Histograms for jvm are in working order.

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

@@ -0,0 +1,20 @@
+package scientifik.kmath.histogram
+
+/*
+ * Common representation for atomic counters
+ */
+
+
+expect class LongCounter(){
+    fun	decrement()
+    fun	increment()
+    fun	reset()
+    fun	sum(): Long
+    fun add(l:Long)
+}
+
+expect class DoubleCounter(){
+    fun	reset()
+    fun	sum(): Double
+    fun add(d: Double)
+}

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

@@ -1,12 +1,22 @@
 package scientifik.kmath.histogram
 
 import scientifik.kmath.linear.RealVector
+import scientifik.kmath.linear.toVector
 import scientifik.kmath.operations.Space
 
+/**
+ * A simple geometric domain
+ * TODO move to geometry module
+ */
+interface Domain {
+    operator fun contains(vector: RealVector): Boolean
+    val dimension: Int
+}
+
 /**
  * The bin in the histogram. The histogram is by definition always done in the real space
  */
-interface Bin {
+interface Bin : Domain {
     /**
      * The value of this bin
      */
@@ -14,26 +24,36 @@ interface Bin {
     val center: RealVector
 }
 
-/**
- * Creates a new bin with zero count corresponding to given point
- */
-interface BinFactory<out B : Bin> {
-    fun createBin(point: RealVector): B
-}
-
 interface Histogram<out B : Bin> : Iterable<B> {
 
     /**
      * Find existing bin, corresponding to given coordinates
      */
-    fun findBin(point: RealVector): B?
+    operator fun get(point: RealVector): B?
 
     /**
      * Dimension of the histogram
      */
     val dimension: Int
+
+    /**
+     * Increment appropriate bin
+     */
+    fun put(point: RealVector)
 }
 
+fun Histogram<*>.put(vararg point: Double) = put(point.toVector())
+
+fun Histogram<*>.fill(sequence: Iterable<RealVector>) = sequence.forEach { put(it) }
+
+/**
+ * Pass a sequence builder into histogram
+ */
+fun Histogram<*>.fill(buider: suspend SequenceScope<RealVector>.() -> Unit) = fill(sequence(buider).asIterable())
+
+/**
+ * A space to perform arithmetic operations on histograms
+ */
 interface HistogramSpace<B : Bin, H : Histogram<B>> : Space<H> {
     /**
      * Rules for performing operations on bins

kmath-core/src/commonMain/kotlin/scientifik/kmath/linear/LinearAlgrebra.kt

@@ -162,9 +162,8 @@ abstract class VectorSpace<T : Any>(val size: Int, val field: Field<T>) : Space<
 }
 
 
-interface Vector<T : Any> : SpaceElement<Vector<T>, VectorSpace<T>> {
+interface Vector<T : Any> : SpaceElement<Vector<T>, VectorSpace<T>>, Iterable<T> {
-    val size: Int
+    val size: Int get() = context.size
-        get() = context.size
 
     operator fun get(i: Int): T
 
@@ -181,6 +180,8 @@ interface Vector<T : Any> : SpaceElement<Vector<T>, VectorSpace<T>> {
         fun ofReal(size: Int, initializer: (Int) -> Double) =
                 ArrayVector(ArrayVectorSpace(size, DoubleField, realNDFieldFactory), initializer)
 
+        fun ofReal(vararg point: Double) = point.toVector()
+
         fun equals(v1: Vector<*>, v2: Vector<*>): Boolean {
             if (v1 === v2) return true
             if (v1.context != v2.context) return false
@@ -265,6 +266,10 @@ class ArrayVector<T : Any> internal constructor(override val context: ArrayVecto
     }
 
     override val self: ArrayVector<T> get() = this
+
+    override fun iterator(): Iterator<T> = (0 until size).map { array[it] }.iterator()
+
+    override fun toString(): String = this.joinToString(prefix = "[",postfix = "]", separator = ", "){it.toString()}
 }
 
 typealias RealVector = Vector<Double>
@@ -284,6 +289,7 @@ interface LinearSolver<T : Any> {
 fun <T : Any> Array<T>.toVector(field: Field<T>) = Vector.of(size, field) { this[it] }
 
 fun DoubleArray.toVector() = Vector.ofReal(this.size) { this[it] }
+fun List<Double>.toVector() = Vector.ofReal(this.size) { this[it] }
 
