Package org.apache.commons.math.optimization

Examples of org.apache.commons.math.optimization.RealPointValuePair

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        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-13, 1.0e-13));
        BrentSolver solver = new BrentSolver();
        solver.setAbsoluteAccuracy(1.0e-15);
        solver.setRelativeAccuracy(1.0e-15);
        optimizer.setLineSearchSolver(solver);
        RealPointValuePair optimum1 =
            optimizer.optimize(problem1, GoalType.MINIMIZE, new double[] { 0, 1, 2, 3 });
        assertEquals(1.0, optimum1.getPoint()[0], 1.0e-5);
        assertEquals(1.0, optimum1.getPoint()[1], 1.0e-5);
        assertEquals(1.0, optimum1.getPoint()[2], 1.0e-5);
        assertEquals(1.0, optimum1.getPoint()[3], 1.0e-5);

        LinearProblem problem2 = new LinearProblem(new double[][] {
                { 10.00, 7.00, 8.10, 7.20 },
                {  7.08, 5.04, 6.00, 5.00 },
                {  8.00, 5.98, 9.89, 9.00 },
                {  6.99, 4.99, 9.00, 9.98 }
        }, new double[] { 32, 23, 33, 31 });
        RealPointValuePair optimum2 =
            optimizer.optimize(problem2, GoalType.MINIMIZE, new double[] { 0, 1, 2, 3 });
        assertEquals(-81.0, optimum2.getPoint()[0], 1.0e-1);
        assertEquals(137.0, optimum2.getPoint()[1], 1.0e-1);
        assertEquals(-34.0, optimum2.getPoint()[2], 1.0e-1);
        assertEquals( 22.0, optimum2.getPoint()[3], 1.0e-1);

    }
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        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 7, 6, 5, 4 });
        assertEquals(0, optimum.getValue(), 1.0e-10);

    }
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        }, new double[] { 3.0, 12.0, -1.0, 7.0, 1.0 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 2, 2, 2, 2, 2, 2 });
        assertEquals(0, optimum.getValue(), 1.0e-10);
    }
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        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 1, 1 });
        assertEquals(2.0, optimum.getPoint()[0], 1.0e-8);
        assertEquals(1.0, optimum.getPoint()[1], 1.0e-8);

    }
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        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6, 1.0e-6));
        RealPointValuePair optimum =
            optimizer.optimize(problem, GoalType.MINIMIZE, new double[] { 1, 1 });
        assertTrue(optimum.getValue() > 0.1);

    }
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        optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-30, 1.0e-30));
        BrentSolver solver = new BrentSolver();
        solver.setAbsoluteAccuracy(1.0e-13);
        solver.setRelativeAccuracy(1.0e-15);
        optimizer.setLineSearchSolver(solver);
        RealPointValuePair optimum =
            optimizer.optimize(circle, GoalType.MINIMIZE, new double[] { 98.680, 47.345 });
        Point2D.Double center = new Point2D.Double(optimum.getPointRef()[0], optimum.getPointRef()[1]);
        assertEquals(69.960161753, circle.getRadius(center), 1.0e-8);
        assertEquals(96.075902096, center.x, 1.0e-8);
        assertEquals(48.135167894, center.y, 1.0e-8);
    }
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                    delta = fX2 - fVal;
                    bigInd = i;
                }
            }

            final RealPointValuePair previous = new RealPointValuePair(x1, fX);
            final RealPointValuePair current = new RealPointValuePair(x, fVal);
            if (getConvergenceChecker().converged(getIterations(), previous, current)) {
                if (goal == GoalType.MINIMIZE) {
                    return (fVal < fX) ? current : previous;
                } else {
                    return (fVal > fX) ? current : previous;
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                  LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, n, startConfiguration.length);
        }

        // set first vertex
        simplex = new RealPointValuePair[n + 1];
        simplex[0] = new RealPointValuePair(startPoint, Double.NaN);

        // set remaining vertices
        for (int i = 0; i < n; ++i) {
            final double[] confI   = startConfiguration[i];
            final double[] vertexI = new double[n];
            for (int k = 0; k < n; ++k) {
                vertexI[k] = startPoint[k] + confI[k];
            }
            simplex[i + 1] = new RealPointValuePair(vertexI, Double.NaN);
        }

    }
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    protected void evaluateSimplex(final Comparator<RealPointValuePair> comparator)
        throws FunctionEvaluationException, OptimizationException {

        // evaluate the objective function at all non-evaluated simplex points
        for (int i = 0; i < simplex.length; ++i) {
            final RealPointValuePair vertex = simplex[i];
            final double[] point = vertex.getPointRef();
            if (Double.isNaN(vertex.getValue())) {
                simplex[i] = new RealPointValuePair(point, evaluate(point), false);
            }
        }

        // sort the simplex from best to worst
        Arrays.sort(simplex, comparator);
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    protected void replaceWorstPoint(RealPointValuePair pointValuePair,
                                     final Comparator<RealPointValuePair> comparator) {
        int n = simplex.length - 1;
        for (int i = 0; i < n; ++i) {
            if (comparator.compare(simplex[i], pointValuePair) > 0) {
                RealPointValuePair tmp = simplex[i];
                simplex[i]         = pointValuePair;
                pointValuePair     = tmp;
            }
        }
        simplex[n] = pointValuePair;
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  • org.apache.commons.math.optimization.direct.NelderMead
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