neurodsp.plts.plot_scv_rs_matrix¶
- neurodsp.plts.plot_scv_rs_matrix(freqs, t_inds, scv_rs, ax=None, **kwargs)[source]¶
Plot spectral coefficient of variation, from the resampling method, as a matrix.
- Parameters
- freqs1d array
Frequency vector.
- t_inds1d array
Time indices.
- scv_rs1d array
Spectral coefficient of variation, from resampling procedure.
- axmatplotlib.Axes, optional
Figure axes upon which to plot.
- **kwargs
Keyword arguments for customizing the plot.
Examples
Plot a SCV matrix from a simulated signal with a high probability of bursting at 10Hz:
>>> from neurodsp.sim import sim_combined >>> from neurodsp.spectral import compute_scv_rs >>> sig = sim_combined(n_seconds=100, fs=500, ... components={'sim_synaptic_current': {}, ... 'sim_bursty_oscillation': {'freq': 10, 'enter_burst':0.75}}) >>> freqs, t_inds, scv_rs = compute_scv_rs(sig, fs=500, method='rolling', rs_params=(10, 2)) >>> # Plot the computed scv, plotting frequencies up to 20 Hz (index of 21) >>> plot_scv_rs_matrix(freqs[:21], t_inds, scv_rs[:21])
Examples using neurodsp.plts.plot_scv_rs_matrix
¶
Spectral Domain Analysis: Variance
Spectral Domain Analysis: Variance