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10 changed files with 199 additions and 24 deletions

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@ -8,7 +8,7 @@ fun main(args: Array<String>) {
val dim = 1000
val n = 1000
// automatically build context most suited for given type.
// automatically build coroutineContext most suited for given type.
val autoField = NDField.auto(RealField, dim, dim)
// specialized nd-field for Double. It works as generic Double field as well
val specializedField = NDField.real(dim, dim)

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@ -111,7 +111,7 @@ fun DiffExpression.derivative(vararg orders: Pair<String, Int>) = derivative(map
fun DiffExpression.derivative(name: String) = derivative(name to 1)
/**
* A context for [DiffExpression] (not to be confused with [DerivativeStructure])
* A coroutineContext for [DiffExpression] (not to be confused with [DerivativeStructure])
*/
object DiffExpressionContext : ExpressionContext<Double>, Field<DiffExpression> {
override fun variable(name: String, default: Double?) =

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@ -4,7 +4,9 @@ import org.apache.commons.math3.random.JDKRandomGenerator
import scientifik.kmath.prob.RandomGenerator
import org.apache.commons.math3.random.RandomGenerator as CMRandom
inline class CMRandomGeneratorWrapper(val generator: CMRandom) : RandomGenerator {
class CMRandomGeneratorWrapper(seed: Long?, val builder: (Long?) -> CMRandom) : RandomGenerator {
val generator = builder(seed)
override fun nextDouble(): Double = generator.nextDouble()
override fun nextInt(): Int = generator.nextInt()
@ -13,20 +15,12 @@ inline class CMRandomGeneratorWrapper(val generator: CMRandom) : RandomGenerator
override fun nextBlock(size: Int): ByteArray = ByteArray(size).apply { generator.nextBytes(this) }
override fun fork(): RandomGenerator {
TODO("not implemented") //To change body of created functions use File | Settings | File Templates.
}
override fun fork(): RandomGenerator = CMRandomGeneratorWrapper(nextLong(), builder)
}
fun CMRandom.asKmathGenerator(): RandomGenerator = CMRandomGeneratorWrapper(this)
fun RandomGenerator.asCMGenerator(): CMRandom =
(this as? CMRandomGeneratorWrapper)?.generator ?: TODO("Implement reverse CM wrapper")
val RandomGenerator.Companion.default: RandomGenerator by lazy { JDKRandomGenerator().asKmathGenerator() }
fun RandomGenerator.Companion.jdk(seed: Int? = null): RandomGenerator = if (seed == null) {
JDKRandomGenerator()
} else {
JDKRandomGenerator(seed)
}.asKmathGenerator()
fun RandomGenerator.Companion.jdk(seed: Long? = null): RandomGenerator =
CMRandomGeneratorWrapper(seed) { JDKRandomGenerator() }

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@ -8,19 +8,19 @@ kotlin.sourceSets {
dependencies {
api(project(":kmath-core"))
api("org.jetbrains.kotlinx:kotlinx-coroutines-core-common:${Versions.coroutinesVersion}")
compileOnly("org.jetbrains.kotlinx:atomicfu-common:${Versions.atomicfuVersion}")
api("org.jetbrains.kotlinx:atomicfu-common:${Versions.atomicfuVersion}")
}
}
jvmMain {
dependencies {
api("org.jetbrains.kotlinx:kotlinx-coroutines-core:${Versions.coroutinesVersion}")
compileOnly("org.jetbrains.kotlinx:atomicfu:${Versions.atomicfuVersion}")
api("org.jetbrains.kotlinx:atomicfu:${Versions.atomicfuVersion}")
}
}
jsMain {
dependencies {
api("org.jetbrains.kotlinx:kotlinx-coroutines-core-js:${Versions.coroutinesVersion}")
compileOnly("org.jetbrains.kotlinx:atomicfu-js:${Versions.atomicfuVersion}")
api("org.jetbrains.kotlinx:atomicfu-js:${Versions.atomicfuVersion}")
}
}
}

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@ -7,19 +7,19 @@ kotlin.sourceSets {
commonMain {
dependencies {
api(project(":kmath-coroutines"))
compileOnly("org.jetbrains.kotlinx:atomicfu-common:${Versions.atomicfuVersion}")
//compileOnly("org.jetbrains.kotlinx:atomicfu-common:${Versions.atomicfuVersion}")
}
}
jvmMain {
dependencies {
// https://mvnrepository.com/artifact/org.apache.commons/commons-rng-simple
//api("org.apache.commons:commons-rng-sampling:1.2")
compileOnly("org.jetbrains.kotlinx:atomicfu:${Versions.atomicfuVersion}")
// compileOnly("org.jetbrains.kotlinx:atomicfu:${Versions.atomicfuVersion}")
}
}
jsMain {
dependencies {
compileOnly("org.jetbrains.kotlinx:atomicfu-js:${Versions.atomicfuVersion}")
// compileOnly("org.jetbrains.kotlinx:atomicfu-js:${Versions.atomicfuVersion}")
}
}

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@ -5,7 +5,6 @@ import scientifik.kmath.chains.Chain
/**
* A possibly stateful chain producing random values.
* TODO make random chain properly fork generator
*/
class RandomChain<out R>(val generator: RandomGenerator, private val gen: suspend RandomGenerator.() -> R) : Chain<R> {
private val atomicValue = atomic<R?>(null)
@ -13,4 +12,9 @@ class RandomChain<out R>(val generator: RandomGenerator, private val gen: suspen
override suspend fun next(): R = generator.gen().also { atomicValue.lazySet(it) }
override fun fork(): Chain<R> = RandomChain(generator.fork(), gen)
}
}
/**
* Create a chain of doubles from generator after forking it so the chain is not affected by operations on generator
*/
fun RandomGenerator.doubles(): Chain<Double> = RandomChain(fork()) { nextDouble() }

