void epoch(map *m, Inputs *in, int iteration, double timeCst, double *epsilon, int numEpoch)
{
register int i;
double radius;
int dst;
double theta;
radius = max_dbl(m->mapRadius * exp(-iteration / timeCst), 1);
radius *= radius;
neuron *n = find_bmu(m, in);
for(i = 0; i < m->latice_size; ++i)
{
dst = neuron_distance_to(&(m->lattice[i]), n);
if(dst < radius)
{
theta = exp(-dst / (2 * radius));
adjust_weights(&(m->lattice[i]), in, *epsilon, theta);
}
*epsilon = EPSILON * exp((double)-iteration / (numEpoch- iteration));
}
}
double log_sum(const double *ptr, const size_t size) {
if (size == 1) /* do special case faster */
return *ptr;
else {
const double max = *max_dbl(ptr, size);
const double *end = ptr + size;
double sum = 0;
assert(size > 0);
for (; ptr != end; ++ptr)
sum += xexp(*ptr - max);
return xlog(sum) + max;
}
}
