feature: checkpoint

1 files changed, 29 insertions, 2 deletions

diff --git a/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala b/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala
index b42ade9..80a1778 100644
--- a/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala
+++ b/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala
@@ -1,5 +1,8 @@
 package com.nsrddyn.fpu
 
+import scala.math._
+import scala.collection.immutable.ListSet
+import scala.collection.mutable.ArrayBuffer
 
 class CholeskyDecomposition {
 
@@ -13,14 +16,38 @@ class CholeskyDecomposition {
    *  Linpack uses the cholesky decomposition
    *  https://www.netlib.org/linpack/
    *
+   *  https://www.geeksforgeeks.org/dsa/cholesky-decomposition-matrix-decomposition/
    *
+   *  The Cholesky decomposition maps matrix A into the product of A = L · LH where L is the lower triangular matrix and LH is the transposed,
+   *  complex conjugate or Hermitian, and therefore of upper triangular form (Fig. 13.6).
+   *  This is true because of the special case of A being a square, conjugate symmetric matrix. 
    */ 
 
-  def choleskyDecomposition(n: Int): Unit =   {
+  def run(matrix: List[List[Int]]): Unit = {
 
-    for (w <- 0 to n) {
+    val n: Int = matrix.size
 
+    // store the lower triangular matrix
+    val lower = Vector[Vector[Int]]()
 
+
+    for (i <- 0 until n)
+    {
+      for (j <- 0 until i)
+        var sum: Double = 0
+
+        if j == i then
+        sum += math.pow(lowerBuffer(i)(j), 2)
+
+        end if 
+        lower(i)(j) = (sqrt(matrix(i)(j))())
+
+        j += 1
     }
+    i += 1
   }
+  
+  def (matrix: Vector[Vector[Int]], index: int, jindex: int ): Int = if j == 1 then return math.pow(matrix(index)(jindex)) else 
+
+
 }