| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You under the Apache License, Version 2.0 |
| * (the "License"); you may not use this file except in compliance with |
| * the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| package org.apache.commons.math4.linear; |
| |
| import org.junit.Test; |
| import org.junit.Assert; |
| import org.apache.commons.math4.Field; |
| import org.apache.commons.math4.exception.MathIllegalArgumentException; |
| import org.apache.commons.math4.exception.NoDataException; |
| import org.apache.commons.math4.exception.NullArgumentException; |
| import org.apache.commons.math4.exception.NumberIsTooSmallException; |
| import org.apache.commons.math4.exception.OutOfRangeException; |
| import org.apache.commons.math4.dfp.Dfp; |
| import org.apache.commons.math4.linear.Array2DRowFieldMatrix; |
| import org.apache.commons.math4.linear.ArrayFieldVector; |
| import org.apache.commons.math4.linear.FieldLUDecomposition; |
| import org.apache.commons.math4.linear.FieldMatrix; |
| import org.apache.commons.math4.linear.FieldVector; |
| import org.apache.commons.math4.linear.NonSquareMatrixException; |
| import org.apache.commons.math4.linear.SparseFieldMatrix; |
| |
| /** |
| * Test cases for the {@link SparseFieldMatrix} class. |
| * |
| */ |
| public class SparseFieldMatrixTest { |
| // 3 x 3 identity matrix |
| protected Dfp[][] id = { {Dfp25.of(1), Dfp25.of(0), Dfp25.of(0) }, { Dfp25.of(0), Dfp25.of(1), Dfp25.of(0) }, { Dfp25.of(0), Dfp25.of(0), Dfp25.of(1) } }; |
| // Test data for group operations |
| protected Dfp[][] testData = { { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3) }, { Dfp25.of(2), Dfp25.of(5), Dfp25.of(3) }, |
| { Dfp25.of(1), Dfp25.of(0), Dfp25.of(8) } }; |
| protected Dfp[][] testDataLU = null; |
| protected Dfp[][] testDataPlus2 = { { Dfp25.of(3), Dfp25.of(4), Dfp25.of(5) }, { Dfp25.of(4), Dfp25.of(7), Dfp25.of(5) }, |
| { Dfp25.of(3), Dfp25.of(2), Dfp25.of(10) } }; |
| protected Dfp[][] testDataMinus = { { Dfp25.of(-1), Dfp25.of(-2), Dfp25.of(-3) }, |
| { Dfp25.of(-2), Dfp25.of(-5), Dfp25.of(-3) }, { Dfp25.of(-1), Dfp25.of(0), Dfp25.of(-8) } }; |
| protected Dfp[] testDataRow1 = { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3) }; |
| protected Dfp[] testDataCol3 = { Dfp25.of(3), Dfp25.of(3), Dfp25.of(8) }; |
| protected Dfp[][] testDataInv = { { Dfp25.of(-40), Dfp25.of(16), Dfp25.of(9) }, { Dfp25.of(13), Dfp25.of(-5), Dfp25.of(-3) }, |
| { Dfp25.of(5), Dfp25.of(-2), Dfp25.of(-1) } }; |
| protected Dfp[] preMultTest = { Dfp25.of(8), Dfp25.of(12), Dfp25.of(33) }; |
| protected Dfp[][] testData2 = { { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3) }, { Dfp25.of(2), Dfp25.of(5), Dfp25.of(3) } }; |
| protected Dfp[][] testData2T = { { Dfp25.of(1), Dfp25.of(2) }, { Dfp25.of(2), Dfp25.of(5) }, { Dfp25.of(3), Dfp25.of(3) } }; |
| protected Dfp[][] testDataPlusInv = { { Dfp25.of(-39), Dfp25.of(18), Dfp25.of(12) }, |
| { Dfp25.of(15), Dfp25.of(0), Dfp25.of(0) }, { Dfp25.of(6), Dfp25.of(-2), Dfp25.of(7) } }; |
| |
| // lu decomposition tests |
| protected Dfp[][] luData = { { Dfp25.of(2), Dfp25.of(3), Dfp25.of(3) }, { Dfp25.of(0), Dfp25.of(5), Dfp25.of(7) }, { Dfp25.of(6), Dfp25.of(9), Dfp25.of(8) } }; |
| protected Dfp[][] luDataLUDecomposition = null; |
| |
| // singular matrices |
| protected Dfp[][] singular = { { Dfp25.of(2), Dfp25.of(3) }, { Dfp25.of(2), Dfp25.of(3) } }; |
| protected Dfp[][] bigSingular = { { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) }, |
