/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2014 by RapidMiner and the contributors
 *
 *  Complete list of developers available at our web site:
 *
 *       http://rapidminer.com
 *
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Affero General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This program is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU Affero General Public License for more details.
 *
 *  You should have received a copy of the GNU Affero General Public License
 *  along with this program.  If not, see http://www.gnu.org/licenses/.
 */
package com.rapidminer.operator;

import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.set.HeaderExampleSet;


/**
 * Abstract model is the superclass for all objects which change a data set. For
 * example, a model generated by a learner might add a predicted attribute.
 * Other models can be created during preprocessing, e.g. a transformation model
 * containing the parameters for a z-transformation. Models can be combined by
 * using a CombinedModel. All models can be applied with a ModelApplier
 * operator.
 * 
 * @author Ingo Mierswa
 */
public abstract class AbstractModel extends ResultObjectAdapter implements Model {
	private static final long serialVersionUID = 1640348739650532634L;

	/** This header example set contains all important nominal mappings of all training attributes.
	 *  These mappings are necessary in order to ensure that the internally used
	 *  double values encoding nominal values are equal for the training and 
	 *  application data sets. */
	private HeaderExampleSet headerExampleSet;

	/** Created a new model which was built on the given example set. Please note
	 *  that the given example set is automatically transformed into a {@link HeaderExampleSet}
	 *  which means that no reference to the data itself is kept but only to the header, i.e.
	 *  to the attribute meta descriptions. */
	protected AbstractModel(ExampleSet exampleSet) {
		if (exampleSet != null) {
			this.headerExampleSet = new HeaderExampleSet(exampleSet);
		}
	}

	/** Delivers the training header example set, i.e. the header of the example set (without
	 *  data reference) which was used for creating this model. Might return null. */
	public HeaderExampleSet getTrainingHeader() {
		return this.headerExampleSet;
	}

	/** This default implementation returns false. Note that subclasses overriding this
	 *  method should also override the method {@link #updateModel(ExampleSet)}. */
	public boolean isUpdatable() { return false; }

	/** This default implementation throws an {@link UserError}. 
	 *  Subclasses overriding this method to update the model according to the given 
	 *  example set should also override the method {@link #isUpdatable()} by
	 *  delivering true. */
	public void updateModel(ExampleSet updateExampleSet) throws OperatorException {
		throw new UserError(null, 135, getClass().getName());
	}

	/**
	 * Throws a UserError since most models should not allow additional
	 * parameters during application. However, subclasses may overwrite this
	 * method.
	 */
	public void setParameter(String key, Object value) throws OperatorException {
		log("The learned model does not support parameter");
	}

	/** The default implementation returns the result of the super class. If the string ends with 
	 *  model, the substring "model" is removed. */
	@Override
	public String getName() {
		String result = super.getName();
		if (result.toLowerCase().endsWith("model")) {
			result = result.substring(0, result.length() - "model".length());
		}
		return result;
	}

	public String getExtension() { return "mod"; }

	public String getFileDescription() { return "model file"; }
	
	@Override
	public boolean isInTargetEncoding() {
		return false;
	}
}