[Numpy-discussion] Re: Is a Python function a gufunc if it broadcasts its arguments appropriately?

[Jim Pivarski via NumPy-Discussion]

I think you're right: the function `stack`, as you've defined it, is a
gufunc.

Here's an implementation using np.vectorize

(rather than nb.vectorize
). Since the
signature is not "()->()" or "(),()->()" (or similar with a different
number of scalar inputs and scalar outputs), it's a generalized ufunc.

>>> def stack(a, b):

... broadcasts = np.broadcast_arrays(a, b)

... return np.stack(broadcasts, axis=-1)

...

>>> stacky = np.vectorize(stack, signature="(),()->(2)")

>>> stacky(np.arange(5), np.arange(5))

array([[0, 0],

   [1, 1],

   [2, 2],

   [3, 3],

   [4, 4]])

>>> stacky(np.arange(5), np.array([[1], [2], [3], [4], [5]]))

array([[[0, 1],

[1, 1],

[2, 1],

[3, 1],

[4, 1]],


   [[0, 2],

[1, 2],

[2, 2],

[3, 2],

[4, 2]],


   [[0, 3],

[1, 3],

[2, 3],

[3, 3],

[4, 3]],


   [[0, 4],

[1, 4],

[2, 4],

[3, 4],

[4, 4]],


   [[0, 5],

[1, 5],

[2, 5],

[3, 5],

[4, 5]]])



On Tue, Dec 31, 2024 at 2:44 AM john.a.dawson--- via NumPy-Discussion <
numpy-discussion@python.org> wrote:

> Is the function `stack` above a gufunc?
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[Numpy-discussion] Re: Is a Python function a gufunc if it broadcasts its arguments appropriately?

[john.a.dawson--- via NumPy-Discussion]

Is the function `stack` above a gufunc?
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