cogpy.spectral

Spectral analysis: multitaper PSD, spectrograms, band power, spectral features, coherence, and whitening. All functions follow the PSD-first convention — compute the PSD once, then derive features from it.

Tutorial: Spectral Analysis | Design: Spectral Conventions

Submodules

cogpy.spectral.bivariate	Bivariate spectral measures: cross-spectrum, coherence, PLV.
cogpy.spectral.features	Spectral features derived from pre-computed PSD estimates.
cogpy.spectral.multitaper	Multitaper spectral estimation utilities.
cogpy.spectral.process_spectrogram	Post-processing helpers for spectrogram-like arrays.
cogpy.spectral.psd	PSD estimators with unified return convention.
cogpy.spectral.psd_utils	PSD utilities for TensorScope (v2.8.0).
cogpy.spectral.specx	Spectral transforms with xarray interface.
cogpy.spectral.whitening	Whitening utilities for time series.

Spectral analysis: PSD, spectrograms, coherence, and multitaper methods.

Submodules

psd : Power spectral density estimation (Welch, periodogram). multitaper : Multitaper spectral estimation and F-tests. specx : Short-time spectrograms and time–frequency representations. bivariate : Coherence, phase-locking value, and cross-spectral measures. features : Band-power extraction, spectral edge, and peak frequency. whitening : Spectral flattening and 1/f removal. process_spectrogram : Post-processing utilities for spectrogram arrays.