content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def select_text(table, col_names, version):
"""Generate a select statement for new or old values of this table."""
slt = "SELECT {tuple_str} FROM {table} WHERE rowid={version}.rowid".format(
tuple_str=sqlite_list_text([col_pair_text(c, version)
for c in col_names]),
... | 28f22ad8478cd87d1d56c7a1a6b86d0b81e1d457 | 52,800 |
def predict(Theta1, Theta2, X):
""" outputs the predicted label of X given the
trained weights of a neural network (Theta1, Theta2)
"""
if X.ndim == 1:
X = X.reshape(1, -1)
# Useful values
m = len(X)
# ====================== YOUR CODE HERE ======================
# Instructions:... | ba3df784fdd2a76fc59f0f010a9a4eb4c5be035f | 52,801 |
def aml_token(chain, team_multisig, token_name, token_symbol, initial_supply) -> Contract:
"""Create the token contract."""
args = [token_name, token_symbol, initial_supply, 0, True] # Owner set
tx = {
"from": team_multisig
}
contract, hash = chain.provider.deploy_contract('AMLToken', de... | b114cfc3abeeea9c600dccbc1bed78de60a7576f | 52,802 |
def invr():
"""
For taking space seperated integer variable inputs.
"""
return(list(map(int, input().split()))) | 9794b5c44a817cbd48709de99f16515c8684712b | 52,803 |
def _path_residuals(X, y, train, test, path, path_params, alphas=None,
l1_ratio=1, X_order=None, dtype=None):
"""Returns the MSE for the models computed by 'path'
Parameters
----------
X : {array-like, sparse matrix}, shape (n_samples, n_features)
Training data.
y : arr... | 0bfb35f3de8f5c8ba136a9cf29650667c110a039 | 52,804 |
def is_an_exact_imagined_object(predicate, imagined_object):
"""
Returns whether the imagined object matches exactly what the predicate
describes.
Inputs:
predicate: WordPredicate instance
imagined_object: RecognizedObject instance
"""
target = possible_reco... | 06aef2d1fb87d02cf60baceff81d8b153d487967 | 52,805 |
def read_field__list(infile, varname, lon, lat):
"""Read point list and initialize field."""
# Read field ...
if infile.endswith(".npz"):
# ... from numpy archive
with np.load(infile) as fi:
pts_lon, pts_lat, pts_fld = fi["lon"], fi["lat"], fi[varname]
fld = point_list_t... | 1e1baafdab9fac5a43bb95d28fb8d7d0c9d8ba31 | 52,806 |
def CircuitHeaderStartConfigurationVector(builder, numElems):
"""This method is deprecated. Please switch to Start."""
return StartConfigurationVector(builder, numElems) | 9ad0c7dd86a9f0cb90f573720802658616f81bff | 52,807 |
def get_processed_masks_and_boundaries(mask_path: str, boundary_path: str) -> tuple[ndarray, ndarray]:
"""Utility function for loading and applying preprocessing to mask and boundary image array
:param paths:
:return: tuple[ndarray, ndarray]
"""
masks = np.array(
cv2.imread(
mask... | 26def41a1e8dfe33d2d35b155164412374dfa30f | 52,808 |
import warnings
def nx_to_gdf(net, points=True, lines=True, spatial_weights=False, nodeID="nodeID"):
"""
Convert ``networkx.Graph`` to LineString GeoDataFrame and Point GeoDataFrame
Parameters
----------
net : networkx.Graph
``networkx.Graph``
points : bool
export point-based ... | 1821d06896eb9b7bfafa81aa748521ff2153bd0f | 52,809 |
def p2pkh(pubkey) -> Script:
"""Return Pay-To-Pubkey-Hash ScriptPubkey"""
return Script(b'\x76\xa9\x14'+hashes.hash160(pubkey.sec())+b'\x88\xac') | 2728805a090ddcd070b7454549018d538d71ee73 | 52,810 |
def _extract_center_face(image_shape, detected_faces):
"""Extracts the face that's the closest to the center of a image.
### Parameters
image: image with the faces.
detected_faces: list of resulting bounding boxes and keypoints from\
MTCNN().detect_faces().
