content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def qrGetGuidesColorFromGuidesNode( guidesNode ):
"""
This method sets the color from the guides node.
It returns the color of the root of all the guides.
"""
return cmds.getAttr( '%s.overrideColorRGB' % guidesNode )[ 0 ] | fbd909e0bbd1dcc12dd5f6c8f74b500d497a4dba | 3,623,139 |
def dbconn_mysql(host=None, user=None, password=None, database=None, port=3306,
from_file=False, filename=None):
"""
Return MySQL database connection and cursor objects. Prompt for
missing credentials.
DESIGN:
Function designed to create a connection to a MySQL database
using ... | 3d2cbe7a775e03446f5912606aca7ce4cb4f9ba2 | 3,623,140 |
def apply_coefficients_for_band(numpyarray, band, regression_coefficients):
"""
Apply regression coefficients in the form: ETM = c0 + OLI*c1
As per table 2 in http://www.mdpi.com/2072-4292/6/9/7952/htm
:param numpyarray: array of measurements to apply coefficients to
:param band: name of the coeffic... | 679c18885fed81de5ea2fe76f03bcf37b017e437 | 3,623,141 |
def append_to_csv(file_name, nda_str, set_id_group):
"""
Output all doc in set_id to a csv file.
Parameters:
file_name (Path): filename to store exported csv
nda_str (String): ex "12345-23456"
set_id_group (String): ex: "7b5489a1-e30f-450f-bd2b-00d05fd52915"
"""
_logger.info... | 37cdf883e74d100a9d71be5743aeabf883474b04 | 3,623,142 |
from typing import Callable
def _sumprod(
func: Callable,
values: np.ndarray,
mask: np.ndarray,
*,
skipna: bool = True,
min_count: int = 0,
):
"""
Sum or product for 1D masked array.
Parameters
----------
func : np.sum or np.prod
values : np.ndarray
Numpy array... | 0a47863f256cb6a60cb6adad27c036e879a188ff | 3,623,143 |
import tarfile
def files_from_archive(tar_archive: tarfile.TarFile):
"""
Extracts only the actual files from the given tarfile
:param tar_archive: the tar archive from which to extract the files
:return: List of file object extracted from the tar archive
"""
file_members = []
# Find the ... | 09ead0b2b955afdc5bf96a8e0a8717989c155406 | 3,623,144 |
def regular_wl_axis(axis, xlims=None):
"""
Converts a wavenumber axis ([cm-1]) into a regular (==equally spaced) wavelength axis ([Angstroms])
Parameters
----------
axis : 1D :class:`~numpy:numpy.ndarray`
Input axis in cm-1
xlims : tuple of floats
(Optional) limits in cm-1 to re... | 62952e855aaba730be77c56e0ada6712ea1b62d9 | 3,623,145 |
def load_stack_plane(image,c,z,x,y,w,h):
"""
Load ROI of a Z plane from every time point in OMERO image
Inputs:
image: OMERO ImageWrapper
c: int, channel
z: int, plane
x: float, x corner of ROI
y: float, y corner of ROI
width: int, width of ROI
height:... | 41b65078b83360776757d4a6ea001557482849a9 | 3,623,146 |
from typing import Optional
def read_file(href: HREF, stac_io: Optional[StacIO] = None) -> STACObject:
"""Reads a STAC object from a file.
This method will return either a Catalog, a Collection, or an Item based on what
the file contains.
This is a convenience method for :meth:`StacIO.read_stac_obje... | 75132349e139af5dc52c2be424b4cdd5d1ae062a | 3,623,147 |
def gcn_encoder(features, hparams, embed_scope,
embed_token_fn=common_embed.embed_tokens,
adjcency_feature="obj_dom_dist",
discretize=True):
"""Encodes a screen using Graph Convolution Networks.
Args:
features: the feature dict.
hparams: the hyperparameter.
... | 5732c937c8f46d74b9ba29fe848b1cbc1d88fa8c | 3,623,148 |
def help(term, arabic_column, english_column):
""" show all details of word"""
exclude_keys = [arabic_column, english_column]
details = {k: term[k] for k in set(list(term.keys())) - set(exclude_keys)}
return details | c1118fd1240802a4ba1f7976d21806eb7302276c | 3,623,149 |
def nodify(n):
"""
Modifies string to contain node#mod_
:param n: string
:return: string
"""
return 'node#mod_{}'.format(n) | b0d09ded891e369d463f44404501d82e5f266941 | 3,623,150 |
def calculate_rescue_time_pulse(very_distracting, distracting, neutral, productive, very_productive):
"""
Per RescueTime API
:param very_distracting: integer - number of seconds spent
:param distracting: integer - number of seconds spent
:param neutral: integer - number of seconds spent
:param ... | 28144b5e1c7820b12971a0f5a88d56971c798dc7 | 3,623,151 |
def load_linux_so():
""" Load the shared object for Linux platforms.
