content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_mgga_data(mol, grid, rdm1):
"""
Get atomic orbital and density data.
See eval_ao and eval_rho docs for details.
Briefly, returns 0-3 derivatives of the atomic orbitals
in ao_data;
and the density, first derivatives of density,
Laplacian of density, and kinetic energy density
in r... | 11de048bbe320721204171d9786a997411b953d6 | 3,645,000 |
def _stringify_lmer_warnings(fg_lmer):
"""create grid w/ _ separated string of lme4::lmer warning list items, else "" """
warning_grids = fitgrid.utils.lmer.get_lmer_warnings(
fg_lmer
) # dict of indicator dataframes
warning_string_grid = pd.DataFrame(
np.full(fg_lmer._grid.shape, ""),... | bbd0fedb2480d4d1ef2a98689861c112552c0b59 | 3,645,001 |
def index():
"""Loads the index page for the 'Admin' controller
:returns: a dictionary to pass to the view with the list of ctr_enabled and the active module ('admin')
"""
ctr_data = get_ctr_data()
users = db().select(db.auth_user.ALL)
approvals = db(db.auth_user.registration_key=='pending').select(db.auth_user.... | 4b5dc978361b970d2dc6b2f5c6df28b06c9f28bf | 3,645,002 |
def get_language_codes():
"""Returns a list of available languages and their 2 char input codes
"""
languages = get_languages()
two_dig_codes = [k for k, v in languages.items()]
return two_dig_codes | 2e368b73783630835ee1ec32875318725f62d72e | 3,645,003 |
def fun_evaluate_ndcg(user_test_recom_zero_one):
"""
计算ndcg。所得是单个用户test的，最后所有用户的求和取平均
:param test_lst: 单个用户的test集
:param zero_one: 0/1序列
:param test_mask: 单个用户的test列表对应的mask列表
:return:
"""
test_lst, zero_one, test_mask, _ = user_test_recom_zero_one
test_lst = test_lst[:np.sum(test_ma... | 018dcf1095ebdd02e253ae6c1c36e17d1f13431a | 3,645,004 |
def prettyDataSize(size_in_bytes):
""" Takes a data size in bytes and formats a pretty string. """
unit = "B"
size_in_bytes = float(size_in_bytes)
if size_in_bytes > 1024:
size_in_bytes /= 1024
unit = "kiB"
if size_in_bytes > 1024:
size_in_bytes /= 1024
unit = "MiB"
... | 30eb068bafe2d9457ea43b59f2f62bdd0ce1c927 | 3,645,005 |
import os
def get_env(env_name: str) -> str:
"""
Safely read an environment variable.
Raises errors if it is not defined or it is empty.
:param env_name: the name of the environment variable
:return: the value of the environment variable
"""
if env_name not in os.environ:
raise KeyError(f"{env_name} not def... | 742a251561e02f59da667d8ebc586d5e0b399103 | 3,645,006 |
def image_resize_and_sharpen(image, size, preserve_aspect_ratio=False, factor=2.0):
"""
Create a thumbnail by resizing while keeping ratio.
A sharpen filter is applied for a better looking result.
:param image: PIL.Image.Image()
:param size: 2-tuple(width, height)
:param pre... | 7f581a0a8b1dccf62a3840269e7b2cea1e78a13b | 3,645,007 |
import subprocess
import pipes
def callHgsql(database, command):
""" Run hgsql command using subprocess, return stdout data if no error."""
cmd = ["hgsql", database, "-Ne", command]
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
cmdout, cmderr = p.communicate()
if p.retu... | d44dce04452323b417830fad1c34fb1ebca300fe | 3,645,008 |
def validate_mash(seq_list, metadata_reports, expected_species):
"""
Takes a species name as a string (i.e. 'Salmonella enterica') and creates a dictionary with keys for each Seq ID
and boolean values if the value pulled from MASH_ReferenceGenome matches the string or not
:param seq_list: List of OLC Se... | 9eb4fd6e1f156a4fed3cc0be0c5b7153a05b038b | 3,645,009 |
def style_strokes(svg_path: str, stroke_color: str='#ff0000',
stroke_width: float=0.07559055) -> etree.ElementTree:
"""Modifies a svg file so that all black paths become laser cutting paths.
Args:
svg_path: a file path to the svg file to modify and overwrite.
stroke_color: the... | 6387625cd71143edb632833cd40006858f239089 | 3,645,010 |
import json
def preview_pipeline(
pipeline: Pipeline, domain_retriever: DomainRetriever, limit: int = 50, offset: int = 0
) -> str:
"""
Execute a pipeline but returns only a slice of the results, determined by `limit` and `offset` parameters, as JSON.
