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Massive On-line Analysis is an environment for massive data mining. MOA provides a framework for data stream mining and includes tools for evaluation and a collection of machine learning algorithms. Related to the WEKA project, also written in Java, while scaling to more demanding problems.

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/*
 *    FilteredStream.java
 *    Copyright (C) 2007 University of Waikato, Hamilton, New Zealand
 *    @author Richard Kirkby ([email protected])
 *
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU 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 General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program. If not, see .
 *    
 */
package moa.streams;

import moa.core.InstancesHeader;
import moa.core.ObjectRepository;
import moa.options.AbstractOptionHandler;
import moa.options.ClassOption;
import moa.options.OptionHandler;
import moa.streams.filters.StreamFilter;
import moa.tasks.TaskMonitor;
import weka.core.Instance;

/**
 * Class for representing a stream that is filtered.
 *
 * @author Richard Kirkby ([email protected])
 * @version $Revision: 7 $
 */
public class FilteredStream extends AbstractOptionHandler implements
        InstanceStream {

    @Override
    public String getPurposeString() {
        return "A stream that is filtered.";
    }

    private static final long serialVersionUID = 1L;

    public ClassOption streamOption = new ClassOption("stream", 's',
            "Stream to filter.", InstanceStream.class,
            "generators.RandomTreeGenerator");

    public ClassOption filtersOption = new ClassOption("filters", 'f',
            "Filters to apply.", StreamFilter.class, 
            "AddNoiseFilter");

    protected InstanceStream filterChain;

    @Override
    public void prepareForUseImpl(TaskMonitor monitor,
            ObjectRepository repository) {
        StreamFilter filters; 
            monitor.setCurrentActivity("Materializing filter " //+ (i + 1)
                    + "...", -1.0);
            filters = (StreamFilter) getPreparedClassOption(this.filtersOption);
            if (monitor.taskShouldAbort()) {
                return;
            }
            if (filters instanceof OptionHandler) {
                monitor.setCurrentActivity("Preparing filter " //+ (i + 1)
                        + "...", -1.0);
                ((OptionHandler) filters).prepareForUse(monitor, repository);
                if (monitor.taskShouldAbort()) {
                    return;
                }
            }
        InstanceStream chain = (InstanceStream) getPreparedClassOption(this.streamOption);
            filters.setInputStream(chain);
            chain = filters;
        this.filterChain = chain;
    }

    @Override
    public long estimatedRemainingInstances() {
        return this.filterChain.estimatedRemainingInstances();
    }

    @Override
    public InstancesHeader getHeader() {
        return this.filterChain.getHeader();
    }

    @Override
    public boolean hasMoreInstances() {
        return this.filterChain.hasMoreInstances();
    }

    @Override
    public boolean isRestartable() {
        return this.filterChain.isRestartable();
    }

    @Override
    public Instance nextInstance() {
        return this.filterChain.nextInstance();
    }

    @Override
    public void restart() {
        this.filterChain.restart();
    }

    @Override
    public void getDescription(StringBuilder sb, int indent) {
        // TODO Auto-generated method stub
    }
}