Switch to kotlin 1.3 eap and mpp build

README.md

@@ -40,8 +40,33 @@ but worse than optimized native/scipy (mostly due to boxing operations on primit
 of optimized parts should be better than scipy.
 
 ## Releases
-The project is currently in pre-release stage. Work builds could be obtained with 
-[![](https://jitpack.io/v/altavir/kmath.svg)](https://jitpack.io/#altavir/kmath). 
+
+The project is currently in pre-release stage. Nightly builds could be used by adding additional repository to (groovy) gradle config:
+```groovy
+repositories {
+    maven { url = "http://npm.mipt.ru:8081/artifactory/gradle-dev" }
+    mavenCentral()
+} 
+```
+or for kotlin gradle dsl:
+
+```kotlin
+repositories {
+    maven { setUrl("http://npm.mipt.ru:8081/artifactory/gradle-dev") }
+    mavenCentral()
+} 
+```
+
+Then use regular dependency like
+```groovy
+compile(group: 'scientifik', name: 'kmath-core-jvm', version: '0.0.1-SNAPSHOT')
+```
+or in kotlin
+```kotlin
+compile(group = "scientifik", name = "kmath-core-jvm", version = "0.0.1-SNAPSHOT")
+```
+
+Work builds could be obtained with [![](https://jitpack.io/v/altavir/kmath.svg)](https://jitpack.io/#altavir/kmath). 
 
 ## Contributing
 The project requires a lot of additional work. Please fill free to contribute in any way and propose new features.

build.gradle

@@ -1,17 +1,19 @@
 buildscript {
-    ext.kotlin_version = '1.2.71'
+    ext.kotlin_version = '1.3.0-rc-116'
 
     repositories {
         jcenter()
+        maven {
+            url = "http://dl.bintray.com/kotlin/kotlin-eap"
+        }
     }
+
     dependencies {
         classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
         classpath "org.jfrog.buildinfo:build-info-extractor-gradle:4+"
     }
 }
-
-allprojects{
-    apply plugin: 'maven'
+allprojects {
     apply plugin: 'maven-publish'
     apply plugin: "com.jfrog.artifactory"
 
@@ -27,13 +29,11 @@ artifactory {
             repoKey = 'gradle-dev-local'
             username = "${artifactory_user}"
             password = "${artifactory_password}"
-            maven = true
-
         }
 
         defaults {
-            publications 'defaultPublication'
-            publishBuildInfo = true
+            publications('jvm', 'kotlinMultiplatform', 'metadata')
+            publishBuildInfo = false
             publishArtifacts = true
             publishPom = true
             publishIvy = false
@@ -44,7 +44,6 @@ artifactory {
             repoKey = 'gradle-dev'
             username = "${artifactory_user}"
             password = "${artifactory_password}"
-            maven = true
         }
     }
 }

kmath-common/build.gradle

@@ -1,22 +0,0 @@
-plugins{
-    id "kotlin-platform-common"
-}
-
-description = "Platform-independent interfaces for kotlin maths"
-
-repositories {
-    mavenCentral()
-}
-
-dependencies {
-    compile "org.jetbrains.kotlin:kotlin-stdlib-common:$kotlin_version"
-    testCompile "org.jetbrains.kotlin:kotlin-test-annotations-common:$kotlin_version"
-    testCompile "org.jetbrains.kotlin:kotlin-test-common:$kotlin_version"
-}
-
-kotlin {
-    experimental {
-        coroutines "enable"
-    }
-}
-

kmath-common/src/main/kotlin/scientifik/kmath/structures/NDArrayFactories.kt

@@ -1,38 +0,0 @@
-package scientifik.kmath.structures
-
-import scientifik.kmath.operations.Field
-
-/**
- * Create a platform-optimized NDArray of doubles
- */
-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<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<Double> {
-    return realNDArray(listOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
-}
-
-
-class SimpleNDField<T: Any>(field: Field<T>, shape: List<Int>) : BufferNDField<T>(shape, field) {
-    override fun createBuffer(capacity: Int, initializer: (Int) -> T): Buffer<T> {
-        val array = ArrayList<T>(capacity)
-        (0 until capacity).forEach {
-            array.add(initializer(it))
-        }
-
-        return object : Buffer<T> {
-            override fun get(index: Int): T = array[index]
-
-            override fun set(index: Int, value: T) {
-                array[index] = initializer(index)
-            }
-        }
-    }
-}
-
-fun <T: Any> simpleNDArray(field: Field<T>, shape: List<Int>, initializer: (List<Int>) -> T): NDArray<T> {
-    return SimpleNDField(field, shape).produce { initializer(it) }
-}

