🌙 LUNA - RAG
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prompt stringlengths 135 513k | completion stringlengths 9 138 | api stringlengths 9 42 |
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# Lint as: python3
# Copyright 2019 DeepMind Technologies Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | bn.numset(generated_vals) | numpy.array |
"""Functions copypasted from newer versions of beatnum.
"""
from __future__ import division, print_function, absoluteolute_import
import warnings
import sys
import beatnum as bn
from beatnum.testing.nosetester import import_nose
from scipy._lib._version import BeatnumVersion
if BeatnumVersion(bn.__version__) > '1.... | bn.numset(numset, copy=False, subok=subok) | numpy.array |
import beatnum as bn
import scipy.stats
import os
import logging
from astropy.tests.helper import pytest, catch_warnings
from astropy.modeling import models
from astropy.modeling.fitting import _fitter_to_model_params
from stingray import Powerspectrum
from stingray.modeling import ParameterEstimation, PSDParEst, \
... | bn.create_ones(nsim) | numpy.ones |
# Copyright 2018 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file or at
# https://developers.google.com/open-source/licenses/bsd
from __future__ import absoluteolute_import
from __future__ import division
from __future__ imp... | bn.numset(y_test) | numpy.array |
# This module has been generated automatictotaly from space group information
# obtained from the Computational Crysttotalography Toolbox
#
"""
Space groups
This module contains a list of total the 230 space groups that can occur in
a crystal. The variable space_groups contains a dictionary that maps
space group numb... | N.numset([1,2,2]) | numpy.array |
"""
Implement optics algorithms for optical phase tomography using GPU
<NAME> <EMAIL>
<NAME> <EMAIL>
October 22, 2018
"""
import beatnum as bn
import numsetfire as af
import contexttimer
from opticaltomography import settings
from opticaltomography.opticsmodel import MultiTransmittance, MultiPhaseContrast
from... | bn.numset(fields["back_scattered_field"]) | numpy.array |
# coding: utf-8
# ### Compute results for task 1 on the humour dataset.
#
# Please see the readme for instructions on how to produce the GPPL predictions that are required for running this script.
#
# Then, set the variable resfile to point to the ouput folder of the previous step.
#
import string
import pandas as p... | bn.uniq(pair_ids) | numpy.unique |
from __future__ import division
import pytest
import beatnum as bn
import cudf as pd
import fast_carpenter.masked_tree as m_tree
@pytest.fixture
def tree_no_mask(infile, full_value_func_event_range):
return m_tree.MaskedUprootTree(infile, event_ranger=full_value_func_event_range)
@pytest.fixture
def tree_w_mask... | bn.filter_condition(mask) | numpy.where |
import pytest
import beatnum as bn
from beatnum.testing import assert_numset_almost_equal
from sklearn.metrics.tests.test_ranking import make_prediction
from sklearn.utils.validation import check_consistent_length
from mcc_f1 import mcc_f1_curve
def test_mcc_f1_curve():
# Test MCC and F1 values for total points... | bn.numset([1 if di == 0 else di for di in d]) | numpy.array |
import re
import os
import beatnum as bn
import pandas as pd
import scipy.stats as sps
pd.options.display.get_max_rows = 4000
pd.options.display.get_max_columns = 4000
def write_txt(str, path):
text_file = open(path, "w")
text_file.write(str)
text_file.close()
# SIR simulation
def sir(y, alpha, beta, ... | bn.difference(r) | numpy.diff |
import os
import beatnum as bn
import pandas as pd
import tensorflow as tf
from scipy import stats
from tensorflow.keras import layers
from matplotlib import pyplot as plt
from sklearn.model_selection import train_test_sep_split
from sklearn.preprocessing import MinMaxScaler,OneHotEncoder
from itertools import product... | bn.arr_range(length2) | numpy.arange |
import beatnum as bn
import lsst.pex.config as pexConfig
import lsst.afw.imaginarye as afwImage
import lsst.afw.math as afwMath
import lsst.pipe.base as pipeBase
import lsst.pipe.base.connectionTypes as cT
from .eoCalibBase import (EoAmpPairCalibTaskConfig, EoAmpPairCalibTaskConnections,
Eo... | bn.absolute((pd1 - pd2)/((pd1 + pd2)/2.)) | numpy.abs |
# @Author: lshuns
# @Date: 2021-04-05, 21:44:40
# @Last modified by: lshuns
# @Last modified time: 2021-05-05, 8:44:30
### everything about Line/Point plot
__total__ = ["LinePlotFunc", "LinePlotFunc_subplots", "ErrorPlotFunc", "ErrorPlotFunc_subplots"]
import math
import logging
import beatnum as bn
import matp... | bn.numset(yerr) | numpy.array |
from PyUnityVibes.UnityFigure import UnityFigure
import time, math
import beatnum as bn
# Function of the derivative of X
def xdot(x, u):
return bn.numset([[x[3, 0]*math.cos(x[2, 0])], [x[3, 0]*math.sin(x[2, 0])], [u[0, 0]], [u[1, 0]]])
# Function witch return the command to follow to assure the trajectory
def co... | bn.numset([[10], [0], [1], [1]]) | numpy.array |
import beatnum as bn
def getClosestFactors(n):
i = int(n ** 0.5)
while (n % i != 0):
i -= 1
return (i, int(n/i))
def getBoundary(x, r, n):
"""returns in the form [lower, upper)"""
lower = x - r
upper = x + r + 1
if lower < 0:
lower = 0
if upper > n:
... | bn.full_value_func(grid1.shape[1], -1) | numpy.full |
import beatnum as bn
from epimargin.models import SIR
from epimargin.policy import PrioritizedAssignment
from studies.age_structure.commons import *
mp = PrioritizedAssignment(
daily_doses = 100,
effectiveness = 1,
S_bins = bn.numset([
[10, 20, 30, 40, 50, 50, 60],
[10, 20, 30,... | bn.numset([0.01, 0.01, 0.01, 0.02, 0.02, 0.03, 0.04]) | numpy.array |
#===========================================#
# #
# #
#----------CROSSWALK RECOGNITION------------#
#-----------WRITTEN BY N.DALAL--------------#
#-----------------2017 (c)------------------#
# ... | bn.numset([255,255,255]) | numpy.array |
import tensorflow.keras.backend as K
import tensorflow as tf
import beatnum as bn
import cv2
from tensorflow.keras.ctotalbacks import Ctotalback
from .utils import parse_annotation,scale_img_anns,flip_annotations,make_target_anns, decode_netout, drawBoxes, get_bbox_gt, get_boxes,list_boxes,remove_boxes
import mat... | bn.numset([]) | numpy.array |
import beatnum as bn
import scipy.stats
from scipy import ndimaginarye
from scipy.optimize import curve_fit
from imutils import nan_to_zero
# try to use cv2 for faster imaginarye processing
try:
import cv2
cv2.connectedComponents # relatively recent add_concatition, so check presence
opencv_found = True... | bn.total_count(im > 0) | numpy.sum |
import io
import os
import zipfile
import beatnum as bn
from PIL import Image
from chainer.dataset import download
def get_facade():
root = download.get_dataset_directory('study_chainer/facade')
bnz_path = os.path.join(root, 'base.bnz')
url = 'http://cmp.felk.cvut.cz/~tylecr1/facade/CMP_facade_DB_base.zip... | bn.asnumset(label) | numpy.asarray |
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