content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _one_q_pauli_prep(label, index, qubit):
"""Prepare the index-th eigenstate of the pauli operator given by label."""
if index not in [0, 1]:
raise ValueError(f'Bad Pauli index: {index}')
if label == 'X':
if index == 0:
return Program(_RY(pi / 2, qubit))
else:
... | 4c4f02c6e1ffcbb57ca161f3cb0f17a678563b0b | 3,631,041 |
def get_movie_data_from_wikidata(slice_movie_set: pd.DataFrame):
"""
Function that consults the wikidata KG for a slice of the movies set
:param slice_movie_set: slice of the movie data set with movie id as index and imdbId, Title, year and imdbUrl
as columns
:return: JSON with the results of the qu... | a4c3a9a7e7cce1a2eb85326422afcb4ff3463db4 | 3,631,044 |
def run_dpc(
filename,
i,
j,
ref_fx=None,
ref_fy=None,
start_point=[1, 0],
pixel_size=55,
focus_to_det=1.46,
dx=0.1,
dy=0.1,
energy=19.5,
zip_file=None,
roi=None,
bad_pixels=[],
max_iters=1000,
solver="Nelder-Mead",
hang=True,
reverse_x=1,
reve... | e7d96201350cb84c323066434d8257631de353f7 | 3,631,045 |
def api_converter():
"""
Handler for conversion API request
:return: Text of response
:rtype: str
"""
try:
parsed_args = parse_request_arguments()
conversion_result = convert_core.convert_currency(**parsed_args)
except (APIRequestError, CurrencyConversionError) as exc_msg:
... | 591961f92a5e1e831976bcb09396630b515785cb | 3,631,047 |
import pytz
def plot1(ctx):
"""Do main plotting logic"""
df = read_sql("""
SELECT * from sm_hourly WHERE
station = %s and valid BETWEEN %s and %s ORDER by valid ASC
""", ctx['pgconn'], params=(ctx['station'], ctx['sts'],
ctx['ets']), index_col='valid')
i... | 8c94e9b989bbf0f04db99cffdc54cc9ec46b8e40 | 3,631,048 |
from typing import Tuple
from typing import Optional
def is_royal_flush(hand: Tuple[Card]) -> Optional[Tuple[str, PokerHand, int]]:
""" If this hand contains a royal flush, return string representation of it """
straight_flush = is_straight_flush(hand)
if straight_flush is not None and "Ten to Ace" in str... | 9e530d3c1ff44b35e6e17bc068f4557e059e3415 | 3,631,049 |
import torch
def make_complex_matrix(x, y):
"""A function that takes two tensors (a REAL (x) and IMAGINARY part (y)) and returns the combine complex tensor.
:param x: The real part of your matrix.
:type x: torch.doubleTensor
:param y: The imaginary part of your matrix.
:type y: torch.doubleTe... | faae031b3aa6f4972c8f558f6b66e33d416dec71 | 3,631,050 |
def array(dtype, ndim):
"""
:param dtype: the Numba dtype type (e.g. double)
:param ndim: the array dimensionality (int)
:return: an array type representation
"""
if ndim == 0:
return dtype
return minitypes.ArrayType(dtype, ndim) | f9b89a414d9bfb7a1e154df34c1c75a47943bca5 | 3,631,051 |
def as_pandas(data):
"""Returns a dataframe if possible, an error otherwise"""
if isinstance(data, pd.DataFrame):
return data
elif isinstance(data, dict):
return pd.DataFrame(data)
else:
raise TypeError(
f"Expected a DataFrame or dict type, got: {type(data)} insead"
... | a9243c327f8f7851b0b8347a9df684db7b152561 | 3,631,052 |
def scale3(v, s):
"""
scale3
"""
return (v[0] * s, v[1] * s, v[2] * s) | 4993c072fb66a33116177023dde7b1ed2c8705fd | 3,631,053 |
def _get_last_ext_comment_id(connection):
"""Returns last external comment id.
Args:
connection: An instance of SQLAlchemy connection.
Returns:
Integer of last comment id from external model.
"""
result = connection.execute(
sa.text("""
SELECT
MAX(id)
FROM ... | 5cc139e3c4490293ebb305b7cac03d4803c51df6 | 3,631,054 |
from typing import SupportsAbs
import math
def is_unit(v: SupportsAbs[float]) -> bool: # <2>
"""'True' if the magnitude of 'v' is close to 1."""
return math.isclose(abs(v), 1.0) | 0b31da2e5a3bb6ce49705d5b2a36d3270cc5d802 | 3,631,055 |
def atom_eq(at1,at2):
""" Returns true lits are syntactically equal """
return at1 == at2 | 43aab77292c81134490eb8a1c79a68b38d50628d | 3,631,056 |
def is_valid_month (val):
""" Checks whether or not a two-digit string is a valid date month.