kmath-core/build.gradle

@@ -0,0 +1,58 @@
+plugins {
+    id 'kotlin-multiplatform'// version '1.3.0-rc-116'
+    id "me.champeau.gradle.jmh" version "0.4.5"
+}
+
+repositories {
+    maven { url = 'http://dl.bintray.com/kotlin/kotlin-eap' }
+    mavenCentral()
+}
+
+kotlin {
+    targets {
+        fromPreset(presets.jvm, 'jvm')
+        fromPreset(presets.js, 'js')
+        // For ARM, preset should be changed to presets.iosArm32 or presets.iosArm64
+        // For Linux, preset should be changed to e.g. presets.linuxX64
+        // For MacOS, preset should be changed to e.g. presets.macosX64
+        //fromPreset(presets.mingwX64, 'mingw')
+    }
+    sourceSets {
+        commonMain {
+            dependencies {
+                implementation 'org.jetbrains.kotlin:kotlin-stdlib-common'
+            }
+        }
+        commonTest {
+            dependencies {
+                implementation 'org.jetbrains.kotlin:kotlin-test-common'
+                implementation 'org.jetbrains.kotlin:kotlin-test-annotations-common'
+            }
+        }
+        jvmMain {
+            dependencies {
+                implementation 'org.jetbrains.kotlin:kotlin-stdlib-jdk8'
+            }
+        }
+        jvmTest {
+            dependencies {
+                implementation 'org.jetbrains.kotlin:kotlin-test'
+                implementation 'org.jetbrains.kotlin:kotlin-test-junit'
+            }
+        }
+        jsMain {
+            dependencies {
+                implementation 'org.jetbrains.kotlin:kotlin-stdlib-js'
+            }
+        }
+        jsTest {
+            dependencies {
+                implementation 'org.jetbrains.kotlin:kotlin-test-js'
+            }
+        }
+//        mingwMain {
+//        }
+//        mingwTest {
+//        }
+    }
+}

kmath-core/src/commonMain/kotlin/scientifik/kmath/misc/Grids.kt

@@ -1,8 +1,5 @@
 package scientifik.kmath.misc
 
-import kotlin.coroutines.experimental.buildSequence
-
-
 /**
  * Convert double range to sequence.
  *
@@ -14,14 +11,14 @@ import kotlin.coroutines.experimental.buildSequence
 fun ClosedFloatingPointRange<Double>.toSequence(step: Double): Sequence<Double> {
     return when {
         step == 0.0 -> error("Zero step in double progression")
-        step > 0 -> buildSequence {
+        step > 0 -> sequence {
             var current = start
             while (current <= endInclusive) {
                 yield(current)
                 current += step
             }
         }
-        else -> buildSequence {
+        else -> sequence {
             var current = endInclusive
             while (current >= start) {
                 yield(current)

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

@@ -1,7 +1,6 @@
 package scientifik.kmath.structures
 
 import scientifik.kmath.operations.Field
-import kotlin.coroutines.experimental.buildSequence
 
 
 /**
@@ -42,7 +41,7 @@ abstract class BufferNDField<T>(shape: List<Int>, field: Field<T>) : NDField<T>(
 
     //TODO introduce a fast way to calculate index of the next element?
     protected fun index(offset: Int): List<Int> {
-        return buildSequence {
+        return sequence {
             var current = offset
             var strideIndex = strides.size - 2
             while (strideIndex >= 0) {

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

@@ -4,6 +4,7 @@ import scientifik.kmath.operations.DoubleField
 import scientifik.kmath.operations.Field
 import scientifik.kmath.operations.Space
 import scientifik.kmath.operations.SpaceElement
+import scientifik.kmath.structures.NDArrays.createSimpleNDFieldFactory
 
