Java RealPointValuePair类代码示例

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本文整理汇总了Java中org.apache.commons.math.optimization.RealPointValuePair类的典型用法代码示例。如果您正苦于以下问题：Java RealPointValuePair类的具体用法？Java RealPointValuePair怎么用？Java RealPointValuePair使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。

RealPointValuePair类属于org.apache.commons.math.optimization包，在下文中一共展示了RealPointValuePair类的20个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Java代码示例。

示例1: minimize

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
/**
 * Resolve linear programming problem when minimizing the equation with current constraints. Returns
 *
 * @param solution Solution to minimize the objective the function from.
 * @return Number of printings and cost value.
 */
public Result minimize(Solution solution) {
    updateFunction(solution);
    updateConstraints(solution);
    try {
        RealPointValuePair result = new SimplexSolver().optimize(function, constraints, GoalType.MINIMIZE, true);
        double[] point = result.getPoint();
        if (result.getValue() < 0) {
            return null;
        }
        for (int i = 0; i < point.length; ++i) {
            if (point[i] < 0) {
                return null;
            }
        }
        return new Result(point, context.getSheetCost(), context.getPatternCost());
    } catch (OptimizationException e) {
        logger.debug("LinearResolutionMethod.minimize: " + e.getMessage());
    }
    return null;
}

开发者ID:achaussende，项目名称:tp-2D-cutting-stock-problem，代码行数:27，代码来源:LinearResolutionMethod.java

示例2: testRosenbrock

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
public void testRosenbrock()
  throws FunctionEvaluationException, ConvergenceException {

  Rosenbrock rosenbrock = new Rosenbrock();
  NelderMead optimizer = new NelderMead();
  optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1, 1.0e-3));
  optimizer.setMaxIterations(100);
  optimizer.setStartConfiguration(new double[][] {
          { -1.2,  1.0 }, { 0.9, 1.2 } , {  3.5, -2.3 }
  });
  RealPointValuePair optimum =
      optimizer.optimize(rosenbrock, GoalType.MINIMIZE, new double[] { -1.2, 1.0 });

  assertEquals(rosenbrock.getCount(), optimizer.getEvaluations());
  assertTrue(optimizer.getEvaluations() > 40);
  assertTrue(optimizer.getEvaluations() < 50);
  assertTrue(optimum.getValue() < 8.0e-4);

}

开发者ID:SpoonLabs，项目名称:astor，代码行数:21，代码来源:NelderMeadTest.java

示例3: testEpsilon

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
  public void testEpsilon() throws OptimizationException {
    LinearObjectiveFunction f =
        new LinearObjectiveFunction(new double[] { 10, 5, 1 }, 0);
    Collection<LinearConstraint> constraints = new ArrayList<LinearConstraint>();
    constraints.add(new LinearConstraint(new double[] {  9, 8, 0 }, Relationship.EQ,  17));
    constraints.add(new LinearConstraint(new double[] {  0, 7, 8 }, Relationship.LEQ,  7));
    constraints.add(new LinearConstraint(new double[] { 10, 0, 2 }, Relationship.LEQ, 10));

    SimplexSolver solver = new SimplexSolver();
    RealPointValuePair solution = solver.optimize(f, constraints, GoalType.MAXIMIZE, false);
    assertEquals(1.0, solution.getPoint()[0], 0.0);
    assertEquals(1.0, solution.getPoint()[1], 0.0);
    assertEquals(0.0, solution.getPoint()[2], 0.0);
    assertEquals(15.0, solution.getValue(), 0.0);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:17，代码来源:SimplexSolverTest.java

示例4: testOneSet

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testOneSet() throws FunctionEvaluationException, OptimizationException {

        LinearProblem problem = new LinearProblem(new double[][] {
                {  1,  0, 0 },
                { -1,  1, 0 },
                {  0, -1, 1 }
        }, new double[] { 1, 1, 1});
        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[] { 0, 0, 0 });
        assertEquals(1.0, optimum.getPoint()[0], 1.0e-10);
        assertEquals(2.0, optimum.getPoint()[1], 1.0e-10);
        assertEquals(3.0, optimum.getPoint()[2], 1.0e-10);

    }

开发者ID:SpoonLabs，项目名称:astor，代码行数:19，代码来源:NonLinearConjugateGradientOptimizerTest.java

