Acoustic features

The module features is an ensemble of functions to characterize audio signals using temporal and spectral features, and ecoacoustic indices.

Spectro-temporal features

shape_features(Sxx[, resolution, rois]) Computes time-frequency shape coefficients at multiple resolutions using 2D Gabor filters.
shape_features_raw(im[, resolution, opt_shape]) Computes raw shape of 2D signal (image or spectrogram) at multiple resolutions using 2D Gabor filters.
opt_shape_presets(resolution[, opt_shape]) Set parameters for multiresolution analysis using presets or custom parameters.
filter_multires(Sxx, kernels[, npyr, rescale]) Computes 2D wavelet coefficients at multiple scales using Gaussian pyramid transformation to downscale the input spectrogram.
filter_bank_2d_nodc(frequency, ntheta[, ...]) Build an ensemble of complex 2D Gabor filters with no DC offset.
centroid_features(Sxx[, rois, im_rois]) Computes intensity centroid of a spectrogram.
all_shape_features(s, fs, rois[, ...]) Computes shape and central frequency features from signal at specified time-frequency limits defined by regions of interest (ROIs).

Alpha acoustic indices

temporal_median(s[, mode, Nt]) Computes the median of the envelope of an audio signal.
temporal_entropy(s[, compatibility, mode, Nt]) Computes the entropy of the envelope of an audio signal.
acoustic_richness_index(Ht_array, M_array) Compute the acoustic richness index of an audio file.
temporal_activity(s[, dB_threshold, mode, Nt]) Compute the acoustic activity index in temporal domain.
temporal_events(s, fs[, dB_threshold, ...]) Compute the acoustic event index from an audio signal [R6d576de36602-1] [R6d576de36602-2].
acoustic_complexity_index(Sxx) Compute the Acoustic Complexity Index (ACI) from a spectrogram [R669a90ddf753-1].
frequency_entropy(X[, compatibility]) Computes the spectral entropy of a power spectral density (1d) or power spectrogram density (2d).
number_of_peaks(X, fn[, mode, min_peak_val, ...]) Count the number of frequency peaks on a mean spectrum.
spectral_entropy(Sxx, fn[, flim, display]) Compute different entropies based on the average spectrum, its variance, and its maxima [R1479941c7526-1] [R1479941c7526-2]
spectral_activity(Sxx_dB[, dB_threshold]) Compute the acoustic activity on a spectrogram.
spectral_events(Sxx_dB, dt[, dB_threshold, ...]) Compute acoustic events from a spectrogram [Rf0ffa84335f9-1] [Rf0ffa84335f9-2].
spectral_cover(Sxx, fn[, dB_threshold, ...]) Compute the proportion (cover) of the spectrogram above a threshold for three bandwidths : low frequency band (LF), medium frequency band (MF) and high frequency band (HF) [R1ef1ced9d4c7-1] [R1ef1ced9d4c7-2].
soundscape_index(Sxx_power, fn[, ...]) Compute the Normalized Difference Soundscape Index from a power spectrogram [Re8a3e6a1d49a-1].
bioacoustics_index(Sxx, fn[, flim, R_compatible]) Compute the Bioacoustics Index from a spectrogram [R4387573841e2-1].
acoustic_diversity_index(Sxx, fn[, fmin, ...]) Compute the Acoustic Diversity Index (ADI) from a spectrogram [R544b09b311be-1].
acoustic_eveness_index(Sxx, fn[, fmin, ...]) Compute the Acoustic Eveness Index (AEI) from a spectrogram [Re3dd41c8e02e-1].
roughness(x[, norm, axis]) Computes the roughness (depends on the number of peaks and their amplitude) of a vector or matrix x (i.e.
temporal_leq(s, fs, gain[, Vadc, ...]) Computes the Equivalent Continuous Sound level (Leq) of an audio signal in the time domain.
spectral_leq(X, gain[, Vadc, sensitivity, ...]) Computes the Equivalent Continuous Sound level (Leq) from a power spectrum (1d) or power spectrogram (2d).
surface_roughness(x[, norm]) Compute the surface roughness index of a signal (1D) or a spectrogram (2D).
tfsd(Sxx, fn, tn[, flim, log, mode, display]) Compute the Time frequency derivation index (tfsd) from a spectrogram.
more_entropy(x[, order, axis]) Compute the entropy of an audio signal using multiple methods.
acoustic_gradient_index(Sxx, dt[, order, ...]) Compute the Acoustic Gradient Index (AGI) from a raw spectrogram.
frequency_raoq(S_power, fn[, bin_step]) Compute Rao's quadratic entropy on a power spectrum (1d).
region_of_interest_index(Sxx_dB_noNoise, tn, fn) Compute an acoustic activity index based on the regions of interested detected on a spectrogram.
all_temporal_alpha_indices(s, fs[, verbose, ...]) Compute 16 temporal domain acoustic indices.
all_spectral_alpha_indices(Sxx_power, tn, fn) Computes the acoustic indices in spectral (spectrum (1d) or spectrogram (2d)) domain.

Temporal features

temporal_moments(s[, fs, roi]) Computes the first 4th moments of an audio signal, mean, variance, skewness, kurtosis.
zero_crossing_rate(s, fs[, roi]) Compute the zero crossing rate feature of an audio signal.
temporal_duration(s, fs[, nperseg, roi, ...]) Compute the temporal duration of the waveform.
temporal_quantile(s, fs[, q, nperseg, roi, ...]) Compute the q-th temporal quantile of the waveform or spectrum.
all_temporal_features(s, fs[, nperseg, roi, ...]) Compute all the temporal features for a signal.

Spectral features

spectral_moments(X[, axis]) Computes the first 4th moments of an amplitude spectrum (1d) or spectrogram (2d), mean, variance, skewness, kurtosis.
peak_frequency(s, fs[, method, nperseg, ...]) Compute the peak frequency for audio signal.
spectral_quantile(s, fs[, q, nperseg, roi, ...]) Compute the q-th quantile of the power spectrum.
spectral_bandwidth(s, fs[, nperseg, roi, ...]) Compute the bandwith of the power spectrum.
all_spectral_features(s, fs[, nperseg, roi, ...]) Compute all the spectral features for a signal.