kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt

@@ -22,7 +22,7 @@ public typealias Vector<T> = Point<T>
  * @param T the type of items in the matrices.
  * @param M the type of operated matrices.
  */
-public interface LinearSpace<T : Any, A : Ring<T>> {
+public interface LinearSpace<T : Any, out A : Ring<T>> {
     public val elementAlgebra: A
 
     /**

kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LupDecomposition.kt

@@ -228,7 +228,7 @@ public inline fun <reified T : Comparable<T>> LinearSpace<T, Field<T>>.inverseWi
 
 
 @OptIn(UnstableKMathAPI::class)
-public fun RealLinearSpace.solveWithLup(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> {
+public fun LinearSpace<Double, RealField>.solveWithLup(a: Matrix<Double>, b: Matrix<Double>): Matrix<Double> {
     // Use existing decomposition if it is provided by matrix
     val bufferFactory: MutableBufferFactory<Double> = MutableBuffer.Companion::real
     val decomposition: LupDecomposition<Double> = a.getFeature() ?: lup(bufferFactory, a) { it < 1e-11 }
@@ -238,5 +238,5 @@ public fun RealLinearSpace.solveWithLup(a: Matrix<Double>, b: Matrix<Double>): M
 /**
  * Inverses a square matrix using LUP decomposition. Non square matrix will throw a error.
  */
-public fun RealLinearSpace.inverseWithLup(matrix: Matrix<Double>): Matrix<Double> =
+public fun LinearSpace<Double, RealField>.inverseWithLup(matrix: Matrix<Double>): Matrix<Double> =
     solveWithLup(matrix, one(matrix.rowNum, matrix.colNum))

kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/MatrixTest.kt

@@ -2,7 +2,6 @@ package space.kscience.kmath.linear
 
 import space.kscience.kmath.nd.NDStructure
 import space.kscience.kmath.nd.as2D
-import space.kscience.kmath.operations.invoke
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
@@ -17,7 +16,7 @@ class MatrixTest {
 
     @Test
     fun testBuilder() {
-        val matrix = Matrix.build(2, 3)(
+        val matrix = LinearSpace.real.matrix(2, 3)(
             1.0, 0.0, 0.0,
             0.0, 1.0, 2.0
         )

kmath-dimensions/src/commonMain/kotlin/space/kscience/kmath/dimensions/Wrappers.kt

@@ -2,7 +2,8 @@ package space.kscience.kmath.dimensions
 
 import space.kscience.kmath.linear.*
 import space.kscience.kmath.nd.Structure2D
-import space.kscience.kmath.operations.invoke
+import space.kscience.kmath.operations.RealField
+import space.kscience.kmath.operations.Ring
 
 /**
  * A matrix with compile-time controlled dimension
@@ -77,7 +78,7 @@ public inline class DPointWrapper<T, D : Dimension>(public val point: Point<T>)
 /**
  * Basic operations on dimension-safe matrices. Operates on [Matrix]
  */
-public inline class DMatrixContext<T : Any>(public val context: LinearSpace<T, Matrix<T>>) {
+public inline class DMatrixContext<T : Any, out A : Ring<T>>(public val context: LinearSpace<T, A>) {
     public inline fun <reified R : Dimension, reified C : Dimension> Matrix<T>.coerce(): DMatrix<T, R, C> {
         require(rowNum == Dimension.dim<R>().toInt()) {
             "Row number mismatch: expected ${Dimension.dim<R>()} but found $rowNum"
@@ -93,13 +94,15 @@ public inline class DMatrixContext<T : Any>(public val context: LinearSpace<T, M
     /**
      * Produce a matrix with this context and given dimensions
      */
-    public inline fun <reified R : Dimension, reified C : Dimension> produce(noinline initializer: (i: Int, j: Int) -> T): DMatrix<T, R, C> {
+    public inline fun <reified R : Dimension, reified C : Dimension> produce(
+        noinline initializer: A.(i: Int, j: Int) -> T
+    ): DMatrix<T, R, C> {
         val rows = Dimension.dim<R>()
         val cols = Dimension.dim<C>()
         return context.buildMatrix(rows.toInt(), cols.toInt(), initializer).coerce<R, C>()
     }
 
