content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def quasi_diagonalize(link):
"""sort clustered assets by distance"""
link = link.astype(int)
sort_idx = pd.Series([link[-1, 0], link[-1, 1]])
num_items = link[-1, 3] # idx of original items
while sort_idx.max() >= num_items:
sort_idx.index = list(range(0, sort_idx.shape[0] * 2, 2)) # make ... | 8f10f62d5f0b3dc7b8687134497dd42f183194b4 | 20,552 |
def keyword(variable):
"""
Verify that the field_name isn't part of know Python keywords
:param variable: String
:return: Boolean
"""
for backend in ADAPTERS:
if variable.upper() in ADAPTERS[backend]:
msg = (
f'Variable "{variable}" is a "{backend.upper()}" '
... | b1c6322d3ce3c9ee4bda4eff251af44ca3e2c699 | 20,554 |
import logging
import json
def gcp_api_main(request):
"""Responds to any HTTP request.
Args:
request (flask.Request): HTTP request object.
Returns:
The response text or any set of values that can be turned into a
Response object using
`make_response <http://flask.pocoo.org/... | 21ec4b1dba4ad6f5dac518a3907cd15579a0ba00 | 20,555 |
def box_area_3d(boxes: Tensor) -> Tensor:
"""
Computes the area of a set of bounding boxes, which are specified by its
(x1, y1, x2, y2, z1, z2) coordinates.
Arguments:
boxes (Union[Tensor, ndarray]): boxes for which the area will be computed. They
are expected to be in (x1, y1, ... | be8b3c4d58d301d2044e7cfe2844516933c1247f | 20,556 |
from sqlalchemy import create_mock_engine
import re
def mock_engine(dialect_name=None):
"""Provides a mocking engine based on the current testing.db.
This is normally used to test DDL generation flow as emitted
by an Engine.
It should not be used in other cases, as assert_compile() and
assert_sq... | d773a6e2cd0b2060e5dd66d5ec4e758ac7f1f504 | 20,557 |
def get_feedback_thread_reply_info_by_reply_to_id(reply_to_id):
"""Gets the domain object corresponding to the model which is fetched by
reply-to-id field.
Args:
reply_to_id: str. The reply_to_id to search for.
Returns:
FeedbackThreadReplyInfo or None. The corresponding domain object.
... | e27521030717a1dc15cd9e678dabafba86007f90 | 20,558 |
def _cross_correlations(n_states):
"""Returns list of crosscorrelations
Args:
n_states: number of local states
Returns:
list of tuples for crosscorrelations
>>> l = _cross_correlations(np.arange(3))
>>> assert l == [(0, 1), (0, 2), (1, 2)]
"""
l = n_states
cross_corr =... | c11c5655ba655a29991421c6627a3eaca4f7681d | 20,559 |
def select_interface(worker):
"""
It gets a worker interface channel to do something.
"""
interfaces = worker.interfaces_list()
if len(interfaces) == 0:
print ' Error. Worker without interface known.'
return -1
elif len(interfaces) == 1:
return 1
option = raw_input('... | 97d90670dd69d57b4e1f85df250a0abc56106fb6 | 20,560 |
def get_middle(arr):
"""
Get middle point ????
"""
n_val = np.array(arr.shape) / 2.0
n_int = n_val.astype(np.int0)
# print(n_int)
if n_val[0] % 2 == 1 and n_val[1] % 2 == 1:
return arr[n_int[0], n_int[1]]
if n_val[0] % 2 == 0 and n_val[1] % 2 == 0:
return np.average(arr[... | 9651bcadc991bbf7a0c635a8870356f422d43e7e | 20,561 |
def annotate_segmentation(image, segmentation):
"""Return annotated segmentation."""
annotation = AnnotatedImage.from_grayscale(image)
for i in segmentation.identifiers:
region = segmentation.region_by_identifier(i)
color = pretty_color()
annotation.mask_region(region.border.dilate()... | 2fadbe8d2339e37bea0dbfe054199002a3997b20 | 20,562 |
def get_champ_data(champ: str, tier: int, rank: int):
"""
Gives Champ Information by their champname, tier, and rank.
"""
champ_info = NewChampsDB()
try:
champ_info.get_data(champ, tier, rank)
champs_dict = {
"name": f"{champ_info.name}",
"released": champ_i... | 7d810fc5ced3d187c68533f42c2443ef8bec651b | 20,563 |
def serving_input_receiver_fn():
"""This is used to define inputs to serve the model.
Returns:
A ServingInputReciever object.