| { Dfp25.of(2), Dfp25.of(5), Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(7), Dfp25.of(3), Dfp25.of(256), Dfp25.of(1930) }, { Dfp25.of(3), Dfp25.of(7), Dfp25.of(6), Dfp25.of(8) } }; // 4th |
| |
| // row |
| // = |
| // 1st |
| // + |
| // 2nd |
| protected Dfp[][] detData = { { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3) }, { Dfp25.of(4), Dfp25.of(5), Dfp25.of(6) }, |
| { Dfp25.of(7), Dfp25.of(8), Dfp25.of(10) } }; |
| protected Dfp[][] detData2 = { { Dfp25.of(1), Dfp25.of(3) }, { Dfp25.of(2), Dfp25.of(4) } }; |
| |
| // vectors |
| protected Dfp[] testVector = { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3) }; |
| protected Dfp[] testVector2 = { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) }; |
| |
| // submatrix accessor tests |
| protected Dfp[][] subTestData = null; |
| |
| // array selections |
| protected Dfp[][] subRows02Cols13 = { {Dfp25.of(2), Dfp25.of(4) }, { Dfp25.of(4), Dfp25.of(8) } }; |
| protected Dfp[][] subRows03Cols12 = { { Dfp25.of(2), Dfp25.of(3) }, { Dfp25.of(5), Dfp25.of(6) } }; |
| protected Dfp[][] subRows03Cols123 = { { Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(5), Dfp25.of(6), Dfp25.of(7) } }; |
| |
| // effective permutations |
| protected Dfp[][] subRows20Cols123 = { { Dfp25.of(4), Dfp25.of(6), Dfp25.of(8) }, { Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) } }; |
| protected Dfp[][] subRows31Cols31 = null; |
| |
| // contiguous ranges |
| protected Dfp[][] subRows01Cols23 = null; |
| protected Dfp[][] subRows23Cols00 = { { Dfp25.of(2) }, { Dfp25.of(4) } }; |
| protected Dfp[][] subRows00Cols33 = { { Dfp25.of(4) } }; |
| |
| // row matrices |
| protected Dfp[][] subRow0 = { { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) } }; |
| protected Dfp[][] subRow3 = { { Dfp25.of(4), Dfp25.of(5), Dfp25.of(6), Dfp25.of(7) } }; |
| |
| // column matrices |
| protected Dfp[][] subColumn1 = null; |
| protected Dfp[][] subColumn3 = null; |
| |
| // tolerances |
| protected double entryTolerance = 10E-16; |
| protected double normTolerance = 10E-14; |
| protected Field<Dfp> field = Dfp25.getField(); |
| |
| public SparseFieldMatrixTest() { |
| testDataLU = new Dfp[][]{ { Dfp25.of(2), Dfp25.of(5), Dfp25.of(3) }, { Dfp25.of(.5d), Dfp25.of(-2.5d), Dfp25.of(6.5d) }, |
| { Dfp25.of(0.5d), Dfp25.of(0.2d), Dfp25.of(.2d) } }; |
| luDataLUDecomposition = new Dfp[][]{ { Dfp25.of(6), Dfp25.of(9), Dfp25.of(8) }, |
| { Dfp25.of(0), Dfp25.of(5), Dfp25.of(7) }, { Dfp25.of(0.33333333333333), Dfp25.of(0), Dfp25.of(0.33333333333333) } }; |
| subTestData = new Dfp[][]{ { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) }, |
| { Dfp25.of(1.5), Dfp25.of(2.5), Dfp25.of(3.5), Dfp25.of(4.5) }, { Dfp25.of(2), Dfp25.of(4), Dfp25.of(6), Dfp25.of(8) }, { Dfp25.of(4), Dfp25.of(5), Dfp25.of(6), Dfp25.of(7) } }; |
| subRows31Cols31 = new Dfp[][]{ { Dfp25.of(7), Dfp25.of(5) }, { Dfp25.of(4.5), Dfp25.of(2.5) } }; |
| subRows01Cols23 = new Dfp[][]{ { Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(3.5), Dfp25.of(4.5) } }; |
| subColumn1 = new Dfp[][]{ { Dfp25.of(2) }, { Dfp25.of(2.5) }, { Dfp25.of(4) }, { Dfp25.of(5) } }; |
| subColumn3 = new Dfp[][]{ { Dfp25.of(4) }, { Dfp25.of(4.5) }, { Dfp25.of(8) }, { Dfp25.of(7) } }; |
| } |
| |
| /** test dimensions */ |
| @Test |
| public void testDimensions() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| SparseFieldMatrix<Dfp> m2 = createSparseMatrix(testData2); |
