content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def effective_sample_size(x, mu, var, logger):
"""
Calculate the effective sample size of sequence generated by MCMC.
:param x:
:param mu: mean of the variable
:param var: variance of the variable
:param logger: logg
:return: effective sample size of the sequence
Make sure that `mu` and ... | 0c19c0f9b95da5d837f16bf6e92248db6e839304 | 79,125 |
def route(*, db_session: Session = Depends(get_db), route_in: RouteRequest):
"""
Determine the correct entities to dispatch.
"""
return {"recommendation": get(db_session=db_session, route_in=route_in)} | b2934dda89249200315464ae73c8c27ecba94aeb | 79,126 |
import torch
def change_last_layer_vgg(model):
"""
Change last layer of a vgg model
:param model: torchvision.models.module
:return: torchvision.models.module
"""
# num filters in bottleneck layer
num_filters = model.classifier[6].in_features
# convert all layers to list and remove the... | 3540ddae99e0cb5d2915ec70fa051f2dc7819e27 | 79,128 |
def xcorr2(signal, kernel, centered_p=True):
"""Signal-kernel 2D convolution
Convolution of a 2-diemensional signal (the contact map) with a kernel
(the pattern template).
Parameters
----------
signal: array_like
A 2-dimensional numpy array Ms x Ns acting as the detrended Hi-C map.
... | fa653530efad0d27d7721d795c1bbc16e576a8b2 | 79,129 |
import unittest
def suite():
"""A testsuite that has all the sender tests.
"""
suite = unittest.TestSuite()
suite.addTest(unittest.makeSuite(MailTestCase))
suite.addTest(unittest.makeSuite(MessageTestCase))
suite.addTest(unittest.makeSuite(AttachmentTestCase))
suite.addTest(unittest.makeSu... | f3338a7a963b4e9cb00e4d60f9fbd9923c0610ba | 79,130 |
from typing import Union
def get_sharpe_ratio(
pf_return: Union[float, pd.Series],
rf_return: float,
std_deviation: Union[float, pd.Series],
) -> Union[float, pd.Series]:
"""
Calculate Sharpe ratio.
"""
return (pf_return - rf_return) / std_deviation | e3d6516e021f0596895fbc8189c70bd91e05060f | 79,132 |
import torch
import tqdm
import math
def estimate_entropies(qzCx_samples, qzCx_params, device, n_samples=10000, weights=None):
"""Computes the term:
E_{p(x)} E_{q(z|x)} [-log q(z)]
and
E_{p(x)} E_{q(z_j|x)} [-log q(z_j)]
where marginal q(z) = 1/N sum_n=1^N q(z|x_n).
Assumes samples ar... | 43e1b8a8b573f182599bb555b229eb1d1494f027 | 79,133 |
import ast
from typing import List
from typing import Tuple
def _get_sim117(node: ast.With) -> List[Tuple[int, int, str]]:
"""
Find multiple with-statements with same scope.
With(
items=[
withitem(
context_expr=Call(
func=Name(id... | d58989f2a832481eb6bb53c166478f415df9769b | 79,135 |
def get_snapshot_arn_instance(rds_client, snapshot_identifier):
"""Function to get the full ARN of a snapshot.
Args:
rds_client (Client): AWS RDS Client object.
snapshot_identifier (str): Snapshot identifier to get full ARN
Returns:
str: The full ARN of the snapshot_identifier input,... | 2693c4eaff9edeadc142957ab0729c4d6d66893d | 79,136 |
from typing import List
from typing import Tuple
def tabulate(rows: List[Tuple[str, str]]) -> List[str]:
"""Utility function for printing a two-column table as text with whitespace padding.
Args:
rows (List[Tuple[str, str]]): Rows of table as tuples of (left cell, right cell)
Returns:
Ro... | 838540161e06544f81bdf4ea78b0973f75949fb3 | 79,138 |
def hit(row, column, fleet):
"""
This method returns a tuple (fleet, ship) where ship is the ship from the fleet that receives a hit
by the shot at the square represented by row and column, and fleet is the fleet resulting from this hit.
