[Mne_analysis] GSoC Idea, Improving decode module
Denis-Alexander Engemann
denis.engemann at gmail.com
Thu Mar 17 03:24:24 EDT 2016
Hi Ashish
can you check your spam folder? We used the email that appears here on the
mailinglist when you are writing.
Denis
On Thu, Mar 17, 2016 at 7:25 AM Asish Panda <asishrocks95 at gmail.com> wrote:
> Thank you for responding. I am afraid I didn't get any invitation. Could
> you kindly re-send it or perhaps share a link here?
>
>
> Asish Panda
>
> On Thu, Mar 17, 2016 at 2:48 AM, Denis-Alexander Engemann <
> denis.engemann at gmail.com> wrote:
>
>> Hi Ashish,
>>
>> we totally agree with you. With Jean-Rémi we just set up a main project
>> and API proposal. See dropbox paper invitation. Let's start a private
>> discussion over the next days based on that draft.
>>
>> Denis
>>
>>
>>
>> On Wed, Mar 16, 2016 at 8:31 PM Asish Panda <asishrocks95 at gmail.com>
>> wrote:
>>
>>> Hi,
>>>
>>> I have been thinking about the priorities of tasks, and I feel that the
>>> visualization can done after gsoc. As the main aim is to first make
>>> decoding more compatible with scikit-learn, we could also probably shift
>>> i/o task for later.
>>> Let me know what you guys think. We can discuss this here, gitter, or
>>> over hangouts, whichever is more suitable for you guys.
>>>
>>> Thank you
>>>
>>> Asish Panda
>>>
>>> On Tue, Mar 15, 2016 at 11:20 AM, Asish Panda <asishrocks95 at gmail.com>
>>> wrote:
>>>
>>>>
>>>>
>>>> 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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