### Returns
(bounding_b... | cbfb3bc4c90a62cb75eaa40854fe8829d76a18eb | 52,811 |
from typing import Optional
from typing import Union
def get_county_polygons(county_ids: Optional[intseq], state_ids: Union[int, intseq]):
"""Get a dataframe with the polygons or multipolygons representing county borders
The returned dataframe will have the county polygons for each county listed. `county_ids... | ad8a71ab0fc38658c4eff0f86030e3b14ac64a28 | 52,812 |
def add_xls_tag(file_name):
"""
Check the file_name to ensure it has ".xlsx" extension, if not add it
"""
if file_name[:-5] != ".xlsx":
return file_name + ".xlsx"
else:
return file_name | e053d9f7dad8e638122e93d05e49c5a06de3e664 | 52,813 |
def order_queryset_by_z_coord_desc(queryset, geometry_field="location"):
"""Order an queryset based on point geometry's z coordinate"""
return queryset.annotate(
z_coord=models.ExpressionWrapper(
models.Func(geometry_field, function="ST_Z"),
output_field=models.FloatField(),
... | bd9e4d9b09b2676727dc2f83452e93b50eda3716 | 52,814 |
def err_number(error) :
""" Return a error number """
result = errOk
if isinstance(error, int) :
result = error
elif isinstance(error, Error) :
result = error.error_code
if result < 0 :
result = (result - ErrorBaseNumber) * -1
return result | 8c6912a8c8466ecf4ce486a43001748d4237a217 | 52,815 |
def value_iteration(env):
"""
Performs Value Iteration to find the most optimal policy for the
Tax-v3 environment
Args:
env: Taxiv3 Gym environment
Returns:
policy: the most optimum policy
"""
V = dict()
gamma = 0.9
state_size = env.observation_space.n
action_si... | 461b65bf8de4cf30f018aad24f8452ed6b7ec247 | 52,816 |
def keypoint_3d_pck(pred, gt, mask, alignment='none', threshold=150.):
"""Calculate the Percentage of Correct Keypoints (3DPCK) w. or w/o rigid
alignment.
Paper ref: `Monocular 3D Human Pose Estimation In The Wild Using Improved
CNN Supervision' 3DV'2017. <https://arxiv.org/pdf/1611.09813>`__ .
Note... | 704cf2cc4b00ad232689d76e65d2a7241eda8fec | 52,817 |
from bioservices import biomart
from io import StringIO
def mitochondrial_genes(host, org):
"""Mitochondrial gene symbols for specific organism through BioMart.
Parameters
----------
host : {{'www.ensembl.org', ...}}
A valid BioMart host URL.
org : {{'hsapiens', 'mmusculus'}}
Orga... | affd7ff1d9014f36238b535732a1cbaac43b1308 | 52,818 |
def Bold(string):
"""Returns string wrapped in escape codes representing bold typeface."""
return '\x02%s\x0F' % string | 4dd1a0d3aecc93873f9763723a3dad76b45e2725 | 52,819 |
import os
import subprocess
def compile_src(commit_id, language):
"""将程序编译成可执行文件"""
commit = Commit.query.get(commit_id)
language = language.lower()
dir_work = os.path.join(work_dir, str(commit_id))
build_cmd = {
"c":
"gcc main.c -o main",
"c++": "g++ main.cpp -o main",
... | 26aa12aa2dceb485d10bbb383a7e967e4619bee8 | 52,820 |
from typing import List
import decimal
import json
def from_bbox_array(bbox_array: List[decimal.Decimal]):
"""returns a geojson geometry object from a bounding box array.
Keeping default number of decimal places to 6 for now,
can change depending on data precision requirements."""
if bbox_array:
... | 3bbaf66d6d5d31f45b93e944474cac5f454df313 | 52,821 |
import os
import json
def Open(filename):
"""
You can open/read a Zype File with Open() function.
Usage: Open(filename)
Filename is the Zype File's Name.
"""
if os.path.isfile(filename):
with open(filename) as Zype:
content = Zype.read()
content = conten... | 20a48af9c7e7a0f74e72fa02c7241915b5c5b78c | 52,822 |
def taiwanLightCompensation(im, theta=0.5, thresh=0.2, B=[10, 30]):
""" Perform light compensation
http://www.csie.ntu.edu.tw/~fuh/personal/LightCompensation.pdf
:param theta: weight of corrected image in final output
:return: light compensated image
"""
def getOptimalB(im, thresh, B):
... | ac7c1fa06bb7cc2f0904b8da1ad360a027d6778f | 52,823 |
def _is_sweep_sequential(radar, sweep_number):
""" Test if a specific sweep is sequentially ordered. """
start = radar.sweep_start_ray_index['data'][sweep_number]
end = radar.sweep_end_ray_index['data'][sweep_number]
if radar.scan_type == 'ppi':
angles = radar.azimuth['data'][start:end+1]
el... | 3bc493b80d245a51295c5e3461f9442baecd15cb | 52,824 |
import random
def random_expand(image, boxes):
"""
Perform a zooming out operation by placing the image.