"""
csv_row = tf.placeholder(shape=[None], dtype=tf.string)
features, _ = _make_input_parser(with_target=False)(csv_row)
return tf.estimator.export.ServingInputReceiver(features... | bcc6f0c4050d40df114ba4e5d895524f736b463a | 20,565 |
import time
def offsetTimer():
"""
'Starts' a timer when called, returns a timer function that returns the
time in seconds elapsed since the timer was started
"""
start_time = time.monotonic()
def time_func():
return time.monotonic() - start_time
return time_func | 348105a408ccedd1fcb840b73d5a58dfd59dd8cc | 20,566 |
from typing import Callable
import functools
def find_resolution(func: Callable = None) -> Callable:
"""Decorator that gives the decorated function the image resolution."""
@functools.wraps(func)
def wrapper(self: MultiTraceChart, *args, **kwargs):
if 'width' not in kwargs:
kwargs['wi... | 70edffcec5ac772bd52cb819db589d26497fda87 | 20,568 |
def transform_spikes_to_isi(self, spikes, time_epoch, last_event_is_spike=False):
"""Convert spike times to data array, which is a suitable format for optimization.
Parameters
----------
spikes : numpy array (num_neuron,N), dtype=np.ndarray
A sequence of spike times for each neuron on each tri... | cc2b54e80e00b10b8cabf79093509fde1980b804 | 20,569 |
def api_github_v2(user_profile, event, payload, branches, default_stream, commit_stream, issue_stream, topic_focus = None):
"""
processes github payload with version 2 field specification
`payload` comes in unmodified from github
`default_stream` is set to what `stream` is in v1 above
`commit_stream... | bed307903d7ddcce216919d18accb3ecfd94937d | 20,570 |
from typing import Iterable
from typing import Optional
from typing import Callable
from typing import Dict
def concatenate(
iterable: Iterable[Results],
callback: Optional[Callable] = None,
modes: Iterable[str] = ("val", "test"),
reduction: str = "none",
) -> Results:
"""Returns a concatenated Re... | 6833a50ddc84d44c942c6e85c1ebbdb793bd78a9 | 20,571 |
def parse_version(s: str) -> tuple[int, ...]:
"""poor man's version comparison"""
return tuple(int(p) for p in s.split('.')) | 445cd029efa3c8d4331e916f9925daddbc277ada | 20,572 |
def replay_train(DQN, train_batch):
"""
์ฌ๊ธฐ์ train_batch๋ minibatch์์ ๊ฐ์ ธ์จ data๋ค์
๋๋ค.
x_stack์ state๋ค์ ์๋ ์ฉ๋๋ก์ด๊ณ ,
y_stack์ deterministic Q-learning ๊ฐ์ ์๊ธฐ ์ํ ์ฉ๋์
๋๋ค.
์ฐ์ ์๊ธฐ์ ์ ๋น์ด์๋ ๋ฐฐ์ด๋ก ๋ง๋ค์ด๋๊ธฐ๋ก ํ์ฃ .
"""
x_stack = np.empty(0).reshape(0, DQN.input_size) # array(10, 4)
y_stack = np.empty(0).reshape(0, DQN.output_size) # arr... | 05b85aab223b82637a23853d15cd8e073ecca845 | 20,573 |
def make_reverse_macro_edge_name(macro_edge_name):
"""Autogenerate a reverse macro edge name for the given macro edge name."""
if macro_edge_name.startswith(INBOUND_EDGE_FIELD_PREFIX):
raw_edge_name = macro_edge_name[len(INBOUND_EDGE_FIELD_PREFIX) :]
prefix = OUTBOUND_EDGE_FIELD_PREFIX
elif ... | 807efcc26fb21e553241b2de4d2c6633a24548a2 | 20,574 |
def unescaped_split(pattern,
string,
max_split=0,
remove_empty_matches=False,
use_regex=False):
"""
Splits the given string by the specified pattern. The return character (\\n)
is not a natural split pattern (if you don't specif... | 5a5cec1a54b94840e13ddec3ca8796a73e908898 | 20,575 |
def citation_distance_matrix(graph):
"""
:param graph: networkx graph
:returns: distance matrix, node labels
"""
sinks = [key for key, outdegree in graph.out_degree() if outdegree==0]
paths = {s: nx.shortest_path_length(graph, target=s) for s in sinks}
paths_df = pd.DataFrame(paths)#, index... | b3c41164c2081704b3b36ce0c5b1ca55440a88be | 20,576 |
from typing import IO
def read_into_dataframe(file: IO, filename: str = "", nrows: int = 100,max_characters: int = 50) -> pd.DataFrame:
"""Reads a file into a DataFrame.
