List of available features

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

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.