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/*
bpro.c
*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
*
* Part of: Any back-propagation-ANN-oriented software
*
* Author: E.BERTIN (IAP)
*
* Contents: Routines for BP-neural network management ("read-only"
* mode).
*
* Requirements: The LDACTools.
*
* Last modify: 13/12/2002
*
*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
*/
#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 "fits/fitscat.h"
#include "bpro.h"
/******************************** play_bpann *********************************/
/*
Single forward pass through the ANN.
*/
void play_bpann(bpannstruct *bpann, NFLOAT *invec, NFLOAT *outvec)
{
NFLOAT u, *neuroni,*neuronj, *weight;
int i,j,l,lp,ll, lflag;
ll = bpann->nlayers-1;
memcpy(bpann->neuron[0], invec, bpann->nn[0]*sizeof(float));
lflag = bpann->linearoutflag;
for (lp=0,l=1; lp<ll; l++, lp++)
{
neuronj = bpann->neuron[l];
weight = bpann->weight[lp];
for (j=bpann->nn[l]; j--; neuronj++)
{ /* note we don't touch the "bias" neuron (=-1) */
neuroni = bpann->neuron[lp];
u = *(weight++)**(neuroni++);
for (i=bpann->nn[lp]; i--;) /* The last one is the bias */
u += *(weight++)**(neuroni++);
if (l == ll)
*(outvec++)= lflag?u:SIGMOID(u);
else
*neuronj = SIGMOID(u);
}
}
return;
}
/******************************* loadtab_bpann *******************************/
/*
Load the relevant ANN structure (using the LDACTools).
*/
bpannstruct *loadtab_bpann(tabstruct *tab, char *filename)
{
bpannstruct *bpann;
keystruct *key;
char *head, str[80];
int l;
/* OK, we now allocate memory for the ANN structure itself */
QCALLOC(bpann, bpannstruct, 1);
/* Load important scalars (which are stored as FITS keywords) */
head = tab->headbuf;
if (fitsread(head, "BPNLAYER", &bpann->nlayers, H_INT, T_LONG) != RETURN_OK)
error(EXIT_FAILURE, "*Error*: incorrect BP-ANN header in ", filename);
if (fitsread(head, "BPLINEAR",&bpann->linearoutflag, H_INT,T_LONG)!=RETURN_OK)
bpann->linearoutflag = 0;
/* Load all vectors!! */
read_keys(tab, NULL, NULL, 0, NULL);
/* Now interpret the result */
if (!(key = name_to_key(tab, "NNEUR_PER_LAYER")))
error(EXIT_FAILURE, "*Error*: incorrect BP-ANN header in ", filename);
bpann->nn = key->ptr; key->ptr = 0;
QMALLOC(bpann->neuron, NFLOAT *, bpann->nlayers);
QMALLOC(bpann->weight, NFLOAT *, bpann->nlayers-1);
for (l=0; l<bpann->nlayers-1; l++)
{
QMALLOC(bpann->neuron[l], NFLOAT, bpann->nn[l]+1);
bpann->neuron[l][bpann->nn[l]] = -1.0;
sprintf(str, "WEIGHT_LAYER%d", l+1);
if (!(key = name_to_key(tab, str)))
error(EXIT_FAILURE, "*Error*: incorrect BP-ANN header in ", filename);
bpann->weight[l] = key->ptr; key->ptr = 0;
}
QMALLOC(bpann->neuron[l], NFLOAT, bpann->nn[l]); /* no bias in this layer */
return bpann;
}
/******************************** free_bpann *********************************/
/*
Free all memory modules allocated for a Back-Propagation ANN structure.*/
void free_bpann(bpannstruct *bpann)
{
int i;
/* Loop over the "true" layers */
for (i=0; i<bpann->nlayers-1; i++)
{
free(bpann->neuron[i]);
free(bpann->weight[i]);
}
free(bpann->neuron[i]); /* Because of the input layer */
/* Then free pointers of pointers */
free(bpann->neuron);
free(bpann->weight);
free(bpann->nn);
/* And finally free the ANN structure itself */
free(bpann);
return;
}