Return format follows the 'table' JSON table sche... | f1e640ec73bbdeb978762774c81d80e00e98adc9 | 3,645,011 |
def redirect_to_url(url):
"""
Return a bcm dictionary with a command to redirect to 'url'
"""
return {'mode': 'redirect', 'url': url} | 01e4deb80bbd8f8e119c99d64001866c6cd644d9 | 3,645,012 |
def get_xml_tagged_data(buffer, include_refstr=True):
"""
figure out what format file it is and call the
respective function to return data for training
:param buffer:
:param include_refstr: during training do not need refstr
:return:
"""
if len(buffer) > 1 and 'http://www.elsevier.com/... | e51cdde728d3e4c5c1f4936bfeb874be8aabf292 | 3,645,013 |
from typing import Dict
from typing import Any
def de_dup(
data: pd.DataFrame,
drop_duplicates_kwargs: Dict[str, Any] = {},
) -> pd.DataFrame:
"""Drop duplicate rows
"""
return data.drop_duplicates(**drop_duplicates_kwargs) | 2cd78627226170af7e184bc60caa5ee39290ab42 | 3,645,014 |
def get_task_defs(workspace: str, num_validators: int, num_fullnodes: int) -> dict:
"""
Builds a dictionary of:
family -> current_task_def
task_def can be used to get the following when updating a service:
- containerDefinitions
- volumes
- placementConstraints
NOTE: on... | 99c131ac60999dd1b2b657575e40f2b813633f61 | 3,645,015 |
from azure.mgmt.marketplaceordering.models import OfferType
def get_terms(cmd, urn=None, publisher=None, offer=None, plan=None):
"""
Get the details of Azure Marketplace image terms.
:param cmd:cmd
:param urn:URN, in the format of 'publisher:offer:sku:version'. If specified, other argument values can ... | 7483e6d150b784535dd47ead0b63d079e66c391d | 3,645,016 |
def encode_payload( result ):
"""JSON encodes a dictionary, named tuple, or object for sending
to the server
"""
try:
return tornado.escape.json_encode( result )
except TypeError:
if type( result ) is list:
return [ tornado.escape.json_encode( r ) for r in result ]
... | 551264dcb0b9ad6d380b8ae393b2dfbfafb93dee | 3,645,017 |
def relu(shape) -> np.ndarray:
"""
Creates a gaussian distribution numpy array with a mean of 0 and variance of sqrt(2/m).
Arguments:
shape : tuple : A tuple with 2 numbers, specifying size of the numpy array.
Returns:
output : np.ndarray : A uniform numpy array.
"""
return np.random.normal(0, np.s... | e41835dc5e6de8f0b6161c8ea73afeffd8f84c31 | 3,645,018 |
def reset_all():
"""Batch reset of batch records."""
_url = request.args.get("url") or request.referrer
task_id = request.form.get("task_id")
task = Task.get(task_id)
try:
count = utils.reset_all_records(task)
except Exception as ex:
flash(f"Failed to reset the selected records:... | a4241ce81531db7d18d226327f6a96b600a50fd0 | 3,645,019 |
def update_to_report(db, data, section_name, img_path,id):
"""
Update data of report
"""
query = '''UPDATE report
SET data = "{}" ,
section_name = "{}",
image_path = "{}"
WHERE id = "{}" '''.format(data, section_name, img_path, id)
result = ge... | 995d17b364bcb6a0b338b1b0323b0fd1f7692f25 | 3,645,020 |
from datetime import datetime
def keyboard(table, day=None):
"""Handler for showing the keyboard statistics page."""
cols, group = "realkey AS key, COUNT(*) AS count", "realkey"
where = (("day", day),) if day else ()
counts_display = counts = db.fetch(table, cols, where, group, "count DESC")
if "c... | d3053f06b85d6606353b71a76096558d760e5a8e | 3,645,021 |
import base64
import logging
def fetch(uri, username='', password=''):
"""Can fetch with Basic Authentication"""
headers = {}
if username and password:
headers['Authorization'] = 'Basic ' + base64.b64encode('%s:%s' % (username, password))
headers['User-Agent'] = 'Twimonial'
f = urlfetch.fetch(uri, ... | e28e96c049d7b4844ca23bd8943b00b29ede3419 | 3,645,022 |
def tsCrossValidationScore(params, series,loss_function=mean_squared_error, nsplits=3, slen=1):
"""
#Parameters:
params : vector of parameters for optimization (three parameters:
alpha, beta, gamma for example
series : dataset with timeseries
sle:
... | f3278ad55a423f6df0b108636c88151a72451cfa | 3,645,023 |
from typing import Any
def get_psf_fwhm(psf_template: np.ndarray) -> float:
"""
Fit a symmetric 2D Gaussian to the given ``psf_template`` to
estimate the full width half maximum (FWHM) of the central "blob".
