benchmarks/src/main/kotlin/scientifik/kmath/structures/StructureWriteBenchmark.kt

@@ -1,6 +1,5 @@
 package scientifik.kmath.structures
 
-import scientifik.kmath.structures.Buffer.Companion.DoubleBufferFactory
 import kotlin.system.measureTimeMillis
 
 
@@ -8,7 +7,7 @@ fun main(args: Array<String>) {
 
     val n = 6000
 
-    val structure = NDStructure.build(intArrayOf(n, n), DoubleBufferFactory) { 1.0 }
+    val structure = NDStructure.build(intArrayOf(n, n), Buffer.Companion::auto) { 1.0 }
 
     structure.mapToBuffer { it + 1 } // warm-up
 

build.gradle.kts

@@ -28,7 +28,7 @@ allprojects {
     }
 
     group = "scientifik"
-    version = "0.0.3-dev"
+    version = "0.1.0-dev"
 
     repositories {
         //maven("https://dl.bintray.com/kotlin/kotlin-eap")

doc/algebra.md

@@ -68,3 +68,44 @@ One important distinction between algebra elements and algebra contexts is that
 The middle type is needed in case algebra members do not store context. For example, it is not possible to add
 a context to regular `Double`. The element performs automatic conversions from context types and back.
 One should used context operations in all important places. The performance of element operations is not guaranteed.
+
+## Spaces and fields
+
+An obvious first choice of mathematical objects to implement in a context-oriented style are algebraic elements like spaces,
+rings and fields. Those are located in the `scientifik.kmath.operations.Algebra.kt` file. Alongside common contexts, the file includes definitions for algebra elements like `FieldElement`. A `FieldElement` object
+stores a reference to the `Field` which contains additive and multiplicative operations, meaning
+it has one fixed context attached and does not require explicit external context. So those `MathElements` can be operated without context:
+
+```kotlin
+val c1 = Complex(1.0, 2.0)
+val c2 = ComplexField.i
+val c3 = c1 + c2
+```
+
+`ComplexField` also features special operations to mix complex and real numbers, for example:
+
+```kotlin
+val c1 = Complex(1.0, 2.0)
+val c2 = ComplexField.run{ c1 - 1.0} // Returns: [re:0.0, im: 2.0]
+val c3 = ComplexField.run{ c1 - i*2.0}
+```
+
+**Note**: In theory it is possible to add behaviors directly to the context, but currently kotlin syntax does not support
+that. Watch [KT-10468](https://youtrack.jetbrains.com/issue/KT-10468) and [KEEP-176](https://github.com/Kotlin/KEEP/pull/176) for updates.
+
+## Nested fields
+
+Contexts allow one to build more complex structures. For example, it is possible to create a `Matrix` from complex elements like so:
+
+```kotlin
+val element = NDElement.complex(shape = intArrayOf(2,2)){ index: IntArray ->
+    Complex(index[0].toDouble() - index[1].toDouble(), index[0].toDouble() + index[1].toDouble())
+}
+```
+
+The `element` in this example is a member of the `Field` of 2-d structures, each element of which is a member of its own
+`ComplexField`. The important thing is one does not need to create a special n-d class to hold complex
+numbers and implement operations on it, one just needs to provide a field for its elements.
+
+**Note**: Fields themselves do not solve the problem of JVM boxing, but it is possible to solve with special contexts like
+`MemorySpec`.

doc/buffers.md

@@ -1 +1,15 @@
-**TODO**
+# Buffers
+Buffer is one of main building blocks of kmath. It is a basic interface allowing random-access read and write (with `MutableBuffer`).
+There are different types of buffers:
+
+* Primitive buffers wrapping like `DoubleBuffer` which are wrapping primitive arrays.
+* Boxing `ListBuffer` wrapping a list
+* Functionally defined `VirtualBuffer` which does not hold a state itself, but provides a function to calculate value
+* `MemoryBuffer` allows direct allocation of objects in continuous memory block.
+
+Some kmath features require a `BufferFactory` class to operate properly. A general convention is to use functions defined in
+`Buffer` and `MutableBuffer` companion classes. For example factory `Buffer.Companion::auto` in most cases creates the most suitable
+buffer for given reified type (for types with custom memory buffer it still better to use their own `MemoryBuffer.create()` factory).
+
+## Buffer performance
+One should avoid using default boxing buffer wherever it is possible. Try to use primitive buffers or memory buffers instead  

doc/features.md

@@ -0,0 +1,17 @@
+# Features
+
+* [Algebra](./algebra.md) - [Context-based](./contexts.md) operations on different primitives and structures.
+
+* [NDStructures](./nd-structure.md)
+
+* [Linear algebra](linear) - Matrices, operations and linear equations solving. To be moved to separate module. Currently supports basic
+api and multiple library back-ends.
+
+* [Histograms](./histograms.md) - Multidimensional histogram calculation and operations.
+
+* [Expressions](./expressions.md)
+
+* Commons math integration
+
+* Koma integration
+

doc/nd-structure.md

@@ -1,3 +1,7 @@
+# Nd-structure generation and operations
+
+**TODO**
+
 # Performance for n-dimensional structures operations
 
