(season, metric, n, connection, generalize=False, traditional=False,
mixed=False, playoffs=False, multiple=False, partitioned=False,
evaluation_start=None, evaluation_end=None):
"""
Calculate the correlation coefficients (Pearson/Spearman) for a specific
numbe... | ca31974b6ec8e78b300afe0bf58931b358b01f18 | 69,166 |
def generate_wrapper(config):
"""
Generates a wrapper script for the format.
:param config: The configuration for the format
"""
return "#!/bin/sh\n%s" % config['interpreter'] | 694ecb3369de8ab4af4c57418c732d39ed57aceb | 69,168 |
import itertools
def string_between(left, right, subject, *args, **kwargs):
"""
string_between(left, right, subject, [,start [,end]] [,greedy=False] [,inclusive=False] [,repl=None] [,retn_all_on_fail=False] [,retn_class=False] [,rightmost=False]) -> str
Return the substring sub delineated by being betwe... | 8f80f15b27fe8dfde0afcbb6aa85d55250fd13ae | 69,169 |
def logout(request):
"""
Return logout page
"""
django_logout(request)
print("Logging out")
return redirect('/') | 923ded3599a435d9a782afdbf43d66f4b4b44a02 | 69,170 |
def tgram_to_bundles(tgram, bundle_dict, reference):
"""
Convert a StatefulTractogram object to a dict with StatefulTractogram
objects for each bundle.
Parameters
----------
tgram : StatefulTractogram class instance.
Requires a data_per_streamline['bundle'][bundle_name]['uid'] attribute... | 9d9595a90a6103641e2acfe551c8d95f001bf5d6 | 69,171 |
def params_to_dict(params):
"""
Converts the parameters of a mwparserfromhell template to a dictionary
"""
dct = {}
for param in params:
dct[param.name.strip()] = param.value.strip()
return dct | 0799a22627b1f09e684d2b506f69eabcc942ec2f | 69,172 |
import fastapi
async def delete_feed(
*,
db: sa.orm.Session = params.Depends(deps.get_db),
id: int,
):
"""
Delete RSS feed.
"""
obj = crud.rss_feed.get(db, id=id)
if obj is None:
raise fastapi.HTTPException(404, detail="RSS Feed not found")
return crud.rss_feed.remove(db, i... | b893b3d48db0476e1ac2f8c0c04a7705027cf2e2 | 69,173 |
def filter_definition_names(names, origin, position=None):
"""
Filter names that are actual definitions in a scope. Names that are just
used will be ignored.
"""
# Just calculate the scope from the first
stmt = names[0].get_definition()
scope = stmt.get_parent_scope()
if not (isinstance... | 14ef64d3df898e1b64890c54252d64079e2b478e | 69,174 |
def new_deconstruct(self):
"""Patches makemigration's logic to ignore fields that are not of relevance to our database.
This avoids unnecessary, annoying migrations whenever a frontend facing string is changed."""
name, path, args, kwargs = original_deconstruct(self)
for attr in IGNORED_ATTRS:
... | 71965fe02b032f31574f42787c8a5f6398540945 | 69,175 |
def render_network_key(ssid, address):
"""ssid:address"""
return ssid + ':' + address | daf47616c455c3b542688293195f45607fb8b7ea | 69,176 |
from typing import Callable
def percentage_income_contributions(
income: float,
contribution_rate: float,
income_growth: float = 0.0,
tax_function: Callable[[float], float] = (lambda x: 0),
) -> Callable[[int], float]:
"""
Creates a function that returns a contribution based on a percentage of... | a122d7d4afa95f3be799e0913ddd127e761fe6ca | 69,177 |
import math
def scattering_filter_factory(N, J_support, J_scattering, Q, T,
r_psi=math.sqrt(0.5), criterion_amplitude=1e-3,
normalize='l1', max_subsampling=None, sigma0=0.1,
alpha=4., P_max=5, eps=1e-7, **kwargs):
"""
Bu... | cbf0c3533037822f24a42c2e27f31263e94dfe72 | 69,178 |
def get_response(zone_key, url, session=None):
"""Get response"""
ses = session or Session()
response = ses.get(url)
if response.status_code != 200:
raise ParserException(zone_key, 'Response code: {0}'.format(response.status_code))
return response | d44b2f9e78e37acd0ed17b0864e8f989e57d0171 | 69,180 |
def make_one_shot_iterator(dataset):
"""Returns a dataset's one-shot iterator."""