Infers the file encoding and whether a header column exists
Args:
file (IO): file buffer.
filename (str): filename. Used... | fe95c60870779353f2aa751c20ed331a2e0156bf | 20,577 |
from typing import OrderedDict
import torch
def Navigatev0_action_to_tensor(act: OrderedDict, task=1):
"""
Creates the following (batch_size, seq_len, 11) action tensor from Navigatev0 actions:
0. cam left
1. cam right
2. cam up
3. cam down
4. place + jump
5. place
6... | 39d481d2e8597902b18695de97f041606f24f035 | 20,579 |
def asfarray(a, dtype=mstype.float32):
"""
Similar to asarray, converts the input to a float tensor.
If non-float dtype is defined, this function will return a float32 tensor instead.
Args:
a (Union[int, float, bool, list, tuple, numpy.ndarray]): Input data, in
any form that can be... | 4da49b2bcab9686b2757cf1b9066c21876f992e6 | 20,580 |
from typing import Optional
from typing import Callable
import click
def _verify_option(value: Optional[str], value_proc: Callable) -> Optional[str]:
"""Verifies that input value via click.option matches the expected value.
This sets ``value`` to ``None`` if it is invalid so the rest of the prompt
can fl... | 4d0f58827982924a9d027112ffa3aaeef7634fe8 | 20,581 |
def batch_jacobian(output, inp, use_pfor=True, parallel_iterations=None):
"""Computes and stacks jacobians of `output[i,...]` w.r.t. `input[i,...]`.
e.g.
x = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
y = x * x
jacobian = batch_jacobian(y, x)
# => [[[2, 0], [0, 4]], [[6, 0], [0, 8]]]
... | dd42fcc9542bba8033a1eb204bf0d3a91b192dbc | 20,582 |
def declare(baseFamily=None, baseDefault=0, derivedFamily=None, derivedDefault=""):
"""
Declare a pair of components
"""
# the declaration
class base(pyre.component, family=baseFamily):
"""a component"""
b = pyre.properties.int(default=baseDefault)
class derived(base, family=der... | 30c8d8f7d264a0e908f4305198b07c3d76a3cfac | 20,583 |
from datetime import datetime
def parse_iso8601(dtstring: str) -> datetime:
"""naive parser for ISO8061 datetime strings,
Parameters
----------
dtstring
the datetime as string in one of two formats:
* ``2017-11-20T07:16:29+0000``
* ``2017-11-20T07:16:29Z``
"""
return... | 415a4f3a9006109e31ea344cf99e885a3fd2738d | 20,584 |
def CalcCurvature(vertices,faces):
"""
CalcCurvature recives a list of vertices and faces
and the normal at each vertex and calculates the second fundamental
matrix and the curvature by least squares, by inverting the 3x3 Normal matrix
INPUT:
vertices -nX3 array of vertices
faces -mX3 a... | b0e31073fe8aff61e60d0393098cca390bb95708 | 20,585 |
from typing import Optional
def query_abstracts(
q: Optional[str] = None,
n_results: Optional[int] = None,
index: str = "agenda-2020-1",
fields: list = ["title^2", "abstract", "fullname", "institution"],
):
"""
Query abstracts from a given Elastic index
q: str, query
n_results: int, n... | 4ed554231c863c3164c5368978da900e3647570d | 20,586 |
import typing
import pickle
def PretrainedEmbeddingIndicesDictionary() -> typing.Dict[str, int]:
"""Read and return the embeddings indices dictionary."""
with open(INST2VEC_DICITONARY_PATH, "rb") as f:
return pickle.load(f) | d4c0c8f5d7c83d99927342c5cacd8fd80a4f7d56 | 20,587 |
def color_negative_red(val):
"""
Takes a scalar and returns a string with
the css property `'color: red'` for negative
strings, black otherwise.
"""
color = 'red' if val < 0 else 'black'
return 'color: %s' % color | 1806af9c915740612a6a11df723f1439c73bde2f | 20,588 |
def get_student_discipline(person_id: str = None):
"""
Returns student discipline information for a particular person.
:param person_id: The numeric ID of the person you're interested in.
:returns: String containing xml or an lxml element.
"""
return get_anonymous('getStudentDiscipline', perso... | 4e96fb4e9d566af7094b16b29540617bbb230f67 | 20,590 |
from re import X
def dot(p1, p2):
"""
Dot product
:param p1:
:param p2:
:return:
"""
return p1[X] * p2[X] + p1[Y] * p2[Y] | 13ba17e8757ebf9022f07d21b58a26376520f84a | 20,592 |
def logout():
"""View function which handles a logout request."""
tf_clean_session()
if current_user.is_authenticated:
logout_user()
# No body is required - so if a POST and json - return OK
if request.method == "POST" and _security._want_json(request):
return _security._render_jso... | 0343be8ec063b5c215a0a019003cbf137588171a | 20,593 |
def splinter_session_scoped_browser():
"""Make it test scoped."""
return False | a7587f6edff821bab3052dca73929201e98dcf56 | 20,595 |
from typing import Counter
def sample_mask(source, freq_vocab, threshold=1e-3, min_freq=0, seed=None, name=None):
"""Generates random mask for downsampling high frequency items.
