alberane
diff --git a/‎ArithmeticAnalysis/LUdecomposition.py‎
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+import math
+import numpy
+
+def LUDecompose (table): #table that contains our data
+    #table has to be a square array so we need to check first
+    rows,columns=numpy.shape(table)
+    L=numpy.zeros((rows,columns))
+    U=numpy.zeros((rows,columns))
+    if rows!=columns:
+        return
+    for i in range (columns):
+        for j in range(i-1):
+            sum=0
+            for k in range (j-1):
+                sum+=L[i][k]*U[k][j]
+            L[i][j]=(table[i][j]-sum)/U[j][j]
+        L[i][i]=1
+        for j in range(i-1,columns):
+            sum1=0
+            for k in range(i-1):
+                sum1+=L[i][k]*U[k][j]
+            U[i][j]=table[i][j]-sum1
+    return L,U
+
+
+
+
+
+
+
+matrix =numpy.array([[2,-2,1],[0,1,2],[5,3,1]])
+L,U = LUDecompose(matrix)
+print(L)
+print(U)