forked from kscience/kmath
Removed GenericNDField. Additional cleanup
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b883455bd3
commit
12b343e905
@ -9,7 +9,7 @@ fun main(args: Array<String>) {
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val bufferedField = NDField.auto(intArrayOf(dim, dim), RealField)
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val bufferedField = NDField.auto(intArrayOf(dim, dim), RealField)
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val specializedField = NDField.real(intArrayOf(dim, dim))
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val specializedField = NDField.real(intArrayOf(dim, dim))
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val genericField = NDField.generic(intArrayOf(dim, dim), RealField)
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val genericField = NDField.buffered(intArrayOf(dim, dim), RealField)
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val lazyNDField = NDField.lazy(intArrayOf(dim, dim), RealField)
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val lazyNDField = NDField.lazy(intArrayOf(dim, dim), RealField)
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// val action: NDField<Double, DoubleField, NDStructure<Double>>.() -> Unit = {
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// val action: NDField<Double, DoubleField, NDStructure<Double>>.() -> Unit = {
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@ -75,7 +75,7 @@ fun main(args: Array<String>) {
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val genericTime = measureTimeMillis {
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val genericTime = measureTimeMillis {
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//genericField.run(action)
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//genericField.run(action)
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genericField.run {
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genericField.run {
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var res = one
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var res: NDBuffer<Double> = one
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repeat(n) {
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repeat(n) {
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res += 1.0
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res += 1.0
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}
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}
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@ -32,6 +32,6 @@ fun ClosedFloatingPointRange<Double>.toSequence(step: Double): Sequence<Double>
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* Convert double range to array of evenly spaced doubles, where the size of array equals [numPoints]
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* Convert double range to array of evenly spaced doubles, where the size of array equals [numPoints]
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*/
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*/
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fun ClosedFloatingPointRange<Double>.toGrid(numPoints: Int): DoubleArray {
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fun ClosedFloatingPointRange<Double>.toGrid(numPoints: Int): DoubleArray {
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if (numPoints < 2) error("Can't generic grid with less than two points")
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if (numPoints < 2) error("Can't buffered grid with less than two points")
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return DoubleArray(numPoints) { i -> start + (endInclusive - start) / (numPoints - 1) * i }
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return DoubleArray(numPoints) { i -> start + (endInclusive - start) / (numPoints - 1) * i }
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}
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}
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@ -35,24 +35,22 @@ object NDElements {
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/**
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/**
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* Simple boxing NDArray
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* Simple boxing NDArray
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*/
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*/
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fun <T : Any, F : Field<T>> generic(
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fun <T : Any, F : Field<T>> buffered(
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shape: IntArray,
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shape: IntArray,
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field: F,
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field: F,
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initializer: F.(IntArray) -> T
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initializer: F.(IntArray) -> T
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): GenericNDElement<T, F> {
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): BufferNDElement<T, F> {
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val ndField = GenericNDField(shape, field)
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val ndField = BufferNDField(shape, field, ::boxingBuffer)
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val structure = ndStructure(shape) { index -> field.initializer(index) }
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return ndField.produce(initializer)
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return GenericNDElement(ndField, structure)
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}
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}
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inline fun <reified T : Any, F : Field<T>> inline(
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inline fun <reified T : Any, F : Field<T>> auto(
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shape: IntArray,
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shape: IntArray,
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field: F,
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field: F,
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noinline initializer: F.(IntArray) -> T
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noinline initializer: F.(IntArray) -> T
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): GenericNDElement<T, F> {
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): BufferNDElement<T, F> {
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val ndField = GenericNDField(shape, field)
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val ndField = NDField.auto(shape, field)
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val structure = ndStructure(shape, ::autoBuffer) { index -> field.initializer(index) }
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return ndField.produce(initializer)
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return GenericNDElement(ndField, structure)
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}
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}
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}
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}
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@ -22,43 +22,10 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N> {
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val elementField: F
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val elementField: F
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fun produce(initializer: F.(IntArray) -> T): N
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fun produce(initializer: F.(IntArray) -> T): N
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fun map(arg: N, transform: F.(T) -> T): N
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fun map(arg: N, transform: F.(T) -> T): N
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fun mapIndexed(arg: N, transform: F.(index: IntArray, T) -> T): N
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fun mapIndexed(arg: N, transform: F.(index: IntArray, T) -> T): N
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fun combine(a: N, b: N, transform: F.(T, T) -> T): N
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fun combine(a: N, b: N, transform: F.(T, T) -> T): N
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/**
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* Element by element application of any operation on elements to the whole array. Just like in numpy
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*/
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operator fun Function1<T, T>.invoke(structure: N): N
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/**
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* Summation operation for [NDElements] and single element
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*/
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operator fun N.plus(arg: T): N
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/**
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* Subtraction operation between [NDElements] and single element
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*/
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operator fun N.minus(arg: T): N
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/**
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* Product operation for [NDElements] and single element
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*/
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operator fun N.times(arg: T): N
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/**
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* Division operation between [NDElements] and single element
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*/
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operator fun N.div(arg: T): N
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operator fun T.plus(arg: N): N
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operator fun T.minus(arg: N): N
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operator fun T.times(arg: N): N
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operator fun T.div(arg: N): N
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companion object {
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companion object {
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/**
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/**
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* Create a nd-field for [Double] values
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* Create a nd-field for [Double] values
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@ -68,14 +35,14 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N> {
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/**
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/**
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* Create a nd-field with boxing generic buffer
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* Create a nd-field with boxing generic buffer
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*/
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*/
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fun <T : Any, F : Field<T>> generic(shape: IntArray, field: F) = GenericNDField(shape, field)
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fun <T : Any, F : Field<T>> buffered(shape: IntArray, field: F) =
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BufferNDField(shape, field, ::boxingBuffer)
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/**
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/**
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* Create a most suitable implementation for nd-field using reified class.