示例5: testRedundantEquations

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testRedundantEquations() throws FunctionEvaluationException, OptimizationException {
    LinearProblem problem = new LinearProblem(new double[][] {
            { 1.0,  1.0 },
            { 1.0, -1.0 },
            { 1.0,  3.0 }
    }, new double[] { 3.0, 1.0, 5.0 });

    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[] { 1, 1 });
    assertEquals(2.0, optimum.getPoint()[0], 1.0e-8);
    assertEquals(1.0, optimum.getPoint()[1], 1.0e-8);

}

开发者ID:SpoonLabs，项目名称:astor，代码行数:18，代码来源:NonLinearConjugateGradientOptimizerTest.java

示例6: testNoDependency

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testNoDependency() throws FunctionEvaluationException, OptimizationException {
    LinearProblem problem = new LinearProblem(new double[][] {
            { 2, 0, 0, 0, 0, 0 },
            { 0, 2, 0, 0, 0, 0 },
            { 0, 0, 2, 0, 0, 0 },
            { 0, 0, 0, 2, 0, 0 },
            { 0, 0, 0, 0, 2, 0 },
            { 0, 0, 0, 0, 0, 2 }
    }, new double[] { 0.0, 1.1, 2.2, 3.3, 4.4, 5.5 });
    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[] { 0, 0, 0, 0, 0, 0 });
    for (int i = 0; i < problem.target.length; ++i) {
        assertEquals(0.55 * i, optimum.getPoint()[i], 1.0e-10);
    }
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:20，代码来源:NonLinearConjugateGradientOptimizerTest.java

示例7: optimize

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
/** {@inheritDoc} */
public RealPointValuePair optimize(final DifferentiableMultivariateRealFunction f,
                                     final GoalType goalType,
                                     final double[] startPoint)
    throws FunctionEvaluationException, OptimizationException, IllegalArgumentException {

    // reset counters
    iterations          = 0;
    evaluations         = 0;
    gradientEvaluations = 0;

    // store optimization problem characteristics
    this.f        = f;
    gradient      = f.gradient();
    this.goalType = goalType;
    point         = startPoint.clone();

    return doOptimize();

}

开发者ID:SpoonLabs，项目名称:astor，代码行数:21，代码来源:AbstractScalarDifferentiableOptimizer.java

示例8: testColumnsPermutation

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testColumnsPermutation() throws FunctionEvaluationException, OptimizationException {

        LinearProblem problem =
            new LinearProblem(new double[][] { { 1.0, -1.0 }, { 0.0, 2.0 }, { 1.0, -2.0 } },
                              new double[] { 4.0, 6.0, 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[] { 0, 0 });
        assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
        assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
        assertEquals(0.0, optimum.getValue(), 1.0e-10);

    }

开发者ID:SpoonLabs，项目名称:astor，代码行数:18，代码来源:NonLinearConjugateGradientOptimizerTest.java

示例9: testPowell

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
public void testPowell() {
    MultivariateRealFunction powell =
        new MultivariateRealFunction() {
            public double value(double[] x) {
                ++count;
                double a = x[0] + 10 * x[1];
                double b = x[2] - x[3];
                double c = x[1] - 2 * x[2];
                double d = x[0] - x[3];
                return a * a + 5 * b * b + c * c * c * c + 10 * d * d * d * d;
            }
        };

    count = 0;
    SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-3);
    optimizer.setSimplex(new MultiDirectionalSimplex(4));
    RealPointValuePair optimum =
        optimizer.optimize(1000, powell, GoalType.MINIMIZE, new double[] { 3, -1, 0, 1 });
    Assert.assertEquals(count, optimizer.getEvaluations());
    Assert.assertTrue(optimizer.getEvaluations() > 800);
    Assert.assertTrue(optimizer.getEvaluations() < 900);
    Assert.assertTrue(optimum.getValue() > 1e-2);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:25，代码来源:SimplexOptimizerMultiDirectionalTest.java

示例10: testMoreEstimatedParametersSimple

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testMoreEstimatedParametersSimple()
    throws FunctionEvaluationException, OptimizationException {

