005_topic_similarity_matrix.r

#' Calculate similarity matrix 
#' Shows which documents are similar to each other
#' by their proportions of topics. Based on Matt Jockers' method 

library(cluster)
topic_df_dist <-  as.matrix(daisy(t(topic_docs), metric =  "euclidean", stand = TRUE))
# Change row values to zero if less than row minimum plus row standard deviation
# keep only closely related documents and avoid a dense spagetti diagram 
# that's difficult to interpret (hat-tip: http://stackoverflow.com/a/16047196/1036500)
topic_df_dist[ sweep(topic_df_dist, 1, (apply(topic_df_dist,1,min) + apply(topic_df_dist,1,sd) )) > 0 ] <- 0