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Dev #127

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altavir merged 214 commits from dev into master 2020-08-11 08:33:21 +03:00
Conversation 0 Commits 214 Files Changed 149 +722 -429
59 changed files with 722 additions and 429 deletions
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9
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/Domain.kt
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@ -3,13 +3,18 @@ package scientifik.kmath.domains
import scientifik.kmath.linear.Point
/**
* A simple geometric domain
* A simple geometric domain.
*
* @param T the type of element of this domain.
*/
interface Domain<T : Any> {
/**
* Checks if the specified point is contained in this domain.
*/
operator fun contains(point: Point<T>): Boolean
/**
* Number of hyperspace dimensions
* Number of hyperspace dimensions.
*/
val dimension: Int
}

3
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/HyperSquareDomain.kt
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@ -42,13 +42,14 @@ class HyperSquareDomain(private val lower: RealBuffer, private val upper: RealBu
override fun getUpperBound(num: Int): Double? = upper[num]
override fun nearestInDomain(point: Point<Double>): Point<Double> {
val res: DoubleArray = DoubleArray(point.size) { i ->
val res = DoubleArray(point.size) { i ->
when {
point[i] < lower[i] -> lower[i]
point[i] > upper[i] -> upper[i]
else -> point[i]
}
}
return RealBuffer(*res)
}

4
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/RealDomain.kt
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@ -22,8 +22,7 @@ import scientifik.kmath.linear.Point
*
* @author Alexander Nozik
*/
interface RealDomain: Domain<Double> {
interface RealDomain : Domain<Double> {
fun nearestInDomain(point: Point<Double>): Point<Double>
/**
@ -61,5 +60,4 @@ interface RealDomain: Domain<Double> {
* @return
*/
fun volume(): Double
}

2
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/UnconstrainedDomain.kt
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@ -18,7 +18,6 @@ package scientifik.kmath.domains
import scientifik.kmath.linear.Point
class UnconstrainedDomain(override val dimension: Int) : RealDomain {
override operator fun contains(point: Point<Double>): Boolean = true
override fun getLowerBound(num: Int, point: Point<Double>): Double? = Double.NEGATIVE_INFINITY
@ -32,5 +31,4 @@ class UnconstrainedDomain(override val dimension: Int) : RealDomain {
override fun nearestInDomain(point: Point<Double>): Point<Double> = point
override fun volume(): Double = Double.POSITIVE_INFINITY
}

3
kmath-core/src/commonMain/kotlin/scientifik/kmath/domains/UnivariateDomain.kt
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@ -4,7 +4,6 @@ import scientifik.kmath.linear.Point
import scientifik.kmath.structures.asBuffer
inline class UnivariateDomain(val range: ClosedFloatingPointRange<Double>) : RealDomain {
operator fun contains(d: Double): Boolean = range.contains(d)
override operator fun contains(point: Point<Double>): Boolean {
@ -15,7 +14,7 @@ inline class UnivariateDomain(val range: ClosedFloatingPointRange<Double>) : Rea
override fun nearestInDomain(point: Point<Double>): Point<Double> {
require(point.size == 1)
val value = point[0]
return when{
return when {
value in range -> point
value >= range.endInclusive -> doubleArrayOf(range.endInclusive).asBuffer()
else -> doubleArrayOf(range.start).asBuffer()

5
kmath-core/src/commonMain/kotlin/scientifik/kmath/expressions/Expression.kt
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@ -14,9 +14,10 @@ interface Expression<T> {
/**
* Create simple lazily evaluated expression inside given algebra
*/
fun <T> Algebra<T>.expression(block: Algebra<T>.(arguments: Map<String, T>) -> T): Expression<T> = object: Expression<T> {
fun <T> Algebra<T>.expression(block: Algebra<T>.(arguments: Map<String, T>) -> T): Expression<T> =
object : Expression<T> {
override fun invoke(arguments: Map<String, T>): T = block(arguments)
}
}
operator fun <T> Expression<T>.invoke(vararg pairs: Pair<String, T>): T = invoke(mapOf(*pairs))

14
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/BufferMatrix.kt
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@ -19,22 +19,20 @@ class BufferMatrixContext<T : Any, R : Ring<T>>(
override fun point(size: Int, initializer: (Int) -> T): Point<T> = bufferFactory(size, initializer)
companion object {
}
companion object
}
@Suppress("OVERRIDE_BY_INLINE")
object RealMatrixContext : GenericMatrixContext<Double, RealField> {
override val elementContext get() = RealField
override val elementContext: RealField get() = RealField
override inline fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): Matrix<Double> {
val buffer = RealBuffer(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
return BufferMatrix(rows, columns, buffer)
}
override inline fun point(size: Int, initializer: (Int) -> Double): Point<Double> = RealBuffer(size,initializer)
override inline fun point(size: Int, initializer: (Int) -> Double): Point<Double> = RealBuffer(size, initializer)
}
class BufferMatrix<T : Any>(
@ -52,7 +50,7 @@ class BufferMatrix<T : Any>(
override val shape: IntArray get() = intArrayOf(rowNum, colNum)
override fun suggestFeature(vararg features: MatrixFeature) =
override fun suggestFeature(vararg features: MatrixFeature): BufferMatrix<T> =
BufferMatrix(rowNum, colNum, buffer, this.features + features)
override fun get(index: IntArray): T = get(index[0], index[1])
@ -84,8 +82,8 @@ class BufferMatrix<T : Any>(
override fun toString(): String {
return if (rowNum <= 5 && colNum <= 5) {
"Matrix(rowsNum = $rowNum, colNum = $colNum, features=$features)\n" +
rows.asSequence().joinToString(prefix = "(", postfix = ")", separator = "\n ") {
it.asSequence().joinToString(separator = "\t") { it.toString() }
rows.asSequence().joinToString(prefix = "(", postfix = ")", separator = "\n ") { buffer ->
buffer.asSequence().joinToString(separator = "\t") { it.toString() }
}
} else {
"Matrix(rowsNum = $rowNum, colNum = $colNum, features=$features)"

10
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/FeaturedMatrix.kt
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@ -23,12 +23,10 @@ interface FeaturedMatrix<T : Any> : Matrix<T> {
*/
fun suggestFeature(vararg features: MatrixFeature): FeaturedMatrix<T>
companion object {
}
companion object
}
fun Structure2D.Companion.real(rows: Int, columns: Int, initializer: (Int, Int) -> Double) =
fun Structure2D.Companion.real(rows: Int, columns: Int, initializer: (Int, Int) -> Double): Matrix<Double> =
MatrixContext.real.produce(rows, columns, initializer)
/**
@ -41,7 +39,7 @@ fun <T : Any> Structure2D.Companion.square(vararg elements: T): FeaturedMatrix<T
return BufferMatrix(size, size, buffer)
}
val Matrix<*>.features get() = (this as? FeaturedMatrix)?.features?: emptySet()
val Matrix<*>.features: Set<MatrixFeature> get() = (this as? FeaturedMatrix)?.features ?: emptySet()
/**
* Check if matrix has the given feature class
@ -68,7 +66,7 @@ fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.one(rows: Int, columns: In
* A virtual matrix of zeroes
*/
fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.zero(rows: Int, columns: Int): FeaturedMatrix<T> =
VirtualMatrix<T>(rows, columns) { _, _ -> elementContext.zero }
VirtualMatrix(rows, columns) { _, _ -> elementContext.zero }
class TransposedFeature<T : Any>(val original: Matrix<T>) : MatrixFeature

22
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/LUPDecomposition.kt
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@ -18,7 +18,7 @@ class LUPDecomposition<T : Any>(
private val even: Boolean
) : LUPDecompositionFeature<T>, DeterminantFeature<T> {
val elementContext get() = context.elementContext
val elementContext: Field<T> get() = context.elementContext
/**
* Returns the matrix L of the decomposition.
@ -67,7 +67,7 @@ class LUPDecomposition<T : Any>(
}
fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.abs(value: T) =
fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.abs(value: T): T =
if (value > elementContext.zero) value else with(elementContext) { -value }
@ -169,9 +169,10 @@ fun <T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.lup(
matrix: Matrix<T>,
noinline checkSingular: (T) -> Boolean
) = lup(T::class, matrix, checkSingular)
): LUPDecomposition<T> = lup(T::class, matrix, checkSingular)
fun GenericMatrixContext<Double, RealField>.lup(matrix: Matrix<Double>) = lup(Double::class, matrix) { it < 1e-11 }
fun GenericMatrixContext<Double, RealField>.lup(matrix: Matrix<Double>): LUPDecomposition<Double> =
lup(Double::class, matrix) { it < 1e-11 }
fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Matrix<T> {
@ -185,7 +186,7 @@ fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Mat
// Apply permutations to b
val bp = create { _, _ -> zero }
for (row in 0 until pivot.size) {
for (row in pivot.indices) {
val bpRow = bp.row(row)
val pRow = pivot[row]
for (col in 0 until matrix.colNum) {
@ -194,7 +195,7 @@ fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Mat
}
// Solve LY = b
for (col in 0 until pivot.size) {
for (col in pivot.indices) {
val bpCol = bp.row(col)
for (i in col + 1 until pivot.size) {
val bpI = bp.row(i)
@ -225,7 +226,7 @@ fun <T : Any> LUPDecomposition<T>.solve(type: KClass<T>, matrix: Matrix<T>): Mat
}
}
inline fun <reified T : Any> LUPDecomposition<T>.solve(matrix: Matrix<T>) = solve(T::class, matrix)
inline fun <reified T : Any> LUPDecomposition<T>.solve(matrix: Matrix<T>): Matrix<T> = solve(T::class, matrix)
/**
* Solve a linear equation **a*x = b**
@ -240,13 +241,12 @@ inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.
return decomposition.solve(T::class, b)
}
fun RealMatrixContext.solve(a: Matrix<Double>, b: Matrix<Double>) =
solve(a, b) { it < 1e-11 }
fun RealMatrixContext.solve(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> = solve(a, b) { it < 1e-11 }
inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F>.inverse(
matrix: Matrix<T>,
noinline checkSingular: (T) -> Boolean
) = solve(matrix, one(matrix.rowNum, matrix.colNum), checkSingular)
): Matrix<T> = solve(matrix, one(matrix.rowNum, matrix.colNum), checkSingular)
fun RealMatrixContext.inverse(matrix: Matrix<Double>) =
fun RealMatrixContext.inverse(matrix: Matrix<Double>): Matrix<Double> =
solve(matrix, one(matrix.rowNum, matrix.colNum)) { it < 1e-11 }

2
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/LinearAlgebra.kt
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@ -25,4 +25,4 @@ fun <T : Any> Matrix<T>.asPoint(): Point<T> =
error("Can't convert matrix with more than one column to vector")
}
fun <T : Any> Point<T>.asMatrix() = VirtualMatrix(size, 1) { i, _ -> get(i) }
fun <T : Any> Point<T>.asMatrix(): VirtualMatrix<T> = VirtualMatrix(size, 1) { i, _ -> get(i) }

8
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/MatrixContext.kt
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@ -29,7 +29,7 @@ interface MatrixContext<T : Any> : SpaceOperations<Matrix<T>> {
/**
* Non-boxing double matrix
*/
val real = RealMatrixContext
val real: RealMatrixContext = RealMatrixContext
/**
* A structured matrix with custom buffer
@ -82,12 +82,12 @@ interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
}
}
override operator fun Matrix<T>.unaryMinus() =
override operator fun Matrix<T>.unaryMinus(): Matrix<T> =
produce(rowNum, colNum) { i, j -> elementContext.run { -get(i, j) } }
override fun add(a: Matrix<T>, b: Matrix<T>): Matrix<T> {
if (a.rowNum != b.rowNum || a.colNum != b.colNum) error("Matrix operation dimension mismatch. [${a.rowNum},${a.colNum}] + [${b.rowNum},${b.colNum}]")
return produce(a.rowNum, a.colNum) { i, j -> elementContext.run { a.get(i, j) + b[i, j] } }
return produce(a.rowNum, a.colNum) { i, j -> elementContext.run { a[i, j] + b[i, j] } }
}
override operator fun Matrix<T>.minus(b: Matrix<T>): Matrix<T> {
@ -96,7 +96,7 @@ interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
}
override fun multiply(a: Matrix<T>, k: Number): Matrix<T> =
produce(a.rowNum, a.colNum) { i, j -> elementContext.run { a.get(i, j) * k } }
produce(a.rowNum, a.colNum) { i, j -> elementContext.run { a[i, j] * k } }
operator fun Number.times(matrix: FeaturedMatrix<T>): Matrix<T> = matrix * this

