How to get my own C++ array class to work with numpy using SWIG and g

Question

I created my own 2D array class in C++ and got it to work with Python using SWIG. I also extended it to have some basic functionality like NumPy arrays. For example, I created a method in my Array2D class, getitem, which returns the elements of the array:

%extend Array2D{
    double __getitem__(vector<int> v) {
        return (*self)[v[0]][v[1]];
    }
}

After compiling the C++ extension using SWIG, I can import this into Python and get an Array2D object:

>>> import myclass
>>> A = myclass.Array2D(2,2,1.0)

which creates a 2x2 matrix of ones. Because of my extension method, I can retrieve individual elements just like with NumPy.

>>> A[0,1]
>>> 1.0

This is great and all, but when I try to use NumPy's mean function, I get the following error:

>>> mean(A)
>>> TypeError: in method 'dblArray2D___getitem__', argument 2 of type 'std::vector< int >'

It seems that NumPy's mean function doesn't know what to do with std::vector. What do I need to do with my getitem method or SWIG interface file to get my Array2D to use NumPy's mean function?

First of all I would suggest to pass v by reference, or even constant reference — user3159253
– user3159253, Commented Apr 20, 2014 at 22:52

Peter Mortensen · Accepted Answer · 2019-08-22 22:00:47Z

1

My guess is that you have to provide an overload of the C++ __getitem__ in your %extend that accepts one int, because mean flattens the array so it probably calls array[i] i.e. with one index, not two.

edited Aug 22, 2019 at 22:00

Peter Mortensen

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answered Apr 22, 2014 at 0:08

Oliver

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1 Comment

Bluegreen17 Over a year ago

I think you're right. I had to get array[i] to return the row vector. Then it all worked!

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