content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def import_odim_hdf5(filename, **kwargs):
"""Import a precipitation field (and optionally the quality field) from a
HDF5 file conforming to the ODIM specification.
Parameters
----------
filename : str
Name of the file to import.
Other Parameters
----------------
qty : {'RATE', ... | 650875bb3d04627f4570507892ee26b42912c39e | 3,641,329 |
def sugerir(update: Update, _: CallbackContext) -> int:
"""Show new choice of buttons"""
query = update.callback_query
query.answer()
keyboard = [
[
InlineKeyboardButton("\U0001F519 Volver", callback_data=str(NINE)),
InlineKeyboardButton("\U0001F44B Salir", callba... | e278c6bdab82e4fdfc38c7a4bb58a5511a003515 | 3,641,330 |
def clone_subgraph(*, outputs, inputs, new_inputs, suffix="cloned"):
"""
Take all of the tensorflow nodes between `outputs` and `inputs` and clone
them but with `inputs` replaced with `new_inputs`.
Args:
outputs (List[tf.Tensor]): list of output tensors
inputs (List[tf.Tensor]): list of... | b61d73d79635551f8277cbc0c2da97d0c5c2908e | 3,641,331 |
async def refresh_replacements(db, sample_id: str) -> list:
"""
Remove sample file `replacement` fields if the linked files have been deleted.
:param db: the application database client
:param sample_id: the id of the sample to refresh
:return: the updated files list
"""
files = await virt... | 43667801bf6bb96edbeb59bf9d538b62c9bf9785 | 3,641,332 |
def torch_model (model_name, device, checkpoint_path = None):
""" select imagenet models by their name and loading weights """
if checkpoint_path:
pretrained = False
else:
pretrained = True
model = models.__dict__ [model_name](pretrained)
if hasattr (model, 'classifier'):
... | 831cf1edd83b76049e7f6d60434961cbd44e4bd9 | 3,641,333 |
from typing import Tuple
from datetime import datetime
def get_timezone() -> Tuple[datetime.tzinfo, str]:
"""Discover the current time zone and it's standard string representation (for source{d})."""
dt = get_datetime_now().astimezone()
tzstr = dt.strftime("%z")
tzstr = tzstr[:-2] + ":" + tzstr[-2:]
... | f73cedb8fb91c75a19104d4d8bef29f73bfb9b1a | 3,641,334 |
def get_timed_roadmaps_grid_common(
ins: Instance, T: int, size: int,
) -> list[TimedRoadmap]:
"""[deprecated] get grid roadmap shared by all agents
Args:
ins (Instance): instance
T (int): assumed makespan
size (int): size x size grid will be constructed
Returns:
list[n... | 9b8e283ad66db35132393b53af2bfa36fc4aaf83 | 3,641,337 |
def arithmetic_series(a: int, n: int, d: int = 1) -> int:
"""Returns the sum of the arithmetic sequence with parameters a, n, d.
a: The first term in the sequence
n: The total number of terms in the sequence
d: The difference between any two terms in the sequence
"""
return n * (2 * a + (n - 1... | 168f0b07cbe6275ddb54c1a1390b41a0f340b0a6 | 3,641,338 |
import re
def get_arc_proxy_user(proxy_file=None):
"""
Returns the owner of the arc proxy. When *proxy_file* is *None*, it defaults to the result of
:py:func:`get_arc_proxy_file`. Otherwise, when it evaluates to *False*, ``arcproxy`` is queried
without a custom proxy file.
"""
out = _arc_proxy... | 01f1040cd1217d7722a691a78b5884125865cf39 | 3,641,339 |
def pass_hot_potato(names, num):
"""Pass hot potato.
A hot potato is sequentially passed to ones in a queue line.
After a number of passes, the one who got the hot potato is out.
Then the passing hot potato game is launched againg,
until the last person is remaining one.
"""
name_queue = Queue()
for name in n... | f78a635bdf3138809329ef8ad97934b125b9335a | 3,641,340 |
import copy
def convert_timeseries_dataframe_to_supervised(df: pd.DataFrame, namevars, target, n_in=1, n_out=0, dropT=True):
"""
Transform a time series in dataframe format into a supervised learning dataset while
keeping dataframe intact.
Returns the transformed pandas DataFrame, the name of the targ... | b62296680f6a871f20078e55eefa20f09392b012 | 3,641,341 |
def build_graph(adj_mat):
"""build sparse diffusion graph. The adjacency matrix need to preserves divergence."""