8
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/MatrixFeatures.kt
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@ -1,7 +1,7 @@
package scientifik.kmath.linear
/**
* A marker interface representing some matrix feature like diagonal, sparce, zero, etc. Features used to optimize matrix
* A marker interface representing some matrix feature like diagonal, sparse, zero, etc. Features used to optimize matrix
* operations performance in some cases.
*/
interface MatrixFeature
@ -36,19 +36,19 @@ interface DeterminantFeature<T : Any> : MatrixFeature {
}
@Suppress("FunctionName")
fun <T: Any> DeterminantFeature(determinant: T) = object: DeterminantFeature<T>{
fun <T : Any> DeterminantFeature(determinant: T): DeterminantFeature<T> = object : DeterminantFeature<T> {
override val determinant: T = determinant
}
/**
* Lower triangular matrix
*/
object LFeature: MatrixFeature
object LFeature : MatrixFeature
/**
* Upper triangular feature
*/
object UFeature: MatrixFeature
object UFeature : MatrixFeature
/**
* TODO add documentation

4
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/VectorSpace.kt
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@ -54,7 +54,7 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
size: Int,
space: S,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
) = BufferVectorSpace(size, space, bufferFactory)
): BufferVectorSpace<T, S> = BufferVectorSpace(size, space, bufferFactory)
/**
* Automatic buffered vector, unboxed if it is possible
@ -70,6 +70,6 @@ class BufferVectorSpace<T : Any, S : Space<T>>(
override val space: S,
val bufferFactory: BufferFactory<T>
) : VectorSpace<T, S> {
override fun produce(initializer: (Int) -> T) = bufferFactory(size, initializer)
override fun produce(initializer: (Int) -> T): Buffer<T> = bufferFactory(size, initializer)
//override fun produceElement(initializer: (Int) -> T): Vector<T, S> = BufferVector(this, produce(initializer))
}

2
kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/VirtualMatrix.kt
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@ -20,7 +20,7 @@ class VirtualMatrix<T : Any>(
override fun get(i: Int, j: Int): T = generator(i, j)
override fun suggestFeature(vararg features: MatrixFeature) =
override fun suggestFeature(vararg features: MatrixFeature): VirtualMatrix<T> =
VirtualMatrix(rowNum, colNum, this.features + features, generator)
override fun equals(other: Any?): Boolean {