Args:
val (str): The string to check.
Returns:
bool: True if the string is a valid date month, otherwise false.
"""
if len(val) == 2 and count_digits(val) == 2:
month = int(val)
... | 53d825473cf497441d09e08402e833fa9c362a83 | 3,631,057 |
def env_repos(action=None):
"""
Perform an action on each environment repository, specified by action.
"""
actions = {
'add': _add_repo,
'reset': _reset_repo,
'rm': _rm_repo
}
def validate_action(input):
if input not in actions:
raise Exception('Inval... | f9b9ab0e671757bbcdf7bf4f50fe05e079aca115 | 3,631,058 |
import re
def get_job_definition_name_by_arn(job_definition_arn):
"""
Parse Job Definition arn and get name.
Args:
job_definition_arn: something like arn:aws:batch:<region>:<account-id>:job-definition/<name>:<version>
Returns: the job definition name
"""
pattern = r".*/(.*):(.*)"
... | d55bab5bbc62bf6d9f7907e26cb2a4a418bd9c50 | 3,631,059 |
def get_polyline_length(polyline: np.ndarray) -> float:
"""Calculate the length of a polyline.
Args:
polyline: Numpy array of shape (N,2)
Returns:
The length of the polyline as a scalar
"""
assert polyline.shape[1] == 2
return float(np.linalg.norm(np.diff(polyline, axis=0), axi... | 9fb76a611c961af8ca10fda33029a55eb8589be1 | 3,631,060 |
def add_update_stock(symbol, is_held):
"""This function takes a stock symbol as a string, makes a call to yfinance, and gets back the necessary data to add the symbol to the database.
`is_held` must also be specified, to mark the is_held flag in the database True/False."""
session = connect_to_sessio... | df5c7782fd07f916e61e4d5dc1f8f8cf9be86eec | 3,631,062 |
import math
def k2(Ti, exp=math.exp):
"""[cm^3 / s]"""
return 2.78e-13 * exp(2.07/(Ti/300) - 0.61/(Ti/300)**2) | 6c1f471b31767f2d95f3900a8811f47dc8c45086 | 3,631,063 |
async def add_source(request):
"""
API Endpoint to add new datasets to an instance
API Params:
file: location of the json or hub file
filetype: 'hub' if trackhub or 'json' if configuration file
Args:
request: a sanic request object
Returns:
success/fail after addi... | 624218d1e773c43a35fa3579d892cc6207e1ee1d | 3,631,064 |
def clean_counties_data():
"""Clean US Counties data from NY Times
Returns:
DataFrame -- clean us counties data
Updates:
database table -- NYTIMES_COUNTIES_TABLEs
database view -- COUNTIES_VIEW
"""
_db = DataBase()
data = _db.get_table(US_COUNTIES_TABLE, parse_dates=['d... | 083e9720de9bfa422984d01fec08c0c4b33b0861 | 3,631,065 |
def get_3D_hist(sub_img):
"""
Take in a sub-image
Get 3D histogram of the colors of the image and return it
"""
M, N = sub_img.shape[:2]
t = 4
pixels = sub_img.reshape(M * N, 3)
hist_3D, _ = np.histogramdd(pixels, (t, t, t))
return hist_3D | c582ec9b7d6bb24585ce5f95d2a770b4b7a06c37 | 3,631,066 |
import math
import torch
def magnitude_prune(masking, mask, weight, name):
"""Prunes the weights with smallest magnitude.
The pruning functions in this sparse learning library
work by constructing a binary mask variable "mask"
which prevents gradient flow to weights and also
sets the weights to z... | 4bac89da952338e133ac0d85735e80631862c7da | 3,631,068 |
import requests
def delete_post(post_id):
"""Authenticates and proxies a request to users service to delete a post."""
try:
my_user_id = get_user()['user_id']
response = requests.delete(app.config['POSTS_ENDPOINT'] + post_id,
data={'author_id': my_user_id})
... | a558ab58ac3129fb543c89c8b3c236126d26ddac | 3,631,069 |
import collections
def file_based_convert_examples_to_features_single(examples, label_list,
max_seq_length, tokenizer,
output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_... | 444afd74b8bccd7e014e727d4be41be75fbdbb11 | 3,631,070 |
def less_equal(x, y):
"""Element-wise truth value of (x <= y).