:param row: int
:param column: int
:param fleet: list
... | 673994265cec6e0167b764b25eba1006e16c7257 | 79,139 |
def is_meta_field(field_name: str) -> bool:
"""Return True if the field is considered a meta field in the schema, and False otherwise."""
return field_name in ALL_SUPPORTED_META_FIELDS | 075d3d326fdca8ca5ed3f83b36b3b6ed925b2e79 | 79,141 |
def expect_FE02_did(cmd, did, value=None,
timeout=2, ack=False, said=None,
gids=None, gid_type="U16",
check_seq=True,
**kwargs):
"""
测试EIOU时，通过工装接收设备发送的报文，采用7E+FE02+7E形式。 解EIOU工装7E包7E
:param cmd: 支持“READ”,"WRITE","REPORT","NO... | 81656e071e5b8f6ff1746e85db3847fd1fad1d53 | 79,142 |
def pack_list(input_list, pack_size=5000):
"""
列表片段打包
:param input_list: 1d list, the whole list
:param pack_size: int, the number of a pack
:return: 2d list [pack_list, pack_list]
"""
assert np.array(input_list).ndim == 1
length = len(input_list)
k = 0
result = []
while ... | 368e6093d905bd6696f42ccc81a2d9140fae32af | 79,146 |
import collections
def format_data(data, exclude_labels=[], exclude_properties=[]):
"""
Format the data into a json response.
:param data: Data that you are formatting and returning a json response
for.
:type data: Iterable of :class:`ruruki.interfaces.IEntity`
:param exclude_labels: List... | 424b34962d8badd8d7b6dff80b955d057f815edd | 79,147 |
import pickle
def load_vocab(load_vocab_model_path):
"""加载模型"""
with open(file=load_vocab_model_path, mode='rb') as fp:
return pickle.load(file=fp) | ccbb1313a28c3f54147fbc7bad899ac9774f91af | 79,148 |
def find_link_to_join(model, link_name):
"""Finds a link in the model to move the contents of the provided link.
This is done by first finding the joint that attaches this link to another
link in the model."""
for el in model.findall('joint'):
# Joining is only possible if the joint is a fixed ... | 68600b70e6a6d29cceeae6e365ae4dfeacfd69f2 | 79,149 |
import json
def generic_exc_handler(exc): # pylint:disable=W0613
"""generic_exc_handler
:param exc:
"""
logger.exception('')
resp = InternalServerError().get_response()
resp.data = json.dumps({
'message': 'Server error',
})
resp.content_type = 'application/json'
return re... | 89e9ca1dfe1417b0e2f57cb143a3a00b7b0eb271 | 79,151 |
def XYZ_to_ProLab(
XYZ: ArrayLike,
illuminant: ArrayLike = CCS_ILLUMINANTS[
"CIE 1931 2 Degree Standard Observer"
]["D65"],
) -> NDArray:
"""
Converts from *CIE XYZ* tristimulus values to *ProLab* colourspace.
Parameters
----------
XYZ
*CIE XYZ* tristimulus values.
i... | 3d49d7d12e29c79937a4e879f8cad2da4cd42c78 | 79,153 |
def is_phrasal(subtree):
"""True if this treebank subtree is not a terminal or a preterminal node."""
return isinstance(subtree, list) and \
(len(subtree) == 1 or isinstance(subtree[1], list)) | c38aa1f092f141b7a14cc14248c19c5c59c7dd45 | 79,154 |
from typing import Iterable
def _produce_not_impl_error(
client_message: lsp_message.LspMessage) -> Iterable[lsp_message.LspMessage]:
"""If the client_message is a request, responds with not impl error.
Produces no response if the client_message is not an LspRequest.
Args:
client_message: An RPC sent ... | e0c5e70fc25af005d4a29ef6149921098707d87c | 79,155 |
def find_first_min_points(pt, n):
"""
Usage
-----
Return the index of the min-point in the vector pt of size n.
Parameters
----------
param pt : len(t1)x1 numpy_array
param n : int
Returns
-------
min_point_index : nbumber of min points x1 numpy_array
"""
if n =... | eb21df246a15e493a24a2bfb6a4896f027bdc210 | 79,156 |
def get_contours(img):
"""Get array of contours around drug pack.
Args:
img: Drug original or resized image.
Returns:
contours: Image contour arrays.
"""
# Convert color to gray
# cvt_color = cv2.cvtColor(img,cv2.COLOR_BGR2Lab)
# Get edges
# edged = cv2.Canny(cvt_c... | 8c8540336ad373fca1ad0c61ae8795781a0fcfa0 | 79,157 |
def gram_matrix(A):
"""
Style Matrix
------------
Argument:
A -- matrix of shape (n_C, n_H*n_W)
Returns:
GA -- Gram matrix of A, of shape (n_C, n_C)
"""
GM = tf.matmul(A,A,transpose_b=True)
return GM | 7e34abf70237b593cb7327341c717f912b68908a | 79,158 |
def splitb(g, mg):
""" Determines a usable rank based on modest rise in Picard Vector
after the low point in the PCV."""
w = decide_width(mg)
if w < 2:
return mg # splitb needs w>=2 to be reliable
# magnify any divergence by squaring
gg = np.zeros(mg)
for i in range(0, mg):
... | e043d05fe05d7ef858ffe11963908d183d0359f2 | 79,159 |
def sync():
"""Decorator which can be applied to functions which adds a field 'sync'
to them. Recovery tests use this to determine if the servers should be
started with the --sync mode flag for backups.
