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

@@ -3,25 +3,24 @@ package scientifik.kmath.commons.prob
 import kotlinx.coroutines.Dispatchers
 import kotlinx.coroutines.async
 import kotlinx.coroutines.runBlocking
-import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
 import org.apache.commons.rng.simple.RandomSource
-import scientifik.kmath.chains.BlockingRealChain
-import scientifik.kmath.prob.*
+import scientifik.kmath.prob.RandomChain
+import scientifik.kmath.prob.RandomGenerator
+import scientifik.kmath.prob.fromSource
 import java.time.Duration
 import java.time.Instant
+import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler as ApacheZigguratNormalizedGaussianSampler
+import scientifik.kmath.prob.samplers.ZigguratNormalizedGaussianSampler as KMathZigguratNormalizedGaussianSampler
 
-
-private suspend fun runChain(): Duration {
+private suspend fun runKMathChained(): Duration {
     val generator = RandomGenerator.fromSource(RandomSource.MT, 123L)
-
-    val normal = Distribution.normal(NormalSamplerMethod.Ziggurat)
-    val chain = normal.sample(generator) as BlockingRealChain
-
+    val normal = KMathZigguratNormalizedGaussianSampler.of()
+    val chain = normal.sample(generator) as RandomChain<Double>
     val startTime = Instant.now()
     var sum = 0.0
-    repeat(10000001) { counter ->
 
-        sum += chain.nextDouble()
+    repeat(10000001) { counter ->
+        sum += chain.next()
 
         if (counter % 100000 == 0) {
             val duration = Duration.between(startTime, Instant.now())
@@ -32,9 +31,9 @@ private suspend fun runChain(): Duration {
     return Duration.between(startTime, Instant.now())
 }
 
-private fun runDirect(): Duration {
-    val provider = RandomSource.create(RandomSource.MT, 123L)
-    val sampler = ZigguratNormalizedGaussianSampler(provider)
+private fun runApacheDirect(): Duration {
+    val rng = RandomSource.create(RandomSource.MT, 123L)
+    val sampler = ApacheZigguratNormalizedGaussianSampler.of<ApacheZigguratNormalizedGaussianSampler>(rng)
     val startTime = Instant.now()
 
     var sum = 0.0
@@ -56,16 +55,9 @@ private fun runDirect(): Duration {
  */
 fun main() {
     runBlocking(Dispatchers.Default) {
-        val chainJob = async {
-            runChain()
-        }
-
-        val directJob = async {
-            runDirect()
-        }
-
-        println("Chain: ${chainJob.await()}")
-        println("Direct: ${directJob.await()}")
+        val chainJob = async { runKMathChained() }
+        val directJob = async { runApacheDirect() }
+        println("KMath Chained: ${chainJob.await()}")
+        println("Apache Direct: ${directJob.await()}")
     }
-
 }

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

@@ -3,9 +3,8 @@ package scientifik.kmath.commons.prob
 import kotlinx.coroutines.runBlocking
 import scientifik.kmath.chains.Chain
 import scientifik.kmath.chains.collectWithState
-import scientifik.kmath.prob.Distribution
 import scientifik.kmath.prob.RandomGenerator
-import scientifik.kmath.prob.normal
+import scientifik.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
 
 data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
 
@@ -18,7 +17,7 @@ fun Chain<Double>.mean(): Chain<Double> = collectWithState(AveragingChainState()
 
 
 fun main() {
-    val normal = Distribution.normal()
+    val normal = ZigguratNormalizedGaussianSampler.of()
     val chain = normal.sample(RandomGenerator.default).mean()
 
     runBlocking {