[python] Convert numpy array to tuple

Note: This is asking for the reverse of the usual tuple-to-array conversion.

I have to pass an argument to a (wrapped c++) function as a nested tuple. For example, the following works

X = MyFunction( ((2,2),(2,-2)) )

whereas the following do not

X = MyFunction( numpy.array(((2,2),(2,-2))) )
X = MyFunction( [[2,2],[2,-2]] )

Unfortunately, the argument I would like to use comes to me as a numpy array. That array always has dimensions 2xN for some N, which may be quite large.

Is there an easy way to convert that to a tuple? I know that I could just loop through, creating a new tuple, but would prefer if there's some nice access the numpy array provides.

If it's not possible to do this as nicely as I hope, what's the prettiest way to do it by looping, or whatever?

Here's a function that'll do it:

def totuple(a):
    try:
        return tuple(totuple(i) for i in a)
    except TypeError:
        return a

And an example:

>>> array = numpy.array(((2,2),(2,-2)))
>>> totuple(array)
((2, 2), (2, -2))

Another option

tuple([tuple(row) for row in myarray])

If you are passing NumPy arrays to C++ functions, you may also wish to look at using Cython or SWIG.

If you like long cuts, here is another way tuple(tuple(a_m.tolist()) for a_m in a )

from numpy import array
a = array([[1, 2],
           [3, 4]])
tuple(tuple(a_m.tolist()) for a_m in a )

The output is ((1, 2), (3, 4))

Note just (tuple(a_m.tolist()) for a_m in a ) will give a generator expresssion. Sort of inspired by @norok2's comment to Greg von Winckel's answer

I was not satisfied, so I finally used this:

>>> a=numpy.array([[1,2,3],[4,5,6]])
>>> a
array([[1, 2, 3],
       [4, 5, 6]])

>>> tuple(a.reshape(1, -1)[0])
(1, 2, 3, 4, 5, 6)

I don't know if it's quicker, but it looks more effective ;)