"""
def decorate(f):
def new_f(*args, **kwargs):
return f(*args, **kwargs)
... | c197ee4c4bd242e7f050501e2114ae4e0f290f4e | 79,160 |
def _countWeightInBins(sortedData, binBoundaries):
"""
This method counts the number of data items in the sorted_data
Returns an array with the number. ret[0] is the number of data
points <= binBoundaries[0], ret[len(binBoundaries)] is the number
of points > binBoundaries[len(binBoundaries)-1]
@ ... | 4c84ccfe6c8055ae52610fa06fd4e4a9c07cf295 | 79,161 |
import time
from mpi4py import MPI
def get_n_workers(pool=None):
"""Extract how many workers our pool has (mostly for working out how many
tasks to pre-dispatch).
"""
if pool is None:
pool = get_pool()
try:
return pool._max_workers
except AttributeError:
pass
back... | 918a26ad3887d67a14cf6a6dedbf11a96c90a031 | 79,162 |
def select_lessons_assoc(user_obj, **kwargs):
"""
Query the database and select
UserLessonAssociations, for the given user_obj and attendance_code.
"""
# Create a base query.
base_query = UserLessonAssociation.query.filter(UserLessonAssociation.user == user_obj).join(UserLessonAssociation.lesson... | ee6b0983cb63574fbc46f6bbff7635c222036490 | 79,163 |
def __lop__(op):
""" binary left operator decorator """
def tmpop(self,right):
return self._run_op(self, right, op)
return tmpop | 5e84a705a2f1901a1545ce75b139ea4cb6342c1a | 79,164 |
def get_instance_name(inst):
"""Get the name of an instance, or None if it doesn't have one.
The name is the value for the metadata tag "Name," if it exists.
"""
if inst.get('Tags'):
for tag in inst['Tags']:
if tag['Key'] == 'Name':
return tag['Value']
return Non... | 1fa24ac813f0245a08585c0a776a9ada27099393 | 79,165 |
def filter_ann_and_variants(annotations_w_aa_variants):
"""
Transforms SUBs and DELs so that they're all of length 1
Removes
- substitutions whose alternative sequence is X (aligner error)
- variants with NULL start coordinate
"""
new_annotations_w_aa_variants = []
for gene_name, product... | d1b3a67ea23f33d68ef81ebd9f79ef5b3e422c66 | 79,166 |
def pack_as_dict(batches, input_name='spect'):
"""
Helper function converting mini-batches from (list of ndarray, list of dict)
to dict of ndarray. `input_name` gives the key to use for the first ndarray.
"""
def pack_array(array):
if isinstance(array, (list, tuple)):
if len(arra... | 39666453aafb912838ad66bf653ef6e9002107b5 | 79,167 |
def peaks(image, return_numpy=True):
"""
Detect all peaks from a full SLI measurement. Peaks will not be filtered
in any way. To detect only significant peaks, filter the peaks by using
the prominence as a threshold.
Args:
image: Complete SLI measurement image stack as a 2D/3D Numpy array
... | db3edfd3c57e842d81d2850212f104bcc9b34f87 | 79,169 |
def post_login(account, password, proxy=None):
"""
Post tinychat login info.
:param account: str tinychat account name.
:param password: str tinychat account password.
