X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=test%2Fjalview%2Fmath%2FMatrixTest.java;fp=test%2Fjalview%2Fmath%2FMatrixTest.java;h=0000000000000000000000000000000000000000;hb=4f77328104498504339216829abf5ea87e2791ec;hp=7dc3b9e018f4e274e5bf660f77b9933c094e10fe;hpb=2b8c0785318a3528e1876e8e2dd48b7d831eae69;p=jalview.git

diff --git a/test/jalview/math/MatrixTest.java b/test/jalview/math/MatrixTest.java
deleted file mode 100644
index 7dc3b9e..0000000
--- a/test/jalview/math/MatrixTest.java
+++ /dev/null
@@ -1,577 +0,0 @@
-package jalview.math;
-
-import static org.testng.Assert.assertEquals;
-import static org.testng.Assert.assertFalse;
-import static org.testng.Assert.assertNotSame;
-import static org.testng.Assert.assertNull;
-import static org.testng.Assert.assertTrue;
-import static org.testng.Assert.fail;
-
-import java.util.Arrays;
-import java.util.Random;
-
-import org.testng.annotations.Test;
-import org.testng.internal.junit.ArrayAsserts;
-
-public class MatrixTest
-{
-  final static double DELTA = 0.000001d;
-
-  @Test(groups = "Timing")
-  public void testPreMultiply_timing()
-  {
-    int rows = 50; // increase to stress test timing
-    int cols = 100;
-    double[][] d1 = new double[rows][cols];
-    double[][] d2 = new double[cols][rows];
-    Matrix m1 = new Matrix(d1);
-    Matrix m2 = new Matrix(d2);
-    long start = System.currentTimeMillis();
-    m1.preMultiply(m2);
-    long elapsed = System.currentTimeMillis() - start;
-    System.out.println(rows + "x" + cols
-            + " multiplications of double took " + elapsed + "ms");
-  }
-
-  @Test(groups = "Functional")
-  public void testPreMultiply()
-  {
-    Matrix m1 = new Matrix(new double[][] { { 2, 3, 4 } }); // 1x3
-    Matrix m2 = new Matrix(new double[][] { { 5 }, { 6 }, { 7 } }); // 3x1
-
-    /*
-     * 1x3 times 3x1 is 1x1
-     * 2x5 + 3x6 + 4*7 =  56
-     */
-    MatrixI m3 = m2.preMultiply(m1);
-    assertEquals(m3.height(), 1);
-    assertEquals(m3.width(), 1);
-    assertEquals(m3.getValue(0, 0), 56d);
-
-    /*
-     * 3x1 times 1x3 is 3x3
-     */
-    m3 = m1.preMultiply(m2);
-    assertEquals(m3.height(), 3);
-    assertEquals(m3.width(), 3);
-    assertEquals(Arrays.toString(m3.getRow(0)), "[10.0, 15.0, 20.0]");
-    assertEquals(Arrays.toString(m3.getRow(1)), "[12.0, 18.0, 24.0]");
-    assertEquals(Arrays.toString(m3.getRow(2)), "[14.0, 21.0, 28.0]");
-  }
-
-  @Test(
-    groups = "Functional",
-    expectedExceptions = { IllegalArgumentException.class })
-  public void testPreMultiply_tooManyColumns()
-  {
-    Matrix m1 = new Matrix(new double[][] { { 2, 3, 4 }, { 3, 4, 5 } }); // 2x3
-
-    /*
-     * 2x3 times 2x3 invalid operation - 
-     * multiplier has more columns than multiplicand has rows
-     */
-    m1.preMultiply(m1);
-    fail("Expected exception");
-  }
-
-  @Test(
-    groups = "Functional",
-    expectedExceptions = { IllegalArgumentException.class })
-  public void testPreMultiply_tooFewColumns()
-  {
-    Matrix m1 = new Matrix(new double[][] { { 2, 3, 4 }, { 3, 4, 5 } }); // 2x3
-
-    /*
-     * 3x2 times 3x2 invalid operation - 
-     * multiplier has more columns than multiplicand has row
-     */
-    m1.preMultiply(m1);
-    fail("Expected exception");
-  }
-  
-  
-  private boolean matrixEquals(Matrix m1, Matrix m2) {
-    if (m1.width() != m2.width() || m1.height() != m2.height())
-    {
-      return false;
-    }
-    for (int i = 0; i < m1.height(); i++)
-    {
-      if (!Arrays.equals(m1.getRow(i), m2.getRow(i)))
-      {
-        return false;
-      }
-    }
-    return true;
-  }
-
-  @Test(groups = "Functional")
-  public void testPostMultiply()
-  {
-    /*
-     * Square matrices
