Random demo

build.gradle.kts

@@ -1,4 +1,4 @@
-val kmathVersion by extra("0.1.2")
+val kmathVersion by extra("0.1.3-dev-1")
 
 allprojects {
     repositories {

doc/nd-structure.md

@@ -14,7 +14,7 @@ Let us consider following contexts:
     // specialized nd-field for Double. It works as generic Double field as well
     val specializedField = NDField.real(dim, dim)
     //A generic boxing field. It should be used for objects, not primitives.
-    val genericField = NDField.buffered(intArrayOf(dim, dim), RealField)
+    val genericField = NDField.buffered(RealField, dim, dim)
 ```
 Now let us perform several tests and see which implementation is best suited for each case:
 

examples/src/benchmarks/kotlin/scientifik/kmath/structures/NDFieldBenchmark.kt

@@ -53,6 +53,6 @@ class NDFieldBenchmark {
 
         val bufferedField = NDField.auto(RealField, dim, dim)
         val specializedField = NDField.real(dim, dim)
-        val genericField = NDField.buffered(intArrayOf(dim, dim), RealField)
+        val genericField = NDField.buffered(RealField, dim, dim)
     }
 }

examples/src/main/kotlin/scientifik/kmath/commons/prob/DistributionDemo.kt

@@ -1,11 +1,31 @@
 package scientifik.kmath.commons.prob
 
-import kotlinx.coroutines.flow.take
+import kotlinx.coroutines.runBlocking
-import scientifik.kmath.chains.flow
+import scientifik.kmath.chains.Chain
+import scientifik.kmath.chains.StatefulChain
 import scientifik.kmath.prob.Distribution
 import scientifik.kmath.prob.RandomGenerator
 
+data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
+
+fun Chain<Double>.mean(): Chain<Double> = StatefulChain(AveragingChainState(), 0.0) {
+    val next = this@mean.next()
+    num++
+    value += next
+    return@StatefulChain value / num
+}
+
+
 fun main() {
     val normal = Distribution.normal()
-    normal.sample(RandomGenerator.default)
+    val chain = normal.sample(RandomGenerator.default).mean()
+
+    runBlocking {
+        repeat(10001) { counter ->
+            val mean = chain.next()
+            if(counter % 1000 ==0){
+                println("[$counter] Average value is $mean")
+            }
+        }
+    }
 }

examples/src/main/kotlin/scientifik/kmath/structures/NDField.kt

@@ -13,7 +13,7 @@ fun main(args: Array<String>) {
     // specialized nd-field for Double. It works as generic Double field as well
     val specializedField = NDField.real(dim, dim)
     //A generic boxing field. It should be used for objects, not primitives.
-    val genericField = NDField.buffered(intArrayOf(dim, dim), RealField)
+    val genericField = NDField.buffered(RealField, dim, dim)
 
 
     val autoTime = measureTimeMillis {

kmath-commons/src/main/kotlin/scientifik/kmath/commons/prob/CMRandomGeneratorWrapper.kt

@@ -1,8 +1,10 @@
 package scientifik.kmath.commons.prob
 
-import org.apache.commons.math3.random.RandomGenerator
+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: RandomGenerator) : scientifik.kmath.prob.RandomGenerator {
+inline class CMRandomGeneratorWrapper(val generator: CMRandom) : RandomGenerator {
     override fun nextDouble(): Double = generator.nextDouble()
 
     override fun nextInt(): Int = generator.nextInt()
@@ -12,7 +14,15 @@ inline class CMRandomGeneratorWrapper(val generator: RandomGenerator) : scientif
     override fun nextBlock(size: Int): ByteArray = ByteArray(size).apply { generator.nextBytes(this) }
 }
 
-fun RandomGenerator.asKmathGenerator() = CMRandomGeneratorWrapper(this)
+fun CMRandom.asKmathGenerator(): RandomGenerator = CMRandomGeneratorWrapper(this)
 
-fun scientifik.kmath.prob.RandomGenerator.asCMGenerator() =
+fun RandomGenerator.asCMGenerator(): CMRandom =
