Histogram refactor
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@ -37,6 +37,7 @@
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- Features moved to NDStructure and became transparent.
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- Capitalization of LUP in many names changed to Lup.
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- Refactored `NDStructure` algebra to be more simple, preferring under-the-hood conversion to explicit NDStructure types
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- Refactor histograms. They are marked as prototype
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### Deprecated
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@ -8,10 +8,10 @@ import kscience.kmath.operations.invoke
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import kscience.kmath.structures.*
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import kotlin.math.floor
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public data class BinDef<T : Comparable<T>>(
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public data class BinDefinition<T : Comparable<T>>(
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public val space: SpaceOperations<Point<T>>,
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public val center: Point<T>,
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public val sizes: Point<T>
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public val sizes: Point<T>,
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) {
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public fun contains(vector: Point<out T>): Boolean {
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require(vector.size == center.size) { "Dimension mismatch for input vector. Expected ${center.size}, but found ${vector.size}" }
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@ -22,14 +22,17 @@ public data class BinDef<T : Comparable<T>>(
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}
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public class MultivariateBin<T : Comparable<T>>(public val def: BinDef<T>, public override val value: Number) : Bin<T> {
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public class MultivariateBin<T : Comparable<T>>(
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public val definition: BinDefinition<T>,
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public override val value: Number,
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) : Bin<T> {
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public override val dimension: Int
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get() = def.center.size
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get() = definition.center.size
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public override val center: Point<T>
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get() = def.center
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get() = definition.center
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public override operator fun contains(point: Point<T>): Boolean = def.contains(point)
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public override operator fun contains(point: Point<T>): Boolean = definition.contains(point)
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}
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/**
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@ -38,11 +41,11 @@ public class MultivariateBin<T : Comparable<T>>(public val def: BinDef<T>, publi
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public class RealHistogram(
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private val lower: Buffer<Double>,
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private val upper: Buffer<Double>,
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private val binNums: IntArray = IntArray(lower.size) { 20 }
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private val binNums: IntArray = IntArray(lower.size) { 20 },
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) : MutableHistogram<Double, MultivariateBin<Double>> {
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private val strides = DefaultStrides(IntArray(binNums.size) { binNums[it] + 2 })
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private val values: NDStructure<LongCounter> = NDStructure.auto(strides) { LongCounter() }
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private val weights: NDStructure<DoubleCounter> = NDStructure.auto(strides) { DoubleCounter() }
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private val counts: NDStructure<LongCounter> = NDStructure.auto(strides) { LongCounter() }
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private val values: NDStructure<DoubleCounter> = NDStructure.auto(strides) { DoubleCounter() }
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public override val dimension: Int get() = lower.size
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private val binSize = RealBuffer(dimension) { (upper[it] - lower[it]) / binNums[it] }
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@ -65,11 +68,11 @@ public class RealHistogram(
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private fun getIndex(point: Buffer<out Double>): IntArray = IntArray(dimension) { getIndex(it, point[it]) }
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private fun getValue(index: IntArray): Long = values[index].sum()
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private fun getValue(index: IntArray): Long = counts[index].sum()
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public fun getValue(point: Buffer<out Double>): Long = getValue(getIndex(point))
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private fun getDef(index: IntArray): BinDef<Double> {
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private fun getBinDefinition(index: IntArray): BinDefinition<Double> {
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val center = index.mapIndexed { axis, i ->
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when (i) {
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0 -> Double.NEGATIVE_INFINITY
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@ -78,14 +81,14 @@ public class RealHistogram(
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}
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}.asBuffer()
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return BinDef(RealBufferFieldOperations, center, binSize)
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return BinDefinition(RealBufferFieldOperations, center, binSize)
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}
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public fun getDef(point: Buffer<out Double>): BinDef<Double> = getDef(getIndex(point))
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public fun getBinDefinition(point: Buffer<out Double>): BinDefinition<Double> = getBinDefinition(getIndex(point))
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public override operator fun get(point: Buffer<out Double>): MultivariateBin<Double>? {
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val index = getIndex(point)
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return MultivariateBin(getDef(index), getValue(index))
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return MultivariateBin(getBinDefinition(index), getValue(index))
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}
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// fun put(point: Point<out Double>){
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@ -95,23 +98,24 @@ public class RealHistogram(
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public override fun putWithWeight(point: Buffer<out Double>, weight: Double) {