    LinearProblem problem = new LinearProblem(new double[][] {
            { 3.0, 2.0,  0.0, 0.0 },
            { 0.0, 1.0, -1.0, 1.0 },
            { 2.0, 0.0,  1.0, 0.0 }
    }, new double[] { 7.0, 3.0, 5.0 });

    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[] { 7, 6, 5, 4 });
    assertEquals(0, optimum.getValue(), 1.0e-10);

}

开发者ID:SpoonLabs，项目名称:astor，代码行数:19，代码来源:NonLinearConjugateGradientOptimizerTest.java

示例11: buildSimplex

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
/** Build an initial simplex.
 * @param startPoint the start point for optimization
 * @exception IllegalArgumentException if the start point does not match
 * simplex dimension
 */
private void buildSimplex(final double[] startPoint)
    throws IllegalArgumentException {

    final int n = startPoint.length;
    if (n != startConfiguration.length) {
        throw MathRuntimeException.createIllegalArgumentException(
                "dimension mismatch {0} != {1}",
                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);
    }

}

开发者ID:SpoonLabs，项目名称:astor，代码行数:31，代码来源:DirectSearchOptimizer.java

示例12: testInconsistentEquations

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testInconsistentEquations() throws FunctionEvaluationException, OptimizationException {
    LinearProblem problem = new LinearProblem(new double[][] {
            { 1.0,  1.0 },
            { 1.0, -1.0 },
            { 1.0,  3.0 }
    }, new double[] { 3.0, 1.0, 4.0 });

    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[] { 1, 1 });
    assertTrue(optimum.getValue() > 0.1);

}

开发者ID:SpoonLabs，项目名称:astor，代码行数:17，代码来源:NonLinearConjugateGradientOptimizerTest.java

示例13: testEpsilon

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
  public void testEpsilon() throws OptimizationException {
    LinearObjectiveFunction f =
        new LinearObjectiveFunction(new double[] { 10, 5, 1 }, 0);
    Collection<LinearConstraint> constraints = new ArrayList<LinearConstraint>();
    constraints.add(new LinearConstraint(new double[] {  9, 8, 0 }, Relationship.EQ,  17));
    constraints.add(new LinearConstraint(new double[] {  0, 7, 8 }, Relationship.LEQ,  7));
    constraints.add(new LinearConstraint(new double[] { 10, 0, 2 }, Relationship.LEQ, 10));

    SimplexSolver solver = new SimplexSolver();
    RealPointValuePair solution = solver.optimize(f, constraints, GoalType.MAXIMIZE, false);
    Assert.assertEquals(1.0, solution.getPoint()[0], 0.0);
    Assert.assertEquals(1.0, solution.getPoint()[1], 0.0);
    Assert.assertEquals(0.0, solution.getPoint()[2], 0.0);
    Assert.assertEquals(15.0, solution.getValue(), 0.0);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:17，代码来源:SimplexSolverTest.java

示例14: testCircleFitting

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testCircleFitting() throws FunctionEvaluationException, OptimizationException {
    Circle circle = new Circle();
    circle.addPoint( 30.0,  68.0);
    circle.addPoint( 50.0,  -6.0);
    circle.addPoint(110.0, -20.0);
    circle.addPoint( 35.0,  15.0);
    circle.addPoint( 45.0,  97.0);
    NonLinearConjugateGradientOptimizer optimizer =
        new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
    optimizer.setMaxIterations(100);
    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);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:23，代码来源:NonLinearConjugateGradientOptimizerTest.java

示例15: testMath283

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
public void testMath283()
    throws FunctionEvaluationException, OptimizationException {
    // fails because MultiDirectional.iterateSimplex is looping forever
    // the while(true) should be replaced with a convergence check
    MultiDirectional multiDirectional = new MultiDirectional();
    multiDirectional.setMaxIterations(100);
    multiDirectional.setMaxEvaluations(1000);

    final Gaussian2D function = new Gaussian2D(0.0, 0.0, 1.0);

    RealPointValuePair estimate = multiDirectional.optimize(function,
                                  GoalType.MAXIMIZE, function.getMaximumPosition());

    final double EPSILON = 1e-5;

    final double expectedMaximum = function.getMaximum();
    final double actualMaximum = estimate.getValue();
    Assert.assertEquals(expectedMaximum, actualMaximum, EPSILON);

    final double[] expectedPosition = function.getMaximumPosition();
    final double[] actualPosition = estimate.getPoint();
    Assert.assertEquals(expectedPosition[0], actualPosition[0], EPSILON );
    Assert.assertEquals(expectedPosition[1], actualPosition[1], EPSILON );