# sources, targets = adj_mat.nonzero()
# edgelist = list(zip(sources.tolist(), targets.tolist()))
# g = Graph(edgelist, edge_attrs={"weight": adj_mat.data.tolist()}, directed=True)
g = Gr... | bdc8dc5d1c107086c4c548b500f6958bdbe48103 | 3,641,342 |
def retrieve_context_path_comp_service_end_point_end_point(uuid): # noqa: E501
"""Retrieve end-point
Retrieve operation of resource: end-point # noqa: E501
:param uuid: ID of uuid
:type uuid: str
:rtype: List[str]
"""
return 'do some magic!' | e3169e139b5992daf00411b694cf77436fb17fba | 3,641,343 |
def get_external_repos(gh):
"""
Get all external repositories from the `repos.config` file
"""
external_repos = []
with open("repos.config") as f:
content = f.readlines()
content = [x.strip() for x in content]
for entry in content:
org_name, repo_name = entry.sp... | a83515acd77c7ef9e30bf05d8d4478fa833ab5bc | 3,641,344 |
import json
def load_fit_profile():
"""
This methods return the FIT profile types based on the Profile.xslx that is included in the Garmin FIT SDK (https://developer.garmin.com/fit/download/).
The returned profile can be used to translate e.g. Garmin product names to their corresponding integer product id... | 13108546c2d88d77d090b222c1b3ff2b59208310 | 3,641,346 |
def mmethod(path, *args, **kwargs):
"""
Returns a mapper function that runs the path method for each instance of
the iterable collection.
>>> mmethod('start')
is equivalent to
>>> lambda thread: thread.start()
>>> mmethod('book_set.filter', number_of_pages__gte=100)
is equivalent to
... | 6ded620d190d338d981c433514018a4182b7e207 | 3,641,347 |
def generate_test_demand_design_image() -> TestDataSet:
"""
Returns
-------
test_data : TestDataSet
2800 points of test data, uniformly sampled from (price, time, emotion). Emotion is transformed into img.
"""
org_test: TestDataSet = generate_test_demand_design(False)
treatment = org... | 238cf11480e0d23f30b426ed19877126edc010fa | 3,641,348 |
def value_iteration(game, depth_limit, threshold):
"""Solves for the optimal value function of a game.
For small games only! Solves the game using value iteration,
with the maximum error for the value function less than threshold.
This algorithm works for sequential 1-player games or 2-player zero-sum
games,... | 2a9ae3903666ee16e86fe30a0458707394fe4695 | 3,641,349 |
def _import_and_infer(save_dir, inputs):
"""Import a SavedModel into a TF 1.x-style graph and run `signature_key`."""
graph = ops.Graph()
with graph.as_default(), session_lib.Session() as session:
model = loader.load(session, [tag_constants.SERVING], save_dir)
signature = model.signature_def[
sign... | 1610c4d52fa8d18a770f1f347b9cd30b4652ab8b | 3,641,351 |
def nth(seq, idx):
"""Return the nth item of a sequence. Constant time if list, tuple, or str;
linear time if a generator"""
return get(seq, idx) | cca44dca33d19a2e0db355be525009dce752445c | 3,641,354 |
def _build_discretize_fn(value_type, stochastic, beta):
"""Builds a `tff.tf_computation` for discretization."""
@computations.tf_computation(value_type, tf.float32, tf.float32)
def discretize_fn(value, scale_factor, prior_norm_bound):
return _discretize_struct(value, scale_factor, stochastic, beta,
... | 75f9f50ec376b1a10b5fcb629527a873b8768235 | 3,641,356 |
def expand_mapping_target(namespaces, val):
"""Expand a mapping target, expressed as a comma-separated list of
CURIE-like strings potentially prefixed with ^ to express inverse
properties, into a list of (uri, inverse) tuples, where uri is a URIRef
and inverse is a boolean."""
vals = [v.strip() for... | b4a4f08d39728c8f61b7b373a521890f88d6f912 | 3,641,357 |
def home(request):
"""Handle the default request, for when no endpoint is specified."""
return Response('This is Michael\'s REST API!') | a37a2eaa68366de4d8542357c043c4e29ac7a9f9 | 3,641,358 |
def create_message(sender, to, subject, message_text, is_html=False):
"""Create a message for an email.
Args:
sender: Email address of the sender.
to: Email address of the receiver.
subject: The subject of the email message.
message_text: The text of the email message.