Args:
psf_template: A 2D numpy array containing the unsaturated
PSF templ... | 1982d89eb5f952d10336003e4d580fda3ab210b7 | 3,645,024 |
def sqrt(number):
"""
Calculate the floored square root of a number
Args:
number(int): Number to find the floored squared root
Returns:
(int): Floored Square Root
"""
assert number >= 0, 'Only square root of positive numbers are valid'
start = 0
end = number
res = None... | 7ed4d547e0dbabebff7ffdf1e368817a415cbb9e | 3,645,025 |
def repetition_sigmoid(M):
"""
Used to model repetition-driven effects of STDP. More repetitions results in stronger increase/decrease.
"""
return 1.0/(1+np.exp(-0.2*M+10)) | 5cfae40b12f2ff871b60f9cad13308b8bb9189b9 | 3,645,026 |
def generate_features(ids0, ids1, forcefield, system, param):
"""
This function performs a minimization of the energy and computes the matrix features.
:param ids0: ids of the atoms for the 1st protein
:param ids1: ids of the atoms for the 2nd protein
:param forcefield: forcefield for OpenMM simula... | 86fbc0fa67ea5a14b38af4c1fc37566b066b50a3 | 3,645,027 |
def extract_bow_feature_vectors(reviews, dictionary):
"""
Inputs a list of string reviews
Inputs the dictionary of words as given by bag_of_words
Returns the bag-of-words feature matrix representation of the data.
The returned matrix is of shape (n, m), where n is the number of reviews
and m the... | 3373179024127ab0202ab50f3e20184d02ed016c | 3,645,028 |
from astropy.io.fits import Header
from scipy.optimize import least_squares
def model_wcs_header(datamodel, get_sip=False, order=4, step=32):
"""
Make a header with approximate WCS for use in DS9.
Parameters
----------
datamodel : `jwst.datamodels.ImageModel`
Image model with full `~g... | 1b43d5382b92f7da47d72dcf5acaaca65c6329df | 3,645,029 |
def create_session():
"""Return a session to be used for database connections
Returns:
Session: SQLAlchemy session object
"""
# Produces integrity errors!
# return _Session()
# db.session is managed by Flask-SQLAlchemy and bound to a request
return db.session | 8c7dbc2ee1db64cfbbb3466704a7e4f70ef073be | 3,645,030 |
def meta_to_indexes(meta, table_name=None, model_name=None):
"""Find all the indexes (primary keys) based on the meta data
"""
indexes, pk_field = {}, None
indexes = []
for meta_model_name, model_meta in meta.iteritems():
if (table_name or model_name) and not (table_name == model_meta['Met... | 12c12055f424680a68d81d5466dc6d3515d797a5 | 3,645,031 |
def index():
"""Render and return the index page.
This is a informational landing page for non-logged-in users, and the corp
homepage for those who are logged in.
"""
success, _ = try_func(auth.is_authenticated)
if success:
module = config.get("modules.home")
if module:
... | 9ebc7a98ee60a59a5bed6ec5a726c5c1a5a11ca7 | 3,645,032 |
def _(origin, category="", default=None):
"""
This function returns the localized string.
"""
return LOCALIZED_STRINGS_HANDLER.translate(origin, category, default) | 58f1d7033b1689068bf1bcb532eea78e8bf51250 | 3,645,033 |
from datetime import datetime
def next_month(month: datetime) -> datetime:
"""Find the first day of the next month given a datetime.
:param month: the date
:type month: datetime
:return: The first day of the next month.
:rtype: datetime
"""
dt = this_month(month)
return datetime((dt+_... | 1d5cb70fa7b3d98689e3dd967aa95deb29f5de45 | 3,645,034 |
from typing import Mapping
from typing import OrderedDict
def walk_json(d, func):
""" Walk over a parsed JSON nested structure `d`, apply `func` to each leaf element and replace it with result
"""
if isinstance(d, Mapping):
return OrderedDict((k, walk_json(v, func)) for k, v in d.items())
elif... | cc977f4cf3eaec03bd591fa4cd1e44ab5717caee | 3,645,035 |
def getUser():
"""This method will be called if a GET request is made to the /user/ route
It will get the details of a specified user
Parameters
----------
username
the name of the user to get info about
Raises
------
DoesNotExist
Raised if the username provided doe... | edc8570b83e4a173ac8028f2d8b51e93a19b27a1 | 3,645,036 |
import types
def _create_ppo_agent(
time_step_spec: types.NestedTensorSpec, action_spec: types.NestedTensorSpec,
preprocessing_layers: types.NestedLayer,
policy_network: types.Network) -> tfa.agents.TFAgent:
"""Creates a ppo_agent."""
