Java Code Examples for org.apache.commons.math.linear.RealMatrix#getColumn()
The following examples show how to use
org.apache.commons.math.linear.RealMatrix#getColumn() .
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Example 1
| Source File: SingularValueSolverTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
/** test solve */
public void testSolve() {
DecompositionSolver solver =
new SingularValueDecompositionImpl(MatrixUtils.createRealMatrix(testSquare)).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ 1, 2, 3 }, { 0, -5, 1 }
});
RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
{ -8.0 / 25.0, -263.0 / 75.0, -29.0 / 75.0 },
{ 19.0 / 25.0, 78.0 / 25.0, 49.0 / 25.0 }
});
// using RealMatrix
assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), normTolerance);
// using double[]
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
new ArrayRealVector(solver.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using Array2DRowRealMatrix
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
solver.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using RealMatrix with an alternate implementation
for (int i = 0; i < b.getColumnDimension(); ++i) {
ArrayRealVectorTest.RealVectorTestImpl v =
new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
assertEquals(0,
solver.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
}
Example 2
| Source File: PearsonsCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 3
| Source File: SpearmansRankCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Override
@Test
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
Assert.assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 4
| Source File: SpearmansRankCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Override
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 5
| Source File: SpearmansRankCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Override
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 6
| Source File: PearsonsCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 7
| Source File: SpearmansRankCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Override
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 8
| Source File: PearsonsCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
Assert.assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 9
| Source File: PearsonsCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 10
| Source File: LUSolverTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
/** test solve */
public void testSolve() {
DecompositionSolver solver =
new LUDecompositionImpl(MatrixUtils.createRealMatrix(testData)).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ 1, 0 }, { 2, -5 }, { 3, 1 }
});
RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
{ 19, -71 }, { -6, 22 }, { -2, 9 }
});
// using RealMatrix
assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), 1.0e-13);
// using double[]
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
new ArrayRealVector(solver.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using ArrayRealVector
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
solver.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using RealVector with an alternate implementation
for (int i = 0; i < b.getColumnDimension(); ++i) {
ArrayRealVectorTest.RealVectorTestImpl v =
new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
assertEquals(0,
solver.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
}
Example 11
| Source File: SpearmansRankCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Override
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 12
| Source File: PearsonsCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 13
| Source File: SpearmansRankCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Override
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 14
| Source File: SpearmansRankCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Override
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 15
| Source File: PearsonsCorrelationTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
Example 16
| Source File: LUSolverTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
/** test solve */
public void testSolve() {
DecompositionSolver solver =
new LUDecompositionImpl(MatrixUtils.createRealMatrix(testData)).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ 1, 0 }, { 2, -5 }, { 3, 1 }
});
RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
{ 19, -71 }, { -6, 22 }, { -2, 9 }
});
// using RealMatrix
assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), 1.0e-13);
// using double[]
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
new ArrayRealVector(solver.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using ArrayRealVector
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
solver.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using RealVector with an alternate implementation
for (int i = 0; i < b.getColumnDimension(); ++i) {
ArrayRealVectorTest.RealVectorTestImpl v =
new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
assertEquals(0,
solver.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
}
Example 17
| Source File: CholeskySolverTest.java From astor with GNU General Public License v2.0 | 4 votes |
