Merge branch 'dev' into gsl-experiment

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/DotBenchmark.kt

@@ -2,19 +2,22 @@ package kscience.kmath.benchmarks
 
 import kotlinx.benchmark.Benchmark
 import kscience.kmath.commons.linear.CMMatrixContext
-import kscience.kmath.commons.linear.CMMatrixContext.dot
 import kscience.kmath.commons.linear.toCM
 import kscience.kmath.ejml.EjmlMatrixContext
 import kscience.kmath.ejml.toEjml
+import kscience.kmath.linear.BufferMatrixContext
+import kscience.kmath.linear.RealMatrixContext
 import kscience.kmath.linear.real
+import kscience.kmath.operations.RealField
 import kscience.kmath.operations.invoke
+import kscience.kmath.structures.Buffer
 import kscience.kmath.structures.Matrix
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State
 import kotlin.random.Random
 
 @State(Scope.Benchmark)
-class MultiplicationBenchmark {
+class DotBenchmark {
     companion object {
         val random = Random(12224)
         val dim = 1000
@@ -32,14 +35,14 @@ class MultiplicationBenchmark {
 
     @Benchmark
     fun commonsMathMultiplication() {
-        CMMatrixContext.invoke {
+        CMMatrixContext {
             cmMatrix1 dot cmMatrix2
         }
     }
 
     @Benchmark
     fun ejmlMultiplication() {
-        EjmlMatrixContext.invoke {
+        EjmlMatrixContext {
             ejmlMatrix1 dot ejmlMatrix2
         }
     }
@@ -48,13 +51,22 @@ class MultiplicationBenchmark {
     fun ejmlMultiplicationwithConversion() {
         val ejmlMatrix1 = matrix1.toEjml()
         val ejmlMatrix2 = matrix2.toEjml()
-        EjmlMatrixContext.invoke {
+        EjmlMatrixContext {
             ejmlMatrix1 dot ejmlMatrix2
         }
     }
 
     @Benchmark
     fun bufferedMultiplication() {
-        matrix1 dot matrix2
+        BufferMatrixContext(RealField, Buffer.Companion::real).invoke{
+            matrix1 dot matrix2
+        }
+    }
+
+    @Benchmark
+    fun realMultiplication(){
+        RealMatrixContext {
+            matrix1 dot matrix2
+        }
     }
 }

examples/src/main/kotlin/kscience/kmath/structures/typeSafeDimensions.kt

@@ -4,9 +4,8 @@ import kscience.kmath.dimensions.D2
 import kscience.kmath.dimensions.D3
 import kscience.kmath.dimensions.DMatrixContext
 import kscience.kmath.dimensions.Dimension
-import kscience.kmath.operations.RealField
 
-private fun DMatrixContext<Double, RealField>.simple() {
+private fun DMatrixContext<Double>.simple() {
     val m1 = produce<D2, D3> { i, j -> (i + j).toDouble() }
     val m2 = produce<D3, D2> { i, j -> (i + j).toDouble() }
 
@@ -18,7 +17,7 @@ private object D5 : Dimension {
     override val dim: UInt = 5u
 }
 
-private fun DMatrixContext<Double, RealField>.custom() {
+private fun DMatrixContext<Double>.custom() {
     val m1 = produce<D2, D5> { i, j -> (i + j).toDouble() }
     val m2 = produce<D5, D2> { i, j -> (i - j).toDouble() }
     val m3 = produce<D2, D2> { i, j -> (i - j).toDouble() }

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

@@ -29,6 +29,7 @@ public class CMMatrix(public val origin: RealMatrix, features: Set<MatrixFeature
     }
 }
 
+//TODO move inside context
 public fun Matrix<Double>.toCM(): CMMatrix = if (this is CMMatrix) {
     this
 } else {

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

@@ -1,8 +1,10 @@
 package kscience.kmath.linear
 
-import kscience.kmath.operations.RealField
 import kscience.kmath.operations.Ring
-import kscience.kmath.structures.*
+import kscience.kmath.structures.Buffer
+import kscience.kmath.structures.BufferFactory
+import kscience.kmath.structures.NDStructure
+import kscience.kmath.structures.asSequence
 