actor_network = policy_network(
time_step_spec.observation,
... | 931e7078bdf634187ac0a506decb2d651373fbab | 3,645,037 |
def stiffness_matrix_CST(element=tetra_4()):
"""Calculate stiffness matrix for linear elasticity"""
element.volume()
B = strain_matrix_CST(element)
D = material()
print('B')
print(B)
print('V',element.V)
return element.V * np.dot(np.dot(np.transpose(B),D),B) | 5c5c443ab1007997848357d698fcce91f069a13f | 3,645,038 |
async def can_action_member(bot, ctx: SlashContext, member: discord.Member) -> bool:
""" Stop mods from doing stupid things. """
# Stop mods from actioning on the bot.
if member.id == bot.user.id:
return False
# Stop mods from actioning one another, people higher ranked than them or themselves.... | c3fa4eee66ec80df2c4f91cfee181d900f0b8c45 | 3,645,039 |
import types
def trim_waveform_signal(
tr: obspy.Trace,
cfg: types.ModuleType = config
) -> obspy.Trace:
"""Cut the time series to signal window
Args:
tr: time series
cfg: configuration file
Returns:
tr: trimmed time series
"""
starttime, en... | bce3a0f88903b7c62c287f6e40bb7d377215a45d | 3,645,040 |
def animation_plot(
x,
y,
z_data,
element_table,
ani_fname,
existing_fig,
ani_funcargs=None,
ani_saveargs=None,
kwargs=None,
):
"""
Tricontourf animation plot.
Resulting file will be saved to MP4
"""
global tf
# Subtract 1 from element table to alig... | e9ef60c6240900de6fd082ff5933dbbbc471933a | 3,645,041 |
def preprocess_adj(adj):
"""Preprocessing of adjacency matrix for simple GCN model and conversion to tuple representation."""
# adj_appr = np.array(sp.csr_matrix.todense(adj))
# # adj_appr = dense_lanczos(adj_appr, 100)
# adj_appr = dense_RandomSVD(adj_appr, 100)
# if adj_appr.sum(1).min()<0:
# ... | 82674be0b9573c24135e56f2a5e3988fbb0966e1 | 3,645,042 |
def plot_figure_one_input_resource_2(style_label=""):
"""
Plot two bar graphs side by side, with letters as x-tick labels.
latency_dev_num_non_reuse.log
"""
prng = np.random.RandomState(96917002)
#plt.set_cmap('Greys')
#plt.rcParams['image.cmap']='Greys'
# Tweak the figure size to b... | 69c25829adf9ef3d5dc818621bb724bb92c29f31 | 3,645,043 |
def comp_rot_dir(self):
"""Compute the rotation direction of the winding
Parameters
----------
self : LamSlotWind
A LamSlotWind object
Returns
-------
rot_dir : int
-1 or +1
"""
MMF = self.comp_mmf_unit()
p = self.get_pole_pair_number()
# Compute rotation ... | 524fdfd195a70bcd07b89e594a90e624ec4db4ea | 3,645,044 |
def search_pk(uuid):
"""uuid can be pk."""
IterHarmonicApprox = WorkflowFactory("phonopy.iter_ha")
qb = QueryBuilder()
qb.append(IterHarmonicApprox, tag="iter_ha", filters={"uuid": {"==": uuid}})
PhonopyWorkChain = WorkflowFactory("phonopy.phonopy")
qb.append(PhonopyWorkChain, with_incoming="ite... | d1a8d9d32e6d3272d49163ee8abf74363a520c8d | 3,645,045 |
def _region_bulk(mode='full', scale=.6):
"""
Estimate of the temperature dependence of bulk viscosity zeta/s.
"""
plt.figure(figsize=(scale*textwidth, scale*aspect*textwidth))
ax = plt.axes()
def zetas(T, zetas_max=0, zetas_width=1):
return zetas_max / (1 + ((T - Tc)/zetas_width)**2)
... | 9a76f28b47a5e8c1ce45a9ea0dcaef723032bcce | 3,645,046 |
def bias(struct,subover=True,trim=True, subbias=False, bstruct=None,
median=False, function='polynomial',order=3,rej_lo=3,rej_hi=3,niter=10,
plotover=False, log=None, verbose=True):
"""Bias subtracts the bias levels from a frame. It will fit and subtract the overscan
region, trim the images... | 035da6b5eaa73a30ffec3f148d33199b275529a8 | 3,645,047 |
def getItemStatus(selected_item, store_id, num_to_average):
""" Method pulls the stock status of the selected item in the given store
:param selected_item: current item being processed (toilet paper or hand sanitizer)
:param store_id: id of the current store
:param num_to_average: number of recent stat... | 00c0ecdec56ac4446b3db247fd234daeecada589 | 3,645,048 |
def filter_and_copy_table(tab, to_remove):
""" Filter and copy a FITS table.
