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"""File which contains data for testing regression with matlab script.""" |
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from unittest import TestCase |
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from unittest.mock import patch |
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import networkx as nx |
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import numpy as np |
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from grortir.main.model.processes.factories.calls_process_factory import \ |
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CallsProcessFactory |
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from grortir.main.optimizers.grouped_optimizer import GroupedOptimizer |
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from grortir.main.optimizers.grouping_strategy import GroupingStrategy |
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from grortir.main.pso.calls_optimization_strategy import \ |
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CallsOptimizationStrategy |
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from grortir.main.pso.pso_algorithm import PsoAlgorithm |
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class TestLinearRVT(TestCase): |
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"""Test class for regression.""" |
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def _regression_mocked(self, rand_mock, max_calls): |
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"""Test use some mocked values of random function from one known example |
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from matlab. Because we set the same values in rand function, we should |
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have equal values as in matlab. This is working example for 3 particles, |
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5 stages, 2 dimensions when all stages are in one group. |
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""" |
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prepare_rand_mock(rand_mock) |
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how_many_particles = 3 |
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max_calls = max_calls |
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calls_factory = CallsProcessFactory("linear", 5, |
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max_calls, |
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[0, 0]) |
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process = calls_factory.construct_process() |
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ordered_stages = nx.topological_sort(process) |
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grouping_strategy = GroupingStrategy(ordered_stages) |
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grouping_strategy.define_group(ordered_stages) |
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optimization_startegy = CallsOptimizationStrategy() |
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pso_algortihm = PsoAlgorithm(process, grouping_strategy, |
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optimization_startegy, |
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how_many_particles) |
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optimizer = GroupedOptimizer(process, grouping_strategy, pso_algortihm) |
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optimizer.optimize_process() |
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for index, stage in enumerate(ordered_stages): |
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self.assertAlmostEqual(stage.final_quality, |
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EXPECTED_RESULTS_X2_MATLAB[max_calls][index], |
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7) |
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@patch('grortir.main.pso.velocity_calculator.np.random.rand') |
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def test_matlab_regression_x2_300(self, rand_mock): |
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"""Test case for max_calls = 300.""" |
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self._regression_mocked(rand_mock, 300) |
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@patch('grortir.main.pso.velocity_calculator.np.random.rand') |
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def test_matlab_regression_x2_102(self, rand_mock): |
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"""Test case for max_calls = 102.""" |
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self._regression_mocked(rand_mock, 102) |
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EXPECTED_RESULTS_X2_MATLAB = {102: [ |
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0.196381073803784, |
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0.182060227702233, |
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0.077236432031289, |
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0.044953250296990, |
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0.121949294446318 |
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], 300: [ |
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0.175906072353589, |
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0.174734347239612, |
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0.042669220710921, |
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0.077825241269615, |
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0.175914451614580 |
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]} |
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def prepare_rand_mock(rand_mock): |
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"""Rand mock for: |
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3 particles |
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5 stages |
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2 dimensions |
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""" |
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returned_values = [ # rand_vec - positions particle 1 |
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[0.076308289, 0.909593528], |
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[0.723465178, 0.93120602], |
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[0.501120464, 0.9501295], |
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[0.499882501, 0.909128375], |
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[0.380941133, 0.750409859], |
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# rand_vec - initial_velocities particle 1 |
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[0.20484909, 0.719324123], |