| Assert.assertEquals("testData row dimension", 3, m.getRowDimension()); |
| Assert.assertEquals("testData column dimension", 3, m.getColumnDimension()); |
| Assert.assertTrue("testData is square", m.isSquare()); |
| Assert.assertEquals("testData2 row dimension", m2.getRowDimension(), 2); |
| Assert.assertEquals("testData2 column dimension", m2.getColumnDimension(), 3); |
| Assert.assertTrue("testData2 is not square", !m2.isSquare()); |
| } |
| |
| /** test copy functions */ |
| @Test |
| public void testCopyFunctions() { |
| SparseFieldMatrix<Dfp> m1 = createSparseMatrix(testData); |
| FieldMatrix<Dfp> m2 = m1.copy(); |
| Assert.assertEquals(m1.getClass(), m2.getClass()); |
| Assert.assertEquals((m2), m1); |
| SparseFieldMatrix<Dfp> m3 = createSparseMatrix(testData); |
| FieldMatrix<Dfp> m4 = m3.copy(); |
| Assert.assertEquals(m3.getClass(), m4.getClass()); |
| Assert.assertEquals((m4), m3); |
| } |
| |
| /** test add */ |
| @Test |
| public void testAdd() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| SparseFieldMatrix<Dfp> mInv = createSparseMatrix(testDataInv); |
| SparseFieldMatrix<Dfp> mDataPlusInv = createSparseMatrix(testDataPlusInv); |
| FieldMatrix<Dfp> mPlusMInv = m.add(mInv); |
| for (int row = 0; row < m.getRowDimension(); row++) { |
| for (int col = 0; col < m.getColumnDimension(); col++) { |
| Assert.assertEquals("sum entry entry", |
| mDataPlusInv.getEntry(row, col).toDouble(), mPlusMInv.getEntry(row, col).toDouble(), |
| entryTolerance); |
| } |
| } |
| } |
| |
| /** test add failure */ |
| @Test |
| public void testAddFail() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| SparseFieldMatrix<Dfp> m2 = createSparseMatrix(testData2); |
| try { |
| m.add(m2); |
| Assert.fail("MathIllegalArgumentException expected"); |
| } catch (MathIllegalArgumentException ex) { |
| // ignored |
| } |
| } |
| |
| |
| /** test m-n = m + -n */ |
| @Test |
| public void testPlusMinus() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| SparseFieldMatrix<Dfp> n = createSparseMatrix(testDataInv); |
| assertClose("m-n = m + -n", m.subtract(n), |
| n.scalarMultiply(Dfp25.of(-1)).add(m), entryTolerance); |
| try { |
| m.subtract(createSparseMatrix(testData2)); |
| Assert.fail("Expecting illegalArgumentException"); |
| } catch (MathIllegalArgumentException ex) { |
| // ignored |
| } |
| } |
| |
| /** test multiply */ |
| @Test |
| public void testMultiply() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| SparseFieldMatrix<Dfp> mInv = createSparseMatrix(testDataInv); |
| SparseFieldMatrix<Dfp> identity = createSparseMatrix(id); |
| SparseFieldMatrix<Dfp> m2 = createSparseMatrix(testData2); |
| assertClose("inverse multiply", m.multiply(mInv), identity, |
| entryTolerance); |
| assertClose("inverse multiply", m.multiply(new Array2DRowFieldMatrix<>(Dfp25.getField(), testDataInv)), identity, |
| entryTolerance); |
| assertClose("inverse multiply", mInv.multiply(m), identity, |
| entryTolerance); |
| assertClose("identity multiply", m.multiply(identity), m, |
| entryTolerance); |
| assertClose("identity multiply", identity.multiply(mInv), mInv, |
| entryTolerance); |
| assertClose("identity multiply", m2.multiply(identity), m2, |
| entryTolerance); |
| try { |
| m.multiply(createSparseMatrix(bigSingular)); |
| Assert.fail("Expecting illegalArgumentException"); |
| } catch (MathIllegalArgumentException ex) { |
| // ignored |
| } |
| } |
| |
| // Additional Test for Array2DRowRealMatrixTest.testMultiply |
