benchmarks/build.gradle

@@ -5,9 +5,10 @@ plugins {
 }
 
 dependencies {
-    api project(":kmath-core")
+    implementation project(":kmath-core")
-    api project(":kmath-coroutines")
+    implementation project(":kmath-coroutines")
-    api project(":kmath-commons")
+    implementation project(":kmath-commons")
+    implementation project(":kmath-koma")
     implementation "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
     //jmh project(':kmath-core')
 }

benchmarks/src/main/kotlin/scientifik/kmath/linear/LinearAlgebraBenchmark.kt

@@ -29,7 +29,7 @@ fun main() {
 
     //commons-math
 
-    val cmSolver = CMSolver
+    val cmSolver = CMMatrixContext
 
     val commonsTime = measureTimeMillis {
         val cm = matrix.toCM()             //avoid overhead on conversion

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

@@ -3,8 +3,6 @@ package scientifik.kmath.linear
 import org.apache.commons.math3.linear.*
 import org.apache.commons.math3.linear.RealMatrix
 import org.apache.commons.math3.linear.RealVector
-import scientifik.kmath.operations.RealField
-import scientifik.kmath.structures.DoubleBuffer
 
 inline class CMMatrix(val origin: RealMatrix) : Matrix<Double> {
     override val rowNum: Int get() = origin.rowDimension
@@ -40,44 +38,51 @@ fun Point<Double>.toCM(): CMVector = if (this is CMVector) {
     CMVector(ArrayRealVector(array))
 }
 
-fun RealVector.toPoint() = DoubleBuffer(this.toArray())
+fun RealVector.toPoint() = CMVector(this)
 
-object CMMatrixContext : MatrixContext<Double, RealField> {
+object CMMatrixContext : MatrixContext<Double>, LinearSolver<Double> {
-    override val elementContext: RealField get() = RealField
 
-    override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): Matrix<Double> {
+    override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> Double): CMMatrix {
         val array = Array(rows) { i -> DoubleArray(columns) { j -> initializer(i, j) } }
         return CMMatrix(Array2DRowRealMatrix(array))
     }
 
-    override fun point(size: Int, initializer: (Int) -> Double): Point<Double> {
+    override fun solve(a: Matrix<Double>, b: Matrix<Double>): CMMatrix {
-        val array = DoubleArray(size, initializer)
+        val decomposition = LUDecomposition(a.toCM().origin)
-        return CMVector(ArrayRealVector(array))
+        return decomposition.solver.solve(b.toCM().origin).toMatrix()
     }
 
-    override fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double> = CMMatrix(this.toCM().origin.multiply(other.toCM().origin))
+    override fun solve(a: Matrix<Double>, b: Point<Double>): CMVector {
+        val decomposition = LUDecomposition(a.toCM().origin)
+        return decomposition.solver.solve(b.toCM().origin).toPoint()
+    }
+
+    override fun inverse(a: Matrix<Double>): CMMatrix {
+        val decomposition = LUDecomposition(a.toCM().origin)
+        return decomposition.solver.inverse.toMatrix()
+    }
+
+    override fun Matrix<Double>.dot(other: Matrix<Double>) =
+        CMMatrix(this.toCM().origin.multiply(other.toCM().origin))
+
+    override fun Matrix<Double>.dot(vector: Point<Double>): CMVector =
+        CMVector(this.toCM().origin.preMultiply(vector.toCM().origin))
+
+
+    override fun Matrix<Double>.unaryMinus(): CMMatrix =
+        produce(rowNum, colNum) { i, j -> -get(i, j) }
+
+    override fun Matrix<Double>.plus(b: Matrix<Double>) =
+        CMMatrix(this.toCM().origin.multiply(b.toCM().origin))
+
+    override fun Matrix<Double>.minus(b: Matrix<Double>) =
+        CMMatrix(this.toCM().origin.subtract(b.toCM().origin))
+
+    override fun Matrix<Double>.times(value: Double) =
+        CMMatrix(this.toCM().origin.scalarMultiply(value.toDouble()))
 }
 