-     * (2 3) . (10   100)
-     * (4 5)   (1000 10000)
-     * =
-     * (3020 30200)
-     * (5040 50400)
-     */
-    MatrixI m1 = new Matrix(new double[][] { { 2, 3 }, { 4, 5 } });
-    MatrixI m2 = new Matrix(new double[][] { { 10, 100 }, { 1000, 10000 } });
-    MatrixI m3 = m1.postMultiply(m2);
-    assertEquals(Arrays.toString(m3.getRow(0)), "[3020.0, 30200.0]");
-    assertEquals(Arrays.toString(m3.getRow(1)), "[5040.0, 50400.0]");
-
-    /*
-     * also check m2.preMultiply(m1) - should be same as m1.postMultiply(m2) 
-     */
-    m3 = m2.preMultiply(m1);
-    assertEquals(Arrays.toString(m3.getRow(0)), "[3020.0, 30200.0]");
-    assertEquals(Arrays.toString(m3.getRow(1)), "[5040.0, 50400.0]");
-
-    /*
-     * m1 has more rows than columns
-     * (2).(10 100 1000) = (20 200 2000)
-     * (3)                 (30 300 3000)
-     */
-    m1 = new Matrix(new double[][] { { 2 }, { 3 } });
-    m2 = new Matrix(new double[][] { { 10, 100, 1000 } });
-    m3 = m1.postMultiply(m2);
-    assertEquals(m3.height(), 2);
-    assertEquals(m3.width(), 3);
-    assertEquals(Arrays.toString(m3.getRow(0)), "[20.0, 200.0, 2000.0]");
-    assertEquals(Arrays.toString(m3.getRow(1)), "[30.0, 300.0, 3000.0]");
-    m3 = m2.preMultiply(m1);
-    assertEquals(m3.height(), 2);
-    assertEquals(m3.width(), 3);
-    assertEquals(Arrays.toString(m3.getRow(0)), "[20.0, 200.0, 2000.0]");
-    assertEquals(Arrays.toString(m3.getRow(1)), "[30.0, 300.0, 3000.0]");
-
-    /*
-     * m1 has more columns than rows
-     * (2 3 4) . (5 4) = (56 25)
-     *           (6 3) 
-     *           (7 2)
-     * [0, 0] = 2*5 + 3*6 + 4*7 = 56
-     * [0, 1] = 2*4 + 3*3 + 4*2 = 25  
-     */
-    m1 = new Matrix(new double[][] { { 2, 3, 4 } });
-    m2 = new Matrix(new double[][] { { 5, 4 }, { 6, 3 }, { 7, 2 } });
-    m3 = m1.postMultiply(m2);
-    assertEquals(m3.height(), 1);
-    assertEquals(m3.width(), 2);
-    assertEquals(m3.getRow(0)[0], 56d);
-    assertEquals(m3.getRow(0)[1], 25d);
-
-    /*
-     * and check premultiply equivalent
-     */
-    m3 = m2.preMultiply(m1);
-    assertEquals(m3.height(), 1);
-    assertEquals(m3.width(), 2);
-    assertEquals(m3.getRow(0)[0], 56d);
-    assertEquals(m3.getRow(0)[1], 25d);
-  }
-
-  @Test(groups = "Functional")
-  public void testCopy()
-  {
-    Random r = new Random();
-    int rows = 5;
-    int cols = 11;
-    double[][] in = new double[rows][cols];
-
-    for (int i = 0; i < rows; i++)
-    {
-      for (int j = 0; j < cols; j++)
-      {
-        in[i][j] = r.nextDouble();
-      }
-    }
-    Matrix m1 = new Matrix(in);
-
-    Matrix m2 = (Matrix) m1.copy();
-    assertNotSame(m1, m2);
-    assertTrue(matrixEquals(m1, m2));
-    assertNull(m2.d);
-    assertNull(m2.e);
-
-    /*
-     * now add d and e vectors and recopy
-     */
-    m1.d = Arrays.copyOf(in[2], in[2].length);
-    m1.e = Arrays.copyOf(in[4], in[4].length);
-    m2 = (Matrix) m1.copy();
-    assertNotSame(m2.d, m1.d);
-    assertNotSame(m2.e, m1.e);
-    assertEquals(m2.d, m1.d);
-    assertEquals(m2.e, m1.e);
-  }
-
-  /**
-   * main method extracted from Matrix
-   * 
-   * @param args
-   */
-  public static void main(String[] args) throws Exception
-  {
-    int n = Integer.parseInt(args[0]);
-    double[][] in = new double[n][n];
-  
-    for (int i = 0; i < n; i++)
-    {
-      for (int j = 0; j < n; j++)
-      {
-        in[i][j] = Math.random();
-      }
-    }
-  
-    Matrix origmat = new Matrix(in);
-  
-    // System.out.println(" --- Original matrix ---- ");
-    // / origmat.print(System.out);
-    // System.out.println();
-    // System.out.println(" --- transpose matrix ---- ");
