t_cplx f_julia(t_coeff col, double x, double y)
{
double r;
t_cplx z;
double theta;
(void)col;
r = sqrt (sqrt (x * x + y * y));
theta = atan2 (y, x) * .5;
if (random_bit ())
theta += M_PI;
z.r = r * cos(theta);
z.i = r * sin(theta);
return (z);
}
vector<bool> Hybrid::do_crossover(Chromosome& c1, Chromosome& c2) {
vector<bool> crossed(flm_conf.chromosome_length, false);
// Do two point crossover in first part
int smoothing_beginning = flm_conf.chromosome_length - flm_conf.smooth_len;
pair<int, int> range = pick_range(smoothing_beginning);
for (int i = range.first; i < range.second; i++) {
swap(c1[i], c2[i]);
crossed[i] = true;
}
// Do uniform crossover in the smoothing part
for (int j = smoothing_beginning; j < flm_conf.chromosome_length; j++) {
if (random_bit()) {
swap(c1[j], c2[j]);
crossed[j] = true;
}
}
return crossed;
}
Genotype::Genotype(const ID_type nID, const std::pair<Genotype*, Genotype*> parents)
: ID(nID), decision_chromosome(), link_chromosome(),
fitness(parents.first->fitness), value(0.0), generator(nID) {
real_type mutation_rate = 0.2, crossover_rate = 0.5;
int i, j, ii, jj;
//breed new chromosomes from parents, use hardcoded mutation and crossover rates
fitness->add(ID, this);
//what does crossover rate mean?
//generate 2 random numbers for decision_chromosome crossover
std::uniform_int_distribution<> random_int(0, decision_chromosome.size() - 1);
std::bernoulli_distribution crossover(crossover_rate);
if( crossover(generator) ) {
i = random_int(generator);
//take beginning of chromosome from first parent ...
for(ii=i; ii>=0; --ii)
decision_chromosome[ii] = parents.first->decision_chromosome[ii];
//... and the rest from the second parent
for(ii=decision_chromosome.size()-1; ii>i; --ii)
decision_chromosome[ii] = parents.second->decision_chromosome[ii];
}
//decide whether to mutate
std::bernoulli_distribution mutate(mutation_rate);
random_int = std::uniform_int_distribution<>(0, decision_chromosome.size() - 1);
if( mutate(generator) ) ~decision_chromosome[random_int(generator)]; //flip a bit
//generate 2 random numbers for link_chromosome crossover
if( crossover(generator) ) {
ii = random_int(generator);
//take beginning of chromosome from first parent ...
for(i=i; i>=0; --i) //over genetic nodes
for(j=link_chromosome[0].size()-1; j>=0; --j) //over each connectivity vector
link_chromosome[i][j] = parents.first->link_chromosome[i][j];
//... and the rest from the second parent
for(i=decision_chromosome.size()-1; i>ii; --i)
for(j=link_chromosome[0].size()-1; j>=0; --j)
link_chromosome[i][j] = parents.second->link_chromosome[i][j];
}
//decide whether to mutate
//mutations must occur in pairs to preserve K=2 connectivity
random_int = std::uniform_int_distribution<>(0, link_chromosome.size() - 1);
i = random_int(generator); //which bitset
random_int = std::uniform_int_distribution<>(0, link_chromosome[0].size() - 1);
j = random_int(generator); //which false bit to flip
std::bernoulli_distribution random_bit(0.5);
bool first = random_bit(generator); //which true bit to flip (there are only 2)
ii = link_chromosome[0].size() - 1;
if( mutate(generator) ) {
for(ii; ii>=0; --ii) {
if( link_chromosome[i][ii] ) { //true bit found
if(first) { link_chromosome[i][ii] = false; break; }
else first = true; //flip next true bit
}
}
while(link_chromosome[i][j]) { //make sure bit is false to start with
j = random_int(generator);
}
//may reflip the same bit, but it doesn't matter; happens rarely
link_chromosome[i][j] = true;
} //if
} //constructor