Helps to learn to detect smaller objects.
Args:
image(numpy.array): image, a array of dimensions (original_h, original_w, 3)
boxes(numpy.array): bounding boxes in boundary coordin... | 79e958a8acdc622e3e2e9270a2a29ededcc110b3 | 52,825 |
import re
import sys
def google_maps(query: str) -> bool:
"""Uses google's places api to get places near by or any particular destination.
This function is triggered when the words in user's statement doesn't match with any predefined functions.
Args:
query: Takes the voice recognized statement ... | f0a8e25e54a93b0296c537cbc035cded8c9b9675 | 52,826 |
def matMULTI(first,second):
"""
Take in two matrix
multiply each element against the other at the same index
return a new matrix
"""
newMAT = []
newCOL = []
for i in range(len(first)):
for j in range(len(first[i])):
newMAT.append(first[i][j]*second[i][j])
#new... | 28b3b5954a483311bca6245c7472a99e8a12395c | 52,827 |
def put_html(html, sanitize=False, scope=Scope.Current, position=OutputPosition.BOTTOM) -> Output:
"""
Output HTML content
:param html: html string
:param bool sanitize: Whether to use `DOMPurify <https://github.com/cure53/DOMPurify>`_ to filter the content to prevent XSS attacks.
:param int scope,... | 60a10c44df3b4ba66f8ac428bfbfeaa60b069ac9 | 52,828 |
import sys
import os
def check_enableusersite():
"""Check if user site directory is safe for inclusion
The function tests for the command line flag (including environment var),
process uid/gid equal to effective uid/gid.
None: Disabled for security reasons
False: Disabled by user (command line o... | 466ce7da62b6578db0f99ca31c7271ef3bc2d832 | 52,829 |
def convert_list2dict(word_list):
"""
把列表写成字典
"""
word_dict = defaultdict(int)
for w in word_list:
word_dict[w] = 1
return word_dict | 72bf12e52f8ebd8d9b9ce3626b995d0ababc2ab5 | 52,830 |
def GetAuthorizationCodeViaCommandLine(config):
"""Gets authorization code via command line.
This way is useful anywhere without a browser.
Args:
config: a dictionary of config.
Returns:
authorization code.
"""
body = urlencode({
'scope': config['scope'],
'redirect_uri': config['redir... | 67f7603825fcf30a4fbb957414e90525a88ceae5 | 52,831 |
def pedestal_ids_file(base_test_dir):
"""Mock pedestal ids file for testing."""
pedestal_ids_dir = base_test_dir / "auxiliary/PedestalFinder/20200117"
pedestal_ids_dir.mkdir(parents=True, exist_ok=True)
file = pedestal_ids_dir / "pedestal_ids_Run01808.0000.h5"
file.touch()
return file | edda4c192e577774e0cc4a38aaa7d838127e7dcd | 52,832 |
def get_fa_icon_class(app_config):
"""Return Font Awesome icon class to use for app."""
if hasattr(app_config, "fa_icon_class"):
return app_config.fa_icon_class
else:
return 'fa-circle' | 3766abb1f80b7ccea9e09a5edf011f1586e9b49e | 52,833 |
def linear_activation_forward(a_prev, w, b, activation):
"""
activation step for forward propagation with multiple choices of activation function.
@param a_prev: previous A from last step of forward propagation, numpy arrays
@param w: parameter W in current layer, numpy arrays
@param b: parameter b... | 58a12f753c42201400747e52213b95d372ae6e89 | 52,834 |
from pathlib import Path
import subprocess
def git_checkout(repo: Repo, git_ref: str) -> str:
"""
git_ref is of the form refs/heads/main or refs/tags/0.0.3
"""
git_dir = repo.directory
is_branch = git_ref.startswith('refs/heads/')
target = git_ref
if is_branch:
# We need the branc... | 1bf14117a38ea8c4eebff5d54956da003f4d8277 | 52,835 |
import time
def create_token(args):
"""
POST /api/v1/create_token HTTP/1.1
Host: 127.0.0.1:5000
Content-Type: application/json
Content-Length: 74
{
"name":"1234",
"password" :"1234",
"email" : "1234",
"duration":123
}
{"access_token":"ad236cdb-f645-456... | 74012f112c5d22a088e1e58032d35de5b1436028 | 52,836 |
def getDictionary(id_or_identifier):
"""
指定した id または identifier を持つ辞書のメタデータを返します。
id, identifier に一致する辞書が存在しない場合は None を返します。
Parameters
----------
id_or_identifier : str or int
str の場合は辞書 identifier で指定。
int の場合は内部辞書 id で指定。
Returns
-------
Metadata
Metadat... | 7d3f19ee4a9952afb336eb00cbc28a07191d02b2 | 52,837 |
from typing import Optional
import os
def load_import_config(project: Project) -> Optional[ImportConfig]:
"""
Loads the import config for the project (if it exists, otherwise None is returned):
"""
import_path = os.path.join(project.folder(), IMPORT_PROJECT_FILENAME)
if not os.path.exists(import_p... | a8911c0810658ce59a04fecb6eeee200a50de2a3 | 52,838 |
def is_phone_in_call(log, ad):
"""Return True if phone in call.