Parameters
----------
tab : FITS Table object
to_remove : [int ...}
list of indices to remove from the table
returns FITS Table object
"""
nsrcs = len(tab)
mask = np.zeros((nsrcs), '?')
mas... | cc13a002715c36cc2c07b836a5045cfb62311529 | 3,645,049 |
def _archive_logs(conn, node_type, logger, node_ip):
"""Creates an archive of all logs found under /var/log/cloudify plus
journalctl.
"""
archive_filename = 'cloudify-{node_type}-logs_{date}_{ip}.tar.gz'.format(
node_type=node_type,
date=get_host_date(conn),
ip=node_ip
)
... | 970683258d664a1170fe9ab5253287313fa9f871 | 3,645,050 |
def get_scripts():
"""Returns the list of available scripts
Returns:
A dict holding the result message
"""
return Response.ok("Script files successfully fetched.", {
"scripts": list_scripts()
}) | 5aa2ecd9a19c3e4d577c679e5249b71b01b62f20 | 3,645,051 |
from typing import Any
from typing import Optional
import functools
import contextvars
import asyncio
from typing import cast
async def invoke(
fn: callbacks.BaseFn,
*args: Any,
settings: Optional[configuration.OperatorSettings] = None,
cause: Optional[causation.BaseCause] = None,
... | 4f132bab3eaae0ebe64f4cfdcfefa89cd2b59f3f | 3,645,052 |
import sys
def getLatestFare(_origin, _destination, _date):
"""
_origin and _destination take airport codes , e.g. BLR for Bangalore
_date in format YYYY-MM-DD e.g.2016-10-30
Returns either:
10 latest results from the results page.
1 lastest result from the results page.
"""
tr... | 209c9c4ee05dc25b575565b0953097049ba21c28 | 3,645,053 |
from datetime import datetime
def home():
"""Renders the home page."""
return render_template(
'index.html',
title='Rococal',
year=datetime.now().year,
) | 4cee1eed6c45d79aad0acebdd55ed61ef7dff9da | 3,645,054 |
def Dx(x):
"""Nombre de survivants actualisés.
Args:
x: l'âge.
Returns:
Nombre de survivants actualisés.
"""
return lx(x)*v**x | 886fdfb8b5337e9520f94fa937cb967328391823 | 3,645,055 |
def tracek(k,aee,aii,see,sii,tau=1,alpha=0):
""" Trace of recurrently connected network of E,I units, analytically determined
input:
k: spatial frequency
aee: ampltidue E to E connectivity
aii: ampltidue I to I connectivity
see: standard deviation/width of E to E connectivity
sii: standard deviation/width of I ... | 005c612f8d54b4ba61b7e701d40b9814136695b4 | 3,645,056 |
import os
def set_working_dir_repo_root(func):
"""
Decorator for checking whether the
current working dir is set as root of repo.
If not, changes the working dir to root of repo
Returns
-------
"""
def inner(*args, **kwargs):
git_repo = git.Repo(".", search_parent_directories... | 07a6d667129d94557fdd20956124933920338e30 | 3,645,057 |
def get_verbose_name(model_or_queryset, field):
"""
returns the value of the ``verbose_name`` of a field
typically used in the templates where you can have a dynamic queryset
:param model_or_queryset: target object
:type model_or_queryset: :class:`django.db.models.Model`, :class:`django.db.query.... | 1f395d62a20b307dce2f802c498630fd237aec33 | 3,645,058 |
def if_then_else(cond, t, f, span=None):
"""Conditional selection expression.
Parameters
----------
cond : PrimExpr
The condition
t : PrimExpr
The result expression if cond is true.
f : PrimExpr
The result expression if cond is false.
span : Optional[Span]
... | dba758c13d3108244f389f0cbae97c1eeb1f8e04 | 3,645,059 |
import argparse
def get_args() -> argparse.Namespace:
"""Get arguments."""
parser = argparse.ArgumentParser(description="Dump Instance")
parser.add_argument(
"network_state_path", type=str, help="File path to network state dump JSON."
)
parser.add_argument("--host", type=str, help="Host to... | 30b1aacc2c13d1ac8fad3411b95d9aeabf625f62 | 3,645,060 |
def get_resources(filetype):
"""Find all HTML template or JavaScript files in the package.
Caches the results for quick access.
Parameters
----------
filetype : {'templates', 'js'}
The type of file resource needed.
