@ -197,14 +197,13 @@ def Arnoldi(A, v, m):
beta = norm(v)
v = v/beta
h = sp.sparse.lil_matrix((m,m))
for j in range(m):
w = A @ v
for i in range(j):
tmp = v.T @ w
h[i,j] = tmp[0,0]
w = w - h[i,j]*v
h[j,j-1] = norm(w)
h[j,j-1] = norm(w) # in the paper the index is referred as h[j+1,j] but since python starts from 0 it's h[j,j-1]
if h[j,j-1] == 0:
print("Arnoldi breakdown")