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. |