Minor change to histogram API. Project build to kts.

build.gradle

@@ -1,24 +0,0 @@
-buildscript {
-    ext.kotlin_version = '1.3.0'
-
-    repositories {
-        jcenter()
-    }
-
-    dependencies {
-        classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
-        classpath "org.jfrog.buildinfo:build-info-extractor-gradle:4+"
-    }
-}
-
-allprojects {
-    apply plugin: 'maven-publish'
-    apply plugin: "com.jfrog.artifactory"
-
-    group = 'scientifik'
-    version = '0.0.1-SNAPSHOT'
-}
-
-if(file('artifactory.gradle').exists()){
-    apply from: 'artifactory.gradle'
-}

build.gradle.kts

@@ -0,0 +1,28 @@
+buildscript {
+    val kotlin_version = "1.3.10"
+
+    repositories {
+        jcenter()
+    }
+
+    dependencies {
+        classpath("org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version")
+        classpath("org.jfrog.buildinfo:build-info-extractor-gradle:4+")
+    }
+}
+
+plugins {
+    id("com.jfrog.artifactory") version "4.8.1"  apply false
+}
+
+allprojects {
+    apply(plugin = "maven-publish")
+    apply(plugin = "com.jfrog.artifactory")
+
+    group = "scientifik"
+    version = "0.0.1-SNAPSHOT"
+}
+
+if(file("artifactory.gradle").exists()){
+    apply(from = "artifactory.gradle")
+}

kmath-core/src/commonMain/kotlin/scientifik/kmath/histogram/FastHistogram.kt

@@ -24,13 +24,14 @@ class MultivariateBin(override val center: RealVector, val sizes: RealVector, va
 }
 
 /**
- * Uniform multivariate histogram with fixed borders. Based on NDStructure implementation with complexity of m for bin search, where m is the number of dimensions
+ * Uniform multivariate histogram with fixed borders. Based on NDStructure implementation with complexity of m for bin search, where m is the number of dimensions.
+ * The histogram is optimized for speed, but have large size in memory
  */
 class FastHistogram(
         private val lower: RealVector,
         private val upper: RealVector,
         private val binNums: IntArray = IntArray(lower.size) { 20 }
-) : Histogram<Double, MultivariateBin> {
+) : MutableHistogram<Double, MultivariateBin> {
 
     init {
         // argument checks
@@ -76,7 +77,8 @@ class FastHistogram(
         return bins[index]
     }
 
-    override fun put(point: Buffer<out Double>) {
+    override fun put(point: Buffer<out Double>, weight: Double) {
+        if (weight != 1.0) TODO("Implement weighting")
         this[point]?.inc() ?: error("Could not find appropriate bin (should not be possible)")
     }
 

kmath-core/src/commonMain/kotlin/scientifik/kmath/histogram/Histogram.kt

@@ -4,12 +4,14 @@ import scientifik.kmath.operations.Space
 import scientifik.kmath.structures.ArrayBuffer
 import scientifik.kmath.structures.Buffer
 
+typealias Point<T> = Buffer<T>
+
 /**
  * A simple geometric domain
  * TODO move to geometry module
  */
 interface Domain<T: Any> {
-    operator fun contains(vector: Buffer<out T>): Boolean
+    operator fun contains(vector: Point<out T>): Boolean
     val dimension: Int
 }
 
@@ -21,7 +23,7 @@ interface Bin<T: Any> : Domain<T> {
      * The value of this bin
      */
     val value: Number
-    val center: Buffer<T>
+    val center: Point<T>
 }
 
 interface Histogram<T: Any, out B : Bin<T>> : Iterable<B> {
@@ -29,27 +31,31 @@ interface Histogram<T: Any, out B : Bin<T>> : Iterable<B> {
     /**
      * Find existing bin, corresponding to given coordinates
      */
-    operator fun get(point: Buffer<out T>): B?
+    operator fun get(point: Point<out T>): B?
 
     /**
      * Dimension of the histogram
      */
     val dimension: Int
 
+}
+
+interface MutableHistogram<T: Any, out B : Bin<T>>: Histogram<T,B>{
+
     /**
      * Increment appropriate bin
      */
-    fun put(point: Buffer<out T>)
+    fun put(point: Point<out T>, weight: Double = 1.0)
 }
 
-fun <T: Any> Histogram<T,*>.put(vararg point: T) = put(ArrayBuffer(point))
+fun <T: Any> MutableHistogram<T,*>.put(vararg point: T) = put(ArrayBuffer(point))
 
-fun <T: Any> Histogram<T,*>.fill(sequence: Iterable<Buffer<T>>) = sequence.forEach { put(it) }
+fun <T: Any> MutableHistogram<T,*>.fill(sequence: Iterable<Point<T>>) = sequence.forEach { put(it) }
 
 /**
  * Pass a sequence builder into histogram
  */
-fun <T: Any> Histogram<T, *>.fill(buider: suspend SequenceScope<Buffer<T>>.() -> Unit) = fill(sequence(buider).asIterable())
+fun <T: Any> MutableHistogram<T, *>.fill(buider: suspend SequenceScope<Point<T>>.() -> Unit) = fill(sequence(buider).asIterable())
 