:param proxy: str(ipv4:port) use a proxy for this request
:return: dict{'content', 'cookies', 'headers', 'status_code'} or None ... | 39ba2ce95f59f1bc777e0fb898210c4e19898ed4 | 79,170 |
def detail(request, pk):
"""
Detailed company view per PK
"""
if not has_access(request):
raise PermissionDenied
context = get_base_context(request)
context["company"] = get_object_or_404(Company, pk=pk)
if request.method == "POST":
company_form = CompanyForm(request.POST... | bfc3b8c73dbe0bc00d1ae6664d1ded8cf0060cd7 | 79,171 |
import json
def get_extracted_hl_features(ofile):
"""returns the extracted high-level features from json file in dictionary
format"""
features = {}
with open(ofile, 'r') as ef:
content = json.load(ef)
for f in content['highlevel']:
features[f] = content['highlevel'][f]['v... | 02ffb2e3881c1293d696e19969cf9246a0835403 | 79,174 |
def get_value(config_map, key):
""" This does not do truly validate the config value but it at least makes sure it is
present and is not an empty string and not just all whitespace
"""
try:
return config_map[key]
except:
return None | 0b5e344de48100882f4d9c6c5d441b75f6900f41 | 79,175 |
def x_seconds_after_now(seconds):
"""
Get the datetime that ``y`` seconds after now.
:type seconds: int
:param seconds:
:rtype: datetime
:return:
"""
return utc_now() + timedelta(seconds=seconds) | 72bb2b2bb71b5924ff8b730af40777dbb2e7ab56 | 79,176 |
def cec_module_params():
"""
Define some CEC module parameters for testing.
The scope of the fixture is set to ``'function'`` to allow tests to modify
parameters if required without affecting other tests.
"""
parameters = {
'Name': 'Example Module',
'BIPV': 'Y',
'Date': ... | 27da851a8253d4309c8efa9f4c8903820531f872 | 79,177 |
async def statistical_ext_source_2():
"""
EndPoint to get some statistics - EXT SOURCE 2
"""
ext_source_2_data_repaid = df_current_clients_by_target_repaid.groupby("EXT_SOURCE_2").size()
ext_source_2_data_repaid = pd.DataFrame(ext_source_2_data_repaid).reset_index()
ext_source_2_data_repaid.co... | a3e536c27cb1bc779297b1501805991d8a24bcb2 | 79,179 |
import logging
def _checkDefaultLogger() -> logging.Logger:
""" Check if default logger already exists and raise exception
if not.
Returns:
Logger instance object.
"""
if _defaultLogger is None:
errorMsg = "No default logger instance available."
raise Exception(errorMsg)
... | 51e01ac6c37d9c27f913ebab558fec84646f4fe3 | 79,180 |
from typing import Any
async def densenet_upload_weights(
file: UploadFile = File(...)
) -> Any:
"""
Upload densenet weights.
"""
if (
file.content_type not in ['application/octet-stream']
or file.filename.split('.')[-1] not in ['h5']
):
raise HTTPException(
... | 56765627e7e9d11810b51a482870ce0a1bc2311a | 79,181 |
def J2Btu(x):
"""J -> Btu"""
return x*3412./1000./3600. | 8136dbb87424e1e7cfabbc98e0b5a33ddbd813a2 | 79,182 |
def GradientBooster(param_grid, n_jobs):
"""Function to optimize the fit with data. Start using:
1. min_samples_split = 0.5%-1% total values
2. min_samples_leaf = 0.1*min_samples_split (or round to 1)
3. max_depth = should be chosen from 5-8
4. max_features = 'sqrt'
5. subsample = 0.8 (common va... | 82921bedf7aaf9e674f6377b8d969ba94ca05266 | 79,183 |
import torch
def fastercnn_loss_focal(class_logits, box_regression, labels, regression_targets):
# type: (Tensor, Tensor, List[Tensor], List[Tensor]) -> Tuple[Tensor, Tensor]
"""
Computes the loss for Faster R-CNN.
Args:
class_logits (Tensor)
box_regression (Tensor)
labels (li... | be2462a43f640aa81bec97738ec9cbc7d8b6d87f | 79,185 |
import dis
def _instructions_up_to_offset(x, lasti: int) -> list:
"""Get all instructions up to offset *lasti*. """
instructions = []
for instruction in dis.get_instructions(x):
instructions.append(instruction)
if instruction.offset == lasti:
break
return instructions | a38ad93350146fb98e559522d86d3674de0539fd | 79,186 |
def calc_rho(RhoRef,T,S,alpha=2.0E-4, beta=7.4E-4):
"""-----------------------------------------------------------------------------
calc_rho calculates the density profile using a linear equation of state.
INPUT:
state: xarray dataframe
RhoRef : reference density at the same z as T and S slice... | 7132858623ec88e7989abb1e383132d269b083b6 | 79,187 |
def add_depth_channels(image_array):
"""Add 2 extra channels to a 1 channel numpy array
One channel is a linear sequence from 0 to 1 starting from the top of the image to the bottom
The second channel is the product of the input channel and the 'depth' channel
Args:
image_array (numpy.Array): 2... | 0af3100d11dc35a35779381535603d0b7e73bef8 | 79,188 |
import msgpack
def structure_to_mmtf_string(structure):
"""Converts a :py:class:`.AtomStructure` to a .mmtf filestring.
