[FIXED] Cholesky implementation in python - Solve Ax=b

Issue

I'm using Cholesky decomposition for Ax=b to find x , by doing L*LT=A then y=L*b and in the end x=LT*b.When I check though I don't seem to get the same results as doing the classic Ax=b . Here's my code :

import numpy as np
import scipy.linalg as sla

myL=np.linalg.cholesky(A)


#check_x = np.dot(A, b)
#check_x = np.dot(A,b)
check_x = sla.solve(A, b)

#check if the composition was done right
myLT=myL.T.conj() #transpose matrix
Ac=np.dot(myL,myLT) #should give the original matrix A



#y=np.dot(myL,b)
y = sla.solve_triangular(myL, b)

#x=np.dot(myL.T.conj(),y)
x = sla.solve_triangular(myLT, b)

Solution

I was sleepless and tired , I got the last line wrong it actually is

x=np.linalg.solve(myLT, y)

Answered By - KevinWendellCrumb