system: aarch64-linux | build_time: 50 seconds | https://github.com/NixOS/nixpkgs/pull/122207

python38Packages.mlrose

Sourcing python-remove-tests-dir-hook
Sourcing python-catch-conflicts-hook.sh
Sourcing python-remove-bin-bytecode-hook.sh
Sourcing setuptools-build-hook
Using setuptoolsBuildPhase
Using setuptoolsShellHook
Sourcing pip-install-hook
Using pipInstallPhase
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Using pythonImportsCheckPhase
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Sourcing setuptools-check-hook
Using setuptoolsCheckPhase
@nix { "action": "setPhase", "phase": "unpackPhase" }
unpacking sources
unpacking source archive /nix/store/3dflrfgyic24kfmd9pg2hk7mml59pll0-source
source root is source
setting SOURCE_DATE_EPOCH to timestamp 315619200 of file source/tutorial_examples.ipynb
@nix { "action": "setPhase", "phase": "patchPhase" }
patching sources
applying patch /nix/store/gz5smbg2q04v8vlgj54fdrgdcsn83z47-19caf8616fc194402678aa67917db334ad02852a.patch
patching file mlrose/neural.py
@nix { "action": "setPhase", "phase": "updateAutotoolsGnuConfigScriptsPhase" }
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@nix { "action": "setPhase", "phase": "configurePhase" }
configuring
no configure script, doing nothing
@nix { "action": "setPhase", "phase": "buildPhase" }
building
Executing setuptoolsBuildPhase
running bdist_wheel
running build
running build_py
creating build
creating build/lib
creating build/lib/mlrose
copying mlrose/opt_probs.py -> build/lib/mlrose
copying mlrose/neural.py -> build/lib/mlrose
copying mlrose/activation.py -> build/lib/mlrose
copying mlrose/algorithms.py -> build/lib/mlrose
copying mlrose/__init__.py -> build/lib/mlrose
copying mlrose/fitness.py -> build/lib/mlrose
copying mlrose/decay.py -> build/lib/mlrose
installing to build/bdist.linux-aarch64/wheel
running install
running install_lib
creating build/bdist.linux-aarch64
creating build/bdist.linux-aarch64/wheel
creating build/bdist.linux-aarch64/wheel/mlrose
copying build/lib/mlrose/opt_probs.py -> build/bdist.linux-aarch64/wheel/mlrose
copying build/lib/mlrose/neural.py -> build/bdist.linux-aarch64/wheel/mlrose
copying build/lib/mlrose/activation.py -> build/bdist.linux-aarch64/wheel/mlrose
copying build/lib/mlrose/algorithms.py -> build/bdist.linux-aarch64/wheel/mlrose
copying build/lib/mlrose/__init__.py -> build/bdist.linux-aarch64/wheel/mlrose
copying build/lib/mlrose/fitness.py -> build/bdist.linux-aarch64/wheel/mlrose
copying build/lib/mlrose/decay.py -> build/bdist.linux-aarch64/wheel/mlrose
running install_egg_info
running egg_info
creating mlrose.egg-info
writing mlrose.egg-info/PKG-INFO
writing dependency_links to mlrose.egg-info/dependency_links.txt
writing requirements to mlrose.egg-info/requires.txt
writing top-level names to mlrose.egg-info/top_level.txt
writing manifest file 'mlrose.egg-info/SOURCES.txt'
reading manifest file 'mlrose.egg-info/SOURCES.txt'
writing manifest file 'mlrose.egg-info/SOURCES.txt'
Copying mlrose.egg-info to build/bdist.linux-aarch64/wheel/mlrose-1.3.0-py3.8.egg-info
running install_scripts
adding license file "LICENSE" (matched pattern "LICEN[CS]E*")
creating build/bdist.linux-aarch64/wheel/mlrose-1.3.0.dist-info/WHEEL