Args:
source: string `Tensor` of any shape, items to be sampled.
freq_vocab: `Counter` with frequencies vocabulary.... | 30fca98f95ac7a6aa2f3a3576f32abf271a693bb | 20,596 |
def _xList(l):
"""
"""
if l is None:
return []
return l | ef09d779c7ebc2beb321d90726f43603c0ac8315 | 20,597 |
def IABN2Float(module: nn.Module) -> nn.Module:
"""If `module` is IABN don't use half precision."""
if isinstance(module, InplaceAbn):
module.float()
for child in module.children():
IABN2Float(child)
return module | 587565ad78afd08d3365f637ab5b98b17e977566 | 20,598 |
from datetime import datetime
def start_of_day(val):
"""
Return a new datetime.datetime object with values that represent
a start of a day.
:param val: Date to ...
:type val: datetime.datetime | datetime.date
:rtype: datetime.datetime
"""
if type(val) == date:
val = datetime.fr... | 74e302513edf428f825f9e24567e23b3a5e5d4f5 | 20,599 |
def pending_mediated_transfer(app_chain, token_network_identifier, amount, identifier):
""" Nice to read shortcut to make a LockedTransfer where the secret is _not_ revealed.
While the secret is not revealed all apps will be synchronized, meaning
they are all going to receive the LockedTransfer message.
... | 82ae40ffa45a759f1aac132c3edc221ebd11ae9e | 20,600 |
def get_comments(post, sort_mode='hot', max_depth=5, max_breadth=5):
"""
Retrieves comments for a post.
:param post: The unique id of a Post from which Comments will be returned.
:type post: `str` or :ref:`Post`
:param str sort_mode: The order that the Posts will be sorted by. Options are: "top... | 333009358f622560135e7e239741613356387d55 | 20,601 |
def neighbor_json(json):
"""Read neighbor game from json"""
utils.check(
json['type'].split('.', 1)[0] == 'neighbor', 'incorrect type')
return _NeighborDeviationGame(
gamereader.loadj(json['model']),
num_neighbors=json.get('neighbors', json.get('devs', None))) | 19891d59970610ad412fd4eb204477c96d1d82fd | 20,602 |
def get_b16_config():
"""Returns the ViT-B/16 configuration."""
config = ml_collections.ConfigDict()
config.name = 'ViT-B_16'
config.half_precision = True
config.encoder = ml_collections.ConfigDict()
config.encoder.patches = ml_collections.ConfigDict({'size': (16, 16)})
config.encoder.hidden_size = 768
... | 6afdb862bd07c21d569db65fbb1780492ff153f2 | 20,603 |
from typing import Container
def build_container_hierarchy(dct):
"""Create a hierarchy of Containers based on the contents of a nested dict.
There will always be a single top level scoping Container regardless of the
contents of dct.
"""
top = Container()
for key,val in dct.items():
if... | 7fb629d7f570e5f77b381766b5c2d909d7c0d6c1 | 20,604 |
def occ_frac(stop_rec_range, bin_size_minutes, edge_bins=1):
"""
Computes fractional occupancy in inbin and outbin.
Parameters
----------
stop_rec_range: list consisting of [intime, outtime]
bin_size_minutes: bin size in minutes
edge_bins: 1=fractional, 2=whole bin
Returns
-------
... | d3d93cd92386a98c865c61ad2b595786aa5d4837 | 20,605 |
def geomprogr_mesh(N=None, a=0, L=None, Delta0=None, ratio=None):
"""Compute a sequence of values according to a geometric progression.
Different options are possible with the input number of intervals in the
sequence N, the length of the first interval Delta0, the total length L
and the ratio of the so... | 3de67b8ee2d75b69638648316fcfad07dbabde3a | 20,606 |
def list_subclasses(package, base_class):
"""
Dynamically import all modules in a package and scan for all subclasses of a base class.
