# distMatrixShow

## PURPOSE

Useful visualization of a distance matrix of clustered points.

## SYNOPSIS

function [D, Dsm] = distMatrixShow( D, IDX, show )

## DESCRIPTION

     Useful visualization of a distance matrix of clustered points.

     D is sorted into k blocks, where the ith block contains all the points in
     cluster i. When D is displayed the blocks are shown explicitly.  Hence
     for a good clustering (under a spherical gaussian assumption) the
     'diagonal' blocks ought to be mostly dark, and all other block ought to be
     relatively white.  One can thus quickly visualize the quality of the
     clustering, or even how clusterable the points are.  Outliers (according
     to IDX) are removed from D.

     USAGE
      [D, Dsm] = distMatrixShow( D, IDX, [show] )

     INPUTS
      D       - nxn distance matrix
      IDX     - cluster membership [see kmeans2.m]
      show    - [1] will display results in figure(show)

     OUTPUTS
      D       - sorted nxn distance matrix
      Dsm     - sorted and smoothed nxn distance matrix

     EXAMPLE
      % not the best example since points are already ordered
      [X,IDX] = demoGenData(100,0,5,2,10,2,0);
      distMatrixShow( pdist2(X,X), IDX );

     See also VISUALIZEDATA, KMEANS2

     Piotr's Image&Video Toolbox      Version 2.0
     Copyright 2008 Piotr Dollar.  [pdollar-at-caltech.edu]
     Please email me if you find bugs, or have suggestions or questions!
     Licensed under the Lesser GPL [see external/lgpl.txt]

## CROSS-REFERENCE INFORMATION

This function calls:

- IDX2order Converts class labels into an ordering.
- im Function for displaying grayscale images.

This function is called by:

- demoCluster Clustering demo.