forked from kscience/kmath
[WIP] Another histogram refactor
This commit is contained in:
parent
39640498fc
commit
29369cd6d7
@ -9,16 +9,21 @@ import space.kscience.kmath.linear.Point
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import space.kscience.kmath.misc.UnstableKMathAPI
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@UnstableKMathAPI
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public class UnivariateDomain(public val range: ClosedFloatingPointRange<Double>) : DoubleDomain {
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public abstract class Domain1D<T : Comparable<T>>(public val range: ClosedRange<T>) : Domain<T> {
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override val dimension: Int get() = 1
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public operator fun contains(d: Double): Boolean = range.contains(d)
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public operator fun contains(value: T): Boolean = range.contains(value)
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override operator fun contains(point: Point<Double>): Boolean {
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override operator fun contains(point: Point<T>): Boolean {
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require(point.size == 0)
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return contains(point[0])
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}
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}
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@UnstableKMathAPI
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public class DoubleDomain1D(
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@Suppress("CanBeParameter") public val doubleRange: ClosedFloatingPointRange<Double>,
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) : Domain1D<Double>(doubleRange), DoubleDomain {
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override fun getLowerBound(num: Int): Double {
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require(num == 0)
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return range.start
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@ -31,3 +36,7 @@ public class UnivariateDomain(public val range: ClosedFloatingPointRange<Double>
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override fun volume(): Double = range.endInclusive - range.start
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}
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@UnstableKMathAPI
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public val DoubleDomain1D.center: Double
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get() = (range.endInclusive + range.start) / 2
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@ -6,6 +6,7 @@
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package space.kscience.kmath.histogram
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import space.kscience.kmath.domains.HyperSquareDomain
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import space.kscience.kmath.linear.Point
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import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.nd.*
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import space.kscience.kmath.operations.DoubleField
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@ -31,7 +32,7 @@ public class DoubleHistogramSpace(
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public val dimension: Int get() = lower.size
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override val shape: IntArray = IntArray(binNums.size) { binNums[it] + 2 }
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override val histogramValueSpace: DoubleFieldND = DoubleField.ndAlgebra(*shape)
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override val histogramValueAlgebra: DoubleFieldND = DoubleField.ndAlgebra(*shape)
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private val binSize = DoubleBuffer(dimension) { (upper[it] - lower[it]) / binNums[it] }
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@ -70,21 +71,20 @@ public class DoubleHistogramSpace(
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}
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@OptIn(UnstableKMathAPI::class)
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public val Bin<Double>.domain: HyperSquareDomain
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get() = (this as? DomainBin<Double>)?.domain as? HyperSquareDomain
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?: error("Im a teapot. This is not my bin")
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@OptIn(UnstableKMathAPI::class)
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override fun produceBin(index: IntArray, value: Double): DomainBin<Double> {
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override fun produceBin(index: IntArray, value: Double): DomainBin<Double, Double> {
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val domain = getDomain(index)
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return DomainBin(domain, value)
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}
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override fun produce(builder: HistogramBuilder<Double>.() -> Unit): IndexedHistogram<Double, Double> {
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override fun produce(builder: HistogramBuilder<Double, Double>.() -> Unit): IndexedHistogram<Double, Double> {
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val ndCounter = StructureND.auto(shape) { Counter.double() }
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val hBuilder = HistogramBuilder<Double> { point, value ->
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val hBuilder = object : HistogramBuilder<Double, Double> {
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override val defaultValue: Double get() = 1.0
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override fun putValue(point: Point<out Double>, value: Double) {
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val index = getIndex(point)
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ndCounter[index].add(value.toDouble())
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ndCounter[index].add(value)
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}
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}
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hBuilder.apply(builder)
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val values: BufferND<Double> = ndCounter.mapToBuffer { it.value }
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@ -13,14 +13,14 @@ import space.kscience.kmath.structures.asBuffer
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/**
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* The binned data element. Could be a histogram bin with a number of counts or an artificial construct.
