Examples of Jama.Matrix

Jama.Matrix
Jama = Java Matrix class.
The Java Matrix Class provides the fundamental operations of numerical linear algebra. Various constructors create Matrices from two dimensional arrays of double precision floating point numbers. Various "gets" and "sets" provide access to submatrices and matrix elements. Several methods implement basic matrix arithmetic, including matrix addition and multiplication, matrix norms, and element-by-element array operations. Methods for reading and printing matrices are also included. All the operations in this version of the Matrix Class involve real matrices. Complex matrices may be handled in a future version.
Five fundamental matrix decompositions, which consist of pairs or triples of matrices, permutation vectors, and the like, produce results in five decomposition classes. These decompositions are accessed by the Matrix class to compute solutions of simultaneous linear equations, determinants, inverses and other matrix functions. The five decompositions are:
- Cholesky Decomposition of symmetric, positive definite matrices.
- LU Decomposition of rectangular matrices.
- QR Decomposition of rectangular matrices.
- Singular Value Decomposition of rectangular matrices.
- Eigenvalue Decomposition of both symmetric and nonsymmetric square matrices.
Example of use:
Solve a linear system A x = b and compute the residual norm, ||b - A x||.
```
 double[][] vals = {{1.,2.,3},{4.,5.,6.},{7.,8.,10.}}; Matrix A = new Matrix(vals); Matrix b = Matrix.random(3,1); Matrix x = A.solve(b); Matrix r = A.times(x).minus(b); double rnorm = r.normInf(); 
```
@author The MathWorks, Inc. and the National Institute of Standards and Technology. @version 5 August 1998

        super(source, new ImageLayout(source), config, true);
        permitInPlaceOperation();
        this.angle = angle;


        ICC_ProfileRGB sRGB = (ICC_ProfileRGB) JAIContext.sRGBColorProfile;
        toSRGB = new Matrix(sRGB.getMatrix()).inverse().times(new Matrix(((ICC_ProfileRGB) JAIContext.linearProfile).getMatrix())).getArrayFloat();
        toLinearRGB = new Matrix(sRGB.getMatrix()).inverse().times(new Matrix(((ICC_ProfileRGB) JAIContext.linearProfile).getMatrix())).inverse().getArrayFloat();
    }

View Full Code Here

        this.transform = transform;


        saturationIncrease = transform[0][0] > 1;


        ICC_ProfileRGB linRGB = (ICC_ProfileRGB) ICC_Profile.getInstance(ColorSpace.CS_LINEAR_RGB);
        toLinearsRGB = new Matrix(linRGB.getMatrix()).inverse().times(new Matrix(((ICC_ProfileRGB) JAIContext.linearProfile).getMatrix())).getArrayFloat();
    }

View Full Code Here

        final DCRaw dcRaw = ((RawImageInfo)auxInfo).getDCRaw();
        return new Dimension( dcRaw.getImageWidth(), dcRaw.getImageHeight() );
    }


    static Matrix pseudoinverse(Matrix m) {
        Matrix t = m.transpose();
        return t.times(m).inverse().times(t).transpose();
    }

View Full Code Here

            for (int j = 0; j < 3; j++)
                cam_rgb[i][j] /= num;
            pre_mul[i] = (float) (1 / num);
        }


        float inverse[][] = new Matrix(cam_rgb).inverse().transpose().getArrayFloat();
        for (int i = 0; i < 3; i++)
            for (int j = 0; j < 3; j++)
                rgb_cam[i][j] = inverse[j][i];
    }

View Full Code Here

    public FilteredGrayscaleOpImage(RenderedImage source, float filter[], float angle, float strenght, Map config) {
        super(source, new ImageLayout(source), config, true);
        permitInPlaceOperation();
        ICC_ProfileRGB sRGB = (ICC_ProfileRGB) JAIContext.sRGBColorProfile;
        ICC_ProfileRGB linRGB = (ICC_ProfileRGB) JAIContext.linearProfile;
        toLinearsRGB = new Matrix(sRGB.getMatrix()).inverse().times(new Matrix(linRGB.getMatrix())).getArrayFloat();


        this.filter = filter.clone();
        this.angle = angle;
    }

View Full Code Here

                this.transform[i][j] = (int) (sMath_scale * transform[i][j]);


        saturationIncrease = transform[0][0] > 1;


