本文整理汇总了Java中org.apache.commons.math3.distribution.RealDistribution.reseedRandomGenerator方法的典型用法代码示例。如果您正苦于以下问题：Java RealDistribution.reseedRandomGenerator方法的具体用法？Java RealDistribution.reseedRandomGenerator怎么用？Java RealDistribution.reseedRandomGenerator使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.commons.math3.distribution.RealDistribution的用法示例。
在下文中一共展示了RealDistribution.reseedRandomGenerator方法的3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，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: testPolynomialFit
import org.apache.commons.math3.distribution.RealDistribution; //导入方法依赖的package包/类
@Test
public void testPolynomialFit() {
final Random randomizer = new Random(53882150042L);
final RealDistribution rng = new UniformRealDistribution(-100, 100);
rng.reseedRandomGenerator(64925784252L);
final double[] coeff = { 12.9, -3.4, 2.1 }; // 12.9 - 3.4 x + 2.1 x^2
final PolynomialFunction f = new PolynomialFunction(coeff);
// Collect data from a known polynomial.
final WeightedObservedPoints obs = new WeightedObservedPoints();
for (int i = 0; i < 100; i++) {
final double x = rng.sample();
obs.add(x, f.value(x) + 0.1 * randomizer.nextGaussian());
}
final ParametricUnivariateFunction function = new PolynomialFunction.Parametric();
// Start fit from initial guesses that are far from the optimal values.
final SimpleCurveFitter fitter
= SimpleCurveFitter.create(function,
new double[] { -1e20, 3e15, -5e25 });
final double[] best = fitter.fit(obs.toList());
TestUtils.assertEquals("best != coeff", coeff, best, 2e-2);
}
示例2: testFit
import org.apache.commons.math3.distribution.RealDistribution; //导入方法依赖的package包/类
@Test
public void testFit() {
final RealDistribution rng = new UniformRealDistribution(-100, 100);
rng.reseedRandomGenerator(64925784252L);
final LevenbergMarquardtOptimizer optim = new LevenbergMarquardtOptimizer();
final PolynomialFitter fitter = new PolynomialFitter(optim);
final double[] coeff = { 12.9, -3.4, 2.1 }; // 12.9 - 3.4 x + 2.1 x^2
final PolynomialFunction f = new PolynomialFunction(coeff);
// Collect data from a known polynomial.
for (int i = 0; i < 100; i++) {
final double x = rng.sample();
fitter.addObservedPoint(x, f.value(x));
}
// Start fit from initial guesses that are far from the optimal values.
final double[] best = fitter.fit(new double[] { -1e-20, 3e15, -5e25 });
TestUtils.assertEquals("best != coeff", coeff, best, 1e-12);
}
示例3: testFit
import org.apache.commons.math3.distribution.RealDistribution; //导入方法依赖的package包/类
@Test
public void testFit() {
final RealDistribution rng = new UniformRealDistribution(-100, 100);
rng.reseedRandomGenerator(64925784252L);
final double[] coeff = { 12.9, -3.4, 2.1 }; // 12.9 - 3.4 x + 2.1 x^2
final PolynomialFunction f = new PolynomialFunction(coeff);
// Collect data from a known polynomial.
final WeightedObservedPoints obs = new WeightedObservedPoints();
for (int i = 0; i < 100; i++) {
final double x = rng.sample();
obs.add(x, f.value(x));
}
// Start fit from initial guesses that are far from the optimal values.
final PolynomialCurveFitter fitter
= PolynomialCurveFitter.create(0).withStartPoint(new double[] { -1e-20, 3e15, -5e25 });
final double[] best = fitter.fit(obs.toList());
TestUtils.assertEquals("best != coeff", coeff, best, 1e-12);
}