Args:
log: log object.
ad: android device.
"""
return ad.droid.telecomIsInCall() | bf279c1892077de53f13976179ecf762f45f54b6 | 52,839 |
def omicron_model(
xs: np.ndarray,
ts: np.ndarray,
params: dict
) -> np.ndarray:
"""
SL_2I_4R model with dual immunity
:param np.ndarray xs: actual array of states
:param np.ndarray ts: time values
:param dict params: dictionary of parameters
:return np.ndarray
""... | 52ce91a0be8f8f5054c12c08993ed8303ffd87f3 | 52,840 |
def identity(n):
""" Return n """
return n | cc3249a1164e18f47f962e4db56a425876a87b17 | 52,841 |
def look_for_general(
m_str: str,
ref_dict: defaultdict,
base_num: t.Pattern[str],
full_num: t.Pattern[str],
doc_type: str,
) -> defaultdict:
"""
Reference Extraction by Regular Expression: For general use
Args:
m_str: text string to search
ref_dict: dictionary of refere... | 1563e85f9228f9ffb14f14869ecf1f73441ae2e6 | 52,842 |
def losses_and_metrics(num_classes):
"""
Define loss and metrics
Loss: Categorical Crossentropy
Metrics: (Train, Validation) Accuracy, Precision, Recall, F1
Returns:
loss, train loss, train acc, valid loss, valid acc, precision, recall, auc, f1
"""
loss_fn = CategoricalCrossentropy... | d8f571c4e2948007d8b6f880afbbd0e2fcfab00d | 52,843 |
import copy
def get_skill_from_model(skill_model):
"""Returns a skill domain object given a skill model loaded
from the datastore.
Args:
skill_model: SkillModel. The skill model loaded from the
datastore.
Returns:
skill. A Skill domain object corresponding to the given
... | c75ea6c7705d316a5d279da36468dd9278ceae44 | 52,844 |
import os
def get_loaders(dataset_path, batch_size=32, num_workers=12, mean=None, std=None):
"""
Function to load the train/test loaders.
Parameters
----------
dataset_path: str, dataset path.
batch_size: int, batch size.
num_workers: int, number of workers.
mean:None or torch.Tensor... | b950f7bb79aa6d6891e58bc256ee7cad30e31f69 | 52,845 |
def delete_tags_for_manifest(manifest):
""" Deletes all tags pointing to the given manifest. Returns the list of tags
deleted.
"""
query = Tag.select().where(Tag.manifest == manifest)
query = filter_to_alive_tags(query)
query = filter_to_visible_tags(query)
tags = list(query)
now_ms = get_epoch_ti... | a78b77ea96a3870b736301443005e45d58f76c42 | 52,846 |
def eeg_epochs_dataset(subject, trial, config, preload=True):
"""Get the epoched eeg data excluding unnessary channels
from fif file and also filter the signal.
Parameter
----------
subject : string of subject ID e.g. 7707
trial : HighFine, HighGross, LowFine, LowGross
Returns
------... | 58e6a1d63d2cc01416761b48a32a5bc9ebeacef9 | 52,847 |
def differences(lis, n=1):
"""
Returns the `n` successive differences of the elements in
`lis`.
EXAMPLES::
sage: differences(prime_range(50))
[1, 2, 2, 4, 2, 4, 2, 4, 6, 2, 6, 4, 2, 4]
sage: differences([i^2 for i in range(1,11)])
[3, 5, 7, 9, 11, 13, 15, 17, 19]
... | 067ee6e5744211f2b41f55f8cd7383431df1e486 | 52,848 |
def get_bounded_progress():
"""
returns progress as a tensor between 0 and 1
"""
assert get_default_counter().expected_count is not None
return get_default_counter()._bounded_progress | 3279ead5729521280bc0fd9295de861944f02b9a | 52,849 |
from matplotlib import path, transforms
def polygon_clip(rp, cp, r0, c0, r1, c1):
"""Clip a polygon to the given bounding box.
Parameters
----------
rp, cp : (N,) ndarray of double
Row and column coordinates of the polygon.
(r0, c0), (r1, c1) : double
Top-left and bottom-right coo... | 4fd565084417c04e1ad45c713704e9ff41d74eaa | 52,850 |
import six
def _is_start_piece_sp(piece):
"""Check if the current word piece is the starting piece (sentence piece)."""
special_pieces = set(list('!"#$%&\"()*+,-./:;?@[\\]^_`{|}~'))
special_pieces.add(u"€".encode("utf-8"))
special_pieces.add(u"£".encode("utf-8"))
# Note(mingdachen):
# For foreign characte... | 591373699c5e4c41248c81dac2bae5520123b2e7 | 52,851 |
import math
def atrpips(data, length):
"""Average True Range indicator in pips
Arguments:
data {list} -- List of ohlc data [open, high, low, close]
length {int} -- Lookback period for atr indicator
Returns:
list -- ATR (in pips) of given ohlc data
"""
atr_pips = []
av... | b73ab18cd0e1f338cc8136c0ccd82fd056d668a9 | 52,852 |
def start_day(start):
"""Return TMIN, TAVG, TMAX."""
start_day = session.query(Measurement.date, func.min(Measurement.tobs), func.avg(Measurement.tobs), func.max(Measurement.tobs)).filter(Measurement.date >= start).group_by(Measurement.date).all()
start_day_list = list(start_day)
return jsonify(start_da... | 3c24c3c22dc1444e4bc46baeaa3e527a1e2af75b | 52,853 |
def R123(a,b,c, degrees=False):
"""Returns a rotation matrix based on: Z*Y*X"""
if degrees:
a *= deg2rad
b *= deg2rad
c *= deg2rad
s3 = np.sin(c); c3 = np.cos(c)
s2 = np.sin(b); c2 = np.cos(b)
s1 = np.sin(a); c1 = np.cos(a)
return np.array(
[
[c1*c2,... | 8097514d390d73d1121c9462cada98060681619e | 52,854 |
from datetime import datetime
from typing import Optional
import time
from typing import Union
import calendar
def get_next(
base: datetime,
interval: Interval,
frequency: int,
at_time: Optional[time] = None,
days: Optional[list[int]] = None,
) -> Union[datetime, date]:
"""Get the next due dat... | 678b5c85615e388e2ae221df7ffba7ee38f97584 | 52,855 |
from typing import Union
def guess_font_size(
size: tuple[int, int], font_name: str
) -> tuple[Union[ImageFont, FreeTypeFont], int]:
"""Try and figure out the correct font size for a given height and font.
Args:
``size``: The dimensions of the image in pixels.
``font_name``: The name of t... | 01733050378885184ea5e0dbaba053263cf139bd | 52,856 |
def create_model(
time_set=None,
time_units=pyo.units.s,
nfe=5,
tee=False,
calc_integ=True,
):
"""Create a test model and solver
Args:
time_set (list): The beginning and end point of the time domain
time_units (Pyomo Unit object): Units of time domain
nfe (int): Numb... | 9330c87db97d42de665c8198eaa113045ef92897 | 52,857 |
from pathlib import Path
def read_table(h5file, path, start=None, stop=None, step=None, condition=None) -> Table:
"""Read a table from an HDF5 file
This reads a table written in the ctapipe format table as an `astropy.table.Table`
object, inversing the column transformations units.
This uses the sam... | f3ef6b3ff7afc81e1afd9cca594727b8117471bc | 52,858 |
from typing import Any
def get_valid_ref(ref: Any) -> str:
"""Checks flow reference input for validity
:param ref: Flow reference to be checked
:return: Valid flow reference, either 't' or 's'
"""
if ref is None:
ref = 't'
else:
if not isinstance(ref, str):
raise ... | 16c66dc9e0568bcd33e1cc9956ed31b5ae47595e | 52,859 |
def k_argmin(l, k, func):
"""
Gets the indices and values of the k-smallest function results
from func.
"""
l_map = map(func, l)
return k_min(l_map, k) | 750f408723ad9e024d45796bcc3250a9fcab296a | 52,860 |
from typing import List
import os
from pathlib import Path
def create_zip_task(
result: dict = None,
task_uid: str = None,
data_provider_task_record_uid: List[str] = None,
data_provider_task_record_uids: List[str] = None,
run_zip_file_uid=None,
*args,
**kwargs,
):
"""
:param result... | 8b04b99cb07b69d263a39863f120e5356f342f1a | 52,861 |
from typing import Optional
from typing import Tuple
def add_ports_from_markers_square(
component: Component,
pin_layer: LayerSpec = "DEVREC",
port_layer: Optional[LayerSpec] = None,
orientation: Optional[int] = 90,
min_pin_area_um2: float = 0,
max_pin_area_um2: float = 150 * 150,
pin_extr... | 349893ef57c43dfc634af54086c98720207d2d6c | 52,862 |
def calc_periodicity(peak_info, period_min=5, period_max=15):
"""
calculate the period
:param peak_info:
:param period_min:
:param period_max:
:return:
"""
num_peaks = peak_info.shape[0]
# calculate periodicity
peak_info[:num_peaks-1, 2] = np.diff(peak_info[:, 0])
peak_info =... | ac7ca44153019773741e6e6ca15fd9961bb16089 | 52,863 |
from typing import Type
def create_global_resource(group: str, version: str, kind: str, plural: str, verbs=None) \
-> Type[GenericGlobalResource]:
"""Create a new class representing a global resource with the provided specifications.
**Parameters**
* **group** `str` - API group of the resource. ... | c6cb2e05a048456ed7103c6e1b4c81692b34987a | 52,864 |
from typing import Dict
from typing import Hashable
from typing import Any
def outline_to_implementation(
name: str,
design: str,
outline: fiat.Outline) -> Dict[Hashable, Any]:
"""[summary]
Args:
name (str): [description]
design (str): [description]
outline (fiat.Outline)... | 871c7fd4f950c291832cbd0fc3dce823831c4257 | 52,865 |
import re
def match(pattern, name):
"""Test whether a name matches a wildcard pattern.
Arguments:
pattern (str): A wildcard pattern, e.g. ``"*.py"``.
name (bool): A filename.
Returns:
bool: `True` if the filename matches the pattern.
"""
try:
re_pat = _PATTERN_CA... | 145023b54449f85bed0421dcf446352c32328bae | 52,866 |
def _OldEnough(try_bot_cache, bot_id):
"""Checks if the build in the given bot's cache is older than threshold."""
built_cp = try_bot_cache.full_build_commit_positions[bot_id]
tot_cp = git.GetCommitPositionFromRevision('HEAD')
return built_cp < tot_cp - STALE_CACHE_AGE | 0b6ff7a3e1f08ecf602239d127ac879539975bcc | 52,867 |
def the_joke():
"""
Combining both joke and emojis into one function.
"""
return yomama() + laugh() | f7a6baa9cba166f8ddd6d8993f4d8d7225c8d467 | 52,868 |
def return_dict():
"""
"interfaces": {
"Tunnel0": {
"state": "UP"
},
"Tunnel1": {
"state": "DOWN"
}
}
}
"""
return {"interfaces": {"Tunnel0": {"state": "UP"}, "Tunnel1": {"state": "DOWN"}}} | 2c3e71341c425166d11aba9175e3a98027c3d53e | 52,869 |
from typing import List
import itertools
def allocation_with_lowest_gain(agents: List[Agent], allocations: List[CakeAllocation]) -> CakeAllocation:
"""
Finds an allocation such that for all agents, gain(agent) (as defined by `get_agent_gain`) in that
allocation scope is less than the sum of gain(agent) fo... | 3de69a8f735329fb110e7323c851b3a13c58522e | 52,870 |
import torch
def replace_magnitude(x, mag):
"""
Extract the phase from x and apply it on mag
x [B,2,F,T] : A tensor, where [:,0,:,:] is real and [:,1,:,:] is imaginary
mag [B,1,F,T] : A tensor containing the absolute magnitude.
"""
phase = torch.atan2(x[:, 1:], x[:, :1]) # imag, real
ret... | b535e4271c6fc4fe508af358fbe3eee59a95cc6b | 52,871 |
def is_ip_address(host: str) -> bool:
"""Determine if host is an IP Address."""
try:
ip_address(host)
except ValueError:
return False
return True | 90b66e8b8b43ee20796ba2e3a408d217978741aa | 52,872 |
def cut_rod2(p, n, r={}):
"""Cut rod.
Same functionality as the original but implemented
as a top-down with memoization.
"""
q = r.get(n, None)
if q:
return q
else:
if n == 0:
return 0
else:
q = 0
for i in range(n):
... | 2fa1433dffb9099709e466025645c4981f289692 | 52,873 |
import logging
def RunLoad(redis_vm, load_vm, threads, port, test_id):
"""Spawn a memteir_benchmark on the load_vm against the redis_vm:port.
