Program for Converting Covariance Matrices to Diagonal Covariance Vectors
* FOR LITTLE ENDIAN

usage: cov2dia [options...] [infile] [outfile]
options:
        -dim dim[24]                    : dimension of vector
        -dia2cov                        : change diagonal vectors into diagonal
matrices
        -sd                             : standard deviation
        -nmsg                           : no message
        -help                           : display this message

The input file is a binary file of covariance matrices. The output
file is a binary file of diagonal covariance vectors. The size of
covariance matrices is [dimension x class]-by-[dimension], and the
size of diagonal covariance vectors is [class]-by-[dimension]. If -sd
is used, the output is standard deviation vectors.

The number of dimensions is changed by -dim.

An inverse process, i.e., converting diagonal covariance vectors
into covariance matrices, is performed by -dia2cov.

Binary data has double-type format.

Some messages are printed while executing this program. If you
don't need those messages, use -nmsg.


<EXAMPLE>
% cov2dia \
	-dim 29 \
	-sd \
	-nmsg \
	input.cov \
	output.sd


Tomoki Toda (tomoki@ics.nitech.ac.jp)


==================================================
The current copyright is

/*********************************************************************/
/*                                                                   */
/*            Nagoya Institute of Technology, Aichi, Japan,          */
/*       Nara Institute of Science and Technology, Nara, Japan       */
/*                                and                                */
/*             Carnegie Mellon University, Pittsburgh, PA            */
/*                      Copyright (c) 2003-2004                      */
/*                        All Rights Reserved.                       */
/*                                                                   */
/*  Permission is hereby granted, free of charge, to use and         */
/*  distribute this software and its documentation without           */
/*  restriction, including without limitation the rights to use,     */
/*  copy, modify, merge, publish, distribute, sublicense, and/or     */
/*  sell copies of this work, and to permit persons to whom this     */
/*  work is furnished to do so, subject to the following conditions: */
/*                                                                   */
/*    1. The code must retain the above copyright notice, this list  */
/*       of conditions and the following disclaimer.                 */
/*    2. Any modifications must be clearly marked as such.           */
/*    3. Original authors' names are not deleted.                    */
/*                                                                   */    
/*  NAGOYA INSTITUTE OF TECHNOLOGY, NARA INSTITUTE OF SCIENCE AND    */
/*  TECHNOLOGY, CARNEGIE MELLON UNIVERSITY, AND THE CONTRIBUTORS TO  */
/*  THIS WORK DISCLAIM ALL WARRANTIES WITH REGARD TO THIS SOFTWARE,  */
/*  INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, */
/*  IN NO EVENT SHALL NAGOYA INSTITUTE OF TECHNOLOGY, NARA           */
/*  INSTITUTE OF SCIENCE AND TECHNOLOGY, CARNEGIE MELLON UNIVERSITY, */
/*  NOR THE CONTRIBUTORS BE LIABLE FOR ANY SPECIAL, INDIRECT OR      */
/*  CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM   */
/*  LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT,  */
/*  NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN        */
/*  CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.         */
/*                                                                   */
/*********************************************************************/
/*                                                                   */
/*          Author :  Tomoki Toda (tomoki@ics.nitech.ac.jp)          */
/*          Date   :  June 2004                                      */
/*                                                                   */
/*-------------------------------------------------------------------*/
/*                                                                   */
/*  Converting Covariance Matrices to Diagonal Covariance Vectors    */
/*                                                                   */
/*-------------------------------------------------------------------*/
