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MATH-413 (point 13) 

Selecting a random start value (instead of interval bounds).


git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1000422 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Gilles Sadowski 2010-09-23 12:11:56 +00:00
parent 8232bfbded
commit 51aa6e6ca2
2 changed files with 14 additions and 20 deletions
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24
src/main/java/org/apache/commons/math/optimization/univariate/MultiStartUnivariateRealOptimizer.java
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@ -143,18 +143,22 @@ public class MultiStartUnivariateRealOptimizer<FUNC extends UnivariateRealFuncti
final GoalType goal, final GoalType goal,
final double min, final double max) final double min, final double max)
throws FunctionEvaluationException { throws FunctionEvaluationException {
return optimize(f, goal, min, max, min + 0.5 * (max - min));
}
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goal,
final double min, final double max,
final double startValue)
throws FunctionEvaluationException {
optima = new UnivariateRealPointValuePair[starts]; optima = new UnivariateRealPointValuePair[starts];
totalEvaluations = 0; totalEvaluations = 0;
// Multi-start loop. // Multi-start loop.
for (int i = 0; i < starts; ++i) { for (int i = 0; i < starts; ++i) {
try { try {
final double bound1 = (i == 0) ? min : min + generator.nextDouble() * (max - min); final double s = (i == 0) ? startValue : min + generator.nextDouble() * (max - min);
final double bound2 = (i == 0) ? max : min + generator.nextDouble() * (max - min); optima[i] = optimizer.optimize(f, goal, min, max, s);
optima[i] = optimizer.optimize(f, goal,
FastMath.min(bound1, bound2),
FastMath.max(bound1, bound2));
} catch (FunctionEvaluationException fee) { } catch (FunctionEvaluationException fee) {
optima[i] = null; optima[i] = null;
} catch (ConvergenceException ce) { } catch (ConvergenceException ce) {
@ -177,16 +181,6 @@ public class MultiStartUnivariateRealOptimizer<FUNC extends UnivariateRealFuncti
return optima[0]; return optima[0];
} }
/** {@inheritDoc} */
public UnivariateRealPointValuePair optimize(final FUNC f, final GoalType goalType,
final double min, final double max,
final double startValue)
throws FunctionEvaluationException {
// XXX Main code should be here, using "startValue" for the first start.
// XXX This method should set "startValue" to min + 0.5 * (max - min)
return optimize(f, goalType, min, max);
}
/** /**
* Sort the optima from best to worst, followed by {@code null} elements. * Sort the optima from best to worst, followed by {@code null} elements.
* *

10
src/test/java/org/apache/commons/math/optimization/univariate/MultiStartUnivariateRealOptimizerTest.java
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@ -50,8 +50,8 @@ public class MultiStartUnivariateRealOptimizerTest {
assertEquals(-1.0, f.value(optima[i].getPoint()), 1.0e-10); assertEquals(-1.0, f.value(optima[i].getPoint()), 1.0e-10);
assertEquals(f.value(optima[i].getPoint()), optima[i].getValue(), 1.0e-10); assertEquals(f.value(optima[i].getPoint()), optima[i].getValue(), 1.0e-10);
} }
assertTrue(optimizer.getEvaluations() > 150); assertTrue(optimizer.getEvaluations() > 200);
assertTrue(optimizer.getEvaluations() < 250); assertTrue(optimizer.getEvaluations() < 300);
} }
@Test @Test
@ -68,14 +68,14 @@ public class MultiStartUnivariateRealOptimizerTest {
UnivariateRealPointValuePair optimum UnivariateRealPointValuePair optimum
= optimizer.optimize(f, GoalType.MINIMIZE, -0.3, -0.2); = optimizer.optimize(f, GoalType.MINIMIZE, -0.3, -0.2);
assertEquals(-0.2719561271, optimum.getPoint(), 1e-9); assertEquals(-0.2719561293, optimum.getPoint(), 1e-9);
assertEquals(-0.0443342695, optimum.getValue(), 1e-9); assertEquals(-0.0443342695, optimum.getValue(), 1e-9);
UnivariateRealPointValuePair[] optima = optimizer.getOptima(); UnivariateRealPointValuePair[] optima = optimizer.getOptima();
for (int i = 0; i < optima.length; ++i) { for (int i = 0; i < optima.length; ++i) {
assertEquals(f.value(optima[i].getPoint()), optima[i].getValue(), 1e-9); assertEquals(f.value(optima[i].getPoint()), optima[i].getValue(), 1e-9);
} }
assertTrue(optimizer.getEvaluations() >= 110); assertTrue(optimizer.getEvaluations() >= 50);
assertTrue(optimizer.getEvaluations() <= 150); assertTrue(optimizer.getEvaluations() <= 100);
} }
} }