 /**
  * Basic implementation of Matrix space based on [NDStructure]
@@ -21,24 +23,6 @@ public class BufferMatrixContext<T : Any, R : Ring<T>>(
     public companion object
 }
 
-@Suppress("OVERRIDE_BY_INLINE")
-public object RealMatrixContext : GenericMatrixContext<Double, RealField, BufferMatrix<Double>> {
-    public override val elementContext: RealField
-        get() = RealField
-
-    public override inline fun produce(
-        rows: Int,
-        columns: Int,
-        initializer: (i: Int, j: Int) -> Double,
-    ): BufferMatrix<Double> {
-        val buffer = RealBuffer(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
-        return BufferMatrix(rows, columns, buffer)
-    }
-
-    public override inline fun point(size: Int, initializer: (Int) -> Double): Point<Double> =
-        RealBuffer(size, initializer)
-}
-
 public class BufferMatrix<T : Any>(
     public override val rowNum: Int,
     public override val colNum: Int,

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

@@ -213,17 +213,8 @@ public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext
     return decomposition.solveWithLUP(bufferFactory, b)
 }
 
-public fun RealMatrixContext.solveWithLUP(a: Matrix<Double>, b: Matrix<Double>): FeaturedMatrix<Double> =
-    solveWithLUP(a, b) { it < 1e-11 }
-
 public inline fun <reified T : Comparable<T>, F : Field<T>> GenericMatrixContext<T, F, FeaturedMatrix<T>>.inverseWithLUP(
     matrix: Matrix<T>,
     noinline bufferFactory: MutableBufferFactory<T> = MutableBuffer.Companion::auto,
     noinline checkSingular: (T) -> Boolean,
-): FeaturedMatrix<T> = solveWithLUP(matrix, one(matrix.rowNum, matrix.colNum), bufferFactory, checkSingular)
+): FeaturedMatrix<T> = solveWithLUP(matrix, one(matrix.rowNum, matrix.colNum), bufferFactory, checkSingular)
-
-/**
- * Inverses a square matrix using LUP decomposition. Non square matrix will throw a error.
- */
-public fun RealMatrixContext.inverseWithLUP(matrix: Matrix<Double>): FeaturedMatrix<Double> =
-    solveWithLUP(matrix, one(matrix.rowNum, matrix.colNum), Buffer.Companion::real) { it < 1e-11 }

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/MatrixContext.kt

@@ -18,6 +18,11 @@ public interface MatrixContext<T : Any, out M : Matrix<T>> : SpaceOperations<Mat
      */
     public fun produce(rows: Int, columns: Int, initializer: (i: Int, j: Int) -> T): M
 
+    /**
+     * Produce a point compatible with matrix space (and possibly optimized for it)
+     */
+    public fun point(size: Int, initializer: (Int) -> T): Point<T> = Buffer.boxing(size, initializer)
+
     @Suppress("UNCHECKED_CAST")
     public override fun binaryOperationFunction(operation: String): (left: Matrix<T>, right: Matrix<T>) -> M =
         when (operation) {
@@ -62,10 +67,6 @@ public interface MatrixContext<T : Any, out M : Matrix<T>> : SpaceOperations<Mat
     public operator fun T.times(m: Matrix<T>): M = m * this
 
     public companion object {
-        /**
-         * Non-boxing double matrix
-         */
-        public val real: RealMatrixContext = RealMatrixContext
 
         /**
          * A structured matrix with custom buffer
@@ -89,11 +90,6 @@ public interface GenericMatrixContext<T : Any, R : Ring<T>, out M : Matrix<T>> :
      */
     public val elementContext: R
 
-    /**
-     * Produce a point compatible with matrix space
-     */
-    public fun point(size: Int, initializer: (Int) -> T): Point<T>
-
     public override infix fun Matrix<T>.dot(other: Matrix<T>): M {
         //TODO add typed error
         require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/RealMatrixContext.kt

