96 lines
2.0 KiB
C
96 lines
2.0 KiB
C
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#include <lilgp.h>
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#include <math.h>
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sel_context *select_sigma_context (int op,
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sel_context *sc,
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population *p,
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char *string )
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{
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interval_data *id;
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int i, j = 0;
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double average;
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double std;
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double n;
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switch ( op )
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{
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case SELECT_INIT:
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sc = (sel_context *)MALLOC ( sizeof ( sel_context ) );
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sc->p = p;
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sc->select_method = select_interval;
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sc->context_method = select_boltzman_context;
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/* the interval_data structure (used with select_interval()) is
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essentially a list of interval widths and indices for each
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individual. */
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id = (interval_data *)MALLOC ( sizeof ( interval_data ) );
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id->ri = (reverse_index *)MALLOC ( (p->size+1) *
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sizeof ( reverse_index ) );
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id->total = 0.0;
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id->count = p->size;
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id->ri[j].fitness = 0.0;
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id->ri[j].index = -1;
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++j;
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/* Compute average */
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average=0;
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for (i=0;i<p->size;++i)
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{
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average += p->ind[i].a_fitness;
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}
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average/=p->size;
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/* Compute Standard Deviation */
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if (p->size<=1)
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std=0;
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else
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{
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std=0;
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for(i=0;i<p->size;i++)
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{
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std += (p->ind[i].a_fitness - average) *
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(p->ind[i].a_fitness - average);
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}
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std/=(p->size-1);
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std=sqrt(std);
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}
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for (i=0; i< p->size; ++i)
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{
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if (std==0)
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{
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n=1.0;
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}
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else
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{
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n= 1 + (p->ind[i].a_fitness - average)/(2 * std);
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}
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id->total += n;
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id->ri[j].fitness = id->total;
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id->ri[j].index = i;
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++j;
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}
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sc->data = (void *)id;
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return sc;
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break;
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case SELECT_CLEAN:
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id = (interval_data *)(sc->data);
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FREE ( id->ri );
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FREE ( sc->data );
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FREE ( sc );
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return NULL;
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break;
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}
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return NULL;
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}
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