Mailman 3 May 2013 - scikit-image

numexpr
by Johannes Schönberger May 20, 2013

May 20, 2013

Hi everyone, I have just come to know the 'numexpr' package and could speed up some of my personnel projects relatively easy. I think, this could also improve performance of some functions in skimage. What's your opinion on adding this as a new dependency? Regards, Johannes Schönberger

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Re: ENH: improved, faster algorithm for array padding
by Chintak Sheth May 20, 2013

May 20, 2013

Cheers Josh! On May 20, 2013 3:27 PM, "Stéfan van der Walt" <stefan(a)sun.ac.za> wrote: > Kudos to Josh Warner for getting this patch into NumPy so quickly! > > ---------- Forwarded message ---------- > From: GitHub > Date: Sun, May 19, 2013 at 9:50 PM > Subject: [Numpy-svn] [numpy/numpy] 246c06: ENH: improved, faster > algorithm for array padding > > Branch: refs/heads/master > Home: https://github.com/numpy/numpy > Commit: 246c06d2475718ec36ba193494444464e497c69a > > https://github.com/numpy/numpy/commit/246c06d2475718ec36ba193494444464e497c… > Author: Josh Warner (Mac) <warner.joshua(a)mayo.edu> > Date: 2013-05-19 (Sun, 19 May 2013) > > Changed paths: > M doc/release/1.8.0-notes.rst > M numpy/lib/arraypad.py > M numpy/lib/tests/test_arraypad.py > > Log Message: > ----------- > ENH: improved, faster algorithm for array padding > > New padding method which scales much better with dimensionality. > This new implementation is fully vectorized, builds each abstracted > n-dimensional padding block in a single step, and takes advantage > of separability. The API is completely preserved, and the old > algorithm is used if a vector function is input for `mode`. > > The new algorithm is faster for all tested combinations of inputs, > and scales much better with dimensionality. Execution time reductions > from ~25% for small rank 1 arrays to >99% for rank 4+ arrays observed. > > > Commit: 7d188bf1c9ac5bf7ee41e0794d59771802b345bf > > https://github.com/numpy/numpy/commit/7d188bf1c9ac5bf7ee41e0794d59771802b34… > Author: Charles Harris <charlesr.harris(a)gmail.com> > Date: 2013-05-19 (Sun, 19 May 2013) > > Changed paths: > M doc/release/1.8.0-notes.rst > M numpy/lib/arraypad.py > M numpy/lib/tests/test_arraypad.py > > Log Message: > ----------- > Merge pull request #3329 from JDWarner/faster_arraypad > > ENH: improved, faster algorithm for array padding > > > Compare: > https://github.com/numpy/numpy/compare/5b28d185a494...7d188bf1c9ac > > -- > You received this message because you are subscribed to the Google Groups > "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. > > >

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ENH: improved, faster algorithm for array padding
by Stéfan van der Walt May 20, 2013

May 20, 2013

Kudos to Josh Warner for getting this patch into NumPy so quickly! ---------- Forwarded message ---------- From: GitHub Date: Sun, May 19, 2013 at 9:50 PM Subject: [Numpy-svn] [numpy/numpy] 246c06: ENH: improved, faster algorithm for array padding Branch: refs/heads/master Home: https://github.com/numpy/numpy Commit: 246c06d2475718ec36ba193494444464e497c69a https://github.com/numpy/numpy/commit/246c06d2475718ec36ba193494444464e497c… Author: Josh Warner (Mac) <warner.joshua(a)mayo.edu> Date: 2013-05-19 (Sun, 19 May 2013) Changed paths: M doc/release/1.8.0-notes.rst M numpy/lib/arraypad.py M numpy/lib/tests/test_arraypad.py Log Message: ----------- ENH: improved, faster algorithm for array padding New padding method which scales much better with dimensionality. This new implementation is fully vectorized, builds each abstracted n-dimensional padding block in a single step, and takes advantage of separability. The API is completely preserved, and the old algorithm is used if a vector function is input for `mode`. The new algorithm is faster for all tested combinations of inputs, and scales much better with dimensionality. Execution time reductions from ~25% for small rank 1 arrays to >99% for rank 4+ arrays observed. Commit: 7d188bf1c9ac5bf7ee41e0794d59771802b345bf https://github.com/numpy/numpy/commit/7d188bf1c9ac5bf7ee41e0794d59771802b34… Author: Charles Harris <charlesr.harris(a)gmail.com> Date: 2013-05-19 (Sun, 19 May 2013) Changed paths: M doc/release/1.8.0-notes.rst M numpy/lib/arraypad.py M numpy/lib/tests/test_arraypad.py Log Message: ----------- Merge pull request #3329 from JDWarner/faster_arraypad ENH: improved, faster algorithm for array padding Compare: https://github.com/numpy/numpy/compare/5b28d185a494...7d188bf1c9ac

