content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from typing import Union
from typing import List
from typing import Dict
from typing import Set
import tqdm
def scaffold_to_smiles(mols: Union[List[str], List[Chem.Mol]],
use_indices: bool = False) -> Dict[str, Union[Set[str], Set[int]]]:
""" Computes the scaffold for each SMILES and return... | 2a45731a5574bb37e81042fa19ac7c2f015c21ef | 14,421 |
import crypt
def encontrar_passwords():
"""
Probar todas las combinaciones de 6 letras, hasheando cada una para ver si
coinciden con los hashes guardados en los /etc/shadow
Para el tema de equipos, basicamente fui probando con copiar y pegar
contenido en texto de distintas paginas de wikipedia en ... | 5762fed1f5e493c2399d40dbbc1e19ad24c6718e | 14,422 |
def queue_merlin_study(study, adapter):
"""
Launch a chain of tasks based off of a MerlinStudy.
"""
samples = study.samples
sample_labels = study.sample_labels
egraph = study.dag
LOG.info("Calculating task groupings from DAG.")
groups_of_chains = egraph.group_tasks("_source")
# magi... | 448365e799001d09281707cab69c71c3be05408e | 14,423 |
import math
def sphere_mass(density,radius):
"""Usage: Find the mass of a sphere using density and radius"""
return density*((4/3)*(math.pi)*radius**3) | 8c1a2dc949980ca96a4f56f3918bacd19568965e | 14,424 |
def generate_stats_table(buildings_clust_df):
"""
Generate statistical analysis table of building types in the area
Args:
buildings_clust_df: building footprints dataframe after performed building blocks assignment (HDBSCAN)
Return:
stat_table: statistical analysis results ... | 732f035e591dc9f0b03673584f3a6e21dad03cad | 14,425 |
def make_multisat(nucsat_tuples):
"""Creates a rst.sty Latex string representation of a multi-satellite RST subtree
(i.e. merge a set of nucleus-satellite relations that share the same nucleus
into one subtree).
"""
nucsat_tuples = [tup for tup in nucsat_tuples] # unpack the iterable, so we can che... | 16c1808267087beea6cea21811cd3c1f7d70932e | 14,426 |
import io
def plot_to_image(figure):
"""Converts the matplotlib figure to a PNG image."""
# The function is adapted from
# github.com/tensorflow/tensorboard/blob/master/docs/image_summaries.ipynb
# Save the plot to a PNG in memory.
buf = io.BytesIO()
plt.savefig(buf, format="png")
# Closing the figure ... | 24a63f7b27d47421baf2c7913bf989903e4d9545 | 14,427 |
async def getDiscordTwitchAlerts(cls:"PhaazebotDiscord", guild_id:str, alert_id:int=None, limit:int=0, offset:int=0) -> list:
"""
Get server discord alerts, if alert_id = None, get all
else only get one associated with the alert_id
Returns a list of DiscordTwitchAlert().
"""
sql:str = """
SELECT
`discord... | 00c1bad85f4f7891d36e5fab5c651f10c79abf02 | 14,428 |
def is_visible_dir(file_info):
"""Checks to see if the file is a visible directory.
@param file_info: The file to check
@type file_info: a gnomevfs.FileInfo
"""
return is_dir(file_info) and not is_hidden(file_info) | 776361d4cbe16a5b3c45dc3073a37192e31e87a9 | 14,429 |
def read_file(item):
"""Read file in key path into key image
"""
item['image'] = tf.read_file(item['path'])
return item | 06b87851717bd486b13f964ad5b45cbdc7a97142 | 14,431 |
def make_joint(withdraw, old_password, new_password):
"""Return a password-protected withdraw function that has joint access to
the balance of withdraw.
>>> w = make_withdraw(100, 'hax0r')
>>> w(25, 'hax0r')
75
>>> make_joint(w, 'my', 'secret')
'Incorrect password'
>>> j = make_joint(w,... | f40073429aea946486263a7d6e0fc8b24cd60a84 | 14,432 |
def should_parse(config, file):
"""Check if file extension is in list of supported file types (can be configured from cli)"""
return file.suffix and file.suffix.lower() in config.filetypes | 1c2258d405ef715574b557d99cdf87e461627ffd | 14,433 |
def _get_pipeline_per_subband(subband_name: str):
"""
Constructs a pipeline to extract the specified subband related features.
Output:
sklearn.pipeline.Pipeline object containing all steps to calculate time-domain feature on the specified subband.
