+/*
+ * Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
+ * Copyright (C) $$Year-Rel$$ The Jalview Authors
+ *
+ * This file is part of Jalview.
+ *
+ * Jalview is free software: you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation, either version 3
+ * of the License, or (at your option) any later version.
+ *
+ * Jalview 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 General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with Jalview. If not, see <http://www.gnu.org/licenses/>.
+ * The Jalview Authors are detailed in the 'AUTHORS' file.
+ */
package jalview.math;
import static org.testng.Assert.assertEquals;
public void testConstructor()
{
MatrixI m1 = new SparseMatrix(
- new double[][] { { 2, 0, 4 }, { 0, 6, 0 } });
+ new double[][]
+ { { 2, 0, 4 }, { 0, 6, 0 } });
assertEquals(m1.getValue(0, 0), 2d);
assertEquals(m1.getValue(0, 1), 0d);
assertEquals(m1.getValue(0, 2), 4d);
public void testTranspose()
{
MatrixI m1 = new SparseMatrix(
- new double[][] { { 2, 0, 4 }, { 5, 6, 0 } });
+ new double[][]
+ { { 2, 0, 4 }, { 5, 6, 0 } });
MatrixI m2 = m1.transpose();
assertTrue(m2 instanceof SparseMatrix);
assertEquals(m2.height(), 3);
assertEquals(m2.getValue(2, 0), 4d);
assertEquals(m2.getValue(2, 1), 0d);
}
+
@Test(groups = "Functional")
public void testPreMultiply()
{
@Test(
groups = "Functional",
- expectedExceptions = { IllegalArgumentException.class })
+ expectedExceptions =
+ { IllegalArgumentException.class })
public void testPreMultiply_tooManyColumns()
{
Matrix m1 = new SparseMatrix(
- new double[][] { { 2, 3, 4 }, { 3, 4, 5 } }); // 2x3
+ new double[][]
+ { { 2, 3, 4 }, { 3, 4, 5 } }); // 2x3
/*
* 2x3 times 2x3 invalid operation -
@Test(
groups = "Functional",
- expectedExceptions = { IllegalArgumentException.class })
+ expectedExceptions =
+ { IllegalArgumentException.class })
public void testPreMultiply_tooFewColumns()
{
Matrix m1 = new SparseMatrix(
- new double[][] { { 2, 3, 4 }, { 3, 4, 5 } }); // 2x3
+ new double[][]
+ { { 2, 3, 4 }, { 3, 4, 5 } }); // 2x3
/*
* 3x2 times 3x2 invalid operation -
m1.preMultiply(m1);
fail("Expected exception");
}
-
+
@Test(groups = "Functional")
public void testPostMultiply()
{
* (5040 50400)
*/
MatrixI m1 = new SparseMatrix(new double[][] { { 2, 3 }, { 4, 5 } });
- MatrixI m2 = new SparseMatrix(new double[][] { { 10, 100 },
- { 1000, 10000 } });
+ MatrixI m2 = new SparseMatrix(
+ new double[][]
+ { { 10, 100 }, { 1000, 10000 } });
MatrixI m3 = m1.postMultiply(m2);
assertEquals(m3.getValue(0, 0), 3020d);
assertEquals(m3.getValue(0, 1), 30200d);
* 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
*/
- // TODO why does this fail for rows > 9??
- int rows = 9;
+ 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);
}
int rows = 6;
int cols = rows;
double[][] d = getSparseValues(rows, cols, 3);
-
+
/*
* make a copy of the values so m1, m2 are not
* sharing arrays!
// 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);
}
/**
@Test(groups = "Functional")
public void testPreMultiply_sparseProduct()
{
- MatrixI m1 = new SparseMatrix(new double[][] { { 1 }, { 0 }, { 0 },
- { 0 }, { 0 } }); // 5x1
+ MatrixI m1 = new SparseMatrix(
+ new double[][]
+ { { 1 }, { 0 }, { 0 }, { 0 }, { 0 } }); // 5x1
MatrixI m2 = new SparseMatrix(new double[][] { { 1, 1, 1, 1 } }); // 1x4
-
+
/*
* m1.m2 makes a row of 4 1's, and 4 rows of zeros
* 20% non-zero so not 'sparse'
@Test(groups = "Functional")
public void testFillRatio()
{
- SparseMatrix m1 = new SparseMatrix(new double[][] { { 2, 0, 4, 1, 0 },
- { 0, 6, 0, 0, 0 } });
+ SparseMatrix m1 = new SparseMatrix(
+ new double[][]
+ { { 2, 0, 4, 1, 0 }, { 0, 6, 0, 0, 0 } });
assertEquals(m1.getFillRatio(), 0.4f);
}
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!
}
Matrix m1 = new SparseMatrix(d);
Matrix m2 = new SparseMatrix(d1);
- assertMatricesMatch(m1, m2); // sanity check
+ assertMatricesMatch(m1, m2, 1.0e16); // sanity check
m1.tred();
m2.tred();
- assertMatricesMatch(m1, m2);
+ assertMatricesMatch(m1, m2, 0.00001d);
}
}
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