mne.viz.plot_filter

mne.viz.plot_filter(h, sfreq, freq=None, gain=None, title=None, color='#1f77b4', flim=None, fscale='log', alim=(-80, 10), show=True, compensate=False)[source]

Plot properties of a filter.

Parameters
hdict or ndarray

An IIR dict or 1D ndarray of coefficients (for FIR filter).

sfreqfloat

Sample rate of the data (Hz).

freqarray_like or None

The ideal response frequencies to plot (must be in ascending order). If None (default), do not plot the ideal response.

gainarray_like or None

The ideal response gains to plot. If None (default), do not plot the ideal response.

titlestr | None

The title to use. If None (default), deteremine the title based on the type of the system.

colorcolor object

The color to use (default ‘#1f77b4’).

flimtuple or None

If not None, the x-axis frequency limits (Hz) to use. If None, freq will be used. If None (default) and freq is None, (0.1, sfreq / 2.) will be used.

fscalestr

Frequency scaling to use, can be “log” (default) or “linear”.

alimtuple

The y-axis amplitude limits (dB) to use (default: (-60, 10)).

showbool

Show figure if True (default).

compensatebool

If True, compensate for the filter delay (phase will not be shown).

  • For linear-phase FIR filters, this visualizes the filter coefficients assuming that the output will be shifted by N // 2.

  • For IIR filters, this changes the filter coefficient display by filtering backward and forward, and the frequency response by squaring it.

New in version 0.18.

Returns
figmatplotlib.figure.Figure

The figure containing the plots.

Notes

New in version 0.14.

Examples using mne.viz.plot_filter