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*/
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public interface Bin<in T : Any> : Domain<T> {
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public interface Bin<in T : Any, out V> : Domain<T> {
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/**
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* The value of this bin.
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*/
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public val value: Number
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public val value: V
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}
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public interface Histogram<in T : Any, out B : Bin<T>> {
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public interface Histogram<in T : Any, out V, out B : Bin<T, V>> {
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/**
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* Find existing bin, corresponding to given coordinates
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*/
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@ -32,29 +32,38 @@ public interface Histogram<in T : Any, out B : Bin<T>> {
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public val dimension: Int
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public val bins: Iterable<B>
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public companion object {
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//A discoverability root
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}
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}
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public fun interface HistogramBuilder<in T : Any> {
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public interface HistogramBuilder<in T : Any, V : Any> {
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/**
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* Increment appropriate bin
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* The default value increment for a bin
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*/
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public fun putValue(point: Point<out T>, value: Number)
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public val defaultValue: V
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/**
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* Increment appropriate bin with given value
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*/
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public fun putValue(point: Point<out T>, value: V = defaultValue)
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}
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public fun <T : Any, B : Bin<T>> HistogramBuilder<T>.put(point: Point<out T>): Unit = putValue(point, 1.0)
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public fun <T : Any> HistogramBuilder<T, *>.put(point: Point<out T>): Unit = putValue(point)
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public fun <T : Any> HistogramBuilder<T>.put(vararg point: T): Unit = put(point.asBuffer())
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public fun <T : Any> HistogramBuilder<T, *>.put(vararg point: T): Unit = put(point.asBuffer())
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public fun HistogramBuilder<Double>.put(vararg point: Number): Unit =
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public fun HistogramBuilder<Double, *>.put(vararg point: Number): Unit =
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put(DoubleBuffer(point.map { it.toDouble() }.toDoubleArray()))
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public fun HistogramBuilder<Double>.put(vararg point: Double): Unit = put(DoubleBuffer(point))
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public fun <T : Any> HistogramBuilder<T>.fill(sequence: Iterable<Point<T>>): Unit = sequence.forEach { put(it) }
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public fun HistogramBuilder<Double, *>.put(vararg point: Double): Unit = put(DoubleBuffer(point))
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public fun <T : Any> HistogramBuilder<T, *>.fill(sequence: Iterable<Point<T>>): Unit = sequence.forEach { put(it) }
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/**
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* Pass a sequence builder into histogram
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*/
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public fun <T : Any> HistogramBuilder<T>.fill(block: suspend SequenceScope<Point<T>>.() -> Unit): Unit =
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public fun <T : Any> HistogramBuilder<T, *>.fill(block: suspend SequenceScope<Point<T>>.() -> Unit): Unit =
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fill(sequence(block).asIterable())
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@ -0,0 +1,56 @@
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/*
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* Copyright 2018-2021 KMath contributors.
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* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
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*/
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package space.kscience.kmath.histogram
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import space.kscience.kmath.domains.Domain1D
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import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.operations.asSequence
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import space.kscience.kmath.structures.Buffer
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/**
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* A univariate bin based on a range
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*
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* @property value The value of histogram including weighting
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* @property standardDeviation Standard deviation of the bin value. Zero or negative if not applicable
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*/
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@UnstableKMathAPI
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public class Bin1D<T : Comparable<T>, out V>(
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public val domain: Domain1D<T>,
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override val value: V,
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) : Bin<T, V>, ClosedRange<T> by domain.range {
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override val dimension: Int get() = 1
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override fun contains(point: Buffer<T>): Boolean = point.size == 1 && contains(point[0])
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}
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@OptIn(UnstableKMathAPI::class)
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public interface Histogram1D<T : Comparable<T>, V> : Histogram<T, V, Bin1D<T, V>> {
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override val dimension: Int get() = 1
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public operator fun get(value: T): Bin1D<T, V>?
