* also check m2.preMultiply(m1) - should be same as m1.postMultiply(m2)
*/
MatrixI m4 = m2.preMultiply(m1);
- assertMatricesMatch(m3, m4);
+ assertMatricesMatch(m3, m4, 0.00001d);
/*
* m1 has more rows than columns
assertEquals(m3.getValue(1, 2), 3000d);
m4 = m2.preMultiply(m1);
- assertMatricesMatch(m3, m4);
+ assertMatricesMatch(m3, m4, 0.00001d);
/*
* m1 has more columns than rows
* and check premultiply equivalent
*/
m4 = m2.preMultiply(m1);
- assertMatricesMatch(m3, m4);
+ assertMatricesMatch(m3, m4, 0.00001d);
}
@Test(groups = "Timing")
{
/*
* make a pseudo-random symmetric matrix as required for tred/tqli
- * note: test fails for matrices larger than 6x6 due to double value
- * rounding only (random values result in very small values)
*/
- int rows = 6;
+ int rows = 10;
int cols = rows;
double[][] d = getSparseValues(rows, cols, 3);
}
Matrix m1 = new Matrix(d);
Matrix m2 = new SparseMatrix(d1);
- assertMatricesMatch(m1, m2); // sanity check
+ assertMatricesMatch(m1, m2, 0.00001d); // sanity check
m1.tred();
m2.tred();
- assertMatricesMatch(m1, m2);
+ assertMatricesMatch(m1, m2, 0.00001d);
}
- private void assertMatricesMatch(MatrixI m1, MatrixI m2)
+ private void assertMatricesMatch(MatrixI m1, MatrixI m2, double delta)
{
if (m1.height() != m2.height())
{
}
}
}
- ArrayAsserts.assertArrayEquals(m1.getD(), m2.getD(), 0.00001d);
+ ArrayAsserts.assertArrayEquals(m1.getD(), m2.getD(), delta);
ArrayAsserts.assertArrayEquals(m1.getE(), m2.getE(), 0.00001d);
}
// have to do tred() before doing tqli()
m1.tred();
m2.tred();
- assertMatricesMatch(m1, m2);
+ assertMatricesMatch(m1, m2, 0.00001d);
m1.tqli();
m2.tqli();
- assertMatricesMatch(m1, m2);
+ assertMatricesMatch(m1, m2, 0.00001d);
}
/**
*
* @param rows
* @param cols
- * @param fraction
- * one n fraction entries will be non-zero
+ * @param occupancy
+ * one in 'occupancy' entries will be non-zero
* @return
*/
- public double[][] getSparseValues(int rows, int cols, int fraction)
+ public double[][] getSparseValues(int rows, int cols, int occupancy)
{
+ /*
+ * 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 % fraction == 0)
+ if (++m % occupancy == 0)
{
- d[i][i] = r.nextDouble(); // diagonal
+ d[i][i] = r.nextInt() % 13; // diagonal
}
for (int j = 0; j < i; j++)
{
- if (++m % fraction == 0)
+ if (++m % occupancy == 0)
{
- d[i][j] = r.nextDouble();
+ d[i][j] = r.nextInt() % 13;
d[j][i] = d[i][j];
}
}
{ 0, 6, 0, 0, 0 } });
assertEquals(m1.getFillRatio(), 0.4f);
}
+
+ /**
+ * 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 SparseMatrix(d);
+ Matrix m2 = new SparseMatrix(d1);
+ assertMatricesMatch(m1, m2, 1.0e16); // sanity check
+ m1.tred();
+ m2.tred();
+ assertMatricesMatch(m1, m2, 0.00001d);
+ }
}
\ No newline at end of file