python - How to properly pass a scipy.sparse CSR matrix to a cython function?

Question

I need to pass a scipy.sparse CSR matrix to a cython function. How do I specify the type, as one would for a numpy array?

Answer 1

Here is an example about how to quickly access the data from a coo_matrix using the properties row, col and data. The purpose of the example is just to show how to declare the data types and create the buffers (also adding the compiler directives that will usually give you a considerable boost)...

#cython: boundscheck=False
#cython: wraparound=False
#cython: cdivision=True
#cython: nonecheck=False

import numpy as np
from scipy.sparse import coo_matrix
cimport numpy as np

ctypedef np.int32_t cINT32
ctypedef np.double_t cDOUBLE

def print_sparse(m):
    cdef np.ndarray[cINT, ndim=1] row, col
    cdef np.ndarray[cDOUBLE, ndim=1] data
    cdef int i
    if not isinstance(m, coo_matrix):
        m = coo_matrix(m)
    row = m.row.astype(np.int32)
    col = m.col.astype(np.int32)
    data = m.data.astype(np.float64)
    for i in range(np.shape(data)[0]):
        print row[i], col[i], data[i]