org.apache.commons.math3.optim.SimpleBounds Java Examples
The following examples show how to use
org.apache.commons.math3.optim.SimpleBounds.
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Example #1
| Source File: NonLinearConjugateGradientOptimizerTest.java From astor with GNU General Public License v2.0 | 6 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
LinearProblem problem
= new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
NonLinearConjugateGradientOptimizer optimizer
= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
new SimpleValueChecker(1e-6, 1e-6),
1e-3, 1e-3, 1);
optimizer.optimize(new MaxEval(100),
problem.getObjectiveFunction(),
problem.getObjectiveFunctionGradient(),
GoalType.MINIMIZE,
new InitialGuess(new double[] { 0 }),
new SimpleBounds(new double[] { -1 },
new double[] { 1 }));
}
Example #2
| Source File: NonLinearConjugateGradientOptimizerTest.java From astor with GNU General Public License v2.0 | 6 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
LinearProblem problem
= new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
NonLinearConjugateGradientOptimizer optimizer
= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
new SimpleValueChecker(1e-6, 1e-6),
1e-3, 1e-3, 1);
optimizer.optimize(new MaxEval(100),
problem.getObjectiveFunction(),
problem.getObjectiveFunctionGradient(),
GoalType.MINIMIZE,
new InitialGuess(new double[] { 0 }),
new SimpleBounds(new double[] { -1 },
new double[] { 1 }));
}
Example #3
| Source File: CMAESOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testMath864() {
final CMAESOptimizer optimizer
= new CMAESOptimizer(30000, 0, true, 10,
0, new MersenneTwister(), false, null);
final MultivariateFunction fitnessFunction = new MultivariateFunction() {
public double value(double[] parameters) {
final double target = 1;
final double error = target - parameters[0];
return error * error;
}
};
final double[] start = { 0 };
final double[] lower = { -1e6 };
final double[] upper = { 1.5 };
final double[] sigma = { 1e-1 };
final double[] result = optimizer.optimize(new MaxEval(10000),
new ObjectiveFunction(fitnessFunction),
GoalType.MINIMIZE,
new CMAESOptimizer.PopulationSize(5),
new CMAESOptimizer.Sigma(sigma),
new InitialGuess(start),
new SimpleBounds(lower, upper)).getPoint();
Assert.assertTrue("Out of bounds (" + result[0] + " > " + upper[0] + ")",
result[0] <= upper[0]);
}
Example #4
| Source File: GaussNewtonOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #5
| Source File: LevenbergMarquardtOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #6
| Source File: NonLinearConjugateGradientOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
LinearProblem problem
= new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
NonLinearConjugateGradientOptimizer optimizer
= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
new SimpleValueChecker(1e-6, 1e-6));
optimizer.optimize(new MaxEval(100),
problem.getObjectiveFunction(),
problem.getObjectiveFunctionGradient(),
GoalType.MINIMIZE,
new InitialGuess(new double[] { 0 }),
new SimpleBounds(new double[] { -1 },
new double[] { 1 }));
}
Example #7
| Source File: SimplexOptimizerMultiDirectionalTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #8
| Source File: PowellOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
final MultivariateFunction func = new SumSincFunction(-1);
final PowellOptimizer optim = new PowellOptimizer(1e-8, 1e-5,
1e-4, 1e-4);
optim.optimize(new MaxEval(100),
new ObjectiveFunction(func),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #9
| Source File: SimplexOptimizerNelderMeadTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #10
| Source File: MultiStartMultivariateVectorOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testIssue914() {
LinearProblem problem = new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
JacobianMultivariateVectorOptimizer underlyingOptimizer =
new GaussNewtonOptimizer(true, new SimpleVectorValueChecker(1e-6, 1e-6)) {
@Override
public PointVectorValuePair optimize(OptimizationData... optData) {
// filter out simple bounds, as they are not supported
// by the underlying optimizer, and we don't really care for this test
OptimizationData[] filtered = optData.clone();
for (int i = 0; i < filtered.length; ++i) {
if (filtered[i] instanceof SimpleBounds) {
filtered[i] = null;
}
}
return super.optimize(filtered);
}
};
JDKRandomGenerator g = new JDKRandomGenerator();
g.setSeed(16069223052l);
RandomVectorGenerator generator =
new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
MultiStartMultivariateVectorOptimizer optimizer =
