EEG Stream¶
Reimplementation of Matplotlib-FigureStream with some renames and a preconfigured server.
- class bci_framework.extensions.visualizations.eeg_stream.EEGStream(*args: Any, **kwargs: Any)[source]¶
Matplotlib figure re-implementation.
This class define some usefull methods to use for simplificate the data manipulation.
- create_lines(mode: Literal['eeg', 'accel', 'analog', 'digital'] = 'eeg', time: Optional[int] = -15, window: Optional[int] = 1000, cmap: Optional[str] = 'cool', fill: Optional[numpy.ndarray] = numpy.nan, subplot: Optional[list] = [1, 1, 1]) Tuple[matplotlib.axes.Axes, numpy.ndarray, list[matplotlib.lines]] [source]¶
Create plot automatically.
Create and configure a subplot to display figures.
- Parameters
mode – Used for select the axis labels.
time – The time window, can be negative.
window – The number of samples used to draw the figure.
cmap – The matplolib cmap to use.
fill – Start signals array with this value.
subplot – The matplolib subplot.
- Returns
axis – The subplot created.
time – The time array.
lines – The matplotlib lines object created for each channel.
- class bci_framework.extensions.visualizations.eeg_stream.MNEObjects[source]¶
Creat MNE handlers using the framework GUI information.
- get_mne_evoked() mne.EvokedArray [source]¶
Create the Evoked object to use with mne handlers.
The information is acquired automatically from GUI interface.