# Arguments
x: Tensor or variable.
y: Tensor or variable.
# Returns
A bool tensor.
# Raise
TypeError: if inputs are not valid.
"""
scalar = False
if isinstance(x, KerasSymbol):
x = x.sym... | 566c46cc4882f167275cb6bc400800413efdc85b | 3,631,071 |
from datetime import datetime
def annual_reports():
""" Return list of all existing annual reports """
database = DataProvider()
total = count(database.objects, lambda x: x.with_cafe) * 2 + \
count(database.objects, lambda x: not x.with_cafe)
reports_list = list()
# calculate count of ... | 2e6daacd7150e47b299948b60866238589881ef5 | 3,631,072 |
def definition_for_include(parsed_include, parent_definition_key):
"""
Given a parsed <xblock-include /> element as a XBlockInclude tuple, get the
definition (OLX file) that it is pointing to.
Arguments:
parsed_include: An XBlockInclude tuple
parent_definition_key: The BundleDefinitionLocator... | 325de830231c9b21a3c7cfce4262fef291ab6fbf | 3,631,074 |
def verify_user(uid, token_value):
"""
Verify the current user's account.
Link should have been sent to the user's email.
Args:
token_value: the verification token value
Returns:
True if successful verification based on the (uid, token_value)
False if token is not valid for... | e63e7044e66bb29e8f44d7fa0a08128597e7b07e | 3,631,075 |
def cholesky_metric(chol: JAXArray, *, lower: bool = True) -> Metric:
"""A general metric parameterized by its Cholesky factor
The units of the Cholesky factor are length, unlike the dense metric.
Therefore,
.. code-block:: python
cholesky_metric(jnp.diag(ell))
and
.. code-block:: p... | 406d0db5d3f6f9317a0b45895823c3927564653a | 3,631,076 |
import typing
def format_roman(value: int) -> str:
"""Format a number as lowercase Roman numerals."""
assert 0 < value < 4000
result: typing.List[str] = []
index = 0
while value != 0:
value, remainder = divmod(value, 10)
if remainder == 9:
result.insert(0, ROMAN_ONES[... | 259b205ffa25bbdeccb0ca6883c02c99d194f60d | 3,631,077 |
def isint(s):
"""Does this object represent an integer?"""
try:
int(s)
return True
except (ValueError, TypeError):
return False | dbcb20b437f1ccfb09f5cb969b7d5b9d369d2e38 | 3,631,079 |
def embed_vimeo(url):
"""
Return HTML for embedding Vimeo videos or ``None``, if argument isn't a
Vimeo link.
The Vimeo ``<iframe>`` is wrapped in a
``<div class="responsive-embed widescreen vimeo">`` element.
"""
match = VIMEO_RE.search(url)
if not match:
return None
d = ma... | 7923991466ec3eafa4c991bb93b2244ebcf99c47 | 3,631,080 |
def random_sample(random_state, size=None, chunk_size=None, gpu=None, dtype=None):
"""
Return random floats in the half-open interval [0.0, 1.0).
Results are from the "continuous uniform" distribution over the
stated interval. To sample :math:`Unif[a, b), b > a` multiply
the output of `random_samp... | 441a8d1b6e972ab961cf5910cd3737e5a21578e7 | 3,631,081 |
def anndata_file():
"""Pytest fixture for creation of anndata files."""
def _create_file(nvals):
size = 15289 * nvals
vals = np.zeros(size, dtype=np.float32)
non_zero = size - int(size * 0.92)
non_zero = int(np.random.normal(loc=non_zero, scale=10, size=1))
rand = np.rand... | 0f9c1ff260ae48837e9f925c65fd87c7b5f75768 | 3,631,082 |
def _heatmap_summary(pvals, coefs, plot_width=1200, plot_height=400):
""" Plots heatmap of coefficients colored by pvalues
Parameters
----------
pvals : pd.DataFrame
Table of pvalues where rows are balances and columns are
covariates.
coefs : pd.DataFrame
Table of coefficien... | 32dae78fbaa3e978d418255e387e63f6346315ff | 3,631,083 |
from datetime import datetime
def get_warehouse_latest_modified_date(email_on_delay=False):
"""
Return in minutes how fresh is the data of app_status warehouse model.