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[0.477401155, 0.180451619], |
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[0.768647507, 0.426453573], |
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[0.276049048, 0.414885978], |
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[0.657399463, 0.709394394], |
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# rand_vec - positions particle 2 |
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[0.779918792, 0.213385354], |
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[0.977989512, 0.024899228], |
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[0.072051133, 0.230302879], |
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[0.679229996, 0.133169446], |
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[0.065936347, 0.669013241], |
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# rand_vec - initial_velocities particle 2 |
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[0.490765889, 0.412991829], |
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[0.365890386, 0.741118873], |
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[0.313994677, 0.634379869], |
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[0.452842933, 0.001426881], |
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[0.370351083, 0.524345597], |
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# rand_vec - positions particle 3 |
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[0.438409231, 0.452123962], |
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[0.53849587, 0.600548917], |
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[0.26843898, 0.548489919], |
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[0.803739036, 0.523412581], |
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[0.288145599, 0.46775286], |
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# rand_vec - initial_velocities particle 3 |
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[0.372384689, 0.906423269], |
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[0.837917994, 0.422374044], |
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[0.572625333, 0.522906201], |
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[0.352978366, 0.092262346], |
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[0.459092978, 0.696160464], |
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# rand_1 |
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0.955468323002926, |
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# rand_2 |
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0.682913854375418, |
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# etc. |
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0.053128690672958, |
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0.308852684863797, |
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0.592594687323373, |
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0.235120407257464, |
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0.964970999536127, |
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0.945048223792794, |
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0.848400880837689, |
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0.472323996288402, |
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0.841476714898397, |
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0.131110642347914, |
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0.308733657297835, |
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0.462996394154417, |
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0.741847200683467, |
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0.485825228708897, |
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0.136876118797451, |
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0.343536529704358, |
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0.324426169672443, |
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0.300418904318040, |
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0.165501400465787, |
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0.414901772573252, |
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0.448120657502723, |
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0.774900375814017, |
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0.796390700782548, |
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0.522390128001612, |
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0.460630296163277, |
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0.778213601543897, |
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0.887288951852735, |
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0.674918769866788, |
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0.800479048998464, |
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0.939111353732185, |
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0.040655809436686, |
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0.875671724870083, |
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0.276563072451134, |
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0.475764499424244, |
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0.796760956931902, |
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0.717242232275230, |
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0.147147571941693, |
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0.658748258954145, |
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0.069252070009835, |
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0.357070628352879, |
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0.812829550163706, |
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0.427704833027551, |
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0.599854437543446, |
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0.728161283147134, |
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0.821227608306559, |
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0.760515119980283, |
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0.007143275278998, |
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0.420256833672535, |
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0.463136218038147, |
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0.055499503112723, |
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0.541442132095220, |
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0.607770751443867, |
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0.828453194996125, |
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0.941809268191449, |
