visualization Package

visualization Package

Visualize the single different data samples or averages

All visualization nodes are zero-processing nodes, i.e. their execute method returns exactly the data that it gets as parameter. However, when the data is passed through the visualization node, it performs different kinds of analysis and creates some plots of the data. In principle, visualization nodes can be plugged between two arbitrary other nodes; however some nodes expect that the data contains some meta-information like channel- or feature names.

Many of the nodes are trainable even though don’t really learn a model (they don’t process the data anyway). The reason for that is that they require information about the class labels for creating the plots.


average_and_feature_vis Visualize average of time series and time domain features
base Base class for visualization nodes
eeg_visualization Visualization of time series based on EEG signals to combine it with mapping to real sensor positions
feature_vector_vis Visualize FeatureVector elements
time_series_vis Visualize data in time-amplitude or time-frequency representations