try:
return v1.data.make_one_shot_iterator(dataset)
except AttributeError:
return dataset.make_one_shot_iterator() | b1d55a21af7f031a2f4f09b4fcdca38167dd0add | 69,181 |
def checkPossibility(nums):
"""
:param nums:
:return:
"""
modified = False
size = len(nums)
for i in range(len(nums)-1):
if nums[i] > nums[i + 1]:
if modified:
return False
"""
i-1 i i+1
1 2 3 ... | 83b5205ad3009b09d6f90a69c1e4a702cc17b6d0 | 69,182 |
from typing import Iterable
from typing import Any
from typing import List
def serialize_list(items: Iterable[Any]) -> List[Any]:
"""Serializes UFP data list"""
new_items: List[Any] = []
for item in items:
new_items.append(serialize_unifi_obj(item))
return new_items | ea24ffca17d7475938cf0400e68a890b4e6bcf4b | 69,183 |
def generic_scalar_product(b1, b2=None, scalar_product=None):
"""
Calculates the pairwise scalar product between the elements
of the :py:class:`.ApproximationBase` *b1* and *b2*.
Args:
b1 (:py:class:`.ApproximationBase`): first basis
b2 (:py:class:`.ApproximationBase`): second basis, if... | 40b9ba0cd785959090f1d70fca489afcfcd6dcde | 69,184 |
def rename(src, dst):
""" Calls gfs_rename."""
p0 = abst_path(src)
s0 = str(p0).encode(name_coding)
p1 = abst_path(dst)
s1 = str(p1).encode(name_coding)
cc = _gfs_rename(s0, s1)
return cc | dd9f04573dbffb17cf8cbf952d2c85b54145b7ea | 69,186 |
def feature_extraction(df, df1, n):
"""The function performs feature extraction on the information from xyz files
Requirements:
numpy
Args:
df (pandas dataframe): Data table with spatial distribution and atom info
df1 (pandas dataframe): Data table with lattice vectors (o... | ef13a079ca454d65603b3544500638e3063b67ab | 69,187 |
def locality_sensitive_hashing(min_hash, b):
"""Locality sensitive hash to find identical pair
:param min_hash: signature matrix
:param b: number of bands to split signature matrix
:return: candidate pairs for each band
"""
all_rdd = [] # Empty list to store all rd... | cacee5c2023fd3d663c69ac0efa7546f13f355b1 | 69,188 |
def false_negative_rate(pred, target):
"""
正样本中被误判为负样本的比例，1 - recall/true_positive_rate
"""
try:
return false_negative(pred, target) / (target == 1).sum().item()
except: # divide by zero
return -1 | f02e77423a9448163fd5e12500a2a651e0084ce5 | 69,189 |
def fateman_poly_F_1(n):
"""Fateman's GCD benchmark: trivial GCD """
Y = [Symbol("y_" + str(i)) for i in range(n + 1)]
y_0, y_1 = Y[0], Y[1]
u = y_0 + Add(*[y for y in Y[1:]])
v = y_0 ** 2 + Add(*[y ** 2 for y in Y[1:]])
F = ((u + 1) * (u + 2)).as_poly(*Y)
G = ((v + 1) * (-3 * y_1 * y_0 *... | aacb38639704e7e64b8f120db662fe5789c566f4 | 69,190 |
import cgi
def safe_enter2p(s):
"""正文 换行替换"""
return '<p>' + cgi.escape(s).replace("\n", "</p><p>") + '</p>' if s else '' | 7ca789f9b12bc6cb685975f37548d43504c4d3f8 | 69,191 |
import torch
def accuracy(output, target, topk=(1,)):
"""Computes the accuracy over the k top predictions for the specified values of k"""
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
_, pred = output.topk(maxk, 1, True, True)
pred = pred.t()
corre... | 76571ef880404138a16f814415a987c8ecbbe750 | 69,192 |
import json
import PIL
import io
import base64
def input_fn(request_body):
"""Pre-processes the input data from JSON to PyTorch Tensor.