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* Create a most suitable implementation for nd-field using reified class.
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*/
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*/
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inline fun <reified T : Any, F : Field<T>> auto(shape: IntArray, field: F): BufferNDField<T, F> {
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inline fun <reified T : Any, F : Field<T>> auto(shape: IntArray, field: F) =
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return BufferNDField(shape, field, ::autoBuffer)
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BufferNDField(shape, field, ::autoBuffer)
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}
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}
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}
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}
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}
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@ -88,16 +55,16 @@ abstract class AbstractNDField<T, F : Field<T>, N : NDStructure<T>>(
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override val one: N by lazy { produce { one } }
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override val one: N by lazy { produce { one } }
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final override operator fun Function1<T, T>.invoke(structure: N) = map(structure) { value -> this@invoke(value) }
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operator fun Function1<T, T>.invoke(structure: N) = map(structure) { value -> this@invoke(value) }
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final override operator fun N.plus(arg: T) = map(this) { value -> elementField.run { arg + value } }
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operator fun N.plus(arg: T) = map(this) { value -> elementField.run { arg + value } }
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final override operator fun N.minus(arg: T) = map(this) { value -> elementField.run { arg - value } }
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operator fun N.minus(arg: T) = map(this) { value -> elementField.run { arg - value } }
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final override operator fun N.times(arg: T) = map(this) { value -> elementField.run { arg * value } }
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operator fun N.times(arg: T) = map(this) { value -> elementField.run { arg * value } }
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final override operator fun N.div(arg: T) = map(this) { value -> elementField.run { arg / value } }
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operator fun N.div(arg: T) = map(this) { value -> elementField.run { arg / value } }
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final override operator fun T.plus(arg: N) = arg + this
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operator fun T.plus(arg: N) = arg + this
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final override operator fun T.minus(arg: N) = arg - this
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operator fun T.minus(arg: N) = arg - this
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final override operator fun T.times(arg: N) = arg * this
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operator fun T.times(arg: N) = arg * this
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final override operator fun T.div(arg: N) = arg / this
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operator fun T.div(arg: N) = arg / this
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/**
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/**
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@ -136,22 +103,3 @@ abstract class AbstractNDField<T, F : Field<T>, N : NDStructure<T>>(
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}
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}
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}
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}
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}
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}
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class GenericNDField<T : Any, F : Field<T>>(
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shape: IntArray,
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elementField: F,
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val bufferFactory: BufferFactory<T> = ::boxingBuffer
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) : AbstractNDField<T, F, NDStructure<T>>(shape, elementField) {
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override fun produce(initializer: F.(IntArray) -> T): NDStructure<T> =
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ndStructure(shape, bufferFactory) { elementField.initializer(it) }
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override fun map(arg: NDStructure<T>, transform: F.(T) -> T): NDStructure<T> =
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produce { index -> transform(arg.get(index)) }
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override fun mapIndexed(arg: NDStructure<T>, transform: F.(index: IntArray, T) -> T): NDStructure<T> =
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produce { index -> transform(index, arg.get(index)) }
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override fun combine(a: NDStructure<T>, b: NDStructure<T>, transform: F.(T, T) -> T): NDStructure<T> =
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produce { index -> transform(a[index], b[index]) }
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}
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@ -9,7 +9,7 @@ class LazyNDFieldTest {
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@Test
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@Test
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fun testLazyStructure() {
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fun testLazyStructure() {
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var counter = 0
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var counter = 0
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val regularStructure = NDField.generic(intArrayOf(2, 2, 2), IntField).produce { it[0] + it[1] - it[2] }
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val regularStructure = NDField.auto(intArrayOf(2, 2, 2), IntField).produce { it[0] + it[1] - it[2] }
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val result = (regularStructure.lazy(IntField) + 2).map {
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val result = (regularStructure.lazy(IntField) + 2).map {
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counter++
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counter++
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it * it
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it * it
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