 operator fun CMMatrix.plus(other: CMMatrix): CMMatrix = CMMatrix(this.origin.add(other.origin))
 operator fun CMMatrix.minus(other: CMMatrix): CMMatrix = CMMatrix(this.origin.subtract(other.origin))
 
 infix fun CMMatrix.dot(other: CMMatrix): CMMatrix = CMMatrix(this.origin.multiply(other.origin))
-
-object CMSolver : LinearSolver<Double, RealField> {
-
-    override fun solve(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> {
-        val decomposition = LUDecomposition(a.toCM().origin)
-        return decomposition.solver.solve(b.toCM().origin).toMatrix()
-    }
-
-    override fun solve(a: Matrix<Double>, b: Point<Double>): Point<Double> {
-        val decomposition = LUDecomposition(a.toCM().origin)
-        return decomposition.solver.solve(b.toCM().origin).toPoint()
-    }
-
-    override fun inverse(a: Matrix<Double>): Matrix<Double> {
-        val decomposition = LUDecomposition(a.toCM().origin)
-        return decomposition.solver.inverse.toMatrix()
-    }
-
-}

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

@@ -9,7 +9,7 @@ import scientifik.kmath.structures.*
 class BufferMatrixContext<T : Any, R : Ring<T>>(
     override val elementContext: R,
     private val bufferFactory: BufferFactory<T>
-) : MatrixContext<T, R> {
+) : GenericMatrixContext<T, R> {
 
     override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): BufferMatrix<T> {
         val buffer = bufferFactory(rows * columns) { offset -> initializer(offset / columns, offset % columns) }

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

@@ -65,7 +65,7 @@ class LUPDecomposition<T : Comparable<T>>(
 
 
 class LUSolver<T : Comparable<T>, F : Field<T>>(
-    val context: MatrixContext<T, F>,
+    val context: GenericMatrixContext<T, F>,
     val bufferFactory: MutableBufferFactory<T> = ::boxing,
     val singularityCheck: (T) -> Boolean
 ) : LinearSolver<T, F> {
@@ -201,6 +201,6 @@ class LUSolver<T : Comparable<T>, F : Field<T>>(
     override fun inverse(a: Matrix<T>): Matrix<T> = solve(a, context.one(a.rowNum, a.colNum))
 
     companion object {
-        val real = LUSolver(MatrixContext.real, MutableBuffer.Companion::auto) { it < 1e-11 }
+        val real = LUSolver(GenericMatrixContext.real, MutableBuffer.Companion::auto) { it < 1e-11 }
     }
 }

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

@@ -3,7 +3,6 @@ package scientifik.kmath.linear
 import scientifik.kmath.operations.Field
 import scientifik.kmath.operations.Norm
 import scientifik.kmath.operations.RealField
-import scientifik.kmath.operations.Ring
 import scientifik.kmath.structures.VirtualBuffer
 import scientifik.kmath.structures.asSequence
 
@@ -11,7 +10,7 @@ import scientifik.kmath.structures.asSequence
 /**
  * A group of methods to resolve equation A dot X = B, where A and B are matrices or vectors
  */
-interface LinearSolver<T : Any, R : Ring<T>>  {
+interface LinearSolver<T : Any>  {
     fun solve(a: Matrix<T>, b: Matrix<T>): Matrix<T>
     fun solve(a: Matrix<T>, b: Point<T>): Point<T> = solve(a, b.toMatrix()).toVector()
     fun inverse(a: Matrix<T>): Matrix<T>

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

@@ -8,28 +8,61 @@ import scientifik.kmath.structures.Buffer.Companion.boxing
 import kotlin.math.sqrt
 