8
kmath-core/src/commonMain/kotlin/scientifik/kmath/misc/AutoDiff.kt
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@ -22,12 +22,12 @@ class DerivationResult<T : Any>(
val deriv: Map<Variable<T>, T>,
val context: Field<T>
) : Variable<T>(value) {
fun deriv(variable: Variable<T>) = deriv[variable] ?: context.zero
fun deriv(variable: Variable<T>): T = deriv[variable] ?: context.zero
/**
* compute divergence
*/
fun div() = context.run { sum(deriv.values) }
fun div(): T = context.run { sum(deriv.values) }
/**
* Compute a gradient for variables in given order
@ -53,7 +53,7 @@ class DerivationResult<T : Any>(
* ```
*/
fun <T : Any, F : Field<T>> F.deriv(body: AutoDiffField<T, F>.() -> Variable<T>): DerivationResult<T> =
AutoDiffContext<T, F>(this).run {
AutoDiffContext(this).run {
val result = body()
result.d = context.one// computing derivative w.r.t result
runBackwardPass()
@ -86,7 +86,7 @@ abstract class AutoDiffField<T : Any, F : Field<T>> : Field<Variable<T>> {
abstract fun variable(value: T): Variable<T>
inline fun variable(block: F.() -> T) = variable(context.block())
inline fun variable(block: F.() -> T): Variable<T> = variable(context.block())
// Overloads for Double constants

35
kmath-core/src/commonMain/kotlin/scientifik/kmath/misc/cumulative.kt
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@ -1,14 +1,15 @@
package scientifik.kmath.misc
import scientifik.kmath.operations.Space
import scientifik.kmath.operations.invoke
import kotlin.jvm.JvmName
/**
* Generic cumulative operation on iterator
* @param T type of initial iterable
* @param R type of resulting iterable
* @param initial lazy evaluated
* Generic cumulative operation on iterator.
*
* @param T the type of initial iterable.
* @param R the type of resulting iterable.
* @param initial lazy evaluated.
*/
fun <T, R> Iterator<T>.cumulative(initial: R, operation: (R, T) -> R): Iterator<R> = object : Iterator<R> {
var state: R = initial
@ -36,41 +37,41 @@ fun <T, R> List<T>.cumulative(initial: R, operation: (R, T) -> R): List<R> =
/**
* Cumulative sum with custom space
*/
fun <T> Iterable<T>.cumulativeSum(space: Space<T>) = with(space) {
fun <T> Iterable<T>.cumulativeSum(space: Space<T>): Iterable<T> = space {
cumulative(zero) { element: T, sum: T -> sum + element }
}
@JvmName("cumulativeSumOfDouble")
fun Iterable<Double>.cumulativeSum() = this.cumulative(0.0) { element, sum -> sum + element }
fun Iterable<Double>.cumulativeSum(): Iterable<Double> = this.cumulative(0.0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfInt")
fun Iterable<Int>.cumulativeSum() = this.cumulative(0) { element, sum -> sum + element }
fun Iterable<Int>.cumulativeSum(): Iterable<Int> = this.cumulative(0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfLong")
fun Iterable<Long>.cumulativeSum() = this.cumulative(0L) { element, sum -> sum + element }
fun Iterable<Long>.cumulativeSum(): Iterable<Long> = this.cumulative(0L) { element, sum -> sum + element }
fun <T> Sequence<T>.cumulativeSum(space: Space<T>) = with(space) {
fun <T> Sequence<T>.cumulativeSum(space: Space<T>): Sequence<T> = with(space) {
cumulative(zero) { element: T, sum: T -> sum + element }
}
@JvmName("cumulativeSumOfDouble")
fun Sequence<Double>.cumulativeSum() = this.cumulative(0.0) { element, sum -> sum + element }
fun Sequence<Double>.cumulativeSum(): Sequence<Double> = this.cumulative(0.0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfInt")
fun Sequence<Int>.cumulativeSum() = this.cumulative(0) { element, sum -> sum + element }
fun Sequence<Int>.cumulativeSum(): Sequence<Int> = this.cumulative(0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfLong")
fun Sequence<Long>.cumulativeSum() = this.cumulative(0L) { element, sum -> sum + element }
fun Sequence<Long>.cumulativeSum(): Sequence<Long> = this.cumulative(0L) { element, sum -> sum + element }
fun <T> List<T>.cumulativeSum(space: Space<T>) = with(space) {
fun <T> List<T>.cumulativeSum(space: Space<T>): List<T> = with(space) {
cumulative(zero) { element: T, sum: T -> sum + element }
}
@JvmName("cumulativeSumOfDouble")
fun List<Double>.cumulativeSum() = this.cumulative(0.0) { element, sum -> sum + element }
fun List<Double>.cumulativeSum(): List<Double> = this.cumulative(0.0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfInt")
fun List<Int>.cumulativeSum() = this.cumulative(0) { element, sum -> sum + element }
fun List<Int>.cumulativeSum(): List<Int> = this.cumulative(0) { element, sum -> sum + element }
@JvmName("cumulativeSumOfLong")
fun List<Long>.cumulativeSum() = this.cumulative(0L) { element, sum -> sum + element }
fun List<Long>.cumulativeSum(): List<Long> = this.cumulative(0L) { element, sum -> sum + element }

225
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/Algebra.kt
View File

@ -1,10 +1,15 @@
package scientifik.kmath.operations
/**
* Stub for DSL the [Algebra] is.
*/
@DslMarker
annotation class KMathContext
/**
* Marker interface for any algebra
* Represents an algebraic structure.
*
* @param T the type of element of this structure.
*/
interface Algebra<T> {
/**
@ -24,50 +29,122 @@ interface Algebra<T> {
}
/**
* An algebra with numeric representation of members
* An algebraic structure where elements can have numeric representation.
*
* @param T the type of element of this structure.
*/
interface NumericAlgebra<T> : Algebra<T> {
/**
* Wrap a number
* Wraps a number.
*/
fun number(value: Number): T
/**
* Dynamic call of binary operation [operation] on [left] and [right] where left element is [Number].
*/
fun leftSideNumberOperation(operation: String, left: Number, right: T): T =
binaryOperation(operation, number(left), right)
/**
* Dynamic call of binary operation [operation] on [left] and [right] where right element is [Number].
*/
fun rightSideNumberOperation(operation: String, left: T, right: Number): T =
leftSideNumberOperation(operation, right, left)
}
/**
* Call a block with an [Algebra] as receiver
* Call a block with an [Algebra] as receiver.
*/
inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = run(block)
/**
* Space-like operations without neutral element
* Represents semigroup, i.e. algebraic structure with associative binary operation called "addition".
*
* In KMath groups are called spaces, and also define multiplication of element by [Number].
*
* @param T the type of element of this semigroup.
*/
interface SpaceOperations<T> : Algebra<T> {
/**
* Addition operation for two context elements
* Addition of two elements.
*
* @param a the addend.
* @param b the augend.
* @return the sum.
*/
fun add(a: T, b: T): T
/**
* Multiplication operation for context element and real number
* Multiplication of element by scalar.
*
* @param a the multiplier.
* @param k the multiplicand.
* @return the produce.
*/
fun multiply(a: T, k: Number): T
//Operation to be performed in this context. Could be moved to extensions in case of KEEP-176
// Operations to be performed in this context. Could be moved to extensions in case of KEEP-176
/**
* The negation of this element.
*
* @receiver this value.
* @return the additive inverse of this value.
*/
operator fun T.unaryMinus(): T = multiply(this, -1.0)
/**
* Returns this value.
*
* @receiver this value.
* @return this value.
*/
operator fun T.unaryPlus(): T = this
/**
* Addition of two elements.
*
* @receiver the addend.
* @param b the augend.
* @return the sum.
*/
operator fun T.plus(b: T): T = add(this, b)
/**
* Subtraction of two elements.
*
* @receiver the minuend.
* @param b the subtrahend.
* @return the difference.
*/
operator fun T.minus(b: T): T = add(this, -b)
operator fun T.times(k: Number) = multiply(this, k.toDouble())
operator fun T.div(k: Number) = multiply(this, 1.0 / k.toDouble())
operator fun Number.times(b: T) = b * this
/**
* Multiplication of this element by a scalar.
*
* @receiver the multiplier.
* @param k the multiplicand.
* @return the product.
*/
operator fun T.times(k: Number): T = multiply(this, k.toDouble())
/**
* Division of this element by scalar.
*
* @receiver the dividend.
* @param k the divisor.
* @return the quotient.
*/
operator fun T.div(k: Number): T = multiply(this, 1.0 / k.toDouble())
/**
* Multiplication of this number by element.
*
* @receiver the multiplier.
* @param b the multiplicand.
* @return the product.
*/
operator fun Number.times(b: T): T = b * this
override fun unaryOperation(operation: String, arg: T): T = when (operation) {
PLUS_OPERATION -> arg
@ -82,37 +159,56 @@ interface SpaceOperations<T> : Algebra<T> {
}
companion object {
const val PLUS_OPERATION = "+"
const val MINUS_OPERATION = "-"
const val NOT_OPERATION = "!"
/**
* The identifier of addition.
*/
const val PLUS_OPERATION: String = "+"
/**
* The identifier of subtraction (and negation).
*/
const val MINUS_OPERATION: String = "-"
const val NOT_OPERATION: String = "!"
}
}
/**
* A general interface representing linear context of some kind.
* The context defines sum operation for its elements and multiplication by real value.
* One must note that in some cases context is a singleton class, but in some cases it
* works as a context for operations inside it.
* Represents group, i.e. algebraic structure with associative binary operation called "addition" and its neutral
* element.
*
* TODO do we need non-commutative context?
* In KMath groups are called spaces, and also define multiplication of element by [Number].
*
* @param T the type of element of this group.
*/
interface Space<T> : SpaceOperations<T> {
/**
* Neutral element for sum operation
* The neutral element of addition.
*/
val zero: T
}
/**
* Operations on ring without multiplication neutral element
* Represents semiring, i.e. algebraic structure with two associative binary operations called "addition" and
* "multiplication".
*
* @param T the type of element of this semiring.
*/
interface RingOperations<T> : SpaceOperations<T> {
/**
* Multiplication for two field elements
* Multiplies two elements.
*
* @param a the multiplier.
* @param b the multiplicand.
*/
fun multiply(a: T, b: T): T
/**
* Multiplies this element by scalar.
*
* @receiver the multiplier.
* @param b the multiplicand.
*/
operator fun T.times(b: T): T = multiply(this, b)
override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) {
@ -121,12 +217,18 @@ interface RingOperations<T> : SpaceOperations<T> {
}
companion object {
const val TIMES_OPERATION = "*"
/**
* The identifier of multiplication.
*/
const val TIMES_OPERATION: String = "*"
}
}
/**
* The same as {@link Space} but with additional multiplication operation
* Represents ring, i.e. algebraic structure with two associative binary operations called "addition" and
* "multiplication" and their neutral elements.
*
* @param T the type of element of this ring.
*/
interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
/**
@ -150,20 +252,64 @@ interface Ring<T> : Space<T>, RingOperations<T>, NumericAlgebra<T> {
else -> super.rightSideNumberOperation(operation, left, right)
}
/**
* Addition of element and scalar.
*
* @receiver the addend.
* @param b the augend.
*/
operator fun T.plus(b: Number): T = this + number(b)
operator fun T.plus(b: Number) = this.plus(number(b))
operator fun Number.plus(b: T) = b + this
/**
* Addition of scalar and element.
*
* @receiver the addend.
* @param b the augend.
*/
operator fun Number.plus(b: T): T = b + this
operator fun T.minus(b: Number) = this.minus(number(b))
operator fun Number.minus(b: T) = -b + this
/**
* Subtraction of element from number.
*
* @receiver the minuend.
* @param b the subtrahend.
* @receiver the difference.
*/
operator fun T.minus(b: Number): T = this - number(b)
/**
* Subtraction of number from element.
*
* @receiver the minuend.
* @param b the subtrahend.
* @receiver the difference.
*/
operator fun Number.minus(b: T): T = -b + this
}
/**
* All ring operations but without neutral elements
* Represents semifield, i.e. algebraic structure with three operations: associative "addition" and "multiplication",
* and "division".
*
* @param T the type of element of this semifield.
*/
interface FieldOperations<T> : RingOperations<T> {
/**
* Division of two elements.
*
* @param a the dividend.
* @param b the divisor.
* @return the quotient.
*/
fun divide(a: T, b: T): T
/**
* Division of two elements.
*
* @receiver the dividend.
* @param b the divisor.
* @return the quotient.
*/
operator fun T.div(b: T): T = divide(this, b)
override fun binaryOperation(operation: String, left: T, right: T): T = when (operation) {