The shared object must be in the same folder as this python script.
"""
shared_name = get_project_root() / "build/libastyle.so"
shared = str(pl.Path(shared_name).absolute())
# file_ = {f for f in pl.Path().iterdir() if f.n... | 7fda7c73995bb99d86ac82f43e06c4d2c2f75a66 | 3,623,152 |
import torch
def load_embeddings_from_imgs(det_df, dataset_params, seq_info_dict, cnn_model, return_imgs = False, use_cuda=True):
"""
Computes embeddings for each detection in det_df with a CNN.
Args:
det_df: pd.DataFrame with detection coordinates
seq_info_dict: dict with sequence meta in... | 1d5dbffb904f98cb8e33247ab5619ba2ff74c0bf | 3,623,153 |
def serial_to_usb_widget(serial_into_USBhub_port_displayed):
"""Function used to create Jupyter widget.
It takes the parameter chosen from the widget and returns it such that it can be used as a variable.
Args:
serial_into_USBhub_port (str) : the port number of the USB Hub that the Serial Adaptor i... | 4bbf68ca2ab90da5a1f6ba3cc0a1b6f140b39484 | 3,623,155 |
def build_discriminator(input_shape=(256, 256, 3)):
"""Returns the discriminator network of the GAN.
Args:
input_shape (tuple, optional): shape of the input image. Defaults to (256, 256, 3).
Returns:
'Model' object: GAN discriminator.
"""
x0 = layers.Input(input_shape)
... | c0d541a6e613f78aabb81e0cb73027961acc7d48 | 3,623,156 |
import json
def user_list(_request):
"""
This will return a list of all users in the database
"""
# We'd really like to do .distinct, but sqlite+django does not support this;
# hence the hack with sorted(set(...))
users = sorted(
user_id[0]
for user_id in set(XBlockState.object... | d9456f0d7348382d4ed8e9ef17443f641cd8d39d | 3,623,157 |
from datetime import datetime
def price_dataframe(symbols='sp5002012',
start=datetime.datetime(2008, 1, 1),
end=datetime.datetime(2009, 12, 31),
price_type='actual_close',
cleaner=clean_dataframe,
):
"""Retrieve the prices of a list of equities as a DataFrame (columns = symbols)
Argumen... | d6c7cdb8d14d097a3f5eddb46c3a38dde58bb416 | 3,623,158 |
def split_nth(string, count):
"""
Splits string to equally-sized chunks
"""
return [string[i:i+count] for i in range(0, len(string), count)] | 38833ef711ce04f5563b343f477e7792035ec669 | 3,623,159 |
def market_EWindex(market: simuldata.Market, name: str="Market EW Index") -> pd.DataFrame:
"""
Sums all assets to make an index, corresponds to the Equally-Weighed (EW) index.
The formula for the weights here is:
w_i = c / N for all i
and we choose c = N so that \sum_i w_i = N.
Thus we... | f6713e7cc5a7dd70c0057de8e7bb252b386f6e70 | 3,623,160 |
import six
def force_unicode(s, encoding='utf-8', strings_only=False, errors='strict'):
"""
Similar to smart_text, except that lazy instances are resolved to
strings, rather than kept as lazy objects.
If strings_only is True, don't convert (some) non-string-like objects.
"""
# Handle the comm... | cf5fdb32b67bb280e6830a9039056793d896354d | 3,623,161 |
def column_hash_values(column0, *other_columns, initial_hash_values=None):
"""Hash all values in the given columns.
Returns a new NumericalColumn[int32]
"""
columns = [column0] + list(other_columns)
buf = Buffer(rmm.device_array(len(column0), dtype=np.int32))
result = NumericalColumn(data=buf, d... | dc8d94e87b16e51979d6b88b6203ae1d09592eff | 3,623,162 |
from typing import Optional
def get_service_from_request(
request, raise_exception: bool = True
) -> Optional[Service]:
"""Return the service for the request.
Unauthenticated calls will identify the service using ServiceAPIKey.
Authenticated calls will check the azp claim of the auth token to
see... | ffe03089902dc73ae6459d5f5f02b40ee049509d | 3,623,163 |
from typing import Any
def resnet50(
sensor: str,
bands: str,
pretrained: bool = False,
progress: bool = True,
**kwargs: Any,
) -> ResNet:
"""ResNet-50 model.
