SparseFloatArrayTest.java

/**
 * Bobo Browse Engine - High performance faceted/parametric search implementation
 * that handles various types of semi-structured data.  Written in Java.
 *
 * Copyright (C) 2005-2006  Spackle
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library 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
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 *
 * To contact the project administrators for the bobo-browse project,
 * please go to https://sourceforge.net/projects/bobo-browse/, or
 * send mail to owner@browseengine.com.
 */
package com.browseengine.bobo.util.test;

import java.util.Random;

import junit.framework.TestCase;

import com.browseengine.bobo.util.SparseFloatArray;

public class SparseFloatArrayTest extends TestCase {
  private static final long SEED = -1587797429870936371L;

  public void testSpeed() throws Throwable {
    try {
      float[] orig = new float[32 * 1024 * 1024];
      float density = 0.4f;
      Random rand = new Random(SEED);
      int idx = 0;
      while (rand.nextFloat() > density) {
        idx++;
      }
      int count = 0;
      while (idx < orig.length) {
        orig[idx] = rand.nextFloat();
        count++;
        idx += 1;
        while (rand.nextDouble() > density) {
          idx++;
        }
      }
      assertTrue("count was bad: " + count, count > 100 && count < orig.length / 2);
      System.out.println("float array with " + count + " out of " + orig.length
          + " non-zero values");

      SparseFloatArray sparse = new SparseFloatArray(orig);

      for (int i = 0; i < orig.length; i++) {
        float o = orig[i];
        float s = sparse.get(i);
        assertTrue("orig " + o + " wasn't the same as sparse: " + s + " for i = " + i, o == s);
      }
      // things came out correct

      long markTime = System.currentTimeMillis();
      for (int i = 0; i < orig.length; i++) {
        @SuppressWarnings("unused")
        float f = orig[i];
      }
      long elapsedTimeOrig = System.currentTimeMillis() - markTime;

      markTime = System.currentTimeMillis();
      for (int i = 0; i < orig.length; i++) {
        sparse.get(i);
      }
      long elapsedTimeSparse = System.currentTimeMillis() - markTime;

      double ratio = (double) elapsedTimeSparse / (double) elapsedTimeOrig;
      System.out.println("fyi on speed, direct array access took " + elapsedTimeOrig
          + " millis, while sparse float access took " + elapsedTimeSparse + "; that's a " + ratio
          + " X slowdown by using the condensed memory model (smaller number is better)");

      System.out.println(getName() + " success!");
    } catch (Throwable t) {
      t.printStackTrace();
      System.err.println("fail: " + t);
      throw t;
    }
  }
}