|
/** test solve */
public void testSolve() throws MathException {
DecompositionSolver solver =
new CholeskyDecompositionImpl(MatrixUtils.createRealMatrix(testData)).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ 78, -13, 1 },
{ 414, -62, -1 },
{ 1312, -202, -37 },
{ 2989, -542, 145 },
{ 5510, -1465, 201 }
});
RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
{ 1, 0, 1 },
{ 0, 1, 1 },
{ 2, 1, -4 },
{ 2, 2, 2 },
{ 5, -3, 0 }
});
// using RealMatrix
assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), 1.0e-13);
// using double[]
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
new ArrayRealVector(solver.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using ArrayRealVector
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
solver.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using RealVector with an alternate implementation
for (int i = 0; i < b.getColumnDimension(); ++i) {
ArrayRealVectorTest.RealVectorTestImpl v =
new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
assertEquals(0,
solver.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
}
Example 18
| Source File: EigenSolverTest.java From astor with GNU General Public License v2.0 | 4 votes |
|
/** test solve */
public void testSolve() {
RealMatrix m = MatrixUtils.createRealMatrix(new double[][] {
{ 91, 5, 29, 32, 40, 14 },
{ 5, 34, -1, 0, 2, -1 },
{ 29, -1, 12, 9, 21, 8 },
{ 32, 0, 9, 14, 9, 0 },
{ 40, 2, 21, 9, 51, 19 },
{ 14, -1, 8, 0, 19, 14 }
});
DecompositionSolver es = new EigenDecompositionImpl(m, MathUtils.SAFE_MIN).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ 1561, 269, 188 },
{ 69, -21, 70 },
{ 739, 108, 63 },
{ 324, 86, 59 },
{ 1624, 194, 107 },
{ 796, 69, 36 }
});
RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
{ 1, 2, 1 },
{ 2, -1, 2 },
{ 4, 2, 3 },
{ 8, -1, 0 },
{ 16, 2, 0 },
{ 32, -1, 0 }
});
// using RealMatrix
assertEquals(0, es.solve(b).subtract(xRef).getNorm(), 2.0e-12);
// using double[]
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
new ArrayRealVector(es.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
2.0e-11);
}
// using Array2DRowRealMatrix
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
es.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
2.0e-11);
}
// using RealMatrix with an alternate implementation
for (int i = 0; i < b.getColumnDimension(); ++i) {
ArrayRealVectorTest.RealVectorTestImpl v =
new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
assertEquals(0,
es.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
2.0e-11);
}
}
Example 19
| Source File: EigenSolverTest.java From astor with GNU General Public License v2.0 | 4 votes |
|
/** test solve */
public void testSolve() {
RealMatrix m = MatrixUtils.createRealMatrix(new double[][] {
{ 91, 5, 29, 32, 40, 14 },
{ 5, 34, -1, 0, 2, -1 },
{ 29, -1, 12, 9, 21, 8 },
{ 32, 0, 9, 14, 9, 0 },
{ 40, 2, 21, 9, 51, 19 },
{ 14, -1, 8, 0, 19, 14 }
});
DecompositionSolver es = new EigenDecompositionImpl(m, MathUtils.SAFE_MIN).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ 1561, 269, 188 },
{ 69, -21, 70 },
{ 739, 108, 63 },
{ 324, 86, 59 },
{ 1624, 194, 107 },
{ 796, 69, 36 }
});
RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
{ 1, 2, 1 },
{ 2, -1, 2 },
{ 4, 2, 3 },
{ 8, -1, 0 },
{ 16, 2, 0 },
{ 32, -1, 0 }
});
// using RealMatrix
assertEquals(0, es.solve(b).subtract(xRef).getNorm(), 2.0e-12);
// using double[]
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
new ArrayRealVector(es.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
2.0e-11);
}
// using Array2DRowRealMatrix
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
es.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
2.0e-11);
}
// using RealMatrix with an alternate implementation
for (int i = 0; i < b.getColumnDimension(); ++i) {
ArrayRealVectorTest.RealVectorTestImpl v =
new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
assertEquals(0,
es.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
2.0e-11);
}
}
Example 20
| Source File: CholeskySolverTest.java From astor with GNU General Public License v2.0 | 4 votes |
|
/** test solve */
public void testSolve() throws MathException {
DecompositionSolver solver =
new CholeskyDecompositionImpl(MatrixUtils.createRealMatrix(testData)).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ 78, -13, 1 },
{ 414, -62, -1 },
{ 1312, -202, -37 },
{ 2989, -542, 145 },
{ 5510, -1465, 201 }
});
RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
{ 1, 0, 1 },
{ 0, 1, 1 },
{ 2, 1, -4 },
{ 2, 2, 2 },
{ 5, -3, 0 }
});
// using RealMatrix
assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), 1.0e-13);
// using double[]
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
new ArrayRealVector(solver.solve(b.getColumn(i))).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using ArrayRealVector
for (int i = 0; i < b.getColumnDimension(); ++i) {
assertEquals(0,
solver.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
// using RealVector with an alternate implementation
for (int i = 0; i < b.getColumnDimension(); ++i) {
ArrayRealVectorTest.RealVectorTestImpl v =
new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
assertEquals(0,
solver.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
1.0e-13);
}
}