 
-interface MatrixContext<T : Any, R : Ring<T>> {
+interface MatrixContext<T : Any> {
+    /**
+     * Produce a matrix with this context and given dimensions
+     */
+    fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): Matrix<T>
+
+    infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T>
+
+    infix fun Matrix<T>.dot(vector: Point<T>): Point<T>
+
+    operator fun Matrix<T>.unaryMinus(): Matrix<T>
+
+    operator fun Matrix<T>.plus(b: Matrix<T>): Matrix<T>
+
+    operator fun Matrix<T>.minus(b: Matrix<T>): Matrix<T>
+
+    operator fun Matrix<T>.times(value: T): Matrix<T>
+
+    operator fun T.times(m: Matrix<T>): Matrix<T> = m * this
+
+    companion object {
+        /**
+         * Non-boxing double matrix
+         */
+        val real = BufferMatrixContext(RealField, DoubleBufferFactory)
+
+        /**
+         * A structured matrix with custom buffer
+         */
+        fun <T : Any, R : Ring<T>> buffered(
+            ring: R,
+            bufferFactory: BufferFactory<T> = ::boxing
+        ): GenericMatrixContext<T, R> =
+            BufferMatrixContext(ring, bufferFactory)
+
+        /**
+         * Automatic buffered matrix, unboxed if it is possible
+         */
+        inline fun <reified T : Any, R : Ring<T>> auto(ring: R): GenericMatrixContext<T, R> =
+            buffered(ring, Buffer.Companion::auto)
+    }
+}
+
+interface GenericMatrixContext<T : Any, R : Ring<T>> : MatrixContext<T> {
     /**
      * The ring context for matrix elements
      */
     val elementContext: R
 
-    /**
-     * Produce a matrix with this context and given dimensions
-     */
-    fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): Matrix<T>
-
     /**
      * Produce a point compatible with matrix space
      */
     fun point(size: Int, initializer: (Int) -> T): Point<T>
 
-    fun scale(a: Matrix<T>, k: Number): Matrix<T> {
+    override infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T> {
-        //TODO create a special wrapper class for scaled matrices
-        return produce(a.rowNum, a.colNum) { i, j -> elementContext.run { a[i, j] * k } }
-    }
-
-    infix fun Matrix<T>.dot(other: Matrix<T>): Matrix<T> {
         //TODO add typed error
         if (this.colNum != other.rowNum) error("Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})")
         return produce(rowNum, other.colNum) { i, j ->
@@ -41,7 +74,7 @@ interface MatrixContext<T : Any, R : Ring<T>> {
         }
     }
 
-    infix fun Matrix<T>.dot(vector: Point<T>): Point<T> {
+    override infix fun Matrix<T>.dot(vector: Point<T>): Point<T> {
         //TODO add typed error
         if (this.colNum != vector.size) error("Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})")
         return point(rowNum) { i ->
@@ -52,15 +85,15 @@ interface MatrixContext<T : Any, R : Ring<T>> {
         }
     }
 
-    operator fun Matrix<T>.unaryMinus() =
+    override operator fun Matrix<T>.unaryMinus() =
         produce(rowNum, colNum) { i, j -> elementContext.run { -get(i, j) } }
 
-    operator fun Matrix<T>.plus(b: Matrix<T>): Matrix<T> {
+    override operator fun Matrix<T>.plus(b: Matrix<T>): Matrix<T> {
         if (rowNum != b.rowNum || colNum != b.colNum) error("Matrix operation dimension mismatch. [$rowNum,$colNum] + [${b.rowNum},${b.colNum}]")
         return produce(rowNum, colNum) { i, j -> elementContext.run { get(i, j) + b[i, j] } }
     }
 
-    operator fun Matrix<T>.minus(b: Matrix<T>): Matrix<T> {
+    override operator fun Matrix<T>.minus(b: Matrix<T>): Matrix<T> {
         if (rowNum != b.rowNum || colNum != b.colNum) error("Matrix operation dimension mismatch. [$rowNum,$colNum] - [${b.rowNum},${b.colNum}]")
         return produce(rowNum, colNum) { i, j -> elementContext.run { get(i, j) + b[i, j] } }
     }
@@ -68,27 +101,10 @@ interface MatrixContext<T : Any, R : Ring<T>> {
     operator fun Matrix<T>.times(number: Number): Matrix<T> =
         produce(rowNum, colNum) { i, j -> elementContext.run { get(i, j) * number } }
 