No compression is currently performed.
:param AtomStructure structure: the structure to convert.
:rtype: ``bytes``"""
chains, ligands, waters, properties, entities = get_struc... | 434078f76d74d35300b74613d45fa3aa028bb637 | 79,189 |
def db_for_read_write(model, write=True):
"""
:param model: Django model being queried
:param write: Default to True since the DB for writes can also handle reads
:return: Django DB alias to use for query
"""
app_label = model._meta.app_label
if app_label == WAREHOUSE_APP:
return se... | 6b497c4be54da0ac62adf1299defaf5b0a73f719 | 79,190 |
import torch
def distance2bbox(points, distance, max_shape=None):
"""Decode distance prediction to bounding box.
Args:
points (Tensor): Shape (n, 2), [x, y].
distance (Tensor): Distance from the given point to 4
boundaries (left, top, right, bottom).
max_shape (tuple): Sha... | fd68eabd7cce196b9e48e794fc981e3d44ae657f | 79,191 |
import pickle
def build_RFC(data, file):
""" Build random forest classifier """
clf = RandomForestClassifier(random_state=42)
train_classifier(clf, data[0], data[2])
pickle.dump(clf, open(file, 'wb'))
return clf | 7b4976e28a87fe6454517f004de570f914ae904d | 79,192 |
from typing import Iterable
from typing import List
from typing import Tuple
def get_eigenvalues_with_degeneracies(evals: Iterable[float]) -> List[Tuple[float, int]]:
"""
Given a set of sorted eigenvalues (possibly including degenerate eigenvalues), return a list of
(eigenvalue, degeneracy) pairs, with ei... | 37b0244b15eda2159f79e4de8da8a86e2b7e6352 | 79,194 |
def rsa_jwk_to_pubkey(jwk):
"""
Only RS256 supported so far
:return:
"""
e = int.from_bytes(base64url_decode(jwk['e']), byteorder='big')
n = int.from_bytes(base64url_decode(jwk['n']), byteorder='big')
pub_num = RSAPublicNumbers(e, n)
return pub_num.public_key(backend=default_backend()) | 78f9aebbbc80f6e01d1dfe9046c018ad47ca953e | 79,195 |
import requests
def address_utxos_asset(self, address: str, asset: str, **kwargs):
"""
UTXOs of the address.
https://docs.blockfrost.io/#tag/Cardano-Addresses/paths/~1addresses~1{address}~1utxos~1{asset}/get
:param address: Bech32 address.
:type address: str
:param asset: Concatenation of th... | 9a7f86f14fba26ba11d3972c7ef7e29f05ae3d14 | 79,197 |
import time
import io
def create_placeholder(cache_id, token_id):
"""
Create a placeholder file for a generated cache_id using a token_id. The metadata on this
placeholder file can be used for later validating uploads and checking expirations.
If a placeholder has already been created, but no file up... | e39235aa1572314ab8f04d1af735b80f4ff550a2 | 79,198 |
def get_municipalities_with_filter(id_state_code=None): # noqa: E501
"""get_municipalities_with_filter
Get municipalities with filter # noqa: E501
:rtype: List[Municipality]
"""
if id_state_code is not None:
return get_municipalities_by_state(id_state_code)
return get_municipalities() | a6d290319bf2b6cd6f3c7f4fa9ac5f64b0b9df57 | 79,200 |
import torch
def to_tensor(pic, use_half=False):
"""Convert a ``PIL Image`` or ``numpy.ndarray`` to tensor.
See ``ToTensor`` for more details.
Args:
pic (PIL Image or numpy.ndarray): Image to be converted to tensor.
Returns:
Tensor: Converted image.
"""
if not(_is_pil_image(... | 2ba0feedbc3d683f2522ea60949b428e85ab49fd | 79,201 |
def _get_first_mstump_profile(start, T_A, T_B, m, excl_zone, M_T, Σ_T):
"""
Multi-dimensional wrapper to compute the multi-dimensional matrix profile
and multi-dimensional matrix profile index for a given window within the
times series or sequence that is denote by the `start` index.