Returns
-------
:class:`dict`
A dictionary mapping fil... | 73244ac590db5a310170142b6b43b7840cfc94ca | 3,645,061 |
def sum_fn(xnum, ynum):
""" A function which performs a sum """
return xnum + ynum | 61a1ae2e4b54348b9e3839f7f2779edd03f181df | 3,645,062 |
def categorical_iou(y_true, y_pred, target_classes=None, strict=True):
"""画像ごとクラスごとのIoUを算出して平均するmetric。
Args:
target_classes: 対象のクラスindexの配列。Noneなら全クラス。
strict: ラベルに無いクラスを予測してしまった場合に減点されるようにするならTrue、ラベルにあるクラスのみ対象にするならFalse。
"""
axes = list(range(1, K.ndim(y_true)))
y_classes = K.ar... | b79f399479127271c3af3ee9b28203622f8d17fe | 3,645,063 |
def convert_string(string: str, type: str) -> str:
"""Convert the string by [e]ncrypting or [d]ecrypting.
:param type: String 'e' for encrypt or 'd' for decrypt.
:return: [en/de]crypted string.
"""
hash_string = hash_()
map_ = mapping(hash_string)
if type.lower() == 'e':
output = e... | 824122fa035dcb164f21eadb5c0e840f8acd2914 | 3,645,064 |
def create_saml_security_context(token, private_key):
"""
Create a security context for SAML token based
authentication scheme
:type token: :class:`str`
:param token: SAML Token
:type private_key: :class:`str`
:param private_key: Absolute file path of the private key of the user
:rtyp... | 430e71697eb3e5b3df438f400a7f07ab8e936af7 | 3,645,065 |
def predictIsDeviceLeftRunning():
"""
Returns if the device is presumed left running without a real need
---
parameters:
name: -device_id
in: query
description: the device id for which the prediction is made
required: false
style: form
explode: true
... | 8a50962f3c52e100d79a74413df0d4bf8230bafd | 3,645,066 |
from typing import Optional
from typing import Callable
from pathlib import Path
def load(
source: AnyPath,
wordnet: Wordnet,
get_synset_id: Optional[Callable] = None,
) -> Freq:
"""Load an Information Content mapping from a file.
Arguments:
source: A path to an information content weigh... | 962bdfbe5d101bdeae966566c16d8a7216c36d8b | 3,645,067 |
from datetime import datetime
def iso_time_str() -> str:
"""Return the current time as ISO 8601 format
e.g.: 2019-01-19T23:20:25.459Z
"""
now = datetime.datetime.utcnow()
return now.isoformat()[:-3]+'Z' | 203617006175079181d702f7d7ed6d2974714f2e | 3,645,068 |
def mass(snap: Snap) -> Quantity:
"""Particle mass."""
massoftype = snap._file_pointer['header/massoftype'][()]
particle_type = np.array(
np.abs(get_dataset('itype', 'particles')(snap)).magnitude, dtype=int
)
return massoftype[particle_type - 1] * snap._array_code_units['mass'] | cf67d66f1e1a47f162b5e538444d2c406b377238 | 3,645,069 |
import os
def _build_pytest_test_results_path(cmake_build_path):
"""
Build the path to the Pytest test results directory.
:param cmake_build_path: Path to the CMake build directory.
:return: Path to the Pytest test results directory.
"""
pytest_results_path = os.path.join(cmake_build_path, TES... | 52198ce508d5d30c322da285c66ff9ba45418ebd | 3,645,070 |
import logging
async def create_object_detection_training(
train_object_detection_model_request: TrainImageModel,
token: str = Depends(oauth2_scheme),
):
"""[API router to train AutoML object detection model]
Args:
train_object_detection_model_request (TrainImageModel): [Train AutoML Object d... | 293dc0bfd8acb52a3207138e13028b6766c7be20 | 3,645,071 |
import torch
def batchify_rays(rays_flat, chunk=1024*32, random_directions=None, background_color=None, **kwargs):
"""Render rays in smaller minibatches to avoid OOM.
"""
all_ret = {}
for i in range(0, rays_flat.shape[0], chunk):
ret = render_rays(rays_flat[i:i+chunk], random_directions=random... | 9897575462e47f98016ebd0a2fcaee186c440f9a | 3,645,072 |
def extract_surfaces(pvol):
""" Extracts surfaces from a volume.
:param pvol: input volume
:type pvol: abstract.Volume
:return: extracted surface
:rtype: dict
"""
if not isinstance(pvol, BSpline.abstract.Volume):
raise TypeError("The input should be an instance of abstract.Volume")
... | cd2b24f200adf9f5ff29cc847693d57d450521ad | 3,645,073 |
import os
import logging
def read_file(filepath: str, config: Config = DEFAULT_CONFIG) -> pd.DataFrame:
"""
Read .csv, .xlsx, .xls to pandas dataframe. Read only a certain sheet name and skip
to header row using sheet_name and header_index.