"""
last_completed_app_status_batch = Batch.objects.filter(
dag_slug='app_status_batch', completed_on__isnull=False
).order... | 541dba13fde93acc51a41a9079a6da5f0344514a | 3,631,084 |
async def async_unload_entry(hass, config_entry):
"""Handle removal of an entry."""
return True | 28005ececbf0c43c562cbaf7a2b8aceb12ce3e41 | 3,631,086 |
def render_links(link_dict):
"""Render links to html
Args:
link_dict: dict where keys are names, and values are lists (url,
text_to_display). For example::
{"column_moistening.mp4": [(url_to_qv, "specific humidity"), ...]}
"""
return {
key: " ".join([_html_l... | c07f388e97f9e723cfc42ee66ef1eea654167820 | 3,631,087 |
import json
def is_valid_json(text: str) -> bool:
"""Is this text valid JSON?
"""
try:
json.loads(text)
return True
except json.JSONDecodeError:
return False | 3013210bafd5c26cacb13e9d3f4b1b708185848b | 3,631,088 |
import signal
def peri_saccadic_response(spike_counts, eye_track, motion_threshold=5, window=15):
"""
Computes the cell average response around saccades.
params:
- spike_counts: cells activity matrix of shape (t, n_cell)
- eye_track: Eye tracking data of shape (t, x_pos, y_pos, ...)
... | 85455106bb1cd438b2aeb25ee0fc3708a166d4b7 | 3,631,089 |
import operator
def assign_subpopulation_from_region(pop, region, criteria, verbose=False):
"""
Compute required consistencies and assign subpopulations to a population of models based on results from
a simulation region.
Inputs:
pop - a PopulationOfModels class
region - a list of simulations
... | 5279d7e398ed164aed4131bb1c826c5f1604c4a4 | 3,631,090 |
def op_structure(ea, opnum, id, **delta):
"""Apply the structure identified by `id` to the instruction operand `opnum` at the address `ea`.
If the offset `delta` is specified, shift the structure by that amount.
"""
ea = interface.address.inside(ea)
if not database.type.is_code(ea):
raise E... | 95d45003c86b4a99bb60d00eb584bb358f1cf350 | 3,631,091 |
from pathlib import Path
def get_config_path(root: str, idiom: str) -> Path:
"""Get path to idiom config
Arguments:
root {str} -- root directory of idiom config
idiom {str} -- basename of idiom config
Returns:
Tuple[Path, Path] -- pathlib.Path to file
"""
root_path = Path... | 86d65f11fbd1dfb8aca13a98e129b085158d2aff | 3,631,092 |
def status():
"""
Method to get the list of components available.
:return: It yields json string for the list of components.
"""
data = pgc.get_data("status")
return render_template('status.html', data=data) | 012431c843d051aec85df45fad005b9d17c71a5d | 3,631,093 |
from typing import Union
from typing import Iterable
from typing import Tuple
from typing import List
import heapq
def dijkstra(
graph: LilMatrix, source: Union[int, Iterable[int]]
) -> Tuple[List[int], List[int]]:
"""Dijkstra
Parameters
----------
graph
Weighted Graph
source
... | 62278adeda336344eadaac00b9240cddd747b496 | 3,631,094 |
def stdev(some_list):
"""
Calculate the standard deviation of a list.
"""
m = mean(some_list)
var = mean([(v - m)**2 for v in some_list])
return sqrt(var) | 4a8cf5d19af1e07e8228d285d1f2fcfb702a2158 | 3,631,095 |
def get_hg19_chroms():
"""Chromosomes in the human genome
Returns:
list: list of chromosomes
"""
return get_hg38_chroms() | 2565eb2fa1ca1dd1b513a2a7dc836777911c7fc8 | 3,631,096 |
def track(im0, im1, p0, lk_params_, fb_threshold=-1):
"""
Main tracking method using sparse optical flow (LK)
im0: previous image in gray scale
im1: next image
lk_params: Lukas Kanade params dict
fb_threshold: minimum acceptable backtracking distance
"""
if p0 is None or not len(p0):
... | 4a35dbb3c206f3b2e967f2b15853b19c7d579eb9 | 3,631,097 |
def get_kernel(X, Y, type='linear', param=1.0):
"""Calculates a kernel given the data X and Y (dims x exms)"""
_, Xn = X.shape
_, Yn = Y.shape
kernel = 1.0
if type == 'linear':
#print('Calculating linear kernel with size {0}x{1}.'.format(Xn, Yn))
kernel = X.T.dot(Y)
if type == ... | 98bd634456bbc4ec115de58fd58a1cd6df84b3a5 | 3,631,098 |
def MIDPOINT(ds, count, timeperiod=-2**31):
"""MidPoint over period"""
return call_talib_with_ds(ds, count, talib.MIDPOINT, timeperiod) | 0315f5148bbd4621db30aa572fd984f23cb6ee79 | 3,631,099 |
def dtype():
"""A fixture providing the ExtensionDtype to validate."""
