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prefuse Tutorial: Scatter Plot

The documentation available for prefuse is quite sparse, it consists mainly of the JavaDoc API documentation and demo source code. Even though the demo source code provides as good starting point (cp. [Heer et al., 1995] ), in my opinion the examples are overly complex for beginners.

Therefore, this tutorial starts with the minimum source code to create a scatter plot and incrementally adds features. Further, it discusses an axis-based visualization technique, whereas the documentation of prefuse focuses on graph visualization.

Phase 0: Infrastructure

Here we create the outline of our demo application. It is designed very simple and consists of four static methods:

  • private static Table generateTable()
    • prepare a prefuse data table with some hard coded values (see below)
  • private static JComponent createVisualization(Table data)
    • now this is only some dummy code, but in the following phases our prefuse code will be inserted here.
  • private static void createAndShowGUI(JComponent display)
    • some basic Swing code to set up a window for the demo application
  • public static void main(String[] args)
    • runs these three methods

This shows, how we create a data table for our tutorial. We use hard coded values so that the demo application stays self-contained. It would be easy to replace this method by a call to prefuse's DelimitedTextTableReader.

	private static Table generateTable() {
		Table table = new Table();
		// use a calendar for input of human-readable dates  
		GregorianCalendar cal = new GregorianCalendar();
		// set up table schema
		table.addColumn("Date", Date.class);
		table.addColumn("BMI", double.class);
		table.addColumn("NBZ", int.class);
		table.addColumn("Insult", String.class);
		cal.set(2007, 11, 23);
		table.set(0, 0, cal.getTime());
		table.set(0, 1, 21.0);
		table.set(0, 2, 236);
		table.set(0, 3, "F");
		cal.set(2008, 6, 22);
		table.set(1, 0, cal.getTime());
		table.set(1, 1, 35.8);
		table.set(1, 2, 400);
		table.set(1, 3, "F");
		cal.set(2009, 3, 8);
		table.set(2, 0, cal.getTime());
		table.set(2, 1, 28.8);
		table.set(2, 2, 309);
		table.set(2, 3, "T");
		return table;

Source Code

Phase 1: Essentials

Next, we extend the method createVisualization(Table) and add the minimal source code to show a scatter plot.

First, we need to create instances of Visualization and Display and link these with each other and the data table.

		Visualization vis = new Visualization();
		Display display = new Display(vis);
		vis.add("data", data);

Second, we create a AxisLayout for the x axis and another one for the y axis. When these layouts are run, they will set the x and coordinate of all visual items.

		AxisLayout x_axis = new AxisLayout("data", "NBZ", Constants.X_AXIS,
		AxisLayout y_axis = new AxisLayout("data", "BMI", Constants.Y_AXIS,

Third, a ColorAction will set the color of all visual items to blue.

		ColorAction color = new ColorAction("data", VisualItem.STROKECOLOR,
				ColorLib.rgb(100, 100, 255));

Fourth, these actions are combined to an ActionList and linked to the Visualization.

		ActionList draw = new ActionList();
		vis.putAction("draw", draw);

Finally, we run this ActionList and return the Display so that it can be shown in the window."draw");
		return display;

This is the resulting visualization:

Source Code

Phase 2: Refinements

Now, we will add some more features to the scatter plot:

First, we want smaller shapes. For this, we create a ShapeRenderer with default size 7.

		vis.setRendererFactory(new DefaultRendererFactory(
						new ShapeRenderer(7)));

Second, we add a DataShapeAction, so that our nominal parameter is shown as star or ellipse.

		int[] palette = { Constants.SHAPE_STAR, Constants.SHAPE_ELLIPSE };
		DataShapeAction shape = new DataShapeAction("data", "Insult", palette);

Third, the new action needs to be included in the action list.

We also add a RepaintAction, just to make sure that the visualization is repainted after the other actions.

		draw.add(new RepaintAction());

Fourth, we set the Display to high quality (anti-aliasing), and change its size.

We also add an empty border, so that visual items at the edge of the visualization are better visible.

		display.setSize(700, 450);
		display.setBorder(BorderFactory.createEmptyBorder(15, 30, 15, 30));

Finally, we add a ToolTipControl to show the values of the two numeric parameters.

		String[] tooltipparams = { "NBZ", "BMI" };
		ToolTipControl ttc = new ToolTipControl(tooltipparams);

This is the resulting visualization:

Source Code

Phase 3: Axis Labels and Grid Lines

In this step, we will add axis labels and grid lines to the visualization.

First, we have to use a new RendererFactory. Visual items from our data table will still be rendered by the ShapeRenderer, but for axis labels we will use AxisRenderer.

		vis.setRendererFactory(new RendererFactory() {
			AbstractShapeRenderer sr = new ShapeRenderer(7);
			Renderer arY = new AxisRenderer(Constants.FAR_LEFT,
			Renderer arX = new AxisRenderer(Constants.CENTER,
			public Renderer getRenderer(VisualItem item) {
				return item.isInGroup("ylab") ? arY
						: item.isInGroup("xlab") ? arX : sr;

Second, we create two instances of AxisLabelLayout and initialize them with the AxisLayouts.

When these layout actions are run, they generate new visual items for the axis labels.

		AxisLabelLayout x_labels = new AxisLabelLayout("xlab", x_axis);
		AxisLabelLayout y_labels = new AxisLabelLayout("ylab", y_axis);

Third, the new layout actions needs to be included in the action list.


Fourth, we create an ItemSorter, so that data items will be displayed in front of the grid lines.

		display.setItemSorter(new ItemSorter() {
			public int score(VisualItem item) {
				int score = super.score(item);
				if (item.isInGroup("data"))
				return score;

This is the resulting visualization:

Source Code

java/prefuse-scatterplot.1249638678.txt · Last modified: 2009/08/11 09:53 (external edit)

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