Add non-boxing BufferView access

kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/bufferPrimitiveAccess.kt

@@ -0,0 +1,37 @@
+package space.kscience.kmath.structures
+
+import space.kscience.kmath.misc.UnstableKMathAPI
+
+/**
+ * Non-boxing access to primitive [Double]
+ */
+@OptIn(UnstableKMathAPI::class)
+public fun Buffer<Double>.getDouble(index: Int): Double = if (this is BufferView) {
+    val originIndex = originIndex(index)
+    if( originIndex>=0) {
+        origin.getDouble(originIndex)
+    } else {
+        get(index)
+    }
+} else if (this is DoubleBuffer) {
+    array[index]
+} else {
+    get(index)
+}
+
+/**
+ * Non-boxing access to primitive [Int]
+ */
+@OptIn(UnstableKMathAPI::class)
+public fun Buffer<Int>.getInt(index: Int): Int = if (this is BufferView) {
+    val originIndex = originIndex(index)
+    if( originIndex>=0) {
+        origin.getInt(originIndex)
+    } else {
+        get(index)
+    }
+} else if (this is IntBuffer) {
+    array[index]
+} else {
+    get(index)
+}

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/random/MCScope.kt

@@ -3,7 +3,7 @@
  * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file.
  */
 
-package space.kscience.kmath.stat
+package space.kscience.kmath.random
 
 import kotlinx.coroutines.*
 import kotlin.contracts.InvocationKind

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/random/RandomChain.kt

@@ -3,7 +3,7 @@
  * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file.
  */
 
-package space.kscience.kmath.stat
+package space.kscience.kmath.random
 
 import space.kscience.kmath.chains.BlockingDoubleChain
 import space.kscience.kmath.chains.Chain

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/random/RandomGenerator.kt

@@ -3,7 +3,7 @@
  * Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file.
  */
 
-package space.kscience.kmath.stat
+package space.kscience.kmath.random
 
 import space.kscience.kmath.structures.DoubleBuffer
 import kotlin.random.Random

kmath-stat/src/commonMain/kotlin/space/kscience/kmath/stat/Rank.kt

@@ -3,26 +3,33 @@ package space.kscience.kmath.stat
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.asIterable
 
-public class Rank<T: Comparable<T>>: BlockingStatistic<T, IntArray> {
-    override fun evaluateBlocking(data: Buffer<T>): IntArray {
-        // https://www.geeksforgeeks.org/rank-elements-array/
-        val permutations = ArrayList<Pair<T, Int>>(data.size)
-        data.asIterable().mapIndexedTo(permutations) { i, v -> v to i }
-        permutations.sortBy { it.first }
-        var rank = 1
-        var i = 0
-        val r = IntArray(data.size) { 0 }
-        while (i < data.size) {
-            var j = i
-            while (j < data.size - 1 && permutations[j].first == permutations[j + 1]) ++j
-            val n = j - i + 1
-            (0 until n).map { k ->
-                val idx = permutations[i + k].second
-                r[idx] = rank + ((n - 1) * 0.5f).toInt()
+/**
+ * Rank statistics
+ */
+public class Rank<T : Comparable<T>> : BlockingStatistic<T, IntArray> {
+    override fun evaluateBlocking(data: Buffer<T>): IntArray = Companion.evaluate(data)
+
+    public companion object {
+        public fun <T : Comparable<T>> evaluate(data: Buffer<T>): IntArray {
+            // https://www.geeksforgeeks.org/rank-elements-array/
+            val permutations = ArrayList<Pair<T, Int>>(data.size)
+            data.asIterable().mapIndexedTo(permutations) { i, v -> v to i }
+            permutations.sortBy { it.first }
+            var rank = 1
+            var i = 0
+            val r = IntArray(data.size)
+            while (i < data.size) {
+                var j = i
+                while (j < data.size - 1 && permutations[j].first == permutations[j + 1]) ++j
+                val n = j - i + 1
+                (0 until n).map { k ->
+                    val idx = permutations[i + k].second
+                    r[idx] = rank + ((n - 1) * 0.5f).toInt()
+                }
+                rank += n
+                i += n
             }
-            rank += n
-            i += n
+            return r
         }
-        return r
     }
 }