# List of available features¶

The following table provides an overview of the available featurest in the current version of TSFEL.

`tsfel.feature_extraction.features` |

`abs_energy` (signal) |
Computes the absolute energy of the signal. |

`auc` (signal, fs) |
Computes the area under the curve of the signal computed with trapezoid rule. |

`autocorr` (signal) |
Computes autocorrelation of the signal. |

`calc_centroid` (signal, fs) |
Computes the centroid along the time axis. |

`calc_max` (signal) |
Computes the maximum value of the signal. |

`calc_mean` (signal) |
Computes mean value of the signal. |

`calc_median` (signal) |
Computes median of the signal. |

`calc_min` (signal) |
Computes the minimum value of the signal. |

`calc_std` (signal) |
Computes standard deviation (std) of the signal. |

`calc_var` (signal) |
Computes variance of the signal. |

`distance` (signal) |
Computes signal traveled distance. |

`ecdf` (signal[, d]) |
Computes the values of ECDF (empirical cumulative distribution function) along the time axis. |

`ecdf_percentile` (signal[, percentile]) |
Computes the percentile values of the ECDF. |

`ecdf_percentile_count` (signal[, percentile]) |
Computes the cumulative sum of samples that are less than the percentile. |

`entropy` (signal[, prob]) |
Computes the entropy of the signal using the Shannon Entropy. |

`fft_mean_coeff` (signal, fs[, nfreq]) |
Computes the mean value of each spectrogram frequency. |

`fundamental_frequency` (signal, fs) |
Computes fundamental frequency of the signal. |

`hist` (signal[, nbins, r]) |
Computes histogram of the signal. |

`human_range_energy` (signal, fs) |
Computes the human range energy ratio. |

`interq_range` (signal) |
Computes interquartile range of the signal. |

`kurtosis` (signal) |
Computes kurtosis of the signal. |

`lpcc` (signal[, n_coeff]) |
Computes the linear prediction cepstral coefficients. |

`max_frequency` (signal, fs) |
Computes maximum frequency of the signal. |

`max_power_spectrum` (signal, fs) |
Computes maximum power spectrum density of the signal. |

`mean_abs_deviation` (signal) |
Computes mean absolute deviation of the signal. |

`mean_abs_diff` (signal) |
Computes mean absolute differences of the signal. |

`mean_diff` (signal) |
Computes mean of differences of the signal. |

`median_abs_deviation` (signal) |
Computes median absolute deviation of the signal. |

`median_abs_diff` (signal) |
Computes median absolute differences of the signal. |

`median_diff` (signal) |
Computes median of differences of the signal. |

`median_frequency` (signal, fs) |
Computes median frequency of the signal. |

`mfcc` (signal, fs[, pre_emphasis, nfft, …]) |
Computes the MEL cepstral coefficients. |

`negative_turning` (signal) |
Computes number of negative turning points of the signal. |

`neighbourhood_peaks` (signal[, n]) |
Computes the number of peaks from a defined neighbourhood of the signal. |

`pk_pk_distance` (signal) |
Computes the peak to peak distance. |

`positive_turning` (signal) |
Computes number of positive turning points of the signal. |

`power_bandwidth` (signal, fs) |
Computes power spectrum density bandwidth of the signal. |

`rms` (signal) |
Computes root mean square of the signal. |

`skewness` (signal) |
Computes skewness of the signal. |

`slope` (signal) |
Computes the slope of the signal. |

`spectral_centroid` (signal, fs) |
Barycenter of the spectrum. |

`spectral_decrease` (signal, fs) |
Represents the amount of decreasing of the spectra amplitude. |

`spectral_distance` (signal, fs) |
Computes the signal spectral distance. |

`spectral_entropy` (signal, fs) |
Computes the spectral entropy of the signal based on Fourier transform. |

`spectral_kurtosis` (signal, fs) |
Measures the flatness of a distribution around its mean value. |

`spectral_positive_turning` (signal, fs) |
Computes number of positive turning points of the fft magnitude signal. |

`spectral_roll_off` (signal, fs) |
Computes the spectral roll-off of the signal. |

`spectral_roll_on` (signal, fs) |
Computes the spectral roll-on of the signal. |

`spectral_skewness` (signal, fs) |
Measures the asymmetry of a distribution around its mean value. |

`spectral_slope` (signal, fs) |
Computes the spectral slope. |

`spectral_spread` (signal, fs) |
Measures the spread of the spectrum around its mean value. |

`spectral_variation` (signal, fs) |
Computes the amount of variation of the spectrum along time. |

`sum_abs_diff` (signal) |
Computes sum of absolute differences of the signal. |

`total_energy` (signal, fs) |
Computes the total energy of the signal. |

`wavelet_abs_mean` (signal[, function, widths]) |
Computes CWT absolute mean value of each wavelet scale. |

`wavelet_energy` (signal[, function, widths]) |
Computes CWT energy of each wavelet scale. |

`wavelet_entropy` (signal[, function, widths]) |
Computes CWT entropy of the signal. |

`wavelet_std` (signal[, function, widths]) |
Computes CWT std value of each wavelet scale. |

`wavelet_var` (signal[, function, widths]) |
Computes CWT variance value of each wavelet scale. |

`zero_cross` (signal) |
Computes Zero-crossing rate of the signal. |