PCA Data

This plot contains two different modes that you can select from in the Common settings pane.

  • Eigenvector: Displays a bar chart plot with the current eigenvector of the Principal Component Analysis (PCA).

  • Load matrix: Displays a matrix grid plot with every column containing the values of one eigenvector of the PCA analysis.

Preferences

The following preference settings are available:

  • Appearance

    • Font size

    • Line width

    • Enable axes

  • Axis Ranges

  • Labels

  • Palette

For more details, see Plot Preference Settings.

Python Scripting

Create Visual

Creates a PCA data plot using data with data_id. 

    pca = Visuals.PCAData(Id("PCA Data"), data_id)

Add to Postprocessing

Adds PCA data plot in postprocessing to control_container, using the specified relative positioning. 

    control_container.add_control (
        pca,
        True,
        RELATIVE_POSITIONING,
        0, 0, 1/2., 70/100.
    )