:filepath: path to file (str)
:config: dtype... | 09f9e626be020cf2d3c02a09863489cf84735c05 | 3,645,074 |
def euler2quaternion( euler_angs ):
"""
Description
-----------
This code is directly from the following reference
[REF] https://computergraphics.stackexchange.com/questions/8195/how-to-convert-euler-angles-to-quaternions-and-get-the-same-euler-angles-back-fr
Conv... | 307385911573af8a6e65617a8b438ca680130b79 | 3,645,075 |
def run_server(server, thread=False, port=8080):
"""
Runs the server.
@param server if None, it becomes ``HTTPServer(('localhost', 8080), SimpleHandler)``
@param thread if True, the server is run in a thread
and the function returns right away,
... | 524b58f012a1029e52d845f40a20e2ae1f7f9c0a | 3,645,076 |
def validate(aLine):
"""
>>> validate(b"$GPGSA,A,2,29,19,28,,,,,,,,,,23.4,12.1,20.0*0F")
[b'GPGSA', b'A', b'2', b'29', b'19', b'28', b'', b'', b'', b'', b'', b'', b'', b'', b'', b'23.4', b'12.1', b'20.0']
>>> validate(b"$GPGSA,A,2,29,19,28,,,,,,,,,,23.4,") # doctest: +IGNORE_EXCEPTION_DETAIL
Traceb... | a8f302f0a03f567bc3c61930ecdf147ff9670b04 | 3,645,077 |
def matlabize(s):
"""Make string s suitable for use as a MATLAB function/script name"""
s = s.replace(' ', '_')
s = s.replace('.', '_')
s = s.replace('-', '_')
assert len(s) <= 63 # MATLAB function/script name length limitation
return s | 5dccb9497a3ee28dae5fb7de6e15a1fa02f144cf | 3,645,078 |
def getApiResults(case, installer, version, criteria):
"""
Get Results by calling the API
criteria is to consider N last results for the case success criteria
"""
results = json.dumps([])
# to remove proxy (to be removed at the end for local test only)
# proxy_handler = urllib2.ProxyHandler... | d54eaf785bc1e80e633cf3f6588f135c54425b79 | 3,645,079 |
def generate_noisy_gaussian(center, std_dev, height, x_domain, noise_domain,
n_datapoints):
"""
Generate a gaussian with some aspect of noise.
Input:
center = central x value
std_dev = standard deviation of the function
height = height (y-off set) of the ... | 5120bb23be1b98663b61ad67df0aa43c61ed1714 | 3,645,080 |
from typing import Tuple
def filter_group_delay(
sos_or_fir_coef: np.ndarray,
N: int = 2048,
fs: float = None,
sos: bool = True,
) -> Tuple[np.ndarray, np.ndarray]:
"""
Given filter spec in second order sections or (num, den) form, return group delay.
Uses method in [1], which is cited by ... | 9cdcf30db5f1308dac27ce057f392fb38d805f1f | 3,645,081 |
import re
def query():
"""Perform a query on the dataset, where the search terms are given by the saleterm parameter"""
# If redis hasn't been populated, stick some tweet data into it.
if redis_db.get("tweet_db_status") != "loaded":
tweet_scraper.add_tweets(default_num_tweets_to_try)
sale_ter... | 9cdb937d45b1314884afb0d53aee174ef160f8a8 | 3,645,082 |
def get_spec_res(z=2.2, spec_res=2.06, pix_size=1.8):
""" Calculates the pixel size (pix_size) and spectral resolution (spec_res) in
km/s for the MOCK SPECTRA.
arguments: z, redshift. spec_res, spectral resoloution in Angst. pixel_size
in sngst.
returns:
(pixel_size, spec_res) in km/s
"""
... | 597db8ce00c071624b0877fe211ab9b01ec889de | 3,645,083 |
from datetime import datetime
import os
def _process_general_config(config: ConfigType) -> ConfigType:
"""Process the `general` section of the config
Args:
config (ConfigType): Config object
Returns:
[ConfigType]: Processed config
"""
general_config = deepcopy(config.general)
... | 370367f718c3830964c6f5f276b1d699400fd1ab | 3,645,084 |
def api_response(response):
"""Response generation for ReST API calls"""
# Errors present
if response.message:
messages = response.message
if not isinstance(messages, list):
messages = [messages]
# Report the errors
return Response({'errors': messages}, status=s... | f41bca36b1cabc6002f730b3b40170415baffc62 | 3,645,085 |
from tensorflow.python.training import moving_averages
def batch_norm(name, inpvar, decay=0.9, epsilon=1e-5, use_affine=True, param_dtype=__default_dtype__):
"""
Batch normalization.
