如何返回数组c到Python？ [英] How to return an C array to Python?
问题描述
我写道，被称为被Python一个Python / C扩展功能，如何可以返回二维数组INT [] []到Python？
静态的PyObject * inference_function（*的PyObject自我，*的PyObject参数）
{
*的PyObject doc_lst;
INT K，V;
双α，β;
INT n_iter; 如果（PyArg_ParseTuple（参数Oiiddi，＆安培;！doc_lst，＆安培; K，和放大器; V，＆安培;α，和放大器;测试版，和放大器; n_iter））
{
的printf（传入参数错误\\ n！）;
返回NULL;
} 返回Py_BuildValue（I，1）;
}
什么样的阵列您使用的是？一种方式，我觉得方便，使用numpy的数组，并在地方修改数据。 numpy的已经有很多关于操纵整型数组很大的操作，所以这是如果你想添加一些额外的功能得心应手。
第1步：将您的C扩展到numpy的
在Windows上，这是一样的东西。
的#includeC：\\ Python34 /库/站点包/ numpy的/核心/有/ numpy的/ arrayobject.h
在OSX上它的东西像
的#include \"/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/numpy/core/include/numpy/arrayobject.h\"
第二步：抢指针数据这是非常容易的。
为int * my_data_to_modify;
如果（PyArg_ParseTuple（参数，O，＆安培; numpy_tmp_array））{
/ *指向我们的数据到numpy的像素阵列中的数据* /
my_data_to_modify =（INT *）numpy_tmp_array-＆GT;数据;
}... / *做有趣的事情与您的数据* /
2D numpy的数组用C
当你使用数据以这种方式工作，你可以分配它作为一个二维数组，例如
np.random.randint（0，100，（100,2））
或全部为零，如果你想有一个空白的石板
不过，所有的C在乎的是连续的数据，这意味着你可以遍历它由一个行的lenght并修改它，仿佛它是一个二维数组
例如，如果你传递颜色RGB格式，例如，它们的100x3数组，你会考虑
INT NUM_COLORS = numpy_tmp_array2-＆GT;尺寸[0]; / *这给你列的长度* /
INT band_size = numpy_tmp_array2-＆GT;尺寸[1]; / *这给你行的长度* /对于（i = 0; I＆LT; NUM_COLORS * band_size; I + = band_size）{
R = my_data [I]
G = my_data第[i + 1];
B = my_data第[i + 2];
}
要修改数据的地方，只是改变了数据阵列中的一个值。在Python的一面，numpy的阵列将有更改的值。
I wrote a Python/C extension function that was called by Python, How can return an 2d array int[][] to Python?
static PyObject* inference_function(PyObject *self, PyObject *args)
{
PyObject* doc_lst;
int K,V;
double alpha,beta;
int n_iter;
if (!PyArg_ParseTuple(args, "Oiiddi", &doc_lst, &K,&V, &alpha,&beta,&n_iter))
{
printf("传入参数错误！\n");
return NULL;
}
return Py_BuildValue("i", 1);
}
What kind of array are you using? One way, which I find convenient, is to use numpy arrays, and modify the data in place. Numpy already has a lot of great operations for manipulating integer arrays, so this is handy if you're trying to add some additional functionality.
Step 1: link your C extension to numpy
on windows, this is something like
#include "C:\Python34/Lib/site-packages/numpy/core/include/numpy/arrayobject.h"
on osx it's something like
#include "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/numpy/core/include/numpy/arrayobject.h"
Step 2: grab the pointer to the data. This is surprisingly easy
int* my_data_to_modify;
if (PyArg_ParseTuple(args, "O", &numpy_tmp_array)){
/* Point our data to the data in the numpy pixel array */
my_data_to_modify = (int*) numpy_tmp_array->data;
}
... /* do interesting things with your data */
2D numpy array in C
When you work with data this way, you can allocate it as a 2d array, e.g.
np.random.randint( 0, 100, (100,2) )
or all zeros if you want a blank slate
But all C cares about is contiguous data, which means you can loop through it by the lenght of a "row" and modify it as if it were a 2D array
for example, if you were passing in colors in rgb form, e.g., a 100x3 array of them, you would consider
int num_colors = numpy_tmp_array2->dimensions[0]; /* This gives you the column length */
int band_size = numpy_tmp_array2->dimensions[1]; /* This gives you the row length */
for ( i=0; i < num_colors * band_size; i += band_size ){
r = my_data[i];
g = my_data[i+1];
b = my_data[i+2];
}
To modify the data in place, just change a value in the data array. On the Python side, the numpy array will have the changed value.
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