@ -172,13 +318,26 @@ interface FieldOperations<T> : RingOperations<T> {
}
companion object {
const val DIV_OPERATION = "/"
/**
* The identifier of division.
*/
const val DIV_OPERATION: String = "/"
}
}
/**
* Four operations algebra
* Represents field, i.e. algebraic structure with three operations: associative "addition" and "multiplication",
* and "division" and their neutral elements.
*
* @param T the type of element of this semifield.
*/
interface Field<T> : Ring<T>, FieldOperations<T> {
operator fun Number.div(b: T) = this * divide(one, b)
/**
* Division of element by scalar.
*
* @receiver the dividend.
* @param b the divisor.
* @return the quotient.
*/
operator fun Number.div(b: T): T = this * divide(one, b)
}

20
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/AlgebraElements.kt
View File

@ -2,13 +2,12 @@ package scientifik.kmath.operations
/**
* The generic mathematics elements which is able to store its context
* @param T the type of space operation results
* @param I self type of the element. Needed for static type checking
* @param C the type of mathematical context for this element
*
* @param C the type of mathematical context for this element.
*/
interface MathElement<C> {
/**
* The context this element belongs to
* The context this element belongs to.
*/
val context: C
}
@ -25,18 +24,17 @@ interface MathWrapper<T, I> {
* @param S the type of space
*/
interface SpaceElement<T, I : SpaceElement<T, I, S>, S : Space<T>> : MathElement<S>, MathWrapper<T, I> {
operator fun plus(b: T) = context.add(unwrap(), b).wrap()
operator fun minus(b: T) = context.add(unwrap(), context.multiply(b, -1.0)).wrap()
operator fun times(k: Number) = context.multiply(unwrap(), k.toDouble()).wrap()
operator fun div(k: Number) = context.multiply(unwrap(), 1.0 / k.toDouble()).wrap()
operator fun plus(b: T): I = context.add(unwrap(), b).wrap()
operator fun minus(b: T): I = context.add(unwrap(), context.multiply(b, -1.0)).wrap()
operator fun times(k: Number): I = context.multiply(unwrap(), k.toDouble()).wrap()
operator fun div(k: Number): I = context.multiply(unwrap(), 1.0 / k.toDouble()).wrap()
}
/**
* Ring element
*/
interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T, I, R> {
operator fun times(b: T) = context.multiply(unwrap(), b).wrap()
operator fun times(b: T): I = context.multiply(unwrap(), b).wrap()
}
/**
@ -44,5 +42,5 @@ interface RingElement<T, I : RingElement<T, I, R>, R : Ring<T>> : SpaceElement<T
*/
interface FieldElement<T, I : FieldElement<T, I, F>, F : Field<T>> : RingElement<T, I, F> {
override val context: F
operator fun div(b: T) = context.divide(unwrap(), b).wrap()
operator fun div(b: T): I = context.divide(unwrap(), b).wrap()
}

22
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/BigInt.kt
View File

@ -194,8 +194,8 @@ class BigInt internal constructor(
}
infix fun or(other: BigInt): BigInt {
if (this == ZERO) return other;
if (other == ZERO) return this;
if (this == ZERO) return other
if (other == ZERO) return this
val resSize = max(this.magnitude.size, other.magnitude.size)
val newMagnitude: Magnitude = Magnitude(resSize)
for (i in 0 until resSize) {
@ -210,7 +210,7 @@ class BigInt internal constructor(
}
infix fun and(other: BigInt): BigInt {
if ((this == ZERO) or (other == ZERO)) return ZERO;
if ((this == ZERO) or (other == ZERO)) return ZERO
val resSize = min(this.magnitude.size, other.magnitude.size)
val newMagnitude: Magnitude = Magnitude(resSize)
for (i in 0 until resSize) {
@ -260,7 +260,7 @@ class BigInt internal constructor(
}
companion object {
const val BASE = 0xffffffffUL
const val BASE: ULong = 0xffffffffUL
const val BASE_SIZE: Int = 32
val ZERO: BigInt = BigInt(0, uintArrayOf())
val ONE: BigInt = BigInt(1, uintArrayOf(1u))
@ -394,12 +394,12 @@ fun abs(x: BigInt): BigInt = x.abs()
/**
* Convert this [Int] to [BigInt]
*/
fun Int.toBigInt() = BigInt(sign.toByte(), uintArrayOf(kotlin.math.abs(this).toUInt()))
fun Int.toBigInt(): BigInt = BigInt(sign.toByte(), uintArrayOf(kotlin.math.abs(this).toUInt()))
/**
* Convert this [Long] to [BigInt]
*/
fun Long.toBigInt() = BigInt(
fun Long.toBigInt(): BigInt = BigInt(
sign.toByte(), stripLeadingZeros(
uintArrayOf(
(kotlin.math.abs(this).toULong() and BASE).toUInt(),
@ -411,17 +411,17 @@ fun Long.toBigInt() = BigInt(
/**
* Convert UInt to [BigInt]
*/
fun UInt.toBigInt() = BigInt(1, uintArrayOf(this))
fun UInt.toBigInt(): BigInt = BigInt(1, uintArrayOf(this))
/**
* Convert ULong to [BigInt]
*/
fun ULong.toBigInt() = BigInt(
fun ULong.toBigInt(): BigInt = BigInt(
1,
stripLeadingZeros(
uintArrayOf(
(this and BigInt.BASE).toUInt(),
((this shr BigInt.BASE_SIZE) and BigInt.BASE).toUInt()
(this and BASE).toUInt(),
((this shr BASE_SIZE) and BASE).toUInt()
)
)
)
@ -434,7 +434,7 @@ fun UIntArray.toBigInt(sign: Byte): BigInt {
return BigInt(sign, this.copyOf())
}
val hexChToInt = hashMapOf(
val hexChToInt: MutableMap<Char, Int> = hashMapOf(
'0' to 0, '1' to 1, '2' to 2, '3' to 3,
'4' to 4, '5' to 5, '6' to 6, '7' to 7,
'8' to 8, '9' to 9, 'A' to 10, 'B' to 11,

14
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/Complex.kt
View File

@ -18,7 +18,7 @@ object ComplexField : ExtendedField<Complex> {
override val one: Complex = Complex(1.0, 0.0)
val i = Complex(0.0, 1.0)
val i: Complex = Complex(0.0, 1.0)
override fun add(a: Complex, b: Complex): Complex = Complex(a.re + b.re, a.im + b.im)
@ -45,15 +45,15 @@ object ComplexField : ExtendedField<Complex> {
override fun ln(arg: Complex): Complex = ln(arg.r) + i * atan2(arg.im, arg.re)
operator fun Double.plus(c: Complex) = add(this.toComplex(), c)
operator fun Double.plus(c: Complex): Complex = add(this.toComplex(), c)
operator fun Double.minus(c: Complex) = add(this.toComplex(), -c)
operator fun Double.minus(c: Complex): Complex = add(this.toComplex(), -c)
operator fun Complex.plus(d: Double) = d + this
operator fun Complex.plus(d: Double): Complex = d + this
operator fun Complex.minus(d: Double) = add(this, -d.toComplex())
operator fun Complex.minus(d: Double): Complex = add(this, -d.toComplex())
operator fun Double.times(c: Complex) = Complex(c.re * this, c.im * this)
operator fun Double.times(c: Complex): Complex = Complex(c.re * this, c.im * this)
override fun symbol(value: String): Complex = if (value == "i") {
i
@ -104,7 +104,7 @@ val Complex.r: Double get() = sqrt(re * re + im * im)
*/
val Complex.theta: Double get() = atan(im / re)
fun Double.toComplex() = Complex(this, 0.0)
fun Double.toComplex(): Complex = Complex(this, 0.0)
inline fun Buffer.Companion.complex(size: Int, crossinline init: (Int) -> Complex): Buffer<Complex> {
return MemoryBuffer.create(Complex, size, init)

125
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/NumberAlgebra.kt
View File

@ -1,6 +1,5 @@
package scientifik.kmath.operations
import scientifik.kmath.operations.RealField.pow
import kotlin.math.abs
import kotlin.math.pow as kpow
@ -38,6 +37,8 @@ interface ExtendedField<T> : ExtendedFieldOperations<T>, Field<T> {
/**
* Real field element wrapping double.
*
* @property value the [Double] value wrapped by this [Real].
*
* TODO inline does not work due to compiler bug. Waiting for fix for KT-27586
*/
inline class Real(val value: Double) : FieldElement<Double, Real, RealField> {
@ -45,7 +46,7 @@ inline class Real(val value: Double) : FieldElement<Double, Real, RealField> {
override fun Double.wrap(): Real = Real(value)
override val context get() = RealField
override val context: RealField get() = RealField
companion object
}
@ -56,36 +57,36 @@ inline class Real(val value: Double) : FieldElement<Double, Real, RealField> {
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
object RealField : ExtendedField<Double>, Norm<Double, Double> {
override val zero: Double = 0.0
override inline fun add(a: Double, b: Double) = a + b
override inline fun multiply(a: Double, b: Double) = a * b
override inline fun multiply(a: Double, k: Number) = a * k.toDouble()
override inline fun add(a: Double, b: Double): Double = a + b
override inline fun multiply(a: Double, b: Double): Double = a * b
override inline fun multiply(a: Double, k: Number): Double = a * k.toDouble()
override val one: Double = 1.0
override inline fun divide(a: Double, b: Double) = a / b
override inline fun divide(a: Double, b: Double): Double = a / b
override inline fun sin(arg: Double) = kotlin.math.sin(arg)
override inline fun cos(arg: Double) = kotlin.math.cos(arg)
override inline fun sin(arg: Double): Double = kotlin.math.sin(arg)
override inline fun cos(arg: Double): Double = kotlin.math.cos(arg)
override inline fun tan(arg: Double): Double = kotlin.math.tan(arg)
override inline fun acos(arg: Double): Double = kotlin.math.acos(arg)
override inline fun asin(arg: Double): Double = kotlin.math.asin(arg)
override inline fun atan(arg: Double): Double = kotlin.math.atan(arg)
override inline fun power(arg: Double, pow: Number) = arg.kpow(pow.toDouble())
override inline fun power(arg: Double, pow: Number): Double = arg.kpow(pow.toDouble())
override inline fun exp(arg: Double) = kotlin.math.exp(arg)
override inline fun ln(arg: Double) = kotlin.math.ln(arg)
override inline fun exp(arg: Double): Double = kotlin.math.exp(arg)
override inline fun ln(arg: Double): Double = kotlin.math.ln(arg)
override inline fun norm(arg: Double) = abs(arg)
override inline fun norm(arg: Double): Double = abs(arg)
override inline fun Double.unaryMinus() = -this
override inline fun Double.unaryMinus(): Double = -this
override inline fun Double.plus(b: Double) = this + b
override inline fun Double.plus(b: Double): Double = this + b
override inline fun Double.minus(b: Double) = this - b
override inline fun Double.minus(b: Double): Double = this - b
override inline fun Double.times(b: Double) = this * b
override inline fun Double.times(b: Double): Double = this * b
override inline fun Double.div(b: Double) = this / b
override inline fun Double.div(b: Double): Double = this / b
override fun binaryOperation(operation: String, left: Double, right: Double): Double = when (operation) {
PowerOperations.POW_OPERATION -> left pow right
@ -96,36 +97,36 @@ object RealField : ExtendedField<Double>, Norm<Double, Double> {
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
object FloatField : ExtendedField<Float>, Norm<Float, Float> {
override val zero: Float = 0f
override inline fun add(a: Float, b: Float) = a + b
override inline fun multiply(a: Float, b: Float) = a * b
override inline fun multiply(a: Float, k: Number) = a * k.toFloat()
override inline fun add(a: Float, b: Float): Float = a + b
override inline fun multiply(a: Float, b: Float): Float = a * b
override inline fun multiply(a: Float, k: Number): Float = a * k.toFloat()
override val one: Float = 1f
override inline fun divide(a: Float, b: Float) = a / b
override inline fun divide(a: Float, b: Float): Float = a / b
override inline fun sin(arg: Float) = kotlin.math.sin(arg)
override inline fun cos(arg: Float) = kotlin.math.cos(arg)
override inline fun tan(arg: Float) = kotlin.math.tan(arg)
override inline fun acos(arg: Float) = kotlin.math.acos(arg)
override inline fun asin(arg: Float) = kotlin.math.asin(arg)
override inline fun atan(arg: Float) = kotlin.math.atan(arg)
override inline fun sin(arg: Float): Float = kotlin.math.sin(arg)
override inline fun cos(arg: Float): Float = kotlin.math.cos(arg)
override inline fun tan(arg: Float): Float = kotlin.math.tan(arg)
override inline fun acos(arg: Float): Float = kotlin.math.acos(arg)
override inline fun asin(arg: Float): Float = kotlin.math.asin(arg)
override inline fun atan(arg: Float): Float = kotlin.math.atan(arg)
override inline fun power(arg: Float, pow: Number) = arg.pow(pow.toFloat())
override inline fun power(arg: Float, pow: Number): Float = arg.pow(pow.toFloat())
override inline fun exp(arg: Float) = kotlin.math.exp(arg)
override inline fun ln(arg: Float) = kotlin.math.ln(arg)
override inline fun exp(arg: Float): Float = kotlin.math.exp(arg)
override inline fun ln(arg: Float): Float = kotlin.math.ln(arg)
override inline fun norm(arg: Float) = abs(arg)
override inline fun norm(arg: Float): Float = abs(arg)
override inline fun Float.unaryMinus() = -this
override inline fun Float.unaryMinus(): Float = -this
override inline fun Float.plus(b: Float) = this + b
override inline fun Float.plus(b: Float): Float = this + b
override inline fun Float.minus(b: Float) = this - b
override inline fun Float.minus(b: Float): Float = this - b