Essentially, th... | c82f4150f29cba8836a3364f0dfabbc4dd70853d | 79,202 |
def directly_follows(trace):
"""
Get the directly-follows relations given a list of activities
Parameters
--------------
trace
List activities
Returns
--------------
rel
Directly-follows relations inside the trace
"""
return set((trace[i], trace[i+1]) for i in r... | 1e93d16a3bd002aa29b43309dc0a32360e2046db | 79,203 |
def inf_is_graph_view(*args):
"""
inf_is_graph_view() -> bool
"""
return _ida_ida.inf_is_graph_view(*args) | 7abb467be1018f3274ecb436a17fec502be30b88 | 79,204 |
import time
def pre_experiment(
board: board_reader.BoardReader,
psd_extractor: feature_extraction.PSDFeatureExtractor,
band_power_chart,
psd_chart: tk_plots.PSDPlot,
) -> float:
"""
:return: average band power for pre-experiment phase
"""
print(
f"Taking PSD baseline before st... | 768b179c323e27802b31debd2b4791c216a03ed3 | 79,205 |
def get_datacap_dashboard():
"""
获取钱包列表
:return:
"""
result = DataCapService.get_datacap_dashboard()
return response_json(result) | 1255e0e0f3fabbe7396dda47123e48e782da2a0c | 79,206 |
def getLibraryVersion():
"""Return a long representing library version"""
m = _ft.DWORD()
call_ft(_ft.FT_GetLibraryVersion, c.byref(m))
return m.value | f475a922c3687cac6dc62109c00f915b432538e2 | 79,207 |
import textwrap
def docMakeChunks(optList, width=80):
"""
Makes doc chunks for option declarations.
Takes a list of dictionaries, each of which may have one or more
of the keys 'long', 'short', 'doc', 'default', 'optType'.
Returns a list of strings.
The strings may be multiple lines,
all... | d89d038668bd69bdd9cbc3c842840aac884475f2 | 79,208 |
def encodetextlist(arr):
"""arrを\n区切りの文字列にする。"""
return encodewrap("\n".join(arr)) | fcd6dfe5d518ceabbcff16e9eb9b9ca314e489c1 | 79,209 |
def app_uninstall(app, request):
"""
Uninstalls the application.
Parameters
----------
app:
application name
request:
the global request object
Returns
-------
`True` on success, `False` on failure
"""
try:
# Hey App, this is your end...
path... | 993ff980f03a52edf73e696ff53e2f9f4a070aaf | 79,210 |
def get_gsub_ligature_lookup(font):
"""If the font does not have a GSUB table, create one with a ligature
substitution lookup. If it does, ensure the first lookup is a properly
initialized ligature substitution lookup. Return the lookup."""
# The template might include more lookups after lookup 0, if it has ... | 10197f392017ca2bdd3d235ec0755eaeb63b5c12 | 79,211 |
import tqdm
def filter_by_language(data, column='text', lan='en'):
"""
Keeps rows of the given DataFrame(data) that have the given column value written in the given language.
Args:
data: pandas DataFrame
column:
lan:
Returns:
pd DataFrame with rows containing texts in the... | d1388452ede7c3bed107c1156da2a9db01725ebb | 79,212 |
from typing import List
from typing import cast
def compute_yaw_rate_from_states(
agent_states_horizon: List[List[StateSE2]], time_stamps: List[TimePoint]
) -> npt.NDArray[np.float32]:
"""
Computes the yaw rate of all agents over the trajectory from heading
:param agent_states_horizon: agent trajector... | ed2c94cf044ca32b30e589ff5536a7b2308612a2 | 79,214 |
def _find_lt(a, x):
""" Find rightmost value less than x"""
i = bisect_left(a, x)
if i:
return int(i - 1)
print('in _find_lt,{}'.format(a))
raise ValueError | 203e66c470d5d50aacca9dff5159d52fc0dcfae5 | 79,215 |
def lj_v(positions_1,positions_2,sigma,epsilon):
"""
Calculate the Lennard-Jones interaction energy between two particles, given their positions and definitions for their equilbrium interaction distance (sigma) and strength (epsilon).
:param positions_1: Positions for the first particle
... | ebb4ab97b6e1e4a257d89e9356bd1b2b99ddf746 | 79,216 |
def minical_data_old(fe, pms, diag=False):
"""
Obtains power meter readings for a mini-calibration
@type fe : FE (front end) instance
@param fe : receiver to be calibrated
@type pms : list of pms instances
@param pms : power meters taking the readings
@type diag : bool
@param diag : output diagnostic... | 37a262ae80f8ac9881fea5a5775b1770b9f94687 | 79,217 |
def function_key_generator(namespace, fn, to_str=compat.string_type):
"""Return a function that generates a string
key, based on a given function as well as
arguments to the returned function itself.