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Re:
by Johannes Schönberger May 19, 2013

May 19, 2013

Thanks, that was me… but it actually was fun for me ;-) Johannes Schönberger Am 19.05.2013 um 09:16 schrieb Ronnie Ghose <ronnie.ghose(a)gmail.com>: > that's a possibility, let me try that :D. also props for whoever made the _geometric.py, that doesn't look fun o-o. > > > On Sun, May 19, 2013 at 2:36 AM, Johannes Schönberger <jschoenberger(a)demuc.de> wrote: > I have only implemented it for 2D but a PR to add functionality for 1D arrays is highly welcome ;-) > > Von: scikit-image(a)googlegroups.com [scikit-image(a)googlegroups.com]" im Auftrag von "Ronnie Ghose [ronnie.ghose(a)gmail.com] > Gesendet: Sonntag, 19. Mai 2013 08:23 > An: scikit-image(a)googlegroups.com > Betreff: > > the transform.resize function does not work for 1-d arrays as it expects a (#,#) instead of (#,) .. should this be changed or is this as intended? > > Thanks, > Ronnie > > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. > > > > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. > > > > > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. > >

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Re:
by Ronnie Ghose May 19, 2013

May 19, 2013

also what do you think about using Bento to build the files? On Sun, May 19, 2013 at 3:16 AM, Ronnie Ghose <ronnie.ghose(a)gmail.com>wrote: > that's a possibility, let me try that :D. also props for whoever made the > _geometric.py, that doesn't look fun o-o. > > > On Sun, May 19, 2013 at 2:36 AM, Johannes Schönberger < > jschoenberger(a)demuc.de> wrote: > >> I have only implemented it for 2D but a PR to add functionality for 1D >> arrays is highly welcome ;-) >> >> ------------------------------ >> *Von:* scikit-image(a)googlegroups.com [scikit-image(a)googlegroups.com]" im >> Auftrag von "Ronnie Ghose [ronnie.ghose(a)gmail.com] >> *Gesendet:* Sonntag, 19. Mai 2013 08:23 >> *An:* scikit-image(a)googlegroups.com >> *Betreff:* >> >> the transform.resize function does not work for 1-d arrays as it >> expects a (#,#) instead of (#,) .. should this be changed or is this as >> intended? >> >> Thanks, >> Ronnie >> >> -- >> You received this message because you are subscribed to the Google Groups >> "scikit-image" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to scikit-image+unsubscribe(a)googlegroups.com. >> For more options, visit https://groups.google.com/groups/opt_out. >> >> >> >> -- >> You received this message because you are subscribed to the Google Groups >> "scikit-image" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to scikit-image+unsubscribe(a)googlegroups.com. >> For more options, visit https://groups.google.com/groups/opt_out. >> >> >> > >

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Re:
by Ronnie Ghose May 19, 2013

