public void eval(
int seed, String parent1Expression, String parent2Expression, String offspringExpression) {
EncogProgramContext context = new EncogProgramContext();
StandardExtensions.createNumericOperators(context.getFunctions());
// parent 1
EncogProgram parent1 = new EncogProgram(context);
parent1.getVariables().setVariable("x", 1);
parent1.compileExpression(parent1Expression);
// parent 2
EncogProgram parent2 = new EncogProgram(context);
parent2.getVariables().setVariable("x", 1);
parent2.compileExpression(parent2Expression);
// offspring
EncogProgram[] offspring = parent1.allocateOffspring(1);
EvolutionaryOperator cross = new SubtreeCrossover();
Genome[] parents = {parent1, parent2};
cross.performOperation(new Random(seed), parents, 0, offspring, 0);
offspring[0].getVariables().setVariable("x", 1);
RenderCommonExpression render = new RenderCommonExpression();
// Assert.assertEquals(offspringExpression,render.render(offspring[0]));
}
/** {@inheritDoc} */
@Override
public Object call() {
boolean success = false;
int tries = this.train.getMaxOperationErrors();
do {
try {
// choose an evolutionary operation (i.e. crossover or a type of
// mutation) to use
final EvolutionaryOperator opp =
this.train.getOperators().pickMaxParents(this.rnd, this.species.getMembers().size());
this.children[0] = null;
// prepare for either sexual or asexual reproduction either way,
// we
// need at least
// one parent, which is the first parent.
//
// Chose the first parent, there must be at least one genome in
// this
// species
this.parents[0] = chooseParent();
// if the number of individuals in this species is only
// one then we can only clone and perhaps mutate, otherwise use
// the crossover probability to determine if we are to use
// sexual reproduction.
if (opp.parentsNeeded() > 1) {
int numAttempts = 5;
this.parents[1] = chooseParent();
while (this.parents[0] == this.parents[1] && numAttempts-- > 0) {
this.parents[1] = chooseParent();
}
// success, perform crossover
if (this.parents[0] != this.parents[1]) {
opp.performOperation(this.rnd, this.parents, 0, this.children, 0);
}
} else {
// clone a child (asexual reproduction)
opp.performOperation(this.rnd, this.parents, 0, this.children, 0);
this.children[0].setPopulation(this.parents[0].getPopulation());
}
// process the new child
for (Genome child : this.children) {
if (child != null) {
child.setPopulation(this.parents[0].getPopulation());
if (this.train.getPopulation().getRules().isValid(child)) {
child.setBirthGeneration(this.train.getIteration());
this.train.calculateScore(child);
if (!this.train.addChild(child)) {
return null;
}
success = true;
}
}
}
} catch (EARuntimeError e) {
tries--;
if (tries < 0) {
throw new EncogError(
"Could not perform a successful genetic operaton after "
+ this.train.getMaxOperationErrors()
+ " tries.");
}
} catch (final Throwable t) {
if (!this.train.getShouldIgnoreExceptions()) {
this.train.reportError(t);
}
}
} while (!success);
return null;
}
