Programs

STRUCTMAN

Download Windows Version
Mac Version Coming Soon
 
For computing the structural manifold of categorical stimuli defined over continuous, binary, and more generally, n-ary dimensions.
 
As input, this program uses Excel files formatted such that each category member is a line, each dimension is a column, and each cell contains a category member's value on a dimension. This example file represents a Type II category from the 32[4] category structure family first examined by Shepard, Hovland, and Jenkins in 1961. For more information on categories in terms of GIST, see Vigo, 2013 under Publications.

GRIT

Download Windows Version
Mac Version Coming Soon

For computing relative degrees of representational information as defined in RIT and GRIT (Generalized Representational Information Theory).

As input, this program uses Excel files formatted such that each category member is a line, each dimension is a column, and each cell contains a category member's value on a dimension. See the Structman Program above for an example. To compute representational information for a removed subset of your category, you can either enter the row numbers representing the objects you want to remove separated by a space, input an Excel file for the reduced category, choose to compute the representational information for all objects systematically, or choose to compute the representational information for each subset of objects systematically. (Please note that the last option is computationally intensive for categories >12 members -- in our tests, a 15 member category took 16.5 minutes to finish. We hope to improve the program's efficiency and stability for large categories in the future.)

STRUCTGEN

Download

STRUCTGEN (structure generator) provides the user with the capability to quickly generate structures and instances, and sample from them, within a given Dn[p] structure family, to include families defined over dimensions of n-ary values.

SMAP

COMING SOON

The SMAP (structural manifold analysis platform) for multivariate data analysis.