-    public inline fun <reified D : Dimension> point(noinline initializer: (Int) -> T): DPoint<T, D> {
+    public inline fun <reified D : Dimension> point(noinline initializer: A.(Int) -> T): DPoint<T, D> {
         val size = Dimension.dim<D>()
 
         return DPoint.coerceUnsafe(
@@ -112,31 +115,31 @@ public inline class DMatrixContext<T : Any>(public val context: LinearSpace<T, M
 
     public inline infix fun <reified R1 : Dimension, reified C1 : Dimension, reified C2 : Dimension> DMatrix<T, R1, C1>.dot(
         other: DMatrix<T, C1, C2>,
-    ): DMatrix<T, R1, C2> = context { this@dot dot other }.coerce()
+    ): DMatrix<T, R1, C2> = context.run { this@dot dot other }.coerce()
 
     public inline infix fun <reified R : Dimension, reified C : Dimension> DMatrix<T, R, C>.dot(vector: DPoint<T, C>): DPoint<T, R> =
-        DPoint.coerceUnsafe(context { this@dot dot vector })
+        DPoint.coerceUnsafe(context.run { this@dot dot vector })
 
     public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, R, C>.times(value: T): DMatrix<T, R, C> =
-        context { this@times.times(value) }.coerce()
+        context.run { this@times.times(value) }.coerce()
 
     public inline operator fun <reified R : Dimension, reified C : Dimension> T.times(m: DMatrix<T, R, C>): DMatrix<T, R, C> =
         m * this
 
     public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.plus(other: DMatrix<T, C, R>): DMatrix<T, C, R> =
-        context { this@plus + other }.coerce()
+        context.run { this@plus + other }.coerce()
 
     public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.minus(other: DMatrix<T, C, R>): DMatrix<T, C, R> =
-        context { this@minus + other }.coerce()
+        context.run { this@minus + other }.coerce()
 
     public inline operator fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.unaryMinus(): DMatrix<T, C, R> =
-        context { this@unaryMinus.unaryMinus() }.coerce()
+        context.run { this@unaryMinus.unaryMinus() }.coerce()
 
     public inline fun <reified R : Dimension, reified C : Dimension> DMatrix<T, C, R>.transpose(): DMatrix<T, R, C> =
-        context { (this@transpose as Matrix<T>).transpose() }.coerce()
+        context.run { (this@transpose as Matrix<T>).transpose() }.coerce()
 
     public companion object {
-        public val real: DMatrixContext<Double> = DMatrixContext(LinearSpace.real)
+        public val real: DMatrixContext<Double, RealField> = DMatrixContext(LinearSpace.real)
     }
 }
 
@@ -144,11 +147,11 @@ public inline class DMatrixContext<T : Any>(public val context: LinearSpace<T, M
 /**
  * A square unit matrix
  */
-public inline fun <reified D : Dimension> DMatrixContext<Double>.one(): DMatrix<Double, D, D> = produce { i, j ->
+public inline fun <reified D : Dimension> DMatrixContext<Double, RealField>.one(): DMatrix<Double, D, D> = produce { i, j ->
     if (i == j) 1.0 else 0.0
 }
 
-public inline fun <reified R : Dimension, reified C : Dimension> DMatrixContext<Double>.zero(): DMatrix<Double, R, C> =
+public inline fun <reified R : Dimension, reified C : Dimension> DMatrixContext<Double, RealField>.zero(): DMatrix<Double, R, C> =
     produce { _, _ ->
         0.0
     }

kmath-ejml/src/main/kotlin/space/kscience/kmath/ejml/EjmlLinearSpace.kt

@@ -44,7 +44,7 @@ public object EjmlLinearSpace : LinearSpace<Double, RealField>, ScaleOperations<
 
     override fun buildVector(size: Int, initializer: RealField.(Int) -> Double): Vector<Double> =
         EjmlVector(SimpleMatrix(size, 1).also {
-            (0 until it.numRows()).forEach { row -> it[row, 0] = initializer(row) }
+            (0 until it.numRows()).forEach { row -> it[row, 0] = RealField.initializer(row) }
         })
 
     private fun SimpleMatrix.wrapMatrix() = EjmlMatrix(this)
@@ -59,43 +59,34 @@ public object EjmlLinearSpace : LinearSpace<Double, RealField>, ScaleOperations<
         EjmlVector(toEjml().origin.mult(vector.toEjml().origin))
 
     public override operator fun Matrix<Double>.minus(other: Matrix<Double>): EjmlMatrix =
-        EjmlMatrix(toEjml().origin - other.toEjml().origin)
+        (toEjml().origin - other.toEjml().origin).wrapMatrix()
 
     public override fun scale(a: Matrix<Double>, value: Double): EjmlMatrix =
         a.toEjml().origin.scale(value).wrapMatrix()
 
     public override operator fun Matrix<Double>.times(value: Double): EjmlMatrix =
-        EjmlMatrix(toEjml().origin.scale(value))
+        toEjml().origin.scale(value).wrapMatrix()
 
     override fun Vector<Double>.unaryMinus(): EjmlVector =
         toEjml().origin.negative().wrapVector()
 