override inline fun Float.times(b: Float) = this * b
override inline fun Float.times(b: Float): Float = this * b
override inline fun Float.div(b: Float) = this / b
override inline fun Float.div(b: Float): Float = this / b
}
/**
@ -134,14 +135,14 @@ object FloatField : ExtendedField<Float>, Norm<Float, Float> {
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
object IntRing : Ring<Int>, Norm<Int, Int> {
override val zero: Int = 0
override inline fun add(a: Int, b: Int) = a + b
override inline fun multiply(a: Int, b: Int) = a * b
override inline fun multiply(a: Int, k: Number) = k.toInt() * a
override inline fun add(a: Int, b: Int): Int = a + b
override inline fun multiply(a: Int, b: Int): Int = a * b
override inline fun multiply(a: Int, k: Number): Int = k.toInt() * a
override val one: Int = 1
override inline fun norm(arg: Int) = abs(arg)
override inline fun norm(arg: Int): Int = abs(arg)
override inline fun Int.unaryMinus() = -this
override inline fun Int.unaryMinus(): Int = -this
override inline fun Int.plus(b: Int): Int = this + b
@ -156,20 +157,20 @@ object IntRing : Ring<Int>, Norm<Int, Int> {
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
object ShortRing : Ring<Short>, Norm<Short, Short> {
override val zero: Short = 0
override inline fun add(a: Short, b: Short) = (a + b).toShort()
override inline fun multiply(a: Short, b: Short) = (a * b).toShort()
override inline fun multiply(a: Short, k: Number) = (a * k.toShort()).toShort()
override inline fun add(a: Short, b: Short): Short = (a + b).toShort()
override inline fun multiply(a: Short, b: Short): Short = (a * b).toShort()
override inline fun multiply(a: Short, k: Number): Short = (a * k.toShort()).toShort()
override val one: Short = 1
override fun norm(arg: Short): Short = if (arg > 0) arg else (-arg).toShort()
override inline fun Short.unaryMinus() = (-this).toShort()
override inline fun Short.unaryMinus(): Short = (-this).toShort()
override inline fun Short.plus(b: Short) = (this + b).toShort()
override inline fun Short.plus(b: Short): Short = (this + b).toShort()
override inline fun Short.minus(b: Short) = (this - b).toShort()
override inline fun Short.minus(b: Short): Short = (this - b).toShort()
override inline fun Short.times(b: Short) = (this * b).toShort()
override inline fun Short.times(b: Short): Short = (this * b).toShort()
}
/**
@ -178,20 +179,20 @@ object ShortRing : Ring<Short>, Norm<Short, Short> {
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
object ByteRing : Ring<Byte>, Norm<Byte, Byte> {
override val zero: Byte = 0
override inline fun add(a: Byte, b: Byte) = (a + b).toByte()
override inline fun multiply(a: Byte, b: Byte) = (a * b).toByte()
override inline fun multiply(a: Byte, k: Number) = (a * k.toByte()).toByte()
override inline fun add(a: Byte, b: Byte): Byte = (a + b).toByte()
override inline fun multiply(a: Byte, b: Byte): Byte = (a * b).toByte()
override inline fun multiply(a: Byte, k: Number): Byte = (a * k.toByte()).toByte()
override val one: Byte = 1
override fun norm(arg: Byte): Byte = if (arg > 0) arg else (-arg).toByte()
override inline fun Byte.unaryMinus() = (-this).toByte()
override inline fun Byte.unaryMinus(): Byte = (-this).toByte()
override inline fun Byte.plus(b: Byte) = (this + b).toByte()
override inline fun Byte.plus(b: Byte): Byte = (this + b).toByte()
override inline fun Byte.minus(b: Byte) = (this - b).toByte()
override inline fun Byte.minus(b: Byte): Byte = (this - b).toByte()
override inline fun Byte.times(b: Byte) = (this * b).toByte()
override inline fun Byte.times(b: Byte): Byte = (this * b).toByte()
}
/**
@ -200,18 +201,18 @@ object ByteRing : Ring<Byte>, Norm<Byte, Byte> {
@Suppress("EXTENSION_SHADOWED_BY_MEMBER", "OVERRIDE_BY_INLINE", "NOTHING_TO_INLINE")
object LongRing : Ring<Long>, Norm<Long, Long> {
override val zero: Long = 0
override inline fun add(a: Long, b: Long) = (a + b)
override inline fun multiply(a: Long, b: Long) = (a * b)
override inline fun multiply(a: Long, k: Number) = a * k.toLong()
override inline fun add(a: Long, b: Long): Long = (a + b)
override inline fun multiply(a: Long, b: Long): Long = (a * b)
override inline fun multiply(a: Long, k: Number): Long = a * k.toLong()
override val one: Long = 1
override fun norm(arg: Long): Long = abs(arg)
override inline fun Long.unaryMinus() = (-this)
override inline fun Long.unaryMinus(): Long = (-this)
override inline fun Long.plus(b: Long) = (this + b)
override inline fun Long.plus(b: Long): Long = (this + b)
override inline fun Long.minus(b: Long) = (this - b)
override inline fun Long.minus(b: Long): Long = (this - b)
override inline fun Long.times(b: Long) = (this * b)
override inline fun Long.times(b: Long): Long = (this * b)
}

186
kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/OptionalOperations.kt
View File

@ -1,84 +1,210 @@
package scientifik.kmath.operations
/* Trigonometric operations */
/**
* A container for trigonometric operations for specific type. Trigonometric operations are limited to fields.
* A container for trigonometric operations for specific type. They are limited to semifields.
*
* The operations are not exposed to class directly to avoid method bloat but instead are declared in the field.
* It also allows to override behavior for optional operations
*
* It also allows to override behavior for optional operations.
*/
interface TrigonometricOperations<T> : FieldOperations<T> {
/**
* Computes the sine of [arg].
*/
fun sin(arg: T): T
/**
* Computes the cosine of [arg].
*/
fun cos(arg: T): T
/**
* Computes the tangent of [arg].
*/
fun tan(arg: T): T
companion object {
const val SIN_OPERATION = "sin"
const val COS_OPERATION = "cos"
const val TAN_OPERATION = "tan"
/**
* The identifier of sine.
*/
const val SIN_OPERATION: String = "sin"
/**
* The identifier of cosine.
*/
const val COS_OPERATION: String = "cos"
/**
* The identifier of tangent.
*/
const val TAN_OPERATION: String = "tan"
}
}
/**
* A container for inverse trigonometric operations for specific type. They are limited to semifields.
*
* The operations are not exposed to class directly to avoid method bloat but instead are declared in the field.
* It also allows to override behavior for optional operations.
*/
interface InverseTrigonometricOperations<T> : TrigonometricOperations<T> {
/**
* Computes the inverse sine of [arg].
*/
fun asin(arg: T): T
/**
* Computes the inverse cosine of [arg].
*/
fun acos(arg: T): T
/**
* Computes the inverse tangent of [arg].
*/
fun atan(arg: T): T
companion object {
const val ASIN_OPERATION = "asin"
const val ACOS_OPERATION = "acos"
const val ATAN_OPERATION = "atan"
/**
* The identifier of inverse sine.
*/
const val ASIN_OPERATION: String = "asin"
/**
* The identifier of inverse cosine.
*/
const val ACOS_OPERATION: String = "acos"
/**
* The identifier of inverse tangent.
*/
const val ATAN_OPERATION: String = "atan"
}
}
fun <T : MathElement<out TrigonometricOperations<T>>> sin(arg: T): T = arg.context.sin(arg)
fun <T : MathElement<out TrigonometricOperations<T>>> cos(arg: T): T = arg.context.cos(arg)
fun <T : MathElement<out TrigonometricOperations<T>>> tan(arg: T): T = arg.context.tan(arg)
fun <T : MathElement<out InverseTrigonometricOperations<T>>> asin(arg: T): T = arg.context.asin(arg)
fun <T : MathElement<out InverseTrigonometricOperations<T>>> acos(arg: T): T = arg.context.acos(arg)
fun <T : MathElement<out InverseTrigonometricOperations<T>>> atan(arg: T): T = arg.context.atan(arg)
/* Power and roots */
/**
* A context extension to include power operations like square roots, etc
* Computes the sine of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> sin(arg: T): T = arg.context.sin(arg)
/**
* Computes the cosine of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> cos(arg: T): T = arg.context.cos(arg)
/**
* Computes the tangent of [arg].
*/
fun <T : MathElement<out TrigonometricOperations<T>>> tan(arg: T): T = arg.context.tan(arg)
/**
* Computes the inverse sine of [arg].
*/
fun <T : MathElement<out InverseTrigonometricOperations<T>>> asin(arg: T): T = arg.context.asin(arg)
/**
* Computes the inverse cosine of [arg].
*/
fun <T : MathElement<out InverseTrigonometricOperations<T>>> acos(arg: T): T = arg.context.acos(arg)
/**
* Computes the inverse tangent of [arg].
*/
fun <T : MathElement<out InverseTrigonometricOperations<T>>> atan(arg: T): T = arg.context.atan(arg)
/**
* A context extension to include power operations based on exponentiation.
*/
interface PowerOperations<T> : Algebra<T> {
/**
* Raises [arg] to the power [pow].
*/
fun power(arg: T, pow: Number): T
fun sqrt(arg: T) = power(arg, 0.5)
infix fun T.pow(pow: Number) = power(this, pow)
/**
* Computes the square root of the value [arg].
*/
fun sqrt(arg: T): T = power(arg, 0.5)
/**
* Raises this value to the power [pow].
*/
infix fun T.pow(pow: Number): T = power(this, pow)
companion object {
const val POW_OPERATION = "pow"
const val SQRT_OPERATION = "sqrt"
/**
* The identifier of exponentiation.
*/
const val POW_OPERATION: String = "pow"
/**
* The identifier of square root.
*/
const val SQRT_OPERATION: String = "sqrt"
}
}
/**
* Raises [arg] to the power [pow].
*/
infix fun <T : MathElement<out PowerOperations<T>>> T.pow(power: Double): T = context.power(this, power)
/**
* Computes the square root of the value [arg].
*/
fun <T : MathElement<out PowerOperations<T>>> sqrt(arg: T): T = arg pow 0.5
/**
* Computes the square of the value [arg].
*/
fun <T : MathElement<out PowerOperations<T>>> sqr(arg: T): T = arg pow 2.0
/* Exponential */
/**
* A container for operations related to `exp` and `ln` functions.
*/
interface ExponentialOperations<T> : Algebra<T> {
/**
* Computes Euler's number `e` raised to the power of the value [arg].
*/
fun exp(arg: T): T
/**
* Computes the natural logarithm (base `e`) of the value [arg].
*/
fun ln(arg: T): T
companion object {
const val EXP_OPERATION = "exp"
const val LN_OPERATION = "ln"
/**
* The identifier of exponential function.
*/
const val EXP_OPERATION: String = "exp"
/**
* The identifier of natural logarithm.
*/
const val LN_OPERATION: String = "ln"
}
}
/**
* The identifier of exponential function.
*/
fun <T : MathElement<out ExponentialOperations<T>>> exp(arg: T): T = arg.context.exp(arg)
/**
* The identifier of natural logarithm.
*/
fun <T : MathElement<out ExponentialOperations<T>>> ln(arg: T): T = arg.context.ln(arg)
/**
* A container for norm functional on element.
*/
interface Norm<in T : Any, out R> {
/**
* Computes the norm of [arg] (i.e. absolute value or vector length).
*/
fun norm(arg: T): R
}
/**
* Computes the norm of [arg] (i.e. absolute value or vector length).
*/
fun <T : MathElement<out Norm<T, R>>, R> norm(arg: T): R = arg.context.norm(arg)

6
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BoxingNDField.kt
View File

@ -19,10 +19,10 @@ class BoxingNDField<T, F : Field<T>>(
if (!elements.all { it.strides == this.strides }) error("Element strides are not the same as context strides")
}
override val zero by lazy { produce { zero } }
override val one by lazy { produce { one } }
override val zero: BufferedNDFieldElement<T, F> by lazy { produce { zero } }
override val one: BufferedNDFieldElement<T, F> by lazy { produce { one } }
override fun produce(initializer: F.(IntArray) -> T) =
override fun produce(initializer: F.(IntArray) -> T): BufferedNDFieldElement<T, F> =
BufferedNDFieldElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) })

6
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BoxingNDRing.kt
View File

@ -18,10 +18,10 @@ class BoxingNDRing<T, R : Ring<T>>(
if (!elements.all { it.strides == this.strides }) error("Element strides are not the same as context strides")
}
override val zero by lazy { produce { zero } }
override val one by lazy { produce { one } }
override val zero: BufferedNDRingElement<T, R> by lazy { produce { zero } }
override val one: BufferedNDRingElement<T, R> by lazy { produce { one } }
override fun produce(initializer: R.(IntArray) -> T) =
override fun produce(initializer: R.(IntArray) -> T): BufferedNDRingElement<T, R> =
BufferedNDRingElement(
this,
buildBuffer(strides.linearSize) { offset -> elementContext.initializer(strides.index(offset)) })

8
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BufferAccessor2D.kt
View File

@ -7,16 +7,16 @@ import kotlin.reflect.KClass
*/
class BufferAccessor2D<T : Any>(val type: KClass<T>, val rowNum: Int, val colNum: Int) {
operator fun Buffer<T>.get(i: Int, j: Int) = get(i + colNum * j)