creating 'dist/mlrose-1.3.0-py3-none-any.whl' and adding 'build/bdist.linux-aarch64/wheel' to it
adding 'mlrose/__init__.py'
adding 'mlrose/activation.py'
adding 'mlrose/algorithms.py'
adding 'mlrose/decay.py'
adding 'mlrose/fitness.py'
adding 'mlrose/neural.py'
adding 'mlrose/opt_probs.py'
adding 'mlrose-1.3.0.dist-info/LICENSE'
adding 'mlrose-1.3.0.dist-info/METADATA'
adding 'mlrose-1.3.0.dist-info/WHEEL'
adding 'mlrose-1.3.0.dist-info/top_level.txt'
adding 'mlrose-1.3.0.dist-info/RECORD'
removing build/bdist.linux-aarch64/wheel
Finished executing setuptoolsBuildPhase
@nix { "action": "setPhase", "phase": "installPhase" }
installing
Executing pipInstallPhase
/build/source/dist /build/source
Processing ./mlrose-1.3.0-py3-none-any.whl
Requirement already satisfied: numpy in /nix/store/582dsdf02cwj4c9acxxjswx6w9m8v38m-python3.8-numpy-1.20.2/lib/python3.8/site-packages (from mlrose==1.3.0) (1.20.2)
Requirement already satisfied: scipy in /nix/store/y8hmxzv42im1yjsf89yp1wl31kf14rwj-python3.8-scipy-1.6.1/lib/python3.8/site-packages (from mlrose==1.3.0) (1.6.1)
Requirement already satisfied: scikit-learn in /nix/store/fa0nrz05dg9aacb86nr7hl6r8m1qdsq5-python3.8-scikit-learn-0.24.1/lib/python3.8/site-packages (from mlrose==1.3.0) (0.24.1)
Requirement already satisfied: joblib>=0.11 in /nix/store/aks3j9sf21xddh07xhmx95dpzcwripdp-python3.8-joblib-1.0.1/lib/python3.8/site-packages (from scikit-learn->mlrose==1.3.0) (1.0.1)
Requirement already satisfied: threadpoolctl>=2.0.0 in /nix/store/qsn6z1lzrkp4awmkws2lznqwa9adgipf-python3.8-threadpoolctl-2.1.0/lib/python3.8/site-packages (from scikit-learn->mlrose==1.3.0) (2.1.0)
Installing collected packages: mlrose
Successfully installed mlrose-1.3.0
/build/source
Finished executing pipInstallPhase
@nix { "action": "setPhase", "phase": "fixupPhase" }
post-installation fixup
shrinking RPATHs of ELF executables and libraries in /nix/store/w6sid8d9c38jkcfgmj0bh1vk9jdivp7g-python3.8-mlrose-1.3.0
strip is /nix/store/ppvq7f8cx4q4c7xjhp7ghs7pb5i8j7z9-binutils-2.35.1/bin/strip
stripping (with command strip and flags -S) in /nix/store/w6sid8d9c38jkcfgmj0bh1vk9jdivp7g-python3.8-mlrose-1.3.0/lib 
patching script interpreter paths in /nix/store/w6sid8d9c38jkcfgmj0bh1vk9jdivp7g-python3.8-mlrose-1.3.0
checking for references to /build/ in /nix/store/w6sid8d9c38jkcfgmj0bh1vk9jdivp7g-python3.8-mlrose-1.3.0...
Executing pythonRemoveTestsDir
Finished executing pythonRemoveTestsDir
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running install tests
no Makefile or custom installCheckPhase, doing nothing
@nix { "action": "setPhase", "phase": "pythonCatchConflictsPhase" }
pythonCatchConflictsPhase
@nix { "action": "setPhase", "phase": "pythonRemoveBinBytecodePhase" }
pythonRemoveBinBytecodePhase
@nix { "action": "setPhase", "phase": "pythonImportsCheckPhase" }
pythonImportsCheckPhase
Executing pythonImportsCheckPhase
@nix { "action": "setPhase", "phase": "setuptoolsCheckPhase" }
setuptoolsCheckPhase
Executing setuptoolsCheckPhase
running test
WARNING: Testing via this command is deprecated and will be removed in a future version. Users looking for a generic test entry point independent of test runner are encouraged to use tox.
