Fixed #5 by removing requirement of NDArray element to be Field element and introducing DoubleField without corresponding element.

build.gradle

@@ -1,3 +1,14 @@
-group = 'scientifik'
+buildscript {
-version = '0.1-SNAPSHOT'
+    ext.kotlin_version = '1.2.41'
+
+    repositories {
+        mavenCentral()
+    }
+    dependencies {
+        classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
+    }
+}
+
+group = 'scientifik'
+version = '0.1 - SNAPSHOT'
 

common/build.gradle

@@ -1,14 +1,3 @@
-buildscript {
-    ext.kotlin_version = '1.2.40'
-
-    repositories {
-        mavenCentral()
-    }
-    dependencies {
-        classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
-    }
-}
-
 description = "Platform-independent interfaces for kotlin maths"
 
 apply plugin: 'kotlin-platform-common'

common/src/main/kotlin/scientifik/kmath/operations/Algebra.kt

@@ -90,7 +90,7 @@ interface Field<T> : Ring<T> {
     fun divide(a: T, b: T): T
 
     operator fun T.div(b: T): T = divide(this, b)
-    operator fun Double.div(b: T) = this * divide(one, b)
+    operator fun Number.div(b: T) = this * divide(one, b)
 }
 
 /**

common/src/main/kotlin/scientifik/kmath/operations/Fields.kt

@@ -76,3 +76,11 @@ data class Complex(val re: Double, val im: Double) : FieldElement<Complex> {
     //TODO is it convenient?
     operator fun not() = conjugate
 }
+
+object DoubleField : Field<Double> {
+    override val zero: Double = 0.0
+    override fun add(a: Double, b: Double): Double = a + b
+    override fun multiply(a: Double, b: Double): Double = a * b
+    override val one: Double = 1.0
+    override fun divide(a: Double, b: Double): Double = a / b
+}

common/src/main/kotlin/scientifik/kmath/structures/NDArray.kt

@@ -2,23 +2,22 @@ package scientifik.kmath.structures
 
 import scientifik.kmath.operations.Field
 import scientifik.kmath.operations.FieldElement
-import scientifik.kmath.operations.Real
 
 class ShapeMismatchException(val expected: List<Int>, val actual: List<Int>) : RuntimeException()
 
 /**
  * Field for n-dimensional arrays.
  * @param shape - the list of dimensions of the array
- * @param elementField - operations field defined on individual array element
+ * @param field - operations field defined on individual array element
  */
-abstract class NDField<T : FieldElement<T>>(val shape: List<Int>, val elementField: Field<T>) : Field<NDArray<T>> {
+abstract class NDField<T>(val shape: List<Int>, val field: Field<T>) : Field<NDArray<T>> {
     /**
      * Create new instance of NDArray using field shape and given initializer
      */
     abstract fun produce(initializer: (List<Int>) -> T): NDArray<T>
 
     override val zero: NDArray<T>
-        get() = produce { elementField.zero }
+        get() = produce { this.field.zero }
 
     private fun checkShape(vararg arrays: NDArray<T>) {
         arrays.forEach {
@@ -33,7 +32,7 @@ abstract class NDField<T : FieldElement<T>>(val shape: List<Int>, val elementFie
      */
     override fun add(a: NDArray<T>, b: NDArray<T>): NDArray<T> {
         checkShape(a, b)
-        return produce { a[it] + b[it] }
+        return produce { with(field) { a[it] + b[it] } }
     }
 
     /**
@@ -41,18 +40,18 @@ abstract class NDField<T : FieldElement<T>>(val shape: List<Int>, val elementFie
      */
     override fun multiply(a: NDArray<T>, k: Double): NDArray<T> {
         checkShape(a)
-        return produce { a[it] * k }
+        return produce { with(field) {a[it] * k} }
     }
 
     override val one: NDArray<T>
-        get() = produce { elementField.one }
+        get() = produce { this.field.one }
 
     /**
      * Element-by-element multiplication
      */
     override fun multiply(a: NDArray<T>, b: NDArray<T>): NDArray<T> {
         checkShape(a)
-        return produce { a[it] * b[it] }
+        return produce { with(field) {a[it] * b[it]} }
     }
 
     /**
@@ -60,12 +59,12 @@ abstract class NDField<T : FieldElement<T>>(val shape: List<Int>, val elementFie
      */
     override fun divide(a: NDArray<T>, b: NDArray<T>): NDArray<T> {
         checkShape(a)
-        return produce { a[it] / b[it] }
+        return produce { with(field) {a[it] / b[it]} }
     }
 }
 