If you use this model in your research, please cite the following paper:
* https://arxiv.org/pdf/1512.03385.pdf
Args:
... | 30200f110e4a3ddab4b8f1ca48bf031531b6024a | 3,623,164 |
def divide_graph(graph, distance):
"""
divide graph with connected components by links whose distance is less than the second argument.
"""
group = [-1] * NUM_NODE
current_group_id = 0
division = []
for i in range(NUM_NODE):
current_group = set()
if(group[i] != -1):
... | 372e88a16a0b3cdbdc5ebebc05a37c0767e360b8 | 3,623,166 |
def deduplicate(elements):
"""Remove duplicate entries in a list of dataset annotations.
Parameters
----------
elements: list(vizier.datastore.annotation.base.DatasetAnnotation)
List of dataset annotations
Returns
-------
list(vizier.datastore.annotation.base.DatasetAnnotation)
... | 99de9667b46ab9da619d28748d3d74bbec54892a | 3,623,167 |
import select
def get_keywords():
""" The get_keywords function retrieves keywords from the database if they are set to active."""
return select(k for k in Keyword if k.active) | bee91f16ec635e41c9576410db8ed55f3f20607d | 3,623,168 |
def parse_spectrum_list2dict(spectrum_list):
"""
Parse the spectrum list [start, stop, num] to a list
"""
if spectrum_list[0].unit.physical_type != 'length' and \
spectrum_list[1].unit.physical_type != 'length':
raise ValueError('start and end of spectrum need to be a length... | 73db559fe9f617d5e0240f444d3fc30d8aed68eb | 3,623,169 |
import io
def RDKit_Mol_from_ProDy(prody_instance, removeHs=True):
"""
Creates an RDKit Mol object from a ProDy AtomGroup instance
:return:
"""
residue_io = io.StringIO()
prody.writePDBStream(residue_io, prody_instance)
return Chem.MolFromPDBBlock(residue_io.getvalue(), removeHs=removeHs) | dba8495f0e69847d678dfad14c62960ec3794701 | 3,623,171 |
def get_cut_rect_x(rect, axis):
"""
cuts one rect about an x axis
"""
rects = [rect]
llx, lly, urx, ury = rect
if llx < axis and urx > axis:
rects = [(llx, lly, axis, ury),
(axis, lly, urx, ury)]
return rects | 98ec23d892b974238d0a064c5e9de044598bb788 | 3,623,172 |
import inspect
def get_class_name(obj, fully_qualified=True, truncate_builtins=True):
"""Get class name for object.
If object is a type, returns name of the type. If object is a bound
method or a class method, returns its ``self`` object's class name.
If object is an instance of class, returns instan... | 41e0233593e76cc81c0afddbce6db644b26c349c | 3,623,173 |
def windShear(u, v, z, top, bottom, unit=None):
""" calculate the wind shear between discrete layers
<div class=jython>
shear = sqrt((u(top)-u(bottom))^2 + (v(top)-v(bottom))^2)/zdiff</pre>
</div>
"""
udiff = layerDiff(u, top, bottom, unit)
vdiff = layerDiff(v, top, bottom, unit)
zdiff = layerDi... | 7164b46c04d114562c0ba3194fabeb3d1a70594d | 3,623,174 |
import requests
def check_all_links(links):
""" Check that the provided links are valid.
Links are considered valid if a HEAD request to the server
returns a 200 status code.
"""
broken_links = []
for link in links:
head = requests.head(link)
if head.status_code != 200:
... | b6e784da72b4f81af3e393804ef3f776c2f3fc85 | 3,623,175 |
def process_currency(curr):
"""Gets a formatted list of cryptocurrency to show in home.html"""
assets = []
for c in curr:
assets.append(c['CGname'])
data = new_lookup(assets, "usd")
final_list = []
i = 1
for name, price in data.items():
final_list.append({"id": i, "name": n... | fdf66c99b3452cd2abafde6c9079589b39c669d4 | 3,623,176 |
async def validation_middleware(request: web.Request, handler) -> web.Response:
"""
Validation middleware for aiohttp web app
Usage:
.. code-block:: python
app.middlewares.append(validation_middleware)
"""
orig_handler = request.match_info.handler
if not hasattr(orig_handler, "_... | 5f529e005fc9de9e5c7ce43d8cab628e960cec18 | 3,623,177 |
import inspect
def register_ranged_hparams(name=None):
"""Register a RangedHParams set. name defaults to fn name snake-cased."""