| |
| private Dfp[][] d3 = new Dfp[][] { { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(5), Dfp25.of(6), Dfp25.of(7), Dfp25.of(8) } }; |
| private Dfp[][] d4 = new Dfp[][] { { Dfp25.of(1) }, { Dfp25.of(2) }, { Dfp25.of(3) }, { Dfp25.of(4) } }; |
| private Dfp[][] d5 = new Dfp[][] { { Dfp25.of(30) }, { Dfp25.of(70) } }; |
| |
| @Test |
| public void testMultiply2() { |
| FieldMatrix<Dfp> m3 = createSparseMatrix(d3); |
| FieldMatrix<Dfp> m4 = createSparseMatrix(d4); |
| FieldMatrix<Dfp> m5 = createSparseMatrix(d5); |
| assertClose("m3*m4=m5", m3.multiply(m4), m5, entryTolerance); |
| } |
| |
| /** test trace */ |
| @Test |
| public void testTrace() { |
| FieldMatrix<Dfp> m = createSparseMatrix(id); |
| Assert.assertEquals("identity trace", 3d, m.getTrace().toDouble(), entryTolerance); |
| m = createSparseMatrix(testData2); |
| try { |
| m.getTrace(); |
| Assert.fail("Expecting NonSquareMatrixException"); |
| } catch (NonSquareMatrixException ex) { |
| // ignored |
| } |
| } |
| |
| /** test scalarAdd */ |
| @Test |
| public void testScalarAdd() { |
| FieldMatrix<Dfp> m = createSparseMatrix(testData); |
| assertClose("scalar add", createSparseMatrix(testDataPlus2), |
| m.scalarAdd(Dfp25.of(2)), entryTolerance); |
| } |
| |
| /** test operate */ |
| @Test |
| public void testOperate() { |
| FieldMatrix<Dfp> m = createSparseMatrix(id); |
| assertClose("identity operate", testVector, m.operate(testVector), |
| entryTolerance); |
| assertClose("identity operate", testVector, m.operate( |
| new ArrayFieldVector<>(testVector)).toArray(), entryTolerance); |
| m = createSparseMatrix(bigSingular); |
| try { |
| m.operate(testVector); |
| Assert.fail("Expecting illegalArgumentException"); |
| } catch (MathIllegalArgumentException ex) { |
| // ignored |
| } |
| } |
| |
| /** test issue MATH-209 */ |
| @Test |
| public void testMath209() { |
| FieldMatrix<Dfp> a = createSparseMatrix(new Dfp[][] { |
| { Dfp25.of(1), Dfp25.of(2) }, { Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(5), Dfp25.of(6) } }); |
| Dfp[] b = a.operate(new Dfp[] { Dfp25.of(1), Dfp25.of(1) }); |
| Assert.assertEquals(a.getRowDimension(), b.length); |
| Assert.assertEquals(3.0, b[0].toDouble(), 1.0e-12); |
| Assert.assertEquals(7.0, b[1].toDouble(), 1.0e-12); |
| Assert.assertEquals(11.0, b[2].toDouble(), 1.0e-12); |
| } |
| |
| /** test transpose */ |
| @Test |
| public void testTranspose() { |
| FieldMatrix<Dfp> m = createSparseMatrix(testData); |
| FieldMatrix<Dfp> mIT = new FieldLUDecomposition<>(m).getSolver().getInverse().transpose(); |
| FieldMatrix<Dfp> mTI = new FieldLUDecomposition<>(m.transpose()).getSolver().getInverse(); |
| assertClose("inverse-transpose", mIT, mTI, normTolerance); |
| m = createSparseMatrix(testData2); |
| FieldMatrix<Dfp> mt = createSparseMatrix(testData2T); |
| assertClose("transpose",mt,m.transpose(),normTolerance); |
| } |
| |
| /** test preMultiply by vector */ |
| @Test |
| public void testPremultiplyVector() { |
| FieldMatrix<Dfp> m = createSparseMatrix(testData); |
| assertClose("premultiply", m.preMultiply(testVector), preMultTest, |
| normTolerance); |
| assertClose("premultiply", m.preMultiply( |
| new ArrayFieldVector<>(testVector).toArray()), preMultTest, normTolerance); |
| m = createSparseMatrix(bigSingular); |
| try { |
| m.preMultiply(testVector); |
| Assert.fail("expecting MathIllegalArgumentException"); |
| } catch (MathIllegalArgumentException ex) { |
| // ignored |
| } |
| } |
| |
