Gram Schmidt process on np.ndarray vectors

gram_schmidt.py

#DISCLAIMER: Gram-Schmidt is numerically unstable. Use np.linalg.qr if you actually need to calculate an orthonormal basis.
def proj(vec,u):
    return np.dot(u,vec)/np.dot(u,u)*u

def gram_schmidt(*vectors):
    retlist=list()
    for vec in vectors:
        vec_calc=np.copy(vec)
        for exist_vec in retlist:
            vec_calc=vec_calc-proj(vec,exist_vec)
        retlist.append(vec_calc)
    return retlist