        ICC_ProfileRGB linRGB = (ICC_ProfileRGB) ICC_Profile.getInstance(ColorSpace.CS_LINEAR_RGB);
        Matrix XYZtoLinsRGB = new Matrix(linRGB.getMatrix()).inverse();
        Matrix CIERGBtoXYZ = new Matrix(((ICC_ProfileRGB) JAIContext.linearProfile).getMatrix());
        double CIERGBtoLinsRGB[][] = XYZtoLinsRGB.times(CIERGBtoXYZ).getArray();


        for (int i = 0; i < 3; i++)
            for (int j = 0; j < 3; j++)
                toLinearsRGB[i][j] = (int) (sMath_scale * CIERGBtoLinsRGB[i][j]);

View Full Code Here


                for (int i = 0; i < 3; i++)
                    for (int j = 0; j < 3; j++)
                        cameraRGBWB[j][i] *= wb[i];


                Matrix B = new Matrix(ColorScience.chromaticAdaptation(daylightTemperature, originalTemperature, caMethod));
                Matrix combo = XYZtoRGB.times(B.times(RGBtoZYX));


                cameraRGBWB = combo.inverse().times(new Matrix(cameraRGBWB)).getArrayFloat();
            }
            
            cameraRGBCA = dcRaw.getCameraRGB();
            dcRaw.getDaylightMultipliers();

View Full Code Here


    static float neutralTemperature(float rgb[], float refT) {
        float sat = Float.MAX_VALUE;
        float minT = 0;
        for (int t = 1000; t < 40000; t+= (0.01 * t)) {
            Matrix B = new Matrix(ColorScience.chromaticAdaptation(t, refT, caMethod));
            Matrix combo = XYZtoRGB.times(B.times(RGBtoZYX));


            Matrix color = new Matrix(new double[][]{{rgb[0]}, {rgb[1]}, {rgb[2]}});


            color = combo.times(color);


            double r = color.get(0, 0);
            double g = color.get(1, 0);
            double b = color.get(2, 0);


            float tSat = (float) ColorScience.saturation(r, g, b);


            if (tSat < sat) {
                sat = tSat;

View Full Code Here

                    }
                }
            }


            // Chromatic adaptation matrix
            Matrix B = new Matrix(ColorScience.chromaticAdaptation(daylightTemperature, temperature, caMethod));
            Matrix CA = XYZtoRGB.times(B.times(RGBtoZYX));


            // Normalize the CA matrix to keep exposure constant
            Matrix m = CA.times(new Matrix(new double[][]{{1},{1},{1}}));
            double max = m.get(1, 0);
            if (max != 1)
                CA = CA.times(new Matrix(new double[][]{{1/max, 0, 0},{0, 1/max, 0},{0, 0, 1/max}}));


            float actualExposure = exposure;
            String thisCamera = metadata.getCameraMake(true);
            for (String camera : fakeISO100Cameras)
                if (thisCamera.equals(camera)) {
                    if (metadata.getISO() == 100) {
                        actualExposure -= 1;
                    }
                    break;
                }


            // The matrix taking into account the camera color space and its basic white balance and exposure
            float camMatrix[][] = new Matrix(cameraRGB(temperature)).times(Math.pow(2, actualExposure)).getArrayFloat();


            front = new HighlightRecoveryOpImage(front, preMul, camMatrix, CA.getArrayFloat(), null);


            if (tint != 0)
                front = WhiteBalanceV2.tintCast(front, tint, lightness);

View Full Code Here

        double sat = ColorScience.saturation(r, g, b);
        int minT = (int) source;
        double wbr = 0, wbg = 0, wbb = 0;


        for (int t = 1000; t < 40000; t+= 0.001 * t) {
            Matrix B = new Matrix(ColorScience.chromaticAdaptation(REF_T, t, caMethod));
            Matrix combo = XYZtoRGB.times(B.times(RGBtoZYX));


            Matrix color = new Matrix(new double[][]{{pixel[0]}, {pixel[1]}, {pixel[2]}});


            color = combo.times(color);


            r = color.get(0, 0);
            g = color.get(1, 0);
            b = color.get(2, 0);


            double tSat = ColorScience.saturation(r, g, b);


            if (tSat < sat) {
                sat = tSat;

View Full Code Here

0 1 2 3 4 5 6 7 8 9

TOP

Related Classes of Jama.Matrix

br.edu.utfpr.cm.JGitMinerWeb.util.matrix.DoubleDenseMatrix

ca.nengo.dynamics.impl.CanonicalModel

ca.nengo.dynamics.impl.ImpulseIntegral

ca.nengo.math.impl.PolynomialCurveFitter

ca.nengo.math.impl.WeightedCostApproximator

ca.nengo.math.impl.WeightedCostApproximatorTest

ca.nengo.model.nef.impl.AdditiveGaussianExpressModel

ca.nengo.model.nef.impl.DecodableEnsembleImpl

caterpillarssa.SpectrumAnalysis

com.heatonresearch.aifh.regression.TrainLeastSquares

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.