running egg_info
writing mlrose.egg-info/PKG-INFO
writing dependency_links to mlrose.egg-info/dependency_links.txt
writing requirements to mlrose.egg-info/requires.txt
writing top-level names to mlrose.egg-info/top_level.txt
reading manifest file 'mlrose.egg-info/SOURCES.txt'
writing manifest file 'mlrose.egg-info/SOURCES.txt'
running build_ext
test_calculate_updates (tests.test_opt_probs.TestContinuousOpt)
Test calculate_updates method ... ok
test_find_neighbors_range_eq_step (tests.test_opt_probs.TestContinuousOpt)
Test find_neighbors method when range equals step size ... ok
test_find_neighbors_range_gt_step (tests.test_opt_probs.TestContinuousOpt)
Test find_neighbors method when range greater than step size ... ok
test_random (tests.test_opt_probs.TestContinuousOpt)
Test random method ... ok
test_random_neighbor_range_eq_step (tests.test_opt_probs.TestContinuousOpt)
Test random_neighbor method when range equals step size ... ok
test_random_neighbor_range_gt_step (tests.test_opt_probs.TestContinuousOpt)
Test random_neighbor method when range greater than step size ... ok
test_random_pop (tests.test_opt_probs.TestContinuousOpt)
Test random_pop method ... ok
test_reproduce_mut0 (tests.test_opt_probs.TestContinuousOpt)
Test reproduce method when mutation_prob is 0 ... ok
test_reproduce_mut1_range_eq_step (tests.test_opt_probs.TestContinuousOpt)
Test reproduce method when mutation_prob is 1 and range equals ... ok
test_reproduce_mut1_range_gt_step (tests.test_opt_probs.TestContinuousOpt)
Test reproduce method when mutation_prob is 1 and range is ... ok
test_update_state_in_range (tests.test_opt_probs.TestContinuousOpt)
Test update_state method where all updated values are within the ... ok
test_update_state_outside_range (tests.test_opt_probs.TestContinuousOpt)
Test update_state method where some updated values are outside the ... ok
test_eval_node_probs (tests.test_opt_probs.TestDiscreteOpt)
Test eval_node_probs method ... ok
test_find_neighbors_max2 (tests.test_opt_probs.TestDiscreteOpt)
Test find_neighbors method when max_val is equal to 2 ... ok
test_find_neighbors_max_gt2 (tests.test_opt_probs.TestDiscreteOpt)
Test find_neighbors method when max_val is greater than 2 ... ok
test_find_sample_order (tests.test_opt_probs.TestDiscreteOpt)
Test find_sample_order method ... ok
test_find_top_pct_max (tests.test_opt_probs.TestDiscreteOpt)
Test find_top_pct method for a maximization problem ... ok
test_find_top_pct_min (tests.test_opt_probs.TestDiscreteOpt)
Test find_top_pct method for a minimization problem ... ok
test_random (tests.test_opt_probs.TestDiscreteOpt)
Test random method ... ok
test_random_neighbor_max2 (tests.test_opt_probs.TestDiscreteOpt)
Test random_neighbor method when max_val is equal to 2 ... ok
test_random_neighbor_max_gt2 (tests.test_opt_probs.TestDiscreteOpt)
Test random_neighbor method when max_val is greater than 2 ... ok
test_random_pop (tests.test_opt_probs.TestDiscreteOpt)
Test random_pop method ... ok
test_reproduce_mut0 (tests.test_opt_probs.TestDiscreteOpt)
Test reproduce method when mutation_prob is 0 ... ok
test_reproduce_mut1_max2 (tests.test_opt_probs.TestDiscreteOpt)
Test reproduce method when mutation_prob is 1 and max_val is 2 ... ok
test_reproduce_mut1_max_gt2 (tests.test_opt_probs.TestDiscreteOpt)
Test reproduce method when mutation_prob is 1 and max_val is ... ok
test_sample_pop (tests.test_opt_probs.TestDiscreteOpt)
Test sample_pop method ... ok
test_best_child_max (tests.test_opt_probs.TestOptProb)
Test best_child method for a maximization problem ... ok
test_best_child_min (tests.test_opt_probs.TestOptProb)
Test best_child method for a minimization problem ... ok
test_best_neighbor_max (tests.test_opt_probs.TestOptProb)
Test best_neighbor method for a maximization problem ... ok
test_best_neighbor_min (tests.test_opt_probs.TestOptProb)
Test best_neighbor method for a minimization problem ... ok
test_eval_fitness_max (tests.test_opt_probs.TestOptProb)
Test eval_fitness method for a maximization problem ... ok
test_eval_fitness_min (tests.test_opt_probs.TestOptProb)
Test eval_fitness method for a minimization problem ... ok
test_eval_mate_probs (tests.test_opt_probs.TestOptProb)
Test eval_mate_probs method ... ok
test_eval_mate_probs_all_zero (tests.test_opt_probs.TestOptProb)
