Merge remote-tracking branch 'upstream/dev' into zelenyy

build.gradle.kts

@@ -1,14 +1,10 @@
 buildscript {
-    extra["kotlinVersion"] = "1.3.20-eap-100"
+    val kotlinVersion: String by rootProject.extra("1.3.20")
-    extra["ioVersion"] = "0.1.2"
+    val ioVersion: String by rootProject.extra("0.1.2")
-    extra["coroutinesVersion"] = "1.1.0"
+    val coroutinesVersion: String by rootProject.extra("1.1.1")
-
-    val kotlinVersion: String by extra
-    val ioVersion: String by extra
-    val coroutinesVersion: String by extra
 
     repositories {
-        maven("https://dl.bintray.com/kotlin/kotlin-eap")
+        //maven("https://dl.bintray.com/kotlin/kotlin-eap")
         jcenter()
     }
 
@@ -28,7 +24,7 @@ allprojects {
     apply(plugin = "com.jfrog.artifactory")
 
     group = "scientifik"
-    version = "0.0.3-dev-3"
+    version = "0.0.3-dev-4"
 
     repositories {
         maven("https://dl.bintray.com/kotlin/kotlin-eap")

kmath-commons/src/main/kotlin/scientifik/kmath/linear/CMMatrix.kt

@@ -4,11 +4,16 @@ import org.apache.commons.math3.linear.*
 import org.apache.commons.math3.linear.RealMatrix
 import org.apache.commons.math3.linear.RealVector
 
-inline class CMMatrix(val origin: RealMatrix) : Matrix<Double> {
+class CMMatrix(val origin: RealMatrix, features: Set<MatrixFeature>? = null) : Matrix<Double> {
     override val rowNum: Int get() = origin.rowDimension
     override val colNum: Int get() = origin.columnDimension
 
-    override val features: Set<MatrixFeature> get() = emptySet()
+    override val features: Set<MatrixFeature> = features ?: sequence<MatrixFeature> {
+        if(origin is DiagonalMatrix) yield(DiagonalFeature)
+    }.toSet()
+
+    override fun suggestFeature(vararg features: MatrixFeature) =
+        CMMatrix(origin, this.features + features)
 
     override fun get(i: Int, j: Int): Double = origin.getEntry(i, j)
 }
@@ -23,7 +28,7 @@ fun Matrix<Double>.toCM(): CMMatrix = if (this is CMMatrix) {
 
 fun RealMatrix.toMatrix() = CMMatrix(this)
 
-inline class CMVector(val origin: RealVector) : Point<Double> {
+class CMVector(val origin: RealVector) : Point<Double> {
     override val size: Int get() = origin.dimension
 
     override fun get(index: Int): Double = origin.getEntry(index)

kmath-core/build.gradle

@@ -1,50 +0,0 @@
-plugins {
-    id "org.jetbrains.kotlin.multiplatform"
-}
-
-kotlin {
-    jvm {
-        compilations["main"].kotlinOptions.jvmTarget = "1.8"
-        compilations["test"].kotlinOptions.jvmTarget = "1.8"
-    }
-    js()
-
-    sourceSets {
-        commonMain {
-            dependencies {
-                api '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 {
-                api 'org.jetbrains.kotlin:kotlin-stdlib-jdk8'
-            }
-        }
-        jvmTest {
-            dependencies {
-                implementation 'org.jetbrains.kotlin:kotlin-test'
-                implementation 'org.jetbrains.kotlin:kotlin-test-junit'
-            }
-        }
-        jsMain {
-            dependencies {
-                api 'org.jetbrains.kotlin:kotlin-stdlib-js'
-            }
-        }
-        jsTest {
-            dependencies {
-                implementation 'org.jetbrains.kotlin:kotlin-test-js'
-            }
-        }
-//        mingwMain {
-//        }
-//        mingwTest {
-//        }
-    }
-}

