forked from kscience/kmath
Fix broken demos, add newlines at the end of files
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@ -3,25 +3,24 @@ package scientifik.kmath.commons.prob
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import kotlinx.coroutines.Dispatchers
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import kotlinx.coroutines.Dispatchers
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import kotlinx.coroutines.async
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import kotlinx.coroutines.async
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import kotlinx.coroutines.runBlocking
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import kotlinx.coroutines.runBlocking
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import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
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import org.apache.commons.rng.simple.RandomSource
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import org.apache.commons.rng.simple.RandomSource
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import scientifik.kmath.chains.BlockingRealChain
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import scientifik.kmath.prob.RandomChain
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import scientifik.kmath.prob.*
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import scientifik.kmath.prob.RandomGenerator
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import scientifik.kmath.prob.fromSource
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import java.time.Duration
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import java.time.Duration
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import java.time.Instant
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import java.time.Instant
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import org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler as ApacheZigguratNormalizedGaussianSampler
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import scientifik.kmath.prob.samplers.ZigguratNormalizedGaussianSampler as KMathZigguratNormalizedGaussianSampler
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private suspend fun runKMathChained(): Duration {
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private suspend fun runChain(): Duration {
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val generator = RandomGenerator.fromSource(RandomSource.MT, 123L)
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val generator = RandomGenerator.fromSource(RandomSource.MT, 123L)
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val normal = KMathZigguratNormalizedGaussianSampler.of()
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val normal = Distribution.normal(NormalSamplerMethod.Ziggurat)
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val chain = normal.sample(generator) as RandomChain<Double>
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val chain = normal.sample(generator) as BlockingRealChain
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val startTime = Instant.now()
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val startTime = Instant.now()
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var sum = 0.0
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var sum = 0.0
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repeat(10000001) { counter ->
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sum += chain.nextDouble()
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repeat(10000001) { counter ->
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sum += chain.next()
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if (counter % 100000 == 0) {
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if (counter % 100000 == 0) {
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val duration = Duration.between(startTime, Instant.now())
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val duration = Duration.between(startTime, Instant.now())
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@ -32,9 +31,9 @@ private suspend fun runChain(): Duration {
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return Duration.between(startTime, Instant.now())
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return Duration.between(startTime, Instant.now())
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}
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}
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private fun runDirect(): Duration {
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private fun runApacheDirect(): Duration {
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val provider = RandomSource.create(RandomSource.MT, 123L)
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val rng = RandomSource.create(RandomSource.MT, 123L)
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val sampler = ZigguratNormalizedGaussianSampler(provider)
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val sampler = ApacheZigguratNormalizedGaussianSampler.of<ApacheZigguratNormalizedGaussianSampler>(rng)
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val startTime = Instant.now()
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val startTime = Instant.now()
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var sum = 0.0
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var sum = 0.0
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@ -56,16 +55,9 @@ private fun runDirect(): Duration {
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*/
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*/
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fun main() {
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fun main() {
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runBlocking(Dispatchers.Default) {
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runBlocking(Dispatchers.Default) {
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val chainJob = async {
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val chainJob = async { runKMathChained() }
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runChain()
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val directJob = async { runApacheDirect() }
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println("KMath Chained: ${chainJob.await()}")
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println("Apache Direct: ${directJob.await()}")
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}
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}
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val directJob = async {
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runDirect()
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}
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println("Chain: ${chainJob.await()}")
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println("Direct: ${directJob.await()}")
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}
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}
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}
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@ -3,9 +3,8 @@ package scientifik.kmath.commons.prob
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import kotlinx.coroutines.runBlocking
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import kotlinx.coroutines.runBlocking
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import scientifik.kmath.chains.Chain
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import scientifik.kmath.chains.Chain
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import scientifik.kmath.chains.collectWithState
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import scientifik.kmath.chains.collectWithState
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import scientifik.kmath.prob.Distribution
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import scientifik.kmath.prob.RandomGenerator
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import scientifik.kmath.prob.RandomGenerator
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import scientifik.kmath.prob.normal
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import scientifik.kmath.prob.samplers.ZigguratNormalizedGaussianSampler
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data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
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data class AveragingChainState(var num: Int = 0, var value: Double = 0.0)
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@ -18,7 +17,7 @@ fun Chain<Double>.mean(): Chain<Double> = collectWithState(AveragingChainState()
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fun main() {
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fun main() {
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val normal = Distribution.normal()
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val normal = ZigguratNormalizedGaussianSampler.of()
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val chain = normal.sample(RandomGenerator.default).mean()
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val chain = normal.sample(RandomGenerator.default).mean()
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runBlocking {
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runBlocking {
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