/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2011 by Rapid-I and the contributors
 *
 *  Complete list of developers available at our web site:
 *
 *       http://rapid-i.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.features.selection;

import java.util.List;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeBoolean;
import com.rapidminer.parameter.ParameterTypeInt;
import com.rapidminer.parameter.conditions.BooleanParameterCondition;
import com.rapidminer.tools.RandomGenerator;

/**
 * This operator selects a randomly chosen number of attributes randomly from the input example set.
 * This can be useful in combination with a ParameterIteration operator or can be used
 * as a baseline for significance test comparisons for feature selection techniques.
 * 
 * @author Ingo Mierswa
 */
public class RandomSelection extends AbstractFeatureSelection {


    public static final String PARAMETER_USE_FIXED_NUMBER_OF_ATTRIBUTES = "use_fixed_number_of_attributes";
    public static final String PARAMETER_NUMBER_OF_ATTRIBUTES = "number_of_attributes";

    public RandomSelection(OperatorDescription description) {
        super(description);
    }

    @Override
    public ExampleSet apply(ExampleSet exampleSet) throws OperatorException {
        ExampleSet result = (ExampleSet)exampleSet.clone();

        RandomGenerator random = RandomGenerator.getRandomGenerator(this);
        int number = 0;
        if (getParameterAsBoolean(PARAMETER_USE_FIXED_NUMBER_OF_ATTRIBUTES))
            number = getParameterAsInt(PARAMETER_NUMBER_OF_ATTRIBUTES);
        else {
            number = random.nextIntInRange(1, result.getAttributes().size() + 1);
            if (number > result.getAttributes().size())
                throw new UserError(this, 125, number, result.getAttributes().size());
        }

        while (result.getAttributes().size() > number) {
            int toDeleteIndex = random.nextIntInRange(0, result.getAttributes().size());
            Attribute toDeleteAttribute = null;
            int counter = 0;
            for (Attribute attribute : result.getAttributes()) {
                if (counter >= toDeleteIndex) {
                    toDeleteAttribute = attribute;
                    break;
                }
                counter++;
            }
            if (toDeleteAttribute != null) {
                result.getAttributes().remove(toDeleteAttribute);
            }
        }

        return result;
    }

    @Override
    public List<ParameterType> getParameterTypes() {
        List<ParameterType> types = super.getParameterTypes();
        ParameterType type = new ParameterTypeBoolean(PARAMETER_USE_FIXED_NUMBER_OF_ATTRIBUTES, "Indicates if a fixed number of attributes should be selected.", false);
        type.setExpert(false);
        types.add(type);

        type = new ParameterTypeInt(PARAMETER_NUMBER_OF_ATTRIBUTES, "The number of attributes which should be randomly selected.", 1, Integer.MAX_VALUE, 1);
        type.registerDependencyCondition(new BooleanParameterCondition(this, PARAMETER_USE_FIXED_NUMBER_OF_ATTRIBUTES, true, true));
        type.setExpert(false);
        types.add(type);
        types.addAll(RandomGenerator.getRandomGeneratorParameters(this));
        return types;
    }
}