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IssueID #3922: v0.16.1 - Readded baseline unit tests - Readded large_number_of_peaks removed in v0.9.0 - Readded mean_autocorrelation removed in v0.9.0 - Reverted to original augmented_dickey_fuller that was changed in v0.9.0 - Reverted to original fft_coefficient that was changed in v0.9.0 - Readded mean_abs_change_quantiles that was removed in v0.9.0 - Readded the original time_reversal_asymmetry_statistic that was in use pre v0.9.0 - blue-yonder#198 - Readded original autocorrelation that was removed in v0.9.0 - Disabled partial_autocorrelation added in v0.10.0 - Disabled cid_ce added in v0.11.1 - Disabled fft_aggregated added in v0.11.0 - Disabled Fix agg change made to agg_autocorrelation added in v0.11.1 blue-yonder@a53fb6a - Changed to new value_count and range_count method added in v0.11.1 - Configured settings for pre v0.9.0 features - Hardcoded TSFRESH_BASELINE_VERSION = '0.9.1' in tests - Disabled linear_trend_timewise added in v0.12.0 - Readded tsfresh/examples/test_tsfresh_baseline_dataset.py which was removed in v0.12.0 - Use v0.11.01 value_count and range_count method not as per v0.13.0 - Disabled count_above and count_below features that were added in v0.15.0 - Configured settings for pre v0.9.0 features - Hardcoded TSFRESH_BASELINE_VERSION = '0.16.1' in tests Added: tests/baseline/tsfresh-0.1.2.py2.data.json.features.transposed.csv tests/baseline/tsfresh-0.3.0.py2.data.json.features.transposed.csv tests/baseline/tsfresh-0.3.0.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.3.1.py2.data.json.features.transposed.csv tests/baseline/tsfresh-0.3.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.4.0.py2.data.json.features.transposed.csv tests/baseline/tsfresh-0.4.0.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.5.0.py2.data.json.features.transposed.csv tests/baseline/tsfresh-0.5.0.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.5.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.6.0.py2.data.json.features.transposed.csv tests/baseline/tsfresh-0.6.0.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.6.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.7.2.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.8.2.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.9.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.10.2.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.11.3.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.12.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.13.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.14.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.15.2.py3.data.json.features.transposed.csv tests/baseline/tsfresh-0.16.1.py3.data.json.features.transposed.csv tests/baseline/tsfresh_features_test.py Modified: CHANGES.rst README.md tsfresh/feature_extraction/feature_calculators.py tsfresh/feature_extraction/settings.py
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tests/baseline/tsfresh-0.1.2.py2.data.json.features.transposed.csv
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,tsfresh_features_test | ||
value__symmetry_looking__r_0.65,1.0 | ||
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value__absolute_sum_of_changes,2755.0 | ||
value__augmented_dickey_fuller,-0.804122034203 | ||
value__large_number_of_peaks__n_3,1.0 | ||
value__large_number_of_peaks__n_5,0.0 | ||
value__last_location_of_minimum,0.0333333333333 | ||
value__mean_abs_change_quantiles__qh_0.4__ql_0.0,35.6 | ||
value__mean_abs_change_quantiles__qh_0.4__ql_0.2,12.0 | ||
value__minimum,9856.0 | ||
value__mean_abs_change_quantiles__qh_0.4__ql_0.6,0.0 | ||
value__mean_abs_change_quantiles__qh_0.4__ql_0.8,0.0 | ||
value__maximum,10123.0 | ||
value__value_count__value_-inf,0.0 | ||
value__number_peaks__n_1,21.0 | ||
value__number_peaks__n_3,9.0 | ||
value__longest_strike_above_mean,10.0 | ||
value__number_peaks__n_5,4.0 | ||
value__first_location_of_minimum,0.0166666666667 | ||
value__large_standard_deviation__r_0.25,0.0 | ||
value__large_number_of_peaks__n_1,1.0 | ||
value__count_above_mean,29.0 | ||
value__symmetry_looking__r_0.75,1.0 | ||
value__mean_abs_change,46.6949152542 | ||
value__mean_change,2.38983050847 | ||
value__value_count__value_1,0.0 | ||
value__value_count__value_0,0.0 | ||
value__mean_abs_change_quantiles__qh_0.4__ql_0.4,0.0 | ||
value__mean_autocorrelation,1.1720475294 | ||
value__autocorrelation__lag_5,0.464639525765 | ||
value__median,9981.0 | ||
value__symmetry_looking__r_0.85,1.0 | ||
value__mean_abs_change_quantiles__qh_0.8__ql_0.4,20.0 | ||
value__symmetry_looking__r_0.05,1.0 | ||
value__mean_abs_change_quantiles__qh_0.8__ql_0.6,13.0 | ||
value__value_count__value_inf,0.0 | ||
value__mean_abs_change_quantiles__qh_0.8__ql_0.0,43.0256410256 | ||
