A tiny C library for managing SOM (Self-Organizing Maps) neural networks
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/*
* =====================================================================================
*
* Filename: example.c
*
* Description: Examle file to benchmark fsom library.
*
* Version: 0.1
* Revision: none
* Compiler: gcc
*
* Author: BlackLight (http://blacklight.gotdns.org), <blacklight@autistici.org>
* Contributor: evilsocket (http://www.evilsocket.net), <evilsocket@gmail.com>
* Licence: BSD-3
*
* =====================================================================================
*/
/*
* Copyright (c) 2010, Fabio "BlackLight" Manganiello
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of the the developers nor the
* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE DEVELOPERS BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include "fsom.h"
#include <alloca.h>
#include <stdio.h>
#include <sys/time.h>
static unsigned long prev_uticks = 0;
static unsigned long get_uticks(){
struct timeval ts;
gettimeofday(&ts,0);
return ((ts.tv_sec * 1000000) + ts.tv_usec);
}
static void start_timer(){
prev_uticks = get_uticks();
}
static void print_timing( const char *msg ){
#define MS_DELTA (1000.0)
#define SS_DELTA (MS_DELTA * 1000.0)
#define MM_DELTA (SS_DELTA * 60.0)
#define HH_DELTA (MM_DELTA * 60.0)
double ticks = get_uticks() - prev_uticks;
if( ticks < MS_DELTA ){
printf( "%s\t : %lf us\n", msg, ticks );
}
else if( ticks < SS_DELTA ){
printf( "%s\t : %lf ms\n", msg, ticks / MS_DELTA );
}
else if( ticks < MM_DELTA ){
printf( "%s\t : %lf s\n", msg, ticks / SS_DELTA );
}
else if( ticks < HH_DELTA ){
printf( "%s\t : %lf m\n", msg, ticks / MM_DELTA );
}
else{
printf( "%s\t : %lf h\n", msg, ticks / HH_DELTA );
}
start_timer();
}
#define VECTORS 10
#define INPUTS 20
#define OUT_ROWS 10
#define OUT_COLS 10
#define TRAIN_STEPS 30
int
main ( int argc, char *argv[] )
{
size_t i, j, x, y;
double step = 0.0;
double **data = NULL;
som_network_t *net = NULL;
data = (double **) alloca ( INPUTS * sizeof ( double* ));
for ( i=0, step = 0.0; i < INPUTS; ++i, step += 0.1 )
{
data[i] = (double *) alloca ( VECTORS * sizeof ( double ));
for ( j=0; j < VECTORS; ++j )
{
data[i][j] = step;
}
}
start_timer();
net = som_network_new ( INPUTS, OUT_ROWS, OUT_COLS );
if ( !net )
{
printf( "ERROR: som_network_new failed.\n" );
return 1;
}
print_timing( "Network Creation" );
som_init_weights ( net, data, INPUTS );
som_train ( net, data, VECTORS, TRAIN_STEPS );
print_timing( "Network Training" );
for ( i=0; i < INPUTS; ++i )
{
som_set_inputs ( net, data[i] );
som_get_best_neuron_coordinates ( net, &x, &y );
// printf ( "best coordinates [%u]: %u,%u\n", i, x, y );
}
print_timing( "Input Recognition" );
som_network_destroy ( net );
print_timing( "Network Destruction" );
}