Implemented fork for default random generator

This commit is contained in:
Alexander Nozik 2019-06-16 14:36:05 +03:00
parent 9c239ebfbd
commit 9efc6da74a
6 changed files with 52 additions and 49 deletions

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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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@ -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)
@ -14,3 +13,8 @@ class RandomChain<out R>(val generator: RandomGenerator, private val gen: suspen
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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@ -1,20 +0,0 @@
package scientifik.kmath.prob
import kotlinx.atomicfu.atomic
import kotlin.random.Random
class CountingRandomWrapper(val seed: Long) : RandomGenerator {
private val counter = atomic(0)
private val random = Random(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 = random.nextBytes(size)
override fun fork(): RandomGenerator = CountingRandomWrapper(seed + counter.addAndGet(10))
}

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@ -8,7 +8,7 @@ import kotlin.coroutines.coroutineContext
/**
* A scope for a monte-carlo simulation or multi-coroutine random number generation
*/
class MCScope(val coroutineContext: CoroutineContext, val random: RandomGenerator)
class MCScope(override val coroutineContext: CoroutineContext, val random: RandomGenerator): CoroutineScope
/**
* Launches a supervised Monte-Carlo scope

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@ -11,7 +11,7 @@ data class RandomResult(val branch: String, val order: Int, val value: Int)
typealias ATest = suspend CoroutineScope.() -> Set<RandomResult>
class MCScopeTest {
val test: ATest = {
val simpleTest: ATest = {
mc(1111) {
val res = Collections.synchronizedSet(HashSet<RandomResult>())
@ -39,7 +39,7 @@ class MCScopeTest {
}
}
val test2: ATest = {
val testWithJoin: ATest = {
mc(1111) {
val res = Collections.synchronizedSet(HashSet<RandomResult>())
@ -48,14 +48,11 @@ class MCScopeTest {
delay(10)
res.add(RandomResult("first", it, random.nextInt()))
}
launch {
"empty fork"
}
}
launch {
repeat(10) {
delay(10)
if(it == 4) job.join()
if (it == 4) job.join()
res.add(RandomResult("second", it, random.nextInt()))
}
}
@ -65,19 +62,24 @@ class MCScopeTest {
}
@Test
fun testParallel() {
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.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() {
val res1 = runBlocking(Dispatchers.Default) { test2() }
val res2 = runBlocking(newSingleThreadContext("test")) { test2() }
assertEquals(res1, res2)
compareResult(testWithJoin)
}
}