This is used by :meth:`.CacheRegion.cache_on_arguments`
to generate a cache key from a decorated fu... | 8d83648ea2bcf7c3f120683d623ec5aabea64878 | 79,219 |
import time
def wait(sentry, timeout=900):
"""Waits for all units to be active/idle."""
def check_status():
status = sentry.get_status()
for service_name in sentry.service_names:
service = status.get(service_name, {})
for unit_name, unit in service.items():
... | a0072f863f5afbde2c0b3b749974fa38f2cf5c55 | 79,220 |
def get_input_fn(dataset_split,
batch_size,
capacity=10000,
min_after_dequeue=3000):
"""Input function over MNIST data."""
def _input_fn():
"""Prepare features and labels."""
images_batch, labels_batch = tf.train.shuffle_batch(
tensors=[dataset_spl... | 8a8ff74aba089cc06e46b04911da08697bdff9f4 | 79,221 |
def coin_piles(t: tuple) -> str:
"""
[Medium] https://cses.fi/problemset/task/1754
[Solution] https://cses.fi/paste/61697edb44edc7a922cce0/
You have two coin piles containing a and b coins. On each move, you can
either remove one coin from the left pile and two coins from the right
pile, or t... | 5bb8ee989377807bfea48d0685e1ffa66bc58a4b | 79,222 |
def bit_mat_det(a):
"""return the determinant of bit Matrix a."""
try:
bit_mat_inverse(a)
return 1
except ZeroDivisionError:
return 0 | 0ce44e87051f6ceb9b8ab0158dc1f0ca122d715f | 79,223 |
def FocalMechanism_Meta():
"""FocalMechanism_Meta() -> MetaObject"""
return _DataModel.FocalMechanism_Meta() | fbf00cef31edaa5ed4c10407ef3ee3e698b56857 | 79,224 |
def find_tag_path(xml, tags):
"""Find a unique xml object with a list of tags."""
assert(type(tags) is not str)
assert(len(tags) > 0)
if (xml.tag == tags[0]):
tags.pop(0)
matches = list(gen_by_tag_path(xml, tags))
if len(matches) == 0:
raise errors.MissingXMLError(f"Object does ... | b90bf1e6ca3e8ea21379ef6017d0f6f09d369337 | 79,225 |
def get_version():
"""
Return the runtime version as a tuple of (major, minor)
"""
return runtime.get_version() | 5da7f18a7c37fb7035910fc78c1dda217a919f76 | 79,226 |
def get_share_in_repo_list(username, org_id):
"""List share in repos.
"""
if org_id:
repo_list = seafile_api.get_org_share_in_repo_list(org_id, username,
-1, -1)
else:
repo_list = seafile_api.get_share_in_repo_list(username, -1, ... | dec8aa885d69d02c4384581571770bd3ddc6979d | 79,227 |
def _get_num_steps(trajectory: gsd.hoomd.HOOMDTrajectory) -> int:
"""Find the number of steps in a Hoomd trajectory handling errors.
There are cases where it makes sense to run an analysis on the trajectory
of a simulation which is not yet finished, which has the potential to
have errors reading the fi... | 45da9138dcc7713c8825dc522ba8e9674fb67abc | 79,228 |
def test_in_df_out_df_dict():
"""Test a function with input and output data set, but as dictionary not DataFrame"""
def func(in_df: DataFrame):
return {"out_df": in_df}
name = "test_in_df_out_df_dict"
sqlpy.drop_sproc(name)
output_params = {"out_df": DataFrame}
sqlpy.create_sproc_from... | 9788fa3d3403f987a2dd300d3673e2165f1fd611 | 79,229 |
def env(belt_ts, samplerate, out_samplerate, window=10, lags=(0,)):
"""Calculate respiratory pattern variability across a sliding window.
Parameters
----------
belt_ts : (X,) :obj:`numpy.ndarray`
A 1D array with the respiratory belt time series.
samplerate : :obj:`float`
Sampling ra... | c32bbbc254e29bdbf22d99c580df0aad1d827fdc | 79,230 |
def nullsink(stream: Stream, *args, **kwargs) -> FilterableStream:
"""https://ffmpeg.org/ffmpeg-filters.html#nullsink"""
return filter(stream, nullsink.__name__, *args, **kwargs) | 8e91ea1a3bd6f6d8c152109522e7bc44661aa7aa | 79,231 |
import tempfile
import ctypes
def delta(f, s, d=None):
"""
Create a delta for the file `f` using the signature read from `s`. The delta
will be written to `d`. If `d` is omitted, a temporary file will be used.