`package`: the package to import
`base_class`: the base class to scan for subclasses
return: a dictionary of possible subclasses with class name as key and class typ... | e5570c30c89869b702c1c1015914540403be356f | 20,607 |
def maxima_in_range(r, g_r, r_min, r_max):
"""Find the maxima in a range of r, g_r values"""
idx = np.where(np.logical_and(np.greater_equal(r, r_min), np.greater_equal(r_max, r)))
g_r_slice = g_r[idx]
g_r_max = g_r_slice[g_r_slice.argmax()]
idx_max, _ = find_nearest(g_r, g_r_max)
return r[idx_ma... | 14a4e3dc65465dd2e515ac09fb74704a366368b4 | 20,608 |
def shared_fit_preprocessing(fit_class):
"""
Shared preprocessing to get X, y, class_order, and row_weights.
Used by _materialize method for both python and R fitting.
:param fit_class: PythonFit or RFit class
:return:
X: pd.DataFrame of features to use in fit
y: pd.Series of target... | b87831540ba6fc4bc65fe0532e2af0574515c3a3 | 20,609 |
import json
def webhook():
"""
Triggers on each GET and POST request. Handles GET and POST requests using this function.
:return: Return status code acknowledge for the GET and POST request
"""
if request.method == 'POST':
data = request.get_json(force=True)
log(json.dumps(data)) ... | 0c9f39c1159990e6a84dc9ce0091078397a3b65e | 20,610 |
def extract_winner(state: 'TicTacToeState') -> str:
"""
Return the winner of the game, or announce if the game resulted in a
tie.
"""
winner = 'No one'
tictactoe = TicTacToeGame(True)
tictactoe.current_state = state
if tictactoe.is_winner('O'):
winner = 'O'
elif tictactoe.is_... | c92cef3bc3214923107871d5f044df16baf63401 | 20,611 |
def _prensor_value_fetch(prensor_tree: prensor.Prensor):
"""Fetch function for PrensorValue. See the document in session_lib."""
# pylint: disable=protected-access
type_spec = prensor_tree._type_spec
components = type_spec._to_components(prensor_tree)
def _construct_prensor_value(component_values):
return... | ccea4a94fff5f17c6e650e1ac820ec6da1be023d | 20,612 |
def request_validation_error(error):
"""Handles Value Errors from bad data"""
message = str(error)
app.logger.error(message)
return {
'status_code': status.HTTP_400_BAD_REQUEST,
'error': 'Bad Request',
'message': message
}, status.HTTP_400_BAD_REQUEST | 1d5c779286d83d756e1d73201f1274dbec7cf84b | 20,614 |
def all(request):
"""Handle places list page."""
places = Place.objects.all()
context = {'places': places}
return render(request, 'rental/list_place.html', context) | d978a4ec22004a1a863e57113639722eaf1f02cf | 20,615 |
def get_key_by_value(dictionary, search_value):
"""
searchs a value in a dicionary and returns the key of the first occurrence
:param dictionary: dictionary to search in
:param search_value: value to search for
"""
for key, value in dictionary.iteritems():
if value == search_value:
... | febad38e70c973de23ce4e1a5702df92860a6c2e | 20,616 |
def _subtract_ten(x):
"""Subtracts 10 from x using control flow ops.
This function is equivalent to "x - 10" but uses a tf.while_loop, in order
to test the use of functions that involve control flow ops.
Args:
x: A tensor of integral type.
Returns:
A tensor representing x - 10.
"""
def stop_con... | f2db402e5c98251dc93036be60f02eb88a4d13d9 | 20,617 |
def load_fortune_file(f: str) -> list:
"""
load fortunes from a file and return it as list
"""
saved = []
try:
with open(f, 'r') as datfile:
text = datfile.read()
for line in text.split('%'):
if len(line.strip()) > 0:
saved.append(l... | 824ddb0bcb34abf597fb317d10fa3eeab99a292e | 20,618 |
def maskStats(wins, last_win, mask, maxLen):
"""
return a three-element list with the first element being the total proportion of the window that is masked,
the second element being a list of masked positions that are relative to the windown start=0 and the window end = window length,
and the third bein... | b5d75d2e86f1b21bf35cbc69d360cd1639c5527b | 20,619 |
def dsoftmax(Z):
"""Given a (m,n) matrix, returns a (m,n,n) jacobian matrix"""
m,n=np.shape(Z)
softZ=(softmax(Z))
prodtensor=np.einsum("ij,ik->ijk",softZ,softZ)
diagtensor=np.einsum('ij,jk->ijk', softZ, np.eye(n, n))
return diagtensor-prodtensor | 15296d493608dac1fc9843dd8a7d6eaaf29c4839 | 20,620 |
async def vbd_unplug(cluster_id: str, vbd_uuid: str):
"""Unplug from VBD"""
try:
session = create_session(
_id=cluster_id, get_xen_clusters=Settings.get_xen_clusters()
)
vbd: VBD = VBD.get_by_uuid(session=session, uuid=vbd_uuid)
if vbd is not None:
ret = ... | 8b36c55354b35470bceb47ef212aa183be09fad4 | 20,621 |
def calculate_age(created, now):
"""
Pprepare a Docker CLI-like output of image age.