"""
freq_range = FREQ_BANDS_RANGE[subband_n... | 2b1d8bd2543ae07b861df6f979297a82e3f5e827 | 14,434 |
def get_credentials_interactively() -> Credentials:
""" Gets credentials for the bl interactively
"""
return ("placeholder-user", "placeholder-pass") | b5e4d55015155589632b958252a3c078b5920e59 | 14,435 |
def reynolds(find="Re", printEqs=True, **kwargs):
"""
Reynolds Number = Inertia / Viscosity
"""
eq = list()
eq.append("Eq(Re, rho * U * L / mu)")
return solveEqs(eq, find=find, printEq=printEqs, **kwargs) | df5ad0c0279894e8f671942ceddb64e08e35fa0d | 14,436 |
def data_app():
""" Data Processer and Visualizer """
st.title("Data Cake")
st.subheader("A to Z Data Analysis")
file = ['./dataset/Ac1',[0,1]]
def file_selector():
filename = st.file_uploader("Upload Excel File", type=['xls','xlsx'])
if filename is not None:
sheetname... | b6286064757d276a5319ef0b3cffe1515c4a7fb1 | 14,437 |
def derivative(x, y, order=1):
"""Returns the derivative of y-coordinates as a function of x-coodinates.
Args:
x (list or array): 1D array x-coordinates.
y (list or array): 1D array y-coordinates.
order (number, optional): derivative order.
Returns:
... | 23a1213721e553e5b72a0bd92877675b499f9848 | 14,438 |
from typing import Dict
def get_ff_parameters(wc_params, molecule=None, components=None):
"""Get the parameters for ff_builder."""
ff_params = {
'ff_framework': wc_params['ff_framework'],
'ff_molecules': {},
'shifted': wc_params['ff_shifted'],
'tail_corrections': wc_params['ff_... | d87008dba0b9d835f71366eb64486b1d18fe2381 | 14,439 |
def healpix_header_odict(nside,nest=False,ordering='RING',coord=None, partial=True):
"""Mimic the healpy header keywords."""
hdr = odict([])
hdr['PIXTYPE']=odict([('name','PIXTYPE'),
('value','HEALPIX'),
('comment','HEALPIX pixelisation')])
ordering =... | 1202d7564b94a3c2288a513f42e4b781a583e41c | 14,440 |
def hello():
"""Test endpoint"""
return {'hello': 'world'} | 91ad620815a6371a4723e21bc79aad8c1d49e73e | 14,441 |
def permute_channels(n_channels, keep_nbr_order=True):
"""Permute the order of neighbor channels
Args:
n_channels: the total number of channels
keep_nbr_order: whether to keep the relative order of neighbors
if true, only do random rotation and flip
if false, random perm... | 5491f181d32a5ff77ef1d9f6ac3327e6b0a746e0 | 14,443 |
def from_file(file,typcls):
"""Parse an instance of the given typeclass from the given file."""
s = Stream(file)
return s.read_value(typcls._ep_typedesc) | 90507278f33fe30a73c31f94ab046c07962250cc | 14,444 |
def read_test_ids():
"""
Read sample submission file, list and return all test image ids.
"""
df_test = pd.read_csv(SAMPLE_SUBMISSION_PATH)
ids_test = df_test['img'].map(lambda s: s.split('.')[0])
return ids_test | cc4d53d28631fe0e22cabe30704a1844ff3e3a5b | 14,445 |
def chuseok(year=None):
"""
:parm year: int
:return: Thanksgiving Day of Korea
"""
year = year if year else _year
return LunarDate(year, 8, 15).toSolarDate() | 28a3170153862bda2ae52176d4931ee10050c3e1 | 14,446 |
def DELETE(request):
"""Delete a user's authorization level over a simulation."""