Returns:
... | 2b5dc225df5786df9f2650631d209c53e3e8145b | 3,641,359 |
def get_agent(runmode, name): # noqa: E501
"""get_agent
# noqa: E501
:param runmode:
:type runmode: str
:param name:
:type name: str
:rtype: None
"""
return 'do some magic!' | 065302bb7793eff12973208db5f35f3494a83930 | 3,641,360 |
def find_splits(array1: list, array2: list) -> list:
"""Find the split points of the given array of events"""
keys = set()
for event in array1:
keys.add(event["temporalRange"][0])
keys.add(event["temporalRange"][1])
for event in array2:
keys.add(event["temporalRange"][0])
... | c52f696caddf35fa050621e7668eec06686cee14 | 3,641,361 |
def to_subtask_dict(subtask):
"""
:rtype: ``dict``
"""
result = {
'id': subtask.id,
'key': subtask.key,
'summary': subtask.fields.summary
}
return result | 5171d055cc693b1aa00976c063188a907a7390dc | 3,641,362 |
from typing import Tuple
from typing import Optional
def _partition_labeled_span(
contents: Text, labeled_span: substitution.LabeledSpan
) -> Tuple[substitution.LabeledSpan, Optional[substitution.LabeledSpan],
Optional[substitution.LabeledSpan]]:
"""Splits a labeled span into first line, intermediate... | 6f22341d32c03ba0057fbfd6f08c88ac8736220f | 3,641,363 |
def is_active(relation_id: RelationID) -> bool:
"""Retrieve an activation record from a relation ID."""
# query to DB
try:
sups = db.session.query(RelationDB) \
.filter(RelationDB.supercedes_or_suppresses == int(relation_id)) \
.first()
except Exception as e:
rais... | 352f44e2f025ac0918519d0fe8e513b3871be7b9 | 3,641,364 |
def vectorize_with_similarities(text, vocab_tokens, vocab_token_to_index, vocab_matrix):
"""
Generate a vector representation of a text string based on a word similarity matrix. The resulting vector has
n positions, where n is the number of words or tokens in the full vocabulary. The value at each position indicate... | 5b843ffbfdefbf691fb5766bbe6772459568cf78 | 3,641,365 |
def get_puppet_node_cert_from_server(node_name):
"""
Init environment to connect to Puppet Master and retrieve the certificate for that node in the server (if exists)
:param node_name: Name of target node
:return: Certificate for that node in Puppet Master or None if this information has not been found
... | 7f7fa2164bf7f289ce9dbc1b35f2d8aea546bb60 | 3,641,366 |
from typing import Optional
def get_notebook_workspace(account_name: Optional[str] = None,
notebook_workspace_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> Awaitabl... | d9020323c0ea520951730a31b2f457ab80fcc931 | 3,641,367 |
def get_current_player(player_one_turn: bool) -> str:
"""Return 'player one' iff player_one_turn is True; otherwise, return
'player two'.
>>> get_current_player(True)
'player one'
>>> get_current_player(False)
'player two'
"""
if player_one_turn:
return P1
else:
retu... | 6bade089054513943aef7656972cadd2d242807c | 3,641,368 |
def is_word(s):
""" String `s` counts as a word if it has at least one letter. """
for c in s:
if c.isalpha(): return True
return False | 524ed5cc506769bd8634a46d346617344485e5f7 | 3,641,370 |
def index_all_messages(empty_index):
"""
Expected index of `initial_data` fixture when model.narrow = []
"""
return dict(empty_index, **{'all_msg_ids': {537286, 537287, 537288}}) | ea2c59a4de8e62d2293f87e26ead1b4c15f15a11 | 3,641,371 |
def compute_affine_matrix(in_shape,
out_shape,
crop=None,
degrees=0.0,
translate=(0.0, 0.0),
flip_h=False,
flip_v=False,
resize=False,
... | 0c3786c44d35341e5e85d3756e50eb59dd473d64 | 3,641,372 |
def Bern_to_Fierz_nunu(C,ddll):
"""From semileptonic Bern basis to Fierz semileptonic basis for Class V.
C should be the corresponding leptonic Fierz basis and
`ddll` should be of the form 'sbl_enu_tau', 'dbl_munu_e' etc."""
ind = ddll.replace('l_','').replace('nu_','')
return {
'F' + in... | 4f08f79d6614c8929c3f42096fac71b04bfe7b4b | 3,641,373 |
def enforce_boot_from_volume(client):
"""Add boot from volume args in create server method call
"""
class ServerManagerBFV(servers.ServerManager):
def __init__(self, client):
super(ServerManagerBFV, self).__init__(client)
self.bfv_image_client = images.ImageManager(client)
... | 4ae4d2624f216c96722e811d9d44cb04caa46e1d | 3,641,374 |
def img_to_yuv(frame, mode, grayscale=False):
"""Change color space of `frame` from any supported `mode` to YUV
Args:
frame: 3-D tensor in either [H, W, C] or [C, H, W]
mode: A string, must be one of [YV12, YV21, NV12, NV21, RGB, BGR]
grayscale: discard uv planes
return:
... | 002506b3a46fa6b601f4ca65255c8f06b990992d | 3,641,375 |
def assemblenet_kinetics600() -> cfg.ExperimentConfig:
"""Video classification on Videonet with assemblenet."""
exp = video_classification.video_classification_kinetics600()
feature_shape = (32, 224, 224, 3)
exp.task.train_data.global_batch_size = 1024
exp.task.validation_data.global_batch_size = 32
exp.ta... | 3356b6ea758baf04cc98421d700f25e342884d5a | 3,641,376 |
import math
import torch
def channel_selection(inputs, module, sparsity=0.5, method='greedy'):
"""
현재 모듈의 입력 채널중, 중요도가 높은 채널을 선택합니다.
