Re: 2D cluster of 2D matrix in Octave?

[Paul Kienzle]

The clustering algorithms you will have to find/write yourself.  Please
include them in octave-forge (http://octave.sf.net).

It is possible to produce plots like that of Matlab's dendrogram in gnuplot:

        x=[1 1 2 2; 1.5 1.5 4 4; 3 3 5 5];
        y=[0 1 1 0; 1.0 3.0 3 2; 0 2 2 0];
        ticlab = [ 13, 11, 21, 8 ];
        ticpos = [ 1, 2, 3, 5];
        tics = sprintf(' "%g" %g,', [ticlab;ticpos]);
        eval(["gset xtics (",tics(2:length(tics)-1),")"]);
        axis([0 6 0 4])
        plot(x',y',"b;;");

But you will have to reset the axis and tic labels when you are done:

        gset xtics autofreq
        axis;

You can use imagesc with with appropriate colormap to view a
matrix.  E.g.,

        r=[linspace(0,1,32)';ones(32,1)];
        g=[linspace(0,1,32)';linspace(1,0,32)'];
        b=[linspace(1,0,32)';zeros(32,1);];
        colormap([r,g,b]);
        x = linspace(0,1,300);
        imagesc(x(ones(20,1),:));

Using epstk you can produce nice printed plots of images with all the
usual plot annotations.

Hope this helps.

Paul Kienzle
address@hidden

On Thu, Apr 18, 2002 at 06:48:22PM -0500, Mark Wall wrote:
> Hello!
> 
> I would love to use Octave for the following 2 tasks, but am unable 
> to determine if Octave will work.  My primary question- is this 
> possible in Octave?  Secondary- if yes, how?
> 
> We routinely use MatLab with the Statistics Tool Box to manipulate 
> and plot a 2 dimensional matrix (m x n) of real numbers.  If you 
> think of each dimension as an array of vectors (e.g. a collection of 
> m vectors (each n-dimensions), we 1) cluster these (and generate a 
> dendrogram) for both dimensions as below using a city-block distance 
> measure:
> 
> original matrix with labels
> ----------------
>     W X Y Z
> A  0 1 0 0
> B  0 1 0 1
> C  5 0 0 0
> D  0 0 0 2
> E  5 0 0 0
> 
> Clustered matrix
> ----------------
>     W Y X Z
> E  5 0 0 0
> C  5 0 0 0
> A  0 0 1 0
> B  0 0 1 1
> D  0 0 0 2
> 
> In reality, m and n are between 50 and 1000 so we 2) display these 
> matrices as an x-y-color plot for easy visualization.  Think of this 
> as a square frame with each pixel representing a matrix element.  The 
> values are represented by a color continuum (dark blue = low values, 
> through yellow to red = high values).  I can provide a JPEG if 
> necessary.
> 
> With large matrices, we isolate sub-clusters by creating new matrices 
> that are the appropriate slices of the original matrix and then 
> repeat steps 1 and 2 on the sub-matrices.
> 
> 
> Thank you,
> 
> Mark Wall
> ---------
> HHMI/UT Southwestern Medical Center
> 5323 Harry Hines Blvd.
> Dallas, Texas  75390-9050
> USA
> 214.648.5050
> 
> 
> 
> -------------------------------------------------------------
> Octave is freely available under the terms of the GNU GPL.
> 
> Octave's home on the web:  http://www.octave.org
> How to fund new projects:  http://www.octave.org/funding.html
> Subscription information:  http://www.octave.org/archive.html
> -------------------------------------------------------------
> 



-------------------------------------------------------------
Octave is freely available under the terms of the GNU GPL.

Octave's home on the web:  http://www.octave.org
How to fund new projects:  http://www.octave.org/funding.html
Subscription information:  http://www.octave.org/archive.html
-------------------------------------------------------------