Visualizes topics in a 2D map

`visualizetopics( DP,ALPHA,S,VIZMODE )` takes the topic strings in `S` and the document-topic count matrix `DP` where `DP(i,j)` contains the number of times a word in document `i` has been assigned to topic `j`. These counts are transformed to probability distributions over documents for each topic. For each topic pair, the symmetrized
Kullback Leibler distance between document distributions is calculated. Classical multidimensional scaling is used to visualize
all pairwise topic distances in a 2D map.

Notes:

The variable `VIZMODE` can be set to 'horizontal' or 'vertical' which determines the way the topics are displayed.

The variable `ALPHA` is the hyperparameter on the topic distributions needed to calculate the topic-document distributions calculate prob distribution
over documents for each topic