=================================== FAILURES ===================================
_____________________ benchmarking/tests/test_evaluator.py _____________________
[gw0] darwin -- Python 3.7.12 /Users/runner/hostedtoolcache/Python/3.7.12/x64/bin/python
worker 'gw0' crashed while running 'benchmarking/tests/test_evaluator.py::test_plots'
=============================== warnings summary ===============================
../../../../hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/coverage/inorout.py:472
../../../../hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/coverage/inorout.py:472
../../../../hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/coverage/inorout.py:472
../../../../hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/coverage/inorout.py:472
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/coverage/inorout.py:472: CoverageWarning: --include is ignored because --source is set (include-ignored)
    self.warn("--include is ignored because --source is set", slug="include-ignored")

benchmarking/tests/test_experiments.py::test_run_clustering_experiment
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/tslearn/utils/utils.py:156: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    def to_time_series_dataset(dataset, dtype=numpy.float):

benchmarking/tests/test_experiments.py::test_run_clustering_experiment
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/tslearn/utils/cast.py:15: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    def to_sklearn_dataset(dataset, dtype=numpy.float, return_dim=False):

benchmarking/tests/test_experiments.py::test_run_clustering_experiment
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/tslearn/metrics/utils.py:9: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    compute_diagonal=True, dtype=numpy.float, *args, **kwargs):

benchmarking/tests/test_experiments.py::test_run_clustering_experiment
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/tslearn/metrics/sax.py:2: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    from .cysax import cydist_sax

benchmarking/tests/test_experiments.py::test_run_clustering_experiment
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/tslearn/metrics/sax.py:2: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    from .cysax import cydist_sax

benchmarking/tests/test_experiments.py::test_run_clustering_experiment
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/tslearn/metrics/__init__.py:24: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
  Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
    from .cycc import cdist_normalized_cc, y_shifted_sbd_vec

benchmarking/tests/test_experiments.py: 4530 warnings
clustering/tests/test_k_shapes.py: 2093 warnings
tests/test_all_estimators.py: 30028 warnings
clustering/tests/test_kernel_k_means.py: 18730 warnings

tests/test_all_estimators.py: 28 warnings
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sktime/transformations/series/boxcox.py:377: RuntimeWarning: invalid value encountered in power
    x_ratio = x_std / x_mean ** (1 - lmb)

tests/test_all_estimators.py::TestAllEstimators::test_fit_idempotent[LogTransformer-TransformerFitTransformPanelUnivariateWithClassY]
tests/test_all_estimators.py::TestAllEstimators::test_methods_do_not_change_state[LogTransformer-TransformerFitTransformPanelUnivariateWithClassY]
tests/test_all_estimators.py::TestAllEstimators::test_methods_have_no_side_effects[LogTransformer-TransformerFitTransformPanelUnivariateWithClassY]
tests/test_all_estimators.py::TestAllEstimators::test_persistence_via_pickle[LogTransformer-TransformerFitTransformPanelUnivariateWithClassY]
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sktime/transformations/series/boxcox.py:250: RuntimeWarning: invalid value encountered in log
    Xt = np.log(X)

transformations/tests/test_all_transformers.py::test_all_transformers[HampelFilter]
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1120: RuntimeWarning: All-NaN slice encountered
    overwrite_input=overwrite_input)

transformations/tests/test_all_transformers.py::test_all_transformers[TransformedTargetForecaster]
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sklearn/utils/extmath.py:985: RuntimeWarning: invalid value encountered in true_divide
    updated_mean = (last_sum + new_sum) / updated_sample_count

transformations/tests/test_all_transformers.py::test_all_transformers[TransformedTargetForecaster]
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sklearn/utils/extmath.py:990: RuntimeWarning: invalid value encountered in true_divide
    T = new_sum / new_sample_count

transformations/tests/test_all_transformers.py::test_all_transformers[TransformedTargetForecaster]
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sklearn/utils/extmath.py:1020: RuntimeWarning: invalid value encountered in true_divide
    new_unnormalized_variance -= correction ** 2 / new_sample_count

performance_metrics/forecasting/_classes.py: 8 warnings
performance_metrics/forecasting/_functions.py: 8 warnings
performance_metrics/tests/test_performance_metrics_forecasting.py: 60 warnings
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sktime/performance_metrics/forecasting/_functions.py:1802: FutureWarning: In the percentage error metric functions the default argument symmetric=True is changing to symmetric=False in v0.12.0.
    FutureWarning,

performance_metrics/forecasting/_classes.py: 8 warnings
performance_metrics/forecasting/_functions.py: 8 warnings
performance_metrics/tests/test_performance_metrics_forecasting.py: 60 warnings
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sktime/performance_metrics/forecasting/_functions.py:1669: FutureWarning: In the percentage error metric functions the default argument symmetric=True is changing to symmetric=False in v0.12.0.
    FutureWarning,

performance_metrics/forecasting/_classes.py: 8 warnings
performance_metrics/forecasting/_functions.py: 8 warnings
performance_metrics/tests/test_performance_metrics_forecasting.py: 60 warnings
  /Users/runner/hostedtoolcache/Python/3.7.12/x64/lib/python3.7/site-packages/sktime/performance_metrics/forecasting/_functions.py:1941: FutureWarning: In the percentage error metric functions the default argument symmetric=True is changing to symmetric=False in v0.12.0.
    FutureWarning,

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform darwin, python 3.7.12-final-0 ----------
---------------------- coverage: failed workers ----------------------
The following workers failed to return coverage data, ensure that pytest-cov is installed on these workers.
gw0
Coverage HTML written to dir htmlcov

============================= slowest 20 durations =============================
47.79s call     classification/distance_based/_proximity_forest.py::sktime.classification.distance_based._proximity_forest.ProximityForest
42.98s call     classification/compose/_column_ensemble.py::sktime.classification.compose._column_ensemble.ColumnEnsembleClassifier
28.47s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-window_length3-fh=1]
28.12s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-5-fh=1]
27.90s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-window_length2-fh=1]
27.82s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-1-fh=1]
27.74s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-window_length4-fh=1]
27.73s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-window_length5-fh=1]
27.57s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=False-step=1-window_length4-fh=1]
27.33s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=False-step=1-1-fh=1]
27.16s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=False-step=1-window_length3-fh=1]
27.11s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=False-step=1-window_length2-fh=1]
27.05s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=False-step=1-window_length5-fh=1]
26.94s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=False-step=1-5-fh=1]
26.54s call     forecasting/statsforecast.py::sktime.forecasting.statsforecast.StatsForecastAutoARIMA
25.92s call     classification/distance_based/tests/test_proximity_forest.py::test_pf_on_unit_test_data
23.90s call     tests/test_all_estimators.py::TestAllEstimators::test_fit_idempotent[MatrixProfileTransformer-TransformerFitTransformSeriesUnivariate]
20.34s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-5-fh=[2 5]]
19.99s call     tests/test_all_estimators.py::TestAllEstimators::test_raises_not_fitted_error[ARIMA-ForecasterFitPredictUnivariateNoX]
19.81s call     forecasting/tests/test_all_forecasters.py::TestAllForecasters::test_update_predict_predicted_index[Prophet-update_params=True-1-fh=[2 5]]
=========================== short test summary info ============================
FAILED benchmarking/tests/test_evaluator.py::test_plots
= 1 failed, 20210 passed, 1684 skipped, 5 xfailed, 1 xpassed, 123303 warnings in 2851.60s (0:47:31) =
make: *** [test] Error 1
Error: Process completed with exit code 2.