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val index = getIndex(point)
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values[index].increment()
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weights[index].add(weight)
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counts[index].increment()
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values[index].add(weight)
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}
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public override operator fun iterator(): Iterator<MultivariateBin<Double>> =
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weights.elements().map { (index, value) -> MultivariateBin(getDef(index), value.sum()) }
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.iterator()
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values.elements().map { (index, value) ->
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MultivariateBin(getBinDefinition(index), value.sum())
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}.iterator()
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/**
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* Convert this histogram into NDStructure containing bin values but not bin descriptions
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* NDStructure containing number of events in bins without weights
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*/
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public fun values(): NDStructure<Number> = NDStructure.auto(values.shape) { values[it].sum() }
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public fun counts(): NDStructure<Long> = NDStructure.auto(counts.shape) { counts[it].sum() }
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/**
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* Sum of weights
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* NDStructure containing values of bins including weights
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*/
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public fun weights(): NDStructure<Double> = NDStructure.auto(weights.shape) { weights[it].sum() }
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public fun values(): NDStructure<Double> = NDStructure.auto(values.shape) { values[it].sum() }
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public companion object {
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/**
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@ -1,8 +1,10 @@
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package kscience.kmath.histogram
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import kscience.kmath.linear.Point
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import kscience.kmath.misc.UnstableKMathAPI
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import kscience.kmath.structures.Buffer
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import kscience.kmath.structures.asBuffer
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import kscience.kmath.structures.asSequence
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import java.util.*
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import kotlin.math.floor
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@ -11,29 +13,36 @@ import kotlin.math.floor
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public class UnivariateBin(
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public val position: Double,
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public val size: Double,
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public val counter: LongCounter = LongCounter(),
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) : Bin<Double> {
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//TODO add weighting
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public override val value: Number get() = counter.sum()
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//internal mutation operations
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internal val counter: LongCounter = LongCounter()
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internal val weightCounter: DoubleCounter = DoubleCounter()
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/**
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* The precise number of events ignoring weighting
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*/
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public val count: Long get() = counter.sum()
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/**
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* The value of histogram including weighting
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*/
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public override val value: Double get() = weightCounter.sum()
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public override val center: Point<Double> get() = doubleArrayOf(position).asBuffer()
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public override val dimension: Int get() = 1
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public operator fun contains(value: Double): Boolean = value in (position - size / 2)..(position + size / 2)
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public override fun contains(point: Buffer<Double>): Boolean = contains(point[0])
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internal operator fun inc(): UnivariateBin = this.also { counter.increment() }
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}
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/**
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* Univariate histogram with log(n) bin search speed
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*/
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public class UnivariateHistogram private constructor(
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private val factory: (Double) -> UnivariateBin,
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) : MutableHistogram<Double, UnivariateBin> {
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public abstract class UnivariateHistogram(
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protected val bins: TreeMap<Double, UnivariateBin> = TreeMap(),
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) : Histogram<Double, UnivariateBin> {
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private val bins: TreeMap<Double, UnivariateBin> = TreeMap()
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private operator fun get(value: Double): UnivariateBin? {
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public operator fun get(value: Double): UnivariateBin? {
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// check ceiling entry and return it if it is what needed
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val ceil = bins.ceilingEntry(value)?.value
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if (ceil != null && value in ceil) return ceil
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@ -44,38 +53,38 @@ public class UnivariateHistogram private constructor(
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return null
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}
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private fun createBin(value: Double): UnivariateBin = factory(value).also {
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synchronized(this) { bins[it.position] = it }
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}
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public override operator fun get(point: Buffer<out Double>): UnivariateBin? = get(point[0])
