[Python] Gauss-Jordan Elimination in python

I am working on code to do Gauss-Jordan elimination in python. My directions are as follows:

def gauss_jordan(A):
for each row k do
i* <- argmax_{k<i<n} |A_{ik}|
if A_{i*k} = 0 then
Matrix is not invertible
end if
Swap rows k and i*
for each row j below k (i.e. j = k + 1,...,n) do
f = A_{jk}/A_{kk}
Aj = Aj - fA_{k}
end for
end for
for each row k = n,..., 1 (i.e. in reverse) do
A_{k} = A_{k}=A_{kk}
for each row j above k (i.e. j = k -1,..., 1) do
f = A_{jk}/A_{kk}
Aj = A_{j}-fA_{k}
end for
end for


So far I have:

def gauss_jordan(A):
(h, w) = (len(A), len(A[0]))
for y in range(0,h):
for pivot in range(y, h):
if A[pivot][y].value % 2 != 0:
break
else:
return None


Is this the correct start? I feel quite lost in where to go next. The input will be a Numpy array. Any thoughts are much appreciated!

Continue reading...