DoubleBuffer generator was moved to DoubleBuffer file and factory fun… #485

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apomytkina wants to merge 3 commits from apomytkina/hse_fix into dev
11 changed files with 115 additions and 43 deletions

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@ -167,9 +167,9 @@ public object MstLogicAlgebra : LogicAlgebra<MST> {
override fun bindSymbolOrNull(value: String): MST = super.bindSymbolOrNull(value) ?: StringSymbol(value)
override fun const(boolean: Boolean): Symbol = if (boolean) {
LogicAlgebra.TRUE
BinaryLogic.TRUE
} else {
LogicAlgebra.FALSE
BinaryLogic.FALSE
}
override fun MST.not(): MST = MST.Unary(Boolean::not.name, this)

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@ -0,0 +1,36 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.operations
import space.kscience.kmath.expressions.Symbol
import space.kscience.kmath.expressions.symbol
interface BinaryLogic<T : Any> {
/**
* Logic 'not'
*/
public operator fun T.not(): T
/**
* Logic 'and'
*/
public infix fun T.and(other: T): T
/**
* Logic 'or'
*/
public infix fun T.or(other: T): T
/**
* Logic 'xor'
*/
public infix fun T.xor(other: T): T
companion object {
public val TRUE: Symbol by symbol
public val FALSE: Symbol by symbol
}
}

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@ -5,16 +5,13 @@
package space.kscience.kmath.operations
import space.kscience.kmath.expressions.Symbol
import space.kscience.kmath.expressions.symbol
import space.kscience.kmath.misc.UnstableKMathAPI
/**
* An algebra for generic boolean logic
*/
@UnstableKMathAPI
public interface LogicAlgebra<T : Any> : Algebra<T> {
public interface LogicAlgebra<T : Any> : Algebra<T>, BinaryLogic<T> {
/**
* Represent constant [Boolean] as [T]
*/
@ -38,32 +35,6 @@ public interface LogicAlgebra<T : Any> : Algebra<T> {
override fun binaryOperationFunction(operation: String): (left: T, right: T) -> T = { l, r ->
binaryOperation(operation, l, r)
}
/**
* Logic 'not'
*/
public operator fun T.not(): T
/**
* Logic 'and'
*/
public infix fun T.and(other: T): T
/**
* Logic 'or'
*/
public infix fun T.or(other: T): T
/**
* Logic 'xor'
*/
public infix fun T.xor(other: T): T
public companion object {
public val TRUE: Symbol by symbol
public val FALSE: Symbol by symbol
}
}
/**

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@ -6,6 +6,7 @@
package space.kscience.kmath.structures
import kotlin.jvm.JvmInline
import kotlin.random.Random.Default.nextDouble
/**
* Specialized [MutableBuffer] implementation over [DoubleArray].
@ -42,6 +43,11 @@ public value class DoubleBuffer(public val array: DoubleArray) : MutableBuffer<D
*/
public inline fun DoubleBuffer(size: Int, init: (Int) -> Double): DoubleBuffer = DoubleBuffer(DoubleArray(size) { init(it) })
/**
* A chunk of doubles of given [size].
*/
public fun nextDoubleBuffer(size: Int): DoubleBuffer = DoubleBuffer(size) { nextDouble() }
/**
* Returns a new [DoubleBuffer] of given elements.
*/

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@ -12,6 +12,7 @@ import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.stat.RandomGenerator
import space.kscience.kmath.stat.nextBuffer
import space.kscience.kmath.structures.nextDoubleBuffer
import kotlin.native.concurrent.ThreadLocal
import kotlin.test.Test
import kotlin.test.assertEquals
@ -35,7 +36,7 @@ internal class UniformHistogram1DTest {
@Test
fun rebinDown() = runTest {
val h1 = Histogram.uniform1D(DoubleField, 0.01).produce(generator.nextDoubleBuffer(10000))
val h1 = Histogram.uniform1D(DoubleField, 0.01).produce(nextDoubleBuffer(10000))
val h2 = Histogram.uniform1D(DoubleField,0.03).produceFrom(h1)
assertEquals(10000, h2.bins.sumOf { it.binValue }.toInt())
@ -43,7 +44,7 @@ internal class UniformHistogram1DTest {
@Test
fun rebinUp() = runTest {
val h1 = Histogram.uniform1D(DoubleField, 0.03).produce(generator.nextDoubleBuffer(10000))
val h1 = Histogram.uniform1D(DoubleField, 0.03).produce(nextDoubleBuffer(10000))
val h2 = Histogram.uniform1D(DoubleField,0.01).produceFrom(h1)
assertEquals(10000, h2.bins.sumOf { it.binValue }.toInt())