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override operator fun get(point: Buffer<T>): Bin1D<T, V>? = get(point[0])
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}
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@UnstableKMathAPI
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public interface Histogram1DBuilder<in T : Any, V : Any> : HistogramBuilder<T, V> {
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/**
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* Thread safe put operation
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*/
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public fun putValue(at: T, value: V = defaultValue)
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}
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@UnstableKMathAPI
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public fun Histogram1DBuilder<Double, *>.fill(items: Iterable<Double>): Unit =
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items.forEach(this::putValue)
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@UnstableKMathAPI
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public fun Histogram1DBuilder<Double, *>.fill(array: DoubleArray): Unit =
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array.forEach(this::putValue)
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@UnstableKMathAPI
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public fun Histogram1DBuilder<Double, *>.fill(buffer: Buffer<Double>): Unit =
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buffer.asSequence().forEach(this::putValue)
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@ -18,24 +18,28 @@ import space.kscience.kmath.operations.invoke
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/**
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* A simple histogram bin based on domain
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*/
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public data class DomainBin<in T : Comparable<T>>(
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public data class DomainBin<in T : Comparable<T>, out V>(
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public val domain: Domain<T>,
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override val value: Number,
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) : Bin<T>, Domain<T> by domain
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override val value: V,
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) : Bin<T, V>, Domain<T> by domain
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/**
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* @param T the type of the argument space
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* @param V the type of bin value
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*/
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public class IndexedHistogram<T : Comparable<T>, V : Any>(
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public val histogramSpace: IndexedHistogramSpace<T, V>,
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public val values: StructureND<V>,
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) : Histogram<T, Bin<T>> {
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) : Histogram<T, V, DomainBin<T, V>> {
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override fun get(point: Point<T>): Bin<T>? {
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override fun get(point: Point<T>): DomainBin<T, V>? {
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val index = histogramSpace.getIndex(point) ?: return null
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return histogramSpace.produceBin(index, values[index])
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}
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override val dimension: Int get() = histogramSpace.shape.size
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override val bins: Iterable<Bin<T>>
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override val bins: Iterable<DomainBin<T, V>>
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get() = DefaultStrides(histogramSpace.shape).asSequence().map {
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histogramSpace.produceBin(it, values[it])
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}.asIterable()
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@ -46,9 +50,8 @@ public class IndexedHistogram<T : Comparable<T>, V : Any>(
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*/
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public interface IndexedHistogramSpace<T : Comparable<T>, V : Any>
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: Group<IndexedHistogram<T, V>>, ScaleOperations<IndexedHistogram<T, V>> {
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//public val valueSpace: Space<V>
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public val shape: Shape
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public val histogramValueSpace: FieldND<V, *> //= NDAlgebra.space(valueSpace, Buffer.Companion::boxing, *shape),
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public val histogramValueAlgebra: FieldND<V, *> //= NDAlgebra.space(valueSpace, Buffer.Companion::boxing, *shape),
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/**
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* Resolve index of the bin including given [point]
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@ -60,19 +63,19 @@ public interface IndexedHistogramSpace<T : Comparable<T>, V : Any>
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*/
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public fun getDomain(index: IntArray): Domain<T>?
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public fun produceBin(index: IntArray, value: V): Bin<T>
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public fun produceBin(index: IntArray, value: V): DomainBin<T, V>
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public fun produce(builder: HistogramBuilder<T>.() -> Unit): IndexedHistogram<T, V>
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public fun produce(builder: HistogramBuilder<T, V>.() -> Unit): IndexedHistogram<T, V>
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override fun add(left: IndexedHistogram<T, V>, right: IndexedHistogram<T, V>): IndexedHistogram<T, V> {
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require(left.histogramSpace == this) { "Can't operate on a histogram produced by external space" }
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require(right.histogramSpace == this) { "Can't operate on a histogram produced by external space" }
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return IndexedHistogram(this, histogramValueSpace { left.values + right.values })
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return IndexedHistogram(this, histogramValueAlgebra { left.values + right.values })
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}
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override fun scale(a: IndexedHistogram<T, V>, value: Double): IndexedHistogram<T, V> {
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require(a.histogramSpace == this) { "Can't operate on a histogram produced by external space" }
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return IndexedHistogram(this, histogramValueSpace { a.values * value })
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return IndexedHistogram(this, histogramValueAlgebra { a.values * value })
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}
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override val zero: IndexedHistogram<T, V> get() = produce { }
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@ -0,0 +1,9 @@
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/*
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* Copyright 2018-2021 KMath contributors.
