forked from kscience/kmath
Merge remote-tracking branch 'upstream/zelenyy' into zelenyy
# Conflicts: # kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/CreationRoutines.kt
This commit is contained in:
commit
ba230d0de1
@ -14,7 +14,7 @@ class ShapeMismatchException(val expected: IntArray, val actual: IntArray) : Run
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/**
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* The base interface for all nd-algebra implementations
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* @param T the type of nd-structure element
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* @param C the type of the context
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* @param C the type of the element context
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* @param N the type of the structure
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*/
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interface NDAlgebra<T, C, N : NDStructure<T>> {
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@ -112,10 +112,13 @@ interface NDField<T, F : Field<T>, N : NDStructure<T>> : Field<N>, NDRing<T, F,
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operator fun T.div(arg: N) = map(arg) { divide(it, this@div) }
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companion object {
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private val realNDFieldCache = HashMap<IntArray, RealNDField>()
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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 or pull it from cache if it was created previously
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*/
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fun real(shape: IntArray) = RealNDField(shape)
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fun real(shape: IntArray) = realNDFieldCache.getOrPut(shape){RealNDField(shape)}
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/**
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* Create a nd-field with boxing generic buffer
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@ -7,6 +7,9 @@ import scientifik.kmath.operations.Space
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/**
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* The root for all [NDStructure] based algebra elements. Does not implement algebra element root because of problems with recursive self-types
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* @param T the type of the element of the structure
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* @param C the type of the context for the element
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* @param N the type of the underlying [NDStructure]
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*/
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interface NDElement<T, C, N : NDStructure<T>> : NDStructure<T> {
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@ -16,9 +19,6 @@ interface NDElement<T, C, N : NDStructure<T>> : NDStructure<T> {
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fun N.wrap(): NDElement<T, C, N>
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fun mapIndexed(transform: C.(index: IntArray, T) -> T) = context.mapIndexed(unwrap(), transform).wrap()
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fun map(transform: C.(T) -> T) = context.map(unwrap(), transform).wrap()
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companion object {
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/**
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* Create a optimized NDArray of doubles
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@ -61,10 +61,17 @@ interface NDElement<T, C, N : NDStructure<T>> : NDStructure<T> {
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}
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}
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fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.mapIndexed(transform: C.(index: IntArray, T) -> T) =
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context.mapIndexed(unwrap(), transform).wrap()
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fun <T, C, N : NDStructure<T>> NDElement<T, C, N>.map(transform: C.(T) -> T) = context.map(unwrap(), transform).wrap()
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/**
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* Element by element application of any operation on elements to the whole [NDElement]
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*/
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operator fun <T, C> Function1<T, T>.invoke(ndElement: NDElement<T, C, *>) =
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operator fun <T, C, N : NDStructure<T>> Function1<T, T>.invoke(ndElement: NDElement<T, C, N>) =
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ndElement.map { value -> this@invoke(value) }
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/* plus and minus */
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@ -72,13 +79,13 @@ operator fun <T, C> Function1<T, T>.invoke(ndElement: NDElement<T, C, *>) =
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/**
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* Summation operation for [NDElement] and single element
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*/
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operator fun <T, S : Space<T>> NDElement<T, S, *>.plus(arg: T) =
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operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.plus(arg: T) =
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map { value -> arg + value }
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/**
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* Subtraction operation between [NDElement] and single element
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*/
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operator fun <T, S : Space<T>> NDElement<T, S, *>.minus(arg: T) =
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operator fun <T, S : Space<T>, N : NDStructure<T>> NDElement<T, S, N>.minus(arg: T) =
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map { value -> arg - value }
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/* prod and div */
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@ -86,13 +93,13 @@ operator fun <T, S : Space<T>> NDElement<T, S, *>.minus(arg: T) =
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/**
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* Product operation for [NDElement] and single element
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*/
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operator fun <T, R : Ring<T>> NDElement<T, R, *>.times(arg: T) =
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operator fun <T, R : Ring<T>, N : NDStructure<T>> NDElement<T, R, N>.times(arg: T) =
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map { value -> arg * value }
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/**
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* Division operation between [NDElement] and single element
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*/
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operator fun <T, F : Field<T>> NDElement<T, F, *>.div(arg: T) =
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operator fun <T, F : Field<T>, N : NDStructure<T>> NDElement<T, F, N>.div(arg: T) =
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map { value -> arg / value }
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@ -1,14 +1,19 @@
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package scientifik.kmath.structures
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import scientifik.kmath.operations.RealField.power
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import kotlin.math.*
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import kotlin.math.ceil
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import kotlin.math.log
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import kotlin.math.min
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import kotlin.math.sign
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object RealFactory {
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/**
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* Create a NDArray filled with ones
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/**
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* Numpy-like factories for [RealNDElement]
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*/
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fun ones(vararg shape: Int) = NDElement.real(shape) { 1.0 }
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object RealNDFactory {
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/**
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* Get a [RealNDElement] filled with [RealNDField.one]. Due to caching all instances with the same shape point to the same object
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*/
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fun ones(vararg shape: Int) = NDField.real(shape).one
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/**
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* Create a 2D NDArray, with ones on the diagonal and zeros elsewhere.