Parameters
----------
request_body: dict, required
The request body submitted by the client. Expect an entry 'url' containing a URL of an image to classify.
... | 363e9a064f7f82576cab77bb40974b39ba0440be | 69,193 |
def _auto_backward(loss,
startup_program=None,
parameter_list=None,
no_grad_set=None,
callbacks=None):
"""
modification is inplaced
"""
act_no_grad_set = _get_no_grad_set(loss, no_grad_set)
assert isinstance(loss, Variable),... | 08977b52e1229eac110f9c3fa37a897bdab6c536 | 69,194 |
from typing import Optional
from typing import Callable
def count_hint(
dsid: str,
etype: ir_datasets.EntityType = ir_datasets.EntityType.docs,
metadata_provier: Optional[MetadataProvider] = None) -> Callable[[], Optional[int]]:
"""
Returns a lambda expression that provides the count from metadata... | c9d6e0f76fb302393f5ad4a6c52ab7fd1d3b76ba | 69,196 |
def lambda_handler(event, context):
""" Main Lambda function """
try:
response = PINPOINT.phone_number_validate(
NumberValidateRequest={
'PhoneNumber': MOBILE_ENDPOINT
}
)
except PINPOINT.exceptions.BadRequestException:
response_body = f"Not a ... | 0e35a1d2c319136298d9836fa83ae05756bca0ef | 69,197 |
def calc_gradient_from_gate(
c_sys: CompositeSystem,
hs: np.ndarray,
var_index: int,
is_estimation_object: bool = True,
on_para_eq_constraint: bool = True,
on_algo_eq_constraint: bool = True,
on_algo_ineq_constraint: bool = True,
mode_proj_order: str = "eq_ineq",
eps_proj_physical: f... | e5da4b971a8b8dc318b51adfc813987209a007f9 | 69,198 |
import io
def part1(stdin: io.TextIOWrapper, stderr: io.TextIOWrapper) -> int:
"""
As a sanity check, look through your list of boarding passes. What is the
highest seat ID on a boarding pass?
"""
tickets = parse(stdin)
stderr.write(f"{tickets}\n")
max_ticket = max(seat_ids(tickets))
... | 2460a3785264ac9d9f6987a88a851f80a1b5a047 | 69,199 |
from typing import OrderedDict
def read_populations(flname):
"""
Read populations from a file.
We assume that the file has one population per line. The population name
comes first and is followed by a comma. The name of each sample follows,
also separated by comma.
For example:
pop1,s... | 9467bf2e882a2de0ebfb1ecfb566baeab16a1500 | 69,200 |
import inspect
def is_instance_of_django_model(reference):
"""
Tests if a given reference is a reference to a class that extends
django.db.models.Model
:param reference: A given Anonymous reference.
:rtype: boolean
:returns:
A boolean value that is true only if the given reference is ... | b54536bded37e4a078c266bdc9b3553cbf48e0f3 | 69,201 |
def extract_peers(units, boxes):
""" **Function Provided by UDACITY**
Initialize a mapping from box names to a list of peer boxes (i.e., a flat list
of boxes that are in a unit together with the key box)
Parameters
----------
units(dict)
a dictionary with a key for each box (string) who... | 7a40e913d4b0c0b059b535d7a2b77481127ebf0b | 69,203 |
async def unset_user(session: CommandSession):
"""注销绑定"""
bot = nonebot.get_bot()
message_type = session.ctx['message_type'] # 消息类型
user_id = session.ctx['user_id'] # qq群的qq成员id号
# 判断消息是否为群消息
if message_type == "group":
message = session.ctx['message']
message = str(message)[1:... | 6422156f25b636324d813f4f5930165f71a28c3e | 69,204 |
def edit(request, carrera_jurisdiccional_id):
"""
Edición de los datos de un título jurisdiccional.