def decorator(rhp_fn, registration_name=None):
"""Registers & returns hp_fn with registration_name or default name."""
rhp_name = registration_name or default_name(rhp_fn)
... | fb0ee544a31bbda610e599f44a6dce4a2cfc0621 | 3,623,178 |
import json
def get_monitoring_data():
"""
1. Get required arguments
2. Call the worker method
3. Render the response
"""
# 1. Get required arguments
args = Eg001Controller.get_args()
try:
# 2. Call the worker method to get your monitor data
results = Eg001Controll... | 63034190afdf72bf0fa4e03416a814aa9ac6c1d8 | 3,623,179 |
def calculate_histogram(magnitudes, angles, bin_count=9, is_signed=False):
"""Calculate the localized histogram of each cell.
:param magnitudes: The maginitude of each cell
:type: np.ndarray
:param angles: The angle of each cell
:type: ... | 82b7ddccd571031fedceee43f51292cf4e21cc19 | 3,623,180 |
def dot_product_mpnn_attention(q, k, v, adjacency_matrix, num_edge_types,
ignore_zero=True, name=None):
"""Dot product attention with edge vectors.
Args:
q: [batch, length, key_depth] tensor
k: [batch, num_edge_types, length, key_depth]
v: [batch, num_edge_types, length, ... | 5e545f714c72a4136352b531d3980fc56931a7a9 | 3,623,181 |
def selective_representer(dumper, data):
"""Process yml to correctly handle \n."""
return dumper.represent_scalar('tag:yaml.org,2002:str', data, style='|' if '\n' in data else None) | 4a748fb6b2eb997aee76239f875b5097648f4d88 | 3,623,182 |
def optimize_trajectory(target, start, parameters):
"""
牛顿迭代法，梯度下降法
:param target:
:param start:
:param parameters:
:return:
"""
for i in range(max_iter):
end_state = generate_last_state(start, parameters)
end_state_error = np.array(calc_diff(target, end_state)).reshape(... | 1b64c7eaf0f5601bf99ed2531677c86b6aab6a5c | 3,623,183 |
def get_session_monitor(target):
"""Px means the session is parallel run coordinator."""
return render_page() | 0bb186cbec3c72d1bbe9c40bfdd01bf68e57ab86 | 3,623,184 |
def _evaluate_embedding_cpu(r, d, r_neighbor, metric="dihedral", epsilon=1e-4):
"""
Evaluate the final embedding by calculating the stress and correlation
Args:
r (ndarray): n-dimensional dataset (rows: frame; columns: angle/intramolecular distance)
d (ndarray): the final projected embe... | 91e7f9c127190e2785775cf388c071a5dea179cf | 3,623,185 |
def encode_type2_user_id(user_id):
"""Append a type-2 error detection code to the user_id."""
return f"{user_id:04d}-{Type2Code.calculate(user_id):02d}" | 0d4b1e3ff919fcbd9bb26d0d5d25ae0e0a1fa5e5 | 3,623,186 |
def twitter(request, account_inactive_template='socialregistration/account_inactive.html',
extra_context=dict(), client_class=None):
"""
Actually setup/login an account relating to a twitter user after the oauth
process is finished successfully
"""
client = client_class(
request, setting... | f86d054fb976884d7b6b94efed8319970fafcafb | 3,623,188 |
def delete_activator_cd(activatorId, dbsession):
"""
Args:
activatorId ([int]): [The Activator id]
list_of_cd ([list]): [A list of CD ids]
1. Logically delete all active CD ids for this activator
"""
# Inactivates the active activator-cd for this activator (activatorId)
cd_l... | 78d06cd824d2f67d7bb3459b929d03b39d84dad2 | 3,623,189 |
def makeVariables_npv(image):
""" Make variables for NPV regression model """
year = ee.Image(image.date().difference(ee.Date('1970-01-01'), 'year'))
season = year.multiply(2 * np.pi)
return image.select().addBands(ee.Image(1)).addBands(
season.sin().rename(['sin'])).addBands(
season.cos().rename(['cos... | 20e8a988e033371296fcd52e86f6e0654657f9f7 | 3,623,190 |
import re
def mrg_labeled(tr):
"""return labeled constituency string."""