This function returns the delta file `d`. All parameters must be file-like
objects.
... | 586cb251033a4f18535e3388451c3b6f8dc43552 | 79,232 |
def l1_divergence(a, b):
"""
The L1 di, a continuous valued norm between two arrays of the same shape.
"""
return np.sum(np.abs(a - b)) | 3e51579495ae15d9defa76ab14bda07a4f6611a8 | 79,234 |
def get_manual_glyphs(glyphs):
"""
From the glyph list, extract the Gamera ImageList of manual glyphs.
"""
# Prepare the training glyphs
training_glyphs = []
for glyph in glyphs:
if glyph['id_state_manual']:
# Get the gamera image
gamera_image = convert_to_gamera_... | 7f3327cafccc12945f684fc4db3cce467bc08048 | 79,235 |
import zipfile
def is_apk_file(filepath):
"""
Function to check if a file is an APK
Params:
- filepath (str): Path where is the file to check
Return:
True (bool) if the file is an APK
False (bool) otherwise
"""
try:
zip = zipfile.ZipFile(... | b859fa83539ce7ae455cfdbd52d42c89ab77c17d | 79,237 |
def best_prefix(bytes, system=NIST):
"""Return a bitmath instance representing the best human-readable
representation of the number of bytes given by ``bytes``. In addition
to a numeric type, the ``bytes`` parameter may also be a bitmath type.
Optionally select a preferred unit system by specifying the ``system``
... | 8ad91a538bf0aab21c61be7147f94687cd207077 | 79,238 |
def signal_to_noise(fname, col=1, method='var', fname_cov=''):
"""Return signal to noise ratio for WL measurements in file fname.
Parameters
----------
fname: string
Input file name
col: integer
Column number for signal, default=1
method: string
Noise method, 'var' (defa... | f86111248e368f4d0e4ba92e5184c0d433154820 | 79,239 |
def _app_oso():
"""Get the flask oso plugin for the current app instance."""
try:
return _app_context().oso_flask_oso
except AttributeError:
raise OsoError(
"No oso instance on current application. "
"Did you forget to call init_app?"
) | d48df0d973852ee2548080695ad716fff0fc11b7 | 79,240 |
def findClosestElements(arr, k, x):
"""
:type arr: List[int]
:type k: int
:type x: int
:rtype: List[int]
"""
lo, hi = 0, len(arr)-k
while lo < hi:
mid = (lo + hi)//2
if x-arr[mid] > arr[mid+k]-x:
lo = mid + 1
else:
hi = mid
return arr[l... | 066a40467b293a57852f0bbbce9415dc387e414e | 79,241 |
import re
import torch
def david_generate_single_program(question, program_generator, vocab, question_len=46):
""" Generate a single program from a given natural-language question using the provided model.
Parameters
----------
question : str
The question to produce a program from.
p... | 67125f701a513b20a671a182084548696eb490e0 | 79,242 |
def scrubbing(time_series, FD, thres=0.2):
"""
simple scrubbing strategy based on timepoint removal
"""
scrubbed_time_series = time_series.T[:, (FD < thres)]
return scrubbed_time_series.T | beacdde75494ad8e4a346657a18ca48bf5990996 | 79,243 |
from typing import cast
def get_all_actors(use_selection=False, actor_class=None, actor_tag=None, world=None):
"""
# use_selection: bool : True if you want to get only the selected actors
# actor_class: class unreal.Actor : The class used to filter the actors. Can be None if you do not want to use this fi... | 4300280086f7837a55b172c6fa9040fc7235e1d8 | 79,244 |
def idrs(A, b, x0=None, tol=1e-5, s=4, maxiter=None,
M=None, callback=None):
"""
Use Induced Dimension Reduction method [IDR(s)] to solve A x = b
Parameters
----------
A : {sparse matrix, dense matrix, LinearOperator}
The real or complex N-by-N matrix of the linear system.
b : ... | 0a0641d85bed334b3654f2a222551247e02bd865 | 79,245 |
def create_instructions_writer(entity, iso_request, rack_containers,
parent=None):
"""
Factory method returning the :class:`_InstructionsWriter` for the passed
entity.
:param entity: The ISO or the ISO job for which to generate the summary.
:type entity: :class:`LabIs... | 73e5c5f20caadfad0b8c3a5b6fc65475b776f07b | 79,246 |
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