value__mean_abs_change_quantiles__qh_0.8__ql_0.2,31.619047619 | ||
value__large_standard_deviation__r_0.45,0.0 | ||
value__mean_abs_change_quantiles__qh_0.8__ql_0.8,0.0 | ||
value__autocorrelation__lag_6,0.512480168514 | ||
value__autocorrelation__lag_7,0.653853495147 | ||
value__autocorrelation__lag_4,0.535012070945 | ||
value__last_location_of_maximum,0.966666666667 | ||
value__autocorrelation__lag_2,0.367658131978 | ||
value__autocorrelation__lag_3,0.411575406169 | ||
value__autocorrelation__lag_0,1.0 | ||
value__autocorrelation__lag_1,0.51547994425 | ||
value__autocorrelation__lag_8,0.360082254297 | ||
value__autocorrelation__lag_9,0.217484000968 | ||
value__variance_larger_than_standard_deviation,1.0 | ||
value__variance,3196.67638889 | ||
value__mean,9986.08333333 | ||
value__mean_abs_change_quantiles__qh_0.6__ql_0.8,0.0 | ||
value__mean_abs_change_quantiles__qh_0.6__ql_0.6,0.0 | ||
value__mean_abs_change_quantiles__qh_0.6__ql_0.4,6.0 | ||
value__mean_abs_change_quantiles__qh_0.6__ql_0.2,23.1818181818 | ||
value__mean_abs_change_quantiles__qh_0.6__ql_0.0,42.25 | ||
value__symmetry_looking__r_0.15,1.0 | ||
value__mean_second_derivate_central,0.706896551724 | ||
value__skewness,-0.135422921254 | ||
value__length,60.0 | ||
value__first_location_of_maximum,0.95 | ||
value__mean_abs_change_quantiles__qh_1.0__ql_0.2,42.4634146341 | ||
value__mean_abs_change_quantiles__qh_1.0__ql_0.4,45.0740740741 | ||
value__mean_abs_change_quantiles__qh_1.0__ql_0.6,41.125 | ||
value__mean_abs_change_quantiles__qh_1.0__ql_0.8,58.3333333333 | ||
value__range_count__max_1__min_-1,0.0 | ||
value__kurtosis,-0.0289015217515 | ||
value__symmetry_looking__r_0.25,1.0 | ||
value__time_reversal_asymmetry_statistic__lag_3,1993963105.11 | ||
value__abs_energy,5983503421.0 | ||
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value__symmetry_looking__r_0.35,1.0 | ||
value__large_standard_deviation__r_0.3,0.0 | ||
value__large_standard_deviation__r_0.2,1.0 | ||
value__large_standard_deviation__r_0.1,1.0 | ||
value__large_standard_deviation__r_0.0,1.0 | ||
value__large_standard_deviation__r_0.4,0.0 | ||
value__large_standard_deviation__r_0.15,1.0 | ||
value__standard_deviation,56.5391580136 | ||
value__binned_entropy__max_bins_10,2.11974362674 | ||
value__large_standard_deviation__r_0.35,0.0 | ||
value__symmetry_looking__r_0.95,1.0 | ||
value__longest_strike_below_mean,9.0 | ||
value__sum_values,599165.0 | ||
value__symmetry_looking__r_0.45,1.0 | ||
value__symmetry_looking__r_0.6,1.0 | ||
value__symmetry_looking__r_0.7,1.0 | ||
value__symmetry_looking__r_0.4,1.0 | ||
value__symmetry_looking__r_0.5,1.0 | ||
value__symmetry_looking__r_0.2,1.0 | ||
value__symmetry_looking__r_0.3,1.0 | ||
value__symmetry_looking__r_0.0,0.0 | ||
value__symmetry_looking__r_0.1,1.0 | ||
value__has_duplicate,1.0 | ||
value__symmetry_looking__r_0.8,1.0 | ||
value__symmetry_looking__r_0.9,1.0 | ||
value__value_count__value_nan,0.0 | ||
value__mean_abs_change_quantiles__qh_0.2__ql_0.8,0.0 | ||
value__large_standard_deviation__r_0.05,1.0 | ||
value__mean_abs_change_quantiles__qh_0.2__ql_0.2,0.0 | ||
value__has_duplicate_max,0.0 | ||
value__mean_abs_change_quantiles__qh_0.2__ql_0.0,29.4 | ||
value__mean_abs_change_quantiles__qh_0.2__ql_0.6,0.0 | ||
value__mean_abs_change_quantiles__qh_0.2__ql_0.4,0.0 | ||
value__number_cwt_peaks__n_5,6.0 | ||
value__number_cwt_peaks__n_1,9.0 | ||
value__has_duplicate_min,0.0 | ||
value__symmetry_looking__r_0.55,1.0 | ||
value__count_below_mean,31.0 | ||
value__quantile__q_0.1,9909.9 | ||
value__quantile__q_0.2,9937.8 | ||
value__quantile__q_0.3,9962.7 | ||
value__quantile__q_0.4,9975.6 | ||
value__quantile__q_0.6,10004.8 | ||
value__quantile__q_0.7,10017.6 | ||
value__quantile__q_0.8,10033.2 | ||
value__quantile__q_0.9,10048.9 | ||
value__ar_coefficient__k_10__coeff_0,904.439185079 | ||
value__ar_coefficient__k_10__coeff_1,0.163578948116 | ||
value__ar_coefficient__k_10__coeff_2,-0.0432470001474 | ||
value__ar_coefficient__k_10__coeff_3,-0.066542370683 | ||
value__ar_coefficient__k_10__coeff_4,0.283685319392 | ||
value__index_mass_quantile__q_0.1,0.116666666667 | ||
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value__index_mass_quantile__q_0.3,0.316666666667 | ||
value__index_mass_quantile__q_0.4,0.416666666667 | ||
value__index_mass_quantile__q_0.6,0.616666666667 | ||
value__index_mass_quantile__q_0.7,0.716666666667 | ||
value__index_mass_quantile__q_0.8,0.816666666667 | ||
value__index_mass_quantile__q_0.9,0.916666666667 | ||
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value__fft_coefficient__coeff_6,13.0 | ||
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value__fft_coefficient__coeff_8,118.187822328 | ||
value__fft_coefficient__coeff_9,-248.0 |
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