 /**
  * Convert matrix to vector if it is possible

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

@@ -105,9 +105,12 @@ abstract class NDField<T>(val shape: IntArray, val field: Field<T>) : Field<NDAr
 }
 
 /**
- * NDStructure coupled to the context. Emulates Python ndarray
+ *  Immutable [NDStructure] coupled to the context. Emulates Python ndarray
  */
 data class NDArray<T>(override val context: NDField<T>, private val structure: NDStructure<T>) : FieldElement<NDArray<T>, NDField<T>>, NDStructure<T> by structure {
+
+    //TODO ensure structure is immutable
+
     override val self: NDArray<T>
         get() = this
 

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

@@ -76,7 +76,7 @@ class DefaultStrides(override val shape: IntArray) : Strides {
     override fun offset(index: IntArray): Int {
         return index.mapIndexed { i, value ->
             if (value < 0 || value >= shape[i]) {
-                throw RuntimeException("Index out of shape bounds: ($i,$value)")
+                throw RuntimeException("Index $value out of shape bounds: (0,${shape[i]})")
             }
             value * strides[i]
         }.sum()

kmath-core/src/jsMain/kotlin/scientifik/kmath/histogram/Counters.kt

@@ -0,0 +1,16 @@
+package scientifik.kmath.histogram
+
+actual class LongCounter{
+    private var sum: Long = 0
+    actual fun decrement() {sum--}
+    actual fun increment() {sum++}
+    actual fun reset() {sum = 0}
+    actual fun sum(): Long = sum
+    actual fun add(l: Long) {sum+=l}
+}
+actual class DoubleCounter{
+    private var sum: Double = 0.0
+    actual fun reset() {sum = 0.0}
+    actual fun sum(): Double = sum
+    actual fun add(d: Double) {sum+=d}
+}

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

@@ -0,0 +1,7 @@
+package scientifik.kmath.histogram
+
+import java.util.concurrent.atomic.DoubleAdder
+import java.util.concurrent.atomic.LongAdder
+
+actual typealias LongCounter = LongAdder
+actual typealias DoubleCounter = DoubleAdder