new MultiStartMultivariateVectorOptimizer(underlyingOptimizer, 10, generator);
optimizer.optimize(new MaxEval(100),
problem.getModelFunction(),
problem.getModelFunctionJacobian(),
problem.getTarget(),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 0 }),
new SimpleBounds(new double[] { -1.0e-10 }, new double[] { 1.0e-10 }));
PointVectorValuePair[] optima = optimizer.getOptima();
// only the first start should have succeeded
Assert.assertEquals(1, optima.length);
}
Example #11
| Source File: GaussNewtonOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #12
| Source File: LevenbergMarquardtOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #13
| Source File: NonLinearConjugateGradientOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
LinearProblem problem
= new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
NonLinearConjugateGradientOptimizer optimizer
= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
new SimpleValueChecker(1e-6, 1e-6));
optimizer.optimize(new MaxEval(100),
problem.getObjectiveFunction(),
problem.getObjectiveFunctionGradient(),
GoalType.MINIMIZE,
new InitialGuess(new double[] { 0 }),
new SimpleBounds(new double[] { -1 },
new double[] { 1 }));
}
Example #14
| Source File: SimplexOptimizerMultiDirectionalTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #15
| Source File: CMAESOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testMath864() {
final CMAESOptimizer optimizer
= new CMAESOptimizer(30000, 0, true, 10,
0, new MersenneTwister(), false, null);
final MultivariateFunction fitnessFunction = new MultivariateFunction() {
public double value(double[] parameters) {
final double target = 1;
final double error = target - parameters[0];
return error * error;
}
};
final double[] start = { 0 };
final double[] lower = { -1e6 };
final double[] upper = { 1.5 };
final double[] sigma = { 1e-1 };
final double[] result = optimizer.optimize(new MaxEval(10000),
new ObjectiveFunction(fitnessFunction),
GoalType.MINIMIZE,
new CMAESOptimizer.PopulationSize(5),
new CMAESOptimizer.Sigma(sigma),
new InitialGuess(start),
new SimpleBounds(lower, upper)).getPoint();
Assert.assertTrue("Out of bounds (" + result[0] + " > " + upper[0] + ")",
result[0] <= upper[0]);
}
Example #16
| Source File: PowellOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
final MultivariateFunction func = new SumSincFunction(-1);
final PowellOptimizer optim = new PowellOptimizer(1e-8, 1e-5,
1e-4, 1e-4);
optim.optimize(new MaxEval(100),
new ObjectiveFunction(func),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #17
| Source File: SimplexOptimizerNelderMeadTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #18
| Source File: MultiStartMultivariateVectorOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testIssue914() {
LinearProblem problem = new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
JacobianMultivariateVectorOptimizer underlyingOptimizer =
new GaussNewtonOptimizer(true, new SimpleVectorValueChecker(1e-6, 1e-6)) {
@Override
public PointVectorValuePair optimize(OptimizationData... optData) {
// filter out simple bounds, as they are not supported
// by the underlying optimizer, and we don't really care for this test
OptimizationData[] filtered = optData.clone();
for (int i = 0; i < filtered.length; ++i) {
if (filtered[i] instanceof SimpleBounds) {
filtered[i] = null;
}
}
return super.optimize(filtered);
}
};
JDKRandomGenerator g = new JDKRandomGenerator();
g.setSeed(16069223052l);
RandomVectorGenerator generator =
new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
MultiStartMultivariateVectorOptimizer optimizer =
new MultiStartMultivariateVectorOptimizer(underlyingOptimizer, 10, generator);
optimizer.optimize(new MaxEval(100),
problem.getModelFunction(),
problem.getModelFunctionJacobian(),
problem.getTarget(),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 0 }),
new SimpleBounds(new double[] { -1.0e-10 }, new double[] { 1.0e-10 }));
PointVectorValuePair[] optima = optimizer.getOptima();
// only the first start should have succeeded
Assert.assertEquals(1, optima.length);
}
Example #19
| Source File: GaussNewtonOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #20
| Source File: LevenbergMarquardtOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #21
| Source File: SimplexOptimizerMultiDirectionalTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #22
| Source File: CMAESOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testMath864() {
final CMAESOptimizer optimizer
= new CMAESOptimizer(30000, 0, true, 10,
0, new MersenneTwister(), false, null);