return RaggedDtype() | d441f5e211c57edf009d9311e411dfb6d9833f75 | 3,631,101 |
import numpy
def geod2cart(rlat, rlon, height):
"""
Geodetic to Cartesian coordinate conversion
Call
cart = geod2cart(rlat, rlon, height)
Input
rlat -- NumPy float array of Geodetic latitudes
rlon -- NumPy float array of Geodetic longitudes
height -- NumPy float array... | 02dbb30ef4960ac523d43a89a3a76336e7b1b564 | 3,631,103 |
import requests
import json
import traceback
def check_deluge():
"""
Connects to an instance of Deluge and returns a tuple containing the instances status.
Returns:
(str) an instance of the Status enum value representing the status of the service
(str) a short descriptive string represent... | 8cc129a4c7465c52e1d9b82da949c33aa5929c8a | 3,631,105 |
def minor_min_width(G):
"""Computes a lower bound for the treewidth of graph G.
Parameters
----------
G : NetworkX graph
The graph on which to compute a lower bound on the treewidth.
Returns
-------
lb : int
A lower bound on the treewidth.
Examples
--------
Thi... | 649ea7fe0a55ec5289b04b761ea1633c2a258000 | 3,631,106 |
def generate_dataset(size=10000, op='sum', n_features=2):
""" Generate dataset for NALU toy problem
Arguments:
size - number of samples to generate
op - the operation that the generated data should represent. sum | prod
Returns:
X - the dataset
Y - the dataset labels
"""
X... | 3bd1b437d64c5260ec03a60114e9b8828f868c24 | 3,631,108 |
def glob2regexp(glob: str) -> str:
"""Translates glob pattern into regexp string.
"""
res = ""
escaping = False
incurlies = 0
pc = None # Previous char
for cc in glob.strip():
if cc == "*":
res += ("\\*" if escaping else ".*")
escaping = False
elif cc... | 1ae8d180663468aaeed44974da3e409b803e4a37 | 3,631,109 |
def distance(array1, array2):
"""计算两个数组矩阵的欧式距离;
axis=0，求每列的
axis=1，求每行的
"""
distance = np.sqrt(np.sum(np.power(array1 - array2, 2)))
return distance | bf6d38c4f6ebf19a048c732bc95796ab9837907f | 3,631,110 |
import IPython.parallel
from engine_manager import EngineManager
def parallel_map(function, *args, **kwargs):
"""Wrapper around IPython's map_sync() that defaults to map().
This might use IPython's parallel map_sync(), or the standard map()
function if IPython cannot be used.
If the 'ask' keyword ar... | 111219097c46ed719e67063ccb079f01d2f38363 | 3,631,111 |
def init_glorot(shape, name=None):
"""Glorot & Bengio (AISTATS 2010) init."""
init_range = np.sqrt(6.0/(shape[0]+shape[1]))
initial = tf.random_uniform(shape, minval=-init_range, maxval=init_range, dtype=tf.float32)
return tf.Variable(initial, name=name) | 05467f77de85c2dada59785e1b211055ce38ebda | 3,631,112 |
def securities(identifier=None, query=None, exch_symbol=None):
"""
Get securities with optional filtering using parameters.
Args:
identifier: Identifier for the legal entity or a security associated
with the company: TICKER SYMBOL | FIGI | OTHER IDENTIFIER
query: Search of secur... | 4c839dc2bc606ee10a70fa6e81f706b3c0ea0f1a | 3,631,113 |
def stations_within_radius(stations, centre, r):
"""The function stations_within_radius returns a list of the stations within a radius r from a centre"""
stations_new=[]
for s in stations:
# distance can be computed using haversine library
d=haversine.haversine(s.coord, centre)
... | de690076ff6d9b58176a3bb14612892344f3c78c | 3,631,114 |
def normalize_email(email):
"""Normalizes the given email address. In the current implementation it is
converted to lower case. If the given email is None, an empty string is
returned.