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

@@ -0,0 +1,117 @@
+package scientifik.kmath.histogram
+
+import scientifik.kmath.linear.RealVector
+import scientifik.kmath.linear.toVector
+import scientifik.kmath.structures.NDStructure
+import scientifik.kmath.structures.ndStructure
+import kotlin.math.floor
+
+class MultivariateBin(override val center: RealVector, val sizes: RealVector, val counter: LongCounter = LongCounter()) : Bin {
+    init {
+        if (center.size != sizes.size) error("Dimension mismatch in bin creation. Expected ${center.size}, but found ${sizes.size}")
+    }
+
+    override fun contains(vector: RealVector): Boolean {
+        assert(vector.size == center.size)
+        return vector.asSequence().mapIndexed { i, value -> value in (center[i] - sizes[i] / 2)..(center[i] + sizes[i] / 2) }.all { it }
+    }
+
+    override val value: Number get() = counter.sum()
+    internal operator fun inc() = this.also { counter.increment() }
+
+    override val dimension: Int get() = center.size
+}
+
+/**
+ * Uniform multivariate histogram with fixed borders. Based on NDStructure implementation with complexity of m for bin search, where m is the number of dimensions
+ */
+class FastHistogram(
+        private val lower: RealVector,
+        private val upper: RealVector,
+        private val binNums: IntArray = IntArray(lower.size) { 100 }
+) : Histogram<MultivariateBin> {
+
+    init {
+        // argument checks
+        if (lower.size != upper.size) error("Dimension mismatch in histogram lower and upper limits.")
+        if (lower.size != binNums.size) error("Dimension mismatch in bin count.")
+        if ((upper - lower).any { it <= 0 }) error("Range for one of axis is not strictly positive")
+    }
+
+
+    override val dimension: Int get() = lower.size
+
+    //TODO optimize binSize performance if needed
+    private val binSize = (upper - lower).mapIndexed { index, value -> value / binNums[index] }.toVector()
+
+    private val bins: NDStructure<MultivariateBin> by lazy {
+        val actualSizes = IntArray(binNums.size) { binNums[it] + 2 }
+        ndStructure(actualSizes) { indexArray ->
+            val center = indexArray.mapIndexed { axis, index ->
+                when (index) {
+                    0 -> Double.NEGATIVE_INFINITY
+                    actualSizes[axis] -> Double.POSITIVE_INFINITY
+                    else -> lower[axis] + (index - 1) * binSize[axis]
+                }
+            }.toVector()
+            MultivariateBin(center, binSize)
+        }
+    }
+
+    /**
+     * Get internal [NDStructure] bin index for given axis
+     */
+    private fun getIndex(axis: Int, value: Double): Int {
+        return when {
+            value >= upper[axis] -> binNums[axis] + 1 // overflow
+            value < lower[axis] -> 0 // underflow
+            else -> floor((value - lower[axis]) / binSize[axis]).toInt() + 1
+        }
+    }
+
+
+    override fun get(point: RealVector): MultivariateBin? {
+        val index = IntArray(dimension) { getIndex(it, point[it]) }
+        return bins[index]
+    }
+
+    override fun put(point: RealVector) {
+        this[point]?.inc() ?: error("Could not find appropriate bin (should not be possible)")
+    }
+
+    override fun iterator(): Iterator<MultivariateBin> = bins.asSequence().map { it.second }.iterator()
+
+    companion object {
+
+        /**
+         * Use it like
+         * ```
+         *FastHistogram.fromRanges(
+         *  (-1.0..1.0),
+         *  (-1.0..1.0)
+         *)
+         *```
+         */
+        fun fromRanges(vararg ranges: ClosedFloatingPointRange<Double>): FastHistogram {
+            return FastHistogram(ranges.map { it.start }.toVector(), ranges.map { it.endInclusive }.toVector())
+        }
+
+        /**
+         * Use it like
+         * ```
+         *FastHistogram.fromRanges(
+         *  (-1.0..1.0) to 50,
+         *  (-1.0..1.0) to 32
+         *)
+         *```
+         */
+        fun fromRanges(vararg ranges: Pair<ClosedFloatingPointRange<Double>,Int>): FastHistogram {
+            return FastHistogram(
+                    ranges.map { it.first.start }.toVector(),
+                    ranges.map { it.first.endInclusive }.toVector(),
+                    ranges.map { it.second }.toIntArray()
+            )
+        }
+    }
+
+}

