How to build a data matrix
Custom case, trial, profile, and surface variables, as well as bullets, are usually based on the combination of a data matrix and a corresponding selection mask. Thus, creating a data matrix and a selection mask is the first step when evaluating any type of custom variable. Here are the steps involved in accomplishing this:
- The Matrix statement generates a data matrix. In this matrix, each trial of the analyzed case document is represented by a column whose cells correspond to the data points of the trial. The number of rows in the data matrix equals the number of data points in the largest trial of the case document. Columns of shorter trials are padded with empty cells. The values assigned to the cells of the data matrix depend on the parameters you specify for the Matrix statement. They may represent anything like current speed, x- or y-position, distance to the border of the maze, etc. Wintrack maintains a single active data matrix in memory which will be overwritten each time you use the Matrix statement.
- Once the active data matrix is built, you can apply transformations to it using the Transform statement. For example you can calculate running averages over the cells in each column or you can take absolute values of all cells, etc.
- Next, you build a selection mask for the active data matrix using
the Exclude and Include
statements. A selection mask is a second matrix in which the selection
state of each cell of the active data matrix is represented by a
binary On/Off value. In the simplest case, you use the Include statement
to build a selection mask which selects all cells the data matrix. But
you may use any combination of Exclude
and Include statements to select only
a subset of cells, for example only those with values smaller than a
given threshold, etc. Wintrack maintains one active selection mask in
memory, to which all Exclude or Include
statements are applied. The active selection mask is not affected
by the Matrix and Transform
statements:
- You can replace or transform the active data matrix while working on a selection mask to base the mask on multiple aspects of the data. For example you may use a first data matrix to exclude all points that have a local speed below a given threshold and then a second data matrix to include only those of these points that lie within a given distance from the border of the arena.
- On the other hand, you can reuse the same selection mask with any number of data matrices created with subsequent Matrix and Transform statements.
- As soon as a data matrix and a selection mask are available, you can use them to define either profile, trial, case or surface variables. Or you may use the data matrix to add bullets to the paths displayed in the case window.
Additional information...
- Using the Memory statement you can build collections of data matrices and selection masks for later reuse in other variables.
- Managing custom variable definition files provides general information on the management of custom variable definition files.
- The Flowchart of advanced data analysis gives a synopsis of data and variable types.
- There is a topic describing how to build a custom variable definition file.
- There is a list of all available variable definition statements.
- See Analyze Case Document command for basic information on that command.
- Inside case documents provides advanced information on case documents.