 
-interface NDArray<T : FieldElement<T>> : FieldElement<NDArray<T>>, Iterable<Pair<List<Int>, T>> {
+interface NDArray<T> : FieldElement<NDArray<T>>, Iterable<Pair<List<Int>, T>> {
 
     /**
      * The list of dimensions of this NDArray
@@ -119,12 +118,12 @@ interface NDArray<T : FieldElement<T>> : FieldElement<NDArray<T>>, Iterable<Pair
 /**
  * Create a platform-specific NDArray of doubles
  */
-expect fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double = { 0.0 }): NDArray<Real>
+expect fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double = { 0.0 }): NDArray<Double>
 
-fun real2DArray(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDArray<Real> {
+fun real2DArray(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDArray<Double> {
     return realNDArray(listOf(dim1, dim2)) { initializer(it[0], it[1]) }
 }
 
-fun real3DArray(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDArray<Real> {
+fun real3DArray(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDArray<Double> {
     return realNDArray(listOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
 }

jvm/build.gradle

@@ -1,15 +1,3 @@
-buildscript {
-    ext.kotlin_version = '1.2.40'
-
-    repositories {
-        mavenCentral()
-    }
-    dependencies {
-        classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
-    }
-}
-
-
 apply plugin: 'kotlin-platform-jvm'
 
 repositories {

jvm/src/main/kotlin/scientifik/kmath/structures/RealNDArray.kt

@@ -1,10 +1,9 @@
 package scientifik.kmath.structures
 
-import scientifik.kmath.operations.Real
+import scientifik.kmath.operations.DoubleField
-import scientifik.kmath.operations.RealField
 import java.nio.DoubleBuffer
 
-private class RealNDField(shape: List<Int>) : NDField<Real>(shape, RealField) {
+private class RealNDField(shape: List<Int>) : NDField<Double>(shape, DoubleField) {
 
     /**
      * Strides for memory access
@@ -33,19 +32,19 @@ private class RealNDField(shape: List<Int>) : NDField<Real>(shape, RealField) {
         get() = strides[shape.size]
 
 
-    override fun produce(initializer: (List<Int>) -> Real): NDArray<Real> {
+    override fun produce(initializer: (List<Int>) -> Double): NDArray<Double> {
         //TODO use sparse arrays for large capacities
         val buffer = DoubleBuffer.allocate(capacity)
         NDArray.iterateIndexes(shape).forEach {
-            buffer.put(offset(it), initializer(it).value)
+            buffer.put(offset(it), initializer(it))
         }
         return RealNDArray(this, buffer)
     }
 
-    class RealNDArray(override val context: RealNDField, val data: DoubleBuffer) : NDArray<Real> {
+    class RealNDArray(override val context: RealNDField, val data: DoubleBuffer) : NDArray<Double> {
 
-        override fun get(vararg index: Int): Real {
+        override fun get(vararg index: Int): Double {
-            return Real(data.get(context.offset(index.asList())))
+            return data.get(context.offset(index.asList()))
         }
 
         override fun equals(other: Any?): Boolean {
@@ -69,12 +68,12 @@ private class RealNDField(shape: List<Int>) : NDField<Real>(shape, RealField) {
         //TODO generate fixed hash code for quick comparison?
 
 
-        override val self: NDArray<Real> = this
+        override val self: NDArray<Double> = this
     }
 }
 
 
-actual fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double): NDArray<Real> {
+actual fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double): NDArray<Double> {
     //TODO cache fields?
-    return RealNDField(shape).produce { Real(initializer(it)) }
+    return RealNDField(shape).produce { initializer(it) }
 }

jvm/src/test/kotlin/scientifik/kmath/structures/RealNDFieldTest.kt

@@ -10,13 +10,13 @@ class RealNDFieldTest {
     @Test
     fun testSum() {
         val sum = array1 + array2
-        assertEquals(4.0, sum[2, 2].toDouble(), 0.1)
+        assertEquals(4.0, sum[2, 2], 0.1)
     }
 
     @Test
     fun testProduct(){
         val product = array1*array2
-        assertEquals(0.0, product[2, 2].toDouble(), 0.1)
+        assertEquals(0.0, product[2, 2], 0.1)
     }
 
     @Test
@@ -27,7 +27,7 @@ class RealNDFieldTest {
         for(i in 0..2){
             for(j in 0..2){
                 val expected= (i * 10 + j).toDouble()
-                assertEquals("Error at index [$i, $j]", expected, array[i,j].value, 0.1)
+                assertEquals("Error at index [$i, $j]", expected, array[i,j], 0.1)
             }
         }
     }