-    MatrixI trans = origmat.transpose();
-  
-    // trans.print(System.out);
-    // System.out.println();
-    // System.out.println(" --- OrigT * Orig ---- ");
-    MatrixI symm = trans.postMultiply(origmat);
-  
-    // symm.print(System.out);
-    // System.out.println();
-    // Copy the symmetric matrix for later
-    // Matrix origsymm = symm.copy();
-  
-    // This produces the tridiagonal transformation matrix
-    // long tstart = System.currentTimeMillis();
-    symm.tred();
-  
-    // long tend = System.currentTimeMillis();
-  
-    // System.out.println("Time take for tred = " + (tend-tstart) + "ms");
-    // System.out.println(" ---Tridiag transform matrix ---");
-    // symm.print(System.out);
-    // System.out.println();
-    // System.out.println(" --- D vector ---");
-    // symm.printD(System.out);
-    // System.out.println();
-    // System.out.println(" --- E vector ---");
-    // symm.printE(System.out);
-    // System.out.println();
-    // Now produce the diagonalization matrix
-    // tstart = System.currentTimeMillis();
-    symm.tqli();
-    // tend = System.currentTimeMillis();
-  
-    // System.out.println("Time take for tqli = " + (tend-tstart) + " ms");
-    // System.out.println(" --- New diagonalization matrix ---");
-    // symm.print(System.out);
-    // System.out.println();
-    // System.out.println(" --- D vector ---");
-    // symm.printD(System.out);
-    // System.out.println();
-    // System.out.println(" --- E vector ---");
-    // symm.printE(System.out);
-    // System.out.println();
-    // System.out.println(" --- First eigenvector --- ");
-    // double[] eigenv = symm.getColumn(0);
-    // for (int i=0; i < eigenv.length;i++) {
-    // Format.print(System.out,"%15.4f",eigenv[i]);
-    // }
-    // System.out.println();
-    // double[] neigenv = origsymm.vectorPostMultiply(eigenv);
-    // for (int i=0; i < neigenv.length;i++) {
-    // Format.print(System.out,"%15.4f",neigenv[i]/symm.d[0]);
-    // }
-    // System.out.println();
-  }
-
-  @Test(groups = "Timing")
-  public void testSign()
-  {
-    assertEquals(Matrix.sign(-1, -2), -1d);
-    assertEquals(Matrix.sign(-1, 2), 1d);
-    assertEquals(Matrix.sign(-1, 0), 1d);
-    assertEquals(Matrix.sign(1, -2), -1d);
-    assertEquals(Matrix.sign(1, 2), 1d);
-    assertEquals(Matrix.sign(1, 0), 1d);
-  }
-
-  /**
-   * Helper method to make values for a sparse, pseudo-random symmetric matrix
-   * 
-   * @param rows
-   * @param cols
-   * @param occupancy
-   *          one in 'occupancy' entries will be non-zero
-   * @return
-   */
-  public double[][] getSparseValues(int rows, int cols, int occupancy)
-  {
-    Random r = new Random(1729);
-
-    /*
-     * generate whole number values between -12 and +12
-     * (to mimic score matrices used in Jalview)
-     */
-    double[][] d = new double[rows][cols];
-    int m = 0;
-    for (int i = 0; i < rows; i++)
-    {
-      if (++m % occupancy == 0)
-      {
-        d[i][i] = r.nextInt() % 13; // diagonal
-      }
-      for (int j = 0; j < i; j++)
-      {
-        if (++m % occupancy == 0)
-        {
-          d[i][j] = r.nextInt() % 13;
-          d[j][i] = d[i][j];
-        }
-      }
-    }
-    return d;
-  
-  }
-
-  /**
-   * Verify that the results of method tred() are the same if the calculation is
-   * redone
-   */
-  @Test(groups = "Functional")
-  public void testTred_reproducible()
-  {
-    /*
-     * make a pseudo-random symmetric matrix as required for tred/tqli
-     */
-    int rows = 10;
-    int cols = rows;
-    double[][] d = getSparseValues(rows, cols, 3);
-  
-    /*
-     * make a copy of the values so m1, m2 are not
-     * sharing arrays!
