9

我想在 C 扩展中使用我的 Numpy 数组。这种情况下的很多例子都使用了 PyArrayObject 的结构，

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

指针以访问数据，如果我想以我更熟悉（或更整洁）的方式访问我的数组，索引如下

array[i][j]

我应该怎么做？我应该对 (bool *) array->data 进行类型转换并使用我创建的 C 数组吗？（我的元素是布尔值）

我现在的函数声明是（当然还没有完成）

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

4 回答 4

2

我不确定这是否回答了您的问题，但是，要在 C 中获取您的 NumPy 数据，您可以尝试创建一个迭代器来循环您在 C 中的数组。它不会为您提供您所追求的索引（[i] [j]) 但它覆盖了整个数组

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(...);
}
于 2013-09-13T16:38:59.980 回答
1

我猜这是这里所有答案中最脏的，但是 2 年前，我最终实现了这样的功能：

只需在此处添加它以记录它。如果您正在阅读本文，您应该查看其他更好的解决方案。

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

于 2013-09-20T20:33:26.117 回答
1

这应该可以帮助你。

http://mail.scipy.org/pipermail/numpy-discussion/2003-November/014837.html

于 2011-10-12T20:39:16.470 回答
1

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

尤其是，

void* PyArray_GETPTR3(PyObject* obj, <npy_intp> i, <npy_intp> j, <npy_intp> k)

和朋友。如果 API 不提供这些功能，David Heffernan 会感到惊讶。

于 2013-09-14T02:16:21.560 回答