/* Initialise */
void initialise() {
/* Allocate memory for parameters */
p0=malloc(nProb*sizeof(parameters));
ip0=malloc(nK*sizeof(intparameters));
fprintf(OUT, "Setting parameters...\n");
initialiseParameters(p0, 0.1, 0, 1, nProb);
probs=malloc( nProb*sizeof(double));
probsProp=malloc( nProb*sizeof(double));
initialisePorg(p0, probs, nProb);
initialisePprop(p0, probsProp, nProb);
setParameterNames(p0, "p", nProb);
/* printParameterNames(OUT, p0, nProb); */
/* printParameters(OUT,p0, nProb); */
/* Allocate memory for changepoints */
k=malloc(nK*sizeof(int));
kProp=malloc(nK*sizeof(int));
initialiseIntPorg(ip0, k, nK);
initialiseIntPprop(ip0, kProp, nK);
/* Set name prefix and parameters for changepoints */
setIntParameterNames(ip0, "k", nK);
/* sample width dK - sample between p-dK and p+dK. */
initialiseIntParameters(ip0, dK, 0, getNdata()-1, nK);
/* Initialising random number generator */
r = gsl_rng_alloc(gsl_rng_taus);
gsl_rng_set(r,seed);
initUniform(r, p0, nProb);
/* Changepoint locations in ascending order. */
initIntUniformAscending(r, ip0, 0, getNdata()-1, nK);
}
int main(void){
struct parameters *params = NULL;
struct chromosome *chromoA = NULL;
struct chromosome *chromoB = NULL;
struct chromosome *chromoC = NULL;
struct dataSet *trainingData = NULL;
double testInputs[NUMINPUTS];
params = initialiseParameters(NUMINPUTS, NUMNODES, NUMOUTPUTS, ARITY);
addNodeFunction(params, "add,sub,mul,sq,cube,sin");
trainingData = initialiseDataSetFromFile("./dataSets/symbolic.data");
chromoA = initialiseChromosome(params);
chromoB = initialiseChromosome(params);
setChromosomeFitness(params, chromoA, trainingData);
mutateChromosome(params,chromoA);
copyChromosome(chromoB, chromoA);
removeInactiveNodes(chromoB);
printf("chromoA with inactive nodes.\n");
printChromosome(chromoA, 0);
printf("chromoB without inactive nodes.\n");
printChromosome(chromoB, 1);
saveChromosome(chromoB, "chromoB.chromo");
chromoC = initialiseChromosomeFromFile("chromoB.chromo");
testInputs[0] = 3;
executeChromosome(chromoC, testInputs);
printf("Applied input: %f\n", testInputs[0]);
printf("Generated output: %f\n", getChromosomeOutput(chromoC, 0));
freeChromosome(chromoA);
freeChromosome(chromoB);
freeChromosome(chromoC);
freeDataSet(trainingData);
freeParameters(params);
return 0;
}
RelativisticBreitWigner::RelativisticBreitWigner(const ParticleStateInfo& psi,
const ExternalParameters& external_parameters) {
J_ = psi.spin_information_;
resonance_width_.reset(
new DoubleParameter(psi.pid_information_.name_ + "_width"));
resonance_mass_.reset(
new DoubleParameter(psi.pid_information_.name_ + "_mass"));
meson_radius_.reset(
new DoubleParameter(psi.pid_information_.name_ + "_meson_radius"));
parameter_list_.AddParameter(resonance_mass_);
parameter_list_.AddParameter(resonance_width_);
parameter_list_.AddParameter(meson_radius_);
index_cms_mass_squared_ =
ComPWA::Kinematics::instance()->FindVariable( "cms_mass_squared" );
initialiseParameters(psi.dynamical_information_, external_parameters);
}
int main(void){
struct parameters *params = NULL;
struct chromosome *chromo = NULL;
int numInputs = 1;
int numNodes = 20;
int numOutputs = 1;
int nodeArity = 5;
int numGens = 25000;
double targetFitness = 0.5;
int updateFrequency = 500;
double weightRange = 5;
params = initialiseParameters(numInputs, numNodes, numOutputs, nodeArity);
setTargetFitness(params, targetFitness);
setUpdateFrequency(params, updateFrequency);
setConnectionWeightRange(params, weightRange);
setCustomFitnessFunction(params, sinWave, "sinWave");
addNodeFunction(params, "tanh,softsign");
chromo = runCGP(params, NULL, numGens);
printChromosome(chromo, 1);
freeChromosome(chromo);
freeParameters(params);
return 0;
}
int main(void){
int i, gen;
struct parameters *params = NULL;
struct chromosome *population[POPULATIONSIZE];
struct chromosome *fittestChromosome = NULL;
struct dataSet *trainingData = NULL;
double targetFitness = 0;
int maxGens = 10000;
params = initialiseParameters(NUMINPUTS, NUMNODES, NUMOUTPUTS, ARITY);
addNodeFunction(params, "or,nor,and,nand");
/*setTargetFitness(params, targetFitness);*/
setMutationType(params, "probabilistic");
setMutationRate(params, 0.08);
trainingData = initialiseDataSetFromFile("./examples/parity3bit.data");
for(i=0; i<POPULATIONSIZE; i++){
population[i] = initialiseChromosome(params);
}
fittestChromosome = initialiseChromosome(params);
/* for the number of allowed generations*/
for(gen=0; gen<maxGens; gen++){
/* set the fitnesses of the population of chromosomes*/
for(i=0; i<POPULATIONSIZE; i++){
setChromosomeFitness(params, population[i], trainingData);
}
/* copy over the last chromosome to fittestChromosome*/
copyChromosome(fittestChromosome, population[POPULATIONSIZE - 1]);
/* for all chromosomes except the last*/
for(i=0; i<POPULATIONSIZE-1; i++){
/* copy ith chromosome to fittestChromosome if fitter*/
if(getChromosomeFitness(population[i]) < getChromosomeFitness(fittestChromosome)){
copyChromosome(fittestChromosome, population[i]);
}
}
/* termination condition*/
if(getChromosomeFitness(fittestChromosome) <= targetFitness){
break;
}
/* set the first member of the population to be the fittest chromosome*/
copyChromosome(population[0], fittestChromosome);
/* set remaining member of the population to be mutations of the
fittest chromosome*/
for(i=1; i<POPULATIONSIZE; i++){
copyChromosome(population[i], fittestChromosome);
mutateChromosome(params, population[i]);
}
}
printf("gen\tfitness\n");
printf("%d\t%f\n", gen, getChromosomeFitness(fittestChromosome));
for(i=0; i<POPULATIONSIZE; i++){
freeChromosome(population[i]);
}
freeChromosome(fittestChromosome);
freeDataSet(trainingData);
freeParameters(params);
return 0;
}
