ValueError: ndarray is not C-contiguous in cython

Question

I have written the following function in cython to estimate the log-likelihood

@cython.boundscheck(False) @cython.wraparound(False) def likelihood(double m,                double c,                np.ndarray[np.double_t, ndim=1, mode='c'] r_mpc not None,                np.ndarray[np.double_t, ndim=1, mode='c'] gtan not None,                np.ndarray[np.double_t, ndim=1, mode='c'] gcrs not None,                np.ndarray[np.double_t, ndim=1, mode='c'] shear_err not None,                np.ndarray[np.double_t, ndim=1, mode='c'] beta not None,                double rho_c,                np.ndarray[np.double_t, ndim=1, mode='c'] rho_c_sigma not None):     cdef double rscale = rscaleConstM(m, c,rho_c, 200)      cdef Py_ssize_t ngals = r_mpc.shape[0]      cdef np.ndarray[DTYPE_T, ndim=1, mode='c'] gamma_inf = Sh(r_mpc, c, rscale, rho_c_sigma)     cdef np.ndarray[DTYPE_T, ndim=1, mode='c'] kappa_inf = Kap(r_mpc, c, rscale, rho_c_sigma)       cdef double delta = 0.     cdef double modelg = 0.     cdef double modsig = 0.      cdef Py_ssize_t i     cdef DTYPE_T logProb = 0.       #calculate logprob     for i from ngals > i >= 0:          modelg = (beta[i]*gamma_inf[i] / (1 - beta[i]*kappa_inf[i]))          delta = gtan[i] - modelg          modsig = shear_err[i]          logProb = logProb -.5*(delta/modsig)**2  - logsqrt2pi - log(modsig)       return logProb 

but when I run the compiled version of this function, I get the following error message:

  File "Tools.pyx", line 3, in Tools.likelihood      def likelihood(double m, ValueError: ndarray is not C-contiguous 

I could not quite understand why this problem occurs??!!! I will appreciate to get any useful tips.

Answer 1

Just before you get the error, try printing the flags attribute of the numpy array(s) you're passing to likelihood. You'll probably see something like:

In [2]: foo.flags Out[2]:    C_CONTIGUOUS : False   F_CONTIGUOUS : True   OWNDATA : True   WRITEABLE : True   ALIGNED : True   UPDATEIFCOPY : False 

Note where it says C_CONTIGUOUS : False, because that's the issue. To fix it, simply convert it to C-order:

In [6]: foo = foo.copy(order='C')  In [7]: foo.flags Out[7]:    C_CONTIGUOUS : True   F_CONTIGUOUS : False   OWNDATA : True   WRITEABLE : True   ALIGNED : True   UPDATEIFCOPY : False