将PyArrayObject数据类型转换为C数组

时间:2011-10-12 17:35:57

标签: python numpy python-c-api

我想在C扩展中使用我的Numpy数组。 在这种情况下,许多示例使用PyArrayObject的结构,

array->data , array->strides[0] , array->strides[1] , ...

如果我想以更熟悉(或更整洁)的方式到达我的数组,以及

之类的索引来获取数据的指针

array[i][j]

我该怎么办呢?我应该转换(bool *)array->数据并使用我创建的C数组吗? (我的元素是bools)

我现在的功能声明是(当然没有完成)

static PyObject *
xor_masking(PyObject *self, PyObject *args)
{

PyObject *input;
PyObject *mask;
PyObject *adjacency;
PyObject *state;
PyArrayObject *arr_mask;
PyArrayObject *arr_adjacency;
PyArrayObject *arr_state;
PyArrayObject *arr_next_state;

double sum;
int counter_node, n_nodes;

/*  PyArg_ParseTuple
 *  checks if from args, the pointers of type "O" can be extracted, and extracts them
 */

if (!PyArg_ParseTuple(args, "OOO:xor_masking_C", &mask, &adjacency, &state))
    return NULL;

/*
 *  The pointer returned by PyArray_ContiguousFromObject is typecasted to
 *  a PyArrayObject Pointer and array is pointed to the same address.
 */

arr_mask = (PyArrayObject *)
PyArray_ContiguousFromObject(mask, PyArray_BOOL, 2, 2);
arr_adjacency = (PyArrayObject *)
PyArray_ContiguousFromObject(adjacency, PyArray_BOOL, 2, 2);
arr_state = (PyArrayObject *)
PyArray_ContiguousFromObject(state, PyArray_BOOL, 2, 2);

if (array == NULL)
    return NULL;

int n_mask_0 = mask->dimensions[0];
int n_mask_1 = mask->dimensions[1];
int n_adjacency_0 = adjacency->dimensions[0];
int n_adjacency_1 = adjacency->dimensions[1];
int n_state_0 = state->dimensions[0];
int n_nodes = n_state_0;
/*
 * if the dimensions don't match, return NULL
 */

bool c_mask[n_nodes][n_nodes];

if (n_mask_0 != n_mask_1 || n_adjacency_0 != n_adjacency_1 ||
n_adjacency_0 != n_mask_0 || n_adjacency_0 != n_adjacency_1) {
    return NULL;
}

/*
 *    The 2D arrays are introduced as follows
 *    array[i][j] = (array->data + i*array->strides[0] + j*array->strides[1])
 */

for (counter_node = 0; i < n_mask; i++){
    *row_start = (array->data + i*array->strides[0]);
}


//Py_DECREF();

//return PyFloat_FromDouble();
}

谢谢!

4 个答案:

答案 0 :(得分:1)

答案 1 :(得分:1)

我不确定这是否能回答你的问题但是,为了在C中获取你的NumPy数据,你可以尝试创建一个迭代器来在C中循环你的数组。它没有给你索引你& #39;在([i] [j]之后)但它涵盖了整个阵列

static PyObject *func1(PyObject *self, PyObject *args) {
    PyArrayObject *X;
    int ndX;
    npy_intp *shapeX;
    NpyIter *iter;
    NpyIter_IterNextFunc *iternext;
    PyArray_Descr *dtype;
    double **dataptr;

    PyArg_ParseTuple(args, "O!", &PyArray_Type, &X);
    ndX = PyArray_NDIM(X);
    shapeX = PyArray_SHAPE(X);
    dtype = PyArray_DescrFromType(NPY_DOUBLE);
    iter = NpyIter_New(X, NPY_ITER_READONLY, NPY_KEEPORDER, NPY_NO_CASTING, dtype);
    iternext = NpyIter_GetIterNext(iter, NULL);
    dataptr = (double **) NpyIter_GetDataPtrArray(iter);
    do {
        cout << **dataptr << endl; //Do something with the data in your array
    } while (iternext(iter));   
    NpyIter_Deallocate(iter);
    return Py_BuildValue(...);
}

答案 2 :(得分:1)

我想你会想看看这个:http://docs.scipy.org/doc/numpy/reference/c-api.array.html

特别是

void* PyArray_GETPTR3(PyObject* obj, <npy_intp> i, <npy_intp> j, <npy_intp> k)
和朋友们。如果API没有提供,David Heffernan会感到惊讶的是这些功能。

答案 3 :(得分:1)

这是所有答案中最脏的,我猜,但是2年前,我最终实现了这样的功能:

只需将其添加到此处即可将其记录下来。如果您正在阅读本文,则应查看其他更好的解决方案。

https://gist.github.com/mehmetalianil/6643299