Hallo! > E.g. in my algorithm I can have a very big internal matrix in C++ (say > 700 MB - in fortran style). Now I want to have this matrix in numpy to > plot some parts of it, get some data out of it ... whatever - if I again > allocate an array of the same size, I am out of memory. > Therefore I simply used the PyArray_FromDimsAndData() function to > allocate the array. > > > > This is why you use INPLACE typemaps that will NOT copy your data. [...] > Are you sure ? Because the original object is not modified, so it is > still the same data.
Hm ... lets consider the same example as before (one 700MB matrix in C++). If I want to get this data with an INPLACE typemap I again have to allocate an 700 MB array in python, then passing it to my C++ library which puts in the data of it - so in the end I have to use two times 700 MB matrices ? (or maybe I don't understand something ;) ?) > If what you want is to provide a view from your C++ matrix, this is > different. You must either : > - propose the array interface > - use a Python object inside your C++ matrix (this is to be done, I've a > basic example in my blog) Yes, maybe thats what I need. Do you have a link to that blog ? LG GEorg _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
