title: Cholesky implementation in python - Solve Ax=b
body: <p>I'm using Cholesky decomposition for <code>Ax=b</code>  to find <code>x</code> , by doing <code>L*LT=A</code> then <code>y=L*b</code> and in the end <code>x=LT*b</code>.When I check though I don't seem to get the same results as doing the classic <code>Ax=b</code> . 
  Here's my code :</p>
  
  <pre><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)
  </code></pre>