population::population(int N_in, int L_in, double r_in, int seed_in, gsl_rng* rng_in, vector< vector<double> >& fit) {
try {
if (fit.size() != N_in || fit[0].size() != L_in) {throw "Incorrect Fitness Landscape dimensions!";}
else if (r_in < 0 || r_in > 1 || N_in < 0 || L_in <0) {throw "Bad inputs. Check arguments.";}
else {
N = N_in;
L = L_in;
r = r_in;
gen_pop = 0;
neutral = false;
avgFit = 0;
selective_weight = vector<double>(N);
genetic_weight = vector< vector<int> >(N,vector<int>(L));
fixations = vector< vector<fixation_event> > (N);
seed = seed_in ? seed_in : get_random_seed();
rng = rng_in;
gsl_rng_set(rng,seed);
blockHist = gsl_histogram_alloc(L);
gsl_histogram_set_ranges_uniform(blockHist,1,L+1); //Questionable range choice. As it stands now, the bins are partitioned as follows {[1,2),[2,3)......[L,L+1)}. Thus if all have length L, then average will come out to be (L+.5). Will have to rescale.
map<int,double> genome_fit;
for(int i=0;i<N;i++) {
genome_fit = convert_vector_toMap(fit[i]);
if (!genome_fit.empty()) {pop.push_back(genome(i, L, rng, genome_fit));}
else {pop.push_back(genome(i,L,rng));}
avgFit += pop[i].get_fit();
}
avgFit/=N;
update_selection_weights();
updateBlockSizes();
}
}
catch (const char* Message) {
cout << "Error:" << Message << "\n";
}
}
void population::evolve(int gen) { //Wright-Fisher Model - Population size is held constant. Parental genotypes are chosen randomly.
for (int j=0; j<gen; j++){
vector<genome> newPop (N);
avgFit = 0;
for(int i=0; i<N; i++) {
if (r == 1) {
newPop[i] = progeny(selectParents());
avgFit += newPop[i].get_fit();
}
else if ((r != 0) && gsl_rng_uniform(rng) <= r) {
newPop[i] = progeny(selectParents());
avgFit += newPop[i].get_fit();
}
else {
if (neutral) {newPop[i] = pop[(int)gsl_rng_uniform_int(rng,N)];}
else {
double fit_rand = selective_weight[N-1]*gsl_rng_uniform(rng);
newPop[i] = pop[binarySearch_int(selective_weight, 0, N-1, fit_rand)];
avgFit += newPop[i].get_fit();
}
}
}
avgFit/= N;
pop = newPop;
gen_pop++;
update_weights();
//updateBlockSizes();
if (!neutral) {update_selection_weights();}
}
update_weights();
updateBlockSizes();
//if (WRITEHIST) {writeBlockHist();}
}
//Overloaded Constructors
population::population(int N_in, int L_in, double r_in, int seed_in, gsl_rng* rng_in) { //Neutral Evolution!
try {
if (r_in < 0 || r_in > 1 || N_in < 0 || L_in <0) {throw "Bad inputs. Check arguments.";}
else {
N = N_in;
L = L_in;
r = r_in;
gen_pop = 0;
neutral = true;
avgFit = 0;
selective_weight = vector<double>(N); //All zeros
genetic_weight = vector< vector<int> >(N,vector<int>(L));
fixations = vector< vector<fixation_event> > (N);
seed = seed_in ? seed_in:get_random_seed();
rng = rng_in;
gsl_rng_set(rng,seed);
blockHist = gsl_histogram_alloc(L);
gsl_histogram_set_ranges_uniform(blockHist,1,L+1);
for(int i=0;i<N;i++) {
pop.push_back(genome(i,L,rng));
}
updateBlockSizes();
}
}
catch(const char* Message) {cout << "Error: " << Message << "\n";}
}
//==========================================================================
// Constructor and Destructor
//==========================================================================
SAFEParameter::SAFEParameter (String nameInit, float& valueRef, float initialValue, float minValueInit, float maxValueInit, String unitsInit, float skewFactorInit, bool convertDBToGainValue, double interpolationTimeInit, float UIScaleFactorInit)
: outputValue (valueRef),
convertToGain (convertDBToGainValue)
{
name = nameInit;
minValue = minValueInit;
maxValue = maxValueInit;
defaultValue = initialValue;
skewFactor = skewFactorInit;
units = unitsInit;
interpolating = false;
initialised = false;
sampleRate = 44100;
controlRate = 64;
interpolationTime = interpolationTimeInit;
updateBlockSizes();
UIScaleFactor = UIScaleFactorInit;
setScaledValue (defaultValue);
}
void SAFEParameter::setInterpolationTime (double newInterpolationTime)
{
interpolationTime = newInterpolationTime;
updateBlockSizes();
}
void SAFEParameter::setControlRate (double newControlRate)
{
controlRate = newControlRate;
updateBlockSizes();
}
//==========================================================================
// Smoothing Bits
//==========================================================================
void SAFEParameter::setSampleRate (double newSampleRate)
{
sampleRate = newSampleRate;
updateBlockSizes();
}
