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Implement Commons RNG-like samplers in kmath-prob module for Multiplatform #164

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CommanderTvis merged 44 commits from feature/mp-samplers into dev 2021-03-31 09:25:44 +03:00
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20 changed files with 71 additions and 76 deletions
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8
examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionBenchmark.kt
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@ -3,10 +3,10 @@ package kscience.kmath.commons.prob
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.runBlocking
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.blocking
import kscience.kmath.prob.fromSource
import kscience.kmath.prob.samplers.GaussianSampler
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.blocking
import kscience.kmath.stat.fromSource
import kscience.kmath.stat.samplers.GaussianSampler
import org.apache.commons.rng.simple.RandomSource
import java.time.Duration
import java.time.Instant

4
examples/src/main/kotlin/kscience/kmath/commons/prob/DistributionDemo.kt
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@ -3,8 +3,8 @@ package kscience.kmath.commons.prob
import kotlinx.coroutines.runBlocking
import kscience.kmath.chains.Chain
import kscience.kmath.chains.collectWithState
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.samplers.ZigguratNormalizedGaussianSampler
private data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)

15
kmath-commons/src/test/kotlin/kscience/kmath/commons/optimization/OptimizeTest.kt
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@ -1,11 +1,11 @@
package kscience.kmath.commons.optimization
import kotlinx.coroutines.runBlocking
import kscience.kmath.commons.expressions.DerivativeStructureExpression
import kscience.kmath.expressions.symbol
import kscience.kmath.stat.Distribution
import kscience.kmath.stat.Fitting
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.normal
import kscience.kmath.stat.distributions.NormalDistribution
import org.junit.jupiter.api.Test
import kotlin.math.pow
@ -39,20 +39,15 @@ internal class OptimizeTest {
}
@Test
fun testCmFit() {
fun testCmFit() = runBlocking {
val a by symbol
val b by symbol
val c by symbol
val sigma = 1.0
val generator = Distribution.normal(0.0, sigma)
val generator = NormalDistribution(0.0, sigma)
val chain = generator.sample(RandomGenerator.default(112667))
val x = (1..100).map(Int::toDouble)
val y = x.map {
it.pow(2) + it + 1 + chain.nextDouble()
}
val y = x.map { it.pow(2) + it + 1.0 + chain.next() }
val yErr = List(x.size) { sigma }
val chi2 = Fitting.chiSquared(x, y, yErr) { x1 ->

14
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/distributions/NormalDistribution.kt
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@ -1,12 +1,12 @@
package kscience.kmath.prob.distributions
package kscience.kmath.stat.distributions
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.UnivariateDistribution
import kscience.kmath.prob.internal.InternalErf
import kscience.kmath.prob.samplers.GaussianSampler
import kscience.kmath.prob.samplers.NormalizedGaussianSampler
import kscience.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.UnivariateDistribution
import kscience.kmath.stat.internal.InternalErf
import kscience.kmath.stat.samplers.GaussianSampler
import kscience.kmath.stat.samplers.NormalizedGaussianSampler
import kscience.kmath.stat.samplers.ZigguratNormalizedGaussianSampler
import kotlin.math.*
public inline class NormalDistribution(public val sampler: GaussianSampler) : UnivariateDistribution<Double> {

2
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/internal/InternalErf.kt
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@ -1,4 +1,4 @@
package kscience.kmath.prob.internal
package kscience.kmath.stat.internal
import kotlin.math.abs

2
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/internal/InternalGamma.kt
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@ -1,4 +1,4 @@
package kscience.kmath.prob.internal
package kscience.kmath.stat.internal
import kotlin.math.*

2
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/internal/InternalUtils.kt
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@ -1,4 +1,4 @@
package kscience.kmath.prob.internal
package kscience.kmath.stat.internal
import kotlin.math.ln
import kotlin.math.min

10
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/AhrensDieterExponentialSampler.kt
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@ -1,10 +1,10 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.prob.internal.InternalUtils
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kscience.kmath.stat.internal.InternalUtils
import kotlin.math.ln
import kotlin.math.pow

10
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/AhrensDieterMarsagliaTsangGammaSampler.kt
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@ -1,10 +1,10 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.prob.next
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kscience.kmath.stat.next
import kotlin.math.*
/**

10
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/AliasMethodDiscreteSampler.kt
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@ -1,10 +1,10 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.prob.internal.InternalUtils
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kscience.kmath.stat.internal.InternalUtils
import kotlin.math.ceil
import kotlin.math.max
import kotlin.math.min

8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/BoxMullerNormalizedGaussianSampler.kt
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@ -1,9 +1,9 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kotlin.math.*
/**

6
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/GaussianSampler.kt
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@ -1,9 +1,9 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.chains.map
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
/**
* Sampling from a Gaussian distribution with given mean and standard deviation.

8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/KempSmallMeanPoissonSampler.kt
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@ -1,9 +1,9 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kotlin.math.exp
/**

12
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/LargeMeanPoissonSampler.kt
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@ -1,12 +1,12 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.chains.ConstantChain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.prob.internal.InternalUtils
import kscience.kmath.prob.next
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kscience.kmath.stat.internal.InternalUtils
import kscience.kmath.stat.next
import kotlin.math.*
/**

8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/MarsagliaNormalizedGaussianSampler.kt
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@ -1,9 +1,9 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kotlin.math.ln
import kotlin.math.sqrt

4
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/NormalizedGaussianSampler.kt
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@ -1,6 +1,6 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.prob.Sampler
import kscience.kmath.stat.Sampler
/**
* Marker interface for a sampler that generates values from an N(0,1)

6
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/PoissonSampler.kt
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@ -1,8 +1,8 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
/**
* Sampler for the Poisson distribution.

8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/SmallMeanPoissonSampler.kt
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@ -1,9 +1,9 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kotlin.math.ceil
import kotlin.math.exp

8
kmath-stat/src/commonMain/kotlin/kscience/kmath/stat/samplers/ZigguratNormalizedGaussianSampler.kt
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@ -1,9 +1,9 @@
package kscience.kmath.prob.samplers
package kscience.kmath.stat.samplers
import kscience.kmath.chains.Chain
import kscience.kmath.prob.RandomGenerator
import kscience.kmath.prob.Sampler
import kscience.kmath.prob.chain
import kscience.kmath.stat.RandomGenerator
import kscience.kmath.stat.Sampler
import kscience.kmath.stat.chain
import kotlin.math.*
/**

2
kmath-stat/src/jvmTest/kotlin/kscience/kmath/stat/CommonsDistributionsTest.kt
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@ -3,7 +3,7 @@ package kscience.kmath.stat
import kotlinx.coroutines.flow.take
import kotlinx.coroutines.flow.toList
import kotlinx.coroutines.runBlocking
import kscience.kmath.prob.samplers.GaussianSampler
import kscience.kmath.stat.samplers.GaussianSampler
import org.junit.jupiter.api.Assertions
import org.junit.jupiter.api.Test