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Caution about rolling ball performance #7424
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And suggest alternatives for when something faster is desired.
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Added suggestions to follow numpydoc referencing syntax, but otherwise LGTM! Thanks @ctrueden!
Co-authored-by: Juan Nunez-Iglesias <jni@fastmail.com>
Co-authored-by: Juan Nunez-Iglesias <jni@fastmail.com>
Co-authored-by: Stefan van der Walt <sjvdwalt@gmail.com>
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Co-authored-by: Marianne Corvellec <marianne.corvellec@ens-lyon.org>
Co-authored-by: Marianne Corvellec <marianne.corvellec@ens-lyon.org>
I'm worried about linting so I'm not pressing merge. But lets try to not have this linger too long, there seems to be strong agreement that this should be merged! I think we can all agree with small one character additions to aid with grammar! Thank you @ctrueden |
Thanks all! Please let me know if there is anything else you would like done on my side to move this forward. |
Description
This patch adds detail to the
skimage.restoration.rolling_ball
docstring, cautioning about the algorithm performance and suggesting alternatives for when something faster is desired.As discussed in #7423, the rolling ball algorithm complexity is such that larger radii and/or images with higher dimensionality can take quite some time to compute. Let's give the user some guidance about this so they can make informed decisions about how to proceed with their image processing.
Release note
For maintainers and optionally contributors, please refer to the instructions on how to document this PR for the release notes.