| @Test |
| public void testPremultiply() { |
| FieldMatrix<Dfp> m3 = createSparseMatrix(d3); |
| FieldMatrix<Dfp> m4 = createSparseMatrix(d4); |
| FieldMatrix<Dfp> m5 = createSparseMatrix(d5); |
| assertClose("m3*m4=m5", m4.preMultiply(m3), m5, entryTolerance); |
| |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| SparseFieldMatrix<Dfp> mInv = createSparseMatrix(testDataInv); |
| SparseFieldMatrix<Dfp> identity = createSparseMatrix(id); |
| assertClose("inverse multiply", m.preMultiply(mInv), identity, |
| entryTolerance); |
| assertClose("inverse multiply", mInv.preMultiply(m), identity, |
| entryTolerance); |
| assertClose("identity multiply", m.preMultiply(identity), m, |
| entryTolerance); |
| assertClose("identity multiply", identity.preMultiply(mInv), mInv, |
| entryTolerance); |
| try { |
| m.preMultiply(createSparseMatrix(bigSingular)); |
| Assert.fail("Expecting illegalArgumentException"); |
| } catch (MathIllegalArgumentException ex) { |
| // ignored |
| } |
| } |
| |
| @Test |
| public void testGetVectors() { |
| FieldMatrix<Dfp> m = createSparseMatrix(testData); |
| assertClose("get row", m.getRow(0), testDataRow1, entryTolerance); |
| assertClose("get col", m.getColumn(2), testDataCol3, entryTolerance); |
| try { |
| m.getRow(10); |
| Assert.fail("expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // ignored |
| } |
| try { |
| m.getColumn(-1); |
| Assert.fail("expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // ignored |
| } |
| } |
| |
| @Test |
| public void testGetEntry() { |
| FieldMatrix<Dfp> m = createSparseMatrix(testData); |
| Assert.assertEquals("get entry", m.getEntry(0, 1).toDouble(), 2d, entryTolerance); |
| try { |
| m.getEntry(10, 4); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| } |
| |
| /** test examples in user guide */ |
| @Test |
| public void testExamples() { |
| // Create a real matrix with two rows and three columns |
| Dfp[][] matrixData = { { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3) }, { Dfp25.of(2), Dfp25.of(5), Dfp25.of(3) } }; |
| FieldMatrix<Dfp> m = createSparseMatrix(matrixData); |
| // One more with three rows, two columns |
| Dfp[][] matrixData2 = { { Dfp25.of(1), Dfp25.of(2) }, { Dfp25.of(2), Dfp25.of(5) }, { Dfp25.of(1), Dfp25.of(7) } }; |
| FieldMatrix<Dfp> n = createSparseMatrix(matrixData2); |
| // Now multiply m by n |
| FieldMatrix<Dfp> p = m.multiply(n); |
| Assert.assertEquals(2, p.getRowDimension()); |
| Assert.assertEquals(2, p.getColumnDimension()); |
| // Invert p |
| FieldMatrix<Dfp> pInverse = new FieldLUDecomposition<>(p).getSolver().getInverse(); |
| Assert.assertEquals(2, pInverse.getRowDimension()); |
| Assert.assertEquals(2, pInverse.getColumnDimension()); |
| |
| // Solve example |
| Dfp[][] coefficientsData = { { Dfp25.of(2), Dfp25.of(3), Dfp25.of(-2) }, { Dfp25.of(-1), Dfp25.of(7), Dfp25.of(6) }, |
| { Dfp25.of(4), Dfp25.of(-3), Dfp25.of(-5) } }; |
| FieldMatrix<Dfp> coefficients = createSparseMatrix(coefficientsData); |
| Dfp[] constants = { Dfp25.of(1), Dfp25.of(-2), Dfp25.of(1) }; |
| Dfp[] solution; |
| solution = new FieldLUDecomposition<>(coefficients) |
| .getSolver() |
| .solve(new ArrayFieldVector<>(constants, false)).toArray(); |
| Assert.assertEquals((Dfp25.of(2).multiply((solution[0])).add(Dfp25.of(3).multiply(solution[1])).subtract(Dfp25.of(2).multiply(solution[2]))).toDouble(), |
| constants[0].toDouble(), 1E-12); |