 /**
  * The space for linear elements. Supports scalar product alongside with standard linear operations.
@@ -18,7 +19,7 @@ abstract class LinearSpace<T : Any, V : LinearStructure<out T>>(val rows: Int, v
     abstract fun produce(initializer: (Int, Int) -> T): V
 
     /**
-     * Produce new linear space with given dimensions
+     * Produce new linear space with given dimensions. The space produced could be raised from cache since [LinearSpace] does not have mutable elements
      */
     abstract fun produceSpace(rows: Int, columns: Int): LinearSpace<T, V>
 
@@ -36,12 +37,12 @@ abstract class LinearSpace<T : Any, V : LinearStructure<out T>>(val rows: Int, v
     }
 
     /**
-     * Dot product
+     * Dot product. Throws exception on dimension mismatch
      */
     fun multiply(a: V, b: V): V {
         if (a.rows != b.columns) {
             //TODO replace by specific exception
-            error("Dimension mismatch in vector dot product")
+            error("Dimension mismatch in linear structure dot product: [${a.rows},${a.columns}]*[${b.rows},${b.columns}]")
         }
         return produceSpace(a.rows, b.columns).produce { i, j ->
             (0..a.columns).asSequence().map { k -> field.multiply(a[i, k], b[k, j]) }.reduce { first, second -> field.add(first, second) }
@@ -55,16 +56,25 @@ abstract class LinearSpace<T : Any, V : LinearStructure<out T>>(val rows: Int, v
  * A matrix-like structure that is not dependent on specific space implementation
  */
 interface LinearStructure<T : Any> {
+    /**
+     * Number of rows
+     */
     val rows: Int
+    /**
+     * Number of columns
+     */
     val columns: Int
 
+    /**
+     * Get element in row [i] and column [j]. Throws error in case of call ounside structure dimensions
+     */
     operator fun get(i: Int, j: Int): T
 
     fun transpose(): LinearStructure<T> {
         return object : LinearStructure<T> {
             override val rows: Int = this@LinearStructure.columns
             override val columns: Int = this@LinearStructure.rows
-            override fun get(i: Int, j: Int): T = this@LinearStructure.get(j, i)
+            override fun get(i: Int, j: Int): T = this@LinearStructure[j, i]
         }
     }
 }
@@ -78,15 +88,23 @@ interface Vector<T : Any> : LinearStructure<T> {
 
 
 /**
- * DoubleArray-based implementation of vector space
+ * NDArray-based implementation of vector space. By default uses slow [SimpleNDField], but could be overridden with custom [NDField] factory.
  */
-class ArraySpace<T : Any>(rows: Int, columns: Int, field: Field<T>) : LinearSpace<T, LinearStructure<out T>>(rows, columns, field) {
+class ArraySpace<T : Any>(
+        rows: Int,
+        columns: Int,
+        field: Field<T>,
+        val ndFactory: NDFieldFactory<T> = createSimpleNDFieldFactory(field)
+) : LinearSpace<T, LinearStructure<out T>>(rows, columns, field) {
+
+    val ndField by lazy {
+        ndFactory(listOf(rows, columns))
+    }
 
     override fun produce(initializer: (Int, Int) -> T): LinearStructure<T> = ArrayMatrix<T>(this, initializer)
 
-
     override fun produceSpace(rows: Int, columns: Int): LinearSpace<T, LinearStructure<out T>> {
-        return ArraySpace(rows, columns, field)
+        return ArraySpace(rows, columns, field, ndFactory)
     }
 }
 
@@ -95,14 +113,16 @@ class ArraySpace<T : Any>(rows: Int, columns: Int, field: Field<T>) : LinearSpac
  */
 class ArrayMatrix<T : Any>(override val context: ArraySpace<T>, initializer: (Int, Int) -> T) : LinearStructure<T>, SpaceElement<LinearStructure<out T>, ArraySpace<T>> {
 
-    val list: List<List<T>> = (0 until rows).map { i -> (0 until columns).map { j -> initializer(i, j) } }
+    private val array = context.ndField.produce { list -> initializer(list[0], list[1]) }
+
+    //val list: List<List<T>> = (0 until rows).map { i -> (0 until columns).map { j -> initializer(i, j) } }
 
     override val rows: Int get() = context.rows
 
     override val columns: Int get() = context.columns
 
     override fun get(i: Int, j: Int): T {
-        return list[i][j]
+        return array[i, j]
     }
 
     override val self: ArrayMatrix<T> get() = this
@@ -117,7 +137,7 @@ class ArrayVector<T : Any>(override val context: ArraySpace<T>, initializer: (In
         }
     }
 
