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Update docstring for SimilarityTransform. #7194

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Update docstring for SimilarityTransform. #7194

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68657c4
Update docstring for consistency
mkcor Oct 9, 2023
62c19ca
Merge branch 'main' into update-transform-docstring
mkcor Oct 14, 2023
0c49315
Use consistent notation for dimensionality
mkcor Oct 14, 2023
12b6b83
Propagate update to EuclideanTransform docstring
mkcor Oct 14, 2023
8901b8f
Propagate update to ProjectiveTransform docstring
mkcor Oct 14, 2023
e0baa7b
Propagate update to other docstrings
mkcor Oct 14, 2023
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4 changes: 2 additions & 2 deletions skimage/transform/_geometric.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1352,8 +1352,8 @@ class SimilarityTransform(EuclideanTransform):
Rotation angle, clockwise, as radians.
Implemented only for 2D and 3D. For 3D, this is given in ZYX Euler
angles.
translation : (dim,) array_like, optional
x, y[, z] translation parameters. Implemented only for 2D and 3D.
translation : (x, y[, z, ...]) sequence of float, length D, optional
Translation parameters for each axis. Implemented only for 2D and 3D.
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It seems that D (as in "length D") is used to mean n, i.e., the image's number of dimensions. We write "an nD image" so n takes values 2, 3, ... (not D).

I don't mind updating this to "n" or "N". Though I do notice that translation is only supported for 2D and 3D. So the ... should be removed as specifying more than xyz wouldn't work?

params : (dim+1, dim+1) (below) should also be updated according to whatever we agree on here.

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Oh, thanks @lagru.

We can't use N because this already denotes something else (number of points):

scikit-image/skimage/transform/_geometric.py

Line 42 in d6ba6db

points : (N, D) array

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I find D (Dimensionality) to be much clearer than n, particularly when next to N (Number of points)

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@scott-vsi I hear you. Have you scanned the other modules to see which usage would currently dominate? Should we update "nD image" everywhere with "D-dim image?" In a sentence, "nD image" seems much more natural though...

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I agree, nD reads better, although it looks like n-D and N-D are also used pretty commonly (there are actually not that many uses of nD. I could see changing those to n-D or N-D).

skimage is a large package, so I doubt you could ever get complete consensus, but it looks like D dominates for the dimensionality of the image. It is used in skimage._shared.utils.check_nD, skimage.measure._moments.moments_coords, skimage.measure._regionprops_utils.euler_number, and skimage.feature.template.match_template. And that is just from a quick spot check.

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Thanks for looking into this, @scott-vsi! I'll mark this PR as draft, because I realize some discussion is needed before we can move forward.

I could see changing those to n-D or N-D

I would avoid uppercase N because, in addition to number of points #7194 (comment), this notation is also used for number of columns, e.g.:

scikit-image/skimage/transform/_geometric.py

Line 98 in d6ba6db

src : (M, N) array_like


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