| Assert.assertEquals(((Dfp25.of(-1).multiply(solution[0])).add(Dfp25.of(7).multiply(solution[1])).add(Dfp25.of(6).multiply(solution[2]))).toDouble(), |
| constants[1].toDouble(), 1E-12); |
| Assert.assertEquals(((Dfp25.of(4).multiply(solution[0])).subtract(Dfp25.of(3).multiply( solution[1])).subtract(Dfp25.of(5).multiply(solution[2]))).toDouble(), |
| constants[2].toDouble(), 1E-12); |
| |
| } |
| |
| // test submatrix accessors |
| @Test |
| public void testSubMatrix() { |
| FieldMatrix<Dfp> m = createSparseMatrix(subTestData); |
| FieldMatrix<Dfp> mRows23Cols00 = createSparseMatrix(subRows23Cols00); |
| FieldMatrix<Dfp> mRows00Cols33 = createSparseMatrix(subRows00Cols33); |
| FieldMatrix<Dfp> mRows01Cols23 = createSparseMatrix(subRows01Cols23); |
| FieldMatrix<Dfp> mRows02Cols13 = createSparseMatrix(subRows02Cols13); |
| FieldMatrix<Dfp> mRows03Cols12 = createSparseMatrix(subRows03Cols12); |
| FieldMatrix<Dfp> mRows03Cols123 = createSparseMatrix(subRows03Cols123); |
| FieldMatrix<Dfp> mRows20Cols123 = createSparseMatrix(subRows20Cols123); |
| FieldMatrix<Dfp> mRows31Cols31 = createSparseMatrix(subRows31Cols31); |
| Assert.assertEquals("Rows23Cols00", mRows23Cols00, m.getSubMatrix(2, 3, 0, 0)); |
| Assert.assertEquals("Rows00Cols33", mRows00Cols33, m.getSubMatrix(0, 0, 3, 3)); |
| Assert.assertEquals("Rows01Cols23", mRows01Cols23, m.getSubMatrix(0, 1, 2, 3)); |
| Assert.assertEquals("Rows02Cols13", mRows02Cols13, |
| m.getSubMatrix(new int[] { 0, 2 }, new int[] { 1, 3 })); |
| Assert.assertEquals("Rows03Cols12", mRows03Cols12, |
| m.getSubMatrix(new int[] { 0, 3 }, new int[] { 1, 2 })); |
| Assert.assertEquals("Rows03Cols123", mRows03Cols123, |
| m.getSubMatrix(new int[] { 0, 3 }, new int[] { 1, 2, 3 })); |
| Assert.assertEquals("Rows20Cols123", mRows20Cols123, |
| m.getSubMatrix(new int[] { 2, 0 }, new int[] { 1, 2, 3 })); |
| Assert.assertEquals("Rows31Cols31", mRows31Cols31, |
| m.getSubMatrix(new int[] { 3, 1 }, new int[] { 3, 1 })); |
| Assert.assertEquals("Rows31Cols31", mRows31Cols31, |
| m.getSubMatrix(new int[] { 3, 1 }, new int[] { 3, 1 })); |
| |
| try { |
| m.getSubMatrix(1, 0, 2, 4); |
| Assert.fail("Expecting NumberIsTooSmallException"); |
| } catch (NumberIsTooSmallException ex) { |
| // expected |
| } |
| try { |
| m.getSubMatrix(-1, 1, 2, 2); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| try { |
| m.getSubMatrix(1, 0, 2, 2); |
| Assert.fail("Expecting NumberIsTooSmallException"); |
| } catch (NumberIsTooSmallException ex) { |
| // expected |
| } |
| try { |
| m.getSubMatrix(1, 0, 2, 4); |
| Assert.fail("Expecting NumberIsTooSmallException"); |
| } catch (NumberIsTooSmallException ex) { |
| // expected |
| } |
| try { |
| m.getSubMatrix(new int[] {}, new int[] { 0 }); |
| Assert.fail("Expecting NoDataException"); |
| } catch (NoDataException ex) { |
| // expected |
| } |
| try { |
| m.getSubMatrix(new int[] { 0 }, new int[] { 4 }); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| } |
| |
| @Test |
| public void testGetRowMatrix() { |
| FieldMatrix<Dfp> m = createSparseMatrix(subTestData); |
| FieldMatrix<Dfp> mRow0 = createSparseMatrix(subRow0); |
| FieldMatrix<Dfp> mRow3 = createSparseMatrix(subRow3); |
| Assert.assertEquals("Row0", mRow0, m.getRowMatrix(0)); |
| Assert.assertEquals("Row3", mRow3, m.getRowMatrix(3)); |
| try { |
| m.getRowMatrix(-1); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| try { |
| m.getRowMatrix(4); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| } |
| |
| @Test |
| public void testGetColumnMatrix() { |
