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

@@ -2,8 +2,8 @@ package kscience.kmath.commons.linear
 
 import kscience.kmath.linear.DiagonalFeature
 import kscience.kmath.linear.MatrixContext
-import kscience.kmath.linear.MatrixWrapper
 import kscience.kmath.linear.Point
+import kscience.kmath.linear.origin
 import kscience.kmath.misc.UnstableKMathAPI
 import kscience.kmath.structures.Matrix
 import org.apache.commons.math3.linear.*
@@ -47,9 +47,9 @@ public object CMMatrixContext : MatrixContext<Double, CMMatrix> {
         return CMMatrix(Array2DRowRealMatrix(array))
     }
 
-    public fun Matrix<Double>.toCM(): CMMatrix = when {
+    @OptIn(UnstableKMathAPI::class)
-        this is CMMatrix -> this
+    public fun Matrix<Double>.toCM(): CMMatrix = when (val matrix = origin) {
-        this is MatrixWrapper && matrix is CMMatrix -> matrix as CMMatrix
+        is CMMatrix -> matrix
         else -> {
             //TODO add feature analysis
             val array = Array(rowNum) { i -> DoubleArray(colNum) { j -> get(i, j) } }

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

@@ -15,29 +15,37 @@ import kotlin.reflect.safeCast
  *
  * @param T the type of items.
  */
-public class MatrixWrapper<T : Any>(
+public class MatrixWrapper<T : Any> internal  constructor(
-    public val matrix: Matrix<T>,
+    public val origin: Matrix<T>,
     public val features: Set<MatrixFeature>,
-) : Matrix<T> by matrix {
+) : Matrix<T> by origin {
 
     /**
      * Get the first feature matching given class. Does not guarantee that matrix has only one feature matching the criteria
      */
     @UnstableKMathAPI
     override fun <T : Any> getFeature(type: KClass<T>): T? = type.safeCast(features.find { type.isInstance(it) })
+        ?: origin.getFeature(type)
 
-    override fun equals(other: Any?): Boolean = matrix == other
+    override fun equals(other: Any?): Boolean = origin == other
-    override fun hashCode(): Int = matrix.hashCode()
+    override fun hashCode(): Int = origin.hashCode()
     override fun toString(): String {
-        return "MatrixWrapper(matrix=$matrix, features=$features)"
+        return "MatrixWrapper(matrix=$origin, features=$features)"
     }
 }
 
+/**
+ * Return the original matrix. If this is a wrapper, return its origin. If not, this matrix.
+ * Origin does not necessary store all features.
+ */
+@UnstableKMathAPI
+public val <T : Any> Matrix<T>.origin: Matrix<T> get() = (this as? MatrixWrapper)?.origin ?: this
+
 /**
  * Add a single feature to a [Matrix]
  */
 public operator fun <T : Any> Matrix<T>.plus(newFeature: MatrixFeature): MatrixWrapper<T> = if (this is MatrixWrapper) {
-    MatrixWrapper(matrix, features + newFeature)
+    MatrixWrapper(origin, features + newFeature)
 } else {
     MatrixWrapper(this, setOf(newFeature))
 }
@@ -47,7 +55,7 @@ public operator fun <T : Any> Matrix<T>.plus(newFeature: MatrixFeature): MatrixW
  */
 public operator fun <T : Any> Matrix<T>.plus(newFeatures: Collection<MatrixFeature>): MatrixWrapper<T> =
     if (this is MatrixWrapper) {
-        MatrixWrapper(matrix, features + newFeatures)
+        MatrixWrapper(origin, features + newFeatures)
     } else {
         MatrixWrapper(this, newFeatures.toSet())
     }

kmath-core/src/commonMain/kotlin/kscience/kmath/operations/Algebra.kt

@@ -92,7 +92,7 @@ public interface Algebra<T> {
  * Call a block with an [Algebra] as receiver.
  */
 // TODO add contract when KT-32313 is fixed
-public inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = block()
+public inline operator fun <A : Algebra<*>, R> A.invoke(block: A.() -> R): R = run(block)
 
 /**
  * Represents "semispace", i.e. algebraic structure with associative binary operation called "addition" as well as

kmath-ejml/src/main/kotlin/kscience/kmath/ejml/EjmlMatrixContext.kt

@@ -2,8 +2,8 @@ package kscience.kmath.ejml
 
 import kscience.kmath.linear.InverseMatrixFeature
 import kscience.kmath.linear.MatrixContext
-import kscience.kmath.linear.MatrixWrapper
 import kscience.kmath.linear.Point
+import kscience.kmath.linear.origin
 import kscience.kmath.misc.UnstableKMathAPI
 import kscience.kmath.structures.Matrix
 import kscience.kmath.structures.getFeature
@@ -19,9 +19,9 @@ public object EjmlMatrixContext : MatrixContext<Double, EjmlMatrix> {
     /**
      * Converts this matrix to EJML one.
      */
-    public fun Matrix<Double>.toEjml(): EjmlMatrix = when {
+    @OptIn(UnstableKMathAPI::class)
-        this is EjmlMatrix -> this
+    public fun Matrix<Double>.toEjml(): EjmlMatrix = when (val matrix = origin) {
-        this is MatrixWrapper && matrix is EjmlMatrix -> matrix as EjmlMatrix
+        is EjmlMatrix -> matrix
         else -> produce(rowNum, colNum) { i, j -> get(i, j) }
     }
 

kmath-ejml/src/test/kotlin/kscience/kmath/ejml/EjmlMatrixTest.kt

@@ -4,6 +4,7 @@ import kscience.kmath.linear.DeterminantFeature
 import kscience.kmath.linear.LupDecompositionFeature
 import kscience.kmath.linear.MatrixFeature
 import kscience.kmath.linear.plus
+import kscience.kmath.misc.UnstableKMathAPI
 import kscience.kmath.structures.getFeature
 import org.ejml.dense.row.factory.DecompositionFactory_DDRM
 import org.ejml.simple.SimpleMatrix
@@ -39,6 +40,7 @@ internal class EjmlMatrixTest {
         assertEquals(listOf(m.numRows(), m.numCols()), w.shape.toList())
     }
 
+    @OptIn(UnstableKMathAPI::class)
     @Test
     fun features() {
         val m = randomMatrix
@@ -57,6 +59,7 @@ internal class EjmlMatrixTest {
 
     private object SomeFeature : MatrixFeature {}
 
+    @OptIn(UnstableKMathAPI::class)
     @Test
     fun suggestFeature() {
         assertNotNull((EjmlMatrix(randomMatrix) + SomeFeature).getFeature<SomeFeature>())

kmath-stat/src/jvmTest/kotlin/kscience/kmath/stat/MCScopeTest.kt

@@ -62,6 +62,7 @@ class MCScopeTest {
     }
 
 
+    @OptIn(ObsoleteCoroutinesApi::class)
     fun compareResult(test: ATest) {
         val res1 = runBlocking(Dispatchers.Default) { test() }
         val res2 = runBlocking(newSingleThreadContext("test")) { test() }