After a couple of hacks to make my python installation work with R, I finally managed to export an heatmap of the cereals task. The map is upside down, but shows in essence that the most populated part of the map is the upper-central.

The plan is to do the same for the number of items selected in relation to the total in the spot. This might show a different trend of the usage. Maybe parts of the map that have been “explored” less were the most important in terms of the number of correct items retrieved in that spot. We will see…

Useful links:

[1] A nice tutorial on how to draw an heatmap with Python and R;

[2] Draw a Heat Map, the R manual page.

Tags: clustering, information visualization, map algorithms, maps