"""
carrera_jurisdiccional = CarreraJurisdiccional.objects.get(pk=carrera_jurisdiccional_id)
titulo_anterior_id = int(carrera_jurisdiccional.carrera_id)
if request.method == 'POST':
form = CarreraJurisdiccionalD... | 2d156a8315f12ec9af746cf10550af457e186be5 | 69,205 |
def parse_expression(expression, doc_dict):
"""Parse an expression."""
return Parser(doc_dict).parse(expression) | 5c01121e102cea1114f34ccf7d2a0f201c47520d | 69,206 |
from datetime import datetime
def get_unix(str_ts, date_format):
"""Get unix timestamp from a string timestamp in date_format.
Args:
str_ts: string timestamp in `date_format`
date_format: datetime time stamp format
Returns:
int: unix timestamp
"""
return datetime.strptim... | 6d0c591734fa78defed11cd5ed8c66da63ad3b5b | 69,207 |
import io
import json
def load_json(buffer):
"""
Returns a structure if file was json
:param buffer:
:return: JSON created object or None
"""
fp = io.BytesIO(buffer)
try:
data = json.load(fp)
return data
except json.decoder.JSONDecodeError:
return None | 6893a22009ca0093298060913d27d30e2645a92e | 69,208 |
def compute_raw_transect_depths(shore_point, \
direction_vector, bathymetry, bathymetry_uri, landmass, landmass_uri, \
bathymetry_resolution, max_land_profile_len, max_land_profile_height, \
max_sea_profile_len):
""" compute the transect endpoints that will be used to cut transects"""
# Maximum tran... | 71b8e7e48ecd28e4431a5be40c4e4dd52bb81c20 | 69,209 |
import torch
def convert_raw_locations_batched_top_down(raw_locations, stacking_program, primitives):
"""
Args
raw_locations (tensor [*shape, num_blocks])
stacking_program (tensor [*shape, num_blocks])
primitives (list [num_primitives])
Returns [*shape, num_blocks, 2]
"""
... | cee051c4e3450910328bb1fa377a0f4cd02499e8 | 69,210 |
def _preprocess_cameras(example, indices, dataset_info):
"""Instantiates the ops used to preprocess the cameras data."""
raw_pose_params = example['cameras']
raw_pose_params = tf.reshape(
raw_pose_params,
[-1, dataset_info.sequence_size, _NUM_RAW_CAMERA_PARAMS])
raw_pose_params = tf.gath... | fc43470ac26d793539f305a9a44117c15861d440 | 69,212 |
def lad_msoa_mapping():
"""Map between lad and msoa
{LAD: [MOAS]}
"""
msoa_lad_map = {
'E06000047': ['E02004297', 'E02004290', 'E02004298', 'E02004299', 'E02004291', 'E02004300', 'E02004292', 'E02004301', 'E02004302', 'E02004303', 'E02004293', 'E02004304', 'E02004294', 'E02004305', 'E02004295',... | 55f97fecca6e11df2141991de9bdb4295ca5e4af | 69,213 |
import random
import logging
def build_encapsulated_ip_packet(
rand_selected_interface,
ptfadapter,
rand_selected_dut,
tunnel_traffic_monitor
):
"""
Build the encapsulated packet to be sent from T1 to ToR.
"""
tor = rand_selected_dut
_, server_ips = rand_selected_interface
s... | f2ac6dd830eeadb60404135206b657b1689a03c2 | 69,214 |
def test_rows_filled():
""" cycles through all rows in placement_map and returns
a list of all row indecies that are filled """
rows_filled = []
for i in range(len(placement_map)):
if 0 not in placement_map[i]:
rows_filled.append(i)
return rows_filled | 8a6d937c089a806992690a96d4bd3cedc684d3fa | 69,216 |
def load_img_info(files):
"""Load the information of one image.