"""
email = email or ''
return email.lower() | 6ee68f9125eef522498c7299a6e793ba11602ced | 3,631,115 |
def _parse_hostname(url, include_port=False):
""" Parses the hostname out of a URL."""
if url:
parsed_url = urlparse((url))
return parsed_url.netloc if include_port else parsed_url.hostname | af37380619121274c608a22f151726ac79a05ad2 | 3,631,116 |
def voy(lr_angle):
""" Returns y component for reference velocity v_0"""
return -np.sin(np.radians(lr_angle))*9+np.cos(np.radians(lr_angle))*(12.+220.) | 156238dec8630b7c98535d54f826682a94e29ed1 | 3,631,117 |
def get_l8turbidwater(rho1, rho2, rho3, rho4, rho5, rho6, rho7):
"""Returns Boolean numpy array that marks shallow, turbid water"""
watercond2 = get_l8commonwater(rho1, rho4, rho5, rho6, rho7)
watercond2 = np.logical_and(watercond2, rho3 > rho2)
return watercond2 | 2690390eab21b53581979f71e1e144a178bcaa75 | 3,631,118 |
def string_extract_only_alphabets(inputString=""):
"""
Returns only alphabets from given input string
"""
return loader.string_extract_only_alphabets(inputString) | 118cf8b6f16585cf7a7418abfe85d4fba54c4d5a | 3,631,120 |
from typing import Optional
def get_trigger(location: Optional[str] = None,
project: Optional[str] = None,
project_id: Optional[str] = None,
trigger_id: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetTriggerResult:
... | c146b8f8bfb47d3207501004531d1d90926dda60 | 3,631,121 |
def selu(x): # https://gist.github.com/naure/78bc7a881a9db17e366093c81425184f
"""Scaled Exponential Linear Unit. (Klambauer et al., 2017)
# Arguments
x: A tensor or variable to compute the activation function for.
# References
- [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.... | 784e82c3921f1b7656a3acbb81c2974d4220b113 | 3,631,123 |
import logging
import importlib
def __clsfn_args_kwargs(config, key, base_module=None, args=None, kwargs=None):
"""
Utility function called by both create_object and create_function. It
implements the code that is common to both.
"""
logger = logging.getLogger('pytorch_lm.utils.config')
logger... | 66aae2787426dc2fd7fdc06b3d0e191c2d77d170 | 3,631,124 |
def parse_read_options(form, prefix=''):
"""Extract read options from form data.
Arguments:
form (obj): Form object
Keyword Arguments:
prefix (str): prefix for the form fields (default: {''})
Returns:
(dict): Read options key - value dictionary.
"""
read_options = {
... | 660e836172015999fe74610dffc331d2b37991c3 | 3,631,125 |
def get_app_version_info(domain, build_id, xform_version, xform_metadata):
"""
there are a bunch of unreliable places to look for a build version
this abstracts that out
"""
appversion_text = get_meta_appversion_text(xform_metadata)
commcare_version = get_commcare_version_from_appversion_text(a... | 78e04bb736fd7d5e7a84e2e4661f3d5c9dde4492 | 3,631,127 |
def plot_components_plotly(
m, fcst, uncertainty=True, plot_cap=True, figsize=(900, 200)):
"""Plot the Prophet forecast components using Plotly.
See plot_plotly() for Plotly setup instructions
Will plot whichever are available of: trend, holidays, weekly
seasonality, yearly seasonality, and add... | cbc9eccfc2cc12a8f0d9a2b13c0846a87f260e4e | 3,631,128 |
def _format_as_geojson(results, geodata_model):
"""joins the results to the corresponding geojson via the Django model.
:param results: [description]
:type results: [type]
:param geodata_model: [description]
:type geodata_model: [type]
:return: [description]
:rtype: [type]
"""
# re... | 5d0cde796dc4687af352de40e22df8d8e412bf8b | 3,631,129 |
def crosscorr(dfA, dfB, method='pearson', minN=0, adjMethod='fdr_bh'):
"""Pairwise correlations between A and B after a join,
when there are potential column name overlaps.
Parameters
----------
dfA,dfB : pd.DataFrame [samples, variables]
DataFrames for correlation assessment (Nans will be ... | 3c326a642cb7891298913db303792305b8f01b12 | 3,631,130 |
import torch
def normalize_gradient(netC, x):
"""
f
f_hat = --------------------
|| grad_f || + | f |
x: real_data_v
f: C_real before mean
"""
x.requires_grad_(True)
f = netC(x)
grad = torch.autograd.grad(
f, [x], torch.ones_like(f), create... | ff1b8b239cb86e62c801496b51d95afe6f6046d4 | 3,631,131 |
import numbers
def compile_snippet(tmpl, **kwargs):
"""
Compiles selected snipped with jinja2
:param tmpl: snippet name
:param kwargs: arguments passed to context
:return: generated HTML
"""
def wrapper(val):
if isinstance(val, numbers.Number):
return val
elif i... | 02926dc6b451d42d48c488811f8c4db9806f589e | 3,631,133 |
from typing import Optional
from re import T
def not_none(t: Optional[T], default: T):
"""
Returns `t` if not None, else `default`.
