From 8b48eaa1ede355628074f02502491cc5795e47c3 Mon Sep 17 00:00:00 2001
From: Margarita <lashina.2000@gmail.com>
Date: Wed, 25 May 2022 01:11:22 +0300
Subject: [PATCH] renamed function and changed structure

---
 .../space/kscience/kmath/tensors/margarita.kt | 36 ++++++++-----------
 .../space/kscience/kmath/tensors/svdcmp.kt    | 30 ++++++----------
 2 files changed, 25 insertions(+), 41 deletions(-)

diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/margarita.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/margarita.kt
index 3629b6a47..c376d6d0f 100644
--- a/examples/src/main/kotlin/space/kscience/kmath/tensors/margarita.kt
+++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/margarita.kt
@@ -11,28 +11,9 @@ import space.kscience.kmath.nd.MutableStructure2D
 import space.kscience.kmath.nd.Structure2D
 import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.tensors.core.*
-import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.dot
-import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.mapIndexed
-import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra.zeros
-import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.minus
-import space.kscience.kmath.tensors.core.DoubleTensorAlgebra.Companion.sum
 import space.kscience.kmath.tensors.core.tensorAlgebra
 import kotlin.math.*
 
-fun DoubleArray.fmap(transform: (Double) -> Double): DoubleArray {
-    return this.map(transform).toDoubleArray()
-}
-
-fun scalarProduct(v1: Structure2D<Double>, v2: Structure2D<Double>): Double {
-    return v1.mapIndexed { index, d -> d * v2[index] }.sum()
-}
-
-internal fun diagonal(shape: IntArray, v: Double) : DoubleTensor {
-    val matrix = zeros(shape)
-    return matrix.mapIndexed { index, _ -> if (index.component1() == index.component2()) v else 0.0 }
-}
-
-
 fun MutableStructure2D<Double>.print() {
     val n = this.shape.component1()
     val m = this.shape.component2()
@@ -63,11 +44,22 @@ fun main(): Unit = Double.tensorAlgebra.withBroadcast {
     )
     val tensor = fromArray(shape, buffer).as2D()
     val v = fromArray(intArrayOf(3, 3), buffer2).as2D()
+    val w_shape = intArrayOf(3, 1)
+    var w_buffer = doubleArrayOf(0.000000)
+    for (i in 0 until 3 - 1) {
+        w_buffer += doubleArrayOf(0.000000)
+    }
+    val w = BroadcastDoubleTensorAlgebra.fromArray(w_shape, w_buffer).as2D()
     tensor.print()
-    tensor.svdcmp(v)
-
-
+    var ans = Pair(w, v)
+    tensor.svdGolabKahan(v, w)
 
+    println("u")
+    tensor.print()
+    println("w")
+    w.print()
+    println("v")
+    v.print()
 
 
 }
diff --git a/examples/src/main/kotlin/space/kscience/kmath/tensors/svdcmp.kt b/examples/src/main/kotlin/space/kscience/kmath/tensors/svdcmp.kt
index e7a424d74..8572bdee9 100644
--- a/examples/src/main/kotlin/space/kscience/kmath/tensors/svdcmp.kt
+++ b/examples/src/main/kotlin/space/kscience/kmath/tensors/svdcmp.kt
@@ -1,7 +1,6 @@
 package space.kscience.kmath.tensors
 
 import space.kscience.kmath.nd.*
-import space.kscience.kmath.tensors.core.BroadcastDoubleTensorAlgebra
 import kotlin.math.abs
 import kotlin.math.max
 import kotlin.math.min
@@ -34,10 +33,12 @@ fun SIGN(a: Double, b: Double): Double {
         return -abs(a)
 }
 
-internal fun MutableStructure2D<Double>.svdcmp(v: MutableStructure2D<Double>) {
+// matrix v is not transposed at the output
+
+internal fun MutableStructure2D<Double>.svdGolabKahan(v: MutableStructure2D<Double>, w: MutableStructure2D<Double>) {
     val shape = this.shape
-    val n = shape.component2()
     val m = shape.component1()
+    val n = shape.component2()
     var f = 0.0
     val rv1 = DoubleArray(n)
     var s = 0.0
@@ -45,12 +46,6 @@ internal fun MutableStructure2D<Double>.svdcmp(v: MutableStructure2D<Double>) {
     var anorm = 0.0
     var g = 0.0
     var l = 0
-    val w_shape = intArrayOf(n, 1)
-    var w_buffer = doubleArrayOf(0.000000)
-    for (i in 0 until n - 1) {
-        w_buffer += doubleArrayOf(0.000000)
-    }
-    val w = BroadcastDoubleTensorAlgebra.fromArray(w_shape, w_buffer).as2D()
     for (i in 0 until n) {
         /* left-hand reduction */
         l = i + 1
@@ -212,6 +207,9 @@ internal fun MutableStructure2D<Double>.svdcmp(v: MutableStructure2D<Double>) {
     this[3, 2] = -0.297540
     this[4, 2] = 0.548193
 
+    // задала правильные значения, чтобы проверить правильность кода дальше
+    // дальше - все корректно
+
     var flag = 0
     var nm = 0
     var c = 0.0
@@ -268,9 +266,10 @@ internal fun MutableStructure2D<Double>.svdcmp(v: MutableStructure2D<Double>) {
                 break
             }
 
-            if (its == 30) {
-                return
-            }
+//            надо придумать, что сделать - выкинуть ошибку?
+//            if (its == 30) {
+//                return
+//            }
 
             x = w[l, 0]
             nm = k - 1
@@ -326,11 +325,4 @@ internal fun MutableStructure2D<Double>.svdcmp(v: MutableStructure2D<Double>) {
             w[k, 0] = x
         }
     }
-
-    println("u")
-    this.print()
-    println("w")
-    w.print()
-    println("v")
-    v.print()
 }
\ No newline at end of file