forked from kscience/kmath
get normals TBD
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@ -1,5 +1,7 @@
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package space.kscience.kmath.tensors.core
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import space.kscience.kmath.stat.RandomGenerator
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import space.kscience.kmath.stat.samplers.BoxMullerNormalizedGaussianSampler
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import space.kscience.kmath.structures.*
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import kotlin.random.Random
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import kotlin.math.*
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@ -35,8 +37,10 @@ internal fun Buffer<Double>.array(): DoubleArray = when (this) {
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is DoubleBuffer -> array
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else -> throw RuntimeException("Failed to cast Buffer to DoubleArray")
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}
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internal inline fun getRandomNormals(n: Int, seed: Long): DoubleArray {
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val u = Random(seed)
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return (0 until n).map { sqrt(-2.0 * ln(u.nextDouble())) * cos(2.0 * PI * u.nextDouble()) }.toDoubleArray()
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/*
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internal inline fun getRandomNormals(n: Int,): DoubleArray {
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val sampler = BoxMullerNormalizedGaussianSampler.of()
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val chain = sampler.sample(RandomGenerator.default)
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return (0 until n).map { chain.next() }.toDoubleArray()
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}
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*/
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