기존의 output을 가장 근접하게 만들어낼 수 있는 입력 채널을 찾아냅니댜.
:param inputs: torch.Tensor, input features map
:param module: torch.nn.module, layer
:param sparsity: float, 0 ~ 1 h... | 957cbcc799185fd6c2547662bfe79205389d44da | 3,641,377 |
import six
def format_host(host_tuple):
"""
Format a host tuple to a string
"""
if isinstance(host_tuple, (list, tuple)):
if len(host_tuple) != 2:
raise ValueError('host_tuple has unexpeted length: %s' % host_tuple)
return ':'.join([six.text_type(s) for s in host_t... | f4822aec5143a99ccc52bb2657e1f42477c65400 | 3,641,378 |
import psutil
def get_cpu_stats():
"""
Obtains the system's CPU status.
:returns: System CPU static.
"""
return psutil.cpu_stats() | f538977db72083f42c710faa987a97511959c973 | 3,641,379 |
def get_minmax_array(X):
"""Utility method that returns the boundaries for each feature of the input array.
Args:
X (np.float array of shape (num_instances, num_features)): The input array.
Returns:
min (np.float array of shape (num_features,)): Minimum values for each feature in array.
... | 5453371759af5bf6d876aa8fe5d2caf88ee6eb08 | 3,641,383 |
def getAllHeaders(includeText=False):
"""
Get a dictionary of dream numbers and headers. If includeText=true, also
add the text of the dream to the dictionary as 'text' (note that this key
is all lowercase so it will not conflict with the usual convention for
header names, even if "Text" would be an... | 2bbd78d9c9cbfaa50a62e99c25148844d7c5e330 | 3,641,384 |
def zscore(arr, period):
"""
ZScore transformation of `arr` for rolling `period.` ZScore = (X - MEAN(X)) / STDEV(X)
:param arr:
:param period:
:return:
"""
if period <= 0:
raise YaUberAlgoArgumentError("'{}' must be positive number".format(period))
# Do quick sanity checks of a... | 8a49afe3ecefc326b3bd889279085cccd1d19a61 | 3,641,385 |
import glob
import pandas
def _load_event_data(prefix, name):
"""Load per-event data for one single type, e.g. hits, or particles.
"""
expr = '{!s}-{}.csv*'.format(prefix, name)
files = glob.glob(expr)
dtype = DTYPES[name]
if len(files) == 1:
return pandas.read_csv(files[0], header=0, ... | 04b2e4a7483ba56fdd282dc6355e9acb2d6da7b1 | 3,641,386 |
from datetime import datetime
def check_file(file_id: str, upsert: bool = False) -> File:
"""Checks that the file with file_id exists in the DB
Args:
file_id: The id for the requested file.
upsert: If the file doesn't exist create a placeholder file
Returns:
The file object
... | 2f4e94a064d0bdfea8f001855eb39675f78ab6e5 | 3,641,387 |
def parse(volume_str):
"""Parse combined k8s volume string into a dict.
Args:
volume_str: The string representation for k8s volume,
e.g. "claim_name=c1,mount_path=/path1".
Return:
A Python dictionary parsed from the given volume string.
"""
kvs = volume_str.split(",")
... | f6984faf90081eb8ca3fbbb8ffaf636b040c7ffc | 3,641,388 |
def longest_common_substring(text1, text2):
"""最长公共子字符串，区分大小写"""
n = len(text1)
m = len(text2)
maxlen = 0
span1 = (0, 0)
span2 = (0, 0)
if n * m == 0:
return span1, span2, maxlen
dp = np.zeros((n+1, m+1), dtype=np.int32)
for i in range(1, n+1):
for j in range(1, m+1)... | ed892739d22ee0763a2fe5dd44b48b8d1902605e | 3,641,389 |
def make_subclasses_dict(cls):
"""
Return a dictionary of the subclasses inheriting from the argument class.
Keys are String names of the classes, values the actual classes.
:param cls:
:return:
"""
the_dict = {x.__name__:x for x in get_all_subclasses(cls)}
the_dict[cls.__name__] = cls
... | 36eb7c9242b83a84fcd6ee18b4ca9297038f9ee6 | 3,641,390 |
import time
def _parse_realtime_data(xmlstr):
"""
Takes xml a string and returns a list of dicts containing realtime data.