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public override val dimension: Int get() = 1
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public override operator fun iterator(): Iterator<UnivariateBin> = bins.values.iterator()
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/**
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* Thread safe put operation
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*/
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public fun put(value: Double) {
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(get(value) ?: createBin(value)).inc()
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}
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override fun putWithWeight(point: Buffer<out Double>, weight: Double) {
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if (weight != 1.0) TODO("Implement weighting")
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put(point[0])
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}
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public companion object {
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public fun uniform(binSize: Double, start: Double = 0.0): UnivariateHistogram = UnivariateHistogram { value ->
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/**
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* Build a histogram with a uniform binning with a start at [start] and a bin size of [binSize]
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*/
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public fun uniformBuilder(binSize: Double, start: Double = 0.0): UnivariateHistogramBuilder =
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UnivariateHistogramBuilder { value ->
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val center = start + binSize * floor((value - start) / binSize + 0.5)
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UnivariateBin(center, binSize)
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}
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public fun custom(borders: DoubleArray): UnivariateHistogram {
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/**
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* Build and fill a [UnivariateHistogram]. Returns a read-only histogram.
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*/
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public fun uniform(
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binSize: Double,
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start: Double = 0.0,
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builder: UnivariateHistogramBuilder.() -> Unit,
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): UnivariateHistogram = uniformBuilder(binSize, start).apply(builder)
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/**
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* Create a histogram with custom cell borders
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*/
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public fun customBuilder(borders: DoubleArray): UnivariateHistogramBuilder {
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val sorted = borders.sortedArray()
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return UnivariateHistogram { value ->
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return UnivariateHistogramBuilder { value ->
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when {
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value < sorted.first() -> UnivariateBin(
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Double.NEGATIVE_INFINITY,
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@ -96,7 +105,55 @@ public class UnivariateHistogram private constructor(
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}
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}
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}
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/**
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* Build and fill a histogram with custom borders. Returns a read-only histogram.
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*/
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public fun custom(
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borders: DoubleArray,
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builder: UnivariateHistogramBuilder.() -> Unit,
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): UnivariateHistogram = customBuilder(borders).apply(builder)
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}
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}
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public fun UnivariateHistogram.fill(sequence: Iterable<Double>): Unit = sequence.forEach(::put)
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public class UnivariateHistogramBuilder(
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private val factory: (Double) -> UnivariateBin,
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) : UnivariateHistogram(), MutableHistogram<Double, UnivariateBin> {
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private fun createBin(value: Double): UnivariateBin = factory(value).also {
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synchronized(this) { bins[it.position] = it }
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}
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/**
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* Thread safe put operation
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*/
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public fun put(value: Double, weight: Double = 1.0) {
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(get(value) ?: createBin(value)).apply{
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counter.increment()
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weightCounter.add(weight)
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}
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}
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override fun putWithWeight(point: Buffer<out Double>, weight: Double) {
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put(point[0], weight)
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}
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/**
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* Put several items into a single bin
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*/
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public fun putMany(value: Double, count: Int, weight: Double = count.toDouble()){
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(get(value) ?: createBin(value)).apply{
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counter.add(count.toLong())
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weightCounter.add(weight)
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}
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}
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}
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@UnstableKMathAPI
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public fun UnivariateHistogramBuilder.fill(items: Iterable<Double>): Unit = items.forEach(::put)
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@UnstableKMathAPI
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public fun UnivariateHistogramBuilder.fill(array: DoubleArray): Unit = array.forEach(::put)
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@UnstableKMathAPI
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public fun UnivariateHistogramBuilder.fill(buffer: Buffer<Double>): Unit = buffer.asSequence().forEach(::put)
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