本文整理了Java中cern.jet.random.Normal.setState()方法的一些代码示例，展示了Normal.setState()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Normal.setState()方法的具体详情如下：
包路径：cern.jet.random.Normal
类名称：Normal
方法名：setState

Normal.setState介绍

[英]Sets the mean and variance.
[中]设置均值和方差。

代码示例

代码示例来源：origin: org.jwall/streams-core

/**
 * @param variance
 *            the variance to set
 */
public void setVariance(Double variance) {
  this.variance = variance;
  this.rnd.setState(mean, variance);
}

代码示例来源：origin: org.jwall/streams-core

/**
 * @param mean
 *            the mean to set
 */
public void setMean(Double mean) {
  this.mean = mean;
  this.rnd.setState(mean, variance);
}

代码示例来源：origin: de.sfb876/streams-core

/**
 * @param mean
 *            the mean to set
 */
public void setMean(Double mean) {
  this.mean = mean;
  this.rnd.setState(mean, variance);
}

代码示例来源：origin: de.sfb876/streams-core

/**
 * @param variance
 *            the variance to set
 */
public void setVariance(Double variance) {
  this.variance = variance;
  this.rnd.setState(mean, variance);
}

代码示例来源：origin: com.blazegraph/colt

/**
 * Constructs a normal (gauss) distribution.
 * Example: mean=0.0, standardDeviation=1.0.
 */
public Normal(double mean, double standardDeviation, RandomEngine randomGenerator) {
  setRandomGenerator(randomGenerator);
  setState(mean,standardDeviation);
}
/**

代码示例来源：origin: blazegraph/database

/**
 * Constructs a normal (gauss) distribution.
 * Example: mean=0.0, standardDeviation=1.0.
 */
public Normal(double mean, double standardDeviation, RandomEngine randomGenerator) {
  setRandomGenerator(randomGenerator);
  setState(mean,standardDeviation);
}
/**

代码示例来源：origin: broadgsa/gatk

@Test
public void testNormalDistribution() {
  final double requiredPrecision = 1E-10;
  final Normal n = new Normal(0.0, 1.0, null);
  for( final double mu : new double[]{-5.0, -3.2, -1.5, 0.0, 1.2, 3.0, 5.8977} ) {
    for( final double sigma : new double[]{1.2, 3.0, 5.8977} ) {
      for( final double x : new double[]{-5.0, -3.2, -1.5, 0.0, 1.2, 3.0, 5.8977} ) {
        n.setState(mu, sigma);
        Assert.assertEquals(n.pdf(x), MathUtils.normalDistribution(mu, sigma, x), requiredPrecision);
        Assert.assertEquals(Math.log10(n.pdf(x)), MathUtils.normalDistributionLog10(mu, sigma, x), requiredPrecision);
      }
    }
  }
}