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/*
neurro.c
*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
*
* Part of: A program using neural networks.
*
* Author: E.BERTIN (IAP)
*
* Contents: run only version of the neural network.
*
* Last modify: 26/11/2003
*
*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
*/
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "define.h"
#include "globals.h"
#include "prefs.h"
#include "neurro.h"
brainstruct *brain;
/******************************** neurinit **********************************/
/*
Initialization of the "brain".
*/
void neurinit()
{
QMALLOC(brain, brainstruct, 1);
return;
}
/********************************* neurend **********************************/
/*
Close the "brain".
*/
void neurclose()
{
free(brain);
return;
}
/******************************** neurresp **********************************/
/*
Neural network response to an input vector.
*/
void neurresp(double *input, double *output)
{
int i, j, l, lastlay = brain->layersnb-1;
double neursum;
for (i=0; i<brain->nn[0]; i++)
brain->n[0][i] = input[i]*brain->inscale[i] + brain->inbias[i];
for (l=0; l<lastlay; l++)
for (j=0; j<brain->nn[l+1]; j++)
{
neursum = brain->b[l][j];
for (i=0; i<brain->nn[l]; i++)
neursum += brain->w[l][i][j] * brain->n[l][i];
brain->n[l+1][j] = f(neursum);
}
for (i=0; i<brain->nn[lastlay]; i++)
output[i] = (brain->n[lastlay][i]-brain->outbias[i])
/ brain->outscale[i];
return;
}
/************************************ f *************************************/
/*
Sigmoid function for a neural network.
*/
double f(double x)
{
return 1.0 / (1.0 + exp(-x));
}
/********************************* getnnw ***********************************/
/*
Read the NNW table that contains the weights.
*/
void getnnw()
{
FILE *infile;
int i, j, k, step;
char str[MAXCHAR], *sstr, *null;
if ((infile = fopen(prefs.nnw_name,"r")) == NULL)
error(EXIT_FAILURE,"*ERROR*: can't read ", prefs.nnw_name);
fgets(str, MAXCHAR, infile);
if (strncmp(str,"NNW",3))
error(EXIT_FAILURE, prefs.nnw_name, " is NOT a NNW table!");
step = 1;
i=j=0; /* To avoid gcc -Wall warnings */
while (fgets(str, MAXCHAR, infile))
{
sstr = &str[(int)strspn(str," \t")];
if (sstr[0]!=(char)'#' && sstr[0]!=(char)'\n')
{
null = sstr;
switch(step)
{
case 1: brain->layersnb = atoi(strtok(sstr, " \t\n"));
for (i=0; i<brain->layersnb; i++)
brain->nn[i] = atoi(strtok(NULL, " \t\n"));
step++;
break;
case 2: for (i=0; i<brain->nn[0]; i++)
{
brain->inbias[i] = atof(strtok(null, " \t\n"));
null = NULL;
}
step++;
break;
case 3: for (i=0; i<brain->nn[0]; i++)
{
brain->inscale[i] = atof(strtok(null, " \t\n"));
null = NULL;
}
i=j=0;
step++;
break;
case 4: if (j == brain->nn[i+1])
{
j = 0;
i++;
}
if (i < brain->layersnb-1)
{
for (k=0; k<brain->nn[i]; k++)
{
brain->w[i][k][j] = atof(strtok(null, " \t\n"));
null = NULL;
}
brain->b[i][j] = atof(strtok(NULL, " \t\n"));
j++;
break;
}
else
step++;
case 5: for (i=0; i<brain->nn[brain->layersnb-1]; i++)
{
brain->outbias[i] = atof(strtok(null, " \t\n"));
null = NULL;
}
step++;
break;
case 6: for (i=0; i<brain->nn[brain->layersnb-1]; i++)
{
brain->outscale[i] = atof(strtok(null, " \t\n"));
null = NULL;
}
step++;
break;
default:error(EXIT_FAILURE, "*Error*: inconsistency in ", prefs.nnw_name);
}
}
}
fclose(infile);
return;
}
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