mne.viz.plot_ica_properties#
- mne.viz.plot_ica_properties(ica, inst, picks=None, axes=None, dB=True, plot_std=True, log_scale=False, topomap_args=None, image_args=None, psd_args=None, figsize=None, show=True, reject='auto', reject_by_annotation=True, *, verbose=None)[source]#
Display component properties.
Properties include the topography, epochs image, ERP/ERF, power spectrum, and epoch variance.
- Parameters:
- icainstance of
mne.preprocessing.ICA
The ICA solution.
- instinstance of
Epochs
orRaw
The data to use in plotting properties.
Note
You can interactively cycle through topographic maps for different channel types by pressing T.
- picks
str
|list
|slice
|None
Components to include. Slices and lists of integers will be interpreted as component indices.
None
(default) will use the first five components. Each component will be plotted in a separate figure.- axes
list
ofAxes
|None
List of five matplotlib axes to use in plotting: [topomap_axis, image_axis, erp_axis, spectrum_axis, variance_axis]. If None a new figure with relevant axes is created. Defaults to None.
- dB
bool
Whether to plot spectrum in dB. Defaults to True.
- plot_std
bool
|float
Whether to plot standard deviation/confidence intervals in ERP/ERF and spectrum plots. Defaults to True, which plots one standard deviation above/below for the spectrum. If set to float allows to control how many standard deviations are plotted for the spectrum. For example 2.5 will plot 2.5 standard deviation above/below. For the ERP/ERF, by default, plot the 95 percent parametric confidence interval is calculated. To change this, use
ci
ints_args
inimage_args
(see below).- log_scale
bool
Whether to use a logarithmic frequency axis to plot the spectrum. Defaults to
False
.Note
You can interactively toggle this setting by pressing L.
New in version 1.1.
- topomap_args
dict
|None
Dictionary of arguments to
plot_topomap
. If None, doesn’t pass any additional arguments. Defaults to None.- image_args
dict
|None
Dictionary of arguments to
plot_epochs_image
. If None, doesn’t pass any additional arguments. Defaults to None.- psd_args
dict
|None
Dictionary of arguments to
psd_multitaper
. If None, doesn’t pass any additional arguments. Defaults to None.- figsizearray_like, shape (2,) |
None
Allows to control size of the figure. If None, the figure size defaults to [7., 6.].
- show
bool
Show figure if True.
- reject‘auto’ |
dict
|None
Allows to specify rejection parameters used to drop epochs (or segments if continuous signal is passed as inst). If None, no rejection is applied. The default is ‘auto’, which applies the rejection parameters used when fitting the ICA object.
- reject_by_annotation
bool
Whether to omit bad segments from the data before fitting. If
True
(default), annotated segments whose description begins with'bad'
are omitted. IfFalse
, no rejection based on annotations is performed.Has no effect if
inst
is not amne.io.Raw
object.New in version 0.21.0.
- verbose
bool
|str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- icainstance of
- Returns:
- fig
list
List of matplotlib figures.
- fig
Notes
New in version 0.13.