Args:
files (tuple): The tuple of (img_file, groundtruth_file)
Returns:
img_info (dict): The dict of the img and annotation information
"""
assert isinstance(files, tuple)
img_file, gt_file = files
assert osp.b... | 5f1e3ce6dc410985e082fc7b66315e7d80167aed | 69,217 |
def run_transport(definition, transport) -> bool:
"""
Runs schedule & watch for a transport
:param definition:
:param transport:
:return:
"""
with definition.transport(binaries=[]):
transport.schedule(
command="--mocked--", definition=definition,
is_backup=T... | e8a3442f670351ed7642abe4b4a837fd84d36f55 | 69,218 |
def rivers_by_station_number(stations, N):
"""Passed a list of station objects and a number N, returns the list of N river objects from with the most monitoring stations on it."""
riverstation = stations_by_river(stations)
numstations = sorted_by_key([(i, len(riverstation[i])) for i in riverstation], 1, rev... | d2965c4f68bb8519144308f4eff11e3017b1ba28 | 69,220 |
def fake_request():
"""A faked APIRequest."""
class FakeApiRequest(APIRequest):
def send(self, params=None):
return self
class FakeApiClient(API):
def __init__(self):
super().__init__("notempty")
self.base_url = "" # Overwrite with empty base
@property
def request_class(self):
return FakeApiR... | c6d1639e8f2b43971ffe1176d3511cd665f15dc1 | 69,221 |
def band_dos_atoms_spin_polarized(
band_folder,
dos_folder,
atoms,
output='band_dos_atoms_sp.png',
scale_factor=5,
color_list=None,
legend=True,
linewidth=0.75,
band_color='black',
unprojected_band_color='gray',
unprojected_linewidth=0.6,
figsize=(8, 6),
width_ratios=... | 83b684619f68f7262ada90f7673bd655f7cde9f6 | 69,223 |
from typing import Dict
from typing import Any
def load_screens() -> Dict[str, Any]:
""" Initialize screen components and screens, and store references to them """
for component_name in SCREEN_COMPONENTS:
load_kv(component_name)
screens = {}
for screen_name, screen_cls in SCREENS.items():
... | 3241880c714dc2a709bcbadd1f9f52b30452c2ef | 69,224 |
def play_game(board, original_total_time, time_left, turn_count, move_count_no_change):
"""
plays the best move using a portion of remaining time
input: board (list), time_left (float), turn_count (int)
output: result (tuple) -> e.g. ("E", (5, 2), (4, 3))
"""
num_pieces_board_in = board.num_pi... | 3bab79e00fc1caeb4b3e06c836f67a9e4186b59d | 69,225 |
def skgrcnn109(num_classes=1000):
"""
Args:
num_classes (uint): number of classes
"""
model = GRCNN([3, 3, 22, 3], [128, 256, 512, 1024], SKconv=True, expansion=2, num_classes=num_classes)
return model | 7ee3b244a0689396423e1a6d9753c74a3135e934 | 69,227 |
import re
def string_to_arrow(datasets_dtype: str) -> pa.DataType:
"""
string_to_arrow takes a datasets string dtype and converts it to a pyarrow.DataType.
In effect, `dt == string_to_arrow(_arrow_to_datasets_dtype(dt))`
This is necessary because the datasets.Value() primitive type is constructed usin... | 206d66e4c18fc085852667890e7bd4903703299a | 69,228 |
def document_list_folders(request, destination, location_id):
"""
Get the folders that are associated with the destination and location id
Method
~~~~~~
1. Get all the document permissions connected to the destination and location
2. Get the folder information from this
:param request:
... | c1c4fe9581128a369cc844e1b29ca601e80a3687 | 69,231 |
def datacursor(artists=None, axes=None, **kwargs):
"""
Create an interactive data cursor for the specified artists or specified
axes. The data cursor displays information about a selected artist in a
"popup" annotation box.
If a specific sequence of artists is given, only the specified artists will... | 713dcdf67a465afd055f10ad94d0744b776c8522 | 69,232 |
def channel_to_module_output(channel):
"""Returns a (module, output) pair given a CCD channel number."""
if channel < 1 or channel > 88:
raise ValueError("Channel number must be in the range 1-88.")
lookup = _get_channel_lookup_array()
lookup[:,0] = 0
modout = np.where(lookup == channel)
... | dddf0a38bae7f03fb5de8fbbb71e1c932594c58c | 69,233 |
def score_openpose(e, image, w, h):
"""Score an image using OpenPose model.