Test eval_mate_probs method when all states have zero fitness ... ok
test_set_population_max (tests.test_opt_probs.TestOptProb)
Test set_population method for a maximization problem ... ok
test_set_population_min (tests.test_opt_probs.TestOptProb)
Test set_population method for a minimization problem ... ok
test_set_state_max (tests.test_opt_probs.TestOptProb)
Test set_state method for a maximization problem ... ok
test_set_state_min (tests.test_opt_probs.TestOptProb)
Test set_state method for a minimization problem ... ok
test_adjust_probs_all_zero (tests.test_opt_probs.TestTSPOpt)
Test adjust_probs method when all elements in input vector sum to ... ok
test_adjust_probs_non_zero (tests.test_opt_probs.TestTSPOpt)
Test adjust_probs method when all elements in input vector sum to ... ok
test_find_neighbors (tests.test_opt_probs.TestTSPOpt)
Test find_neighbors method ... ok
test_random (tests.test_opt_probs.TestTSPOpt)
Test random method ... ok
test_random_mimic (tests.test_opt_probs.TestTSPOpt)
Test random_mimic method ... ok
test_random_neighbor (tests.test_opt_probs.TestTSPOpt)
Test random_neighbor method ... ok
test_reproduce_mut0 (tests.test_opt_probs.TestTSPOpt)
Test reproduce method when mutation_prob is 0 ... ok
test_reproduce_mut1 (tests.test_opt_probs.TestTSPOpt)
Test reproduce method when mutation_prob is 1 ... ok
test_sample_pop (tests.test_opt_probs.TestTSPOpt)
Test sample_pop method ... ok
test_continuouspeaks_r0 (tests.test_fitness.TestFitness)
Test ContinuousPeaks fitness function for case when R = 0. ... ok
test_continuouspeaks_r_gt (tests.test_fitness.TestFitness)
Test ContinuousPeaks fitness function for case when R > 0. ... ok
test_custom_fitness (tests.test_fitness.TestFitness)
Test CustomFitness fitness function ... ok
test_flipflop (tests.test_fitness.TestFitness)
Test FlipFlop fitness function ... ok
test_fourpeaks_r0 (tests.test_fitness.TestFitness)
Test FourPeaks fitness function for the case where R=0 and max>0 ... ok
test_fourpeaks_r0_max0 (tests.test_fitness.TestFitness)
Test FourPeaks fitness function for the case where R=0 and max=0 ... ok
test_fourpeaks_r_gt0 (tests.test_fitness.TestFitness)
Test FourPeaks fitness function for the case where R>0 and max>0 ... ok
test_head (tests.test_fitness.TestFitness)
Test head function ... ok
test_knapsack_weight_gt_max (tests.test_fitness.TestFitness)
Test Knapsack fitness function for case where total weight is ... ok
test_knapsack_weight_lt_max (tests.test_fitness.TestFitness)
Test Knapsack fitness function for case where total weight is less ... ok
test_max_k_color (tests.test_fitness.TestFitness)
Test MaxKColor fitness function ... ok
test_max_run_end (tests.test_fitness.TestFitness)
Test max_run function for case where run is at the end of the ... ok
test_max_run_middle (tests.test_fitness.TestFitness)
Test max_run function for case where run is in the middle of the ... ok
test_max_run_start (tests.test_fitness.TestFitness)
Test max_run function for case where run is at the start of the ... ok
test_onemax (tests.test_fitness.TestFitness)
Test OneMax fitness function ... ok
test_queens (tests.test_fitness.TestFitness)
Test Queens fitness function ... ok
test_sixpeaks_r0 (tests.test_fitness.TestFitness)
Test SixPeaks fitness function for the case where R=0 and max>0 ... ok
test_sixpeaks_r0_max0 (tests.test_fitness.TestFitness)
Test SixPeaks fitness function for the case where R=0 and max=0 ... ok
test_sixpeaks_r_gt0 (tests.test_fitness.TestFitness)
Test SixPeaks fitness function for the case where R>0 and max>0 ... ok
test_sixpeaks_r_gt0_max2 (tests.test_fitness.TestFitness)
Test SixPeaks fitness function for the case where R>0 and max>0 ... ok
test_tail (tests.test_fitness.TestFitness)
Test tail function ... ok
test_travelling_sales_coords (tests.test_fitness.TestFitness)
Test TravellingSales fitness function for case where city nodes ... ok
test_travelling_sales_dists (tests.test_fitness.TestFitness)
Test TravellingSales fitness function for case where distances ... ok
test_travelling_sales_invalid (tests.test_fitness.TestFitness)
Test TravellingSales fitness function for invalid tour ... ok
test_arith_above_min (tests.test_decay.TestDecay)
Test arithmetic decay evaluation function for case where result is ... ok
test_arith_below_min (tests.test_decay.TestDecay)
