[Mne_analysis] GSoC Idea, Improving decode module

Asish Panda asishrocks95 at gmail.com
Tue Mar 15 01:50:22 EDT 2016
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On Mon, Mar 14, 2016 at 7:21 PM, Denis-Alexander Engemann <
denis.engemann at gmail.com> wrote:

> Looks also good to me.
>
> At the same time it's ambitions, which is great! We should, however, see
> what are the most important goals such that the rest can be seen as nice to
> have additions but won't determine your overall GSOC success.
> One tiny remark: we should not go use pickling for persistence for several
> reasons. Short: it's not made for long-lived persistence and will break. We
> will rather look into something like saving the estimator attributes and
> their constructor parameters into hd5 files and re-instantiate the objects
> based on this information.
> We might need a hangoug or skype together to decide about the priorities
> of all the elements you listed.
>
I agree. We should have priorities sorted out. When would be a good idea to
have a hangout? I am usually free after 10pm, +5:30GMT.

>
> --Denis
>
>
>
>
> On Mon, Mar 14, 2016 at 2:40 PM JR KING <jeanremi.king at gmail.com> wrote:
>
>> Thanks Asish.
>>
>> It's good overall. I added some corrections.
>>
> Thank you for your help! :)

>
>> Hope that helps,
>>
>> JR
>>
>> On 14 March 2016 at 03:38, Asish Panda <asishrocks95 at gmail.com> wrote:
>>
>>> Hello everyone
>>>
>>> Thank you for explaining me the details. Based on that and the original
>>> idea I have drafted an initial proposal. Please give me your reviews and
>>> let me know if I am understanding your points correctly. You can check out
>>> the
>>> project details section in the wiki page
>>> <https://github.com/kaichogami/mne-python/wiki/GSoC-Proposal#project-detail>
>>> .
>>>
>>> Thank you
>>> Asish Panda
>>>
>>> On Fri, Mar 11, 2016 at 6:06 AM, Phillip Alday <
>>> Phillip.Alday at unisa.edu.au> wrote:
>>>
>>>> Hi guys,
>>>>
>>>> PyMVPA might be a good place to look for inspiration and maybe
>>>> integration: http://www.pymvpa.org/
>>>>
>>>> They have a really nice workflow and API.
>>>>
>>>> Best,
>>>> Phillip
>>>>
>>>>
>>>> > On 11 Mar 2016, at 08:57, JR KING <jeanremi.king at gmail.com> wrote:
>>>> >
>>>> > Hi Asish,
>>>> >
>>>> > As Denis said, the decoding module is one possible target. Just FYI,
>>>> there are other possibilities too: e.g. across-subjects stats and viz isn't
>>>> really well developed/documented.
>>>> >
>>>> > Currently the decoding classes have been developed separately, by
>>>> different authors and with different architectures. IMO, one great goal
>>>> would thus be to
>>>> >
>>>> > 1. (hard) homogenize the existing functions so that they all become
>>>> strictly compatible with sklearn (i.e, based on BaseEstimator_, using fit,
>>>> transform, predict and score methods).
>>>> >
>>>> > 2. (medium-hard): develop transformer objects that would ultimately
>>>> allow the users to pipe multiple processing steps: e.g. we typically aim at
>>>> getting:
>>>> > make_pipeline(TimeFreq(), InverseTransform(), DataVectorizer(),
>>>> LogisticRegression())
>>>> > or
>>>> > make_pipeline(Filter(10, 30), Covariances(method='shrunk'),
>>>> Xdawn(n_components=4), TangentSpace(), SVM(kernel='linear'))
>>>> >
>>>> > for which all the steps could be typically initialized with inst.info
>>>> and would take an X and a y to be fitted/predicted/scored.
>>>> >
>>>> > 3. (easy) Setup a systematic i/o to store the estimators, the
>>>> predictions and the scores.
>>>> >
>>>> > As a concrete example, to optimize memory and CPU, the GAT currently
>>>> stores the predictions (y_pred_) in the object, and the scoring approach is
>>>> performed outside the CV. This storing and scoring isn't following sklearn
>>>> API. Consequently, one cannot use cross_val_score(GAT). Typically
>>>> refactoring this kind of feature requires some deep thinking because,
>>>> unlike sklearn, several decoding module are applied in a "mass
>>>> multivariate" way: i.e. many multivariate models are fitted on
>>>> independent/partially common/or even identical data. Optimizing memory and
>>>> CPU is thus probably the main challenge here.
>>>> >
>>>> > I would consequently start by tackling the easy/medium problem first
>>>> (e.g. i/o in all decoding classes, vizualizing the fitted weights/patterns
>>>> for each decoding method), and see how we can develop some transformers,
>>>> such as EpochVectorizer, that would be common across decoding modules to
>>>> format.
>>>> >
>>>> > Hope this helps,
>>>> >
>>>> >
>>>> > JR
>>>> >
>>>> >
>>>> > In summary, this project will involve a series of usability
>>>> improvements for the decoding module and extend its functionality.
>>>> > I feel the above statement is quite vague for writing a detailed plan
>>>> in the proposal. Or perhaps the "improvements" can only be known while the
>>>> objectives(listed above) are being fulfilled?
>>>> > Lastly, going a little out of topic, could you now please elaborate
>>>> on how to set up the cleaner framework of the decoding module, that you
>>>> mentioned in the last message?
>>>> >
>>>> > Thank you
>>>> > Asish Panda
>>>> >
>>>> > On Fri, Feb 26, 2016 at 9:50 PM, Asish Panda <asishrocks95 at gmail.com>
>>>> wrote:
>>>> > Hello Jean
>>>> >
>>>> > Thank you very much for your response and the issues. I will get my
>>>> hand dirty right away! :)
>>>> >
>>>> > Thank you
>>>> > Asish Panda
>>>> >
>>>> > On Fri, Feb 26, 2016 at 8:37 PM, JR KING <jeanremi.king at gmail.com>
>>>> wrote:
>>>> > Hi Asish,
>>>> >
>>>> > Thanks for your interest!.
>>>> >
>>>> > You can start with one of these easy PR:
>>>> > https://github.com/mne-tools/mne-python/issues/2874
>>>> > https://github.com/mne-tools/mne-python/issues/2176
>>>> > https://github.com/mne-tools/mne-python/issues/2189 (probably needs
>>>> a bit of discussion)
>>>> >
>>>> > Once you're there I can suggest you some more fun things that you
>>>> could do to set up a cleaner framework for the decoding module.
>>>> >
>>>> > All the best,
>>>> >
>>>> > Jean-Rémi
>>>> >
>>>> > On 26 February 2016 at 09:57, Asish Panda <asishrocks95 at gmail.com>
>>>> wrote:
>>>> > Hello everyone,
>>>> >
>>>> > I am looking forward to participate in GSoC and I am interested in
>>>> the idea of improving the decode module. I have installed and set up the
>>>> development environment and have been trying to get familiar with various
>>>> modules. However being quite new to MEG, EEG I'm looking for some pointers
>>>> to start as well as prerequisites to work on decode module.
>>>> > Lastly I apologize if I have been rude in any manner.
>>>> >
>>>> > Thank you
>>>> > Asish Panda
>>>> >
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