package net.bmahe.genetics4j.gp.spec;
   
   import java.util.Objects;
   import java.util.random.RandomGenerator;
   
   import net.bmahe.genetics4j.core.chromosomes.factory.ImmutableChromosomeFactoryProvider;
   import net.bmahe.genetics4j.core.spec.ImmutableEAExecutionContext;
   import net.bmahe.genetics4j.core.spec.ImmutableEAExecutionContext.Builder;
   import net.bmahe.genetics4j.gp.chromosomes.factory.ProgramTreeChromosomeFactory;
  import net.bmahe.genetics4j.gp.combination.ProgramRandomCombineHandler;
  import net.bmahe.genetics4j.gp.mutation.NodeReplacementPolicyHandler;
  import net.bmahe.genetics4j.gp.mutation.ProgramRandomMutatePolicyHandler;
  import net.bmahe.genetics4j.gp.mutation.ProgramRandomPrunePolicyHandler;
  import net.bmahe.genetics4j.gp.mutation.ProgramRulesApplicatorPolicyHandler;
  import net.bmahe.genetics4j.gp.mutation.TrimTreePolicyHandler;
  import net.bmahe.genetics4j.gp.program.ProgramGenerator;
  import net.bmahe.genetics4j.gp.program.ProgramHelper;
  import net.bmahe.genetics4j.gp.program.RampedHalfAndHalfProgramGenerator;
  
  /**
   * Defines multiple factory and helper methods to create and manage EAExecutionContexts appropriate for Genetic
   * Programming
   */
  public class GPEAExecutionContexts {
  
  	private GPEAExecutionContexts() {
  	}
  
  	/**
  	 * Create a new EAExecutionContext pre-configured to support Genetic Programming.
  	 * <p>It adds support for some operators to select, mutate and combine programs.
  	 * 
  	 * @param <T>              Type of the fitness measurement
  	 * @param randomGenerator  Random Generator
  	 * @param programHelper    Instance of ProgramHelper
  	 * @param programGenerator Instance of a program generator which will be used to generate individuals
  	 * @return A new instance of a EAExecutionContext
  	 */
  	public static <T extends Comparable<T>> Builder<T> forGP(final RandomGenerator randomGenerator,
  			final ProgramHelper programHelper, final ProgramGenerator programGenerator) {
  		Objects.requireNonNull(randomGenerator);
  		Objects.requireNonNull(programHelper);
  		Objects.requireNonNull(programGenerator);
  
  		final var builder = ImmutableEAExecutionContext.<T>builder();
  		builder.randomGenerator(randomGenerator);
  
  		builder.addMutationPolicyHandlerFactories(
  				gsd -> new ProgramRandomPrunePolicyHandler<>(gsd.randomGenerator(), programHelper),
  				gsd -> new ProgramRandomMutatePolicyHandler<>(gsd.randomGenerator(), programGenerator),
  				gsd -> new NodeReplacementPolicyHandler<>(randomGenerator, programHelper),
  				gsd -> new ProgramRulesApplicatorPolicyHandler<>(),
  				gsd -> new TrimTreePolicyHandler<>(randomGenerator, programGenerator));
  
  		builder.addChromosomeCombinatorHandlerFactories(gsd -> new ProgramRandomCombineHandler<T>(gsd.randomGenerator()));
  
  		final var chromosomeFactoryProviderBuilder = ImmutableChromosomeFactoryProvider.builder();
  		chromosomeFactoryProviderBuilder.randomGenerator(randomGenerator);
  		chromosomeFactoryProviderBuilder
  				.addChromosomeFactoriesGenerator(cdp -> new ProgramTreeChromosomeFactory(programGenerator));
  		builder.chromosomeFactoryProvider(chromosomeFactoryProviderBuilder.build());
  
  		return builder;
  	}
  
  	/**
  	 * Create a new EAExecutionContext pre-configured to support Genetic Programming.
  	 * <p>It adds support for some operators to select, mutate and combine programs. It also configure a default program
  	 * generation based on ramped hald and half.
  	 * 
  	 * @param <T>             Type of the fitness measurement
  	 * @param randomGenerator Random Generator
  	 * @return A new instance of a EAExecutionContext
  	 */
  	public static <T extends Comparable<T>> Builder<T> forGP(final RandomGenerator randomGenerator) {
  		Objects.requireNonNull(randomGenerator);
  
  		final var programHelper = new ProgramHelper(randomGenerator);
  		final var programGenerator = new RampedHalfAndHalfProgramGenerator(randomGenerator, programHelper);
  
  		return forGP(randomGenerator, programHelper, programGenerator);
  	}
  }