Args:
e: OpenPose model.
image: Image in CV2 format.
Returns:
Nubmer of people in image.
"""
resize_out_ratio = 4.0
humans = e.inference(
image, resize_to_default=(w > 0 and h > ... | d2969d5af4736497d463482c6b0f532b9e9f908c | 69,234 |
def generate_expired_token(create_user):
"""
generate expired JWT token
"""
user = create_user
user_data = {
"email": user.email,
"username": user.username
}
jwt = JWTAuthentication()
# encode token
encoded_token = jwt.generate_token(user_data)
return encoded_toke... | 437745a9a7276f448f4dae60e9d405887fb72cb0 | 69,235 |
def int_fn_vt(dm_comp, method, timeArr=time_arr, vArr=v_arr, vsun=v_sun, t1=tvernal, from_scratch=False, what_inter='interp2d'):
"""
Interpolation of a function method for a DM component, coming from a 2D time [days]-velocity [km/s] table, for fixed vsun and t1. The table is either constructed from scratch, or ... | 4294f3a7349bffc3552b78612dd17c5677c81547 | 69,236 |
def readable_join(xs, conjunction="and", sep=","):
"""
Accepts a list of strings and separates them with commas as grammatically
appropriate with a conjunction before the final entry. Any input strings
containing only whitespace will not be included in the result.
>>> readable_join(['foo'])
'fo... | d518007954b79ff1cf8120a9bdea010e9594f02b | 69,237 |
def minimize_sat(u, u_min, u_max, desaturation_vector):
"""
Minimize the saturation of the actuators by
adding or substracting a fraction of desaturation_vector.
desaturation_vector is the vector that added to the output u,
modifies the thrust or angular acceleration on a
specific axis.
For ... | 79e5e898cad83e32c9eb09b084ce3bd3df0639d1 | 69,239 |
import shlex
def help(bot, message):
"""#help
"""
try:
cmd, *args = shlex.split(message.text)
except ValueError:
return False
if not cmd[0] in config['trigger']:
return False
if not cmd[1:] == 'help':
return False
msg = ['ケルベロス ver3.0.5']
msg_help = []
... | f07caa7b3b00b334fc1af153ed1a086ff72282e2 | 69,240 |
def _cond_apply(x, y, func, prob):
"""Conditionally apply func to x and y with probability prob."""
return tf.cond((tf.random.uniform([], 0, 1) >= (1.0 - prob)), lambda: func(x,y), lambda: (x,y)) | c8f93e40407fc4e7edf8c72095036f19a49db455 | 69,241 |
def replace_underscore_with_space(original_string):
"""
Another really simple method to remove underscores and replace with spaces for titles of plots.
Args:
original_string: String with underscores
Returns:
replaced_string: String with underscores replaced
"""
return original_... | 27bea63c33c2ffe44b1ddc591a7813d8830e9f76 | 69,242 |
def residual(parameters_vector, datatube, vartube, xfibre, yfibre,
wavelength, model_name, fixed_parameters=None, secondary=False):
"""Return the residual in each fibre for the given model."""
parameters_dict = parameters_vector_to_dict(parameters_vector, model_name)
parameters_dict = insert_fi... | 6353f2fa17aa09df6f4b98e6195ebc4be07d19a5 | 69,243 |
import numpy
def gradient_array(ndarray):
""" transform numpy array into python list
"""
out = ndarray
if isinstance(out, numpy.ndarray):
out = ndarray.tolist()
return out | 41d4a37e50db0a319d23d18d95978f0d16e569f8 | 69,244 |
def is_submod(mod_obj):
"""
Find out whether module has a parent or not.
:param mod_obj: module object
:return: module status
"""
try:
bt = mod_obj.get('belongs-to')
if not bt:
return False
return True
except Exception as e:
return False | 274d985b3b7b07f02e919af20ed7fd4531136ccc | 69,245 |
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