"""
doc = minidom.parseString(xmlstr)
ret = []
elem_map = {"LineID": "id", "DirectionID": "direction",
"DestinationStop": "destination" }
ack = _singl... | 90958c7f66072ecfd6c57b0da95293e35196354c | 3,641,391 |
def tocopo_accuracy_fn(tocopo_logits: dt.BatchedTocopoLogits,
target_data: dt.BatchedTrainTocopoTargetData,
oov_token_id: int,
pad_token_id: int,
is_distributed: bool = True) -> AccuracyMetrics:
"""Computes accuracy metrics.
... | 828b7d3db40d488a7e05bbfe1f3d2d94f58d8efa | 3,641,392 |
def cols_from_html_tbl(tbl):
""" Extracts columns from html-table tbl and puts columns in a list.
tbl must be a results-object from BeautifulSoup)"""
rows = tbl.tbody.find_all('tr')
if rows:
for row in rows:
cols = row.find_all('td')
for i,cell in enumerate(cols):
... | 94bef05b782073955738cf7b774af34d64520499 | 3,641,393 |
from typing import List
from typing import Tuple
def get_score_park(board: List[List[str]]) -> Tuple[int]:
"""
Calculate the score for the building - park (PRK).
Score 1: If ONLY 1 park.
Score 3: If the park size is 2.
Score 8: If the park size is 3.
Score 16: If the par... | 2bf1629aeb9937dfd871aa118e675cd9358b65ef | 3,641,394 |
def kernel_epanechnikov(inst: np.ndarray) -> np.ndarray:
"""Epanechnikov kernel."""
if inst.ndim != 1:
raise ValueError("'inst' vector must be one-dimensional!")
return 0.75 * (1.0 - np.square(inst)) * (np.abs(inst) < 1.0) | 7426e068c3a939595b77c129af4f8d30bbfc89fb | 3,641,395 |
def submission_parser(reddit_submission_object):
"""Parses a submission and returns selected parameters"""
post_timestamp = reddit_submission_object.created_utc
post_id = reddit_submission_object.id
score = reddit_submission_object.score
ups = reddit_submission_object.ups
downs = reddit_submiss... | d2b406f38e799230474e918df91d55e48d27f385 | 3,641,396 |
def dashboard():
"""Displays dashboard to logged in user"""
user_type = session.get('user_type')
user_id = session.get('user_id')
if user_type == None:
return redirect ('/login')
if user_type == 'band':
band = crud.get_band_by_id(user_id)
display_name = band.display... | 1cec9fcd17a963921f23f03478a8c3195db9a18e | 3,641,397 |
from bs4 import BeautifulSoup
def parse_site(site_content, gesture_id):
""" Parses the following attributes:
title, image, verbs and other_gesture_ids
:param site_content: a html string
:param gesture_id: the current id
:return: {
title: str,
img: str,
id: number,
compares... | b9719dbbd2ca7883257c53410423de5e3df3fe93 | 3,641,398 |
from multiprocessing import Pool
import multiprocessing
def test_multiprocessing_function () :
"""Test parallel processnig with multiprocessing
"""
logger = getLogger ("ostap.test_multiprocessing_function")
logger.info ('Test job submission with module %s' % multiprocessing )
ncpus = mu... | a59635b844b4ff80a090a1ec8e3661e340903269 | 3,641,399 |
import math
def fnCalculate_Bistatic_Coordinates(a,B):
"""
Calculate the coordinates of the target in the bistatic plane
A,B,C = angles in the triangle
a,b,c = length of the side opposite the angle
Created: 22 April 2017
"""
u = a*math.cos(B);
v = a*math.sin(B);
return u,v | cc1dce6ef0506b987e42e3967cf36ea7b46a30d7 | 3,641,400 |
def _fn_lgamma_ ( self , b = 1 ) :
""" Gamma function: f = log(Gamma(ab))
>>> f =
>>> a = f.lgamma ( )
>>> a = f.lgamma ( b )
>>> a = lgamma ( f )
"""
return _fn_make_fun_ ( self ,
b ,
Os... | 62183327967840e26dfc009c2357de2c31171082 | 3,641,401 |
def convolve_smooth(x, win=10, mode="same"):
"""Smooth data using a given window size, in units of array elements, using
the numpy.convolve function."""
return np.convolve(x, np.ones((win,)), mode=mode) / win | b41edf8c0d58355e28b507a96b129c4720412a81 | 3,641,402 |
import array
def descent(x0, fn, iterations=1000, gtol=10**(-6), bounds=None, limit=0, args=()):
"""A gradient descent optimisation solver.
