Examples of mikera.matrixx.AMatrix

mikera.matrixx.AMatrix
Abstract 2D matrix class. All Vectorz 2D matrices inherit from this class. Implements generic version of most key matrix operations. @author Mike

  
  public static void main(String[] args) {
    SparseRowMatrix sm=createMatrix();
    System.out.println(sm.nonZeroCount() +" elements are non-zero out of " + sm.elementCount()+" total elements");
    
    AMatrix smm=sm.innerProduct(sm);
    System.out.println(smm.nonZeroCount() +" elements are non-zero in the product.");
  }

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    System.out.println(m);
    System.out.println(m.getTranspose());


    System.out.println();
    
    AMatrix m2=Matrixx.createRandomSquareMatrix(2);
    System.out.println(m2);
    System.out.println(m2.getTranspose());
    m2.transposeInPlace();
    System.out.println(m2);
    
    
  }

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  @Test public void testOuterProducts() {
    AVector v=Vectorz.createUniformRandomVector(5);
    INDArray a=v.outerProduct(v);
    assertTrue(a instanceof AMatrix);
    
    AMatrix m=(AMatrix)a;
    AVector v2=v.clone();
    v2.square();
    assertEquals(v2,m.getLeadingDiagonal());
  }

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    AVector c=Vectorz.createUniformRandomVector(v.length());
    assertEquals(v.dotProduct(c),v.innerProduct((INDArray)c).get(),0.00001);
    
    if (len>20) return;
    
    AMatrix m=Matrixx.createRandomMatrix(len, len);
    assertTrue(v.innerProduct(m).epsilonEquals(m.getTranspose().transform(v)));
  }

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    AVector g4=new GrowableVector(v4);
    doGenericTests(g4);
  }
    
  @Test public void g_MatrixViews5x5() {  
    AMatrix m1=Matrixx.createRandomSquareMatrix(5);
    doGenericTests(m1.asVector());
    doGenericTests(m1.getRow(4));
    doGenericTests(m1.getColumn(1));
    doGenericTests(m1.getLeadingDiagonal());
  }

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    doGenericTests(m1.getColumn(1));
    doGenericTests(m1.getLeadingDiagonal());
  }
    
  @Test public void g_MatrixViews3x3() {  
    AMatrix m2=Matrixx.createRandomSquareMatrix(3);
    doGenericTests(m2.asVector());
    doGenericTests(m2.getRow(1));
    doGenericTests(m2.getColumn(1));
    doGenericTests(m2.getLeadingDiagonal());
    doGenericTests(new MatrixAsVector(m2));
  }

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    doGenericTests(m2.getLeadingDiagonal());
    doGenericTests(new MatrixAsVector(m2));
  }


  @Test public void g_MatrixViews4x5() {  
    AMatrix m3=Matrixx.createRandomMatrix(4,5);
    doGenericTests(m3.asVector());
    doGenericTests(m3.getRow(2));
    doGenericTests(m3.getColumn(2));
    doGenericTests(m3.subMatrix(1, 1, 2, 3).asVector());
    doGenericTests(new MatrixAsVector(m3));
  }

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        Matrix b = Matrix.create(new double[][] {{18}, {21.5}, {4.9000}});


        LUSolver solver = new LUSolver();
        
        assertNotNull(solver.setA(A));
        AMatrix x = solver.solve(b);




        Matrix x_expected = Matrix.create(new double[][] {{1}, {2}, {3}});


        assertTrue(x_expected.epsilonEquals(x,1e-8));

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        Matrix A = Matrix.create(new double[][] {{5, 2, 3}, {1.5, -2, 8}, {-3, 4.7, -0.5}});
        Matrix b = Matrix.create(new double[][] {{18}, {21.5}, {4.9000}});


        QRHouseColSolver solver = new QRHouseColSolver();
        assertTrue(solver.setA(A));
        AMatrix x = solver.solve(b);




        Matrix x_expected = Matrix.create(new double[][] {{1}, {2}, {3}});


        assertTrue(x_expected.epsilonEquals(x,1e-8));

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        Matrix A = createPolyA(t,3);


        QRHouseColSolver solver = new QRHouseColSolver();
        assertTrue(solver.setA(A));


        AMatrix x = solver.solve(B);


        assertEquals(a,x.get(0,0),tol);
        assertEquals(b,x.get(1,0),tol);
        assertEquals(c,x.get(2,0),tol);
    }

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Related Classes of mikera.matrixx.AMatrix

example.BasicMatrixUsage

example.SparseArrays

example.SparseMatrix

mikera.arrayz.INDArray

mikera.arrayz.TestMiscArrayOps

mikera.matrixx.algo.TestCholesky

mikera.matrixx.algo.TestLinear

mikera.matrixx.algo.TestQR

mikera.matrixx.decompose.impl.chol.SimpleCholesky

mikera.matrixx.decompose.impl.eigen.SymmetricQRAlgorithmDecomposition

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