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* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
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*/
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package space.kscience.kmath.histogram
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//class UniformDoubleHistogram1D: DoubleHistogram1D {
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//}
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@ -1,59 +0,0 @@
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/*
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* Copyright 2018-2021 KMath contributors.
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* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
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*/
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package space.kscience.kmath.histogram
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import space.kscience.kmath.domains.UnivariateDomain
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import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.operations.asSequence
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import space.kscience.kmath.structures.Buffer
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@UnstableKMathAPI
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public val UnivariateDomain.center: Double
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get() = (range.endInclusive + range.start) / 2
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/**
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* A univariate bin based on a range
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*
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* @property value The value of histogram including weighting
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* @property standardDeviation Standard deviation of the bin value. Zero or negative if not applicable
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*/
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@UnstableKMathAPI
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public class UnivariateBin(
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public val domain: UnivariateDomain,
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override val value: Double,
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public val standardDeviation: Double,
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) : Bin<Double>, ClosedFloatingPointRange<Double> by domain.range {
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override val dimension: Int get() = 1
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override fun contains(point: Buffer<Double>): Boolean = point.size == 1 && contains(point[0])
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}
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@OptIn(UnstableKMathAPI::class)
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public interface UnivariateHistogram : Histogram<Double, UnivariateBin> {
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public operator fun get(value: Double): UnivariateBin?
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override operator fun get(point: Buffer<Double>): UnivariateBin? = get(point[0])
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}
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@UnstableKMathAPI
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public interface UnivariateHistogramBuilder : HistogramBuilder<Double> {
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/**
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* Thread safe put operation
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*/
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public fun putValue(at: Double, value: Double = 1.0)
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override fun putValue(point: Buffer<Double>, value: Number)
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}
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@UnstableKMathAPI
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public fun UnivariateHistogramBuilder.fill(items: Iterable<Double>): Unit = items.forEach(this::putValue)
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@UnstableKMathAPI
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public fun UnivariateHistogramBuilder.fill(array: DoubleArray): Unit = array.forEach(this::putValue)
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@UnstableKMathAPI
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public fun UnivariateHistogramBuilder.fill(buffer: Buffer<Double>): Unit = buffer.asSequence().forEach(this::putValue)
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@ -5,7 +5,7 @@
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package space.kscience.kmath.histogram
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import space.kscience.kmath.domains.UnivariateDomain
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import space.kscience.kmath.domains.DoubleDomain1D
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import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.operations.Group
