void Source::reproduction(const gsl_rng *rand){
assign_fitness();
gsl_ran_multinomial(rand, pop_size, pop_size, fitness, off_numbers);
next_generation(rand);
mutate_population(rand);
}
//~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~;~//
void Population::reproduce(Constraint constraints[], int n)
{
assign_fitness();
//old population
member old_members[POP_SIZE] = members;
member mother;
member father;
//The crossover between father, mother and mutate
int threshold_1 = MUTATION_RATE/.2, threshold_2 = MUTATION_RATE * 10.;
//for each member of the population
for(int i = 0; i < POP_SIZE; i++)
{
//Selects parents
mother = old_members[binary_search(fitness_total,
POP_SIZE,
rand()%int(fitness_total[POP_SIZE-1]))];
father = old_members[binary_search(fitness_total,
POP_SIZE,
rand()%int(fitness_total[POP_SIZE-1]))];
//goes through each trait and selects where it comes from
for(int c = 0; c < n; c++)
{
int rnd = rand() % 10;
if(rnd <= threshold_1)
{
//gets trait from mother
members[i].values[c] = mother.values[c];
}
else if(rnd <= threshold_2)
{
//gets trait from father
members[i].values[c] = father.values[c];
}
else
{
//mutates (completely random)
members[i].values[c] = (rand()/double(RAND_MAX))*(constraints[c].max -
constraints[c].min) +
constraints[c].min;
}
if(!constraints[c].within_constraint(members[i].values[c]))
{
members[i].values[c] = (rand()/double(RAND_MAX))*(constraints[c].max -
constraints[c].min) +
constraints[c].min;
}
}
}
}
void Colony::reproduction(const gsl_rng *rand){
int k,j,new_pop_size;
double pop_fitness;
assign_fitness();
pop_fitness = 0.;
for(j=0;j<pop_size;j++)
{
pop_fitness += fitness[j];
}
pop_fitness = pop_fitness*max_fitness;
new_pop_size = gsl_ran_poisson(rand,pop_fitness);
// printf("fitness: %lf\tnew pop size: %i\n", pop_fitness, new_pop_size);
if (new_pop_size==0)
{
printf("extinct\n");
exit(0);
}
if (new_pop_size>limit)
{
printf("established\n");
exit(0);
}
gsl_ran_multinomial(rand, pop_size, new_pop_size, fitness, off_numbers);
next_generation(rand);
pop_size = new_pop_size;
mutate_population(rand);
for(j=pop_size;j<limit;j++)
{
for(k=0; k<n_del; k++)
{
del_matrix[j][k] = 0;
}
for(k=0; k<n_env; k++)
{
env_matrix[j][k] = 0;
}
}
};