operator fun Buffer<T>.get(i: Int, j: Int): T = get(i + colNum * j)
operator fun MutableBuffer<T>.set(i: Int, j: Int, value: T) {
set(i + colNum * j, value)
}
inline fun create(init: (i: Int, j: Int) -> T) =
inline fun create(init: (i: Int, j: Int) -> T): MutableBuffer<T> =
MutableBuffer.auto(type, rowNum * colNum) { offset -> init(offset / colNum, offset % colNum) }
fun create(mat: Structure2D<T>) = create { i, j -> mat[i, j] }
fun create(mat: Structure2D<T>): MutableBuffer<T> = create { i, j -> mat[i, j] }
//TODO optimize wrapper
fun MutableBuffer<T>.collect(): Structure2D<T> =
@ -41,5 +41,5 @@ class BufferAccessor2D<T : Any>(val type: KClass<T>, val rowNum: Int, val colNum
/**
* Get row
*/
fun MutableBuffer<T>.row(i: Int) = Row(this, i)
fun MutableBuffer<T>.row(i: Int): Row = Row(this, i)
}

4
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BufferedNDAlgebra.kt
View File

@ -2,7 +2,7 @@ package scientifik.kmath.structures
import scientifik.kmath.operations.*
interface BufferedNDAlgebra<T, C>: NDAlgebra<T, C, NDBuffer<T>>{
interface BufferedNDAlgebra<T, C> : NDAlgebra<T, C, NDBuffer<T>> {
val strides: Strides
override fun check(vararg elements: NDBuffer<T>) {
@ -30,7 +30,7 @@ interface BufferedNDAlgebra<T, C>: NDAlgebra<T, C, NDBuffer<T>>{
}
interface BufferedNDSpace<T, S : Space<T>> : NDSpace<T, S, NDBuffer<T>>, BufferedNDAlgebra<T,S> {
interface BufferedNDSpace<T, S : Space<T>> : NDSpace<T, S, NDBuffer<T>>, BufferedNDAlgebra<T, S> {
override fun NDBuffer<T>.toElement(): SpaceElement<NDBuffer<T>, *, out BufferedNDSpace<T, S>>
}

14
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BufferedNDElement.kt
View File

@ -8,7 +8,7 @@ import scientifik.kmath.operations.*
abstract class BufferedNDElement<T, C> : NDBuffer<T>(), NDElement<T, C, NDBuffer<T>> {
abstract override val context: BufferedNDAlgebra<T, C>
override val strides get() = context.strides
override val strides: Strides get() = context.strides
override val shape: IntArray get() = context.shape
}
@ -54,9 +54,9 @@ class BufferedNDFieldElement<T, F : Field<T>>(
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy
* Element by element application of any operation on elements to the whole array. Just like in numpy.
*/
operator fun <T : Any, F : Field<T>> Function1<T, T>.invoke(ndElement: BufferedNDElement<T, F>) =
operator fun <T : Any, F : Field<T>> Function1<T, T>.invoke(ndElement: BufferedNDElement<T, F>): MathElement<out BufferedNDAlgebra<T, F>> =
ndElement.context.run { map(ndElement) { invoke(it) }.toElement() }
/* plus and minus */
@ -64,13 +64,13 @@ operator fun <T : Any, F : Field<T>> Function1<T, T>.invoke(ndElement: BufferedN
/**
* Summation operation for [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.plus(arg: T) =
operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.plus(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it + arg }.wrap()
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.minus(arg: T) =
operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.minus(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it - arg }.wrap()
/* prod and div */
@ -78,11 +78,11 @@ operator fun <T : Any, F : Space<T>> BufferedNDElement<T, F>.minus(arg: T) =
/**
* Product operation for [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Ring<T>> BufferedNDElement<T, F>.times(arg: T) =
operator fun <T : Any, F : Ring<T>> BufferedNDElement<T, F>.times(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it * arg }.wrap()
/**
* Division operation between [BufferedNDElement] and single element
*/
operator fun <T : Any, F : Field<T>> BufferedNDElement<T, F>.div(arg: T) =
operator fun <T : Any, F : Field<T>> BufferedNDElement<T, F>.div(arg: T): NDElement<T, F, NDBuffer<T>> =
context.map(this) { it / arg }.wrap()

19
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/Buffers.kt
View File

@ -15,22 +15,22 @@ typealias MutableBufferFactory<T> = (Int, (Int) -> T) -> MutableBuffer<T>
interface Buffer<T> {
/**
* The size of the buffer
* The size of this buffer.
*/
val size: Int
/**
* Get element at given index
* Gets element at given index.
*/
operator fun get(index: Int): T
/**
* Iterate over all elements
* Iterates over all elements.
*/
operator fun iterator(): Iterator<T>
/**
* Check content eqiality with another buffer
* Checks content equality with another buffer.
*/
fun contentEquals(other: Buffer<*>): Boolean =
asSequence().mapIndexed { index, value -> value == other[index] }.all { it }
@ -124,10 +124,9 @@ inline class ListBuffer<T>(val list: List<T>) : Buffer<T> {
override fun iterator(): Iterator<T> = list.iterator()
}
fun <T> List<T>.asBuffer() = ListBuffer<T>(this)
fun <T> List<T>.asBuffer(): ListBuffer<T> = ListBuffer(this)
@Suppress("FunctionName")
inline fun <T> ListBuffer(size: Int, init: (Int) -> T) = List(size, init).asBuffer()
inline fun <T> ListBuffer(size: Int, init: (Int) -> T): ListBuffer<T> = List(size, init).asBuffer()
inline class MutableListBuffer<T>(val list: MutableList<T>) : MutableBuffer<T> {
@ -165,13 +164,13 @@ fun <T> Array<T>.asBuffer(): ArrayBuffer<T> = ArrayBuffer(this)
inline class ReadOnlyBuffer<T>(val buffer: MutableBuffer<T>) : Buffer<T> {
override val size: Int get() = buffer.size
override fun get(index: Int): T = buffer.get(index)
override fun get(index: Int): T = buffer[index]
override fun iterator() = buffer.iterator()
override fun iterator(): Iterator<T> = buffer.iterator()
}
/**
* A buffer with content calculated on-demand. The calculated contect is not stored, so it is recalculated on each call.
* A buffer with content calculated on-demand. The calculated content is not stored, so it is recalculated on each call.
* Useful when one needs single element from the buffer.
*/
class VirtualBuffer<T>(override val size: Int, private val generator: (Int) -> T) : Buffer<T> {

35
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/ComplexNDField.kt
View File

@ -17,8 +17,8 @@ class ComplexNDField(override val shape: IntArray) :
override val strides: Strides = DefaultStrides(shape)
override val elementContext: ComplexField get() = ComplexField
override val zero by lazy { produce { zero } }
override val one by lazy { produce { one } }
override val zero: ComplexNDElement by lazy { produce { zero } }
override val one: ComplexNDElement by lazy { produce { one } }
inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Complex): Buffer<Complex> =
Buffer.complex(size) { initializer(it) }
@ -69,23 +69,23 @@ class ComplexNDField(override val shape: IntArray) :
override fun NDBuffer<Complex>.toElement(): FieldElement<NDBuffer<Complex>, *, out BufferedNDField<Complex, ComplexField>> =
BufferedNDFieldElement(this@ComplexNDField, buffer)
override fun power(arg: NDBuffer<Complex>, pow: Number) = map(arg) { power(it, pow) }
override fun power(arg: NDBuffer<Complex>, pow: Number): ComplexNDElement = map(arg) { power(it, pow) }
override fun exp(arg: NDBuffer<Complex>) = map(arg) { exp(it) }
override fun exp(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { exp(it) }
override fun ln(arg: NDBuffer<Complex>) = map(arg) { ln(it) }
override fun ln(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { ln(it) }
override fun sin(arg: NDBuffer<Complex>) = map(arg) { sin(it) }
override fun sin(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { sin(it) }
override fun cos(arg: NDBuffer<Complex>) = map(arg) { cos(it) }
override fun cos(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { cos(it) }
override fun tan(arg: NDBuffer<Complex>): NDBuffer<Complex> = map(arg) { tan(it) }
override fun tan(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { tan(it) }
override fun asin(arg: NDBuffer<Complex>): NDBuffer<Complex> = map(arg) { asin(it) }
override fun asin(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { asin(it) }
override fun acos(arg: NDBuffer<Complex>): NDBuffer<Complex> = map(arg) {acos(it)}
override fun acos(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { acos(it) }
override fun atan(arg: NDBuffer<Complex>): NDBuffer<Complex> = map(arg) {atan(it)}
override fun atan(arg: NDBuffer<Complex>): ComplexNDElement = map(arg) { atan(it) }
}
@ -100,7 +100,7 @@ inline fun BufferedNDField<Complex, ComplexField>.produceInline(crossinline init
/**
* Map one [ComplexNDElement] using function with indexes
*/
inline fun ComplexNDElement.mapIndexed(crossinline transform: ComplexField.(index: IntArray, Complex) -> Complex) =
inline fun ComplexNDElement.mapIndexed(crossinline transform: ComplexField.(index: IntArray, Complex) -> Complex): ComplexNDElement =
context.produceInline { offset -> transform(strides.index(offset), buffer[offset]) }
/**
@ -114,7 +114,7 @@ inline fun ComplexNDElement.map(crossinline transform: ComplexField.(Complex) ->
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy
*/
operator fun Function1<Complex, Complex>.invoke(ndElement: ComplexNDElement) =
operator fun Function1<Complex, Complex>.invoke(ndElement: ComplexNDElement): ComplexNDElement =
ndElement.map { this@invoke(it) }
@ -123,19 +123,18 @@ operator fun Function1<Complex, Complex>.invoke(ndElement: ComplexNDElement) =
/**
* Summation operation for [BufferedNDElement] and single element
*/
operator fun ComplexNDElement.plus(arg: Complex) =
map { it + arg }
operator fun ComplexNDElement.plus(arg: Complex): ComplexNDElement = map { it + arg }
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
operator fun ComplexNDElement.minus(arg: Complex) =
operator fun ComplexNDElement.minus(arg: Complex): ComplexNDElement =
map { it - arg }
operator fun ComplexNDElement.plus(arg: Double) =
operator fun ComplexNDElement.plus(arg: Double): ComplexNDElement =
map { it + arg }
operator fun ComplexNDElement.minus(arg: Double) =
operator fun ComplexNDElement.minus(arg: Double): ComplexNDElement =
map { it - arg }
fun NDField.Companion.complex(vararg shape: Int): ComplexNDField = ComplexNDField(shape)

3
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/ExtendedNDField.kt
View File

@ -4,7 +4,6 @@ import scientifik.kmath.operations.ExtendedField
interface ExtendedNDField<T : Any, F : ExtendedField<T>, N : NDStructure<T>> : NDField<T, F, N>, ExtendedField<N>
///**
// * NDField that supports [ExtendedField] operations on its elements
// */
@ -36,5 +35,3 @@ interface ExtendedNDField<T : Any, F : ExtendedField<T>, N : NDStructure<T>> : N
// return produce { with(elementContext) { cos(arg[it]) } }
// }
//}

10
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/FlaggedBuffer.kt
View File

@ -19,11 +19,11 @@ interface FlaggedBuffer<T> : Buffer<T> {
/**
* The value is valid if all flags are down
*/
fun FlaggedBuffer<*>.isValid(index: Int) = getFlag(index) != 0.toByte()
fun FlaggedBuffer<*>.isValid(index: Int): Boolean = getFlag(index) != 0.toByte()
fun FlaggedBuffer<*>.hasFlag(index: Int, flag: ValueFlag) = (getFlag(index) and flag.mask) != 0.toByte()
fun FlaggedBuffer<*>.hasFlag(index: Int, flag: ValueFlag): Boolean = (getFlag(index) and flag.mask) != 0.toByte()
fun FlaggedBuffer<*>.isMissing(index: Int) = hasFlag(index, ValueFlag.MISSING)
fun FlaggedBuffer<*>.isMissing(index: Int): Boolean = hasFlag(index, ValueFlag.MISSING)
/**
* A real buffer which supports flags for each value like NaN or Missing
@ -45,8 +45,8 @@ class FlaggedRealBuffer(val values: DoubleArray, val flags: ByteArray) : Flagged
}
inline fun FlaggedRealBuffer.forEachValid(block: (Double) -> Unit) {
for(i in indices){
if(isValid(i)){
for (i in indices) {
if (isValid(i)) {
block(values[i])
}
}

5
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/IntBuffer.kt
View File

@ -9,12 +9,11 @@ inline class IntBuffer(val array: IntArray) : MutableBuffer<Int> {
array[index] = value
}
override fun iterator() = array.iterator()
override fun iterator(): IntIterator = array.iterator()
override fun copy(): MutableBuffer<Int> =
IntBuffer(array.copyOf())
}
fun IntArray.asBuffer() = IntBuffer(this)
fun IntArray.asBuffer(): IntBuffer = IntBuffer(this)

4
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/LongBuffer.kt
View File

@ -9,11 +9,11 @@ inline class LongBuffer(val array: LongArray) : MutableBuffer<Long> {
array[index] = value
}
override fun iterator() = array.iterator()
override fun iterator(): LongIterator = array.iterator()
override fun copy(): MutableBuffer<Long> =
LongBuffer(array.copyOf())
}
fun LongArray.asBuffer() = LongBuffer(this)
fun LongArray.asBuffer(): LongBuffer = LongBuffer(this)

12