 One of the most sought after features of mathematical libraries is the high-performance operations on n-dimensional

doc/operations.md

@@ -1,40 +0,0 @@
-## Spaces and fields
-
-An obvious first choice of mathematical objects to implement in a context-oriented style are algebraic elements like spaces,
-rings and fields. Those are located in the `scientifik.kmath.operations.Algebra.kt` file. Alongside common contexts, the file includes definitions for algebra elements like `FieldElement`. A `FieldElement` object
-stores a reference to the `Field` which contains additive and multiplicative operations, meaning
-it has one fixed context attached and does not require explicit external context. So those `MathElements` can be operated without context:
-
-```kotlin
-val c1 = Complex(1.0, 2.0)
-val c2 = ComplexField.i
-val c3 = c1 + c2
-```
-
-`ComplexField` also features special operations to mix complex and real numbers, for example:
-
-```kotlin
-val c1 = Complex(1.0, 2.0)
-val c2 = ComplexField.run{ c1 - 1.0} // Returns: [re:0.0, im: 2.0]
-val c3 = ComplexField.run{ c1 - i*2.0}
-```
-
-**Note**: In theory it is possible to add behaviors directly to the context, but currently kotlin syntax does not support
-that. Watch [KT-10468](https://youtrack.jetbrains.com/issue/KT-10468) and [KEEP-176](https://github.com/Kotlin/KEEP/pull/176) for updates.
-
-## Nested fields
-
-Contexts allow one to build more complex structures. For example, it is possible to create a `Matrix` from complex elements like so:
-
-```kotlin
-val element = NDElement.complex(shape = intArrayOf(2,2)){ index: IntArray ->
-    Complex(index[0].toDouble() - index[1].toDouble(), index[0].toDouble() + index[1].toDouble())
-}
-```
-
-The `element` in this example is a member of the `Field` of 2-d structures, each element of which is a member of its own
-`ComplexField`. The important thing is one does not need to create a special n-d class to hold complex
-numbers and implement operations on it, one just needs to provide a field for its elements.
-
-**Note**: Fields themselves do not solve the problem of JVM boxing, but it is possible to solve with special contexts like
-`BufferSpec`. This feature is in development phase.

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

@@ -4,7 +4,6 @@ import scientifik.kmath.operations.RealField
 import scientifik.kmath.operations.Ring
 import scientifik.kmath.operations.sum
 import scientifik.kmath.structures.*
-import scientifik.kmath.structures.Buffer.Companion.DoubleBufferFactory
 import scientifik.kmath.structures.Buffer.Companion.boxing
 import kotlin.math.sqrt
 
@@ -33,7 +32,7 @@ interface MatrixContext<T : Any> {
         /**
          * Non-boxing double matrix
          */
-        val real = BufferMatrixContext(RealField, DoubleBufferFactory)
+        val real = BufferMatrixContext(RealField, Buffer.Companion::auto)
 
         /**
          * A structured matrix with custom buffer

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

@@ -42,7 +42,7 @@ interface VectorSpace<T : Any, S : Space<T>> : Space<Point<T>> {
          * Non-boxing double vector space
          */
         fun real(size: Int): BufferVectorSpace<Double, RealField> {
-            return realSpaceCache.getOrPut(size) { BufferVectorSpace(size, RealField, Buffer.DoubleBufferFactory) }
+            return realSpaceCache.getOrPut(size) { BufferVectorSpace(size, RealField, Buffer.Companion::auto) }
         }
 
         /**

kmath-core/src/commonMain/kotlin/scientifik/kmath/operations/Complex.kt

@@ -1,8 +1,8 @@
 package scientifik.kmath.operations
 
 import scientifik.kmath.structures.Buffer
+import scientifik.kmath.structures.MemoryBuffer
 import scientifik.kmath.structures.MutableBuffer
-import scientifik.kmath.structures.ObjectBuffer
 import scientifik.memory.MemoryReader
 import scientifik.memory.MemorySpec
 import scientifik.memory.MemoryWriter
@@ -88,10 +88,10 @@ data class Complex(val re: Double, val im: Double) : FieldElement<Complex, Compl
 
 fun Double.toComplex() = Complex(this, 0.0)
 
-fun Buffer.Companion.complex(size: Int, init: (Int) -> Complex): Buffer<Complex> {
-    return ObjectBuffer.create(Complex, size, init)
+inline fun Buffer.Companion.complex(size: Int, crossinline init: (Int) -> Complex): Buffer<Complex> {
+    return MemoryBuffer.create(Complex, size, init)
 }
 