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0.128147854002733, |
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0.230430674410219, |
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0.659158397070561, |
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0.132473988816749, |
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0.224078636946319, |
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0.574862587589149, |
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0.169523723566209, |
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0.782230151323778, |
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0.856975626111760, |
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0.033674204502848, |
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0.532644804943674, |
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0.796951357443564, |
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0.975139681157116, |
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0.274258593194421, |
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0.169101063365383, |
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0.876700930181635, |
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0.909182463760849, |
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0.197532889467157, |
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0.441529742702640, |
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0.719232141692337, |
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0.845345158763973, |
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0.168275305367244, |
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0.664968962904761, |
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0.807835459296069, |
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0.549714120800727, |
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0.164716658779013, |
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0.035528804830363, |
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0.281533817848494, |
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0.807870846453552, |
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0.044766260845139, |
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0.008216505039312, |
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0.361616647712057, |
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0.063622285698552, |
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0.149486303324230, |
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0.023190368099362, |
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0.524719836768632, |
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0.696695902189413, |
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0.427053493013728, |
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0.134570458644688, |
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0.331357210962406, |
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0.590345854306335, |
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0.940661393396388, |
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0.992557719172640, |
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0.241602916653850, |
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0.010579906938346, |
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0.830640325993805, |
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0.926612937770057, |
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0.458603479767969, |
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0.771442344563682, |
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0.866199034084391, |
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0.609614798334559, |
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0.872627183144187, |
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0.023903026142331, |
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0.271595220259564, |
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0.277219582694295, |
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0.120632428306158, |
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0.910713454288238, |
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0.030439266665623, |
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0.672561029522113, |
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0.071339687257207, |
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0.360780493785221, |
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0.418099542677566, |
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0.181404289057367, |
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0.521014103282176, |
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0.534991760927916, |
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0.317043881936196, |
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0.737088059552291, |
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0.160202410619170, |
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0.192508218959855, |
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0.354511018045606, |
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0.378376133431419, |
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0.206285856500654, |
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0.918709205142268, |
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0.828093569546948, |
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0.106876744256641, |
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0.369485915660384, |
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0.232671095631974, |
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0.451078602950542, |
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0.276317186210793, |
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0.501806891118423, |
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0.922603153077957, |
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0.382511138929834, |
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0.650128328628633, |
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0.595621113020374, |
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0.751953561142208, |
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0.061665330169869, |
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0.744823673681810, |
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0.946275927172428, |
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0.603559551695486, |
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0.287579942119900, |
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0.672369218429286, |