-    operator fun Number.times(m: Matrix<T>): Matrix<T> = m * this
+    operator fun Number.times(matrix: Matrix<T>): Matrix<T> = matrix * this
 
-
+    override fun Matrix<T>.times(value: T): Matrix<T> =
-    companion object {
+        produce(rowNum, colNum) { i, j -> elementContext.run { get(i, j) * value } }
-        /**
-         * Non-boxing double matrix
-         */
-        val real = BufferMatrixContext(RealField, DoubleBufferFactory)
-
-        /**
-         * A structured matrix with custom buffer
-         */
-        fun <T : Any, R : Ring<T>> buffered(ring: R, bufferFactory: BufferFactory<T> = ::boxing): MatrixContext<T, R> =
-            BufferMatrixContext(ring, bufferFactory)
-
-        /**
-         * Automatic buffered matrix, unboxed if it is possible
-         */
-        inline fun <reified T : Any, R : Ring<T>> auto(ring: R): MatrixContext<T, R> =
-            buffered(ring, Buffer.Companion::auto)
-    }
 }
 
 /**
@@ -173,7 +189,7 @@ inline fun <reified T : Any> Matrix<*>.getFeature(): T? = features.filterIsInsta
 /**
  * Diagonal matrix of ones. The matrix is virtual no actual matrix is created
  */
-fun <T : Any, R : Ring<T>> MatrixContext<T, R>.one(rows: Int, columns: Int): Matrix<T> =
+fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.one(rows: Int, columns: Int): Matrix<T> =
     VirtualMatrix<T>(rows, columns) { i, j ->
         if (i == j) elementContext.one else elementContext.zero
     }
@@ -182,7 +198,7 @@ fun <T : Any, R : Ring<T>> MatrixContext<T, R>.one(rows: Int, columns: Int): Mat
 /**
  * A virtual matrix of zeroes
  */
-fun <T : Any, R : Ring<T>> MatrixContext<T, R>.zero(rows: Int, columns: Int): Matrix<T> =
+fun <T : Any, R : Ring<T>> GenericMatrixContext<T, R>.zero(rows: Int, columns: Int): Matrix<T> =
     VirtualMatrix<T>(rows, columns) { i, j ->
         elementContext.zero
     }

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

@@ -22,7 +22,7 @@ class MatrixTest {
 
     @Test
     fun testTranspose() {
-        val matrix = MatrixContext.real.one(3, 3)
+        val matrix = GenericMatrixContext.real.one(3, 3)
         val transposed = matrix.transpose()
         assertEquals((matrix as BufferMatrix).buffer, (transposed as BufferMatrix).buffer)
         assertEquals(matrix, transposed)
@@ -36,7 +36,7 @@ class MatrixTest {
 
         val matrix1 = vector1.toMatrix()
         val matrix2 = vector2.toMatrix().transpose()
-        val product = MatrixContext.real.run { matrix1 dot matrix2 }
+        val product = GenericMatrixContext.real.run { matrix1 dot matrix2 }
 
 
         assertEquals(5.0, product[1, 0])

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

@@ -6,7 +6,7 @@ import kotlin.test.assertEquals
 class RealLUSolverTest {
     @Test
     fun testInvertOne() {
-        val matrix = MatrixContext.real.one(2, 2)
+        val matrix = GenericMatrixContext.real.one(2, 2)
         val inverted = LUSolver.real.inverse(matrix)
         assertEquals(matrix, inverted)
     }
@@ -25,7 +25,7 @@ class RealLUSolverTest {
         assertEquals(8.0, decomposition.determinant)
 
