Package org.encog.ml.factory.method

Source Code of org.encog.ml.factory.method.EPLFactory

/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*     http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*  
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.ml.factory.method;

import java.util.Map;
import java.util.Random;
import java.util.StringTokenizer;

import org.encog.EncogError;
import org.encog.ml.MLMethod;
import org.encog.ml.factory.MLMethodFactory;
import org.encog.ml.factory.parse.ArchitectureParse;
import org.encog.ml.prg.EncogProgramContext;
import org.encog.ml.prg.extension.StandardExtensions;
import org.encog.ml.prg.generator.RampedHalfAndHalf;
import org.encog.ml.prg.train.PrgPopulation;
import org.encog.util.ParamsHolder;

public class EPLFactory {
  /**
   * Create a feed forward network.
   * @param architecture The architecture string to use.
   * @param input The input count.
   * @param output The output count.
   * @return The feedforward network.
   */
  public MLMethod create(final String architecture, final int input,
      final int output) {
   
    if( input<=0 ) {
      throw new EncogError("Must have at least one input for EPL.");
    }
   
    if( output<=0 ) {
      throw new EncogError("Must have at least one output for EPL.");
    }
   
   
    final Map<String, String> args = ArchitectureParse.parseParams(architecture);
    final ParamsHolder holder = new ParamsHolder(args);
   
    final int populationSize = holder.getInt(
        MLMethodFactory.PROPERTY_POPULATION_SIZE, false, 1000);
    String variables = holder.getString("vars", false, "x");
    String funct = holder.getString("funct", false, null);
   
    EncogProgramContext context = new EncogProgramContext();
    StringTokenizer tok = new StringTokenizer(variables,",");
    while(tok.hasMoreElements()) {
      context.defineVariable(tok.nextToken());
    }

    if( "numeric".equalsIgnoreCase(funct) ) {
      StandardExtensions.createNumericOperators(context);
    }
   
    PrgPopulation pop = new PrgPopulation(context,populationSize);
   
    if( context.getFunctions().size()>0 ) {
      (new RampedHalfAndHalf(context,2,6)).generate(new Random(), pop);
    }
    return pop;
  }
}
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