After researching `datetime`, `dateutil` and other libraries
I decided to do this manually to get as close as possible to
Docker CLI output.
`created` and `now` are both datetime.datetime objects.
"""
a... | f2b1a6fc643a78c9a2d3cdd0f497e05c3294eb03 | 20,622 |
def Maxout(x, num_unit):
"""
Maxout as in the paper `Maxout Networks <http://arxiv.org/abs/1302.4389>`_.
Args:
x (tf.Tensor): a NHWC or NC tensor. Channel has to be known.
num_unit (int): a int. Must be divisible by C.
Returns:
tf.Tensor: of shape NHW(C/num_unit) named ``output... | d10294d7ad180b47c4276e3bb0f43e7ac4a9fa3b | 20,623 |
import re
def is_youtube_url(url: str) -> bool:
"""Checks if a string is a youtube url
Args:
url (str): youtube url
Returns:
bool: true of false
"""
match = re.match(r"^(https?\:\/\/)?(www\.youtube\.com|youtu\.be)\/.+$", url)
return bool(match) | 97536b8e7267fb5a72c68f242b3f5d6cbd1b9492 | 20,624 |
def time_nanosleep():
""" Delay for a number of seconds and nanoseconds"""
return NotImplementedError() | 9ec91f2ef2656b5a481425dc65dc9f81a07386c2 | 20,625 |
import jinja2
def render_series_fragment(site_config):
"""
Adds "other posts in this series" fragment to series posts.
"""
series_fragment = open("_includes/posts_in_series.html", "r").read()
for post_object in site_config["series_posts"]:
print("Generating 'Other posts in this series' fr... | 6cf947148af2978e926d51e9007684b9580d2cb0 | 20,627 |
def get_class_by_name(name):
"""Gets a class object by its name, e.g. sklearn.linear_model.LogisticRegression"""
if name.startswith('cid.analytics'):
# We changed package names in March 2017. This preserves compatibility with old models.
name = name.replace('cid.analytics', 'analytics.core')
... | bf52eb8472e63cbb453183b57c5275d592665fc9 | 20,629 |
import functools
def _single_optimize(
direction,
criterion,
criterion_kwargs,
params,
algorithm,
constraints,
algo_options,
derivative,
derivative_kwargs,
criterion_and_derivative,
criterion_and_derivative_kwargs,
numdiff_options,
logging,
log_options,
erro... | 9f349f8e1124da3a2747b3880969a90e76aad52a | 20,630 |
def item_len(item):
"""return length of the string format of item"""
return len(str(item)) | 7d68629a5c2ae664d267844fc90006a7f23df1ba | 20,631 |
def get_progress_logger():
"""Returns the swift progress logger"""
return progress_logger | b1c0e8e206e2f051dcb97337dc51d4971fe0aa8b | 20,632 |
def instantiate_me(spec2d_files, spectrograph, **kwargs):
"""
Instantiate the CoAdd2d subclass appropriate for the provided
spectrograph.
The class must be subclassed from Reduce. See :class:`Reduce` for
the description of the valid keyword arguments.
Args:
spectrograph
(:... | f9961231ead7c3ece5757e5b18dc5620a3492a40 | 20,634 |
def quoteattr(s, table=ESCAPE_ATTR_TABLE):
"""Escape and quote an attribute value.
"""
for c, r in table:
if c in s:
s = s.replace(c, r)
return '"%s"' % s | 7af3e8ed6bfc0c23a957881ca41065d24cb288d5 | 20,635 |
def is_numeric(array):
"""Return False if any value in the array or list is not numeric
Note boolean values are taken as numeric"""
for i in array:
try:
float(i)
except ValueError:
return False
else:
return True | 2ab0bb3e6c35e859e54e435671b5525c6392f66c | 20,636 |
def reductions_right(collection, callback=None, accumulator=None):
"""This method is like :func:`reductions` except that it iterates over
elements of a `collection` from right to left.
Args:
collection (list|dict): Collection to iterate over.
callback (mixed): Callback applied per iteration... | eba2de662a6386d609da8cf3011010ae822c0440 | 20,637 |
import math
def pelt_settling_time(margin=1, init=0, final=PELT_SCALE, window=PELT_WINDOW, half_life=PELT_HALF_LIFE, scale=PELT_SCALE):
"""
Compute an approximation of the PELT settling time.
:param margin: How close to the final value we want to get, in PELT units.