if isinstance(tr, nltk.Tree):
if tr.label() in WORD_TAGS:
return tr.leaves()[0] + ' '
else:
s = '(%s ' % (re.split(r'[-=]', tr.label())[0])
for subtr in tr:
s += mrg_labeled(subtr)
s += ') '
retu... | 95540cfcb3d5a2da7b14dcdcdcfb196c8923d3ff | 3,623,191 |
def compute_seen_words(inscription_list):
"""Computes the set of all words seen in phrases in the game"""
return {word
for inscription in inscription_list
for phrase in inscription['phrases']
for word in phrase.split()} | 496fc64ee37a6a6b0b3df0c3e9230d7b7ef46d0f | 3,623,193 |
def replace_previous(user, code, is_alt):
"""function replace_previous This function changes the previous lesson code
Args:
user: user model using tutor
code: code that user submitted in last lesson
is_alt: boolean for if alternate lesson
Returns:
code: ? string of code
... | 22c8ecb38611c9d184d588be8ca29bcd8430bd17 | 3,623,194 |
def page_rank_dense_lstsq(datafile, d, datasize, n=None):
""" Solve the page rank problem, given the data in 'datafile',
the dampening factor 'd', the size 'datasize' of the dataset,
and the number 'n' of nodes to include.
Have 'n' default to None.
Use the method involving least squares."""
data... | 2a392f769e3f1ccc0c4a8b999ccaec80ad8c98a1 | 3,623,196 |
def resume(request):
"""
Resume the container
"""
if request.method != "POST":
messages.error(request, "Invalid request method.")
return redirect('containers')
if 'id' not in request.POST or not request.POST.get('id').isdigit():
messages.error(request, "Invalid POST request."... | 6c1a880b2c927d51cdcf146bb9bae952287c7c9d | 3,623,197 |
def TextNodeEnd(builder):
"""This method is deprecated. Please switch to End."""
return End(builder) | 78dd2492d43531cad4e53d6f7fa0f79bd244cf70 | 3,623,198 |
def set_item_checked(service, context):
"""
Fixture for factory function to set whether an item is checked.
"""
def _set_item_checked(shopping_list, item, checked):
request = shopping_list_pb2.SetItemCheckedRequest(
shopping_list_id=shopping_list.id,
item_id=item.id,
... | 6d4619489ef5c8c1648a076f98e9f8ef3cd56d91 | 3,623,199 |
def as_singleton_instance(cls):
"""
This is where the magic happens. This defines a
class decorator that returns an *instance* of a class
with the name "_<original_name>__class" that has
the same member functions, etc as the cls argument.
The type of the returned value is not accessible to the
... | 3fc00dbfb24cd87401214806ddd93ff2ba15be50 | 3,623,200 |
def set_size(width, fraction=1, subplots=(1, 1)):
""" Set figure dimensions to avoid scaling in LaTeX.
Parameters
----------
width: float or string
Document width in points, or string of predined document type
fraction: float, optional
Fraction of the width which you wish th... | 2cbc82e17baceffcb81249d5dde99b6e10c4afa9 | 3,623,201 |
def create_keras_model():
"""
create model
"""
model = Sequential()
model.add(Conv1D(500,
input_shape=(1280, 1),
kernel_size=128,
strides=128,
activation='relu',
padding='same'))
model.add(De... | 043b3db24bb4b24932d1fad50acc72f9354a154d | 3,623,203 |
def ndgrid(*args,**kwargs):
"""
Same as calling meshgrid with indexing='ij' (see meshgrid for
documentation).
"""
kwargs['indexing'] = 'ij'
return meshgrid(*args,**kwargs) | 342530125f045d36a7c49baff72904ed90877452 | 3,623,204 |
def _wass_gen_loss_fn(gen_images, discriminator: tf.keras.Model,
generator: tf.keras.Model):
"""Calculate the Wasserstein (generator) loss."""
disc_gen_output = discriminator(
gen_images, training=TRAINING_KWARG_FOR_SECOND_MODEL)
gen_loss = tf.reduce_mean(-disc_gen_output)
# Now add... | caaacb970476a38364ffc9e1b82566c6cda1481a | 3,623,205 |
from typing import List
def _get_create_repo(request) -> List[str]:
"""
Retrieves the list of all GIT repositories to be created.
Args:
request: The pytest requests object from which to retrieve the marks.
Returns: The list of GIT repositories to be created.
"""
names = request.confi... | 4ac8cefefb75af3bb86fcc16f5c8b79953b136bf | 3,623,206 |
def read_in_posterior(date):
"""
read in samples from posterior from inference
"""
df = pd.read_hdf("results/soc_mob_posterior"+date+".h5", key='samples')
return df | f5754628f17de8629e3d197a73645e6fa541722b | 3,623,207 |
def wrap_dtype(func):
""" Check the dtype of the `X` array.
Convert dtype of X to np.float64 before to pass to cython function and
convert to specified dtype at the end.
