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?
>>> arr = numpy.array(((2,2),(2,-2))) >>> tuple(map(tuple, arr)) ((2, 2), (2, -2))
tuple(arr)FindOutIslamNow 2019-02-05 11:46
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))
type(a)==numpy.ndarray- Mike 2012-04-05 15:36
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)) (1, 2, 3, 4, 5, 6)
I don't know if it's quicker, but it looks more effective ;)
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.