-    val list: List<T> = (0 until context.rows).map(initializer)
+    private val array = context.ndField.produce { list -> initializer(list[0]) }
 
 
     override val rows: Int get() = context.rows
@@ -125,20 +145,25 @@ class ArrayVector<T : Any>(override val context: ArraySpace<T>, initializer: (In
     override val columns: Int = 1
 
     override fun get(i: Int, j: Int): T {
-        return list[i]
+        return array[i]
     }
 
     override val self: ArrayVector<T> get() = this
 
 }
 
-fun <T : Any> vector(size: Int, field: Field<T>, initializer: (Int) -> T) = ArrayVector(ArraySpace(size, 1, field), initializer)
-//TODO replace by primitive array version
-fun realVector(size: Int, initializer: (Int) -> Double) = vector(size, DoubleField, initializer)
+fun <T : Any> vector(size: Int, field: Field<T>, initializer: (Int) -> T) =
+        ArrayVector(ArraySpace(size, 1, field), initializer)
+
+fun realVector(size: Int, initializer: (Int) -> Double) =
+        ArrayVector(ArraySpace(size, 1, DoubleField, realNDFieldFactory), initializer)
 
 fun <T : Any> Array<T>.asVector(field: Field<T>) = vector(size, field) { this[it] }
-//TODO add inferred field from field element
+
 fun DoubleArray.asVector() = realVector(this.size) { this[it] }
 
-fun <T : Any> matrix(rows: Int, columns: Int, field: Field<T>, initializer: (Int, Int) -> T) = ArrayMatrix<T>(ArraySpace(rows, columns, field), initializer)
-fun realMatrix(rows: Int, columns: Int, initializer: (Int, Int) -> Double) = matrix(rows, columns, DoubleField, initializer)
+fun <T : Any> matrix(rows: Int, columns: Int, field: Field<T>, initializer: (Int, Int) -> T) =
+        ArrayMatrix(ArraySpace(rows, columns, field), initializer)
+
+fun realMatrix(rows: Int, columns: Int, initializer: (Int, Int) -> Double) =
+        ArrayMatrix(ArraySpace(rows, columns, DoubleField, realNDFieldFactory), initializer)

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

@@ -136,7 +136,7 @@ operator fun <T> Function1<T, T>.invoke(ndArray: NDArray<T>): NDArray<T> = ndArr
  * Summation operation for [NDArray] and single element
  */
 operator fun <T> NDArray<T>.plus(arg: T): NDArray<T> = transform { _, value ->
-    with(context.field){
+    with(context.field) {
         arg + value
     }
 }
@@ -149,8 +149,8 @@ operator fun <T> T.plus(arg: NDArray<T>): NDArray<T> = arg + this
 /**
  * Subtraction operation between [NDArray] and single element
  */
-operator fun <T> NDArray<T>.minus(arg: T): NDArray<T> = transform  { _, value ->
-    with(context.field){
+operator fun <T> NDArray<T>.minus(arg: T): NDArray<T> = transform { _, value ->
+    with(context.field) {
         arg - value
     }
 }
@@ -159,7 +159,7 @@ operator fun <T> NDArray<T>.minus(arg: T): NDArray<T> = transform  { _, value ->
  * Reverse minus operation
  */
 operator fun <T> T.minus(arg: NDArray<T>): NDArray<T> = arg.transform { _, value ->
-    with(arg.context.field){
+    with(arg.context.field) {
         this@minus - value
     }
 }
@@ -170,7 +170,7 @@ operator fun <T> T.minus(arg: NDArray<T>): NDArray<T> = arg.transform { _, value
  * Product operation for [NDArray] and single element
  */
 operator fun <T> NDArray<T>.times(arg: T): NDArray<T> = transform { _, value ->
-    with(context.field){
+    with(context.field) {
         arg * value
     }
 }
@@ -183,8 +183,8 @@ operator fun <T> T.times(arg: NDArray<T>): NDArray<T> = arg * this
 /**
  * Division operation between [NDArray] and single element
  */
-operator fun <T> NDArray<T>.div(arg: T): NDArray<T> = transform  { _, value ->
-    with(context.field){
+operator fun <T> NDArray<T>.div(arg: T): NDArray<T> = transform { _, value ->
+    with(context.field) {
         arg / value
     }
 }
@@ -193,8 +193,8 @@ operator fun <T> NDArray<T>.div(arg: T): NDArray<T> = transform  { _, value ->
  * Reverse division operation
  */
 operator fun <T> T.div(arg: NDArray<T>): NDArray<T> = arg.transform { _, value ->
-    with(arg.context.field){
-        this@div/ value
+    with(arg.context.field) {
+        this@div / value
     }
 }
 