@@ -0,0 +1,84 @@
+package kscience.kmath.linear
+
+import kscience.kmath.operations.RealField
+import kscience.kmath.structures.Matrix
+import kscience.kmath.structures.MutableBuffer
+import kscience.kmath.structures.MutableBufferFactory
+import kscience.kmath.structures.RealBuffer
+
+@Suppress("OVERRIDE_BY_INLINE")
+public object RealMatrixContext : MatrixContext<Double, BufferMatrix<Double>> {
+
+    public override inline fun produce(
+        rows: Int,
+        columns: Int,
+        initializer: (i: Int, j: Int) -> Double,
+    ): BufferMatrix<Double> {
+        val buffer = RealBuffer(rows * columns) { offset -> initializer(offset / columns, offset % columns) }
+        return BufferMatrix(rows, columns, buffer)
+    }
+
+    private fun Matrix<Double>.wrap(): BufferMatrix<Double> = if (this is BufferMatrix) this else {
+        produce(rowNum, colNum) { i, j -> get(i, j) }
+    }
+
+    public fun one(rows: Int, columns: Int): FeaturedMatrix<Double> = VirtualMatrix(rows, columns, DiagonalFeature) { i, j ->
+        if (i == j) 1.0 else 0.0
+    }
+
+    public override infix fun Matrix<Double>.dot(other: Matrix<Double>): BufferMatrix<Double> {
+        require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
+        return produce(rowNum, other.colNum) { i, j ->
+            var res = 0.0
+            for (l in 0 until colNum) {
+                res += get(i, l) * other.get(l, j)
+            }
+            res
+        }
+    }
+
+    public override infix fun Matrix<Double>.dot(vector: Point<Double>): Point<Double> {
+        require(colNum == vector.size) { "Matrix dot vector operation dimension mismatch: ($rowNum, $colNum) x (${vector.size})" }
+        return RealBuffer(rowNum) { i ->
+            var res = 0.0
+            for (j in 0 until colNum) {
+                res += get(i, j) * vector[j]
+            }
+            res
+        }
+    }
+
+    override fun add(a: Matrix<Double>, b: Matrix<Double>): BufferMatrix<Double> {
+        require(a.rowNum == b.rowNum) { "Row number mismatch in matrix addition. Left side: ${a.rowNum}, right side: ${b.rowNum}" }
+        require(a.colNum == b.colNum) { "Column number mismatch in matrix addition. Left side: ${a.colNum}, right side: ${b.colNum}" }
+        return produce(a.rowNum, a.colNum) { i, j ->
+            a[i, j] + b[i, j]
+        }
+    }
+
+    override fun Matrix<Double>.times(value: Double): BufferMatrix<Double> =
+        produce(rowNum, colNum) { i, j -> get(i, j) * value }
+
+
+    override fun multiply(a: Matrix<Double>, k: Number): BufferMatrix<Double> =
+        produce(a.rowNum, a.colNum) { i, j -> a.get(i, j) * k.toDouble() }
+}
+
+
+/**
+ * Partially optimized real-valued matrix
+ */
+public val MatrixContext.Companion.real: RealMatrixContext get() = RealMatrixContext
+
+public fun RealMatrixContext.solveWithLUP(a: Matrix<Double>, b: Matrix<Double>): FeaturedMatrix<Double> {
+    // Use existing decomposition if it is provided by matrix
+    val bufferFactory: MutableBufferFactory<Double> = MutableBuffer.Companion::real
+    val decomposition = a.getFeature() ?: lup(bufferFactory, RealField, a) { it < 1e-11 }
+    return decomposition.solveWithLUP(bufferFactory, b)
+}
+
+/**
+ * Inverses a square matrix using LUP decomposition. Non square matrix will throw a error.
+ */
+public fun RealMatrixContext.inverseWithLUP(matrix: Matrix<Double>): FeaturedMatrix<Double> =
+    solveWithLUP(matrix, one(matrix.rowNum, matrix.colNum))