kmath-core/build.gradle.kts

@@ -0,0 +1,55 @@
+plugins {
+    kotlin("multiplatform")
+}
+
+
+kotlin {
+    jvm {
+        compilations.all {
+            kotlinOptions {
+                jvmTarget = "1.8"
+                freeCompilerArgs += "-progressive"
+            }
+        }
+    }
+    js()
+
+    sourceSets {
+        val commonMain by getting {
+            dependencies {
+                api(kotlin("stdlib"))
+            }
+        }
+        val commonTest by getting {
+            dependencies {
+                implementation(kotlin("test-common"))
+                implementation(kotlin("test-annotations-common"))
+            }
+        }
+        val jvmMain by getting {
+            dependencies {
+                api(kotlin("stdlib-jdk8"))
+            }
+        }
+        val jvmTest by getting {
+            dependencies {
+                implementation(kotlin("test"))
+                implementation(kotlin("test-junit"))
+            }
+        }
+        val jsMain by getting {
+            dependencies {
+                api(kotlin("stdlib-js"))
+            }
+        }
+        val jsTest by getting {
+            dependencies {
+                implementation(kotlin("test-js"))
+            }
+        }
+//        mingwMain {
+//        }
+//        mingwTest {
+//        }
+    }
+}

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

@@ -35,6 +35,9 @@ class BufferMatrix<T : Any>(
 
     override val shape: IntArray get() = intArrayOf(rowNum, colNum)
 
+    override fun suggestFeature(vararg features: MatrixFeature) =
+        BufferMatrix(rowNum, colNum, buffer, this.features + features)
+
     override fun get(index: IntArray): T = get(index[0], index[1])
 
     override fun get(i: Int, j: Int): T = buffer[i * colNum + j]

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

@@ -8,20 +8,19 @@ import scientifik.kmath.structures.MutableBufferFactory
 import scientifik.kmath.structures.NDStructure
 import scientifik.kmath.structures.get
 
-
 class LUPDecomposition<T : Comparable<T>>(
     private val elementContext: Ring<T>,
     internal val lu: NDStructure<T>,
     val pivot: IntArray,
     private val even: Boolean
-) : DeterminantFeature<T> {
+) : LUPDecompositionFeature<T>, DeterminantFeature<T> {
 
     /**
      * Returns the matrix L of the decomposition.
      *
      * L is a lower-triangular matrix with [Ring.one] in diagonal
      */
-    val l: Matrix<T> = VirtualMatrix(lu.shape[0], lu.shape[1]) { i, j ->
+    override val l: Matrix<T> = VirtualMatrix(lu.shape[0], lu.shape[1], setOf(LFeature)) { i, j ->
         when {
             j < i -> lu[i, j]
             j == i -> elementContext.one
@@ -35,7 +34,7 @@ class LUPDecomposition<T : Comparable<T>>(
      *
      * U is an upper-triangular matrix including the diagonal
      */
-    val u: Matrix<T> = VirtualMatrix(lu.shape[0], lu.shape[1]) { i, j ->
+    override val u: Matrix<T> = VirtualMatrix(lu.shape[0], lu.shape[1], setOf(UFeature)) { i, j ->
         if (j >= i) lu[i, j] else elementContext.zero
     }
 
@@ -46,7 +45,7 @@ class LUPDecomposition<T : Comparable<T>>(
      * P is a sparse matrix with exactly one element set to [Ring.one] in
      * each row and each column, all other elements being set to [Ring.zero].
      */
-    val p: Matrix<T> = VirtualMatrix(lu.shape[0], lu.shape[1]) { i, j ->
+    override val p: Matrix<T> = VirtualMatrix(lu.shape[0], lu.shape[1]) { i, j ->
         if (j == pivot[i]) elementContext.one else elementContext.zero
     }
 

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

@@ -107,26 +107,6 @@ interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
         produce(rowNum, colNum) { i, j -> elementContext.run { get(i, j) * value } }
 }
 