# Make sure required parameters are there
try:
request.check_required_parameters(
path={
'simulationId': 'int',
'userId': 'int'
}
)
except exceptio... | 7ac7c6277126a827790e786cbfdf9f84ccaace7b | 14,447 |
def process_query(data):
"""
Concat query, question, and narrative then 'preprocess'
:data: a dataframe with queries in rows; query, question, and narrative in columns
:return: 2d list of tokens (rows: queries, columns: tokens)
"""
lst_index = []
lst_words = []
for index, row in da... | 8a8067f1766abdc08aa7b8995508d6cdc9057bd2 | 14,448 |
def nb_view_patches(Yr, A, C, S, b, f, d1, d2, YrA=None, image_neurons=None, thr=0.99, denoised_color=None, cmap='jet'):
"""
Interactive plotting utility for ipython notebook
Args:
Yr: np.ndarray
movie
A,C,b,f: np.ndarrays
outputs of matrix factorization algorithm
... | 84db2e40734b21ebb6be5eef8eeb89bbe2838542 | 14,450 |
def menu():
"""Manda el Menú \n
Opciones:
1: Añadir a un donante
2: Añadir a un donatario
3: Revisar la lista de donantes
4: Revisar la lista de donatarios
5: Realizar una transfusion
6: Estadisticas
7: Salir
Returns:
opc(num):Opcion del menu "... | 805d1ef48fbe03f8185e3c7be71ce3d9aa6104df | 14,451 |
import shutil
def get_engine(hass, config):
"""Set up Pico speech component."""
if shutil.which("pico2wave") is None:
_LOGGER.error("'pico2wave' was not found")
return False
return PicoProvider(config[CONF_LANG]) | d03a19dcff4bc8556a84b434d14468a45ffc7e6c | 14,452 |
from typing import Tuple
from typing import List
def load_cp() -> Tuple[List[str], List[List[float]]]:
"""
Loads cloud point data; target values given in Celsius
Returns:
Tuple[List[str], List[List[float]]]: (smiles strings, target values);
target values have shape (n_samples, 1)
... | 84b11da1b3cd1a9ecaf5e1419d69b877c160e2aa | 14,453 |
def look_up(f, *args, **kwargs):
"""
:param f:
:type f:
:param args:
:type args:
:param kwargs:
:type kwargs:
:return:
:rtype:"""
ag_hash = hash(args) + make_hash(kwargs)
if f in global_table:
if ag_hash in global_table[f]:
return global_table[f][ag_hash]... | ebc9015066959f66cd98db226178cdf087fc897b | 14,454 |
def getenv(key, default=None):
"""Get an environment variable, return None if it doesn't exist.
The optional second argument can specify an alternate default.
"""
return environ.get(key, default) | 0e355c73dbbdc971e4442123dc5945dc04fac8fc | 14,455 |
def read_tag(request, tid, *args, **kwargs):
"""read_tag(tid) returns ..."""
s = api.read_tag(request, tid, *args, **kwargs)
return render_to_response('read/tag.html', s) | 7582e752563f35eb8d025625eaac87d8a9f45f32 | 14,456 |
def ber_img(original_img_bin, decoded_img_bin):
"""Compute Bit-Error-Rate (BER) by comparing 2 binary images."""
if not original_img_bin.shape == decoded_img_bin.shape:
raise ValueError('Original and decoded images\' shapes don\'t match !')
height, width, k = original_img_bin.shape
errors_bits... | f5768aa5435a76bcd82b331d76dadf554749e82d | 14,457 |
def get_fractal_patterns_WtoE_NtoS(fractal_portrait, width, height):
""" get all fractal patterns from fractal portrait, from West to East, from North to South """
fractal_patterns = []
for x in range(width):
# single fractal pattern
f_p = get_fractal_patterns_zero_amounts()
for y in... | ad5e2025515231ae8efb256b5dc466d66fedb467 | 14,458 |
import time
from datetime import datetime
import requests
import io
def rating(date=None):
"""P2peye comprehensive rating and display results.
from https://www.p2peye.com
Args:
date: if None, download latest data, if like '201812', that download month data.
Returns:
DataFrame... | d76205c933c07764938b38fbfcdcbbe84b584471 | 14,459 |
def crop_image(src, box, expand=0):
"""Read sensor data and crop a bounding box
Args:
src: a rasterio opened path
box: geopandas geometry polygon object
expand: add padding in percent to the edge of the crop
Returns:
masked_image: a crop of sensor data at specified bounds
... | 84948cf3c81fe650d15acd834f89c532e9658466 | 14,460 |
def add_msgpack_support(cls, ext, add_cls_methods=True):
"""Adds serialization support,
Enables packing and unpacking with msgpack with 'pack.packb' and
'pack.unpackb' methods.
If add_method then enables equality, reading and writing for the classs.