-     */
-    double[][] d1 = new double[rows][cols];
-    for (int row = 0; row < rows; row++)
-    {
-      for (int col = 0; col < cols; col++)
-      {
-        d1[row][col] = d[row][col];
-      }
-    }
-    Matrix m1 = new Matrix(d);
-    Matrix m2 = new Matrix(d1);
-    assertMatricesMatch(m1, m2); // sanity check
-    m1.tred();
-    m2.tred();
-    assertMatricesMatch(m1, m2);
-  }
-
-  public static void assertMatricesMatch(MatrixI m1, MatrixI m2)
-  {
-    if (m1.height() != m2.height())
-    {
-      fail("height mismatch");
-    }
-    if (m1.width() != m2.width())
-    {
-      fail("width mismatch");
-    }
-    for (int row = 0; row < m1.height(); row++)
-    {
-      for (int col = 0; col < m1.width(); col++)
-      {
-        double v2 = m2.getValue(row, col);
-        double v1 = m1.getValue(row, col);
-        if (Math.abs(v1 - v2) > DELTA)
-        {
-          fail(String.format("At [%d, %d] %f != %f", row, col, v1, v2));
-        }
-      }
-    }
-    ArrayAsserts.assertArrayEquals("D vector", m1.getD(), m2.getD(),
-            0.00001d);
-    ArrayAsserts.assertArrayEquals("E vector", m1.getE(), m2.getE(),
-            0.00001d);
-  }
-
-  @Test(groups = "Functional")
-  public void testFindMinMax()
-  {
-    /*
-     * empty matrix case
-     */
-    Matrix m = new Matrix(new double[][] { {} });
-    assertNull(m.findMinMax());
-
-    /*
-     * normal case
-     */
-    double[][] vals = new double[2][];
-    vals[0] = new double[] {7d, 1d, -2.3d};
-    vals[1] = new double[] {-12d, 94.3d, -102.34d};
-    m = new Matrix(vals);
-    double[] minMax = m.findMinMax();
-    assertEquals(minMax[0], -102.34d);
-    assertEquals(minMax[1], 94.3d);
-  }
-
-  @Test(groups = { "Functional", "Timing" })
-  public void testFindMinMax_timing()
-  {
-    Random r = new Random();
-    int size = 1000; // increase to stress test timing
-    double[][] vals = new double[size][size];
-    double max = -Double.MAX_VALUE;
-    double min = Double.MAX_VALUE;
-    for (int i = 0; i < size; i++)
-    {
-      vals[i] = new double[size];
-      for (int j = 0; j < size; j++)
-      {
-        // use nextLong rather than nextDouble to include negative values
-        double d = r.nextLong();
-        if (d > max)
-        {
-          max = d;
-        }
-        if (d < min)
-        {
-          min = d;
-        }
-        vals[i][j] = d;
-      }
-    }
-    Matrix m = new Matrix(vals);
-    long now = System.currentTimeMillis();
-    double[] minMax = m.findMinMax();
-    System.out.println(String.format("findMinMax for %d x %d took %dms",
-            size, size, (System.currentTimeMillis() - now)));
-    assertEquals(minMax[0], min);
-    assertEquals(minMax[1], max);
-  }
-
-  /**
-   * Test range reversal with maximum value becoming zero
-   */
-  @Test(groups = "Functional")
-  public void testReverseRange_maxToZero()
-  {
-    Matrix m1 = new Matrix(
-            new double[][] { { 2, 3.5, 4 }, { -3.4, 4, 15 } });
-
-    /*
-     * subtract all from max: range -3.4 to 15 becomes 18.4 to 0
-     */
-    m1.reverseRange(true);
-    assertEquals(m1.getValue(0, 0), 13d, DELTA);
-    assertEquals(m1.getValue(0, 1), 11.5d, DELTA);
-    assertEquals(m1.getValue(0, 2), 11d, DELTA);
-    assertEquals(m1.getValue(1, 0), 18.4d, DELTA);
-    assertEquals(m1.getValue(1, 1), 11d, DELTA);
