Package org.encog.plugin.system

Source Code of org.encog.plugin.system.SystemActivationPlugin

/*
* 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.plugin.system;

import org.encog.EncogError;
import org.encog.engine.network.activation.ActivationBiPolar;
import org.encog.engine.network.activation.ActivationCompetitive;
import org.encog.engine.network.activation.ActivationFunction;
import org.encog.engine.network.activation.ActivationGaussian;
import org.encog.engine.network.activation.ActivationLOG;
import org.encog.engine.network.activation.ActivationLinear;
import org.encog.engine.network.activation.ActivationRamp;
import org.encog.engine.network.activation.ActivationSIN;
import org.encog.engine.network.activation.ActivationSigmoid;
import org.encog.engine.network.activation.ActivationSoftMax;
import org.encog.engine.network.activation.ActivationSteepenedSigmoid;
import org.encog.engine.network.activation.ActivationStep;
import org.encog.engine.network.activation.ActivationTANH;
import org.encog.ml.MLMethod;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.factory.MLActivationFactory;
import org.encog.ml.train.MLTrain;
import org.encog.plugin.EncogPluginBase;
import org.encog.plugin.EncogPluginService1;
import org.encog.util.csv.CSVFormat;
import org.encog.util.csv.NumberList;

public class SystemActivationPlugin implements EncogPluginService1 {

  /**
   * {@inheritDoc}
   */
  @Override
  public final String getPluginDescription() {
    return "This plugin provides the built in machine " +
        "learning methods for Encog.";
  }

  /**
   * {@inheritDoc}
   */
  @Override
  public final String getPluginName() {
    return "HRI-System-Methods";
  }

  /**
   * @return This is a type-1 plugin.
   */
  @Override
  public final int getPluginType() {
    return 1;
  }
 
  private ActivationFunction allocateAF(String name) {
    if (name.equalsIgnoreCase(MLActivationFactory.AF_BIPOLAR)) {
      return new ActivationBiPolar();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_COMPETITIVE)) {
      return new ActivationCompetitive();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_GAUSSIAN)) {
      return new ActivationGaussian();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_LINEAR)) {
      return new ActivationLinear();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_LOG)) {
      return new ActivationLOG();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_RAMP)) {
      return new ActivationRamp();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_SIGMOID)) {
      return new ActivationSigmoid();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_SIN)) {
      return new ActivationSIN();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_SOFTMAX)) {
      return new ActivationSoftMax();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_STEP)) {
      return new ActivationStep();
    }

    if (name.equalsIgnoreCase(MLActivationFactory.AF_TANH)) {
      return new ActivationTANH();
    }
   
    if( name.equalsIgnoreCase(MLActivationFactory.AF_SSIGMOID)) {
      return new ActivationSteepenedSigmoid();
    }

    return null;
  }


  /**
   * {@inheritDoc}
   */
  @Override
  public ActivationFunction createActivationFunction(String fn) {
    String name;
    double[] params;

    int index = fn.indexOf('[');
    if (index != -1) {
      name = fn.substring(0, index).toLowerCase();
      int index2 = fn.indexOf(']');
      if (index2 == -1) {
        throw new EncogError(
            "Unbounded [ while parsing activation function.");
      }
      String a = fn.substring(index + 1, index2);
      params = NumberList.fromList(CSVFormat.EG_FORMAT, a);

    } else {
      name = fn.toLowerCase();
      params = new double[0];
    }

    ActivationFunction af = allocateAF(name);
   
    if( af==null ) {
      return null;
    }

    if (af.getParamNames().length != params.length) {
      throw new EncogError(name + " expected "
          + af.getParamNames().length + ", but " + params.length
          + " were provided.");
    }

    for (int i = 0; i < af.getParamNames().length; i++) {
      af.setParam(i, params[i]);
    }

    return af;
  }

  /**
   * {@inheritDoc}
   */
  @Override
  public MLMethod createMethod(String methodType, String architecture,
      int input, int output) {
    return null;
  }

  /**
   * {@inheritDoc}
   */
  @Override
  public MLTrain createTraining(MLMethod method, MLDataSet training,
      String type, String args) {
    return null;
  }

  /**
   * {@inheritDoc}
   */
  @Override
  public int getPluginServiceType() {
    return EncogPluginBase.TYPE_SERVICE;
  }
}
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