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import space.kscience.kmath.operations.ScaleOperations
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@ -15,7 +15,7 @@ import kotlin.math.abs
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import kotlin.math.floor
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import kotlin.math.sqrt
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private fun <B : ClosedFloatingPointRange<Double>> TreeMap<Double, B>.getBin(value: Double): B? {
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private fun <B : ClosedRange<Double>> TreeMap<Double, B>.getBin(value: Double): B? {
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// check ceiling entry and return it if it is what needed
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val ceil = ceilingEntry(value)?.value
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if (ceil != null && value in ceil) return ceil
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@ -28,19 +28,18 @@ private fun <B : ClosedFloatingPointRange<Double>> TreeMap<Double, B>.getBin(val
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@UnstableKMathAPI
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public class TreeHistogram(
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private val binMap: TreeMap<Double, out UnivariateBin>,
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) : UnivariateHistogram {
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override fun get(value: Double): UnivariateBin? = binMap.getBin(value)
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override val dimension: Int get() = 1
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override val bins: Collection<UnivariateBin> get() = binMap.values
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private val binMap: TreeMap<Double, out Bin1D<Double, Double>>,
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) : Histogram1D<Double, Double> {
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override fun get(value: Double): Bin1D<Double, Double>? = binMap.getBin(value)
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override val bins: Collection<Bin1D<Double, Double>> get() = binMap.values
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}
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@OptIn(UnstableKMathAPI::class)
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@PublishedApi
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internal class TreeHistogramBuilder(val binFactory: (Double) -> UnivariateDomain) : UnivariateHistogramBuilder {
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internal class TreeHistogramBuilder(val binFactory: (Double) -> DoubleDomain1D) : Histogram1DBuilder<Double, Double> {
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internal class BinCounter(val domain: UnivariateDomain, val counter: Counter<Double> = Counter.double()) :
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ClosedFloatingPointRange<Double> by domain.range
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internal class BinCounter(val domain: DoubleDomain1D, val counter: Counter<Double> = Counter.double()) :
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ClosedRange<Double> by domain.range
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private val bins: TreeMap<Double, BinCounter> = TreeMap()
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@ -64,15 +63,15 @@ internal class TreeHistogramBuilder(val binFactory: (Double) -> UnivariateDomain
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}
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}
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override fun putValue(point: Buffer<Double>, value: Number) {
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override fun putValue(point: Buffer<Double>, value: Double) {
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require(point.size == 1) { "Only points with single value could be used in univariate histogram" }
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putValue(point[0], value.toDouble())
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}
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fun build(): TreeHistogram {
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val map = bins.mapValuesTo(TreeMap<Double, UnivariateBin>()) { (_, binCounter) ->
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val map = bins.mapValuesTo(TreeMap<Double, Bin1D<Double,Double>>()) { (_, binCounter) ->
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val count = binCounter.counter.value
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UnivariateBin(binCounter.domain, count, sqrt(count))
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Bin1D(binCounter.domain, count, sqrt(count))
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}
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return TreeHistogram(map)
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}
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@ -83,23 +82,23 @@ internal class TreeHistogramBuilder(val binFactory: (Double) -> UnivariateDomain
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*/
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@UnstableKMathAPI
