def __init__(self): initial_map = ComprehensiveFCParameters() initial_map.pop("sample_entropy") initial_map.pop("change_quantiles") initial_map.pop("linear_trend_timewise") # broken super().__init__(initial_map)
def __init__( self, has_duplicate_max, binned_entropy, last_location_of_maximum, abs_energy, c3, value_count, mean_second_derivative_central, first_location_of_minimum, standard_deviation, length, mean_abs_change, has_duplicate_min, mean_change, sum_values, percentage_of_reoccurring_datapoints_to_all_datapoints, range_count, absolute_sum_of_changes, energy_ratio_by_chunks, last_location_of_minimum, linear_trend, variance_larger_than_standard_deviation, spkt_welch_density, cid_ce, symmetry_looking, has_duplicate, skewness, count_above_mean, longest_strike_below_mean, mean, agg_autocorrelation, ratio_value_number_to_time_series_length, fft_aggregated, first_location_of_maximum, partial_autocorrelation, sum_of_reoccurring_data_points, count_below_mean, variance, longest_strike_above_mean, median, kurtosis, minimum, time_reversal_asymmetry_statistic, number_crossing_m, sum_of_reoccurring_values, maximum, approximate_entropy, number_cwt_peaks, augmented_dickey_fuller, quantile, agg_linear_trend, max_langevin_fixed_point, friedrich_coefficients, fft_coefficient, large_standard_deviation, autocorrelation, cwt_coefficients, percentage_of_reoccurring_values_to_all_values, ar_coefficient, ratio_beyond_r_sigma, number_peaks, sample_entropy, change_quantiles): initial_map = ComprehensiveFCParameters() initial_map.pop("linear_trend_timewise") # broken if not has_duplicate_max: initial_map.pop("has_duplicate_max") if not binned_entropy: initial_map.pop("binned_entropy") if not last_location_of_maximum: initial_map.pop("last_location_of_maximum") if not abs_energy: initial_map.pop("abs_energy") if not c3: initial_map.pop("c3") if not value_count: initial_map.pop("value_count") if not mean_second_derivative_central: initial_map.pop("mean_second_derivative_central") if not first_location_of_minimum: initial_map.pop("first_location_of_minimum") if not standard_deviation: initial_map.pop("standard_deviation") if not length: initial_map.pop("length") if not mean_abs_change: initial_map.pop("mean_abs_change") if not has_duplicate_min: initial_map.pop("has_duplicate_min") if not mean_change: initial_map.pop("mean_change") if not sum_values: initial_map.pop("sum_values") if not percentage_of_reoccurring_datapoints_to_all_datapoints: initial_map.pop( "percentage_of_reoccurring_datapoints_to_all_datapoints") if not range_count: initial_map.pop("range_count") if not absolute_sum_of_changes: initial_map.pop("absolute_sum_of_changes") if not energy_ratio_by_chunks: initial_map.pop("energy_ratio_by_chunks") if not last_location_of_minimum: initial_map.pop("last_location_of_minimum") if not linear_trend: initial_map.pop("linear_trend") if not variance_larger_than_standard_deviation: initial_map.pop("variance_larger_than_standard_deviation") if not spkt_welch_density: initial_map.pop("spkt_welch_density") if not cid_ce: initial_map.pop("cid_ce") if not symmetry_looking: initial_map.pop("symmetry_looking") if not has_duplicate: initial_map.pop("has_duplicate") if not skewness: initial_map.pop("skewness") if not count_above_mean: initial_map.pop("count_above_mean") if not longest_strike_below_mean: initial_map.pop("longest_strike_below_mean") if not mean: initial_map.pop("mean") if not agg_autocorrelation: initial_map.pop("agg_autocorrelation") if not ratio_value_number_to_time_series_length: initial_map.pop("ratio_value_number_to_time_series_length") if not fft_aggregated: initial_map.pop("fft_aggregated") if not first_location_of_maximum: initial_map.pop("first_location_of_maximum") if not partial_autocorrelation: initial_map.pop("partial_autocorrelation") if not sum_of_reoccurring_data_points: initial_map.pop("sum_of_reoccurring_data_points") if not count_below_mean: initial_map.pop("count_below_mean") if not variance: initial_map.pop("variance") if not longest_strike_above_mean: initial_map.pop("longest_strike_above_mean") if not median: initial_map.pop("median") if not kurtosis: initial_map.pop("kurtosis") if not minimum: initial_map.pop("minimum") if not time_reversal_asymmetry_statistic: initial_map.pop("time_reversal_asymmetry_statistic") if not number_crossing_m: initial_map.pop("number_crossing_m") if not sum_of_reoccurring_values: initial_map.pop("sum_of_reoccurring_values") if not maximum: initial_map.pop("maximum") if not approximate_entropy: initial_map.pop("approximate_entropy") if not number_cwt_peaks: initial_map.pop("number_cwt_peaks") if not augmented_dickey_fuller: initial_map.pop("augmented_dickey_fuller") if not quantile: initial_map.pop("quantile") if not agg_linear_trend: initial_map.pop("agg_linear_trend") if not max_langevin_fixed_point: initial_map.pop("max_langevin_fixed_point") if not friedrich_coefficients: initial_map.pop("friedrich_coefficients") if not fft_coefficient: initial_map.pop("fft_coefficient") if not large_standard_deviation: initial_map.pop("large_standard_deviation") if not autocorrelation: initial_map.pop("autocorrelation") if not cwt_coefficients: initial_map.pop("cwt_coefficients") if not percentage_of_reoccurring_values_to_all_values: initial_map.pop("percentage_of_reoccurring_values_to_all_values") if not ar_coefficient: initial_map.pop("ar_coefficient") if not ratio_beyond_r_sigma: initial_map.pop("ratio_beyond_r_sigma") if not number_peaks: initial_map.pop("number_peaks") if not sample_entropy: initial_map.pop("sample_entropy") if not change_quantiles: initial_map.pop("change_quantiles") super().__init__(initial_map)
def __init__(self): initial_map = ComprehensiveFCParameters() initial_map.pop("sample_entropy") initial_map.pop("change_quantiles") initial_map.pop("approximate_entropy") initial_map.pop("number_cwt_peaks") initial_map.pop("augmented_dickey_fuller") initial_map.pop("quantile") initial_map.pop("agg_linear_trend") initial_map.pop("max_langevin_fixed_point") initial_map.pop("friedrich_coefficients") initial_map.pop("fft_coefficient") initial_map.pop("large_standard_deviation") initial_map.pop("autocorrelation") initial_map.pop("cwt_coefficients") initial_map.pop("percentage_of_reoccurring_values_to_all_values") initial_map.pop("ar_coefficient") initial_map.pop("ratio_beyond_r_sigma") initial_map.pop("number_peaks") initial_map.pop("linear_trend_timewise") #broken super().__init__(initial_map)