Args:
redis_vm: The target of the memtier_benchmark
load_vm: The vm that will run the memtier_benchmark.
threads: The number of threads to run in this memtier_... | 9935a619a6c267023fdcf751b24b9a339d28551a | 52,874 |
import os
def choose_vnc_display():
"""Try to choose a free vnc display.
"""
def netstat_local_ports():
"""Run netstat to get a list of the local ports in use.
"""
l = os.popen("netstat -nat").readlines()
r = []
# Skip 2 lines of header.
for x in l[2:]:
... | 66f65fbbbf51323975af0050a7225aaf71ab1a8c | 52,875 |
import os
def change_last_activation_to_linear(model: Model, dependencies=None) -> Model:
"""
Changes last activation function to linear, if it already is linear - returns same model
:param dependencies: necessary objects for custom functions in keras
:param model: Keras model
:return: Keras model... | 41b206de30179c67dce9aa56af04831574c4ef67 | 52,876 |
from re import T
def import_data():
"""
Export data via CRUD controller.
Old - being replaced by Sync.
"""
title = T("Import Data")
return dict(title=title) | 5547236231e524e3d36fde1249f0eb0eaa9427df | 52,877 |
def _set_karma(bot, trigger, change, reset=False):
"""Helper function for increasing/decreasing/resetting user karma."""
channel = trigger.sender
user = trigger.group(2).split()[0]
if reset:
bot.db.set_nick_value(user, 'karma', 0)
return
karma = bot.db.get_nick_value(user, ... | 72531c032625c365e057057edb84672b86a4faac | 52,878 |
def read_kazr(filename, field_names=None, additional_metadata=None,
file_field_names=False, exclude_fields=None):
"""
Read K-band ARM Zenith Radar (KAZR) NetCDF ingest data.
Parameters
----------
filename : str
Name of NetCDF file to read data from.
field_names : dict, opt... | 7b8d87c27b4a69ddbe40ed4e8c5b68b981b06ef9 | 52,879 |
def addScriptOptions(parser, pos_args, kw_args):
""" add script-specific script options """
script_options_group = parser.add_argument_group('Options')
hlpstr = "Prefix string for output filenames. Can optionally include a " \
"full path. Defaults to the input filename."
... | fbf44211bd23eb46e564dee9e6f8b5262f613176 | 52,880 |
def get_dag(node):
"""
:param str node:
:return: Maya dag path node
:rtype: OpenMaya.MDagPath
"""
sel = OpenMaya.MSelectionList()
sel.add(node)
return sel.getDagPath(0) | c28ce48a801ebde3c55e34235546eafa9f67b612 | 52,881 |
def aistats2022():
"""Font size for AISTATS 2022."""
return _from_base(base=10) | 984c4e7e697fea6a8c7643d2e8ac80b20f1fdfc5 | 52,882 |
def format_filt( something ):
"""
Example of a filter that can be used within
the Jinja2 code
"""
return "Not what you asked for" | 3878f805f21f2be3a4b96173f04257308f72bd45 | 52,883 |
def conv_upample(conv, x, occupy, real_num, out_coords, out_occupy, out_stride=1, mul_occupy_after=True):
"""
Add occupancy value for sparse convolution that decreases the stride for input data
"""
if occupy.ndim < 2:
occupy = occupy.unsqueeze(1)
if conv.kernel.ndim < 3:
conv.kerne... | 84b21d16fe3105dd6b1c8cc191b1a1a9303fc1f7 | 52,884 |
def get_field_node(field_config: dict, config: dict, source=None) -> object:
"""
get field node.
"""
required = field_config.get(FIELD_REQUIRED, False)
field_type, field_attrs = tuple(field_config[FIELD_TYPE].items())[0][0], tuple(
field_config[FIELD_TYPE].items())[0][1]
if field_type ==... | 431b43032fa77823860aa697df776d4539628615 | 52,885 |
from typing import Optional
def subcycles() -> Parser:
"""Return a parser to parse the <subcycles> tag.
