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apomytkina
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0e8eb44670 | ||
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2cdaa6989c | ||
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d9b719fe5a |
@ -167,9 +167,9 @@ public object MstLogicAlgebra : LogicAlgebra<MST> {
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override fun bindSymbolOrNull(value: String): MST = super.bindSymbolOrNull(value) ?: StringSymbol(value)
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override fun const(boolean: Boolean): Symbol = if (boolean) {
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LogicAlgebra.TRUE
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BinaryLogic.TRUE
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} else {
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LogicAlgebra.FALSE
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BinaryLogic.FALSE
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}
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override fun MST.not(): MST = MST.Unary(Boolean::not.name, this)
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@ -0,0 +1,36 @@
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/*
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* Copyright 2018-2021 KMath contributors.
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* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
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*/
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package space.kscience.kmath.operations
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import space.kscience.kmath.expressions.Symbol
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import space.kscience.kmath.expressions.symbol
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interface BinaryLogic<T : Any> {
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/**
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* Logic 'not'
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*/
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public operator fun T.not(): T
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/**
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* Logic 'and'
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*/
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public infix fun T.and(other: T): T
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/**
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* Logic 'or'
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*/
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public infix fun T.or(other: T): T
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/**
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* Logic 'xor'
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*/
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public infix fun T.xor(other: T): T
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companion object {
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public val TRUE: Symbol by symbol
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public val FALSE: Symbol by symbol
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}
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}
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@ -5,16 +5,13 @@
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package space.kscience.kmath.operations
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import space.kscience.kmath.expressions.Symbol
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import space.kscience.kmath.expressions.symbol
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import space.kscience.kmath.misc.UnstableKMathAPI
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/**
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* An algebra for generic boolean logic
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*/
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@UnstableKMathAPI
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public interface LogicAlgebra<T : Any> : Algebra<T> {
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public interface LogicAlgebra<T : Any> : Algebra<T>, BinaryLogic<T> {
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/**
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* Represent constant [Boolean] as [T]
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*/
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@ -38,32 +35,6 @@ public interface LogicAlgebra<T : Any> : Algebra<T> {
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override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = { l, r ->
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binaryOperation(operation, l, r)
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}
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/**
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* Logic 'not'
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*/
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public operator fun T.not(): T
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/**
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* Logic 'and'
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*/
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public infix fun T.and(other: T): T
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/**
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* Logic 'or'
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*/
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public infix fun T.or(other: T): T
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/**
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* Logic 'xor'
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*/
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public infix fun T.xor(other: T): T
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public companion object {
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public val TRUE: Symbol by symbol
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public val FALSE: Symbol by symbol
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}
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}
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/**
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@ -6,6 +6,7 @@
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package space.kscience.kmath.structures
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import kotlin.jvm.JvmInline
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import kotlin.random.Random.Default.nextDouble
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/**
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* Specialized [MutableBuffer] implementation over [DoubleArray].
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@ -42,6 +43,11 @@ public value class DoubleBuffer(public val array: DoubleArray) : MutableBuffer<D
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*/
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public inline fun DoubleBuffer(size: Int, init: (Int) -> Double): DoubleBuffer = DoubleBuffer(DoubleArray(size) { init(it) })
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/**
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* A chunk of doubles of given [size].
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*/
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public fun nextDoubleBuffer(size: Int): DoubleBuffer = DoubleBuffer(size) { nextDouble() }
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/**
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* Returns a new [DoubleBuffer] of given elements.
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*/
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@ -12,6 +12,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.operations.DoubleField
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import space.kscience.kmath.stat.RandomGenerator
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import space.kscience.kmath.stat.nextBuffer
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import space.kscience.kmath.structures.nextDoubleBuffer
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import kotlin.native.concurrent.ThreadLocal
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import kotlin.test.Test
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import kotlin.test.assertEquals
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@ -35,7 +36,7 @@ internal class UniformHistogram1DTest {
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@Test
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fun rebinDown() = runTest {
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val h1 = Histogram.uniform1D(DoubleField, 0.01).produce(generator.nextDoubleBuffer(10000))
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val h1 = Histogram.uniform1D(DoubleField, 0.01).produce(nextDoubleBuffer(10000))
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val h2 = Histogram.uniform1D(DoubleField,0.03).produceFrom(h1)
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assertEquals(10000, h2.bins.sumOf { it.binValue }.toInt())
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@ -43,7 +44,7 @@ internal class UniformHistogram1DTest {
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@Test
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fun rebinUp() = runTest {
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val h1 = Histogram.uniform1D(DoubleField, 0.03).produce(generator.nextDoubleBuffer(10000))
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val h1 = Histogram.uniform1D(DoubleField, 0.03).produce(nextDoubleBuffer(10000))
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val h2 = Histogram.uniform1D(DoubleField,0.01).produceFrom(h1)
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assertEquals(10000, h2.bins.sumOf { it.binValue }.toInt())
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@ -8,3 +8,13 @@ package space.kscience.kmath.nd4j
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import space.kscience.kmath.misc.toIntExact
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internal fun LongArray.toIntArray(): IntArray = IntArray(size) { this[it].toIntExact() }
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internal fun LongArray.linspace(start: Long, stop: Long) = Array(this.size) {
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start + it * ((stop - start) / (this.size - 1))
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}
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internal fun LongArray.zeros() = Array(this.size) { 0 }
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internal fun LongArray.ones() = Array(this.size) { 1 }
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internal fun repeat(number: Long, size: Int) = LongArray(size) { number }
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@ -0,0 +1,43 @@
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/*
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* Copyright 2018-2021 KMath contributors.