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public class TreeHistogramSpace(
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@PublishedApi internal val binFactory: (Double) -> UnivariateDomain,
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) : Group<UnivariateHistogram>, ScaleOperations<UnivariateHistogram> {
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@PublishedApi internal val binFactory: (Double) -> DoubleDomain1D,
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) : Group<Histogram1D<Double,Double>>, ScaleOperations<Histogram1D<Double,Double>> {
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public inline fun fill(block: UnivariateHistogramBuilder.() -> Unit): UnivariateHistogram =
|
||||
public inline fun fill(block: Histogram1DBuilder<Double,Double>.() -> Unit): Histogram1D<Double,Double> =
|
||||
TreeHistogramBuilder(binFactory).apply(block).build()
|
||||
|
||||
override fun add(
|
||||
left: UnivariateHistogram,
|
||||
right: UnivariateHistogram,
|
||||
): UnivariateHistogram {
|
||||
left: Histogram1D<Double,Double>,
|
||||
right: Histogram1D<Double,Double>,
|
||||
): Histogram1D<Double,Double> {
|
||||
// require(a.context == this) { "Histogram $a does not belong to this context" }
|
||||
// require(b.context == this) { "Histogram $b does not belong to this context" }
|
||||
val bins = TreeMap<Double, UnivariateBin>().apply {
|
||||
val bins = TreeMap<Double, Bin1D<Double,Double>>().apply {
|
||||
(left.bins.map { it.domain } union right.bins.map { it.domain }).forEach { def ->
|
||||
put(
|
||||
def.center,
|
||||
UnivariateBin(
|
||||
Bin1D(
|
||||
def,
|
||||
value = (left[def.center]?.value ?: 0.0) + (right[def.center]?.value ?: 0.0),
|
||||
standardDeviation = (left[def.center]?.standardDeviation
|
||||
@ -111,12 +110,12 @@ public class TreeHistogramSpace(
|
||||
return TreeHistogram(bins)
|
||||
}
|
||||
|
||||
override fun scale(a: UnivariateHistogram, value: Double): UnivariateHistogram {
|
||||
val bins = TreeMap<Double, UnivariateBin>().apply {
|
||||
override fun scale(a: Histogram1D<Double,Double>, value: Double): Histogram1D<Double,Double> {
|
||||
val bins = TreeMap<Double, Bin1D<Double,Double>>().apply {
|
||||
a.bins.forEach { bin ->
|
||||
put(
|
||||
bin.domain.center,
|
||||
UnivariateBin(
|
||||
Bin1D(
|
||||
bin.domain,
|
||||
value = bin.value * value,
|
||||
standardDeviation = abs(bin.standardDeviation * value)
|
||||
@ -128,38 +127,38 @@ public class TreeHistogramSpace(
|
||||
return TreeHistogram(bins)
|
||||
}
|
||||
|
||||
override fun UnivariateHistogram.unaryMinus(): UnivariateHistogram = this * (-1)
|
||||
override fun Histogram1D<Double,Double>.unaryMinus(): Histogram1D<Double,Double> = this * (-1)
|
||||
|
||||
override val zero: UnivariateHistogram by lazy { fill { } }
|
||||
override val zero: Histogram1D<Double,Double> by lazy { fill { } }
|
||||
|
||||
public companion object {
|
||||
/**
|
||||
* Build and fill a [UnivariateHistogram]. Returns a read-only histogram.
|
||||
* Build and fill a [DoubleHistogram1D]. Returns a read-only histogram.
|
||||
*/
|
||||
public inline fun uniform(
|
||||
binSize: Double,
|
||||
start: Double = 0.0,
|
||||
builder: UnivariateHistogramBuilder.() -> Unit,
|
||||
): UnivariateHistogram = uniform(binSize, start).fill(builder)
|
||||
builder: Histogram1DBuilder<Double,Double>.() -> Unit,
|
||||
): Histogram1D<Double,Double> = uniform(binSize, start).fill(builder)
|
||||
|
||||
/**
|
||||
* Build and fill a histogram with custom borders. Returns a read-only histogram.
|
||||
*/
|
||||
public inline fun custom(
|
||||
borders: DoubleArray,
|
||||
builder: UnivariateHistogramBuilder.() -> Unit,
|
||||
): UnivariateHistogram = custom(borders).fill(builder)
|
||||
builder: Histogram1DBuilder<Double,Double>.() -> Unit,
|
||||
): Histogram1D<Double,Double> = custom(borders).fill(builder)
|
||||
|
||||
|
||||
/**
|
||||
* Build and fill a [UnivariateHistogram]. Returns a read-only histogram.
|
||||
* Build and fill a [DoubleHistogram1D]. Returns a read-only histogram.
|
||||
*/
|
||||
public fun uniform(
|
||||
binSize: Double,
|
||||
start: Double = 0.0,
|
||||
): TreeHistogramSpace = TreeHistogramSpace { value ->
|
||||
val center = start + binSize * floor((value - start) / binSize + 0.5)
|
||||
UnivariateDomain((center - binSize / 2)..(center + binSize / 2))
|
||||
DoubleDomain1D((center - binSize / 2)..(center + binSize / 2))
|
||||
}
|
||||
|
||||
/**
|
||||
@ -170,11 +169,11 @@ public class TreeHistogramSpace(
|
||||
|
||||
return TreeHistogramSpace { value ->
|
||||
when {
|
||||
value < sorted.first() -> UnivariateDomain(
|
||||
value < sorted.first() -> DoubleDomain1D(
|
||||
Double.NEGATIVE_INFINITY..sorted.first()
|
||||
)
|
||||
|
||||
value > sorted.last() -> UnivariateDomain(
|
||||
value > sorted.last() -> DoubleDomain1D(
|
||||
sorted.last()..Double.POSITIVE_INFINITY
|
||||
)
|
||||
|
||||
@ -182,7 +181,7 @@ public class TreeHistogramSpace(
|
||||
val index = sorted.indices.first { value > sorted[it] }
|
||||
val left = sorted[index]
|
||||
val right = sorted[index + 1]
|
||||
UnivariateDomain(left..right)
|
||||
DoubleDomain1D(left..right)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user