final MultivariateFunction fitnessFunction = new MultivariateFunction() {
public double value(double[] parameters) {
final double target = 1;
final double error = target - parameters[0];
return error * error;
}
};
final double[] start = { 0 };
final double[] lower = { -1e6 };
final double[] upper = { 1.5 };
final double[] sigma = { 1e-1 };
final double[] result = optimizer.optimize(new MaxEval(10000),
new ObjectiveFunction(fitnessFunction),
GoalType.MINIMIZE,
new CMAESOptimizer.PopulationSize(5),
new CMAESOptimizer.Sigma(sigma),
new InitialGuess(start),
new SimpleBounds(lower, upper)).getPoint();
Assert.assertTrue("Out of bounds (" + result[0] + " > " + upper[0] + ")",
result[0] <= upper[0]);
}
Example #23
| Source File: PowellOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
final MultivariateFunction func = new SumSincFunction(-1);
final PowellOptimizer optim = new PowellOptimizer(1e-8, 1e-5,
1e-4, 1e-4);
optim.optimize(new MaxEval(100),
new ObjectiveFunction(func),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #24
| Source File: SimplexOptimizerNelderMeadTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #25
| Source File: SimplexOptimizerNelderMeadTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #26
| Source File: MultiStartMultivariateVectorOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testIssue914() {
LinearProblem problem = new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
JacobianMultivariateVectorOptimizer underlyingOptimizer =
new GaussNewtonOptimizer(true, new SimpleVectorValueChecker(1e-6, 1e-6)) {
@Override
public PointVectorValuePair optimize(OptimizationData... optData) {
// filter out simple bounds, as they are not supported
// by the underlying optimizer, and we don't really care for this test
OptimizationData[] filtered = optData.clone();
for (int i = 0; i < filtered.length; ++i) {
if (filtered[i] instanceof SimpleBounds) {
filtered[i] = null;
}
}
return super.optimize(filtered);
}
};
JDKRandomGenerator g = new JDKRandomGenerator();
g.setSeed(16069223052l);
RandomVectorGenerator generator =
new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
MultiStartMultivariateVectorOptimizer optimizer =
new MultiStartMultivariateVectorOptimizer(underlyingOptimizer, 10, generator);
optimizer.optimize(new MaxEval(100),
problem.getModelFunction(),
problem.getModelFunctionJacobian(),
problem.getTarget(),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 0 }),
new SimpleBounds(new double[] { -1.0e-10 }, new double[] { 1.0e-10 }));
PointVectorValuePair[] optima = optimizer.getOptima();
// only the first start should have succeeded
Assert.assertEquals(1, optima.length);
}
Example #27
| Source File: GaussNewtonOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #28
| Source File: LevenbergMarquardtOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testConstraintsUnsupported() {
createOptimizer().optimize(new MaxEval(100),
new Target(new double[] { 2 }),
new Weight(new double[] { 1 }),
new InitialGuess(new double[] { 1, 2 }),
new SimpleBounds(new double[] { -10, 0 },
new double[] { 20, 30 }));
}
Example #29
| Source File: SimplexOptimizerMultiDirectionalTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test(expected=MathUnsupportedOperationException.class)
public void testBoundsUnsupported() {
SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
final FourExtrema fourExtrema = new FourExtrema();
optimizer.optimize(new MaxEval(100),
new ObjectiveFunction(fourExtrema),
GoalType.MINIMIZE,
new InitialGuess(new double[] { -3, 0 }),
new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
new SimpleBounds(new double[] { -5, -1 },
new double[] { 5, 1 }));
}
Example #30
| Source File: CMAESOptimizerTest.java From astor with GNU General Public License v2.0 | 5 votes |
|
@Test
public void testMath864() {
final CMAESOptimizer optimizer
= new CMAESOptimizer(30000, 0, true, 10,
0, new MersenneTwister(), false, null);
final MultivariateFunction fitnessFunction = new MultivariateFunction() {
public double value(double[] parameters) {
final double target = 1;
final double error = target - parameters[0];
return error * error;
}
};
final double[] start = { 0 };
final double[] lower = { -1e6 };
final double[] upper = { 1.5 };
final double[] sigma = { 1e-1 };
final double[] result = optimizer.optimize(new MaxEval(10000),
new ObjectiveFunction(fitnessFunction),
GoalType.MINIMIZE,
new CMAESOptimizer.PopulationSize(5),
new CMAESOptimizer.Sigma(sigma),
new InitialGuess(start),
new SimpleBounds(lower, upper)).getPoint();
Assert.assertTrue("Out of bounds (" + result[0] + " > " + upper[0] + ")",
result[0] <= upper[0]);
}
