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.
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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