///////////////////////////////////////////////////////////////////////////////
// For information as to what this class does, see the Javadoc, below.       //
// Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006,       //
// 2007, 2008, 2009, 2010, 2014, 2015, 2022 by Peter Spirtes, Richard        //
// Scheines, Joseph Ramsey, and Clark Glymour.                               //
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// 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      //
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// GNU General Public License for more details.                              //
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///////////////////////////////////////////////////////////////////////////////

package edu.cmu.tetrad.data;

import edu.cmu.tetrad.util.RandomUtil;

import java.util.ArrayList;
import java.util.List;

/**
 * Provides a static method for sampling without replacement from a dataset to
 * create a new dataset with a sample size supplied by the user.
 *
 * @author Frank Wimberly
 */
public final class RandomSampler {

    /**
     * This method takes a dataset and a sample size and creates a new dataset
     * containing that number of samples by drawing with replacement from the
     * original dataset.
     */
    public static DataSet sample(DataSet dataSet,
                                 int newSampleSize) {
        if (newSampleSize < 1) {
            throw new IllegalArgumentException("Sample size must be > 0.");
        }

        if (dataSet.getNumRows() < 1) {
            throw new IllegalArgumentException("Dataset must contain samples.");
        }

        if (dataSet.getNumRows() < newSampleSize) {
            throw new IllegalArgumentException("Not enough cases in data to " +
                    "generate " + newSampleSize + " samples without replacement.");
        }

        List<Integer> indices = new ArrayList<>(dataSet.getNumRows());

        for (int i = 0; i < dataSet.getNumRows(); i++) {
            indices.add(i);
        }

        RandomUtil.shuffle(indices);

        //Number of samples in input dataset
        int ncols = dataSet.getNumColumns();

        DataSet newDataSet =
                new BoxDataSet(new VerticalDoubleDataBox(newSampleSize, dataSet.getVariables().size()), dataSet.getVariables());

        for (int i = 0; i < newSampleSize; i++) {
            int oldCase = indices.get(i);

            for (int j = 0; j < ncols; j++) {
                newDataSet.setObject(i, j, dataSet.getObject(oldCase, j));
            }
        }

        return newDataSet;
    }
}