"""
@wraps(func)
def check_dtype(X, *args, dtype=None, **kwargs):
X, dtype = _check_dtype(X, dtype)
if dtyp... | 2ace06e7f6447e71d3b7f586fde1cf853400d4d1 | 3,623,208 |
def dirdiff(HEADING,Nmin,loffset):
"""
Function to calculate the maximum difference of a [0, 360) direction during specified time averging intervals
:param HEADING: time series of a direction in degrees [0, 360)
:param Nmin: integer specifying the number of minutes to average
... | e552018dbdfc0dd83f9ac5e25116a9144133d9fc | 3,623,209 |
def update_outputs(region, resource_type, name, outputs):
""" update outputs with appropriate results """
element = {
"op": "remove",
"path": "/%s/%s" % (resource_type, name)
}
outputs[region].append(element)
return outputs | 97858e5d183af9974bd31be180dfe05c26048ab3 | 3,623,210 |
def generate_inputs_1d_spherical():
"""Return inputs that parser will expect for the 1D case with spherical averaging."""
inputs = {
'parent_folder':
orm.FolderData().store(),
'parameters':
orm.Dict(
dict={
'INPUTPP': {
'plot_num':... | 633fb78031eaeaf0067479d5aa600ed8fd462f90 | 3,623,211 |
def _check_electrification_scenarios_for_download(es):
"""Checks the electrification scenarios input to :py:func:`download_demand_data`
and :py:func:`download_flexibility_data`.
:param set/list es: The input electrification scenarios that will be checked. Can
be any of: *'Reference'*, *'Medium'*, *... | ccd1ec8f0b1349267ba1334f7744056bc43e32ec | 3,623,212 |
from typing import Sequence
from typing import List
def bubble_sort(nums: Sequence) -> List:
"""Sort a list in non-descending order using bubble sort.
Return a new list, leaving the original `nums` intact.
"""
# Bubble sort compares each element with the next element, and if the previous one
... | 0cc60f00fd7fb55098e34745e3bad76be7fcdf5f | 3,623,213 |
def image_to_byte_array(image: Image):
"""
Converts an image into a byte array
"""
imgByteArr = BytesIO()
image.save(imgByteArr, format=image.format if image.format else 'JPEG')
imgByteArr = imgByteArr.getvalue()
return imgByteArr | 82e6413978ee07d1d2cd434e144c1f1732133dab | 3,623,214 |
import logging
def crawling_tweet():
"""
Twitter APIを利用して対象ユーザーのツイートを収集する
収集したツイートはGoogle Cloud Text to Speech APIへ連携し、
音声読み上げデータとしてmp3に変換し、保存する
:return:
"""
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tw... | 008bf8a4c08cdce18c1fbea0dc053b8e5a974025 | 3,623,215 |
from typing import Optional
def is_subject_condition_dataframe(
data: SubjectConditionDataFrame, raise_exception: Optional[bool] = True
) -> Optional[bool]:
"""Check whether dataframe is a :obj:`~biopsykit.utils.datatype_helper.SubjectConditionDataFrame`.
Parameters
----------
data : :class:`~pan... | 993065496e7fff951986fd2141af7a222060433b | 3,623,216 |
def _update_earned_request(player_id, achievement_id, current_value, max_value):
"""
Create the DynamoDB update_item parameter request to update earned attribute
"""
now = ddb.timestamp()
return {
'Key': {
'player_id': player_id,
'achievement_id': achievement_id
... | f9c1cd62f537bcd6841ee33d59645fba976c82f9 | 3,623,217 |
def mosaic(*rasters):
"""
Mosaic rasters covering different areas together into one file.
Parts of the rasters may overlap each other, in which case we use the value
from the last listed raster (the "last" overlap rule).
