https://github.com/tompollard/sammon

Sammon mapping in Python
https://github.com/tompollard/sammon

data visualization

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Sammon mapping in Python

• Host: GitHub
• URL: https://github.com/tompollard/sammon
• Owner: tompollard
• Created: 2014-04-18T13:01:50.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2019-06-27T01:06:33.000Z (over 5 years ago)
• Last Synced: 2024-10-31T19:42:33.855Z (2 months ago)
• Topics: data, visualization
• Language: Python
• Size: 19.5 KB
• Stars: 32
• Watchers: 3
• Forks: 18
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

        
Sammon mapping in Python

========================

Date: 18 April 2014

sammontest.py

-------------

Run sammontest.py() with no arguments to test sammon.py

on Fisher's iris dataset. You should get an output image 

as the one shown below:

![alt tag](http://i.imgur.com/ngfNeEn.png)

sammon.py

---------

Simple python implementation of Sammon's non-linear mapping 

algorithm [1]. Perform Sammon mapping on dataset x

y = sammon(x) applies the Sammon nonlinear mapping procedure on

multivariate data x, where each row represents a pattern and each column

represents a feature.  On completion, y contains the corresponding

co-ordinates of each point on the map.  By default, a two-dimensional

map is created.  Note if x contains any duplicated rows, SAMMON will

fail (ungracefully). 

[y,E] = sammon(x) also returns the value of the cost function in E (i.e.

the stress of the mapping).

An N-dimensional output map is generated by y = sammon(x,n) .

A set of optimisation options can be specified using optional

arguments, y = sammon(x,n,[OPTS]):

* maxiter        - maximum number of iterations

* tolfun         - relative tolerance on objective function

* maxhalves      - maximum number of step halvings

* input          - {'raw','distance'} if set to 'distance', X is interpreted as a matrix of pairwise distances.

* display        - 0 to 2. 0 least verbose, 2 max verbose.

* init           - {'pca', 'random'}

The default options are retrieved by calling sammon(x) with no

parameters.

Authors

-------

Tom J. Pollard (https://twitter.com/tompollard)

Ported from MATLAB implementation by 

  Gavin C. Cawley and Nicola L. C. Talbot

References

----------

[1] Sammon, John W. Jr., "A Nonlinear Mapping for Data

    Structure Analysis", IEEE Transactions on Computers,

    vol. C-18, no. 5, pp 401-409, May 1969.

Copyright

---------

Copyright   : (c) Dr Gavin C. Cawley, November 2007.

This program is free software; you can redistribute it and/or modify

it under the terms of the GNU General Public License as published by

the Free Software Foundation; either version 2 of the License, or

(at your option) any later version.

This program is distributed in the hope that it will be useful,

but WITHOUT ANY WARRANTY; without even the implied warranty of

MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

GNU General Public License for more details.

You should have received a copy of the GNU General Public License

along with this program; if not, write to the Free Software

Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA