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)