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/MemoryBuffer.kt
View File

@ -3,7 +3,7 @@ package scientifik.kmath.structures
import scientifik.memory.*
/**
* A non-boxing buffer based on [ByteBuffer] storage
* A non-boxing buffer over [Memory] object.
*/
open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spec: MemorySpec<T>) : Buffer<T> {
@ -17,7 +17,7 @@ open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spe
companion object {
fun <T : Any> create(spec: MemorySpec<T>, size: Int) =
fun <T : Any> create(spec: MemorySpec<T>, size: Int): MemoryBuffer<T> =
MemoryBuffer(Memory.allocate(size * spec.objectSize), spec)
inline fun <T : Any> create(
@ -36,21 +36,21 @@ open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spe
class MutableMemoryBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) : MemoryBuffer<T>(memory, spec),
MutableBuffer<T> {
private val writer = memory.writer()
private val writer: MemoryWriter = memory.writer()
override fun set(index: Int, value: T) = writer.write(spec, spec.objectSize * index, value)
override fun set(index: Int, value: T): Unit = writer.write(spec, spec.objectSize * index, value)
override fun copy(): MutableBuffer<T> = MutableMemoryBuffer(memory.copy(), spec)
companion object {
fun <T : Any> create(spec: MemorySpec<T>, size: Int) =
fun <T : Any> create(spec: MemorySpec<T>, size: Int): MutableMemoryBuffer<T> =
MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec)
inline fun <T : Any> create(
spec: MemorySpec<T>,
size: Int,
crossinline initializer: (Int) -> T
) =
): MutableMemoryBuffer<T> =
MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach {
buffer[it] = initializer(it)

26
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/NDAlgebra.kt
View File

@ -56,7 +56,7 @@ interface NDAlgebra<T, C, N : NDStructure<T>> {
/**
* element-by-element invoke a function working on [T] on a [NDStructure]
*/
operator fun Function1<T, T>.invoke(structure: N) = map(structure) { value -> this@invoke(value) }
operator fun Function1<T, T>.invoke(structure: N): N = map(structure) { value -> this@invoke(value) }
companion object
}
@ -76,12 +76,12 @@ interface NDSpace<T, S : Space<T>, N : NDStructure<T>> : Space<N>, NDAlgebra<T,
override fun multiply(a: N, k: Number): N = map(a) { multiply(it, k) }
//TODO move to extensions after KEEP-176
operator fun N.plus(arg: T) = map(this) { value -> add(arg, value) }
operator fun N.plus(arg: T): N = map(this) { value -> add(arg, value) }
operator fun N.minus(arg: T) = map(this) { value -> add(arg, -value) }
operator fun N.minus(arg: T): N = map(this) { value -> add(arg, -value) }
operator fun T.plus(arg: N) = map(arg) { value -> add(this@plus, value) }
operator fun T.minus(arg: N) = map(arg) { value -> add(-this@minus, value) }
operator fun T.plus(arg: N): N = map(arg) { value -> add(this@plus, value) }
operator fun T.minus(arg: N): N = map(arg) { value -> add(-this@minus, value) }
companion object
}
@ -97,20 +97,18 @@ interface NDRing<T, R : Ring<T>, N : NDStructure<T>> : Ring<N>, NDSpace<T, R, N>
override fun multiply(a: N, b: N): N = combine(a, b) { aValue, bValue -> multiply(aValue, bValue) }
//TODO move to extensions after KEEP-176
operator fun N.times(arg: T) = map(this) { value -> multiply(arg, value) }
operator fun N.times(arg: T): N = map(this) { value -> multiply(arg, value) }
operator fun T.times(arg: N) = map(arg) { value -> multiply(this@times, value) }
operator fun T.times(arg: N): N = map(arg) { value -> multiply(this@times, value) }
companion object
}
/**
* Field for n-dimensional structures.
* @param shape - the list of dimensions of the array
* @param elementField - operations field defined on individual array element
*
* @param T - the type of the element contained in ND structure
* @param F - field of structure elements
* @param R - actual nd-element type of this field
*/
interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F, N> {
@ -120,9 +118,9 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F,
override fun divide(a: N, b: N): N = combine(a, b) { aValue, bValue -> divide(aValue, bValue) }
//TODO move to extensions after KEEP-176
operator fun N.div(arg: T) = map(this) { value -> divide(arg, value) }
operator fun N.div(arg: T): N = map(this) { value -> divide(arg, value) }
operator fun T.div(arg: N) = map(arg) { divide(it, this@div) }
operator fun T.div(arg: N): N = map(arg) { divide(it, this@div) }
companion object {
@ -131,7 +129,7 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F,
/**
* Create a nd-field for [Double] values or pull it from cache if it was created previously
*/
fun real(vararg shape: Int) = realNDFieldCache.getOrPut(shape) { RealNDField(shape) }
fun real(vararg shape: Int): RealNDField = realNDFieldCache.getOrPut(shape) { RealNDField(shape) }
/**
* Create a nd-field with boxing generic buffer
@ -140,7 +138,7 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F,
field: F,
vararg shape: Int,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing
) = BoxingNDField(shape, field, bufferFactory)
): BoxingNDField<T, F> = BoxingNDField(shape, field, bufferFactory)
/**
* Create a most suitable implementation for nd-field using reified class.

29
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/NDElement.kt
View File

@ -23,19 +23,23 @@ interface NDElement<T, C, N : NDStructure<T>> : NDStructure<T> {
/**
* Create a optimized NDArray of doubles
*/
fun real(shape: IntArray, initializer: RealField.(IntArray) -> Double = { 0.0 }) =
fun real(shape: IntArray, initializer: RealField.(IntArray) -> Double = { 0.0 }): RealNDElement =
NDField.real(*shape).produce(initializer)
fun real1D(dim: Int, initializer: (Int) -> Double = { _ -> 0.0 }) =
fun real1D(dim: Int, initializer: (Int) -> Double = { _ -> 0.0 }): RealNDElement =
real(intArrayOf(dim)) { initializer(it[0]) }
fun real2D(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }) =
fun real2D(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): RealNDElement =
real(intArrayOf(dim1, dim2)) { initializer(it[0], it[1]) }
fun real3D(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }) =
real(intArrayOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
fun real3D(
dim1: Int,
dim2: Int,
dim3: Int,
initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }
): RealNDElement = real(intArrayOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
/**
@ -62,16 +66,17 @@ interface NDElement<T, C, N : NDStructure<T>> : NDStructure<T> {
}
fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.mapIndexed(transform: C.(index: IntArray, T) -> T) =
fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.mapIndexed(transform: C.(index: IntArray, T) -> T): NDElement<T, C, N> =
context.mapIndexed(unwrap(), transform).wrap()
fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.map(transform: C.(T) -> T) = context.map(unwrap(), transform).wrap()
fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.map(transform: C.(T) -> T): NDElement<T, C, N> =
context.map(unwrap(), transform).wrap()
/**
* Element by element application of any operation on elements to the whole [NDElement]
*/
operator fun <T, C, N : NDStructure<T>> Function1<T, T>.invoke(ndElement: NDElement<T, C, N>) =
operator fun <T, C, N : NDStructure<T>> Function1<T, T>.invoke(ndElement: NDElement<T, C, N>): NDElement<T, C, N> =
ndElement.map { value -> this@invoke(value) }
/* plus and minus */
@ -79,13 +84,13 @@ operator fun <T, C, N : NDStructure<T>> Function1<T, T>.invoke(ndElement: NDElem
/**
* Summation operation for [NDElement] and single element
*/
operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.plus(arg: T) =
operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.plus(arg: T): NDElement<T, S, N> =
map { value -> arg + value }
/**
* Subtraction operation between [NDElement] and single element
*/
operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.minus(arg: T) =
operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.minus(arg: T): NDElement<T, S, N> =
map { value -> arg - value }
/* prod and div */
@ -93,13 +98,13 @@ operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.minus(arg:
/**
* Product operation for [NDElement] and single element
*/
operator fun <T, R : Ring<T>, N : NDStructure<T>> NDElement<T, R, N>.times(arg: T) =
operator fun <T, R : Ring<T>, N : NDStructure<T>> NDElement<T, R, N>.times(arg: T): NDElement<T, R, N> =
map { value -> arg * value }
/**
* Division operation between [NDElement] and single element
*/
operator fun <T, F : Field<T>, N : NDStructure<T>> NDElement<T, F, N>.div(arg: T) =
operator fun <T, F : Field<T>, N : NDStructure<T>> NDElement<T, F, N>.div(arg: T): NDElement<T, F, N> =
map { value -> arg / value }

39
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/NDStructure.kt
View File

@ -8,7 +8,7 @@ interface NDStructure<T> {
val shape: IntArray
val dimension get() = shape.size
val dimension: Int get() = shape.size
operator fun get(index: IntArray): T
@ -44,32 +44,49 @@ interface NDStructure<T> {
strides: Strides,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
initializer: (IntArray) -> T
) =
): BufferNDStructure<T> =
BufferNDStructure(strides, bufferFactory(strides.linearSize) { i -> initializer(strides.index(i)) })
/**
* Inline create NDStructure with non-boxing buffer implementation if it is possible
*/
inline fun <reified T : Any> auto(strides: Strides, crossinline initializer: (IntArray) -> T) =
inline fun <reified T : Any> auto(
strides: Strides,
crossinline initializer: (IntArray) -> T
): BufferNDStructure<T> =
BufferNDStructure(strides, Buffer.auto(strides.linearSize) { i -> initializer(strides.index(i)) })
inline fun <T : Any> auto(type: KClass<T>, strides: Strides, crossinline initializer: (IntArray) -> T) =
inline fun <T : Any> auto(
type: KClass<T>,
strides: Strides,
crossinline initializer: (IntArray) -> T
): BufferNDStructure<T> =
BufferNDStructure(strides, Buffer.auto(type, strides.linearSize) { i -> initializer(strides.index(i)) })
fun <T> build(
shape: IntArray,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
initializer: (IntArray) -> T
) = build(DefaultStrides(shape), bufferFactory, initializer)
): BufferNDStructure<T> = build(DefaultStrides(shape), bufferFactory, initializer)
inline fun <reified T : Any> auto(shape: IntArray, crossinline initializer: (IntArray) -> T) =
inline fun <reified T : Any> auto(
shape: IntArray,
crossinline initializer: (IntArray) -> T
): BufferNDStructure<T> =
auto(DefaultStrides(shape), initializer)
@JvmName("autoVarArg")
inline fun <reified T : Any> auto(vararg shape: Int, crossinline initializer: (IntArray) -> T) =
inline fun <reified T : Any> auto(
vararg shape: Int,
crossinline initializer: (IntArray) -> T
): BufferNDStructure<T> =
auto(DefaultStrides(shape), initializer)
inline fun <T : Any> auto(type: KClass<T>, vararg shape: Int, crossinline initializer: (IntArray) -> T) =
inline fun <T : Any> auto(
type: KClass<T>,
vararg shape: Int,
crossinline initializer: (IntArray) -> T
): BufferNDStructure<T> =
auto(type, DefaultStrides(shape), initializer)
}
}
@ -128,7 +145,7 @@ class DefaultStrides private constructor(override val shape: IntArray) : Strides
/**
* Strides for memory access
*/
override val strides by lazy {
override val strides: List<Int> by lazy {
sequence {
var current = 1
yield(1)
@ -238,7 +255,7 @@ inline fun <T, reified R : Any> NDStructure<T>.mapToBuffer(
}
/**
* Mutable ND buffer based on linear [autoBuffer]
* Mutable ND buffer based on linear [MutableBuffer].
*/
class MutableBufferNDStructure<T>(
override val strides: Strides,
@ -251,7 +268,7 @@ class MutableBufferNDStructure<T>(
}
}
override fun set(index: IntArray, value: T) = buffer.set(strides.offset(index), value)
override fun set(index: IntArray, value: T): Unit = buffer.set(strides.offset(index), value)
}
inline fun <reified T : Any> NDStructure<T>.combine(

4
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/RealBuffer.kt
View File

@ -9,7 +9,7 @@ inline class RealBuffer(val array: DoubleArray) : MutableBuffer<Double> {
array[index] = value
}
override fun iterator() = array.iterator()
override fun iterator(): DoubleIterator = array.iterator()
override fun copy(): MutableBuffer<Double> =
RealBuffer(array.copyOf())
@ -31,4 +31,4 @@ val MutableBuffer<out Double>.array: DoubleArray
DoubleArray(size) { get(it) }
}
fun DoubleArray.asBuffer() = RealBuffer(this)
fun DoubleArray.asBuffer(): RealBuffer = RealBuffer(this)

24
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/RealNDField.kt
