## itertools to numpy array

Question

I would like to use itertools' various functions to create numpy arrays. I can easily compute ahead of time the number of elements in the product, combinations, permutations, etc, so allotting space shouldn't be a problemo.

e.g.

``````coords = [[1,2,3],[4,5,6]]
iterable = itertools.product(*coords)
shape = (len(coords[0]), len(coords[1]))
arr = np.iterable_to_array(
iterable,
shape=shape,
dtype=np.float64,
count=shape[0]*shape[1]
) #not a real thing
[1,4],[1,5],[1,6],
[2,4],[2,5],[2,6],
[3,4],[3,5],[3,6]])
``````

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## Answers to itertools to numpy array ( 1 )

1. Here are several numpy ways of generating an array with these values

``````In [469]: coords = [[1,2,3],[4,5,6]]
In [470]: it = itertools.product(*coords)
In [471]: arr = np.array(list(it))
In [472]: arr
Out[472]:
array([[1, 4],
[1, 5],
[1, 6],
[2, 4],
[2, 5],
[2, 6],
[3, 4],
[3, 5],
[3, 6]])
``````

`fromiter` will work with an appropriate structured `dtype`:

``````In [473]: it = itertools.product(*coords)
In [474]: arr = np.fromiter(it, dtype='i,i')
In [475]: arr
Out[475]:
array([(1, 4), (1, 5), (1, 6), (2, 4), (2, 5), (2, 6), (3, 4), (3, 5),
(3, 6)],
dtype=[('f0', '<i4'), ('f1', '<i4')])
``````

But usually we use the tools that `numpy` provides for generating sequences and meshes. `np.arange` is used all over the place.

`meshgrid` is widely used. With a bit of trial and error I found that I could transpose its output, and produce the same sequence:

``````In [481]: np.transpose(np.meshgrid(coords[0], coords[1], indexing='ij'), (1,2,0)).reshape(-1,2)
Out[481]:
array([[1, 4],
[1, 5],
[1, 6],
[2, 4],
[2, 5],
[2, 6],
[3, 4],
[3, 5],
[3, 6]])
``````

`repeat` and `tile` also useful for tasks like this:

``````In [487]: np.column_stack((np.repeat(coords[0],3), np.tile(coords[1],3)))
Out[487]:
array([[1, 4],
[1, 5],
[1, 6],
[2, 4],
[2, 5],
[2, 6],
[3, 4],
[3, 5],
[3, 6]])
``````

I've done some timings on `fromiter` in the past. My memory is that it offers only a modest time savings over `np.array`.

A while back I explored `itertools` and `fromiter`, and found a way to combine them using`itertools.chain`

convert itertools array into numpy array

``````In [499]: it = itertools.product(*coords)
In [500]: arr = np.fromiter(itertools.chain(*it),int).reshape(-1,2)
In [501]: arr
Out[501]:
array([[1, 4],
[1, 5],
[1, 6],
[2, 4],
[2, 5],
[2, 6],
[3, 4],
[3, 5],
[3, 6]])
``````