Parameters
----------
x0 : array-like
n x 1 starting guess of x.
fn : obj
The objective function to minimise.
iterations : int
Ma... | ec132e7857cf4a941c54fc5db9085bdf013fb7a2 | 3,641,404 |
def count_teams_for_party(party_id: PartyID) -> int:
"""Return the number of orga teams for that party."""
return db.session \
.query(DbOrgaTeam) \
.filter_by(party_id=party_id) \
.count() | 07373325dd7d7ab21ef0cb1145d37b2d85292358 | 3,641,405 |
def num_series(datetime_series) -> pd.Series:
"""Return a datetime series with numeric values."""
return datetime_series(LENGTH) | 4d208bfbae5f3e7263663d06102aa0b290f4fd4e | 3,641,406 |
import re
def obtain_ranks(outputs, targets, mode=0):
"""
outputs : tensor of size (batch_size, 1), required_grad = False, model predictions
targets : tensor of size (batch_size, ), required_grad = False, labels
Assume to be of format [1, 0, ..., 0, 1, 0, ..., 0, ..., 0]
mode == 0: rank from ... | 72fc737d72fe0d6d3ff4e08a5a16acf05e0e88cb | 3,641,407 |
from typing import Dict
from typing import Any
def sample_a2c_params(trial: optuna.Trial) -> Dict[str, Any]:
"""
Sampler for A2C hyperparams.
"""
lr_schedule = trial.suggest_categorical("lr_schedule", ["linear", "constant"])
learning_rate = trial.suggest_loguniform("learning_rate", 1e-5, 1)
n_... | f9f966f3c41a32a15253ba612d94e1254a586e86 | 3,641,408 |
def location_parser(selected_variables, column):
"""
Parse the location variable by creating a list of tuples.
Remove the hyphen between the start/stop positions. Convert all elements to
integers and create a list of tuples.
Parameters:
selected_variables (dataframe): The dataframe contain... | 106f669269276c37652e92e62eb8c2c52dfe7637 | 3,641,409 |
import torch
import math
def get_qmf_bank(h, n_band):
"""
Modulates an input protoype filter into a bank of
cosine modulated filters
Parameters
----------
h: torch.Tensor
prototype filter
n_band: int
number of sub-bands
"""
k = torch.arange(n_band).reshape(-1, 1)
... | 87e8cf3b0d85a6717cce9dc09f7a0a3e3581e498 | 3,641,410 |
import math
def compare_one(col, cons_aa, aln_size, weights, aa_freqs, pseudo_size):
"""Compare column amino acid frequencies to overall via G-test."""
observed = count_col(col, weights, aa_freqs, pseudo_size)
G = 2 * sum(obsv * math.log(obsv / aa_freqs.get(aa, 0.0))
for aa, obsv in observ... | 910431062ac9ddef467d4818d3960385a2d4392b | 3,641,411 |
def open(uri, mode='a', eclass=_eclass.manifest):
"""Open a Blaze object via an `uri` (Uniform Resource Identifier).
Parameters
----------
uri : str
Specifies the URI for the Blaze object. It can be a regular file too.
The URL scheme indicates the storage type:
* carray: Ch... | c0a5069f5d7f39c87aae5af361df86b6f4fc4189 | 3,641,412 |
def create_df(dic_in, cols, input_type):
"""
Convert JSON output from OpenSea API to pandas DataFrame
:param dic_in: JSON output from OpenSea API
:param cols: Keys in JSON output from OpenSea API
:param input_type: <TBD> save the columns with dictionaries as entries seperately
:return: Cleaned D... | 7b6a9445c956cc5d2850516d4c7dc2208b7391f7 | 3,641,413 |
def file_updated_at(file_id, db_cursor):
"""
Update the last time the file was checked
"""
db_cursor.execute(queries.file_updated_at, {'file_id': file_id})
db_cursor.execute(queries.insert_log, {'project_id': settings.project_id, 'file_id': file_id,
'log_ar... | bb0ec859c249b96e3ed066c3664e792100f5f23c | 3,641,414 |
def action_to_upper(action):
"""
action to upper receives an action in pddl_action_representation, and returns it in upper case.
:param action: A action in PddlActionRepresentation
:return: PddlActionRepresentation: The action in upper case
"""
if action:
action.name = action.name.uppe... | e9266ad79d60a58bf61d6ce81284fa2accbb0b8d | 3,641,415 |
from typing import Type
from typing import Dict
from typing import Any
def generate_model_example(model: Type["Model"], relation_map: Dict = None) -> Dict:
"""
Generates example to be included in schema in fastapi.
