Reformat
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@ -15,8 +15,9 @@ class GaussianSampler private constructor(
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private val standardDeviation: Double,
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private val normalized: NormalizedGaussianSampler
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) : Sampler<Double> {
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override fun sample(generator: RandomGenerator): Chain<Double> =
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normalized.sample(generator).map { standardDeviation * it + mean }
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override fun sample(generator: RandomGenerator): Chain<Double> = normalized
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.sample(generator)
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.map { standardDeviation * it + mean }
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override fun toString(): String = "Gaussian deviate [$normalized]"
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@ -30,10 +30,8 @@ class MarsagliaNormalizedGaussianSampler private constructor(): NormalizedGaussi
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if (r2 < 1 && r2 > 0) {
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// Pair (x, y) is within unit circle.
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alpha = sqrt(-2 * ln(r2) / r2)
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// Keep second element of the pair for next invocation.
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nextGaussian = alpha * y
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// Return the first element of the generated pair.
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break
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}
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@ -46,7 +44,6 @@ class MarsagliaNormalizedGaussianSampler private constructor(): NormalizedGaussi
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// Use the second element of the pair (generated at the
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// previous invocation).
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val r = nextGaussian
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// Both elements of the pair have been used.
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nextGaussian = Double.NaN
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r
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@ -73,8 +73,7 @@ class ZigguratNormalizedGaussianSampler private constructor() :
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// Filling the tables.
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var d = R
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var t = d
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var fd =
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gauss(d)
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var fd = gauss(d)
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val q = V / fd
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K[0] = (d / q * MAX).toLong()
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K[1] = 0
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@ -85,10 +84,7 @@ class ZigguratNormalizedGaussianSampler private constructor() :
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(LAST - 1 downTo 1).forEach { i ->
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d = sqrt(-2 * ln(V / d + fd))
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fd =
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gauss(
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d
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)
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fd = gauss(d)
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K[i + 1] = (d / t * MAX).toLong()
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t = d
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F[i] = fd
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