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@ -31,40 +36,37 @@ object RealFactory {
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* Return evenly spaced values within a given interval.
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*
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* Values are generated within the half-open interval [start, stop) (in other words, the interval including start but excluding stop).
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* @param range use it like:
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* (start..stop) to step
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*/
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fun range(range: Pair<ClosedFloatingPointRange<Double>, Double>) =
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NDElement.real1D(ceil((range.first.endInclusive - range.first.start) / range.second).toInt()) { i -> range.first.start + i * range.second }
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fun range(range: ClosedFloatingPointRange<Double>, step: Double = 1.0) =
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NDElement.real1D(ceil((range.endInclusive - range.start) / step).toInt()) { i ->
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range.start + i * step
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}
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/**
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* Return evenly spaced numbers over a specified interval.
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* @param range use it like:
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* (start..stop) to number
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* start is starting value, finaly value depend from endPoint parameter
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* @param range start is starting value, final value depend from endPoint parameter
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* @param endPoint If True, right boundary of range is the last sample. Otherwise, it is not included.
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*/
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fun linSpace(
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range: Pair<ClosedFloatingPointRange<Double>, Int>,
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fun linspace(
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range: ClosedFloatingPointRange<Double>,
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num: Int = 100,
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endPoint: Boolean = true
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): Pair<RealNDElement, Double> {
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val div = if (endPoint) (range.second - 1) else range.second
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val delta = range.first.start - range.first.endInclusive
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if (range.second > 1) {
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): RealNDElement {
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val div = if (endPoint) (num - 1) else num
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val delta = range.start - range.endInclusive
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return if (num > 1) {
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val step = delta / div
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if (step == 0.0) {
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error("Bad ranges: step = $step")
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}
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val result = NDElement.real1D(range.second) {
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if (endPoint and (it == range.second - 1)) {
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range.first.endInclusive
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NDElement.real1D(num) {
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if (endPoint and (it == num - 1)) {
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range.endInclusive
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}
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range.first.start + it * step
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range.start + it * step
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}
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return result to step
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} else {
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val step = Double.NaN
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return NDElement.real1D(1) { range.first.start } to step
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NDElement.real1D(1) { range.start }
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}
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}
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@ -77,29 +79,25 @@ object RealFactory {
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* @param endPoint If True, power(base,stop) is the last sample. Otherwise, it is not included.
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* @param base - The base of the log space.
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*/
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fun logSpace(
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range: Pair<ClosedFloatingPointRange<Double>, Int>,
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fun logspace(
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range: ClosedFloatingPointRange<Double>,
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num: Int = 100,
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endPoint: Boolean = true,
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base: Double = 10.0
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): RealNDElement {
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val lin = linSpace(range, endPoint).first
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val tempFun = { x: Double -> power(base, x) }
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return tempFun(lin) // FIXME: RealNDElement.map return not suitable type ( `linSpace(range, endPoint).first.map{power(base, it}`)
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}
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) = linspace(range, num, endPoint).map { power(base, it) }
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/**
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* Return numbers spaced evenly on a log scale (a geometric progression).
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*
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* This is similar to [logSpace], but with endpoints specified directly. Each output sample is a constant multiple of the previous.
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* This is similar to [logspace], but with endpoints specified directly. Each output sample is a constant multiple of the previous.
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* @param range use it like:
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* (start..stop) to number
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* start is starting value, finaly value depend from endPoint parameter
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* @param endPoint If True, right boundary of range is the last sample. Otherwise, it is not included.