:param model: ormar.Model
:type model: Type["Model"]
:param relation_map: dict wit... | 1aafb069ff129453f9012de79d09c326224ceb5b | 3,641,417 |
def compare_folder(request):
""" Creates the compare folder path `dione-sr/tests/data/test_name/compare`.
"""
return get_test_path('compare', request) | b78bc261373d47bd3444c24c54c57a600a3855ad | 3,641,418 |
def _get_param_combinations(lists):
"""Recursive function which generates a list of all possible parameter values"""
if len(lists) == 1:
list_p_1 = [[e] for e in lists[0]]
return list_p_1
list_p_n_minus_1 = _get_param_combinations(lists[1:])
list_p_1 = [[e] for e in lists[0]]
list_... | b4903bea79aebeabf3123f03de986058a06a21f4 | 3,641,419 |
def system_mass_spring_dumper():
"""マスバネダンパ系の設計例"""
# define the system
m = 1.0
k = 1.0
c = 1.0
A = np.array([
[0.0, 1.0],
[-k/m, -c/m]
])
B = np.array([
[0],
[1/m]
])
C = np.eye(2)
D = np.zeros((2,1),dtype=float)
W = np.diag([1.0, 1.0])
... | 8a054753d7bbaa06b7217ce98d38074122d41f32 | 3,641,420 |
import requests
def get_green_button_xml(
session: requests.Session, start_date: date, end_date: date
) -> str:
"""Download Green Button XML."""
response = session.get(
f'https://myusage.torontohydro.com/cassandra/getfile/period/custom/start_date/{start_date:%m-%d-%Y}/to_date/{end_date:%m-%d-%Y}/f... | 2ed71202a40214b75007db7b16d5c1806ae35406 | 3,641,422 |
def calculateSecFromEpoch(date,hour):
"""
Calculates seconds from EPOCH
"""
months={
'01':'Jan',
'02':'Feb',
'03':'Mar',
'04':'Apr',
'05':'May',
'06':'Jun',
'07':'Jul',
'08':'Aug',
'09':'Sep',
'10':'Oct',
'11':'Nov',
'12':'Dec'
}
year=YEAR_PREFIX+date[0:2]
month=months[date[2:4]]
day=d... | 29adf78dbe795c70cb84f66b1dc249674869c417 | 3,641,423 |
def star_noise_simulation(Variance, Pk, nongaussian = False):
"""simulates star + noise signal, Pk is hyperprior on star variability and flat at high frequencies which is stationary noise"""
Pk_double = np.concatenate((Pk, Pk))
phases = np.random.uniform(0, 2 * np.pi, len(Pk))
nodes0 = np.sqrt(Pk_double... | 5ccc89f455b7347c11cac36abead172b352f7b9c | 3,641,424 |
from datetime import datetime
import time
def get_seq_num():
"""
Simple class for creating sequence numbers
Truncate epoch time to 7 digits which is about one month
"""
t = datetime.datetime.now()
mt = time.mktime(t.timetuple())
nextnum = int(mt)
retval = nextnum % 10000000
return ... | 34a2b3a7082d061987c7a0b67c91df040b86938c | 3,641,425 |
import logging
def get_packages_for_file_or_folder(source_file, source_folder):
"""
Collects all the files based on given parameters. Exactly one of the parameters has to be specified.
If source_file is given, it will return with a list containing source_file.
If source_folder is given, it will searc... | fc047dd10dfd18fc8efecb240d06aeb91686c0cb | 3,641,426 |
def sanitize_tag(tag: str) -> str:
"""Clean tag by replacing empty spaces with underscore.
Parameters
----------
tag: str
Returns
-------
str
Cleaned tag
Examples
--------
>>> sanitize_tag(" Machine Learning ")
"Machine_Learning"
"""
return tag.strip().rep... | 40ac78846f03e8b57b5660dd246c8a15fed8e008 | 3,641,427 |
def _vmf_normalize(kappa, dim):
"""Compute normalization constant using built-in numpy/scipy Bessel
approximations.
Works well on small kappa and mu.
"""
num = np.power(kappa, dim / 2.0 - 1.0)
if dim / 2.0 - 1.0 < 1e-15:
denom = np.power(2.0 * np.pi, dim / 2.0) * i0(kappa)
else:
... | 24d22469a572e7ff4b7e1c918fce7001731cec2a | 3,641,428 |
import urllib
def twitter_map():
"""
Gets all the required information and returns the start page or map with
people locations depending on input
"""
# get arguments from url
account = request.args.get('q')
count = request.args.get('count')
if account and count:
# create map a... | 54a37f91141e52d24f88214ea476a2f199c78674 | 3,641,429 |
def path_states(node):
"""The sequence of states to get to this node."""