}

开发者ID:SpoonLabs，项目名称:astor，代码行数:27，代码来源:MultiDirectionalTest.java

示例16: testLeastSquares1

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
public void testLeastSquares1()
throws FunctionEvaluationException, ConvergenceException {

    final RealMatrix factors =
        new Array2DRowRealMatrix(new double[][] {
            { 1.0, 0.0 },
            { 0.0, 1.0 }
        }, false);
    LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
        public double[] value(double[] variables) {
            return factors.operate(variables);
        }
    }, new double[] { 2.0, -3.0 });
    NelderMead optimizer = new NelderMead();
    optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1.0, 1.0e-6));
    optimizer.setMaxIterations(200);
    RealPointValuePair optimum =
        optimizer.optimize(ls, GoalType.MINIMIZE, new double[] { 10.0, 10.0 });
    assertEquals( 2.0, optimum.getPointRef()[0], 3.0e-5);
    assertEquals(-3.0, optimum.getPointRef()[1], 4.0e-4);
    assertTrue(optimizer.getEvaluations() > 60);
    assertTrue(optimizer.getEvaluations() < 80);
    assertTrue(optimum.getValue() < 1.0e-6);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:26，代码来源:NelderMeadTest.java

示例17: testMath434PivotRowSelection2

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
public void testMath434PivotRowSelection2() throws OptimizationException
{
    LinearObjectiveFunction f = new LinearObjectiveFunction(new double[] {0.0d, 1.0d, 1.0d, 0.0d, 0.0d, 0.0d, 0.0d}, 0.0d);

    ArrayList<LinearConstraint> constraints = new ArrayList<LinearConstraint>();
    constraints.add(new LinearConstraint(new double[] {1.0d, -0.1d, 0.0d, 0.0d, 0.0d, 0.0d, 0.0d}, Relationship.EQ, -0.1d));
    constraints.add(new LinearConstraint(new double[] {1.0d, 0.0d, 0.0d, 0.0d, 0.0d, 0.0d, 0.0d}, Relationship.GEQ, -1e-18d));
    constraints.add(new LinearConstraint(new double[] {0.0d, 1.0d, 0.0d, 0.0d, 0.0d, 0.0d, 0.0d}, Relationship.GEQ, 0.0d));
    constraints.add(new LinearConstraint(new double[] {0.0d, 0.0d, 0.0d, 1.0d, 0.0d, -0.0128588d, 1e-5d}, Relationship.EQ, 0.0d));
    constraints.add(new LinearConstraint(new double[] {0.0d, 0.0d, 0.0d, 0.0d, 1.0d, 1e-5d, -0.0128586d}, Relationship.EQ, 1e-10d));
    constraints.add(new LinearConstraint(new double[] {0.0d, 0.0d, 1.0d, -1.0d, 0.0d, 0.0d, 0.0d}, Relationship.GEQ, 0.0d));
    constraints.add(new LinearConstraint(new double[] {0.0d, 0.0d, 1.0d, 1.0d, 0.0d, 0.0d, 0.0d}, Relationship.GEQ, 0.0d));
    constraints.add(new LinearConstraint(new double[] {0.0d, 0.0d, 1.0d, 0.0d, -1.0d, 0.0d, 0.0d}, Relationship.GEQ, 0.0d));
    constraints.add(new LinearConstraint(new double[] {0.0d, 0.0d, 1.0d, 0.0d, 1.0d, 0.0d, 0.0d}, Relationship.GEQ, 0.0d));

    double epsilon = 1e-7;
    SimplexSolver simplex = new SimplexSolver();
    RealPointValuePair solution = simplex.optimize(f, constraints, GoalType.MINIMIZE, false);
    
    Assert.assertTrue(MathUtils.compareTo(solution.getPoint()[0], -1e-18d, epsilon) >= 0);
    Assert.assertEquals(1.0d, solution.getPoint()[1], epsilon);        
    Assert.assertEquals(0.0d, solution.getPoint()[2], epsilon);
    Assert.assertEquals(1.0d, solution.getValue(), epsilon);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:26，代码来源:SimplexSolverTest.java