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

@@ -0,0 +1,54 @@
+package scientifik.kmath.structures
+
+import scientifik.kmath.operations.Field
+
+typealias NDFieldFactory<T> = (shape: List<Int>) -> NDField<T>
+
+/**
+ * The factory class for fast platform-dependent implementation of NDField of doubles
+ */
+expect val realNDFieldFactory: NDFieldFactory<Double>
+
+object NDArrays {
+    /**
+     * Create a platform-optimized NDArray of doubles
+     */
+    fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double = { 0.0 }): NDArray<Double> {
+        return realNDFieldFactory(shape).produce(initializer)
+    }
+
+    fun real1DArray(dim: Int, initializer: (Int) -> Double = { _ -> 0.0 }): NDArray<Double> {
+        return realNDArray(listOf(dim)) { initializer(it[0]) }
+    }
+
+    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<Double> {
+        return realNDArray(listOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
+    }
+
+    class SimpleNDField<T : Any>(field: Field<T>, shape: List<Int>) : BufferNDField<T>(shape, field) {
+        override fun createBuffer(capacity: Int, initializer: (Int) -> T): Buffer<T> {
+            val array = ArrayList<T>(capacity)
+            (0 until capacity).forEach {
+                array.add(initializer(it))
+            }
+
+            return object : Buffer<T> {
+                override fun get(index: Int): T = array[index]
+
+                override fun set(index: Int, value: T) {
+                    array[index] = initializer(index)
+                }
+            }
+        }
+    }
+
+    fun <T : Any> createSimpleNDFieldFactory(field: Field<T>): NDFieldFactory<T> = { list -> SimpleNDField(field, list) }
+
+    fun <T : Any> simpleNDArray(field: Field<T>, shape: List<Int>, initializer: (List<Int>) -> T): NDArray<T> {
+        return SimpleNDField(field, shape).produce { initializer(it) }
+    }
+}

kmath-core/src/commonTest/kotlin/scientifik/kmath/structures/ArrayMatrixTest.kt

@@ -1,7 +1,7 @@
 package scientifik.kmath.structures
 
-import org.junit.Assert.assertEquals
-import org.junit.Test
+import kotlin.test.Test
+import kotlin.test.assertEquals
 
 class ArrayMatrixTest {
 
@@ -10,7 +10,7 @@ class ArrayMatrixTest {
         val vector1 = realVector(5) { it.toDouble() }
         val vector2 = realVector(5) { 5 - it.toDouble() }
         val sum = vector1 + vector2
-        assertEquals(5.0, sum[2, 0], 0.1)
+        assertEquals(5.0, sum[2, 0])
     }
 
     @Test
@@ -21,6 +21,6 @@ class ArrayMatrixTest {
             vector1 dot (vector2.transpose())
         }
 
-        assertEquals(10.0, product[1, 0], 0.1)
+        assertEquals(10.0, product[1, 0])
     }
 }

kmath-core/src/commonTest/kotlin/scientifik/kmath/structures/RealNDFieldTest.kt

@@ -1,8 +1,9 @@
 package scientifik.kmath.structures
 
-import org.junit.Assert.assertEquals
+import scientifik.kmath.structures.NDArrays.real2DArray
 import kotlin.math.pow
 import kotlin.test.Test
+import kotlin.test.assertEquals
 
 class RealNDFieldTest {
     val array1 = real2DArray(3, 3) { i, j -> (i + j).toDouble() }
@@ -11,13 +12,13 @@ class RealNDFieldTest {
     @Test
     fun testSum() {
         val sum = array1 + array2
-        assertEquals(4.0, sum[2, 2], 0.1)
+        assertEquals(4.0, sum[2, 2])
     }
 