if node in (cutoff, failure, None):
return []
return path_states(node.parent) + [node.state] | 21ed5eb98eca0113dd5f446066cd10df73665f10 | 3,641,430 |
def find_named_variables(mapping):
"""Find correspondance between variable and relation and its attribute."""
var_dictionary = dict()
for relation_instance in mapping.lhs:
for i, variable in enumerate(relation_instance.variables):
name = relation_instance.relation.name
field ... | 0b9a78ca94b25e7a91fe88f0f15f8a8d408cb2fd | 3,641,431 |
import urllib
def attribute_formatter(attribute):
""" translate non-alphabetic chars and 'spaces' to a URL applicable format
:param attribute: text string that may contain not url compatible chars (e.g. ' 무작위의')
:return: text string with riot API compatible url encoding (e.g. %20%EB%AC%B4%EC%9E%91%EC%9C%8... | 6c6745a5cea9a3f6bcee8cbcedb7a1493372dc96 | 3,641,432 |
import json
def maestro_splits():
"""
Get list of indices for each split. Stolen from my work on Perceptual
Evaluation of AMT Resynthesized.
Leve here for reference.
"""
d = asmd.Dataset().filter(datasets=['Maestro'])
maestro = json.load(open(MAESTRO_JSON))
train, validation, test = ... | 119b033d3fd507b77bbb3d16d993237f8658b5f5 | 3,641,434 |
def get_choice_selectivity(trials, perf, r):
"""
Compute d' for choice.
"""
N = r.shape[-1]
L = np.zeros(N)
L2 = np.zeros(N)
R = np.zeros(N)
R2 = np.zeros(N)
nL = 0
nR = 0
for n, trial in enumerate(trials):
if not perf.decisions[n]:
continue
... | f33593ad06bf3c54c950eda562a93e348320a5e1 | 3,641,435 |
def author_productivity(pub2author_df, colgroupby = 'AuthorId', colcountby = 'PublicationId', show_progress=False):
"""
Calculate the total number of publications for each author.
Parameters
----------
pub2author_df : DataFrame, default None, Optional
A DataFrame with the author2publication... | 15c56b22cc9d5014fe4dcfab8be37a9e4b0ef329 | 3,641,436 |
def smoothed_epmi(matrix, alpha=0.75):
"""
Performs smoothed epmi.
See smoothed_ppmi for more info.
Derived from this:
#(w,c) / #(TOT)
--------------
(#(w) / #(TOT)) * (#(c)^a / #(TOT)^a)
==>
#(w,c) / #(TOT)
--------------
(#(w) * #(c)^a) / #(TOT)^(a+1))
==>
#(w,c)
... | e2f72c4169aee2f394445f42e4835f1b55f347c9 | 3,641,437 |
import six
def encode(input, errors='strict'):
""" convert from unicode text (with possible UTF-16 surrogates) to wtf-8
encoded bytes. If this is a python narrow build this will actually
produce UTF-16 encoded unicode text (e.g. with surrogates).
"""
# method to convert surrogate pairs t... | 525199690f384304a72176bd1eaeeb1b9cb30880 | 3,641,438 |
def forgot_password(request, mobile=False):
"""Password reset form. This view sends an email with a reset link.
"""
if request.method == "POST":
form = PasswordResetForm(request.POST)
valid = form.is_valid()
if valid:
form.save(use_https=request.is_secure(),
... | ea27378253a7ed1b98cb91fd52fe724e79f35e26 | 3,641,439 |
def rotation_components(x, y, eps=1e-12, costh=None):
"""Components for the operator Rotation(x,y)
Together with `rotation_operator` achieves best memory complexity: O(N_batch * N_hidden)
Args:
x: a tensor from where we want to start
y: a tensor at which we want to finish
... | 79cec86425bce65ac92ce8cf9c720f98857d7e1a | 3,641,440 |
def erode(np_image_bin, struct_elem='rect', size=3):
"""Execute erode morphological operation on binaryzed image
Keyword argument:
np_image_bin -- binaryzed image
struct_elem:
cross - cross structural element
rect - rectangle structural element
circ -- cricle structural element(... | 4692b40555a8047d70ad8c4b33de636a0c6c87b0 | 3,641,441 |
def setup_counter_and_timer(nodemap):
"""
This function configures the camera to setup a Pulse Width Modulation signal using
Counter and Timer functionality. By default, the PWM signal will be set to run at
50hz, with a duty cycle of 70%.
:param nodemap: Device nodemap.
:type nodemap: INodeMap... | 9874b17ce49aca766504891bd9828aad1e075e21 | 3,641,443 |
def concat(l1, l2):
""" Join two possibly None lists """
if l1 is None:
return l2
if l2 is None:
return l1
return l1 + l2 | 9e87bead7eedc4c47f665808b9e0222437bc01b5 | 3,641,444 |
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