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

@@ -36,7 +36,7 @@ public class EjmlMatrix(public val origin: SimpleMatrix, features: Set<MatrixFea
                 Triple(
                     EjmlMatrix(SimpleMatrix(ludecompositionF64.getRowPivot(null))),
                     EjmlMatrix(SimpleMatrix(ludecompositionF64.getLower(null))),
-                    EjmlMatrix(SimpleMatrix(ludecompositionF64.getUpper(null)))
+                    EjmlMatrix(SimpleMatrix(ludecompositionF64.getUpper(null))),
                 )
             }
 
@@ -51,7 +51,7 @@ public class EjmlMatrix(public val origin: SimpleMatrix, features: Set<MatrixFea
         }
     ) union features.orEmpty()
 
-    public override fun suggestFeature(vararg features: MatrixFeature): FeaturedMatrix<Double> =
+    public override fun suggestFeature(vararg features: MatrixFeature): EjmlMatrix =
         EjmlMatrix(origin, this.features + features)
 
     public override operator fun get(i: Int, j: Int): Double = origin[i, j]

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

@@ -0,0 +1,75 @@
+package kscience.kmath.ejml
+
+import kscience.kmath.linear.DeterminantFeature
+import kscience.kmath.linear.LUPDecompositionFeature
+import kscience.kmath.linear.MatrixFeature
+import kscience.kmath.linear.getFeature
+import org.ejml.dense.row.factory.DecompositionFactory_DDRM
+import org.ejml.simple.SimpleMatrix
+import kotlin.random.Random
+import kotlin.random.asJavaRandom
+import kotlin.test.*
+
+internal class EjmlMatrixTest {
+    private val random = Random(0)
+
+    private val randomMatrix: SimpleMatrix
+        get() {
+            val s = random.nextInt(2, 100)
+            return SimpleMatrix.random_DDRM(s, s, 0.0, 10.0, random.asJavaRandom())
+        }
+
+    @Test
+    fun rowNum() {
+        val m = randomMatrix
+        assertEquals(m.numRows(), EjmlMatrix(m).rowNum)
+    }
+
+    @Test
+    fun colNum() {
+        val m = randomMatrix
+        assertEquals(m.numCols(), EjmlMatrix(m).rowNum)
+    }
+
+    @Test
+    fun shape() {
+        val m = randomMatrix
+        val w = EjmlMatrix(m)
+        assertEquals(listOf(m.numRows(), m.numCols()), w.shape.toList())
+    }
+
+    @Test
+    fun features() {
+        val m = randomMatrix
+        val w = EjmlMatrix(m)
+        val det = w.getFeature<DeterminantFeature<Double>>() ?: fail()
+        assertEquals(m.determinant(), det.determinant)
+        val lup = w.getFeature<LUPDecompositionFeature<Double>>() ?: fail()
+
+        val ludecompositionF64 = DecompositionFactory_DDRM.lu(m.numRows(), m.numCols())
+            .also { it.decompose(m.ddrm.copy()) }
+
+        assertEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getLower(null))), lup.l)
+        assertEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getUpper(null))), lup.u)
+        assertEquals(EjmlMatrix(SimpleMatrix(ludecompositionF64.getRowPivot(null))), lup.p)
+    }
+
+    private object SomeFeature : MatrixFeature {}
+
+    @Test
+    fun suggestFeature() {
+        assertNotNull(EjmlMatrix(randomMatrix).suggestFeature(SomeFeature).getFeature<SomeFeature>())
+    }
+
+    @Test
+    fun get() {
+        val m = randomMatrix
+        assertEquals(m[0, 0], EjmlMatrix(m)[0, 0])
+    }
+
+    @Test
+    fun origin() {
+        val m = randomMatrix
+        assertSame(m, EjmlMatrix(m).origin)
+    }
+}

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

@@ -0,0 +1,47 @@
+package kscience.kmath.ejml
+
+import org.ejml.simple.SimpleMatrix
+import kotlin.random.Random
+import kotlin.random.asJavaRandom
+import kotlin.test.Test
+import kotlin.test.assertEquals
+import kotlin.test.assertSame
+
+internal class EjmlVectorTest {
+    private val random = Random(0)
+
+    private val randomMatrix: SimpleMatrix
+        get() = SimpleMatrix.random_DDRM(random.nextInt(2, 100), 1, 0.0, 10.0, random.asJavaRandom())
+
+    @Test
+    fun size() {
+        val m = randomMatrix
+        val w = EjmlVector(m)
+        assertEquals(m.numRows(), w.size)
+    }
+
+    @Test
+    fun get() {
+        val m = randomMatrix
+        val w = EjmlVector(m)
+        assertEquals(m[0, 0], w[0])
+    }
+
+    @Test
+    fun iterator() {
+        val m = randomMatrix
+        val w = EjmlVector(m)
+
+        assertEquals(
+            m.iterator(true, 0, 0, m.numRows() - 1, 0).asSequence().toList(),
+            w.iterator().asSequence().toList()
+        )
+    }
+
+    @Test
+    fun origin() {
+        val m = randomMatrix
+        val w = EjmlVector(m)
+        assertSame(m, w.origin)
+    }
+}