| FieldMatrix<Dfp> m = createSparseMatrix(subTestData); |
| FieldMatrix<Dfp> mColumn1 = createSparseMatrix(subColumn1); |
| FieldMatrix<Dfp> mColumn3 = createSparseMatrix(subColumn3); |
| Assert.assertEquals("Column1", mColumn1, m.getColumnMatrix(1)); |
| Assert.assertEquals("Column3", mColumn3, m.getColumnMatrix(3)); |
| try { |
| m.getColumnMatrix(-1); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| try { |
| m.getColumnMatrix(4); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| } |
| |
| @Test |
| public void testGetRowVector() { |
| FieldMatrix<Dfp> m = createSparseMatrix(subTestData); |
| FieldVector<Dfp> mRow0 = new ArrayFieldVector<>(subRow0[0]); |
| FieldVector<Dfp> mRow3 = new ArrayFieldVector<>(subRow3[0]); |
| Assert.assertEquals("Row0", mRow0, m.getRowVector(0)); |
| Assert.assertEquals("Row3", mRow3, m.getRowVector(3)); |
| try { |
| m.getRowVector(-1); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| try { |
| m.getRowVector(4); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| } |
| |
| @Test |
| public void testGetColumnVector() { |
| FieldMatrix<Dfp> m = createSparseMatrix(subTestData); |
| FieldVector<Dfp> mColumn1 = columnToVector(subColumn1); |
| FieldVector<Dfp> mColumn3 = columnToVector(subColumn3); |
| Assert.assertEquals("Column1", mColumn1, m.getColumnVector(1)); |
| Assert.assertEquals("Column3", mColumn3, m.getColumnVector(3)); |
| try { |
| m.getColumnVector(-1); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| try { |
| m.getColumnVector(4); |
| Assert.fail("Expecting OutOfRangeException"); |
| } catch (OutOfRangeException ex) { |
| // expected |
| } |
| } |
| |
| private FieldVector<Dfp> columnToVector(Dfp[][] column) { |
| Dfp[] data = new Dfp[column.length]; |
| for (int i = 0; i < data.length; ++i) { |
| data[i] = column[i][0]; |
| } |
| return new ArrayFieldVector<>(data, false); |
| } |
| |
| @Test |
| public void testEqualsAndHashCode() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| SparseFieldMatrix<Dfp> m1 = (SparseFieldMatrix<Dfp>) m.copy(); |
| SparseFieldMatrix<Dfp> mt = (SparseFieldMatrix<Dfp>) m.transpose(); |
| Assert.assertTrue(m.hashCode() != mt.hashCode()); |
| Assert.assertEquals(m.hashCode(), m1.hashCode()); |
| Assert.assertEquals(m, m); |
| Assert.assertEquals(m, m1); |
| Assert.assertFalse(m.equals(null)); |
| Assert.assertFalse(m.equals(mt)); |
| Assert.assertFalse(m.equals(createSparseMatrix(bigSingular))); |
| } |
| |
| /* Disable for now |
| @Test |
| public void testToString() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| Assert.assertEquals("SparseFieldMatrix<Dfp>{{1.0,2.0,3.0},{2.0,5.0,3.0},{1.0,0.0,8.0}}", |
| m.toString()); |
| m = new SparseFieldMatrix<Dfp>(field, 1, 1); |
| Assert.assertEquals("SparseFieldMatrix<Dfp>{{0.0}}", m.toString()); |
| } |
| */ |
| |
| @Test |
| public void testSetSubMatrix() { |
| SparseFieldMatrix<Dfp> m = createSparseMatrix(testData); |
| m.setSubMatrix(detData2, 1, 1); |
| FieldMatrix<Dfp> expected = createSparseMatrix(new Dfp[][] { |
| { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3) }, { Dfp25.of(2), Dfp25.of(1), Dfp25.of(3) }, { Dfp25.of(1), Dfp25.of(2), Dfp25.of(4) } }); |
| Assert.assertEquals(expected, m); |
| |
| m.setSubMatrix(detData2, 0, 0); |
| expected = createSparseMatrix(new Dfp[][] { |
| { Dfp25.of(1), Dfp25.of(3), Dfp25.of(3) }, { Dfp25.of(2), Dfp25.of(4), Dfp25.of(3) }, { Dfp25.of(1), Dfp25.of(2), Dfp25.of(4) } }); |
| Assert.assertEquals(expected, m); |