:return:
A parser that consumes the <subcycles> tag and produces an
:class:`rads.config.ast.Assignment` AST node which assigns to
"subcycles" a :class:`rads.config.tree.SubCycles` d... | 50d79b8424b1ec082f12cf8af4f295f057294aeb | 52,886 |
from gtmcore.container.local_container import LocalProjectContainer
from gtmcore.container.hub_container import HubProjectContainer
from typing import Optional
def container_for_context(username: str, labbook: Optional[LabBook] = None, path: Optional[str] = None,
override_image_name: Optiona... | 792b2111de209e7a11900eae513e839677ad8f82 | 52,887 |
import re
def suggest(term):
"""
Find most appropriate EFO term for arbitrary string
Arg:
* string
Returntype: string (EFO ID)
"""
server = 'http://www.ebi.ac.uk/spot/zooma/v2/api'
url_term = re.sub(" ", "%20", re.sub("[%&]", "", term))
ext = "/services/annotate?propertyValue=%s&filter=required:[none],... | 4673c1fc715cc77bfb0db8b877174c5be6e6af51 | 52,888 |
import numpy
def plot_matplotlib_dgt(func, **kwargs):
"""
Plot scalar discontinuous Galerkin Trace functions in 2D
"""
# Get information about the underlying function space
function_space = func.function_space()
family = func.ufl_element().family()
mesh = function_space.mesh()
ndim = m... | e581b761614ba99424d0933a1f4b4d124921e44d | 52,889 |
from typing import Callable
from typing import Awaitable
def mapi_async(mapper: Callable[[TSource, int], Awaitable[TResult]]) -> Projection[TSource, TResult]:
"""Map with index async.
Returns an observable sequence whose elements are the result of
invoking the async mapper function by incorporating the e... | 86c2f1ea0a20b04dab24246a92dda87e29ed4ead | 52,890 |
def descriptors_to_file(config_filepath: str, descriptors: kapture.Descriptors) -> None:
"""
Writes descriptors to CSV file.
:param config_filepath:
:param descriptors:
"""
return image_feature_to_file(config_filepath, descriptors) | cfbfa147893681672666cd09a1b94574893a9798 | 52,891 |
def parseEdmSize(lines):
"""
Returns a list of dictionaries
Example of data:
>>> parseEdmSize(lines = ( 'File MINBIAS__RAW2DIGI,RECO.root Events 8000', 'TrackingRecHitsOwned_generalTracks__RECO. 407639 18448.4', 'recoPreshowerClusterShapes_multi5x5PreshowerClusterShape_multi5x5PreshowerXClustersShape_RECO. 289.787... | 432f697d2c4baf795b3e41f574ba9d3d7ea6a802 | 52,892 |
def get_activation_function(label: str) -> ActivationFunction:
"""Get activation function by label
:param label: string denoting function
:return: callable function
"""
if label == 'lin':
return Linear()
if label == 'sigmoid':
return Sigmoid()
if label == 'tanh':
ret... | d143734f0e2713fbc6e660467d1256afd876a681 | 52,893 |
def Detector_List(scanIOC):
"""
Define the detector used for:
keithley_live_strseq()
Detector_Triggers_StrSeq()
BeforeScan_StrSeq() => puts everybody in passive
CA_Average()
WARNING: can't have more than 5 otherwise keithley_live_strseq gets angry.
"""
BL_mode=BL_Mod... | c2303314fb556e504540ccd2f2f0af0c9c2590b2 | 52,894 |
import torch
def _instance_accuracy(label, raw_pred, compare_func, return_float=True, feed_dict=None, args=None):
"""get instance-wise accuracy for structured prediction task instead of pointwise task"""
# disctretize output predictions
if not args.task_is_sudoku:
pred = as_tensor(raw_pred)
... | 51831f2160a0eec6fbec4e7d8992009b3fff7811 | 52,895 |
import html
def get_stressors(lat,lon):
"""
Example for looking up stressors at a particular location.
"""
# Note df is a flattened list of lat/lon values that only includes those over land
df = pvcz.get_pvcz_data()
# Point of interest specified by lat/lon coordinates.
lat_poi = float(l... | 34718b197d265c98d2d3e0a30d041af6e8b1e44e | 52,896 |
def load_and_prepare_image(filename, img_shape=224, rescale=True):
"""
Preparing an image for image prediction task.
Reads and reshapes the tensor into needed shape (img_shape, img_shape, 3).
Image tensor is rescaled.
:param filename (str): full-path filename of the image
:param img_shape (int):... | e666dc909dbc0411c009ca791d1ee2aacf9d32c1 | 52,897 |
def jacobi_recr_coeffs(n, alpha, beta):
"""calculate the coefficients used in recursion relationship
Args:
n: the targeting order
alpha: the alpha coefficient of Jacobi polynomial
beta: the veta coefficient of Jacobi polynomial
Returns:
a1, a2, a3, a4: the coefficients used... | f9beb604af7b82fad8e0a81beed6852ea007cd30 | 52,898 |
def get_key(window, key):
"""
Returns the last reported state of a keyboard key for the specified
window.
Wrapper for:
int glfwGetKey(GLFWwindow* window, int key);
"""
return _glfw.glfwGetKey(window, key) | b3b1b699d766ae9054278bcc85654c35cd9b3241 | 52,899 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.