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Provide a public method for iradon_filters #4952

Open

hmaarrfk wants to merge 1 commit into scikit-image:master from hmaarrfk:iradon-filter-2020_2

Member

hmaarrfk commented Aug 30, 2020

Description

Continuation of #3099

Not sure why
#4950 was failing.

Checklist

Docstrings for all functions
Gallery example in ./doc/examples (new features only)
Benchmark in ./benchmarks, if your changes aren't covered by an
existing benchmark
Unit tests
Clean style in the spirit of PEP8

For reviewers

Check that the PR title is short, concise, and will make sense 1 year
later.
Check that new functions are imported in corresponding __init__.py.
Check that new features, API changes, and deprecations are mentioned in
doc/release/release_dev.rst.


          Provide a public method for iradon_filters

a9dfed6

rfezzani mentioned this pull request

Calendar of community management #4486

Open

emmanuelle reviewed

skimage/transform/radon_transform.py

  
            f = np.zeros(size)

            f[0] = 0.25

            f[1::2] = -1 / (np.pi * n) ** 2

            f[1::2] = -1 / (np.pi * n[1::2])**2

emmanuelle Sep 12, 2020
Member

was it a bug which you corrected? I don't understand why f is zero on even values of indices, this does not correspond to Kak and Slaney I think.

emmanuelle Sep 12, 2020
Member

ok I took a look at one of the previous PRs and apparently it's not the classical ramp filter which is used here. I'll try to understand better which filter is used here. Did you just make this change for the sake of a clearer syntax or is there a difference?

hmaarrfk Sep 14, 2020
Author Member

I think at the time, the change was introduced for cleaner syntax.

hmaarrfk Sep 14, 2020
Author Member

The "fixes" for the filter performance were merged in a pervious PR.

rfezzani

Member

Your current refactoring of n calculation is different from previous one:

>>> size = 10
>>> n1 = np.arange(0, size / 2 + 1, dtype=np.int)
>>> n2 = np.arange(size / 2 - 1, 0, -1, dtype=np.int)
>>> n = np.concatenate((n1, n2))
>>> n[1::2]  # This PR refactoring
array([1, 3, 5, 3, 1])
>>> np.concatenate((np.arange(1, size / 2 + 1, 2, dtype=np.int),
                    np.arange(size / 2 - 1, 0, -2, dtype=np.int)))  # Previous version
array([1, 3, 5, 4, 2])

I don't know which version is correct, but there is a difference...

Contributor

jni commented Sep 13, 2020

I'm not familiar with these methods but the code looks good to me. I'll let others more familiar with radon review/merge but it'd be good to get this in.

@hmaarrfk could you please elaborate more on the motivation for the PR in the description? When making release notes, it's quite annoying to have to go back 7 links to figure out why this PR was made. (The PR you link to is also described as "continuation of...")

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