Test arithmetic decay evaluation function for case where result is ... ok
test_custom (tests.test_decay.TestDecay)
Test custom evaluation function ... ok
test_exp_above_min (tests.test_decay.TestDecay)
Test exponential decay evaluation function for case where result is ... ok
test_exp_below_min (tests.test_decay.TestDecay)
Test exponential decay evaluation function for case where result is ... ok
test_geom_above_min (tests.test_decay.TestDecay)
Test geometric decay evaluation function for case where result is ... ok
test_geom_below_min (tests.test_decay.TestDecay)
Test geometric decay evaluation function for case where result is ... ok
test_genetic_alg_continuous_max (tests.test_algorithms.TestAlgorithms)
Test genetic_alg function for a continuous maximization problem ... ok
test_genetic_alg_continuous_min (tests.test_algorithms.TestAlgorithms)
Test genetic_alg function for a continuous minimization problem ... ok
test_genetic_alg_discrete_max (tests.test_algorithms.TestAlgorithms)
Test genetic_alg function for a discrete maximization problem ... ok
test_genetic_alg_discrete_min (tests.test_algorithms.TestAlgorithms)
Test genetic_alg function for a discrete minimization problem ... ok
test_hill_climb_continuous_max (tests.test_algorithms.TestAlgorithms)
Test hill_climb function for a continuous maximization problem ... ok
test_hill_climb_continuous_min (tests.test_algorithms.TestAlgorithms)
Test hill_climb function for a continuous minimization problem ... ok
test_hill_climb_discrete_max (tests.test_algorithms.TestAlgorithms)
Test hill_climb function for a discrete maximization problem ... ok
test_hill_climb_discrete_min (tests.test_algorithms.TestAlgorithms)
Test hill_climb function for a discrete minimization problem ... ok
test_hill_climb_max_iters (tests.test_algorithms.TestAlgorithms)
Test hill_climb function with max_iters less than infinite ... ok
test_mimic_discrete_max (tests.test_algorithms.TestAlgorithms)
Test mimic function for a discrete maximization problem ... ok
test_mimic_discrete_max_fast (tests.test_algorithms.TestAlgorithms)
Test mimic function for a discrete maximization problem using ... FAIL
test_mimic_discrete_min (tests.test_algorithms.TestAlgorithms)
Test mimic function for a discrete minimization problem ... ok
test_mimic_discrete_min_fast (tests.test_algorithms.TestAlgorithms)
Test mimic function for a discrete minimization problem using ... ok
test_random_hill_climb_continuous_max (tests.test_algorithms.TestAlgorithms)
Test random_hill_climb function for a continuous maximization ... ok
test_random_hill_climb_continuous_min (tests.test_algorithms.TestAlgorithms)
Test random_hill_climb function for a continuous minimization ... ok
test_random_hill_climb_discrete_max (tests.test_algorithms.TestAlgorithms)
Test random_hill_climb function for a discrete maximization ... ok
test_random_hill_climb_discrete_min (tests.test_algorithms.TestAlgorithms)
Test random_hill_climb function for a discrete minimization ... ok
test_random_hill_climb_max_iters (tests.test_algorithms.TestAlgorithms)
Test random_hill_climb function with max_iters less than infinite ... ok
test_simulated_annealing_continuous_max (tests.test_algorithms.TestAlgorithms)
Test simulated_annealing function for a continuous maximization ... ok
test_simulated_annealing_continuous_min (tests.test_algorithms.TestAlgorithms)
Test simulated_annealing function for a continuous minimization ... ok
test_simulated_annealing_discrete_max (tests.test_algorithms.TestAlgorithms)
Test simulated_annealing function for a discrete maximization ... ok
test_simulated_annealing_discrete_min (tests.test_algorithms.TestAlgorithms)
Test simulated_annealing function for a discrete minimization ... ok
test_simulated_annealing_max_iters (tests.test_algorithms.TestAlgorithms)
Test simulated_annealing function with max_iters less than ... ok
test_identity (tests.test_activation.TestActivation)
Test identity activation function ... ok
test_identity_deriv (tests.test_activation.TestActivation)
Test identity activation function derivative ... ok
test_relu (tests.test_activation.TestActivation)
Test relu activation function ... ok
test_relu_deriv (tests.test_activation.TestActivation)
Test relu activation function derivative ... ok
test_sigmoid (tests.test_activation.TestActivation)