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

@@ -1,11 +1,6 @@
 package kscience.kmath.dimensions
 
-import kscience.kmath.linear.GenericMatrixContext
+import kscience.kmath.linear.*
-import kscience.kmath.linear.MatrixContext
-import kscience.kmath.linear.Point
-import kscience.kmath.linear.transpose
-import kscience.kmath.operations.RealField
-import kscience.kmath.operations.Ring
 import kscience.kmath.operations.invoke
 import kscience.kmath.structures.Matrix
 import kscience.kmath.structures.Structure2D
@@ -42,7 +37,7 @@ public interface DMatrix<T, R : Dimension, C : Dimension> : Structure2D<T> {
  * An inline wrapper for a Matrix
  */
 public inline class DMatrixWrapper<T, R : Dimension, C : Dimension>(
-    private val structure: Structure2D<T>
+    private val structure: Structure2D<T>,
 ) : DMatrix<T, R, C> {
     override val shape: IntArray get() = structure.shape
     override operator fun get(i: Int, j: Int): T = structure[i, j]
@@ -81,7 +76,7 @@ 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, Ri : Ring<T>>(public val context: GenericMatrixContext<T, Ri, Matrix<T>>) {
+public inline class DMatrixContext<T : Any>(public val context: MatrixContext<T, Matrix<T>>) {
     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"
@@ -115,7 +110,7 @@ public inline class DMatrixContext<T : Any, Ri : Ring<T>>(public val context: Ge
     }
 
     public inline infix fun <reified R1 : Dimension, reified C1 : Dimension, reified C2 : Dimension> DMatrix<T, R1, C1>.dot(
-        other: DMatrix<T, C1, C2>
+        other: DMatrix<T, C1, C2>,
     ): DMatrix<T, R1, C2> = context { 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> =
@@ -139,18 +134,19 @@ public inline class DMatrixContext<T : Any, Ri : Ring<T>>(public val context: Ge
     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()
 
-    /**
-     * A square unit matrix
-     */
-    public inline fun <reified D : Dimension> one(): DMatrix<T, D, D> = produce { i, j ->
-        if (i == j) context.elementContext.one else context.elementContext.zero
-    }
-
-    public inline fun <reified R : Dimension, reified C : Dimension> zero(): DMatrix<T, R, C> = produce { _, _ ->
-        context.elementContext.zero
-    }
-
     public companion object {
-        public val real: DMatrixContext<Double, RealField> = DMatrixContext(MatrixContext.real)
+        public val real: DMatrixContext<Double> = DMatrixContext(MatrixContext.real)
     }
 }
+
+
+/**
+ * A square unit matrix
+ */
+public inline fun <reified D : Dimension> DMatrixContext<Double>.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> = produce { _, _ ->
+    0.0
+}

kmath-dimensions/src/commonTest/kotlin/kscience/dimensions/DMatrixContextTest.kt

@@ -3,6 +3,7 @@ package kscience.dimensions
 import kscience.kmath.dimensions.D2
 import kscience.kmath.dimensions.D3
 import kscience.kmath.dimensions.DMatrixContext
+import kscience.kmath.dimensions.one
 import kotlin.test.Test
 
 internal class DMatrixContextTest {

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

@@ -1,13 +1,7 @@
 package kscience.kmath.real
 
-import kscience.kmath.linear.FeaturedMatrix
+import kscience.kmath.linear.*
-import kscience.kmath.linear.MatrixContext
-import kscience.kmath.linear.RealMatrixContext.elementContext
-import kscience.kmath.linear.VirtualMatrix
-import kscience.kmath.linear.inverseWithLUP
 import kscience.kmath.misc.UnstableKMathAPI
-import kscience.kmath.operations.invoke
-import kscience.kmath.operations.sum
 import kscience.kmath.structures.Buffer
 import kscience.kmath.structures.RealBuffer
 import kscience.kmath.structures.asIterable
@@ -122,8 +116,7 @@ public fun RealMatrix.extractColumn(columnIndex: Int): RealMatrix =
     extractColumns(columnIndex..columnIndex)
 
 public fun RealMatrix.sumByColumn(): RealBuffer = RealBuffer(colNum) { j ->
-    val column = columns[j]
+    columns[j].asIterable().sum()
-    elementContext { sum(column.asIterable()) }
 }
 
 public fun RealMatrix.minByColumn(): RealBuffer = RealBuffer(colNum) { j ->