Specificly, adds methods:
bytes <- obj... | fa8a6fcce7103466f923b84eeb6f5bdae8383b79 | 14,461 |
def UnN(X, Z, N, sampling_type):
"""Computes block-wise complete U-statistic."""
return UN(X, Z, N, Un, sampling_type=sampling_type) | 0e2fb8c62cbcca99017bc7d0ff2c13dbecad1ab3 | 14,463 |
def view_log_view(request, model_name, object_id):
"""view log view
Arguments:
request {object} -- wsgi request object
content_type {str} -- content type
object_id {int} -- admin_log id
Returns:
retun -- html view
"""
if model_name not in register_form:
re... | 55ebd2d5226e06b1f5833595b0efad3de81140d7 | 14,464 |
from typing import Tuple
from typing import Dict
def parse_markdown(source: str) -> Tuple[str, Dict]:
"""Parse a Markdown document using our custom parser.
Args:
source (str): the Markdown source text
Returns:
tuple(str, dict):
1. the converted output as a string
... | 2bf5a8d43f3763d6b1356dc0496ab4ed1896fe99 | 14,465 |
def flatten_list(nested_list):
# Essentially we want to loop through each element in the list
# and check to see if it is of type integer or list
"""
Flatten a arbitrarily nested list
Args:
nested_list: a nested list with item to be either integer or list
example:
[2,[[... | d79b350167cd1fdf35582e9b149bfb364741d566 | 14,466 |
import inspect
def detect_runner():
""" Guess which test runner we're using by traversing the stack and looking
for the first matching module. This *should* be reasonably safe, as
it's done during test discovery where the test runner should be the
stack frame immediately outside. """
i... | 881758d42e5047fe58106a99377dcc7191c0010c | 14,467 |
def retinanet(
mode,
offsets_mean=None,
offsets_std=None,
architecture='resnet50',
train_bn=False,
channels_fmap=256,
num_anchors_per_pixel=9,
num_object_classes=1,
pi=0.01,
alpha=0.25,
gamma=2.0,
confidence_threshold=0.... | a3cdb088345740583c7ea08049e5f03f8d496cad | 14,468 |
from typing import Union
from typing import Tuple
from typing import List
from typing import Literal
def default_chap_exec(gallery_or_id: Union[Gallery, int], chap: Chapter, only_values=False) \
-> Union[Tuple[str, dict], Tuple[int, Union[str, List[str]], int, bytes, int, Literal[0, 1]]]:
"""Pass a Galler... | 8bd8cbfc47ce3463f2ea6da313cc871d8b6dcdf5 | 14,469 |
from typing import List
from typing import Dict
from typing import Literal
from typing import Any
def get_matching_based_variables(match_definitions:List[Dict[Literal['name', 'matching'],Any]],
global_dict=None,
local_dict=None,
... | 6722bb4f258ef69c4aab74970f8f924ca938bbf5 | 14,471 |
def _AStar_graph(problem: BridgeProblem) -> (list, list):
"""Used for graphing, returns solution as well as all nodes in a list"""
all_nodes = [problem.initial_node]
pq = [(problem.initial_node.path_cost + problem.h(problem.initial_node.state), problem.initial_node)]
closed = set()
while True:
... | a1616f7d499f12a229843007d7bc4939cbd02a7a | 14,472 |
def plot_setup(name, figsize=None, fontsize=9, font='paper', dpi=None):
""" Setup a PDF page for plot.
name: PDF file name. If not ending with .pdf, will automatically append.
figsize: dimension of the plot in inches, should be an array of length two.
fontsize: fontsize for legends and labels.
font... | 4f9595757df57ee451dddc82815a91b727feb1f1 | 14,473 |
def author_endyear(pub2author_df = None, colgroupby = 'AuthorId', datecol = 'Year', show_progress=False):
"""
Calculate the year of last publication for each author.
Parameters
----------
pub2author_df : DataFrame, default None, Optional
A DataFrame with the author2publication information.
... | 8a3ebf5e1870a8aa79ed2cba18fbb18fa634e604 | 14,474 |
def to_gif(images, fps):
"""Converts image sequence (4D numpy array) to gif."""
imageio.mimsave('./animation.gif', images, fps=fps)
return embed.embed_file('./animation.gif') | b329da4710a5ad2da57ed2cf6b774ac4b6b8c7dd | 14,475 |
import logging
def get_half_max_down(signal, peak):
"""See `get_half_max_up` for explanation.
This is a minor modification of the above function.
"""
if peak['peak'] == 0:
return np.nan
fflag = False
half_max = signal[peak['peak']] / 2
falling_signal = signal[peak['peak']:(peak['r... | 0b9b20b66a82d8a60aa650bc1bacd24f67f217f1 | 14,476 |
import copy
def ternary(c):
"""
Encodes the circuit with ternary values
Parameters
----------
c : Circuit
Circuit to encode.
