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DOC: Mention that expand_dims and squeeze are inverses #8737

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DOC: Mention that expand_dims and squeeze are inverses #8737

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18 changes: 17 additions & 1 deletion numpy/core/fromnumeric.py
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Expand Up @@ -1162,14 +1162,30 @@ def squeeze(a, axis=None):
dimensions of length 1 removed. This is always `a` itself
or a view into `a`.

Raises
------
ValueError
If `axis` is not `None`, and an axis being squeezed is not of length 1

See Also
--------
expand_dims : The inverse operation, adding singleton dimensions
reshape : Insert, remove, and combine dimensions, and resize existing ones

Examples
--------
>>> x = np.array([[[0], [1], [2]]])
>>> x.shape
(1, 3, 1)
>>> np.squeeze(x).shape
(3,)
>>> np.squeeze(x, axis=(2,)).shape
>>> np.squeeze(x, axis=0).shape
(3, 1)
>>> np.squeeze(x, axis=1).shape
Traceback (most recent call last):
...
ValueError: cannot select an axis to squeeze out which has size not equal to one
>>> np.squeeze(x, axis=2).shape
(1, 3)

"""
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2 changes: 2 additions & 0 deletions numpy/lib/shape_base.py
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Expand Up @@ -255,6 +255,8 @@ def expand_dims(a, axis):

See Also
--------
squeeze : The inverse operation, removing singleton dimensions
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Maybe, "removes all singleton dimensions".

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What I mean here is that np.squeeze(arr, axis=a) and np.expand_dims(arr, axis=a) are inverses. I guess this only applies to one of the two overloads

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Might also mention reshape in both contexts as it allows adding and removing axis.

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@seberg seberg Mar 5, 2017 •
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I personally like indexing a lot for this both of this too, unless it gets very clunky with counting :. EDIT: Though I guess I admit that for squeezing, indexing does not give the information that there really is only one element.

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@charris: Added comments about reshape

reshape : Insert, remove, and combine dimensions, and resize existing ones
doc.indexing, atleast_1d, atleast_2d, atleast_3d

Examples
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