-    (this as? CMRandomGeneratorWrapper)?.generator ?: TODO("Implement reverse CM wrapper")
+    (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()

kmath-commons/src/main/kotlin/scientifik/kmath/commons/prob/CommonsDistribution.kt

@@ -1,8 +1,6 @@
 package scientifik.kmath.commons.prob
 
 import org.apache.commons.math3.distribution.*
-import scientifik.kmath.chains.Chain
-import scientifik.kmath.chains.SimpleChain
 import scientifik.kmath.prob.Distribution
 import scientifik.kmath.prob.RandomChain
 import scientifik.kmath.prob.RandomGenerator
@@ -38,7 +36,7 @@ class CMIntDistributionWrapper(val builder: (CMRandom?) -> IntegerDistribution)
 }
 
 
-fun Distribution.Companion.normal(mean: Double, sigma: Double): UnivariateDistribution<Double> =
+fun Distribution.Companion.normal(mean: Double = 0.0, sigma: Double = 1.0): UnivariateDistribution<Double> =
     CMRealDistributionWrapper { generator -> NormalDistribution(generator, mean, sigma) }
 
 fun Distribution.Companion.poisson(mean: Double): UnivariateDistribution<Int> = CMIntDistributionWrapper { generator ->

kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/NDAlgebra.kt

@@ -1,9 +1,9 @@
 package scientifik.kmath.structures
 
+import scientifik.kmath.operations.Complex
 import scientifik.kmath.operations.Field
 import scientifik.kmath.operations.Ring
 import scientifik.kmath.operations.Space
-import kotlin.jvm.JvmName
 
 
 /**
@@ -77,6 +77,7 @@ interface NDSpace<T, S : Space<T>, N : NDStructure<T>> : Space<N>, NDAlgebra<T,
 
     //TODO move to extensions after KEEP-176
     operator fun N.plus(arg: T) = map(this) { value -> add(arg, value) }
+
     operator fun N.minus(arg: T) = map(this) { value -> add(arg, -value) }
 
     operator fun T.plus(arg: N) = map(arg) { value -> add(this@plus, value) }
@@ -95,6 +96,7 @@ interface NDRing<T, R : Ring<T>, N : NDStructure<T>> : Ring<N>, NDSpace<T, R, N>
 
     //TODO move to extensions after KEEP-176
     operator fun N.times(arg: T) = map(this) { value -> multiply(arg, value) }
+
     operator fun T.times(arg: N) = map(arg) { value -> multiply(this@times, value) }
 }
 
@@ -115,6 +117,7 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F,
 
     //TODO move to extensions after KEEP-176
     operator fun N.div(arg: T) = map(this) { value -> divide(arg, value) }
+
     operator fun T.div(arg: N) = map(arg) { divide(it, this@div) }
 
     companion object {
@@ -130,11 +133,10 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F,
          * Create a nd-field with boxing generic buffer
          */
         fun <T : Any, F : Field<T>> buffered(
-            shape: IntArray,
             field: F,
+            vararg shape: Int,
             bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
-        ) =
+        ) = BoxingNDField(shape, field, bufferFactory)
-            BoxingNDField(shape, field, bufferFactory)
 
         /**
          * Create a most suitable implementation for nd-field using reified class.
@@ -143,6 +145,7 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F,
         inline fun <reified T : Any, F : Field<T>> auto(field: F, vararg shape: Int): BufferedNDField<T, F> =
             when {
                 T::class == Double::class -> real(*shape) as BufferedNDField<T, F>
+                T::class == Complex::class -> complex(*shape) as BufferedNDField<T, F>
                 else -> BoxingNDField(shape, field, Buffer.Companion::auto)
             }
     }

kmath-prob/src/commonMain/kotlin/scientifik/kmath/prob/RandomGenerator.kt

@@ -8,4 +8,6 @@ interface RandomGenerator {
     fun nextInt(): Int
     fun nextLong(): Long
     fun nextBlock(size: Int): ByteArray
+
+    companion object
 }