On Sat, Mar 3, 2012 at 8:07 AM, Luis Pedro Coelho <l...@cmu.edu> wrote: > Hi, > > I sort of missed the big C++ discussion, but I'd like to give some examples of > how writing code can become much simpler if you are based on C++. This is from > my mahotas package, which has a thin C++ wrapper around numpy's C API > > https://github.com/luispedro/mahotas/blob/master/mahotas/_morph.cpp > > and it implements multi-type greyscale erosion. > > > // numpy::aligned_array wraps PyArrayObject* > template<typename T> > void erode(numpy::aligned_array<T> res, > numpy::aligned_array<T> array, > numpy::aligned_array<T> Bc) { > > > // Release the GIL using RAII > gil_release nogil; > const int N = res.size(); > typename numpy::aligned_array<T>::iterator iter = array.begin(); > // this is adapted from scipy.ndimage. > // it implements the convolution-like filtering. > filter_iterator<T> filter(res.raw_array(), > > Bc.raw_array(), > > EXTEND_NEAREST, > > is_bool(T())); > const int N2 = filter.size(); > T* rpos = res.data(); > > for (int i = 0; i != N; ++i, ++rpos, filter.iterate_both(iter)) { > T value = std::numeric_limits<T>::max(); > for (int j = 0; j != N2; ++j) { > T arr_val = T(); > filter.retrieve(iter, j, arr_val); > value = std::min<T>(value, erode_sub(arr_val, filter[j])); > } > *rpos = value; > } > } > > If you compare this with the equivalent scipy.ndimage function, which is very > good C code (but mostly write-only—in fact, ndimage has not been maintainable > because it is so hard [at least for me, I've tried]):
The fact that this is good C is matter of opinon :) I don't think the code is comparable either - some of the stuff done in the C code is done in the C++ code your are calling. The C code could be significantly improved. Even more important here: almost none of this code should be written anymore anyway, C++ or not. This is really the kind of code that should be done in cython, as it is mostly about wrapping C code into the python C API. cheers, David _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