-fun MutableBuffer.Companion.complex(size: Int, init: (Int) -> Complex): Buffer<Complex> {
-    return ObjectBuffer.create(Complex, size, init)
+inline fun MutableBuffer.Companion.complex(size: Int, crossinline init: (Int) -> Complex): Buffer<Complex> {
+    return MemoryBuffer.create(Complex, size, init)
 }

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

@@ -1,5 +1,8 @@
 package scientifik.kmath.structures
 
+import scientifik.kmath.operations.Complex
+import scientifik.kmath.operations.complex
+
 
 typealias BufferFactory<T> = (Int, (Int) -> T) -> Buffer<T>
 typealias MutableBufferFactory<T> = (Int, (Int) -> T) -> MutableBuffer<T>
@@ -43,21 +46,16 @@ interface Buffer<T> {
          */
         @Suppress("UNCHECKED_CAST")
         inline fun <reified T : Any> auto(size: Int, crossinline initializer: (Int) -> T): Buffer<T> {
+            //TODO add resolution based on Annotation or companion resolution
             return when (T::class) {
                 Double::class -> DoubleBuffer(DoubleArray(size) { initializer(it) as Double }) as Buffer<T>
                 Short::class -> ShortBuffer(ShortArray(size) { initializer(it) as Short }) as Buffer<T>
                 Int::class -> IntBuffer(IntArray(size) { initializer(it) as Int }) as Buffer<T>
                 Long::class -> LongBuffer(LongArray(size) { initializer(it) as Long }) as Buffer<T>
+                Complex::class -> complex(size) { initializer(it) as Complex } as Buffer<T>
                 else -> boxing(size, initializer)
             }
         }
-
-        val DoubleBufferFactory: BufferFactory<Double> =
-            { size, initializer -> DoubleBuffer(DoubleArray(size, initializer)) }
-        val ShortBufferFactory: BufferFactory<Short> =
-            { size, initializer -> ShortBuffer(ShortArray(size, initializer)) }
-        val IntBufferFactory: BufferFactory<Int> = { size, initializer -> IntBuffer(IntArray(size, initializer)) }
-        val LongBufferFactory: BufferFactory<Long> = { size, initializer -> LongBuffer(LongArray(size, initializer)) }
     }
 }
 

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

@@ -5,7 +5,7 @@ import scientifik.memory.*
 /**
  * A non-boxing buffer based on [ByteBuffer] storage
  */
-open class ObjectBuffer<T : Any>(protected val memory: Memory, protected val spec: MemorySpec<T>) : Buffer<T> {
+open class MemoryBuffer<T : Any>(protected val memory: Memory, protected val spec: MemorySpec<T>) : Buffer<T> {
 
     override val size: Int get() = memory.size / spec.objectSize
 
@@ -18,14 +18,14 @@ open class ObjectBuffer<T : Any>(protected val memory: Memory, protected val spe
 
     companion object {
         fun <T : Any> create(spec: MemorySpec<T>, size: Int) =
-            ObjectBuffer(Memory.allocate(size * spec.objectSize), spec)
+            MemoryBuffer(Memory.allocate(size * spec.objectSize), spec)
 
         inline fun <T : Any> create(
             spec: MemorySpec<T>,
             size: Int,
             crossinline initializer: (Int) -> T
-        ): ObjectBuffer<T> =
-            MutableObjectBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
+        ): MemoryBuffer<T> =
+            MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
                 (0 until size).forEach {
                     buffer[it] = initializer(it)
                 }
@@ -33,16 +33,28 @@ open class ObjectBuffer<T : Any>(protected val memory: Memory, protected val spe
     }
 }
 
-class MutableObjectBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) : ObjectBuffer<T>(memory, spec),
+class MutableMemoryBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) : MemoryBuffer<T>(memory, spec),
     MutableBuffer<T> {
 
     private val writer = memory.writer()
 
     override fun set(index: Int, value: T) = writer.write(spec, spec.objectSize * index, value)
 
-    override fun copy(): MutableBuffer<T> = MutableObjectBuffer(memory.copy(), spec)
+    override fun copy(): MutableBuffer<T> = MutableMemoryBuffer(memory.copy(), spec)
 
     companion object {
+        fun <T : Any> create(spec: MemorySpec<T>, size: Int) =
+            MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec)
 
+        inline fun <T : Any> create(
+            spec: MemorySpec<T>,
+            size: Int,
+            crossinline initializer: (Int) -> T
+        ) =
+            MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
+                (0 until size).forEach {
+                    buffer[it] = initializer(it)
+                }
+            }
     }
 }

kmath-memory/src/commonMain/kotlin/scientifik/memory/MemorySpec.kt

@@ -1,5 +1,7 @@
 package scientifik.memory
 
+import kotlin.reflect.KClass
+
 /**
  * A specification to read or write custom objects with fixed size in bytes
  */