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@ -8,3 +8,13 @@ package space.kscience.kmath.nd4j
import space.kscience.kmath.misc.toIntExact
internal fun LongArray.toIntArray(): IntArray = IntArray(size) { this[it].toIntExact() }
internal fun LongArray.linspace(start: Long, stop: Long) = Array(this.size) {
start + it * ((stop - start) / (this.size - 1))
}
internal fun LongArray.zeros() = Array(this.size) { 0 }
internal fun LongArray.ones() = Array(this.size) { 1 }
internal fun repeat(number: Long, size: Int) = LongArray(size) { number }

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@ -0,0 +1,43 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.nd4j
import org.junit.jupiter.api.Test
import kotlin.test.assertEquals
class ArraysTest {
@Test
fun checkLinspaceBuilder() {
val array = LongArray(3).linspace(15, 22)
assertEquals(array[0], 15)
assertEquals(array[1], 18)
assertEquals(array[2], 21)
}
@Test
fun checkZerosBuilder() {
val array = LongArray(3).zeros()
assertEquals(array[0], 0)
assertEquals(array[1], 0)
assertEquals(array[2], 0)
}
@Test
fun checkOnesBuilder() {
val array = LongArray(3).ones()
assertEquals(array[0], 1)
assertEquals(array[1], 1)
assertEquals(array[2], 1)
}
@Test
fun checkRepeatBuilder() {
val array = repeat(5, 3)
assertEquals(array[0], 5)
assertEquals(array[1], 5)
assertEquals(array[2], 5)
}
}

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@ -8,6 +8,7 @@ package space.kscience.kmath.samplers
import space.kscience.kmath.chains.BlockingDoubleChain
import space.kscience.kmath.stat.RandomGenerator
import space.kscience.kmath.structures.DoubleBuffer
import space.kscience.kmath.structures.nextDoubleBuffer
import kotlin.math.*
/**
@ -23,8 +24,8 @@ public object BoxMullerSampler : NormalizedGaussianSampler {
var state = Double.NaN
override fun nextBufferBlocking(size: Int): DoubleBuffer {
val xs = generator.nextDoubleBuffer(size)
val ys = generator.nextDoubleBuffer(size)
val xs = nextDoubleBuffer(size)
val ys = nextDoubleBuffer(size)
return DoubleBuffer(size) { index ->
if (state.isNaN()) {

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@ -8,6 +8,7 @@ package space.kscience.kmath.stat
import space.kscience.kmath.chains.BlockingDoubleChain
import space.kscience.kmath.chains.Chain
import space.kscience.kmath.structures.DoubleBuffer
import space.kscience.kmath.structures.nextDoubleBuffer
/**
* A possibly stateful chain producing random values.
@ -31,7 +32,7 @@ public fun <R> RandomGenerator.chain(generator: suspend RandomGenerator.() -> R)
* A type-specific double chunk random chain
*/
public class UniformDoubleChain(public val generator: RandomGenerator) : BlockingDoubleChain {
override fun nextBufferBlocking(size: Int): DoubleBuffer = generator.nextDoubleBuffer(size)
override fun nextBufferBlocking(size: Int): DoubleBuffer = nextDoubleBuffer(size)
override suspend fun nextBuffer(size: Int): DoubleBuffer = nextBufferBlocking(size)
override suspend fun fork(): UniformDoubleChain = UniformDoubleChain(generator.fork())

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@ -22,11 +22,6 @@ public interface RandomGenerator {
*/
public fun nextDouble(): Double
/**
* A chunk of doubles of given [size].
*/
public fun nextDoubleBuffer(size: Int): DoubleBuffer = DoubleBuffer(size) { nextDouble() }
/**
* Gets the next random `Int` from the random number generator.
*

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@ -20,4 +20,12 @@ public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.sin(
public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.cos(
arg: StructureND<T>,
): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.cos(it) }
): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.cos(it) }
public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.tan(
arg: StructureND<T>,
): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.tan(it) }
public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.abs(
arg: StructureND<T>,
): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.abs(it) }