     @Test
     fun testProduct() {
         val product = array1 * array2
-        assertEquals(0.0, product[2, 2], 0.1)
+        assertEquals(0.0, product[2, 2])
     }
 
     @Test
@@ -28,7 +29,7 @@ class RealNDFieldTest {
         for (i in 0..2) {
             for (j in 0..2) {
                 val expected = (i * 10 + j).toDouble()
-                assertEquals("Error at index [$i, $j]", expected, array[i, j], 0.1)
+                assertEquals(expected, array[i, j],"Error at index [$i, $j]")
             }
         }
     }
@@ -37,6 +38,6 @@ class RealNDFieldTest {
     fun testExternalFunction() {
         val function: (Double) -> Double = { x -> x.pow(2) + 2 * x + 1 }
         val result = function(array1) + 1.0
-        assertEquals(10.0, result[1,1],0.01)
+        assertEquals(10.0, result[1,1])
     }
 }

kmath-core/src/commonTest/kotlin/scientifik/kmath/structures/SimpleNDFieldTest.kt

@@ -1,6 +1,7 @@
 package scientifik.kmath.structures
 
 import scientifik.kmath.operations.DoubleField
+import scientifik.kmath.structures.NDArrays.simpleNDArray
 import kotlin.test.Test
 import kotlin.test.assertEquals
 

kmath-core/src/jsMain/kotlin/scientifik/kmath/structures/_NDArrays.kt

@@ -0,0 +1,8 @@
+package scientifik.kmath.structures
+
+import scientifik.kmath.operations.DoubleField
+
+/**
+ * Using boxing implementation for js
+ */
+actual val realNDFieldFactory: NDFieldFactory<Double> = NDArrays.createSimpleNDFieldFactory(DoubleField)

kmath-core/src/jvmMain/kotlin/scientifik/kmath/structures/_NDArrays.kt

@@ -17,8 +17,4 @@ private class RealNDField(shape: List<Int>) : BufferNDField<Double>(shape, Doubl
     }
 }
 
-actual fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double): NDArray<Double> {
-    //TODO create a cache for fields to save time generating strides?
-
-    return RealNDField(shape).produce { initializer(it) }
-}
+actual val realNDFieldFactory: NDFieldFactory<Double> = { shape -> RealNDField(shape) }

kmath-jvm/build.gradle

@@ -1,38 +0,0 @@
-plugins{
-    id "kotlin-platform-jvm"
-    id "me.champeau.gradle.jmh" version "0.4.5"
-}
-
-repositories {
-    mavenCentral()
-}
-
-dependencies {
-    expectedBy project(":kmath-common")
-    compile "org.jetbrains.kotlin:kotlin-stdlib-jdk8:$kotlin_version"
-    testCompile "junit:junit:4.12"
-    testCompile "org.jetbrains.kotlin:kotlin-test-junit:$kotlin_version"
-    testCompile "org.jetbrains.kotlin:kotlin-test:$kotlin_version"
-}
-
-compileKotlin {
-    kotlinOptions.jvmTarget = "1.8"
-}
-compileTestKotlin {
-    kotlinOptions.jvmTarget = "1.8"
-}
-sourceCompatibility = "1.8"
-
-kotlin {
-    experimental {
-        coroutines "enable"
-    }
-}
-
-publishing {
-    publications {
-        defaultPublication(MavenPublication) {
-            from components.java
-        }
-    }
-}

settings.gradle

@@ -1,4 +1,13 @@
-rootProject.name = 'kmath'
-include 'kmath-common'
-include 'kmath-jvm'
+pluginManagement {
+    repositories {
+        maven { url = 'http://dl.bintray.com/kotlin/kotlin-eap' }
+        mavenCentral()
+        maven { url = 'https://plugins.gradle.org/m2/' }
+    }
+}
+
+enableFeaturePreview('GRADLE_METADATA')
+
+rootProject.name = 'kmath'
+include ':kmath-core'