--- /dev/null
+package jalview.math;
+
+import static org.testng.Assert.assertEquals;
+import static org.testng.Assert.fail;
+
+import java.util.Arrays;
+
+import org.testng.annotations.Test;
+
+public class MatrixTest
+{
+ @Test(groups = "Timing")
+ public void testPreMultiply_timing()
+ {
+ int rows = 500;
+ int cols = 1000;
+ double[][] d1 = new double[rows][cols];
+ double[][] d2 = new double[cols][rows];
+ Matrix m1 = new Matrix(d1, rows, cols);
+ Matrix m2 = new Matrix(d2, cols, rows);
+ 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 } }, 1, 3); // 1x3
+ Matrix m2 = new Matrix(new double[][] { { 5 }, { 6 }, { 7 } }, 3, 1); // 3x1
+
+ /*
+ * 1x3 times 3x1 is 1x1
+ * 2x5 + 3x6 + 4*7 = 56
+ */
+ Matrix m3 = m2.preMultiply(m1);
+ assertEquals(m3.rows, 1);
+ assertEquals(m3.cols, 1);
+ assertEquals(m3.value[0][0], 56d);
+
+ /*
+ * 3x1 times 1x3 is 3x3
+ */
+ m3 = m1.preMultiply(m2);
+ assertEquals(m3.rows, 3);
+ assertEquals(m3.cols, 3);
+ assertEquals(Arrays.toString(m3.value[0]), "[10.0, 15.0, 20.0]");
+ assertEquals(Arrays.toString(m3.value[1]), "[12.0, 18.0, 24.0]");
+ assertEquals(Arrays.toString(m3.value[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 } }, 2,
+ 3); // 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 } }, 2,
+ 3); // 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) {
+ return Arrays.deepEquals(m1.value, m2.value);
+ }
+
+ @Test(groups = "Functional")
+ public void testPostMultiply()
+ {
+ /*
+ * Square matrices
+ * (2 3) . (10 100)
+ * (4 5) (1000 10000)
+ * =
+ * (3020 30200)
+ * (5040 50400)
+ */
+ Matrix m1 = new Matrix(new double[][] { { 2, 3 }, { 4, 5 } }, 2, 2);
+ Matrix m2 = new Matrix(new double[][] { { 10, 100 }, { 1000, 10000 } },
+ 2, 2);
+ Matrix m3 = m1.postMultiply(m2);
+ assertEquals(Arrays.toString(m3.value[0]), "[3020.0, 30200.0]");
+ assertEquals(Arrays.toString(m3.value[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.value[0]), "[3020.0, 30200.0]");
+ assertEquals(Arrays.toString(m3.value[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 } }, 2, 1);
+ m2 = new Matrix(new double[][] { { 10, 100, 1000 } }, 1, 3);
+ m3 = m1.postMultiply(m2);
+ assertEquals(m3.rows, 2);
+ assertEquals(m3.cols, 3);
+ assertEquals(Arrays.toString(m3.value[0]), "[20.0, 200.0, 2000.0]");
+ assertEquals(Arrays.toString(m3.value[1]), "[30.0, 300.0, 3000.0]");
+ m3 = m2.preMultiply(m1);
+ assertEquals(m3.rows, 2);
+ assertEquals(m3.cols, 3);
+ assertEquals(Arrays.toString(m3.value[0]), "[20.0, 200.0, 2000.0]");
+ assertEquals(Arrays.toString(m3.value[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 } }, 1, 3);
+ m2 = new Matrix(new double[][] { { 5, 4 }, { 6, 3 }, { 7, 2 } }, 3, 2);
+ m3 = m1.postMultiply(m2);
+ assertEquals(m3.rows, 1);
+ assertEquals(m3.cols, 2);
+ assertEquals(m3.value[0][0], 56d);
+ assertEquals(m3.value[0][1], 25d);
+
+ /*
+ * and check premultiply equivalent
+ */
+ m3 = m2.preMultiply(m1);
+ assertEquals(m3.rows, 1);
+ assertEquals(m3.cols, 2);
+ assertEquals(m3.value[0][0], 56d);
+ assertEquals(m3.value[0][1], 25d);
+ }
+
+ /**
+ * 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, n, n);
+
+ // System.out.println(" --- Original matrix ---- ");
+ // / origmat.print(System.out);
+ // System.out.println();
+ // System.out.println(" --- transpose matrix ---- ");
+ Matrix trans = origmat.transpose();
+
+ // trans.print(System.out);
+ // System.out.println();
+ // System.out.println(" --- OrigT * Orig ---- ");
+ Matrix 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();
+ }
+}
git://source.jalview.org / jalview.git / blobdiff