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.
