Making a Multi-D Scatter Plot

In this tutorial example, we'll plot the points from a 4-D Gaussian distribution as a scatter plot. You will learn how to set up a scatter plot when the coordinates of the data are organized as columns in a single table, and how such plots can be interactively pivoted to view the scatter points from each dimension.

First, let's create the data to be plotted. For this, we'll define a 4-D gaussian distribution. Follow these steps:

1. Start with a fresh model.

2. In the model's object window, fill in the title and description.

3. Close the object window.

4. Select File->Add Library... -> Multivariate Distributions.ana

5. Create these two indexes:

Index Dim := [1,2,3,4]
Index Dim2 := CopyIndex(Dim)

7. Define the covariance matrix. Create a variable named covar and set the definition type to Table. Select the Dim and Dim2 indexes and fill in the edit table with a covariance matrix:

8. Define the Gaussian distribution. Create a chance variable node named X and set the definition to:

Gaussian( 0, covar, Dim, Dim2 )

9. Select Result-> Uncertainty Options... and set the sample size to 1000. (so we have more points on our plot)

10. Select X and show Result->Sample. Switch to graph mode if not already.

11. Switch to table view to examine the actual data. For convenience, pivot so that Index Dim forms the columns, Run the rows.

= Setting the Coordinate Index

At this point you have defined some data to graph, and are viewing the default graph.