Returns
-------
Circuit
Encoded circuit.
"""
if c.blackboxes:
raise ValueError(f"{c.name} contains a blackbox")
t ... | 6fd813b957da408c23cc8a37038b8f3b660fdc73 | 14,478 |
from typing import List
from typing import Dict
def eval_lane_per_frame(
gt_file: str, pred_file: str, bound_ths: List[float]
) -> Dict[str, np.ndarray]:
"""Compute mean,recall and decay from per-frame evaluation."""
task2arr: Dict[str, np.ndarray] = dict() # str -> 2d array
gt_byte = np.asarray(Imag... | 571cd737151576869170e33d181f89d22bc0657b | 14,479 |
import torch
def membrane(field, voxel_size=1, bound='dct2', dim=None, weights=None):
"""Precision matrix for the Membrane energy
Note
----
.. This is exactly equivalent to SPM's membrane energy
Parameters
----------
field : (..., *spatial) tensor
voxel_size : float or sequence[float... | 5e238ca2253fc7105b1bbfba58947ac442c05699 | 14,480 |
from typing import Tuple
import struct
def get_uint64(dgram: bytes, start_index: int) -> Tuple[int, int]:
"""Get a 64-bit big-endian unsigned integer from the datagram.
Args:
dgram: A datagram packet.
start_index: An index where the integer starts in the datagram.
Returns:
A tuple cont... | e5ed2470656e3c0d1a8efe02bd638ac05245f187 | 14,481 |
import torch
from typing import Optional
from typing import List
def fftshift(x: torch.Tensor, dim: Optional[List[int]] = None) -> torch.Tensor:
"""
Similar to np.fft.fftshift but applies to PyTorch Tensors
Args:
x: A PyTorch tensor.
dim: Which dimension to fftshift.
Returns:
... | a1ff7a81df83df63dcbcf56cf89d9b0e54c16ba0 | 14,482 |
def flatten(x):
"""Flattens nested list"""
if isinstance(x, list):
return [a for i in x for a in flatten(i)]
else:
return [x] | 7d348f8287dfccfbb77a52a84a5642c265381eb1 | 14,483 |
import copy
def get_capture_points_gazebo(bag, odom_topic='/gazebo/model_states', sync_topic='/mavros/imu/data_raw', camera_freq=20, sync_topic_freq=100, method='every'):
"""
method(string): method for sampling capturing points.
'every': Sample IMU for every n msgs, and then capture odometry msg whic... | 75d351c0ecd6ad8dad6e7cfcd2ecd04d0826405b | 14,484 |
import fileinput
def parse_input():
"""Parse input and return array of calendar
A user can either pass the calendar via the stdin or via one or several
icalendar files. This method will parse the input and return an array
of valid icalendar
"""
input_data = ''
calendars = []
for line... | a60a760968f139da0b7753ae5717d78b640cb232 | 14,485 |
def identity(obj):
"""Returns the ``obj`` parameter itself
:param obj: The parameter to be returned
:return: ``obj`` itself
>>> identity(5)
5
>>> foo = 2
>>> identity(foo) is foo
True
"""
return obj | a3271a831d2e91fe6eebed7e80c18e7c81996da6 | 14,486 |
def percent_clipper(x, percentiles):
"""
Takes data as np.ndarray and percentiles as array-like
Returns clipped ndarray
"""
LOWERBOUND, UPPERBOUND = np.percentile(x, [percentiles[0], percentiles[1])
return np.clip(x, LOWERBOUND, UPPERBOUND) | 3d114a956bfd0b6b8349c39f5c42f4487a812ee7 | 14,487 |
def check_prob_vector(p):
"""
Check if a vector is a probability vector.
Args:
p, array/list.
"""
assert np.all(p >= 0), p
assert np.isclose(np.sum(p), 1), p
return True | f9a6ea74fe9e5ff8a7244e7cc8aee2cbf5ae512e | 14,488 |
def relabel_subgraph():
""" This function adapts an existing sampler by relabelling the vertices in the edge list
to have dense index.
Returns
-------
sample: a function, that when invoked, produces a sample for the input function.
