本文整理汇总了Java中org.apache.commons.math3.util.FastMath.E属性的典型用法代码示例。如果您正苦于以下问题：Java FastMath.E属性的具体用法？Java FastMath.E怎么用？Java FastMath.E使用的例子？那么恭喜您, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类org.apache.commons.math3.util.FastMath的用法示例。
在下文中一共展示了FastMath.E属性的1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: GammaDistribution
/**
* Creates a Gamma distribution.
*
* @param rng Random number generator.
* @param shape the shape parameter
* @param scale the scale parameter
* @param inverseCumAccuracy the maximum absolute error in inverse
* cumulative probability estimates (defaults to
* {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
* @throws NotStrictlyPositiveException if {@code shape <= 0} or
* {@code scale <= 0}.
* @since 3.1
*/
public GammaDistribution(RandomGenerator rng,
double shape,
double scale,
double inverseCumAccuracy)
throws NotStrictlyPositiveException {
super(rng);
if (shape <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SHAPE, shape);
}
if (scale <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SCALE, scale);
}
this.shape = shape;
this.scale = scale;
this.solverAbsoluteAccuracy = inverseCumAccuracy;
this.shiftedShape = shape + Gamma.LANCZOS_G + 0.5;
final double aux = FastMath.E / (2.0 * FastMath.PI * shiftedShape);
this.densityPrefactor2 = shape * FastMath.sqrt(aux) / Gamma.lanczos(shape);
this.logDensityPrefactor2 = FastMath.log(shape) + 0.5 * FastMath.log(aux) -
FastMath.log(Gamma.lanczos(shape));
this.densityPrefactor1 = this.densityPrefactor2 / scale *
FastMath.pow(shiftedShape, -shape) *
FastMath.exp(shape + Gamma.LANCZOS_G);
this.logDensityPrefactor1 = this.logDensityPrefactor2 - FastMath.log(scale) -
FastMath.log(shiftedShape) * shape +
shape + Gamma.LANCZOS_G;
this.minY = shape + Gamma.LANCZOS_G - FastMath.log(Double.MAX_VALUE);
this.maxLogY = FastMath.log(Double.MAX_VALUE) / (shape - 1.0);
}