:param name: operator name
:param inpvar: input tensor, of data type NHWC
:param decay: decay for moving average
... | 74565379d15d4ec7cfa647a4f7833328f2c86ac7 | 3,645,086 |
import os
def get_engine(onnx_file_path, engine_file_path="", input_shapes=((1, 3, 640, 640)), force_rebuild=False):
"""Attempts to load a serialized engine if available, otherwise builds a new TensorRT engine and saves it."""
assert len(input_shapes) in [1, 3], 'length of input_shapes should be 1 or 3, 3 fo... | 57489225c3854408f880f024443811d59c88df9f | 3,645,087 |
from typing import Callable
def _window_when(closing_mapper: Callable[[], Observable]) -> Callable[[Observable], Observable]:
"""Projects each element of an observable sequence into zero or
more windows.
Args:
source: Source observable to project into windows.
Returns:
An observable ... | d0f51f8385b2d45f1cbd64649953c312247644eb | 3,645,088 |
def generate_features(df):
"""Generate features for a stock/index based on historical price and performance
Args:
df(dataframe with columns "Open", "Close", "High", "Low", "Volume", "Adjusted Close")
Returns:
dataframe, data set with new features
"""
df_new = pd.DataFrame()
#... | ec64c9562287e0dd32b7cfd07c477acd8d799dc3 | 3,645,089 |
from typing import Dict
from typing import Union
from typing import Optional
def format_plate(barcode: str) -> Dict[str, Union[str, bool, Optional[int]]]:
"""Used by flask route /plates to format each plate. Determines whether there is sample data for the barcode and if
so, how many samples meet the fit to pi... | 5508ee508ef6d2a8329a2899bf9e90c9ac399874 | 3,645,090 |
def method_only_in(*states):
"""
Checks if function has a MethodMeta representation, calls wrap_method to
create one if it doesn't and then adds only_in to it from *states
Args:
*args(list): List of state names, like DefaultStateMachine.RESETTING
Returns:
function: Updated function... | 33fbd619deb4b2a1761b3bf7f860ed2ae728df44 | 3,645,091 |
import igraph
def to_igraph(adjacency_matrix:Image, centroids:Image=None):
"""
Converts a given adjacency matrix to a iGraph [1] graph data structure.
Note: the given centroids typically have one entry less than the adjacency matrix is wide, because
those matrices contain a first row and column repre... | e0cac1dd85b79b30e3f7e3139201b97e092603eb | 3,645,092 |
def Laplacian(src, ddepth, dst=None, ksize=1, scale=1, delta=0, borderType=cv2.BORDER_DEFAULT):
"""dst = cv.Laplacian( src, ddepth[, dst[, ksize[, scale[, delta[, borderType]]]]] )
Executes the Laplacian operator on hardware if input parameters fit to hardware constraints.
Otherwise the OpenCV Laplacian fun... | 88237f83ed9b2159829f4a9b194c18007699c1a9 | 3,645,093 |
def get_docptr(n_dw_matrix):
"""
Parameters
----------
n_dw_matrix: array-like
Returns
-------
np.array
row indices for the provided matrix
"""
return _get_docptr(n_dw_matrix.shape[0], n_dw_matrix.indptr) | 7a20ca17f16475d6fd836bb5b7b70221f5cf4378 | 3,645,094 |
def check_if_shift_v0(data, column_name, start_index, end_index, check_period):
""" using median to see if it changes significantly in shift """
period_before = data[column_name][start_index - check_period: start_index]
period_in_the_middle = data[column_name][start_index:end_index]
period_after = data[... | e73629dae7d6cce70b344f24acb98a3ae24c4e64 | 3,645,095 |
def opening2d(value, kernel, stride=1, padding="SAME"):
"""
erode and then dilate
Parameters
----------
value : Tensor
4-D with shape [batch, in_height, in_width, depth].
kernel : Tensor
Must have the same type as 'value'. 3-D with shape '[kernel_height, kernel_width, depth]... | b425735dacceac825b4394fdc72a744b168acc91 | 3,645,096 |
def convert_npy_mat(user_num, item_num, df):
"""
method of convert dataframe to numpy matrix
Parameters
----------
user_num : int, the number of users
item_num : int, the number of items
df : pd.DataFrame, rating dataframe
Returns
-------
mat : np.matrix, rating matrix
"""
... | 627fcc45a490be1554445582dc8a2312e25b1152 | 3,645,097 |
def user_enter_state_change_response():
"""
Prompts the user to enter a key event response.
nothing -> str
"""
return input('>> ') | 22da5cb99fa603c3dff04e8afd03cb9fae8210cd | 3,645,098 |
def call_worker(job_spec):
"""Calls command `cron_worker run <job_spec>` and parses the output"""
output = call_command("cron_worker", "run", job_spec)
status = exc_class_name = exc_message = None
if output:
result_match = RESULT_PATTERN.match(output)
if result_match:
status ... | 5a914c742319e2528b1668309ff57e507efd26bb | 3,645,099 |
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