neurodsp.spectral.compute_spectrum

neurodsp.spectral.compute_spectrum(sig, fs, method='welch', **kwargs)[source]

Compute the power spectral density of a time series.

Parameters:
sigarray

Time series.

fsfloat

Sampling rate, in Hz.

method{‘welch’, ‘wavelet’, ‘medfilt’, ‘multitaper’}, optional

Method to use to estimate the power spectrum.

**kwargs

Keyword arguments to pass through to the function that calculates the spectrum. See compute_spectrum_{welch, wavelet, medfilt} for details.

Returns:
freqs1d array

Frequencies at which the measure was calculated.

spectrumarray

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)

Examples using neurodsp.spectral.compute_spectrum

Using NeuroDSP with MNE

Using NeuroDSP with MNE

IRASA

IRASA

Simulating Periodic Signals

Simulating Periodic Signals

Simulating Aperiodic Signals

Simulating Aperiodic Signals

Simulating Combined Signals

Simulating Combined Signals

Spectral Domain Analysis: Power

Spectral Domain Analysis: Power

Spectral Domain Analysis: Variance

Spectral Domain Analysis: Variance