neurodsp.spectral.compute_spectrum¶
- neurodsp.spectral.compute_spectrum(sig, fs, method='welch', avg_type='mean', **kwargs)[source]¶
Compute the power spectral density of a time series.
- Parameters
- sig1d or 2d array
Time series.
- fsfloat
Sampling rate, in Hz.
- method{‘welch’, ‘wavelet’, ‘medfilt’}, optional
Method to use to estimate the power spectrum.
- avg_type{‘mean’, ‘median’}, optional
If relevant, the method to average across windows to create the spectrum.
- **kwargs
Keyword arguments to pass through to the function that calculates the spectrum.
- Returns
- freqs1d array
Frequencies at which the measure was calculated.
- spectrum1d or 2d array
Power spectral density.
Examples
Compute the power spectrum of a simulated time series:
>>> from neurodsp.sim import sim_combined >>> sig = sim_combined(n_seconds=10, fs=500, ... components={'sim_powerlaw': {}, 'sim_oscillation' : {'freq': 10}}) >>> freqs, spectrum = compute_spectrum(sig, fs=500)
