如何将 scipy.sparse CSR 矩阵正确传递给 cython 函数? [英] How to properly pass a scipy.sparse CSR matrix to a cython function?

问题描述

我需要将 scipy.sparse CSR 矩阵传递给 cython 函数.如何指定类型，就像 numpy 数组一样?

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?

推荐答案

这里有一个例子，说明如何使用 row 属性快速访问 coo_matrix 中的数据，col 和 data.该示例的目的只是展示如何声明数据类型和创建缓冲区(还添加编译器指令，这通常会给您带来相当大的提升)...

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]

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