May 19, 2013

that's a possibility, let me try that :D. also props for whoever made the _geometric.py, that doesn't look fun o-o. On Sun, May 19, 2013 at 2:36 AM, Johannes Schönberger < jschoenberger(a)demuc.de> wrote: > I have only implemented it for 2D but a PR to add functionality for 1D > arrays is highly welcome ;-) > > ------------------------------ > *Von:* scikit-image(a)googlegroups.com [scikit-image(a)googlegroups.com]" im > Auftrag von "Ronnie Ghose [ronnie.ghose(a)gmail.com] > *Gesendet:* Sonntag, 19. Mai 2013 08:23 > *An:* scikit-image(a)googlegroups.com > *Betreff:* > > the transform.resize function does not work for 1-d arrays as it > expects a (#,#) instead of (#,) .. should this be changed or is this as > intended? > > Thanks, > Ronnie > > -- > You received this message because you are subscribed to the Google Groups > "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. > > > > -- > You received this message because you are subscribed to the Google Groups > "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. > > >

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Re: Convex Hull Object function
by Josh Warner May 19, 2013

May 19, 2013

Hi Chintak, It appears Matlab does it your way, combining with OR (with a toggle for 4- or 8-connected neighborhood to identify connected components). I'm not convinced this is the best way, since the convex hulls of separate objects can easily overlap. This is a challenging problem. To do this truly correctly you need the ability for each voxel to belong to more than one object, or to return a separate array for each individual connected component. Either of these is possible. Bit depth is probably the limiting factor in the first case (64 or 128 unique objects max), while memory is probably going to become problematic for the second. On the other hand, we could leave it alone, accept your current implementation, and make these Matlab-like limitations clear to the user in the docstring. If they care about potential overlap, they can always use the original `convex_hull_image` repeatedly on each label. This is probably the best way forward from the perspective of user expectations. Josh On Saturday, May 18, 2013 4:16:18 AM UTC-5, Chintak Sheth wrote: > > Hi everyone, > > Its been a while since my last correspondence. I had my exams and then > went for a small trip with family. > > So I was working on adding a convex_hull_object function to skimage. I had > earlier written code for this, but now I've incorporated certain changes in > convex_hull.py as pointed out by you'll. > https://github.com/chintak/scikit-image/tree/convex_hull/skimage/morphology > > I am using label() to generate a mask for extracting the different > connected components and then adding up all the separate convex hull's of > different objects. However, I was wondering if there is a better way of > combining the different hulls as opposed to just logical ADD. > > Any thoughts ? > > Chintak >

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AW:
by Johannes Schönberger May 19, 2013

May 19, 2013

I have only implemented it for 2D but a PR to add functionality for 1D arrays is highly welcome ;-) ________________________________ Von: scikit-image(a)googlegroups.com [scikit-image(a)googlegroups.com]" im Auftrag von "Ronnie Ghose [ronnie.ghose(a)gmail.com] Gesendet: Sonntag, 19. Mai 2013 08:23 An: scikit-image(a)googlegroups.com Betreff: the transform.resize function does not work for 1-d arrays as it expects a (#,#) instead of (#,) .. should this be changed or is this as intended? Thanks, Ronnie -- You received this message because you are subscribed to the Google Groups "scikit-image" group. To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. For more options, visit https://groups.google.com/groups/opt_out.

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(no subject)
by Ronnie Ghose May 19, 2013

May 19, 2013

the transform.resize function does not work for 1-d arrays as it expects a (#,#) instead of (#,) .. should this be changed or is this as intended? Thanks, Ronnie

1 0

Convex Hull Object function
by Chintak Sheth May 18, 2013

May 18, 2013

Hi everyone, Its been a while since my last correspondence. I had my exams and then went for a small trip with family. So I was working on adding a convex_hull_object function to skimage. I had earlier written code for this, but now I've incorporated certain changes in convex_hull.py as pointed out by you'll. https://github.com/chintak/scikit-image/tree/convex_hull/skimage/morphology I am using label() to generate a mask for extracting the different connected components and then adding up all the separate convex hull's of different objects. However, I was wondering if there is a better way of combining the different hulls as opposed to just logical ADD. Any thoughts ? Chintak

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