"""
def relabel(edge_list, positive_vertices):
sha... | e9b8269640663b830c894c4aa4f8a8cce2b49af7 | 14,489 |
def init_binary(mocker):
"""Initialize a dummy BinaryDigitalAssetFile for testing."""
mocker.patch.multiple(
houdini_package_runner.items.digital_asset.BinaryDigitalAssetFile,
__init__=lambda x, y, z: None,
)
def _create():
return houdini_package_runner.items.digital_asset.Binar... | 34a3ee5fb09f413bf07b36f1b73189472c188f3d | 14,491 |
def with_setup_(setup=None, teardown=None):
"""Decorator like `with_setup` of nosetest but which can be applied to any
function"""
def decorated(function):
def app(*args, **kwargs):
if setup:
setup()
try:
function(*args, **kwargs)
f... | f9e8eddfd01ee99e458857de403c49b91dafa92c | 14,492 |
import click
def post_options():
"""Standard arguments and options for posting timeseries readings.
"""
options = [
click.argument('port'),
click.argument('value', type=JSONParamType()),
click.option('--timestamp', metavar='DATE',
help='the time of the reading'... | 7b7c386bfcbf36f1365392a6ba2562fa0ed520ce | 14,493 |
def authenticated(f):
"""Decorator for authenticating with the Hub"""
@wraps(f)
def decorated(*args, **kwargs):
token = request.cookies.get(auth.cookie_name)
if token:
user = auth.user_for_token(token)
else:
user = None
if user:
return f(u... | 1149f14ad540521b71efa3a3240c13719ccf8a17 | 14,494 |
def json_complex_hook(dct):
"""
Return an encoded complex number to it's python representation.
:param dct: (dict) json encoded complex number (__complex__)
:return: python complex number
"""
if isinstance(dct, dict):
if '__complex__' in dct:
parts = dct['__complex__']
assert len(parts) == 2
return pa... | a3c8cb13485279ab3b222eb63efdfdf6421c17a6 | 14,495 |
def reg_logLiklihood(x, weights, y, C):
"""Regularizd log-liklihood function (cost function to minimized in logistic
regression classification with L2 regularization)
Parameters
-----------
x : {array-like}, shape = [n_samples, n_features + 1]
feature vectors. Note, first column of x mu... | 4a13bac09a6989463014784c72c72729ec40e718 | 14,496 |
import itertools
def estimate_gridsearch_size(model, params):
""" Compute the total number of parameter combinations in a grid search
Parameters
----------
model: str
name of the model to train. The function currently supports feedforward neural networks (model = 'FNN'),
long-short ... | 8105a457b3ec30c3cdc6c42bb71afd229770b376 | 14,499 |
import pytz
from datetime import datetime
def str2posix(timelist):
""" This will take a list of strings with the date along with a start and
end time and make a list with the posix times.
Inputs
timelist - A list of strings with the data followed by two times.
The date for ... | 476fc634b967419818ef41d9ff4b21f9e4f76ff1 | 14,502 |
def keys_verif(verif: bool = True):
"""
Used to verify existence of private or/and public keys of ElGamal.
"""
print("\nChecking the presence of keys in the system....")
if isFileHere("public_key.kpk", config.DIRECTORY_PROCESSING):
# from cipher.asymmetric import elGamal as elG
p... | 824b8c31ad9cc0fb1b2ef7eef585e47c2e338a8b | 14,503 |
def r2(ground_truth, simulation, join='inner', fill_value=0):
"""
R-squared value between ground truth and simulation
Inputs:
ground_truth - ground truth measurement (data frame) with measurement in the "value" column
simulation - simulation measurement (data frame) with measurement in the "value" ... | 75d78e575bef0a59620cbdbf1992396a8edd0929 | 14,504 |
def depth_analysis_transform_1(rgb_tensor, depth_tensor, num_filters):
"""Builds the analysis transform."""
with tf.variable_scope("analysis"):
# --------------------------------------- rgb branch
with tf.variable_scope("layer_0"):
layer = tfc.SignalConv2D(
num_filters, (9, 9), corr=True, s... | 27637e35619f61e5da2b965392a39b38cdfb6a29 | 14,506 |
def hub_quantile_prediction_dict_validator(target_group_dict, prediction_dict):
"""
Does hub prediction_dict validation as documented in `json_io_dict_from_quantile_csv_file()`
"""
error_messages = [] # return value. filled next
valid_quantiles = target_group_dict['quantiles']
prediction_quanti... | ec13824557ef9533d7c4a777daadd07414752767 | 14,508 |
def allclose_periodical(x, y, a, b, atol=1e-10):
"""
Checks np.allclose(x,y), but assumes both x and y are periodical with respect to interval (a,b)
"""
assert(len(x) == len(y))
period = b-a
x_p = np.remainder(x-a,period) # now in 0, b-a
y_p = np.remainder(y-a,period)
return all(np.isclo... | bd1c58a362a9c3926bffbcb0a27e355bfc982955 | 14,509 |
import operator
def get_categories_to_rows_ratio(df):
"""
Gets ratio of unique categories to number of rows
in the categorical variable; do this for each categorical
variable
:param df: pd.DataFrame
:return: array of tuples
"""
cat_columns = get_categorical_variable_names(df)
rati... | 2734b898b6c6538b65d54709be617a6dd393c3da | 14,510 |
def _width_left_set(size: int, lsize: int, value: list, fmt: str, meta: dict) -> dict:
"""Width setting of paragraph with left repositioning."""