:param t: the value to return if not None
:param default: the default value to return
:return: t if not None, else default
"""
return t if t is not None else... | b49d9fb621af64e347dc02aebd93c6fb987e94c1 | 3,631,134 |
def fallback_feature(func):
"""Decorator to fallback to `batch_feature` in FeatureModule
"""
def wrapper(self, *args, **kwargs):
if self.features is not None:
ids = args[0] if len(args) > 0 else kwargs['batch_ids']
return FeatureModule.batch_feature(self, batch_ids=ids)
... | cb1fd52c6ddcbbf1d0065f70b5656ddda937440e | 3,631,135 |
def extract_segment_features(y, sr):
"""
Extract audio features from a segment of audio using librosa.
Input: An array of a audiofile.
Output: Dictionary of segments with keys:
tempo, beats, chroma_stft, rms, spec_cent, spec_bw, rolloff, zcr,
and mfcc values from 1-12.
"""
tem... | a64fde839199c8d800c9bae39799f353f71a4b5e | 3,631,136 |
def find_info_by_ep(ep):
""" 通过请求的endpoint寻找路由函数的meta信息"""
return manager.find_info_by_ep(ep) | 3fd834c9b17b1e0e2e58a60e790998c751c70743 | 3,631,137 |
def obtener_cantidad_total_turistas_entrantes_en_ciudad_anio(Ciudad, Anio):
"""
Dado una ciudad y un año obtiene la cantidad total de personas que llegan a esa ciudad de forma total
Dado una ciudad y un año obtiene la cantidad total de personas que llegan a esa ciudad de forma total
:param Ciudad: Ciuda... | c7512aa8e640afc3a84f94d1f0c1c3d82094921d | 3,631,138 |
def update_from_file(params, par_file):
"""Update the config dictionary params from file.
Args:
params (dict):
Dictionary holding the to-be-updated values.
par_file (str):
Name of the parameter file with the update values.
Returns:
params (dict):
... | 1de0f3fc3f379508cb29d38c6e9bd1b70fa1e9c7 | 3,631,139 |
def accumulated_other_comprehensive_income(ticker, frequency):
"""
:param ticker: e.g., 'AAPL' or MULTIPLE SECURITIES
:param frequency: 'A' or 'Q' for annual or quarterly, respectively
:return: obvious..
"""
df = financials_download(ticker, 'bs', frequency)
return (df.loc['Accumulated other ... | 81b02370790457db598cac699cc0ffa835b9f6ac | 3,631,140 |
def PDifHist (inPixHistFDR):
""" Return the differential pixel histogram
returns differential pixel histogram
inPixHistFDR = Python PixHistFDR object
"""
################################################################
# Checks
if not PIsA(inPixHistFDR):
raise TypeError("inPixHist... | eae6b0c354482b48c3ef9d39bb556ce7e9ef93ca | 3,631,141 |
def SendToRietveld(request_path, payload=None,
content_type="application/octet-stream", timeout=None):
"""Send a POST/GET to Rietveld. Returns the response body."""
def GetUserCredentials():
"""Prompts the user for a username and password."""
email = upload.GetEmail()
password = getp... | d0937307a894b55f4ed5534de81bb60bf1f46333 | 3,631,142 |
def _parse_args():
"""
For parsing args when run as __main__.
"""
parser = ArgumentParser(description='Simulates the action of a Turing Machine.')
parser.add_argument('path', help="Path of a file containing rule quintuples.")
parser.add_argument('input', help="Input string.")
parser.add_argument('--rules', ac... | 0b059e467703f34ac2358db19b87c06ab90b9771 | 3,631,143 |
def join_2_steps(boundaries, arguments):
"""
Joins the tags for argument boundaries and classification accordingly.
"""
answer = []
for pred_boundaries, pred_arguments in zip(boundaries, arguments):
cur_arg = ''
pred_answer = []
for boundary_tag in pred_boundari... | 9801ca876723d092f89a68bd45a138dba406468d | 3,631,144 |
def qac_image(image, idict=None, merge=True):
""" save a QAC dictionary, optionally merge it with an old one
return the new dictionary.