-    override fun Matrix<Double>.plus(other: Matrix<Double>): Matrix<Double> {
+    override fun Matrix<Double>.plus(other: Matrix<Double>): EjmlMatrix =
-        TODO("Not yet implemented")
+        (toEjml().origin + other.toEjml().origin).wrapMatrix()
-    }
 
-    override fun Vector<Double>.plus(other: Vector<Double>): Vector<Double> {
+    override fun Vector<Double>.plus(other: Vector<Double>): EjmlVector =
-        TODO("Not yet implemented")
+        (toEjml().origin + other.toEjml().origin).wrapVector()
-    }
 
-    override fun Vector<Double>.minus(other: Vector<Double>): Vector<Double> {
+    override fun Vector<Double>.minus(other: Vector<Double>): EjmlVector =
-        TODO("Not yet implemented")
+        (toEjml().origin - other.toEjml().origin).wrapVector()
-    }
 
-    override fun Double.times(m: Matrix<Double>): Matrix<Double> {
+    override fun Double.times(m: Matrix<Double>): EjmlMatrix =
-        TODO("Not yet implemented")
+        m.toEjml().origin.scale(this).wrapMatrix()
-    }
 
-    override fun Vector<Double>.times(value: Double): Vector<Double> {
+    override fun Vector<Double>.times(value: Double): EjmlVector =
-        TODO("Not yet implemented")
+        toEjml().origin.scale(value).wrapVector()
-    }
 
-    override fun Double.times(v: Vector<Double>): Vector<Double> {
+    override fun Double.times(v: Vector<Double>): EjmlVector =
-        TODO("Not yet implemented")
+        v.toEjml().origin.scale(this).wrapVector()
-    }
-
-    public override fun add(a: Matrix<Double>, b: Matrix<Double>): EjmlMatrix =
-        EjmlMatrix(a.toEjml().origin + b.toEjml().origin)
 }
 
 /**

kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/RealMatrix.kt

@@ -2,6 +2,7 @@ package space.kscience.kmath.real
 
 import space.kscience.kmath.linear.*
 import space.kscience.kmath.misc.UnstableKMathAPI
+import space.kscience.kmath.operations.RealField
 import space.kscience.kmath.structures.Buffer
 import space.kscience.kmath.structures.RealBuffer
 import space.kscience.kmath.structures.asIterable
@@ -21,11 +22,11 @@ import kotlin.math.pow
 
 public typealias RealMatrix = Matrix<Double>
 
-public fun realMatrix(rowNum: Int, colNum: Int, initializer: (i: Int, j: Int) -> Double): RealMatrix =
+public fun realMatrix(rowNum: Int, colNum: Int, initializer: RealField.(i: Int, j: Int) -> Double): RealMatrix =
     LinearSpace.real.buildMatrix(rowNum, colNum, initializer)
 
 public fun Array<DoubleArray>.toMatrix(): RealMatrix {
-    return LinearSpace.real.buildMatrix(size, this[0].size) { row, col -> this[row][col] }
+    return LinearSpace.real.buildMatrix(size, this[0].size) { row, col -> this@toMatrix[row][col] }
 }
 
 public fun Sequence<DoubleArray>.toMatrix(): RealMatrix = toList().let {
@@ -43,37 +44,37 @@ public fun RealMatrix.repeatStackVertical(n: Int): RealMatrix =
 
 public operator fun RealMatrix.times(double: Double): RealMatrix =
     LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
-        this[row, col] * double
+        get(row, col) * double
     }
 
 public operator fun RealMatrix.plus(double: Double): RealMatrix =
     LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
-        this[row, col] + double
+        get(row, col) + double
     }
 
 public operator fun RealMatrix.minus(double: Double): RealMatrix =
     LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
-        this[row, col] - double
+        get(row, col) - double
     }
 
 public operator fun RealMatrix.div(double: Double): RealMatrix =
     LinearSpace.real.buildMatrix(rowNum, colNum) { row, col ->
-        this[row, col] / double
+        get(row, col) / double
     }
 
 public operator fun Double.times(matrix: RealMatrix): RealMatrix =
     LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col ->
-        this * matrix[row, col]
+        this@times * matrix[row, col]
     }
 
 public operator fun Double.plus(matrix: RealMatrix): RealMatrix =
     LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col ->
-        this + matrix[row, col]
+        this@plus + matrix[row, col]
     }
 
 public operator fun Double.minus(matrix: RealMatrix): RealMatrix =
     LinearSpace.real.buildMatrix(matrix.rowNum, matrix.colNum) { row, col ->
-        this - matrix[row, col]
+        this@minus - matrix[row, col]
     }
 