 /**
  * A space to perform arithmetic operations on histograms

kmath-core/src/commonMain/kotlin/scientifik/kmath/histogram/PhantomHistogram.kt

@@ -0,0 +1,42 @@
+package scientifik.kmath.histogram
+
+import scientifik.kmath.linear.RealVector
+import scientifik.kmath.structures.NDStructure
+
+class BinTemplate(val center: RealVector, val sizes: RealVector) {
+    fun contains(vector: Point<out Double>): Boolean {
+        if (vector.size != center.size) error("Dimension mismatch for input vector. Expected ${center.size}, but found ${vector.size}")
+        return vector.asSequence().mapIndexed { i, value -> value in (center[i] - sizes[i] / 2)..(center[i] + sizes[i] / 2) }.all { it }
+    }
+}
+
+class PhantomBin(val template: BinTemplate, override val value: Number) : Bin<Double> {
+
+    override fun contains(vector: Point<out Double>): Boolean = template.contains(vector)
+
+    override val dimension: Int
+        get() = template.center.size
+
+    override val center: Point<Double>
+        get() = template.center
+
+}
+
+class PhantomHistogram(
+        val bins: Map<BinTemplate, IntArray>,
+        val data: NDStructure<Double>
+) : Histogram<Double, PhantomBin> {
+
+    override val dimension: Int
+        get() = data.dimension
+
+    override fun iterator(): Iterator<PhantomBin> {
+        return bins.asSequence().map {entry-> PhantomBin(entry.key,data[entry.value]) }.iterator()
+    }
+
+    override fun get(point: Point<out Double>): PhantomBin? {
+        val template = bins.keys.find { it.contains(point) }
+        return template?.let { PhantomBin(it, data[bins[it]!!]) }
+    }
+
+}

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

@@ -56,7 +56,7 @@ class ArrayBuffer<T>(private val array: Array<T>) : MutableBuffer<T> {
     override fun copy(): MutableBuffer<T> = ArrayBuffer(array.copyOf())
 }
 
-class DoubleBuffer(private val array: DoubleArray) : MutableBuffer<Double> {
+inline class DoubleBuffer(private val array: DoubleArray) : MutableBuffer<Double> {
     override val size: Int
         get() = array.size
 
@@ -71,6 +71,21 @@ class DoubleBuffer(private val array: DoubleArray) : MutableBuffer<Double> {
     override fun copy(): MutableBuffer<Double> = DoubleBuffer(array.copyOf())
 }
 
+inline class IntBuffer(private val array: IntArray): MutableBuffer<Int>{
+    override val size: Int
+        get() = array.size
+
+    override fun get(index: Int): Int = array[index]
+
+    override fun set(index: Int, value: Int) {
+        array[index] = value
+    }
+
+    override fun iterator(): Iterator<Int>  = array.iterator()
+
+    override fun copy(): MutableBuffer<Int> = IntBuffer(array.copyOf())
+}
+
 inline fun <reified T : Any> buffer(size: Int, noinline initializer: (Int) -> T): Buffer<T> {
     return ArrayBuffer(Array(size, initializer))
 }

kmath-core/src/jvmMain/kotlin/scientifik/kmath/histogram/UnivariateHistogram.kt

@@ -26,7 +26,7 @@ class UnivariateBin(val position: Double, val size: Double, val counter: LongCou
 /**
  * Univariate histogram with log(n) bin search speed
  */
-class UnivariateHistogram private constructor(private val factory: (Double) -> UnivariateBin) : Histogram<Double,UnivariateBin> {
+class UnivariateHistogram private constructor(private val factory: (Double) -> UnivariateBin) : MutableHistogram<Double,UnivariateBin> {
 
     private val bins: TreeMap<Double, UnivariateBin> = TreeMap()
 
@@ -58,7 +58,10 @@ class UnivariateHistogram private constructor(private val factory: (Double) -> U
         (get(value) ?: createBin(value)).inc()
     }
 
-    override fun put(point: Buffer<out Double>) = put(point[0])
+    override fun put(point: Buffer<out Double>, weight: Double) {
+        if (weight != 1.0) TODO("Implement weighting")
+        put(point[0])
+    }
 
     companion object {
         fun uniform(binSize: Double, start: Double = 0.0): UnivariateHistogram {

settings.gradle

@@ -1,13 +0,0 @@
-pluginManagement {
-    repositories {
-        mavenCentral()
-        maven { url = 'https://plugins.gradle.org/m2/' }
-    }
-}
-
-enableFeaturePreview('GRADLE_METADATA')
-
-rootProject.name = 'kmath'
-include ':kmath-core'
-include ':kmath-jmh'
-

settings.gradle.kts

@@ -0,0 +1,14 @@
+pluginManagement {
+    repositories {
+        mavenCentral()
+        maven("https://plugins.gradle.org/m2/")
+    }
+}
+
+enableFeaturePreview("GRADLE_METADATA")
+
+rootProject.name = "kmath"
+include(
+        ":kmath-core",
+        ":kmath-jmh"
+)