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?
5 Answers
>>> arr = numpy.array(((2,2),(2,-2)))
>>> tuple(map(tuple, arr))
((2, 2), (2, -2))
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))
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 ;)
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
