forked from kscience/kmath
Fix package names
This commit is contained in:
Iaroslav Postovalov
parent
3c602e859d
commit
f18cd9ad40
examples/src/main/kotlin/kscience/kmath/commons/prob
kmath-commons/src/test/kotlin/kscience/kmath/commons/optimization
kmath-stat/src
commonMain/kotlin/kscience/kmath/stat
distributions
internal
samplers
AhrensDieterExponentialSampler.ktAhrensDieterMarsagliaTsangGammaSampler.ktAliasMethodDiscreteSampler.ktBoxMullerNormalizedGaussianSampler.ktGaussianSampler.ktKempSmallMeanPoissonSampler.ktLargeMeanPoissonSampler.ktMarsagliaNormalizedGaussianSampler.ktNormalizedGaussianSampler.ktPoissonSampler.ktSmallMeanPoissonSampler.ktZigguratNormalizedGaussianSampler.kt
jvmTest/kotlin/kscience/kmath/stat
@ -3,10 +3,10 @@ package kscience.kmath.commons.prob
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import kotlinx.coroutines.Dispatchers
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import kotlinx.coroutines.async
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import kotlinx.coroutines.runBlocking
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.blocking
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import kscience.kmath.prob.fromSource
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import kscience.kmath.prob.samplers.GaussianSampler
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.blocking
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import kscience.kmath.stat.fromSource
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import kscience.kmath.stat.samplers.GaussianSampler
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import org.apache.commons.rng.simple.RandomSource
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import java.time.Duration
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import java.time.Instant
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@ -3,8 +3,8 @@ package kscience.kmath.commons.prob
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import kotlinx.coroutines.runBlocking
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import kscience.kmath.chains.Chain
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import kscience.kmath.chains.collectWithState
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.samplers.ZigguratNormalizedGaussianSampler
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private data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
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@ -1,11 +1,11 @@
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package kscience.kmath.commons.optimization
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import kotlinx.coroutines.runBlocking
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import kscience.kmath.commons.expressions.DerivativeStructureExpression
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import kscience.kmath.expressions.symbol
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import kscience.kmath.stat.Distribution
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import kscience.kmath.stat.Fitting
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.normal
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import kscience.kmath.stat.distributions.NormalDistribution
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import org.junit.jupiter.api.Test
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import kotlin.math.pow
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@ -39,20 +39,15 @@ internal class OptimizeTest {
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}
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@Test
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fun testCmFit() {
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fun testCmFit() = runBlocking {
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val a by symbol
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val b by symbol
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val c by symbol
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val sigma = 1.0
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val generator = Distribution.normal(0.0, sigma)
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val generator = NormalDistribution(0.0, sigma)
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val chain = generator.sample(RandomGenerator.default(112667))
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val x = (1..100).map(Int::toDouble)
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val y = x.map {
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it.pow(2) + it + 1 + chain.nextDouble()
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}
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val y = x.map { it.pow(2) + it + 1.0 + chain.next() }
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val yErr = List(x.size) { sigma }
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val chi2 = Fitting.chiSquared(x, y, yErr) { x1 ->
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@ -1,12 +1,12 @@
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package kscience.kmath.prob.distributions
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package kscience.kmath.stat.distributions
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.UnivariateDistribution
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import kscience.kmath.prob.internal.InternalErf
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import kscience.kmath.prob.samplers.GaussianSampler
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import kscience.kmath.prob.samplers.NormalizedGaussianSampler
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import kscience.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.UnivariateDistribution
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import kscience.kmath.stat.internal.InternalErf
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import kscience.kmath.stat.samplers.GaussianSampler
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import kscience.kmath.stat.samplers.NormalizedGaussianSampler
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import kscience.kmath.stat.samplers.ZigguratNormalizedGaussianSampler
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import kotlin.math.*
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public inline class NormalDistribution(public val sampler: GaussianSampler) : UnivariateDistribution<Double> {
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@ -1,4 +1,4 @@
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package kscience.kmath.prob.internal
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package kscience.kmath.stat.internal
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import kotlin.math.abs
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@ -1,4 +1,4 @@
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package kscience.kmath.prob.internal
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package kscience.kmath.stat.internal
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import kotlin.math.*
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@ -1,4 +1,4 @@
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package kscience.kmath.prob.internal
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package kscience.kmath.stat.internal
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import kotlin.math.ln
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import kotlin.math.min
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@ -1,10 +1,10 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.prob.internal.InternalUtils
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kscience.kmath.stat.internal.InternalUtils
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import kotlin.math.ln
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import kotlin.math.pow
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@ -1,10 +1,10 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.prob.next
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kscience.kmath.stat.next
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import kotlin.math.*
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/**
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@ -1,10 +1,10 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.prob.internal.InternalUtils
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kscience.kmath.stat.internal.InternalUtils
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import kotlin.math.ceil
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import kotlin.math.max
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import kotlin.math.min
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8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/BoxMullerNormalizedGaussianSampler.kt
8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/BoxMullerNormalizedGaussianSampler.kt
@ -1,9 +1,9 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kotlin.math.*
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/**
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@ -1,9 +1,9 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.chains.map
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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/**
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* Sampling from a Gaussian distribution with given mean and standard deviation.
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@ -1,9 +1,9 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kotlin.math.exp
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/**
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@ -1,12 +1,12 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.chains.ConstantChain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.prob.internal.InternalUtils
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import kscience.kmath.prob.next
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kscience.kmath.stat.internal.InternalUtils
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import kscience.kmath.stat.next
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import kotlin.math.*
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/**
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8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/MarsagliaNormalizedGaussianSampler.kt
8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/MarsagliaNormalizedGaussianSampler.kt
@ -1,9 +1,9 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kotlin.math.ln
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import kotlin.math.sqrt
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@ -1,6 +1,6 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.prob.Sampler
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import kscience.kmath.stat.Sampler
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/**
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* Marker interface for a sampler that generates values from an N(0,1)
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@ -1,8 +1,8 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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/**
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* Sampler for the Poisson distribution.
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@ -1,9 +1,9 @@
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kotlin.math.ceil
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import kotlin.math.exp
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8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/ZigguratNormalizedGaussianSampler.kt
8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/ZigguratNormalizedGaussianSampler.kt
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package kscience.kmath.prob.samplers
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package kscience.kmath.stat.samplers
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import kscience.kmath.chains.Chain
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import kscience.kmath.prob.RandomGenerator
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import kscience.kmath.prob.Sampler
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import kscience.kmath.prob.chain
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import kscience.kmath.stat.RandomGenerator
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import kscience.kmath.stat.Sampler
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import kscience.kmath.stat.chain
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import kotlin.math.*
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/**
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@ -3,7 +3,7 @@ package kscience.kmath.stat
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import kotlinx.coroutines.flow.take
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import kotlinx.coroutines.flow.toList
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import kotlinx.coroutines.runBlocking
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import kscience.kmath.prob.samplers.GaussianSampler
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import kscience.kmath.stat.samplers.GaussianSampler
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import org.junit.jupiter.api.Assertions
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import org.junit.jupiter.api.Test
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