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* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
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*/
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package space.kscience.kmath.nd4j
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import org.junit.jupiter.api.Test
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import kotlin.test.assertEquals
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class ArraysTest {
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@Test
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fun checkLinspaceBuilder() {
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val array = LongArray(3).linspace(15, 22)
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assertEquals(array[0], 15)
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assertEquals(array[1], 18)
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assertEquals(array[2], 21)
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}
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@Test
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fun checkZerosBuilder() {
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val array = LongArray(3).zeros()
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assertEquals(array[0], 0)
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assertEquals(array[1], 0)
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assertEquals(array[2], 0)
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}
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@Test
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fun checkOnesBuilder() {
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val array = LongArray(3).ones()
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assertEquals(array[0], 1)
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assertEquals(array[1], 1)
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assertEquals(array[2], 1)
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}
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@Test
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fun checkRepeatBuilder() {
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val array = repeat(5, 3)
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assertEquals(array[0], 5)
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assertEquals(array[1], 5)
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assertEquals(array[2], 5)
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}
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}
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@ -8,6 +8,7 @@ package space.kscience.kmath.samplers
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import space.kscience.kmath.chains.BlockingDoubleChain
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import space.kscience.kmath.stat.RandomGenerator
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import space.kscience.kmath.structures.DoubleBuffer
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import space.kscience.kmath.structures.nextDoubleBuffer
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import kotlin.math.*
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/**
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@ -23,8 +24,8 @@ public object BoxMullerSampler : NormalizedGaussianSampler {
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var state = Double.NaN
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override fun nextBufferBlocking(size: Int): DoubleBuffer {
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val xs = generator.nextDoubleBuffer(size)
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val ys = generator.nextDoubleBuffer(size)
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val xs = nextDoubleBuffer(size)
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val ys = nextDoubleBuffer(size)
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return DoubleBuffer(size) { index ->
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if (state.isNaN()) {
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@ -8,6 +8,7 @@ package space.kscience.kmath.stat
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import space.kscience.kmath.chains.BlockingDoubleChain
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import space.kscience.kmath.chains.Chain
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import space.kscience.kmath.structures.DoubleBuffer
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import space.kscience.kmath.structures.nextDoubleBuffer
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/**
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* A possibly stateful chain producing random values.
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@ -31,7 +32,7 @@ public fun <R> RandomGenerator.chain(generator: suspend RandomGenerator.() -> R)
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* A type-specific double chunk random chain
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*/
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public class UniformDoubleChain(public val generator: RandomGenerator) : BlockingDoubleChain {
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override fun nextBufferBlocking(size: Int): DoubleBuffer = generator.nextDoubleBuffer(size)
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override fun nextBufferBlocking(size: Int): DoubleBuffer = nextDoubleBuffer(size)
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override suspend fun nextBuffer(size: Int): DoubleBuffer = nextBufferBlocking(size)
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override suspend fun fork(): UniformDoubleChain = UniformDoubleChain(generator.fork())
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@ -22,11 +22,6 @@ public interface RandomGenerator {
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*/
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public fun nextDouble(): Double
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/**
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* A chunk of doubles of given [size].
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*/
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public fun nextDoubleBuffer(size: Int): DoubleBuffer = DoubleBuffer(size) { nextDouble() }
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/**
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* Gets the next random `Int` from the random number generator.
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*
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@ -21,3 +21,11 @@ public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.sin(
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public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.cos(
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arg: StructureND<T>,
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): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.cos(it) }
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public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.tan(
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arg: StructureND<T>,
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): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.tan(it) }
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public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.abs(
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arg: StructureND<T>,
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): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.abs(it) }
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