:type margin_pct: float
:para... | c8d53d1132bc45278f2c127ed95ce10cfea0498b | 20,638 |
def InstancesOverlap(instanceList,instance):
"""Returns True if instance contains a vertex that is contained in an instance of the given instanceList."""
for instance2 in instanceList:
if InstanceOverlap(instance,instance2):
return True
return False | 634312b7e8d2ce4e36826410fcd1f6c3c06a40ce | 20,640 |
def calc_qm_lea(p_zone_ref, temp_zone, temp_ext, u_wind_site, dict_props_nat_vent):
"""
Calculation of leakage infiltration and exfiltration air mass flow as a function of zone indoor reference pressure
:param p_zone_ref: zone reference pressure (Pa)
:param temp_zone: air temperature in ventilation zon... | 4d3f4789b3faedf68b9de3b3e6c8f17bcb478a51 | 20,641 |
async def ban(bon):
""" For .ban command, bans the replied/tagged person """
# Here laying the sanity check
chat = await bon.get_chat()
admin = chat.admin_rights
creator = chat.creator
# Well
if not (admin or creator):
return await bon.edit(NO_ADMIN)
user, reason = await get_us... | f79f16c5e2722f576511a528f546a7f87f7e5236 | 20,642 |
def read_offset(rt_info):
"""
่ทๅๆๆๅๅบ็offset
:param rt_info: rt็่ฏฆ็ปไฟกๆฏ
:return: offset_msgs ๅ offset_info
"""
rt_id = rt_info[RESULT_TABLE_ID]
task_config = get_task_base_conf_by_name(f"{HDFS}-table_{rt_id}")
if not task_config:
return {}
try:
partition_num = task_confi... | cc890301d4403a7815480ad0b414e16e26283fa7 | 20,643 |
def _CalculateElementMaxNCharge(mol,AtomicNum=6):
"""
#################################################################
**Internal used only**
Most negative charge on atom with atomic number equal to n
#################################################################
"""
Hmol=Chem.AddHs... | f7bd9957c6e958f31cccc2bc20d6651baaf2f5fa | 20,644 |
def check_stability(lambda0, W, mu, tau, dt_max):
"""Check if the model is stable for given parameter estimates."""
N, _ = W.shape
model = NetworkPoisson(N=N, dt_max=dt_max)
model.lamb = lambda0
model.W = W
model.mu = mu
model.tau = tau
return model.check_stability(return_value=True) | d417bdba0f236edf5f5c9e17c09e2d2a93bf2b4a | 20,646 |
import re
def pid2id(pid):
"""convert pid to slurm jobid"""
with open('/proc/%s/cgroup' % pid) as f:
for line in f:
m = re.search('.*slurm\/uid_.*\/job_(\d+)\/.*', line)
if m:
return m.group(1)
return None | e7d0ee60d5a8930b8a6f761d5c27451a28b6ec2a | 20,647 |
import copy
def multiaxis_scatterplot(xdata,
ydata,
*,
axes_loc,
xlabel='',
ylabel='',
title='',
num_cols=1,
n... | 22d9aa3b0de496c498535b2b4bf663be429b8f48 | 20,649 |
import torch
def log1p_mse_loss(estimate: torch.Tensor, target: torch.Tensor,
reduce: str = 'sum'):
"""
Computes the log1p-mse loss between `x` and `y` as defined in [1], eq. 4.
The `reduction` only affects the speaker dimension; the time dimension is
always reduced by a mean operat... | 7c67a67dcf6f6d14bb712d5a92b54ea979f7a73c | 20,650 |
def quaternion_inverse(quaternion: np.ndarray) -> np.ndarray:
"""Return inverse of quaternion."""
return quaternion_conjugate(quaternion) / np.dot(quaternion, quaternion) | b71c5b544199b02a76362bc42db900b157ea80ec | 20,651 |
def _make_indexable(iterable):
"""Ensure iterable supports indexing or convert to an indexable variant.
Convert sparse matrices to csr and other non-indexable iterable to arrays.
Let `None` and indexable objects (e.g. pandas dataframes) pass unchanged.
Parameters
----------
iterable : {list, d... | 29d067826e0a863b06b1fb0295b12d57ecaea00d | 20,652 |
def batchnorm_forward(x, gamma, beta, bn_param):
"""
Forward pass for batch normalization.
During training the sample mean and (uncorrected) sample variance are
computed from minibatch statistics and used to normalize the incoming data.