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@ -1,5 +1,7 @@
package scientifik.kmath.prob
import kotlin.random.Random
/**
* A basic generator
*/
@ -10,9 +12,30 @@ interface RandomGenerator {
fun nextBlock(size: Int): ByteArray
/**
* Fork the current state of generator
* Create a new generator which is independent from current generator (operations on new generator do not affect this one
* and vise versa). The statistical properties of new generator should be the same as for this one.
* For pseudo-random generator, the fork is keeping the same sequence of numbers for given call order for each run.
*
* The thread safety of this operation is not guaranteed since it could affect the state of the generator.
*/
fun fork(): RandomGenerator
companion object
companion object {
val default by lazy { DefaultGenerator(Random.nextLong()) }
}
}
class DefaultGenerator(seed: Long?) : RandomGenerator {
private val random = seed?.let { Random(it) } ?: Random
override fun nextDouble(): Double = random.nextDouble()
override fun nextInt(): Int = random.nextInt()
override fun nextLong(): Long = random.nextLong()
override fun nextBlock(size: Int): ByteArray = random.nextBytes(size)
override fun fork(): RandomGenerator = DefaultGenerator(nextLong())
}

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@ -0,0 +1,44 @@
package scientifik.kmath.prob
import kotlinx.coroutines.*
import kotlin.coroutines.CoroutineContext
import kotlin.coroutines.EmptyCoroutineContext
import kotlin.coroutines.coroutineContext
/**
* A scope for a monte-carlo simulation or multi-coroutine random number generation
*/
class MCScope(override val coroutineContext: CoroutineContext, val random: RandomGenerator): CoroutineScope
/**
* Launches a supervised Monte-Carlo scope
*/
suspend fun <T> mc(generator: RandomGenerator, block: suspend MCScope.() -> T): T =
MCScope(coroutineContext, generator).block()
suspend fun <T> mc(seed: Long = -1, block: suspend MCScope.() -> T): T =
mc(SplitRandomWrapper(seed), block)
inline fun MCScope.launch(
context: CoroutineContext = EmptyCoroutineContext,
start: CoroutineStart = CoroutineStart.DEFAULT,
crossinline block: suspend MCScope.() -> Unit
): Job {
val newRandom = synchronized(this){random.fork()}
return CoroutineScope(coroutineContext).launch(context, start) {
MCScope(coroutineContext, newRandom).block()
}
}
inline fun <T> MCScope.async(
context: CoroutineContext = EmptyCoroutineContext,
start: CoroutineStart = CoroutineStart.DEFAULT,
crossinline block: suspend MCScope.() -> T
): Deferred<T> {
val newRandom = synchronized(this){random.fork()}
return CoroutineScope(coroutineContext).async(context, start) {
MCScope(coroutineContext, newRandom).block()
}
}

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@ -0,0 +1,25 @@
package scientifik.kmath.prob
import java.util.*
class SplitRandomWrapper(random: SplittableRandom) : RandomGenerator {
var random = random
private set
constructor(seed: Long) : this(SplittableRandom(seed))
override fun nextDouble(): Double = random.nextDouble()
override fun nextInt(): Int = random.nextInt()
override fun nextLong(): Long = random.nextLong()
override fun nextBlock(size: Int): ByteArray = ByteArray(size).also { random.nextBytes(it) }
override fun fork(): RandomGenerator {
synchronized(this) {
return SplitRandomWrapper(random.split()).also { this.random = random.split() }
}
}
}

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@ -0,0 +1,85 @@
package scientifik.kmath.prob
import kotlinx.coroutines.*
import java.util.*
import kotlin.collections.HashSet
import kotlin.test.Test
import kotlin.test.assertEquals
data class RandomResult(val branch: String, val order: Int, val value: Int)
typealias ATest = suspend CoroutineScope.() -> Set<RandomResult>
class MCScopeTest {
val simpleTest: ATest = {
mc(1111) {
val res = Collections.synchronizedSet(HashSet<RandomResult>())
launch {
//println(random)
repeat(10) {
delay(10)
res.add(RandomResult("first", it, random.nextInt()))
}
launch {
"empty fork"
}
}
launch {
//println(random)
repeat(10) {
delay(10)
res.add(RandomResult("second", it, random.nextInt()))
}
}
res
}
}
val testWithJoin: ATest = {
mc(1111) {
val res = Collections.synchronizedSet(HashSet<RandomResult>())
val job = launch {
repeat(10) {
delay(10)
res.add(RandomResult("first", it, random.nextInt()))
}
}
launch {
repeat(10) {
delay(10)
if (it == 4) job.join()
res.add(RandomResult("second", it, random.nextInt()))
}
}
res
}
}
fun compareResult(test: ATest) {
val res1 = runBlocking(Dispatchers.Default) { test() }
val res2 = runBlocking(newSingleThreadContext("test")) { test() }
assertEquals(
res1.find { it.branch == "first" && it.order == 7 }?.value,
res2.find { it.branch == "first" && it.order == 7 }?.value
)
assertEquals(res1, res2)
}
@Test
fun testParallel() {
compareResult(simpleTest)
}
@Test
fun testConditionalJoin() {
compareResult(testWithJoin)
}
}