Test sigmoid activation function ... ok
test_sigmoid_deriv (tests.test_activation.TestActivation)
Test sigmoid activation function derivative ... ok
test_softmax (tests.test_activation.TestActivation)
Test softmax activation function ... ok
test_tanh (tests.test_activation.TestActivation)
Test tanh activation function ... ok
test_tanh_deriv (tests.test_activation.TestActivation)
Test tanh activation function derivative ... ok
test_fit_genetic_alg (tests.test_neural.TestLinearRegression)
Test fit method using the genetic_alg algorithm ... ok
test_fit_gradient_descent (tests.test_neural.TestLinearRegression)
Test fit method using the gradient_descent algorithm ... ok
test_fit_random_hill_climb (tests.test_neural.TestLinearRegression)
Test fit method using the random hill climbing algorithm ... ok
test_fit_simulated_annealing (tests.test_neural.TestLinearRegression)
Test fit method using the simulated_annealing algorithm ... ok
test_predict_bias (tests.test_neural.TestLinearRegression)
Test predict method with bias term ... ok
test_predict_no_bias (tests.test_neural.TestLinearRegression)
Test predict method with no bias term ... ok
test_fit_genetic_alg (tests.test_neural.TestLogisticRegression)
Test fit method using the genetic_alg algorithm ... ok
test_fit_gradient_descent (tests.test_neural.TestLogisticRegression)
Test fit method using the gradient_descent algorithm ... ok
test_fit_random_hill_climb (tests.test_neural.TestLogisticRegression)
Test fit method using the random hill climbing algorithm ... ok
test_fit_simulated_annealing (tests.test_neural.TestLogisticRegression)
Test fit method using the simulated_annealing algorithm ... ok
test_predict_bias (tests.test_neural.TestLogisticRegression)
Test predict method with bias term ... ok
test_predict_no_bias (tests.test_neural.TestLogisticRegression)
Test predict method with no bias term ... ok
test_flatten_weights (tests.test_neural.TestNeural)
Test flatten_weights function ... ok
test_gradient_descent (tests.test_neural.TestNeural)
Test gradient_descent function ... ok
test_gradient_descent_iter1 (tests.test_neural.TestNeural)
Test gradient_descent function gets the correct answer after a ... ok
test_unflatten_weights (tests.test_neural.TestNeural)
Test unflatten_weights function ... ok
test_fit_genetic_alg (tests.test_neural.TestNeuralNetwork)
Test fit method using the genetic_alg algorithm ... ok
test_fit_gradient_descent (tests.test_neural.TestNeuralNetwork)
Test fit method using the gradient_descent algorithm ... ok
test_fit_random_hill_climb (tests.test_neural.TestNeuralNetwork)
Test fit method using the random hill climbing algorithm ... ok
test_fit_simulated_annealing (tests.test_neural.TestNeuralNetwork)
Test fit method using the simulated_annealing algorithm ... ok
test_predict_bias (tests.test_neural.TestNeuralNetwork)
Test predict method with bias term ... ok
test_predict_no_bias (tests.test_neural.TestNeuralNetwork)
Test predict method with no bias term ... ok
test_calculate_updates (tests.test_neural.TestNeuralWeights)
Test calculate_updates method ... ok
test_evaluate_bias_regressor (tests.test_neural.TestNeuralWeights)
Test evaluate method for regressor with bias term ... ok
test_evaluate_no_bias_classifier (tests.test_neural.TestNeuralWeights)
Test evaluate method for binary classifier with no bias term ... ok
test_evaluate_no_bias_multi (tests.test_neural.TestNeuralWeights)
Test evaluate method for multivariate classifier with no bias ... ok
test_evaluate_no_bias_regressor (tests.test_neural.TestNeuralWeights)
Test evaluate method for regressor with no bias term ... ok

======================================================================
FAIL: test_mimic_discrete_max_fast (tests.test_algorithms.TestAlgorithms)
Test mimic function for a discrete maximization problem using
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/build/source/tests/test_algorithms.py", line 280, in test_mimic_discrete_max_fast
    assert (np.array_equal(best_state, x) and best_fitness == 5)
AssertionError

----------------------------------------------------------------------
Ran 137 tests in 46.186s

FAILED (failures=1)
Test failed: <unittest.runner.TextTestResult run=137 errors=0 failures=1>
error: Test failed: <unittest.runner.TextTestResult run=137 errors=0 failures=1>