Package org.apache.commons.math3.fraction

Examples of org.apache.commons.math3.fraction.AbstractFormat

91
92
93
94
95
96
97
98
99
100
101
102
        SiteWithPolynomial nearSite = nearestSites.get(row);
        DefaultPolynomial.populateMatrix(matrix, row, nearSite.pos.x, nearSite.pos.z);
        vector.setEntry(row, nearSite.pos.y);
      }
     
      QRDecomposition qr = new QRDecomposition(matrix);
      RealVector solution = qr.getSolver().solve(vector);
       
      double[] coeffs = solution.toArray();
     
      for (double coeff : coeffs) {
        if (coeff > 10e3) {
View Full Code Here
287
288
289
290
291
292
293
294
295
296
        }

        // solve the rectangular system in the least square sense
        // to get the best estimate of the Nordsieck vector [s2 ... sk]
        QRDecomposition decomposition;
        decomposition = new QRDecomposition(new Array2DRowRealMatrix(a, false));
        RealMatrix x = decomposition.getSolver().solve(new Array2DRowRealMatrix(b, false));
        return new Array2DRowRealMatrix(x.getData(), false);
    }
View Full Code Here
137
138
139
140
141
142
143
144
145
146
147
148
149
150
     * if the covariance matrix cannot be computed (singular problem).
     */
    public double[][] computeCovariances(double[] params,
                                         double threshold) {
        // Set up the Jacobian.
        final RealMatrix j = computeWeightedJacobian(params);

        // Compute transpose(J)J.
        final RealMatrix jTj = j.transpose().multiply(j);

        // Compute the covariances matrix.
        final DecompositionSolver solver
            = new QRDecomposition(jTj, threshold).getSolver();
        return solver.getInverse().getData();
View Full Code Here
264
265
266
267
268
269
270
271
272
273
274
275
276
     * @return the square-root of the weight matrix.
     */
    private RealMatrix squareRoot(RealMatrix m) {
        if (m instanceof DiagonalMatrix) {
            final int dim = m.getRowDimension();
            final RealMatrix sqrtM = new DiagonalMatrix(dim);
            for (int i = 0; i < dim; i++) {
                sqrtM.setEntry(i, i, FastMath.sqrt(m.getEntry(i, i)));
            }
            return sqrtM;
        } else {
            final EigenDecomposition dec = new EigenDecomposition(m);
            return dec.getSquareRoot();
View Full Code Here
82
83
84
85
86
87
88
89
90
91
92
     
      List<SiteWithPolynomial> nearestSites =
          nearestSiteMap.get(site);
     
      RealVector vector = new ArrayRealVector(SITES_FOR_APPROX);
      RealMatrix matrix = new Array2DRowRealMatrix(
          SITES_FOR_APPROX, DefaultPolynomial.NUM_COEFFS);
     
      for (int row = 0; row < SITES_FOR_APPROX; row++) {
        SiteWithPolynomial nearSite = nearestSites.get(row);
        DefaultPolynomial.populateMatrix(matrix, row, nearSite.pos.x, nearSite.pos.z);
View Full Code Here
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
     * @param matrix matrix with columns representing variables to correlate
     * @return correlation matrix
     */
    public RealMatrix computeCorrelationMatrix(final RealMatrix matrix) {
        int nVars = matrix.getColumnDimension();
        RealMatrix outMatrix = new BlockRealMatrix(nVars, nVars);
        for (int i = 0; i < nVars; i++) {
            for (int j = 0; j < i; j++) {
                double corr = correlation(matrix.getColumn(i), matrix.getColumn(j));
                outMatrix.setEntry(i, j, corr);
                outMatrix.setEntry(j, i, corr);
            }
            outMatrix.setEntry(i, i, 1d);
        }
        return outMatrix;
    }
View Full Code Here
289
290
291
292
293
294
295
296
        // solve the rectangular system in the least square sense
        // to get the best estimate of the Nordsieck vector [s2 ... sk]
        QRDecomposition decomposition;
        decomposition = new QRDecomposition(new Array2DRowRealMatrix(a, false));
        RealMatrix x = decomposition.getSolver().solve(new Array2DRowRealMatrix(b, false));
        return new Array2DRowRealMatrix(x.getData(), false);
    }
View Full Code Here
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
        double[] qtf     = new double[nR];
        double[] work1   = new double[nC];
        double[] work2   = new double[nC];
        double[] work3   = new double[nC];

        final RealMatrix weightMatrixSqrt = getWeightSquareRoot();

        // Evaluate the function at the starting point and calculate its norm.
        double[] currentObjective = computeObjectiveValue(currentPoint);
        double[] currentResiduals = computeResiduals(currentObjective);
        PointVectorValuePair current = new PointVectorValuePair(currentPoint, currentObjective);
        double currentCost = computeCost(currentResiduals);

        // Outer loop.
        lmPar = 0;
        boolean firstIteration = true;
        final ConvergenceChecker<PointVectorValuePair> checker = getConvergenceChecker();
        while (true) {
            incrementIterationCount();

            final PointVectorValuePair previous = current;

            // QR decomposition of the jacobian matrix
            qrDecomposition(computeWeightedJacobian(currentPoint));

            weightedResidual = weightMatrixSqrt.operate(currentResiduals);
            for (int i = 0; i < nR; i++) {
                qtf[i] = weightedResidual[i];
            }

            // compute Qt.res
View Full Code Here
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
        double[] qtf     = new double[nR];
        double[] work1   = new double[nC];
        double[] work2   = new double[nC];
        double[] work3   = new double[nC];

        final RealMatrix weightMatrixSqrt = getWeightSquareRoot();

        // Evaluate the function at the starting point and calculate its norm.
        double[] currentObjective = computeObjectiveValue(currentPoint);
        double[] currentResiduals = computeResiduals(currentObjective);
        PointVectorValuePair current = new PointVectorValuePair(currentPoint, currentObjective);
        double currentCost = computeCost(currentResiduals);

        // Outer loop.
        lmPar = 0;
        boolean firstIteration = true;
        int iter = 0;
        final ConvergenceChecker<PointVectorValuePair> checker = getConvergenceChecker();
        while (true) {
            ++iter;
            final PointVectorValuePair previous = current;

            // QR decomposition of the jacobian matrix
            qrDecomposition(computeWeightedJacobian(currentPoint));

            weightedResidual = weightMatrixSqrt.operate(currentResiduals);
            for (int i = 0; i < nR; i++) {
                qtf[i] = weightedResidual[i];
            }

            // compute Qt.res
View Full Code Here
141
142
143
144
145
146
147
148
149
150
151
152
153
154
     * if the covariance matrix cannot be computed (singular problem).
     */
    public double[][] computeCovariances(double[] params,
                                         double threshold) {
        // Set up the Jacobian.
        final RealMatrix j = computeWeightedJacobian(params);

        // Compute transpose(J)J.
        final RealMatrix jTj = j.transpose().multiply(j);

        // Compute the covariances matrix.
        final DecompositionSolver solver
            = new QRDecomposition(jTj, threshold).getSolver();
        return solver.getInverse().getData();
View Full Code Here
TOP

Related Classes of org.apache.commons.math3.fraction.AbstractFormat

  • org.apache.commons.math3.analysis.differentiation.DerivativeStructure
  • org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction
  • org.apache.commons.math3.analysis.function.HarmonicOscillator
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
  • org.apache.commons.math3.analysis.solvers.BrentSolver
  • org.apache.commons.math3.analysis.UnivariateFunction
  • org.apache.commons.math3.complex.Complex
    • Copyright © 2018 www.massapicom. All rights reserved.
    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.