"""
# align all rasters, ie resampling to the same dimensions as the first... | fd43edbafc4173129614dcc8ced6aa01390f0d3a | 3,623,218 |
def typing_loop(options, add, atom_type_dict):
"""
types atoms in ambiguous cases, options should be ordered correctly
"""
ty = None
for option in options:
try:
ty = atom_type_dict[add + option]
break
except KeyError:
continue
if ty !=... | 5198375c775cdbf1819998dca4d7c05287ba273d | 3,623,219 |
def enable_func_trace(*args):
"""
enable_func_trace(enable=True) -> bool
"""
return _ida_dbg.enable_func_trace(*args) | f2e9944f9651c56ab19fa1b444395d5ccf0df036 | 3,623,220 |
def get_exp_or_package_from_repo_name(repo_name):
"""Helper function to retrieve experiment or InternalPackage DB object based on repository name
Useful for tasks that do not have a session or other information"""
git_repo = GitRepository.objects.filter(name=repo_name)
if git_repo:
git_repo = gi... | 32403e7b223e55583959e0cd0be556e476be591a | 3,623,221 |
import re
def text_to_pronounceable_text(text,
symbols_for_base_idx=vowels_and_consonants,
captured_alphabet=alpha_numerics,
case_sensitive=False,
max_word_length=30,
... | d7f60bfc784975b166793edc1e8baee09036c5db | 3,623,222 |
def is_shuffle(s1, s2, s3):
"""
Runtime: O(n)
"""
if len(s3) != len(s1) + len(s2):
return False
i1 = i2 = i3 = 0
while i1 < len(s1) and i2 < len(s2):
c = s3[i3]
if s1[i1] == c:
i1 += 1
elif s2[i2] == c:
i2 += 1
else:
return False
i3 += 1
return True | 3b88d117efde1d6b8ea8e0266a9c3ac7ae039458 | 3,623,223 |
def header_is_sorted_by_coordinate(header):
"""Return True if bam header indicates that this file is sorted by coordinate.
"""
return 'HD' in header and 'SO' in header['HD'] and header['HD']['SO'].lower() == 'coordinate' | b656770806818abe742be32bc14c31a8a8e3e535 | 3,623,224 |
def delete(
name,
endpoint="incidents",
id=None,
api_url=None,
page_id=None,
api_key=None,
api_version=None,
):
"""
Remove an entry from an endpoint.
endpoint: incidents
Request a specific endpoint.
page_id
Page ID. Can also be specified in the config file.
... | 900126d08761793a4f97c1b4acbda224218103da | 3,623,225 |
import re
def name_conversion(caffe_layer_name):
""" Convert a caffe parameter name to a tensorflow parameter name as
defined in the above model """
# beginning & end mapping
NAME_MAP = {'bn_conv1/beta': 'conv0/bn/beta',
'bn_conv1/gamma': 'conv0/bn/gamma',
'bn_conv1... | c9025c01eeb8d319a4e76db167f65bac99adf396 | 3,623,226 |
def square(x, name=None):
"""Computes square of x element-wise.
I.e., \\(y = x * x = x^2\\).
Args:
x: An `Output` or `SparseTensor`. Must be one of the following types:
`half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`.
name: A name for the operation (optional).
Returns:... | 666e4b272b454561d2474229ed12ff94b8a629ef | 3,623,227 |
def manually_adjust_data(pnid, sc_entry):
"""Returns a modified version of sc_entry to fix some issues manually.
Args:
pnid: string, ProteinNet ID
sc_entry: dictionary containing "seq", "ang", "crd" data
Returns:
If sc_entry must be modified, then it is corrected and returned.
... | 90d801a5549b87e15e0c8e45f11de92ab2ad6cea | 3,623,228 |
def get_network_container_hostnames(name):
"""Returns a list of every container hostname in the specified network."""
for network in get_networks():
if network["Name"] == name:
return [get_container_hostname(container) for container in network["Containers"]] | f7b1f176f2c0e5a879930c2189f36f933075664e | 3,623,229 |
def spearmanr_no_pval_vec(X, Y):
"""Returns spearmans correlation, vectorized version
Parameters
----------
X : ndarray (n_samples, n_observations)
Y : ndarray (n_samples, 1)
Returns
-------
R : array (n_observations,)
spearmans correlation between each column of X and Y
""... | 9a4aeae514d80963ba1d12a574c3aebb8bdc30d4 | 3,623,230 |
import json
async def surprise_communities(request):
"""
---
description: This end-point allows to compute surprise_communities Community Discovery algorithm to a network dataset.
tags:
- surprise_communities
produces:
- application/json
responses:
... | 785c2b6e14516b0f5ddd140310fe75fb4759900f | 3,623,231 |
def set_case(words, method="lower", testing=False):
"""
Perform capitalization on some or all of the strings in `words`.
Default method is "lower".
Args:
words (list): word list generated by `choose_words()` or
`find_acrostic()`.
method (str): one of {"alter... | 92465688c8a7e2e85d2631b8acd8496fab5d0c33 | 3,623,232 |
def button(channel, red, blue):
"""Returns the button for a Combo PWM Mode command."""
return (pf_rc.CHANNEL[channel], PWM_STEP[red], PWM_STEP[blue]) | 821ce8c5684bb7634281b95960607537de15b4a4 | 3,623,233 |
def mini_xception(input_shape, num_classes, regularization = l2(0.01)):
"""
This function architects the mini_xception model network. This is the best
performing model in the facial emotion analysis
input_shape: input shape of the image
num_classes: number of classes in the output
return: Ret... | a7003277cc25e4029cfcf0dea580833f68916af5 | 3,623,234 |
def calc_node_size(self):
"""
calculate minimum node size.