 // TODO: does this operation make sense? Should it be 'this/matrix[row, col]'?
@@ -87,13 +88,13 @@ public operator fun Double.minus(matrix: RealMatrix): RealMatrix =
 
 @UnstableKMathAPI
 public operator fun RealMatrix.times(other: RealMatrix): RealMatrix =
-    LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this[row, col] * other[row, col] }
+    LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this@times[row, col] * other[row, col] }
 
 public operator fun RealMatrix.plus(other: RealMatrix): RealMatrix =
-    LinearSpace.real.add(this, other)
+    LinearSpace.real.run { this@plus + other }
 
 public operator fun RealMatrix.minus(other: RealMatrix): RealMatrix =
-    LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this[row, col] - other[row, col] }
+    LinearSpace.real.buildMatrix(rowNum, colNum) { row, col -> this@minus[row, col] - other[row, col] }
 
 /*
  *  Operations on columns
@@ -102,14 +103,14 @@ public operator fun RealMatrix.minus(other: RealMatrix): RealMatrix =
 public inline fun RealMatrix.appendColumn(crossinline mapper: (Buffer<Double>) -> Double): RealMatrix =
     LinearSpace.real.buildMatrix(rowNum, colNum + 1) { row, col ->
         if (col < colNum)
-            this[row, col]
+            get(row, col)
         else
             mapper(rows[row])
     }
 
 public fun RealMatrix.extractColumns(columnRange: IntRange): RealMatrix =
     LinearSpace.real.buildMatrix(rowNum, columnRange.count()) { row, col ->
-        this[row, columnRange.first + col]
+        this@extractColumns[row, columnRange.first + col]
     }
 
 public fun RealMatrix.extractColumn(columnIndex: Int): RealMatrix =

kmath-for-real/src/commonMain/kotlin/space/kscience/kmath/real/dot.kt

@@ -1,31 +1,31 @@
 package space.kscience.kmath.real
 
-import space.kscience.kmath.linear.BufferMatrix
+import space.kscience.kmath.linear.LinearSpace
-import space.kscience.kmath.structures.Buffer
+import space.kscience.kmath.nd.Matrix
-import space.kscience.kmath.structures.RealBuffer
 
 
 /**
  * Optimized dot product for real matrices
  */
-public infix fun BufferMatrix<Double>.dot(other: BufferMatrix<Double>): BufferMatrix<Double> {
+public infix fun Matrix<Double>.dot(other: Matrix<Double>): Matrix<Double> = LinearSpace.real.run{
-    require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
+    this@dot dot other
-    val resultArray = DoubleArray(this.rowNum * other.colNum)
+//    require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
-
+//    val resultArray = DoubleArray(this.rowNum * other.colNum)
-    //convert to array to insure there is no memory indirection
+//
-    fun Buffer<Double>.unsafeArray() = if (this is RealBuffer)
+//    //convert to array to insure there is no memory indirection
-        this.array
+//    fun Buffer<Double>.unsafeArray() = if (this is RealBuffer)
-    else
+//        this.array
-        DoubleArray(size) { get(it) }
+//    else
-
+//        DoubleArray(size) { get(it) }
-    val a = this.buffer.unsafeArray()
+//
-    val b = other.buffer.unsafeArray()
+//    val a = this.buffer.unsafeArray()
-
+//    val b = other.buffer.unsafeArray()
-    for (i in (0 until rowNum))
+//
-        for (j in (0 until other.colNum))
+//    for (i in (0 until rowNum))
-            for (k in (0 until colNum))
+//        for (j in (0 until other.colNum))
-                resultArray[i * other.colNum + j] += a[i * colNum + k] * b[k * other.colNum + j]
+//            for (k in (0 until colNum))
-
+//                resultArray[i * other.colNum + j] += a[i * colNum + k] * b[k * other.colNum + j]
-    val buffer = RealBuffer(resultArray)
+//
-    return BufferMatrix(rowNum, other.colNum, buffer)
+//    val buffer = RealBuffer(resultArray)
+//    return BufferMatrix(rowNum, other.colNum, buffer)
 }