-/**
- * A marker interface representing some matrix feature like diagonal, sparce, zero, etc. Features used to optimize matrix
- * operations performance in some cases.
- */
-interface MatrixFeature
-
-object DiagonalFeature : MatrixFeature
-
-object ZeroFeature : MatrixFeature
-
-object UnitFeature : MatrixFeature
-
-interface InverseMatrixFeature<T : Any> : MatrixFeature {
-    val inverse: Matrix<T>
-}
-
-interface DeterminantFeature<T : Any> : MatrixFeature {
-    val determinant: T
-}
-
 /**
  * Specialized 2-d structure
  */
@@ -136,6 +116,14 @@ interface Matrix<T : Any> : NDStructure<T> {
 
     val features: Set<MatrixFeature>
 
+    /**
+     * Suggest new feature for this matrix. The result is the new matrix that may or may not reuse existing data structure.
+     *
+     * The implementation does not guarantee to check that matrix actually have the feature, so one should be careful to
+     * add only those features that are valid.
+     */
+    fun suggestFeature(vararg features: MatrixFeature): Matrix<T>
+
     operator fun get(i: Int, j: Int): T
 
     override fun get(index: IntArray): T = get(index[0], index[1])
@@ -167,12 +155,22 @@ interface Matrix<T : Any> : NDStructure<T> {
         /**
          * Build a square matrix from given elements.
          */
-        fun <T : Any> build(vararg elements: T): Matrix<T> {
+        fun <T : Any> square(vararg elements: T): Matrix<T> {
             val size: Int = sqrt(elements.size.toDouble()).toInt()
             if (size * size != elements.size) error("The number of elements ${elements.size} is not a full square")
             val buffer = elements.asBuffer()
             return BufferMatrix(size, size, buffer)
         }
+
+        fun <T : Any> build(rows: Int, columns: Int): MatrixBuilder<T> = MatrixBuilder(rows, columns)
+    }
+}
+
+class MatrixBuilder<T : Any>(val rows: Int, val columns: Int) {
+    operator fun invoke(vararg elements: T): Matrix<T> {
+        if (rows * columns != elements.size) error("The number of elements ${elements.size} is not equal $rows * $columns")
+        val buffer = elements.asBuffer()
+        return BufferMatrix(rows, columns, buffer)
     }
 }
 

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

@@ -0,0 +1,62 @@
+package scientifik.kmath.linear
+
+/**
+ * A marker interface representing some matrix feature like diagonal, sparce, zero, etc. Features used to optimize matrix
+ * operations performance in some cases.
+ */
+interface MatrixFeature
+
+/**
+ * The matrix with this feature is considered to have only diagonal non-null elements
+ */
+object DiagonalFeature : MatrixFeature
+
+/**
+ * Matrix with this feature has all zero elements
+ */
+object ZeroFeature : MatrixFeature
+
+/**
+ * Matrix with this feature have unit elements on diagonal and zero elements in all other places
+ */
+object UnitFeature : MatrixFeature
+
+/**
+ * Inverted matrix feature
+ */
+interface InverseMatrixFeature<T : Any> : MatrixFeature {
+    val inverse: Matrix<T>
+}
+
+/**
+ * A determinant container
+ */
+interface DeterminantFeature<T : Any> : MatrixFeature {
+    val determinant: T
+}
+
+@Suppress("FunctionName")
+fun <T: Any> DeterminantFeature(determinant: T) = object: DeterminantFeature<T>{
+    override val determinant: T = determinant
+}
+
+/**
+ * Lower triangular matrix
+ */
+object LFeature: MatrixFeature
+
+/**
+ * Upper triangular feature
+ */
+object UFeature: MatrixFeature
+
+/**
+ * TODO add documentation
+ */
+interface LUPDecompositionFeature<T : Any> : MatrixFeature {
+    val l: Matrix<T>
+    val u: Matrix<T>
+    val p: Matrix<T>
+}
+
+//TODO add sparse matrix feature

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

@@ -8,6 +8,9 @@ class VirtualMatrix<T : Any>(
 ) : Matrix<T> {
     override fun get(i: Int, j: Int): T = generator(i, j)
 
+    override fun suggestFeature(vararg features: MatrixFeature) =
+        VirtualMatrix(rowNum, colNum, this.features + features, generator)
+
     override fun equals(other: Any?): Boolean {
         if (this === other) return true
         if (other !is Matrix<*>) return false

