Hallo! > OK, so the key here is the *internal* matrix. I think you need to > provide a way to extract that matrix from the C++ application as a numpy > array. Then you can provide it to your function/method as an INPLACE > array. No new memory will be allocated. [...] > The INPLACE typemaps force you to provide the allocated memory. If you > do it by accessing whatever your C++ app has already allocated, you > should be fine.
Hm ... I still don't understand that ... With INPLACE I have to allocate the numpy array before, then pass it to my getMyMatrix(my_inplace_numarray) method, then copy the data in that method to the my_inplace_numarray - right ? But I am still not convinced by the INPLACE method - the more natural way for me is to simply return the matrix ... Maybe the most usefull way would be to add also OUT_WITHOUTCOPY macros to numpy.i, where the data is allocated with PyArray_FromDimsAndData() ? (as a "long term" goal ...) >> Hm ... maybe this is a misunderstanding ? - I mean with 2D output a two >> dimensional numpy array (simply a matrix). >> In numpy2carray.i the macros are called ARRAY2_OUT and FARRAY2_OUT. > > I guess my assumption was that in the general case you would want to > retain the dimensions as input arguments, since it is logical for ARGOUT > typemaps to allocate new memory. Since swig typemaps only allow > numinputs=0 or numinputs=1, this was problematic. I guess the user > could provide a sequence (tuple or list) as the single argument . . . > don't know why I didn't think of that before. Again I do not see the problem - see e.g. ARRAY2_OUT_COPY in numpy2carray.i, shouldn't this be the same ? > Yes, it shouldn't be too hard. And I like your FARRAY notation for the > interface. So your experience is that the flags and strides are all > that have to be set differently? Yes, so far I had no crash ... ;) The only thing to do is the following: -------8<----------- PyArrayObject *tmp = (PyArrayObject*)obj; tmp->flags = NPY_FARRAY; int s = tmp->strides[1]; tmp->strides[0] = s; tmp->strides[1] = s * dim0[0]; -------8<----------- LG Georg _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