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0.712048786781395, |
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0.656450286538602, |
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0.146930315693544, |
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0.973475568269701, |
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0.955383451820879, |
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0.424625532795641, |
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0.593637329408872, |
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0.039628573866894, |
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0.988634334561939, |
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0.818744992623299, |
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0.636502342429667, |
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0.761084744221686, |
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0.188029928582586, |
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0.307654590092852, |
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0.246393644285721, |
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0.596049120125150, |
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0.091904852163772, |
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0.895609985214942, |
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0.462275942130728, |
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0.444812364954379, |
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0.104711303573244, |
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0.536806445779076, |
|
593
|
|
|
0.618185702219458, |
|
594
|
|
|
0.668866801761036, |
|
595
|
|
|
0.926538709044051, |
|
596
|
|
|
0.467508678029278, |
|
597
|
|
|
0.582878176454622, |
|
598
|
|
|
0.226539656503770, |
|
599
|
|
|
0.242398242505033, |
|
600
|
|
|
0.522112194722591, |
|
601
|
|
|
0.229204951410235, |
|
602
|
|
|
0.030252785430061, |
|
603
|
|
|
0.368407959481347, |
|
604
|
|
|
0.749945144136553, |
|
605
|
|
|
0.277070182795515, |
|
606
|
|
|
0.862703938488081, |
|
607
|
|
|
0.702502384733204, |
|
608
|
|
|
0.653319109148049, |
|
609
|
|
|
0.892483140903137, |
|
610
|
|
|
0.073811030749940, |
|
611
|
|
|
0.178765399504983, |
|
612
|
|
|
0.909270222459388, |
|
613
|
|
|
0.907037376819791, |
|
614
|
|
|
0.078267255898490, |
|
615
|
|
|
0.774231552555221, |
|
616
|
|
|
0.015432415436891, |
|
617
|
|
|
0.135235553368546, |
|
618
|
|
|
0.109760573693710, |
|
619
|
|
|
0.293995577818383, |
|
620
|
|
|
0.388268420643610, |
|
621
|
|
|
0.910873864270862, |
|
622
|
|
|
0.436397812772955, |
|
623
|
|
|
0.123849077393590, |
|
624
|
|
|
0.272348747150734, |
|
625
|
|
|
0.006376828101283, |
|
626
|
|
|
0.028049402896190, |
|
627
|
|
|
0.431068321456428, |
|
628
|
|
|
0.512188268191776, |
|
629
|
|
|
0.249961583279100, |
|
630
|
|
|
0.379892416692459, |
|
631
|
|
|
0.103368972691539, |
|
632
|
|
|
0.658821561774462, |
|
633
|
|
|
0.392605570467657, |
|
634
|
|
|
0.161525599474659, |
|
635
|
|
|
0.497393631286220, |
|
636
|
|
|
0.208374839752940, |
|
637
|
|
|
0.292129277966286, |
|
638
|
|
|
0.124170432861418, |
|
639
|
|
|
0.780730491164767, |
|
640
|
|
|
0.279315228275671, |
|
641
|
|
|
0.955676655905381, |
|
642
|
|
|
0.405431910896856, |
|
643
|
|
|
0.155194491682113, |
|
644
|
|
|
0.705212968993427, |
|
645
|
|
|
0.733558148258664, |
|
646
|
|
|
0.881319646023381, |
|
647
|
|
|
0.131512475929842, |
|
648
|
|
|
0.789885959077657, |
|
649
|
|
|
0.859759087461651, |
|
650
|
|
|
0.304518295195883, |
|
651
|
|
|
0.454482181611214, |
|
652
|
|
|
0.619641959041911, |
|
653
|
|
|
0.245513143317838, |
|
654
|
|
|
0.871355919631592, |
|
655
|
|
|
0.699194254911087, |
|
656
|
|
|
0.856683045869332, |
|
657
|
|
|
0.449915049918563, |
|
658
|
|
|
0.518998362932756, |
|
659
|
|
|
0.194254445030116, |
|
660
|
|
|
0.314024381595863, |
|
661
|
|
|
0.729512159519921, |
|
662
|
|
|
0.959007778167720, |
|
663
|
|
|
0.152102868420930, |
|
664
|
|
|
0.050643527733202, |
|
665
|
|
|
0.067452674119625, |
|
666
|
|
|
0.435471768821968, |
|
667
|
|
|
0.792671277316913, |
|
668
|
|
|
0.224877270039349, |
|
669
|
|
|
0.477132071395185, |
|
670
|
|
|
0.515402183663472, |
|
671
|
|
|
0.837702398077169, |
|
672
|
|
|
0.164033206983383, |
|
673
|
|
|
0.014718606080760, |
|
674
|
|
|
0.506655032325643, |
|
675
|
|
|
0.355245916780601, |
|
676
|
|
|
0.292165375856786, |
|
677
|
|
|
0.772237097456584, |
|
678
|
|
|
0.683467071380522, |
|
679
|
|
|
0.083937147680062, |
|
680
|
|
|
0.548103362726367, |
|
681
|
|
|
0.797844619110595, |
|
682
|
|
|
0.909684337475206, |
|
683
|
|
|
1.849190299395564e-04, |
|
684
|
|
|
0.807550098685804, |
|
685
|
|
|
0.043247927660589, |
|
686
|
|
|
0.682120580410576, |
|
687
|
|
|
0.598007103650569, |
|
688
|
|
|
0.952016292239996, |
|
689
|
|
|
0.631879092240196, |
|
690
|
|
|
0.069939064084080, |
|
691
|
|
|
0.670397983148165, |
|
692
|
|
|
0.254920416648672, |
|
693
|
|
|
0.831943993534743, |
|
694
|
|
|
0.031462089910604, |
|
695
|
|
|
0.324135823771549, |
|
696
|
|
|
0.676435886980024, |
|
697
|
|
|
0.155634800139984, |
|
698
|
|
|
0.646272009255702, |
|
699
|
|
|
0.697224805278189, |
|
700
|
|
|
0.733777664963868, |
|
701
|
|
|
0.875335192151078, |
|
702
|
|
|
0.413166116051979, |
|
703
|
|
|
0.142482973491241, |
|
704
|
|
|
0.260310930391146, |
|
705
|
|
|
0.389685401442653, |
|
706
|
|
|
0.054577570176633, |
|
707
|
|
|
0.708548829749348, |
|
708
|
|
|
0.063010647774122, |
|
709
|
|
|
0.057708757228460, |
|
710
|
|
|
0.932499537221799, |
|
711
|
|
|
0.806245878340841, |
|
712
|
|
|
0.253681046813631, |
|
713
|
|
|
0.341708091806300, |
|
714
|
|
|
0.825919699801219, |
|
715
|
|
|
0.619235464658352, |
|
716
|
|
|
0.264917616209675, |
|
717
|
|
|
0.449019195939970, |
|
718
|
|
|
0.855559587316900, |
|
719
|
|
|
6.913526320485586e-04, |
|
720
|
|
|
0.992393866454483, |
|
721
|
|
|
0.565933533985480, |
|
722
|
|
|
0.182020076790290, |
|
723
|
|
|
0.800192805760516, |
|
724
|
|
|
0.076195188027430, |
|
725
|
|
|
0.410000079369867, |
|
726
|
|
|
0.573132263268180 |
|
727
|
|
|
] |
|
728
|
|
|
|
|
729
|
|
|
returned_values_arrays = [] |
|
730
|
|
|
for row in returned_values: |
|
731
|
|
|
returned_values_arrays.append(np.array(row)) |
|
732
|
|
|
|
|
733
|
|
|
rand_mock.side_effect = returned_values_arrays |
|
734
|
|
|
|
qbahn /
grortir
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This can be caused by one of the following:
1. Missing Dependencies
This error could indicate a configuration issue of Pylint. Make sure that your libraries are available by adding the necessary commands.
2. Missing __init__.py files
This error could also result from missing
__init__.pyfiles in your module folders. Make sure that you place one file in each sub-folder.