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

@@ -15,6 +15,7 @@ class ShortNDRing(override val shape: IntArray) :
     override val zero by lazy { produce { ShortRing.zero } }
     override val one by lazy { produce { ShortRing.one } }
 
+    @Suppress("OVERRIDE_BY_INLINE")
     override inline fun buildBuffer(size: Int, crossinline initializer: (Int) -> Short): Buffer<Short> =
         ShortBuffer(ShortArray(size) { initializer(it) })
 

kmath-core/src/commonTest/kotlin/scientifik/kmath/linear/MatrixTest.kt

@@ -41,4 +41,14 @@ class MatrixTest {
         assertEquals(5.0, product[1, 0])
         assertEquals(6.0, product[2, 2])
     }
+
+    @Test
+    fun testBuilder() {
+        val matrix = Matrix.build<Double>(2, 3)(
+            1.0, 0.0, 0.0,
+            0.0, 1.0, 2.0
+        )
+
+        assertEquals(2.0, matrix[1, 2])
+    }
 }

kmath-core/src/commonTest/kotlin/scientifik/kmath/linear/RealLUSolverTest.kt

@@ -13,7 +13,7 @@ class RealLUSolverTest {
 
     @Test
     fun testInvert() {
-        val matrix = Matrix.build(
+        val matrix = Matrix.square(
             3.0, 1.0,
             1.0, 3.0
         )
@@ -31,7 +31,7 @@ class RealLUSolverTest {
 
         val inverted = LUSolver.real.inverse(decomposed)
 
-        val expected = Matrix.build(
+        val expected = Matrix.square(
             0.375, -0.125,
             -0.125, 0.375
         )

kmath-koma/build.gradle.kts

@@ -1,5 +1,5 @@
 plugins {
-    id("kotlin-multiplatform")
+    kotlin("multiplatform")
 }
 
 repositories {
@@ -8,8 +8,12 @@ repositories {
 
 kotlin {
     jvm {
-        compilations["main"].kotlinOptions.jvmTarget = "1.8"
+        compilations.all {
-        compilations["test"].kotlinOptions.jvmTarget = "1.8"
+            kotlinOptions {
+                jvmTarget = "1.8"
+                freeCompilerArgs += "-progressive"
+            }
+        }
     }
     js()
 

kmath-koma/src/commonMain/kotlin/scientifik.kmath.linear/KomaMatrix.kt

@@ -48,10 +48,25 @@ class KomaMatrixContext<T : Any>(val factory: MatrixFactory<koma.matrix.Matrix<T
         KomaMatrix(a.toKoma().origin.inv())
 }
 
-inline class KomaMatrix<T : Any>(val origin: koma.matrix.Matrix<T>) : Matrix<T> {
+class KomaMatrix<T : Any>(val origin: koma.matrix.Matrix<T>, features: Set<MatrixFeature>? = null) :
+    Matrix<T> {
     override val rowNum: Int get() = origin.numRows()
     override val colNum: Int get() = origin.numCols()
-    override val features: Set<MatrixFeature> get() = emptySet()
+
+    override val features: Set<MatrixFeature> = features ?: setOf(
+        object : DeterminantFeature<T> {
+            override val determinant: T get() = origin.det()
+        },
+        object : LUPDecompositionFeature<T> {
+            private val lup by lazy { origin.LU() }
+            override val l: Matrix<T> get() = KomaMatrix(lup.second)
+            override val u: Matrix<T> get() = KomaMatrix(lup.third)
+            override val p: Matrix<T> get() = KomaMatrix(lup.first)
+        }
+    )
+
+    override fun suggestFeature(vararg features: MatrixFeature): Matrix<T> =
+        KomaMatrix(this.origin, this.features + features)
 
     override fun get(i: Int, j: Int): T = origin.getGeneric(i, j)
 }

settings.gradle.kts

@@ -2,7 +2,7 @@ pluginManagement {
     repositories {
         mavenCentral()
         maven("https://plugins.gradle.org/m2/")
-        maven ("https://dl.bintray.com/kotlin/kotlin-eap")
+        //maven ("https://dl.bintray.com/kotlin/kotlin-eap")
     }
 }