/*
 * Copyright (c) 2020, Peter Abeles. All Rights Reserved.
 *
 * This file is part of Efficient Java Matrix Library (EJML).
 *
 * 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.
 */

package org.ejml.dense.row.decomposition.bidiagonal;

import org.ejml.data.DMatrixRMaj;
import org.ejml.dense.row.RandomMatrices_DDRM;
import org.ejml.interfaces.decomposition.BidiagonalDecomposition_F64;

import java.util.Random;

/**
 * Compare the speed of various algorithms at inverting square matrices
 *
 * @author Peter Abeles
 */
public class BenchmarkBidiagonalDecomposition {

    public static long evaluate( BidiagonalDecomposition_F64<DMatrixRMaj> alg, DMatrixRMaj orig, int numTrials ) {

        long prev = System.currentTimeMillis();

        for (long i = 0; i < numTrials; i++) {
            if (!alg.decompose(orig.copy())) {
                throw new RuntimeException("Bad matrix");
            }
//            dense.getU(null,false,false);
//            dense.getV(null,false,false);

        }

        return System.currentTimeMillis() - prev;
    }

    private static void runAlgorithms( DMatrixRMaj mat, int numTrials ) {
        if (numTrials <= 0) return;
        System.out.println("row               = " + evaluate(new BidiagonalDecompositionRow_DDRM(), mat, numTrials));
        System.out.println("tall              = " + evaluate(new BidiagonalDecompositionTall_DDRM(), mat, numTrials));
    }

    public static void main( String[] args ) {
        Random rand = new Random(23423);

        int[] size = new int[]{2, 4, 10, 100, 500, 1000, 2000, 5000, 10000};
        int[] trials = new int[]{(int)4e6, (int)1e6, (int)1e5, 200, 1, 1, 1, 1, 1};
//        int trials[] = new int[]{(int)1e6,(int)2e5,(int)2e4,50,1,1,1,1,1};

        System.out.println("Square matrix");
        // results vary significantly depending if it starts from a small or large matrix
        for (int i = 0; i < size.length; i++) {
            int w = size[i];

            System.out.printf("Decomposition size %3d for %12d trials\n", w, trials[i]);

            System.out.print("* Creating matrix ");
            DMatrixRMaj mat = RandomMatrices_DDRM.rectangle(w, w, rand);
            System.out.println("  Done.");
            runAlgorithms(mat, trials[i]);
        }

        System.out.println("Tall matrix");
        // results vary significantly depending if it starts from a small or large matrix
        for (int i = 0; i < size.length; i++) {
            int w = size[i];
            int h = w*3;

            int t = trials[i];

            if (t == 0) continue;

            System.out.printf("Decomposition size w=%3d h=%3d for %12d trials\n", w, h, t);

            System.out.print("* Creating matrix ");
            DMatrixRMaj mat = RandomMatrices_DDRM.rectangle(h, w, rand);
            System.out.println("  Done.");
            runAlgorithms(mat, t);
        }
    }
}