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*/
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fun geomSpace(range: Pair<ClosedFloatingPointRange<Double>, Int>, endPoint: Boolean = true): RealNDElement {
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var start = range.first.start
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var stop = range.first.endInclusive
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val num = range.second
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fun geomspace(range: ClosedFloatingPointRange<Double>, num : Int = 100, endPoint: Boolean = true): RealNDElement {
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var start = range.start
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var stop = range.endInclusive
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if (start == 0.0 || stop == 0.0) {
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error("Geometric sequence cannot include zero")
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}
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@ -110,10 +108,9 @@ object RealFactory {
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outSign = -outSign
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}
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val logRange = logSpace((log(start, 10.0)..log(stop, 10.0) to num), endPoint = endPoint)
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val function = { x: Double -> outSign * x }
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return function(logRange) // FIXME: `outSign*log_` --- don't define times operator
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return logspace(log(start, 10.0)..log(stop, 10.0), num, endPoint = endPoint).map {
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outSign * it
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}
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}
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/**
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@ -126,12 +123,11 @@ object RealFactory {
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error("Input must be 2D NDArray")
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}
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val size = min(array.shape[0], array.shape[0])
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if (offset >= 0) {
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return NDElement.real1D(size) { i -> array[i, i + offset] }
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return if (offset >= 0) {
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NDElement.real1D(size) { i -> array[i, i + offset] }
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} else {
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return NDElement.real1D(size) { i -> array[i - offset, i] }
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NDElement.real1D(size) { i -> array[i - offset, i] }
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}
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}
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/**
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@ -144,13 +140,13 @@ object RealFactory {
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error("Input must be 1D NDArray")
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}
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val size = array.shape[0]
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if (offset >= 0) {
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return NDElement.real2D(size, size + offset) { i, j ->
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if (i == j + offset) array[i] else 0.0
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return if (offset < 0) {
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NDElement.real2D(size - offset, size) { i, j ->
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if (i - offset == j) array[j] else 0.0
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}
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} else {
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return NDElement.real2D(size - offset, size) { i, j ->
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if (i - offset == j) array[j] else 0.0
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NDElement.real2D(size, size + offset) { i, j ->
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if (i == j + offset) array[i] else 0.0
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}
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}
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}
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@ -166,12 +162,12 @@ object RealFactory {
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error("Input must be 1D NDArray")
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}
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val size = if (nCols == 0) array.shape[0] else nCols
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if (increasing) {
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return NDElement.real2D(array.shape[0], size) { i, j ->
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return if (increasing) {
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NDElement.real2D(array.shape[0], size) { i, j ->
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power(array[i], j)
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}
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} else {
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return NDElement.real2D(array.shape[0], size) { i, j ->
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NDElement.real2D(array.shape[0], size) { i, j ->
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power(array[i], size - j - 1)
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}
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}
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@ -86,11 +86,25 @@ inline fun BufferedNDField<Double, RealField>.produceInline(crossinline initiali
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return BufferedNDFieldElement(this, DoubleBuffer(array))
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}
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/**
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* Map one [RealNDElement] using function with indexes
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*/
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inline fun RealNDElement.mapIndexed(crossinline transform: RealField.(index: IntArray, Double) -> Double) =
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context.produceInline { offset -> transform(strides.index(offset), buffer[offset]) }
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/**
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* Map one [RealNDElement] using function without indexes
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*/
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inline fun RealNDElement.map(crossinline transform: RealField.(Double) -> Double): RealNDElement {
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val array = DoubleArray(strides.linearSize) { offset -> RealField.transform(buffer[offset]) }
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return BufferedNDFieldElement(context, DoubleBuffer(array))
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}
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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<Double, Double>.invoke(ndElement: RealNDElement) =
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ndElement.context.produceInline { i -> invoke(ndElement.buffer[i]) }
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ndElement.map { this@invoke(it) }
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/* plus and minus */
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@ -99,10 +113,10 @@ operator fun Function1<Double, Double>.invoke(ndElement: RealNDElement) =
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* Summation operation for [BufferedNDElement] and single element
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*/
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operator fun RealNDElement.plus(arg: Double) =
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context.produceInline { i -> buffer[i] + arg }
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map { it + arg }
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/**
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* Subtraction operation between [BufferedNDElement] and single element
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*/
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operator fun RealNDElement.minus(arg: Double) =
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context.produceInline { i -> buffer[i] - arg }
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map { it - arg }
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@ -2,8 +2,7 @@ pluginManagement {
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repositories {
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mavenCentral()
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maven("https://plugins.gradle.org/m2/")
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maven { setUrl("https://dl.bintray.com/kotlin/kotlin-eap") }
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maven { setUrl("https://plugins.gradle.org/m2/") }
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maven ("https://dl.bintray.com/kotlin/kotlin-eap")
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}
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}
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Block a user