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Golub-Kahan SVD algorithm for KMP tensors #499

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grinisrit wants to merge 64 commits from dev into dev
pull from: dev
merge into: kscience:dev
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kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt
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@ -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)