-    assertEquals(m1.getValue(1, 2), 0d, DELTA);
-
-    /*
-     * repeat operation - range is now 0 to 18.4
-     */
-    m1.reverseRange(true);
-    assertEquals(m1.getValue(0, 0), 5.4d, DELTA);
-    assertEquals(m1.getValue(0, 1), 6.9d, DELTA);
-    assertEquals(m1.getValue(0, 2), 7.4d, DELTA);
-    assertEquals(m1.getValue(1, 0), 0d, DELTA);
-    assertEquals(m1.getValue(1, 1), 7.4d, DELTA);
-    assertEquals(m1.getValue(1, 2), 18.4d, DELTA);
-  }
-
-  /**
-   * Test range reversal with minimum and maximum values swapped
-   */
-  @Test(groups = "Functional")
-  public void testReverseRange_swapMinMax()
-  {
-    Matrix m1 = new Matrix(
-            new double[][] { { 2, 3.5, 4 }, { -3.4, 4, 15 } });
-  
-    /*
-     * swap all values in min-max range
-     * = subtract from (min + max = 11.6) 
-     * range -3.4 to 15 becomes 18.4 to -3.4
-     */
-    m1.reverseRange(false);
-    assertEquals(m1.getValue(0, 0), 9.6d, DELTA);
-    assertEquals(m1.getValue(0, 1), 8.1d, DELTA);
-    assertEquals(m1.getValue(0, 2), 7.6d, DELTA);
-    assertEquals(m1.getValue(1, 0), 15d, DELTA);
-    assertEquals(m1.getValue(1, 1), 7.6d, DELTA);
-    assertEquals(m1.getValue(1, 2), -3.4d, DELTA);
-  
-    /*
-     * repeat operation - original values restored
-     */
-    m1.reverseRange(false);
-    assertEquals(m1.getValue(0, 0), 2d, DELTA);
-    assertEquals(m1.getValue(0, 1), 3.5d, DELTA);
-    assertEquals(m1.getValue(0, 2), 4d, DELTA);
-    assertEquals(m1.getValue(1, 0), -3.4d, DELTA);
-    assertEquals(m1.getValue(1, 1), 4d, DELTA);
-    assertEquals(m1.getValue(1, 2), 15d, DELTA);
-  }
-
-  @Test(groups = "Functional")
-  public void testMultiply()
-  {
-    Matrix m = new Matrix(new double[][] { { 2, 3.5, 4 }, { -3.4, 4, 15 } });
-    m.multiply(2d);
-    assertEquals(m.getValue(0, 0), 4d, DELTA);
-    assertEquals(m.getValue(0, 1), 7d, DELTA);
-    assertEquals(m.getValue(0, 2), 8d, DELTA);
-    assertEquals(m.getValue(1, 0), -6.8d, DELTA);
-    assertEquals(m.getValue(1, 1), 8d, DELTA);
-    assertEquals(m.getValue(1, 2), 30d, DELTA);
-  }
-
-  @Test(groups = "Functional")
-  public void testConstructor()
-  {
-    double[][] values = new double[][] { { 1, 2, 3 }, { 4, 5, 6 } };
-    Matrix m = new Matrix(values);
-    assertEquals(m.getValue(0, 0), 1d, DELTA);
-
-    /*
-     * verify the matrix has a copy of the original array
-     */
-    assertNotSame(values[0], m.getRow(0));
-    values[0][0] = -1d;
-    assertEquals(m.getValue(0, 0), 1d, DELTA); // unchanged
-  }
-
-  @Test(groups = "Functional")
-  public void testEquals()
-  {
-    double[][] values = new double[][] { { 1, 2, 3 }, { 4, 5, 6 } };
-    Matrix m1 = new Matrix(values);
-    double[][] values2 = new double[][] { { 1, 2, 3 }, { 4, 5, 6 } };
-    Matrix m2 = new Matrix(values2);
-
-    double delta = 0.0001d;
-    assertTrue(m1.equals(m1, delta));
-    assertTrue(m1.equals(m2, delta));
-    assertTrue(m2.equals(m1, delta));
-
-    double[][] values3 = new double[][] { { 1, 2, 3 }, { 4, 5, 7 } };
-    m2 = new Matrix(values3);
-    assertFalse(m1.equals(m2, delta));
-    assertFalse(m2.equals(m1, delta));
-
-    // must be same shape
-    values2 = new double[][] { { 1, 2, 3 } };
-    m2 = new Matrix(values2);
-    assertFalse(m2.equals(m1, delta));
-
-    assertFalse(m1.equals(null, delta));
-  }
-}