示例18: testMath272

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
public void testMath272() throws OptimizationException {
    LinearObjectiveFunction f = new LinearObjectiveFunction(new double[] { 2, 2, 1 }, 0);
    Collection<LinearConstraint> constraints = new ArrayList<LinearConstraint>();
    constraints.add(new LinearConstraint(new double[] { 1, 1, 0 }, Relationship.GEQ,  1));
    constraints.add(new LinearConstraint(new double[] { 1, 0, 1 }, Relationship.GEQ,  1));
    constraints.add(new LinearConstraint(new double[] { 0, 1, 0 }, Relationship.GEQ,  1));

    SimplexSolver solver = new SimplexSolver();
    RealPointValuePair solution = solver.optimize(f, constraints, GoalType.MINIMIZE, true);

    Assert.assertEquals(0.0, solution.getPoint()[0], .0000001);
    Assert.assertEquals(1.0, solution.getPoint()[1], .0000001);
    Assert.assertEquals(1.0, solution.getPoint()[2], .0000001);
    Assert.assertEquals(3.0, solution.getValue(), .0000001);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:17，代码来源:SimplexSolverTest.java

示例19: testLeastSquares3

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
@Test
public void testLeastSquares3() {

    final RealMatrix factors =
        new Array2DRowRealMatrix(new double[][] {
                { 1, 0 },
                { 0, 1 }
            }, false);
    LeastSquaresConverter ls = new LeastSquaresConverter(new MultivariateVectorialFunction() {
            public double[] value(double[] variables) {
                return factors.operate(variables);
            }
        }, new double[] { 2, -3 }, new Array2DRowRealMatrix(new double [][] {
                { 1, 1.2 }, { 1.2, 2 }
            }));
    SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-6);
    optimizer.setSimplex(new NelderMeadSimplex(2));
    RealPointValuePair optimum =
        optimizer.optimize(200, ls, GoalType.MINIMIZE, new double[] { 10, 10 });
    Assert.assertEquals( 2, optimum.getPointRef()[0], 2e-3);
    Assert.assertEquals(-3, optimum.getPointRef()[1], 8e-4);
    Assert.assertTrue(optimizer.getEvaluations() > 60);
    Assert.assertTrue(optimizer.getEvaluations() < 80);
    Assert.assertTrue(optimum.getValue() < 1e-6);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:26，代码来源:SimplexOptimizerNelderMeadTest.java

示例20: testMoreEstimatedParametersUnsorted

import org.apache.commons.math.optimization.RealPointValuePair; //导入依赖的package包/类
public void testMoreEstimatedParametersUnsorted()
    throws FunctionEvaluationException, OptimizationException {
    LinearProblem problem = new LinearProblem(new double[][] {
             { 1.0, 1.0,  0.0,  0.0, 0.0,  0.0 },
             { 0.0, 0.0,  1.0,  1.0, 1.0,  0.0 },
             { 0.0, 0.0,  0.0,  0.0, 1.0, -1.0 },
             { 0.0, 0.0, -1.0,  1.0, 0.0,  1.0 },
             { 0.0, 0.0,  0.0, -1.0, 1.0,  0.0 }
    }, 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);
}

开发者ID:SpoonLabs，项目名称:astor，代码行数:18，代码来源:NonLinearConjugateGradientOptimizerTest.java

注：本文中的org.apache.commons.math.optimization.RealPointValuePair类示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。

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Java RealPointValuePair类代码示例

示例1: minimize

示例2: testRosenbrock

示例3: testEpsilon

示例4: testOneSet

示例5: testRedundantEquations

示例6: testNoDependency

示例7: optimize

示例8: testColumnsPermutation

示例9: testPowell

示例10: testMoreEstimatedParametersSimple

示例11: buildSimplex

示例12: testInconsistentEquations

示例13: testEpsilon

示例14: testCircleFitting

示例15: testMath283

示例16: testLeastSquares1

示例17: testMath434PivotRowSelection2

示例18: testMath272

示例19: testLeastSquares3

示例20: testMoreEstimatedParametersUnsorted

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