This dictionary is stored in a casa sub-table called "QAC"
image: input image
idict: new or updated dictionary. If blank, it return QAC
... | 32bd3ffac05455a7157c7471bad559df24702b6e | 3,631,145 |
import random
def get_random_useragent():
"""生成随机的UserAgent
:return: UserAgent字符串
"""
return random.choice(USER_AGENTS) | f70de4e52399a291e8d65633e8f555d748905fc6 | 3,631,146 |
def product_detail_view(request, pk='', **kwargs):
"""
Display a detailed view of a product, showing all specifications
"""
ctxt = {'pk': pk}
# Empty (thus invalid) pk
if pk == '':
return client_error_view(request, ERROR_MSG['wrong_prod_pk'].format(pk), 404)
matching_products = Product.objects.filter(pk=pk... | 3244156920798b4c3008ee2e8a19d5fd5de86559 | 3,631,147 |
def _convert_velocities(
velocities: np.ndarray, lattice_matrix: np.ndarray
) -> np.ndarray:
"""Convert velocities from atomic units to cm/s.
Args:
velocities: The velocities in atomic units.
lattice_matrix: The lattice matrix in Angstrom.
Returns:
The velocities in cm/s.
"... | 8848d58a37244b2109455a73c2fd2458b0e21c58 | 3,631,148 |
import operator
import math
def unit_vector(vec1, vec2):
""" Return a unit vector pointing from vec1 to vec2 """
diff_vector = map(operator.sub, vec2, vec1)
scale_factor = math.sqrt( sum( map( lambda x: x**2, diff_vector ) ) )
if scale_factor == 0:
scale_factor = 1 # We don't have an actu... | 79e2cff8970c97d6e5db5259801c58f82075b1a2 | 3,631,150 |
def shuffle_list(gene_list, rand=np.random.RandomState(0)):
"""Returns a copy of a shuffled input gene_list.
:param gene_list: rank_metric['gene_name'].values
:param rand: random seed. Use random.Random(0) if you like.
:return: a ranodm shuffled list.
"""
l2 = gene_list.copy()
rand... | 3e3660a2266bb8f5d7ea2172148806d20a4b1b2b | 3,631,151 |
def my_map(f, lst):
"""this does something to every object in a list"""
if(lst == []):
return []
return [f(lst[0])] + my_map(f, lst[1:]) | 20016cd580763289a45a2df704552ee5b5b4f25e | 3,631,152 |
import struct
import ipaddress
def read_ipv6(d):
"""Read an IPv6 address from the given file descriptor."""
u, l = struct.unpack('>QQ', d)
return ipaddress.IPv6Address((u << 64) + l) | c2006e6dde0de54b80b7710980a6b0cb175d3e19 | 3,631,153 |
def normalizeRounding(value):
"""
Normalizes rounding.
Python 2 and Python 3 handing the rounding of halves (0.5, 1.5, etc)
differently. This normalizes rounding to be the same (Python 3 style)
in both environments.
* **value** must be an :ref:`type-int-float`
* Returned value is a ``int``... | 442bbee5838f5bef0edbe6ce6e42f8c744f7d220 | 3,631,154 |
def pin_light(a: np.ndarray, b: np.ndarray) -> np.ndarray:
"""Combines lighten and darken blends.
:param a: The existing values. This is like the bottom layer in
a photo editing tool.
:param b: The values to blend. This is like the top layer in a
photo editing tool.
:param colorize: (Op... | f551bc26cebdbc6750fb42653ff23b4aeda09d6f | 3,631,155 |
from pathlib import Path
def sun():
"""Get Sun data source"""
filename = (
Path(nowcasting_dataset.__file__).parent.parent / "tests" / "data" / "sun" / "test.zarr"
)
return SunDataSource(
zarr_path=filename,
history_minutes=30,
forecast_minutes=60,
) | 06f9db778662d65e7a157b314b8a1cd3e647c7e7 | 3,631,156 |
def generate_level08():
"""Generate the bricks."""
bricks = bytearray(8 * 5 * 3)
colors = [2, 0, 1, 3, 4]
index = 0
col_x = 0
for x in range(6, 111, 26):
for y in range(27, 77, 7):
bricks[index] = x
bricks[index + 1] = y
bricks[index + 2] = colors[col_... | c1535d8efb285748693f0a457eb6fe7c91ce55d4 | 3,631,157 |
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