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

@@ -0,0 +1,88 @@
+package scientifik.kmath.histogram
+
+import scientifik.kmath.linear.RealVector
+import scientifik.kmath.linear.toVector
+import java.util.*
+import kotlin.math.floor
+
+//TODO move to common
+
+class UnivariateBin(val position: Double, val size: Double, val counter: LongCounter = LongCounter()) : Bin {
+    //TODO add weighting
+    override val value: Number get() = counter.sum()
+
+    override val center: RealVector get() = doubleArrayOf(position).toVector()
+
+    operator fun contains(value: Double): Boolean = value in (position - size / 2)..(position + size / 2)
+
+    override fun contains(vector: RealVector): Boolean = contains(vector[0])
+
+    internal operator fun inc() = this.also { counter.increment()}
+
+    override val dimension: Int get() = 1
+}
+
+/**
+ * Univariate histogram with log(n) bin search speed
+ */
+class UnivariateHistogram private constructor(private val factory: (Double) -> UnivariateBin) : Histogram<UnivariateBin> {
+
+    private val bins: TreeMap<Double, UnivariateBin> = TreeMap()
+
+    private operator fun get(value: Double): UnivariateBin? {
+        // check ceiling entry and return it if it is what needed
+        val ceil = bins.ceilingEntry(value)?.value
+        if (ceil != null && value in ceil) return ceil
+        //check floor entry
+        val floor = bins.floorEntry(value)?.value
+        if (floor != null && value in floor) return floor
+        //neither is valid, not found
+        return null
+    }
+
+    private fun createBin(value: Double): UnivariateBin = factory(value).also {
+        synchronized(this) { bins.put(it.position, it) }
+    }
+
+    override fun get(point: RealVector): UnivariateBin? = get(point[0])
+
+    override val dimension: Int get() = 1
+
+    override fun iterator(): Iterator<UnivariateBin> = bins.values.iterator()
+
+    /**
+     * Thread safe put operation
+     */
+    fun put(value: Double) {
+        (get(value) ?: createBin(value)).inc()
+    }
+
+    override fun put(point: RealVector) = put(point[0])
+
+    companion object {
+        fun uniform(binSize: Double, start: Double = 0.0): UnivariateHistogram {
+            return UnivariateHistogram { value ->
+                val center = start + binSize * floor((value - start) / binSize + 0.5)
+                UnivariateBin(center, binSize)
+            }
+        }
+
+        fun custom(borders: DoubleArray): UnivariateHistogram {
+            val sorted = borders.sortedArray()
+            return UnivariateHistogram { value ->
+                if (value < sorted.first()) {
+                    UnivariateBin(Double.NEGATIVE_INFINITY, Double.MAX_VALUE)
+                } else if (value > sorted.last()) {
+                    UnivariateBin(Double.POSITIVE_INFINITY, Double.MAX_VALUE)
+                } else {
+                    val index = (0 until sorted.size).first { value > sorted[it] }
+                    val left = sorted[index]
+                    val right = sorted[index + 1]
+                    UnivariateBin((left + right) / 2, (right - left))
+                }
+            }
+        }
+    }
+}
+
+fun UnivariateHistogram.fill(sequence: Iterable<Double>) = sequence.forEach { put(it) }

kmath-core/src/jvmTest/kotlin/scientifik/kmath/histogram/MultivariateHistogramTest.kt

@@ -0,0 +1,43 @@
+package scientifik.kmath.histogram
+
+import org.junit.Test
+import scientifik.kmath.linear.Vector
+import kotlin.random.Random
+import kotlin.test.assertEquals
+import kotlin.test.assertFalse
+import kotlin.test.assertTrue
+
+class MultivariateHistogramTest {
+    @Test
+    fun testSinglePutHistogram() {
+        val histogram = FastHistogram.fromRanges(
+                (-1.0..1.0),
+                (-1.0..1.0)
+        )
+        histogram.put(0.6, 0.6)
+        val bin = histogram.find { it.value.toInt() > 0 }!!
+        assertTrue { bin.contains(Vector.ofReal(0.6, 0.6)) }
+        assertFalse { bin.contains(Vector.ofReal(-0.6, 0.6)) }
+    }
+
+    @Test
+    fun testSequentialPut(){
+        val histogram = FastHistogram.fromRanges(
+                (-1.0..1.0),
+                (-1.0..1.0),
+                (-1.0..1.0)
+        )
+        val random = Random(1234)
+
+        fun nextDouble() = random.nextDouble(-1.0,1.0)
+
+        val n = 10000
+
+        histogram.fill {
+            repeat(n){
+                yield(Vector.ofReal(nextDouble(),nextDouble(),nextDouble()))
+            }
+        }
+        assertEquals(n, histogram.sumBy { it.value.toInt() })
+    }
+}