kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt

@@ -167,6 +167,18 @@ internal class TestDoubleLinearOpsTensorAlgebra {
         testSVDFor(fromArray(intArrayOf(2, 2), doubleArrayOf(-1.0, 0.0, 239.0, 238.0)))
     }
 
+//    @Test
+//    fun testSVDError() = DoubleTensorAlgebra{
+//       val buffer = doubleArrayOf(
+//            1.000000, 2.000000, 3.000000,
+//            2.000000, 3.000000, 4.000000,
+//            3.000000, 4.000000, 5.000000,
+//            4.000000, 5.000000, 6.000000,
+//            5.000000, 6.000000, 7.000000
+//        )
+//        testSVDFor(fromArray(intArrayOf(5, 3), buffer))
+//    }
+
     @Test
     fun testBatchedSVD() = DoubleTensorAlgebra {
         val tensor = randomNormal(intArrayOf(2, 5, 3), 0)
@@ -189,6 +201,28 @@ internal class TestDoubleLinearOpsTensorAlgebra {
         testSVDGolabKahanFor(fromArray(intArrayOf(5, 3), buffer))
     }
 
+//    @Test
+//    fun testSVDGolabKahanError() = DoubleTensorAlgebra{
+//        val buffer = doubleArrayOf(
+//            1.0, 2.0, 3.0, 2.0, 3.0,
+//            4.0, 3.0, 4.0, 5.0, 4.0,
+//            5.0, 6.0, 5.0, 6.0, 7.0
+//        )
+//        testSVDGolabKahanFor(fromArray(intArrayOf(3, 5), buffer))
+//    }
+
+    @Test
+    fun testSVDGolabKahanBig() = DoubleTensorAlgebra{
+        val tensor = DoubleTensorAlgebra.randomNormal(intArrayOf(100, 100, 100), 0)
+        testSVDGolabKahanFor(tensor)
+    }
+
+    @Test
+    fun testSVDBig() = DoubleTensorAlgebra{
+        val tensor = DoubleTensorAlgebra.randomNormal(intArrayOf(100, 100, 100), 0)
+        testSVDFor(tensor)
+    }
+
     @Test
     fun testBatchedSVDGolabKahan() = DoubleTensorAlgebra{
         val tensor = randomNormal(intArrayOf(2, 5, 3), 0)