return Plain([RawInline(fmt, '<p style="text-align:left !important;'
'text-indent:0 !important;'
'position:rela... | 6042b0d255fe804d7423b5e49dd700bd7f0b9bdf | 14,511 |
def GetMappingKeyName(run, user):
"""Returns a str used to uniquely identify a mapping."""
return 'RunTesterMap_%s_%s' % (run.key().name(), str(user.user_id())) | b4eb80ca5f084ea956f6a458f92de1b85e722cda | 14,512 |
def get_invitee_from_table(invite_code: str, table):
"""
Get a dictionary of the stored information for this invite code.
Args:
invite_code: The invitation code to search for
table: A DynamoDB table for querying
Returns:
A dictionary of information stored under the invite code
... | 1377e20a58174f69d8984e36aab3426c0eb392bd | 14,513 |
import math
def d_beta_dr(radius, beta, mass_r, epsilon, pressure, h_r):
""" d_beta_dr """
return 2. * (1 - 2 * (mass_r/radius)) ** (-1.) * h_r * \
( -2. * math.pi * (5*epsilon + 9*pressure + f(epsilon, pressure)) + (3/radius**2.) + 2*(1 - 2 * mass_r / radius)**(-1) * \
((mass_r/radius) + 4 * ... | 0880439516b70e07c01be3164a3c030bb9deeaca | 14,514 |
import json
def score(capstone, student_api):
"""
Calculates the score of the students' API model
:param student_api: StudentApi object
:return: score as a float
"""
# Check which simulators have datapoints with outcomes outcomes
simulator_ids = []
for simulator in capstone.simulators... | bb4f545835f480c9fac97acc698daef08a7684f2 | 14,515 |
def clean_lhdf(df: pd.DataFrame):
"""
Removes unneccessary columms from the location history data frame and computes new required columns
Parameters
----------
df : pandas.DataFrame
DataFrame to process
Returns
-------
Copy of `df`, altered the following way:
* Colums remov... | 86280a333082e964553030d4e586a267e93edfae | 14,516 |
def year_from_operating_datetime(df):
"""Add a 'year' column based on the year in the operating_datetime.
Args:
df (pandas.DataFrame): A DataFrame containing EPA CEMS data.
Returns:
pandas.DataFrame: A DataFrame containing EPA CEMS data with a 'year'
column.
"""
df['year']... | 1c7bbc6465d174465151e5e777671f319ee656b7 | 14,517 |
def is_thrift(target):
"""Returns True if the target has thrift IDL sources."""
return isinstance(target, JavaThriftLibrary) | 4a56cf5cec923933fec628173cb2ab1a122b0127 | 14,518 |
def get_instance(value, model):
"""Returns a model instance from value. If value is a string, gets by key
name, if value is an integer, gets by id and if value is an instance,
returns the instance.
"""
if not issubclass(model, db.Model):
raise TypeError('Invalid type (model); expected subcla... | 85544b057e3e6c82730ba743a625610c55b48ff0 | 14,519 |
def clean_infix(token, INFIX):
"""
Checks token for infixes. (ex. bumalik = balik)
token: word to be stemmed for infixes
returns STRING
"""
if check_validation(token):
return token
for infix in INFIX_SET:
if len(token) - len(infix) >= 3 and count_vowel(token[len(infix):]) >= 2:
if token[0] == token[... | fdd8e90bdea14ca2344dd465622bd2e79905e4fe | 14,520 |
def seq_to_encoder(input_seq):
"""从输入空格分隔的数字id串，转成预测用的encoder、decoder、target_weight等
"""
input_seq_array = [int(v) for v in input_seq.split()]
encoder_input = [PAD_ID] * \
(input_seq_len - len(input_seq_array)) + input_seq_array
decoder_input = [GO_ID] + [PAD_ID] * (output_seq_len - 1)
e... | 9a9203aa9e3005acd7d55516fbe8c5710ea25ae3 | 14,521 |
def getMergers(tree, map_strain2species, options):
"""merge strains to species.
returns the new tree with species merged and
a dictionary of genes including the genes that have been merged.