View File

@ -12,8 +12,8 @@ class RealNDField(override val shape: IntArray) :
override val strides: Strides = DefaultStrides(shape)
override val elementContext: RealField get() = RealField
override val zero by lazy { produce { zero } }
override val one by lazy { produce { one } }
override val zero: RealNDElement by lazy { produce { zero } }
override val one: RealNDElement by lazy { produce { one } }
inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Double): Buffer<Double> =
RealBuffer(DoubleArray(size) { initializer(it) })
@ -64,15 +64,15 @@ class RealNDField(override val shape: IntArray) :
override fun NDBuffer<Double>.toElement(): FieldElement<NDBuffer<Double>, *, out BufferedNDField<Double, RealField>> =
BufferedNDFieldElement(this@RealNDField, buffer)
override fun power(arg: NDBuffer<Double>, pow: Number) = map(arg) { power(it, pow) }
override fun power(arg: NDBuffer<Double>, pow: Number): RealNDElement = map(arg) { power(it, pow) }
override fun exp(arg: NDBuffer<Double>) = map(arg) { exp(it) }
override fun exp(arg: NDBuffer<Double>): RealNDElement = map(arg) { exp(it) }
override fun ln(arg: NDBuffer<Double>) = map(arg) { ln(it) }
override fun ln(arg: NDBuffer<Double>): RealNDElement = map(arg) { ln(it) }
override fun sin(arg: NDBuffer<Double>) = map(arg) { sin(it) }
override fun sin(arg: NDBuffer<Double>): RealNDElement = map(arg) { sin(it) }
override fun cos(arg: NDBuffer<Double>) = map(arg) { cos(it) }
override fun cos(arg: NDBuffer<Double>): RealNDElement = map(arg) { cos(it) }
override fun tan(arg: NDBuffer<Double>): NDBuffer<Double> = map(arg) { tan(it) }
@ -95,7 +95,7 @@ inline fun BufferedNDField<Double, RealField>.produceInline(crossinline initiali
/**
* Map one [RealNDElement] using function with indexes
*/
inline fun RealNDElement.mapIndexed(crossinline transform: RealField.(index: IntArray, Double) -> Double) =
inline fun RealNDElement.mapIndexed(crossinline transform: RealField.(index: IntArray, Double) -> Double): RealNDElement =
context.produceInline { offset -> transform(strides.index(offset), buffer[offset]) }
/**
@ -107,9 +107,9 @@ inline fun RealNDElement.map(crossinline transform: RealField.(Double) -> Double
}
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy
* Element by element application of any operation on elements to the whole array. Just like in numpy.
*/
operator fun Function1<Double, Double>.invoke(ndElement: RealNDElement) =
operator fun Function1<Double, Double>.invoke(ndElement: RealNDElement): RealNDElement =
ndElement.map { this@invoke(it) }
@ -118,13 +118,13 @@ operator fun Function1<Double, Double>.invoke(ndElement: RealNDElement) =
/**
* Summation operation for [BufferedNDElement] and single element
*/
operator fun RealNDElement.plus(arg: Double) =
operator fun RealNDElement.plus(arg: Double): RealNDElement =
map { it + arg }
/**
* Subtraction operation between [BufferedNDElement] and single element
*/
operator fun RealNDElement.minus(arg: Double) =
operator fun RealNDElement.minus(arg: Double): RealNDElement =
map { it - arg }
/**

5
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/ShortBuffer.kt
View File

@ -9,12 +9,11 @@ inline class ShortBuffer(val array: ShortArray) : MutableBuffer<Short> {
array[index] = value
}
override fun iterator() = array.iterator()
override fun iterator(): ShortIterator = array.iterator()
override fun copy(): MutableBuffer<Short> =
ShortBuffer(array.copyOf())
}
fun ShortArray.asBuffer() = ShortBuffer(this)
fun ShortArray.asBuffer(): ShortBuffer = ShortBuffer(this)

19
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/ShortNDRing.kt
View File

@ -12,8 +12,8 @@ class ShortNDRing(override val shape: IntArray) :
override val strides: Strides = DefaultStrides(shape)
override val elementContext: ShortRing get() = ShortRing
override val zero by lazy { produce { ShortRing.zero } }
override val one by lazy { produce { ShortRing.one } }
override val zero: ShortNDElement by lazy { produce { zero } }
override val one: ShortNDElement by lazy { produce { one } }
inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Short): Buffer<Short> =
ShortBuffer(ShortArray(size) { initializer(it) })
@ -40,6 +40,7 @@ class ShortNDRing(override val shape: IntArray) :
transform: ShortRing.(index: IntArray, Short) -> Short
): ShortNDElement {
check(arg)
return BufferedNDRingElement(
this,
buildBuffer(arg.strides.linearSize) { offset ->
@ -67,7 +68,7 @@ class ShortNDRing(override val shape: IntArray) :
/**
* Fast element production using function inlining
* Fast element production using function inlining.
*/
inline fun BufferedNDRing<Short, ShortRing>.produceInline(crossinline initializer: ShortRing.(Int) -> Short): ShortNDElement {
val array = ShortArray(strides.linearSize) { offset -> ShortRing.initializer(offset) }
@ -75,22 +76,22 @@ inline fun BufferedNDRing<Short, ShortRing>.produceInline(crossinline initialize
}
/**
* Element by element application of any operation on elements to the whole array. Just like in numpy
* Element by element application of any operation on elements to the whole array.
*/
operator fun Function1<Short, Short>.invoke(ndElement: ShortNDElement) =
operator fun Function1<Short, Short>.invoke(ndElement: ShortNDElement): ShortNDElement =
ndElement.context.produceInline { i -> invoke(ndElement.buffer[i]) }
/* plus and minus */
/**
* Summation operation for [StridedNDFieldElement] and single element
* Summation operation for [ShortNDElement] and single element.
*/
operator fun ShortNDElement.plus(arg: Short) =
operator fun ShortNDElement.plus(arg: Short): ShortNDElement =
context.produceInline { i -> (buffer[i] + arg).toShort() }
/**
* Subtraction operation between [StridedNDFieldElement] and single element
* Subtraction operation between [ShortNDElement] and single element.
*/
operator fun ShortNDElement.minus(arg: Short) =
operator fun ShortNDElement.minus(arg: Short): ShortNDElement =
context.produceInline { i -> (buffer[i] - arg).toShort() }

6
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/Structure1D.kt
View File

@ -17,7 +17,7 @@ interface Structure1D<T> : NDStructure<T>, Buffer<T> {
/**
* A 1D wrapper for nd-structure
*/
private inline class Structure1DWrapper<T>(val structure: NDStructure<T>) : Structure1D<T>{
private inline class Structure1DWrapper<T>(val structure: NDStructure<T>) : Structure1D<T> {
override val shape: IntArray get() = structure.shape
override val size: Int get() = structure.shape[0]
@ -39,14 +39,14 @@ private inline class Buffer1DWrapper<T>(val buffer: Buffer<T>) : Structure1D<T>
override fun elements(): Sequence<Pair<IntArray, T>> =
asSequence().mapIndexed { index, value -> intArrayOf(index) to value }
override fun get(index: Int): T = buffer.get(index)
override fun get(index: Int): T = buffer[index]
}
/**
* Represent a [NDStructure] as [Structure1D]. Throw error in case of dimension mismatch
*/
fun <T> NDStructure<T>.as1D(): Structure1D<T> = if (shape.size == 1) {
if( this is NDBuffer){
if (this is NDBuffer) {
Buffer1DWrapper(this.buffer)
} else {
Structure1DWrapper(this)

4
kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/Structure2D.kt
View File

@ -32,9 +32,7 @@ interface Structure2D<T> : NDStructure<T> {
}
}
companion object {
}
companion object
}
/**

4
kmath-core/src/commonTest/kotlin/scientifik/kmath/expressions/ExpressionFieldTest.kt
View File

@ -31,7 +31,7 @@ class ExpressionFieldTest {
@Test
fun separateContext() {
fun <T> FunctionalExpressionField<T,*>.expression(): Expression<T> {
fun <T> FunctionalExpressionField<T, *>.expression(): Expression<T> {
val x = variable("x")
return x * x + 2 * x + one
}
@ -42,7 +42,7 @@ class ExpressionFieldTest {
@Test
fun valueExpression() {
val expressionBuilder: FunctionalExpressionField<Double,*>.() -> Expression<Double> = {
val expressionBuilder: FunctionalExpressionField<Double, *>.() -> Expression<Double> = {
val x = variable("x")
x * x + 2 * x + one
}

10
kmath-core/src/commonTest/kotlin/scientifik/kmath/linear/MatrixTest.kt
View File

@ -49,17 +49,17 @@ class MatrixTest {
@Test
fun test2DDot() {
val firstMatrix = NDStructure.auto(2,3){ (i, j) -> (i + j).toDouble() }.as2D()
val secondMatrix = NDStructure.auto(3,2){ (i, j) -> (i + j).toDouble() }.as2D()
val firstMatrix = NDStructure.auto(2, 3) { (i, j) -> (i + j).toDouble() }.as2D()
val secondMatrix = NDStructure.auto(3, 2) { (i, j) -> (i + j).toDouble() }.as2D()
MatrixContext.real.run {
// val firstMatrix = produce(2, 3) { i, j -> (i + j).toDouble() }
// val secondMatrix = produce(3, 2) { i, j -> (i + j).toDouble() }
val result = firstMatrix dot secondMatrix
assertEquals(2, result.rowNum)
assertEquals(2, result.colNum)
assertEquals(8.0, result[0,1])
assertEquals(8.0, result[1,0])
assertEquals(14.0, result[1,1])
assertEquals(8.0, result[0, 1])
assertEquals(8.0, result[1, 0])
assertEquals(14.0, result[1, 1])
}
}
}

7
kmath-core/src/commonTest/kotlin/scientifik/kmath/misc/AutoDiffTest.kt
View File

@ -8,10 +8,10 @@ import kotlin.test.assertEquals
import kotlin.test.assertTrue
class AutoDiffTest {
fun Variable(int: Int): Variable<Double> = Variable(int.toDouble())
fun Variable(int: Int) = Variable(int.toDouble())
fun deriv(body: AutoDiffField<Double, RealField>.() -> Variable<Double>) = RealField.deriv(body)
fun deriv(body: AutoDiffField<Double, RealField>.() -> Variable<Double>): DerivationResult<Double> =
RealField.deriv(body)
@Test
fun testPlusX2() {
@ -178,5 +178,4 @@ class AutoDiffTest {
private fun assertApprox(a: Double, b: Double) {
if ((a - b) > 1e-10) assertEquals(a, b)
}
}

1
kmath-core/src/commonTest/kotlin/scientifik/kmath/operations/BigIntAlgebraTest.kt
View File

@ -47,4 +47,3 @@ class BigIntAlgebraTest {
}
}

2
kmath-core/src/commonTest/kotlin/scientifik/kmath/operations/BigIntConstructorTest.kt
View File

@ -19,7 +19,7 @@ class BigIntConstructorTest {
@Test
fun testConstructor_0xffffffffaL() {
val x = -0xffffffffaL.toBigInt()
val x = (-0xffffffffaL).toBigInt()
val y = uintArrayOf(0xfffffffaU, 0xfU).toBigInt(-1)
assertEquals(x, y)
}

2
kmath-core/src/commonTest/kotlin/scientifik/kmath/operations/BigIntConversionsTest.kt
View File

@ -19,7 +19,7 @@ class BigIntConversionsTest {
@Test
fun testToString_0x17ead2ffffd() {
val x = -0x17ead2ffffdL.toBigInt()
val x = (-0x17ead2ffffdL).toBigInt()
assertEquals("-0x17ead2ffffd", x.toString())
}

22
kmath-core/src/commonTest/kotlin/scientifik/kmath/operations/BigIntOperationsTest.kt
View File

@ -31,7 +31,7 @@ class BigIntOperationsTest {
@Test
fun testUnaryMinus() {
val x = 1234.toBigInt()
val y = -1234.toBigInt()
val y = (-1234).toBigInt()
assertEquals(-x, y)
}
@ -48,18 +48,18 @@ class BigIntOperationsTest {
@Test
fun testMinus__2_1() {
val x = -2.toBigInt()
val x = (-2).toBigInt()
val y = 1.toBigInt()
val res = x - y
val sum = -3.toBigInt()
val sum = (-3).toBigInt()
assertEquals(sum, res)
}
@Test
fun testMinus___2_1() {
val x = -2.toBigInt()
val x = (-2).toBigInt()
val y = 1.toBigInt()
val res = -x - y
@ -74,7 +74,7 @@ class BigIntOperationsTest {
val y = 0xffffffffaL.toBigInt()
val res = x - y
val sum = -0xfffffcfc1L.toBigInt()
val sum = (-0xfffffcfc1L).toBigInt()
assertEquals(sum, res)
}
@ -92,11 +92,11 @@ class BigIntOperationsTest {
@Test
fun testMultiply__2_3() {
val x = -2.toBigInt()
val x = (-2).toBigInt()
val y = 3.toBigInt()
val res = x * y
val prod = -6.toBigInt()
val prod = (-6).toBigInt()
assertEquals(prod, res)
}
@ -129,7 +129,7 @@ class BigIntOperationsTest {
val y = -0xfff456
val res = x * y
val prod = -0xffe579ad5dc2L.toBigInt()
val prod = (-0xffe579ad5dc2L).toBigInt()
assertEquals(prod, res)
}
@ -259,7 +259,7 @@ class BigIntOperationsTest {
val y = -3
val res = x / y
val div = -6.toBigInt()
val div = (-6).toBigInt()
assertEquals(div, res)
}
@ -267,10 +267,10 @@ class BigIntOperationsTest {
@Test
fun testBigDivision_20__3() {
val x = 20.toBigInt()
val y = -3.toBigInt()
val y = (-3).toBigInt()
val res = x / y
val div = -6.toBigInt()
val div = (-6).toBigInt()
assertEquals(div, res)
}

4
kmath-core/src/commonTest/kotlin/scientifik/kmath/structures/NumberNDFieldTest.kt
View File

@ -8,8 +8,8 @@ import kotlin.test.Test
import kotlin.test.assertEquals
class NumberNDFieldTest {
val array1 = real2D(3, 3) { i, j -> (i + j).toDouble() }
val array2 = real2D(3, 3) { i, j -> (i - j).toDouble() }
val array1: RealNDElement = real2D(3, 3) { i, j -> (i + j).toDouble() }
val array2: RealNDElement = real2D(3, 3) { i, j -> (i - j).toDouble() }
@Test
fun testSum() {