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
- h
dict
orndarray
An IIR dict or 1D ndarray of coefficients (for FIR filter).
- sfreq
float
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.
- title
str
|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’).
- flim
tuple
orNone
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.- fscale
str
Frequency scaling to use, can be “log” (default) or “linear”.
- alim
tuple
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.
- h
- Returns
- fig
matplotlib.figure.Figure
The figure containing the plots.
- fig
Notes
New in version 0.14.