         //Check decomposition
-        with(MatrixContext.real) {
+        with(GenericMatrixContext.real) {
             assertEquals(decomposition.p dot matrix, decomposition.l dot decomposition.u)
         }
 

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

@@ -1,27 +1,70 @@
 package scientifik.kmath.linear
 
-import scientifik.kmath.operations.Ring
+import koma.extensions.fill
+import koma.matrix.MatrixFactory
 
-class KomaMatrixContext<T: Any, R: Ring<T>> : MatrixContext<T,R> {
+class KomaMatrixContext<T : Any>(val factory: MatrixFactory<koma.matrix.Matrix<T>>) : MatrixContext<T>,
-    override val elementContext: R
+    LinearSolver<T> {
-        get() = TODO("not implemented") //To change initializer of created properties use File | Settings | File Templates.
 
-    override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): Matrix<T> {
+    override fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T) =
-        TODO("not implemented") //To change body of created functions use File | Settings | File Templates.
+        KomaMatrix(factory.zeros(rows, columns).fill(initializer))
+
+    fun Matrix<T>.toKoma(): KomaMatrix<T> = if (this is KomaMatrix) {
+        this
+    } else {
+        produce(rowNum, colNum) { i, j -> get(i, j) }
     }
 
-    override fun point(size: Int, initializer: (Int) -> T): Point<T> {
+    fun Point<T>.toKoma(): KomaVector<T> = if (this is KomaVector) {
-        TODO("not implemented") //To change body of created functions use File | Settings | File Templates.
+        this
+    } else {
+        KomaVector(factory.zeros(size, 1).fill { i, _ -> get(i) })
     }
 
+
+    override fun Matrix<T>.dot(other: Matrix<T>) =
+        KomaMatrix(this.toKoma().origin * other.toKoma().origin)
+
+    override fun Matrix<T>.dot(vector: Point<T>) =
+        KomaVector(this.toKoma().origin * vector.toKoma().origin)
+
+    override fun Matrix<T>.unaryMinus() =
+        KomaMatrix(this.toKoma().origin.unaryMinus())
+
+    override fun Matrix<T>.plus(b: Matrix<T>) =
+        KomaMatrix(this.toKoma().origin + b.toKoma().origin)
+
+    override fun Matrix<T>.minus(b: Matrix<T>) =
+        KomaMatrix(this.toKoma().origin - b.toKoma().origin)
+
+    override fun Matrix<T>.times(value: T) =
+        KomaMatrix(this.toKoma().origin * value)
+
+
+    override fun solve(a: Matrix<T>, b: Matrix<T>) =
+        KomaMatrix(a.toKoma().origin.solve(b.toKoma().origin))
+
+    override fun inverse(a: Matrix<T>) =
+        KomaMatrix(a.toKoma().origin.inv())
 }
 
-inline class KomaMatrix<T : Any>(val matrix: koma.matrix.Matrix<T>) : Matrix<T> {
+inline class KomaMatrix<T : Any>(val origin: koma.matrix.Matrix<T>) : Matrix<T> {
-    override val rowNum: Int get() = matrix.numRows()
+    override val rowNum: Int get() = origin.numRows()
-    override val colNum: Int get() = matrix.numCols()
+    override val colNum: Int get() = origin.numCols()
     override val features: Set<MatrixFeature> get() = emptySet()
 
-    @Suppress("OVERRIDE_BY_INLINE")
+    override fun get(i: Int, j: Int): T = origin.getGeneric(i, j)
-    override inline fun get(i: Int, j: Int): T = matrix.getGeneric(i, j)
-
 }
+
+class KomaVector<T : Any> internal constructor(val origin: koma.matrix.Matrix<T>) : Point<T> {
+    init {
+        if (origin.numCols() != 1) error("Only single column matrices are allowed")
+    }
+
+    override val size: Int get() = origin.numRows()
+
+    override fun get(index: Int): T = origin.getGeneric(index)
+
+    override fun iterator(): Iterator<T> = origin.toIterable().iterator()
+}
+