"""
title_width = self._text_item.boundingRect().width()
port_names_width = 0.0
port_height = 0.0
if self._input_items:
input_widths = []
for port, text in self._input_items.items():
input_width = port.bo... | 9d6b8a37ef13a9698d6523baeacc2da0686c9c4d | 3,623,235 |
def page_osr_vieworder():
"""Return everything."""
query = f'SELECT DISTINCT orderdate FROM orderlog'
g.cur.execute(query)
rows = g.cur.fetchall()
return render_template('vieworder.html', dates=rows) | a28ce95ae9930d1da19cd1af817b6376d3dc4f83 | 3,623,236 |
def eval_metric_fns():
"""Returns a dict from name to metric functions.
This can be customized as follows. Care must be taken when handling padded
lists. (only takes labels >= 0.
def _auc(labels, predictions, features):
is_label_valid = tf_reshape(tf.greater_equal(labels, 0.), [-1, 1])
clean_l... | cfa13913bd7132fc558b0e3b4ab71fd8dc9328c7 | 3,623,237 |
from typing import List
from typing import Dict
from typing import Optional
from typing import Union
def combine_score_weights(
weights: List[Dict[str, float]],
overrides: Dict[str, Optional[Union[float, int]]] = SimpleFrozenDict(),
) -> Dict[str, float]:
"""Combine and normalize score weights defined by ... | f75b444a013087350412b1bb65780b42496632af | 3,623,238 |
def calc_ideal_vel(traj_ref, dt):
"""
Parameters
------------
traj_ref : numpy.ndarray, shape (2, N)
these points should follow subseqently
dt : float
sampling time of system
"""
# end point and start point
diff = traj_ref[:, -1] - traj_ref[:, 0]
distance = np.sqrt(n... | 45c4ae252c9689d57733ffc4fb0b976999e2b583 | 3,623,239 |
def make_rgba(grid2D, levels, colorlist, mask=None,
mercator=False):
"""
Make an rgba (red, green, blue, alpha) grid out of raw data values and
provide extent and limits needed to save as an image file
Args:
grid2D: Mapio Grid2D object of result to mape
levels (list): list... | f337ac86909d0941d513648f309602e76dd56374 | 3,623,241 |
import binascii
def AES_encryption(enc,server=False):
"""
Performs AES encryption using the globablly declared AES key.
"""
enc = str(enc)
enc = enc + ((16 - len(enc) % 16) * ' ')
iv = enc[:16]
aes_cipher = None
if server:
aes_cipher = AES.new(login_server_key, AES.MODE_CBC, iv... | 00f89db237a746a6a72cc7f168d14d616aded659 | 3,623,242 |
def named_cache_page(cache_timeout):
"""
Decorator for views that tries getting the page from the cache and
populates the cache if the page isn't in the cache yet.
The cache is keyed by view name and arguments.
"""
def wrapper(func):
def foo(*args, **kwargs):
key = func.__na... | 1c946370640bd76c3a4a3d3a6a3c0fe5a76d0215 | 3,623,243 |
def get_product(location, product_id, quantity):
""" Used by the movement route to get a product from a location. """
product_array = []
db = get_db()
b_id = session.get("user_id")
if location == "product_factory":
# Get product from product table, deduct the quantity
ogquantity = d... | cda91efeb3bbc280a609bc560e4a9b9867d6d1ed | 3,623,244 |
def calc_psi_r(qr, r1, r2, r3, r4):
"""
radial geodesic angle
Parameters:
qr (float)
r1 (float): radial root
r2 (float): radial root
r3 (float): radial root
r4 (float): radial root
Returns:
psi_r (float)
"""
kr = ((r1 - r2) * (r3 - r4)) / ((r1 - ... | 2d9744361739db19e1c347b902a5844f1a23c655 | 3,623,245 |
def mse(tensor_true, tensor_pred):
""" Mean squared error
Parameters
----------
tensor_true : Tensor
tensor_pred : {Tensor, TensorCPD, TensorTKD, TensorTT}
Returns
-------
float
"""
tensor_res = residual_tensor(tensor_true, tensor_pred)
return np.mean(tensor_res.data ** 2) | afc7bce6515bfc656da3fdb15f5605184bcc10a7 | 3,623,246 |
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