| |
| m.setSubMatrix(testDataPlus2, 0, 0); |
| expected = createSparseMatrix(new Dfp[][] { |
| { Dfp25.of(3), Dfp25.of(4), Dfp25.of(5) }, { Dfp25.of(4), Dfp25.of(7), Dfp25.of(5) }, { Dfp25.of(3), Dfp25.of(2), Dfp25.of(10) } }); |
| Assert.assertEquals(expected, m); |
| |
| // javadoc example |
| SparseFieldMatrix<Dfp> matrix = |
| createSparseMatrix(new Dfp[][] { |
| { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(5), Dfp25.of(6), Dfp25.of(7), Dfp25.of(8) }, { Dfp25.of(9), Dfp25.of(0), Dfp25.of(1), Dfp25.of(2) } }); |
| matrix.setSubMatrix(new Dfp[][] { { Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(5), Dfp25.of(6) } }, 1, 1); |
| expected = createSparseMatrix(new Dfp[][] { |
| { Dfp25.of(1), Dfp25.of(2), Dfp25.of(3), Dfp25.of(4) }, { Dfp25.of(5), Dfp25.of(3), Dfp25.of(4), Dfp25.of(8) }, { Dfp25.of(9), Dfp25.of(5), Dfp25.of(6), Dfp25.of(2) } }); |
| Assert.assertEquals(expected, matrix); |
| |
| // dimension overflow |
| try { |
| m.setSubMatrix(testData, 1, 1); |
| Assert.fail("expecting OutOfRangeException"); |
| } catch (OutOfRangeException e) { |
| // expected |
| } |
| // dimension underflow |
| try { |
| m.setSubMatrix(testData, -1, 1); |
| Assert.fail("expecting OutOfRangeException"); |
| } catch (OutOfRangeException e) { |
| // expected |
| } |
| try { |
| m.setSubMatrix(testData, 1, -1); |
| Assert.fail("expecting OutOfRangeException"); |
| } catch (OutOfRangeException e) { |
| // expected |
| } |
| |
| // null |
| try { |
| m.setSubMatrix(null, 1, 1); |
| Assert.fail("expecting NullArgumentException"); |
| } catch (NullArgumentException e) { |
| // expected |
| } |
| try { |
| new SparseFieldMatrix<>(field, 0, 0); |
| Assert.fail("expecting MathIllegalArgumentException"); |
| } catch (MathIllegalArgumentException e) { |
| // expected |
| } |
| |
| // ragged |
| try { |
| m.setSubMatrix(new Dfp[][] { { Dfp25.of(1) }, { Dfp25.of(2), Dfp25.of(3) } }, 0, 0); |
| Assert.fail("expecting MathIllegalArgumentException"); |
| } catch (MathIllegalArgumentException e) { |
| // expected |
| } |
| |
| // empty |
| try { |
| m.setSubMatrix(new Dfp[][] { {} }, 0, 0); |
| Assert.fail("expecting MathIllegalArgumentException"); |
| } catch (MathIllegalArgumentException e) { |
| // expected |
| } |
| } |
| |
| // --------------- -----------------Protected methods |
| |
| /** verifies that two matrices are close (1-norm) */ |
| protected void assertClose(String msg, FieldMatrix<Dfp> m, FieldMatrix<Dfp> n, |
| double tolerance) { |
| for(int i=0; i < m.getRowDimension(); i++){ |
| for(int j=0; j < m.getColumnDimension(); j++){ |
| Assert.assertEquals(msg, m.getEntry(i,j).toDouble(), n.getEntry(i,j).toDouble(), tolerance); |
| } |
| |
| } |
| } |
| |
| /** verifies that two vectors are close (sup norm) */ |
| protected void assertClose(String msg, Dfp[] m, Dfp[] n, |
| double tolerance) { |
| if (m.length != n.length) { |
| Assert.fail("vectors not same length"); |
| } |
| for (int i = 0; i < m.length; i++) { |
| Assert.assertEquals(msg + " " + i + " elements differ", m[i].toDouble(), n[i].toDouble(), |
| tolerance); |
| } |
| } |
| |
| private SparseFieldMatrix<Dfp> createSparseMatrix(Dfp[][] data) { |
| SparseFieldMatrix<Dfp> matrix = new SparseFieldMatrix<>(field, data.length, data[0].length); |
| for (int row = 0; row < data.length; row++) { |
| for (int col = 0; col < data[row].length; col++) { |
| matrix.setEntry(row, col, data[row][col]); |
| } |
| } |
| return matrix; |
| } |
| } |