[SciPy-Dev] GSoC 2014 : Discrete Wavelets Transform

Tue Mar 18 05:36:06 EDT 2014

Hi Ralf,

> On Tue, Mar 18, 2014 at 2:05 AM, Ankit Agrawal <aaaagrawal at gmail.com>wrote:
>>
>>> Hi everyone,
>>>
>>>         I apologize for not responding fast enough as I was consumed by
>>> some assignment deadlines until today.
>>>
>>>         The draft of my proposal is ready and can be found here<https://github.com/scipy/scipy/wiki/GSoC-2014-:-Discrete-Wavelet-Transform-(draft)>.
>>> Please review it. Any suggestions for changes/improvements are welcome.
>>> Thanks.
>>>
>>> @Ralf and Stefan : Does the timeline and the chronological order of
>>> tasks seem good to you?
>>>
>>
> The order of tasks looks sensible. I would expand the descriptions in some
> cases a little bit.
>
> For integration into scipy you could say what the tasks are (I expect
> adding code and making it build is very quick, adding docs and a small
> tutorial may be part of this task).
>
For 1d/2d SWT one week should be enough I think. There are Python
> implementations already posted on the PyWavelets list, moving those to
> C/Cython and testing them should be doable fairly quickly.
>

I found Mike Marino's code on 1d ISWT on the Pywavelets list. I would now
prefer to put this week long task after the mid-term evaluation in
conjunction with Sureshrink and compression algorithms and pre-pone the 2
week task of putting a private copy of _pywt in scikit-image
 and modifying @thearn's PR containing Bayeshrink and Visushrink before the
mid-term evaluation. Let me know your opinion on this.

For image compression algorithm I'd expect more details on which ones
> exactly. Maybe worth discussing on the scikit-image list what they'd like
> to see. JPEG 2000 isn't in the Matlab toolbox you linked but may be a good
> candidate. I think the patent issues with JPEG are history.
>
There was a scikit-image thread about compression active about a month ago
in the context of GSoC. I will discuss about the algorithms that would be
preferred and update here.

> You made two more PRs in the meantime, I'd link those as well. And please
> remind me if I haven't reviewed/merged your changes to the thresholding
> functions before the deadline.
>

I have already linked them below the timeline. I will better move them up(I
am not sure you meant linking the closed PR relating to stats.f_oneway
here?). Thanks a lot for the feedback.

Cheers,
> Ralf
>
>
>
>>>
>>> Regards,
>>> Ankit Agrawal,
>>> Communication and Signal Processing,
>>> IIT Bombay.
>>>
>>>
>>> On Sat, Mar 15, 2014 at 9:37 PM, Ralf Gommers <ralf.gommers at gmail.com>wrote:
>>>
>>>>
>>>>
>>>>
>>>> On Thu, Mar 13, 2014 at 6:49 PM, Ankit Agrawal <aaaagrawal at gmail.com>wrote:
>>>>
>>>>>
>>>>> On Wed, Mar 12, 2014 at 5:27 AM, Skipper Seabold <jsseabold at gmail.com>wrote:
>>>>>
>>>>>> On Tue, Mar 11, 2014 at 6:22 PM, Ankit Agrawal <aaaagrawal at gmail.com>
>>>>>> wrote:
>>>>>> > Hi everyone,
>>>>>> >
>>>>>> >          I have created a page on wiki to list the possible tasks
>>>>>> that can
>>>>>> > go along with the project idea of integrating `pywt` library in
>>>>>> scipy.signal
>>>>>> > and addition of some related algorithms(denoising and compression
>>>>>> using
>>>>>> > wavelets) to scikit-image and scipy.signal. Please feel free to
>>>>>> suggest or
>>>>>> > add any other related task. In the coming 2-3 days, I will go
>>>>>> through some
>>>>>> > papers and the pywt codebase to come up with better estimates of
>>>>>> the time in
>>>>>> > which I can complete those tasks. By the end of coming
>>>>>> weekend(16th), I hope
>>>>>> > to have shortlisted the tasks and the timeline for my GSoC
>>>>>> proposal. Thanks.
>>>>>> >
>>>>>>
>>>>>> Hi Ankit,
>>>>>>
>>>>>> I wrote up a blog post on using pywt for doing wavelet regression a
>>>>>> while back. There are some suggestions at the bottom for things I
>>>>>> found difficult and could easily be improved
>>>>>
>>>>>
>>>> Would be useful to get more suggestions like this. Because the API is
>>>> more or less fixed after one release, ideas that improve that API should be
>>>> prioritized I think. So far I've kept compatibility with upstream so that
>>>> it would be easy to contribute back, but it's now clear that upstream is
>>>> dead.
>>>>
>>>> Some things that need changing or a closer look:
>>>> - the thresholding functions cannot keep their current names. Probably
>>>> should be a single function instead of four.
>>>> - the tuple of tuples of approximation coefficients returned by
>>>> dwt/swt/wavedec functions is ugly. Some container class with a few useful
>>>> methods would be nicer.
>>>> - the very different approach in the dwt/swt versus the wavelet packets
>>>> is quite odd.
>>>> - also some renaming is in order: `MODES` is not PEP8 compliant, `qmf`
>>>> is already used in scipy.signal, `families` is too generic,
>>>> upcoef/downcoef/scal2frq/orthfilt are not very informative.
>>>>
>>>> Ralf
>>>>
>>>>
>>>>
>>>>
>>>>>  like making pywt a little
>>>>>> more consistently object-oriented to save some keystrokes.
>>>>>>
>>>>>
>>>>> Hi Skipper,
>>>>>
>>>>>          Great blog post. What are your suggestions for some objects
>>>>> that could be introduced? For instance in your blog post example, you hint
>>>>> of a wavelet object that holds the coefficient arrays returned from
>>>>> `wavedec`, so that it could be passed to threshold functions. If I
>>>>> understand your use case correctly, won't this be a bit less generic in
>>>>> cases where you want only a subset of coefficient arrays to be thresholded?
>>>>>
>>>>>
>>>>>> Feel free to use any of this example code as well, if you think it
>>>>>> could find a home somewhere.
>>>>>>
>>>>>
>>>>> The example could find a home in tutorial section. Thanks.
>>>>>
>>>>> http://jseabold.net/blog/2012/02/23/wavelet-regression-in-python/
>>>>>>
>>>>>> Skipper
>>>>>> _______________________________________________
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>>>>>> http://mail.scipy.org/mailman/listinfo/scipy-dev
>>>>>>
>>>>>
>>>>>
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>>>>
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>>>
>>
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