During training we also keep an exponentially decaying running ... | b36ea808c5865eb92a81464c3efe14ab9325d01e | 20,653 |
def chunking():
"""
transforms dataframe of full texts into a list of chunked texts of 2000 tokens each
"""
word_list = []
chunk_list = []
text_chunks = []
# comma separating every word in a book
for entry in range(len(df)):
word_list.append(df.text[entry].split())
# create a chunk of ... | 66e1976b3bd9e88420fab370f1eee9053986bd56 | 20,654 |
def generate_random_string():
"""Create a random string with 8 letters for users."""
letters = ascii_lowercase + digits
return ''.join(choice(letters) for i in range(8)) | 027a9d50e2ff5b80b7344d35e492ace7c65366e8 | 20,655 |
def contains_message(response, message):
"""
Inspired by django's self.assertRaisesMessage
Useful for confirming the response contains the provided message,
"""
if len(response.context['messages']) != 1:
return False
full_message = str(list(response.context['messages'])[0])
return... | 4afcdba84603b8b53095a52e769d0a8e3f7bbb17 | 20,656 |
def definition():
"""To be used by UI."""
sql = f"""
SELECT c.course_id,
c.curriculum_id,
cs.course_session_id,
description + ' year ' +CAST(session as varchar(2)) as description,
CASE WHEN conf.course_id IS NULL THEN 0 ELSE 1 END as linked,
0 as changed
FROM (... | ac67783943604e0e83bd4ccfc2b704737e427edd | 20,657 |
def exec_psql_cmd(command, host, port, db="template1", tuples_only=True):
"""
Sets up execution environment and runs the HAWQ queries
"""
src_cmd = "export PGPORT={0} && source {1}".format(port, hawq_constants.hawq_greenplum_path_file)
if tuples_only:
cmd = src_cmd + " && psql -d {0} -c \\\\\\\"{1};\\\\\\... | 453f0c2ef0dfdf2a5d03b22d4a6fbd03282dd72a | 20,658 |
def carla_cityscapes_image_to_ndarray(image: carla.Image) -> np.ndarray: # pylint: disable=no-member
"""Returns a `NumPy` array from a `CARLA` semantic segmentation image.
Args:
image: The `CARLA` semantic segmented image.
Returns:
A `NumPy` array representation of the image.
"""
image.convert(carl... | f191d3f9700b281178f395726d649e90dfc57bb7 | 20,659 |
import re
def since(version):
"""A decorator that annotates a function to append the version
of skutil the function was added. This decorator is an adaptation of PySpark's.
Parameters
----------
version : str, float or int
The version the specified method was added to skutil.
Exam... | e6b29b5e4c67ba4a213b183a0b79a1f16a85d81c | 20,660 |
def get_dMdU():
"""Compute dMdU"""
dMdC = form_nd_array("dMdC", [3,3,3,3,3])
dMdPsi = form_nd_array("dMdPsi", [3,3,3,3,3])
dMdGamma = form_nd_array("dMdGamma",[3,3,3,3,3,3])
dCdU = form_symb_dCdU()
dPsidU = form_symb_dPhidU()
dGammadU = form_symb_dGammadU()
... | 55d6dedc5311c8a2a30c44569508bd7687400cb5 | 20,661 |
def get_group_value_ctx_nb(sc_oc):
"""Get group value from context.
Accepts `vectorbt.portfolio.enums.SegmentContext` and `vectorbt.portfolio.enums.OrderContext`.
Best called once from `segment_prep_func_nb`.
To set the valuation price, change `last_val_price` of the context in-place.
!!! note
... | 0646e7a26b36af42ee38196e0ee60e3684da2d16 | 20,662 |
import math
import torch
import scipy
def motion_blur_generate_kernel(radius, angle, sigma):
"""
Args:
radius
angle (float): Radians clockwise from the (x=1, y=0) vector. This
is how ImageMagick's -motion-blur filter accepts angles, as far
as I can tell.
>>> mb_1_0... | ff4e939d2ffbc91b6ef6af2ca11aceb1d32df594 | 20,663 |
def substitute_crypto_to_req(req):
"""Replace crypto requirements if customized."""
crypto_backend = get_crypto_req()
if crypto_backend is None:
return req
def is_not_crypto(r):
CRYPTO_LIBS = PYCRYPTO_DIST, "cryptography"
return not any(r.lower().startswith(c) for c in CRYPTO_L... | 0e1836120f52981c3ff126038c0c74b9da94aa7f | 20,664 |
def remove_att(doc_id, doc_rev, att_id, **kwargs):
"""Delete an attachment.
http://docs.couchdb.org/en/stable/api/document/attachments.html#delete--db-docid-attname
:param str doc_id: The attachment document.
:param str doc_rev: The document revision.
:param str att_id: The attachment to remove.
... | 2b9361468baf4dc2e358b2fa2f4c43403556cd40 | 20,665 |
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