Currently, only binary merges are supported.
"""
n = TreeTools.GetSize(tree) + 1
all_strains = map_... | 48fb083027e00d93754ee4064edbc268ea4047a5 | 14,522 |
def convolve_with_gaussian(
data: np.ndarray, kernel_width: int = 21
) -> np.ndarray:
"""
Convolves a 1D array with a gaussian kernel of given width
"""
# create kernel and normalize area under curve
norm = stats.norm(0, kernel_width)
X = np.linspace(norm.ppf(0.0001), norm.ppf(0.9999), k... | 63949d9c235a1a467858077de8dda8455c139551 | 14,523 |
def post_netspeed(event, context):
"""
Speed test data ingestion handler
"""
return process_reading(event['query'], NETSPEED_SQL) | 8414fe3608b7433a177f0c8c54cce61d01339b67 | 14,524 |
import json
def notify_host_disabled(token, host_name):
"""
Notify OpenStack Nova that a host is disabled
"""
url = token.get_service_url(OPENSTACK_SERVICE.NOVA, strip_version=True)
if url is None:
raise ValueError("OpenStack Nova URL is invalid")
# Get the service ID for the nova-com... | 904c951a37b8b84df4aa48951c424686a123ff30 | 14,525 |
def compute_moments_weights_slow(mu, x2, neighbors, weights):
"""
This version exaustively iterates over all |E|^2 terms
to compute the expected moments exactly. Used to test
the more optimized formulations that follow
"""
N = neighbors.shape[0]
K = neighbors.shape[1]
# Calculate E[G]... | 5a2984174f366a34f16490bb7b9252ec4eaf08db | 14,526 |
import functools
def sum_fn(fun, ndims=0):
"""Higher order helper for summing the result of fun."""
@functools.wraps(fun)
def wrapped(*args):
batch_loglik = fun(*args)
return jnp.sum(
batch_loglik.reshape((-1,) +
batch_loglik.shape[-ndims +
... | 521a4084fee84f16de5714010be9528296f8b231 | 14,527 |
from typing import Optional
def get_control_policy_attachments(language: Optional[str] = None,
output_file: Optional[str] = None,
policy_type: Optional[str] = None,
target_id: Optional[str] = None,
... | cfa39ca8926c281151b5ae06ef89ce865dfd0af4 | 14,528 |
def get_gdb(chip_name=None,
gdb_path=None,
log_level=None,
log_stream_handler=None,
log_file_handler=None,
log_gdb_proc_file=None,
remote_target=None,
remote_address=None,
remote_port=None, **kwargs):
"""
set to != N... | 15dc451b9cbf21c5f96279a17449e4169e0bae83 | 14,529 |
from typing import Callable
from typing import Awaitable
def check(func: Callable[..., Awaitable[Callable[[CommandContext], Awaitable[bool]]]]) -> Check:
"""
A decorator which creates a check from a function.
"""
return Check(func) | 2354eef311e1867333ade47996fb37cee07ce4cd | 14,531 |
def service_c(request):
""" Renders the service chair page with service submissions """
events = ServiceEvent.objects.filter(semester=get_semester())
submissions_pending = ServiceSubmission.objects.filter(semester=get_semester(), status='0').order_by("date")
submissions_submitted = ServiceSubmission.ob... | 96d9b281c562a0ddb31d09723012cc9411c4ff09 | 14,532 |
def get_tank_history(request, tankid):
"""
Returns a response listing the device history for each tank.
"""
# Sanitize tankid
tankid = int(tankid)
# This query is too complex to be worth constructing in ORM, so just use raw SQL.
cursor = connection.cursor()
cursor.execute("""\
SE... | 39c21c9761ff0e40e1c1f8904cf9b9881faf13ed | 14,533 |
import inspect
def get_absolute_module(obj):
"""
Get the abolulte path to the module for the given object.
e.g. assert get_absolute_module(get_absolute_module) == 'artemis.general.should_be_builtins'
:param obj: A python module, class, method, function, traceback, frame, or code object
:retu... | ea2c85d9ba90414cddce00dcc5ed092b8c6777a2 | 14,534 |
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