I have a cythonized function that I call a bunch of times in my code. The cython version and the original python code give me the same answers (to the extent 1e-7that, as I understand it, are related to the types of cython and python ... not a question here, but may be important).
I am trying to find the root of a function using scipy.optimize.fsolve(). The python version works fine, but the cython version diverges.
The code is pretty involved and has a large external file to prepare some arguments, so I cannot publish everything. I am posting cython code. Full code here .
def euler_outside(float b_prime, int index_b,
np.ndarray[np.double_t, ndim=1] b_grid, int index_y,
np.ndarray[np.double_t, ndim=1] y_grid,
np.ndarray[np.double_t, ndim=1] y_vec,
np.ndarray[np.double_t, ndim=2] pol_mat_b, float q,
np.ndarray[np.double_t, ndim=2] pol_mat_q,
np.ndarray[np.double_t, ndim=2] P, float beta,
int n_ygrid, int check=0):
'''
b_prime - the variable of interest. want to find b_prime that solves this
function
'''
cdef double b, y, c, uc, e_ucp, eul_val
cdef int i
cdef np.ndarray[np.float64_t, ndim=1] uct, c_prime = np.zeros((n_ygrid,))
b = b_grid[index_b]
y = y_grid[index_y]
c = b + y - b_prime/q
if check:
c_prime = b_prime + y_vec - b_grid[0]/q
else:
for i in range(n_ygrid):
c_prime[i] = (b_prime + y_vec[i] -
(np.interp(b_prime, b_grid, pol_mat_b[:,i]) /
np.interp(b_prime, b_grid, pol_mat_q[:,i])))
if c<0:
return 1e10
uc = utility_prime(c)
uct = utility_prime(c_prime)
e_ucp = np.inner( uct, P[index_y,:] )
eul_val = uc - beta*q * e_ucp
return eul_val
python , cdef . , , . , scipy fsolve , . , cython?
python 2.7 Anaconda. pyximport.