int maxIter = 45; // fudge - add 15 iterations, just in case
/**
- * Creates a new Matrix object.
+ * Creates a new Matrix object. For example
*
- * @param value
- * DOCUMENT ME!
+ * <pre>
+ * new Matrix(new double[][] {{2, 3}, {4, 5}, 2, 2)
+ * constructs
+ * (2 3)
+ * (4 5)
+ * </pre>
+ *
+ * Note that ragged arrays (with not all rows, or columns, of the same
+ * length), are not supported by this class. They can be constructed, but
+ * results of operations on them are undefined and may throw exceptions.
+ *
+ * @param values
+ * the matrix values in row-major order
* @param rows
- * DOCUMENT ME!
* @param cols
- * DOCUMENT ME!
*/
- public Matrix(double[][] value, int rows, int cols)
+ public Matrix(double[][] values, int rows, int cols)
{
this.rows = rows;
this.cols = cols;
- this.value = value;
+ this.value = values;
}
/**
- * DOCUMENT ME!
+ * Returns a new matrix which is the transposes of this one
*
* @return DOCUMENT ME!
*/
}
/**
- * DOCUMENT ME!
+ * Returns a new matrix which is the result of premultiplying this matrix by
+ * the supplied argument. If this of size AxB (A rows and B columns), and the
+ * argument is CxA (C rows and A columns), the result is of size CxB.
*
* @param in
- * DOCUMENT ME!
*
- * @return DOCUMENT ME!
+ * @return
+ * @throws IllegalArgumentException
+ * if the number of columns in the pre-multiplier is not equal to
+ * the number of rows in the multiplicand (this)
*/
public Matrix preMultiply(Matrix in)
{
+ if (in.cols != this.rows)
+ {
+ throw new IllegalArgumentException("Can't pre-multiply " + this.rows
+ + " rows by " + in.cols + " columns");
+ }
double[][] tmp = new double[in.rows][this.cols];
for (int i = 0; i < in.rows; i++)
}
/**
- * DOCUMENT ME!
*
* @param in
- * DOCUMENT ME!
*
- * @return DOCUMENT ME!
+ * @return
*/
public double[] vectorPostMultiply(double[] in)
{
}
/**
- * DOCUMENT ME!
+ * Returns a new matrix which is the result of postmultiplying this matrix by
+ * the supplied argument. If this of size AxB (A rows and B columns), and the
+ * argument is BxC (B rows and C columns), the result is of size AxC.
+ * <p>
+ * This method simply returns the result of in.preMultiply(this)
*
* @param in
- * DOCUMENT ME!
*
- * @return DOCUMENT ME!
+ * @return
+ * @throws IllegalArgumentException
+ * if the number of rows in the post-multiplier is not equal to the
+ * number of columns in the multiplicand (this)
+ * @see #preMultiply(Matrix)
*/
public Matrix postMultiply(Matrix in)
{
- double[][] out = new double[this.rows][in.cols];
-
- for (int i = 0; i < this.rows; i++)
+ if (in.rows != this.cols)
{
- for (int j = 0; j < in.cols; j++)
- {
- out[i][j] = 0.0;
-
- for (int k = 0; k < rows; k++)
- {
- out[i][j] = out[i][j] + (value[i][k] * in.value[k][j]);
- }
- }
+ throw new IllegalArgumentException("Can't post-multiply " + this.cols
+ + " columns by " + in.rows + " rows");
}
-
- return new Matrix(out, this.cols, in.rows);
+ return in.preMultiply(this);
}
/**
- * DOCUMENT ME!
+ * Answers a new matrix with a copy of the values in this one
*
- * @return DOCUMENT ME!
+ * @return
*/
public Matrix copy()
{
for (int i = 0; i < rows; i++)
{
- for (int j = 0; j < cols; j++)
- {
- newmat[i][j] = value[i][j];
- }
+ System.arraycopy(value[i], 0, newmat[i], 0, value[i].length);
+ // for (int j = 0; j < cols; j++)
+ // {
+ // newmat[i][j] = value[i][j];
+ // }
}
return new Matrix(newmat, rows, cols);
}
/**
- * DOCUMENT ME!
+ * Returns an array containing the values in the specified column
*
- * @param n
- * DOCUMENT ME!
+ * @param col
*
- * @return DOCUMENT ME!
+ * @return
*/
- public double[] getColumn(int n)
+ public double[] getColumn(int col)
{
double[] out = new double[rows];
for (int i = 0; i < rows; i++)
{
- out[i] = value[i][n];
+ out[i] = value[i][col];
}
return out;
Format.print(ps, "%15.4e", e[j]);
}
}
-
- /**
- * DOCUMENT ME!
- *
- * @param args
- * DOCUMENT ME!
- */
- 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] = (double) 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();
- }
}
--- /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 / commitdiff