[Neuroimaging] FA images Was: Nipy.org new website needs a complete remake
Ariel Rokem
arokem at gmail.com
Mon Aug 3 23:01:59 CEST 2015
Yeah, I'm also -1 on flask.
Seems like you would have to build from scratch a static webpage generator
out of a system that really isn't meant to be a static webpage generator,
while never needing/using what flask is actually for.
My preference in order:
* Jekyll - the tool built specifically for serving up github pages. That's
basically the negative of the above argument against flask. In contrast to
all the other options, this provides continuous integration for building
the webpages. Requires zero installation to contribute.
* Pelican - also up to the job, but requires that someone build the website
locally on their machine every time a change is made. Requires people learn
a new system (at least those that aren't already building their own blogs
with this), but hey, at least it's written in Python.
* Sphinx - has the advantage that it's already being used by all the
projects in the eco-system. The advantage of familiarity is balanced by
general finickiness, that we have all grown to tolerate. Also, I am not
sure what we'd need to do to create a mobile-responsive website, while both
Pelican and Jekyll do that out of the box.
In my opinion the best solution would be a Jekyll-backed webpage with the
layout and design of the page that Vanessa created.
Cheers,
Ariel
On Mon, Aug 3, 2015 at 10:14 AM, Gael Varoquaux <
gael.varoquaux at normalesup.org> wrote:
> -1 on flask: it's twisting something that not been built for this
> purpose.
>
> My votes in order of preference (note that my opinion doesn't matter
> much, as I won't be doing the work):
>
> * sphinx: every package of the nipy constellation already uses it
> * pelican: I have a great experience with it (using purecss that's much
> lighter than bootstrap, check my personnal website out)
> * jekyll: seems reasonnably easy to use, but will require most people to
> learn a new development ecosystem
> * flask: great project to serve dynamic websites, but not designed for
> static.
>
> Gael
>
> On Mon, Aug 03, 2015 at 06:38:05AM -0700, vanessa sochat wrote:
> > My .02 on flask:
>
> > The extra step is "freezing." The workflow to push an update will always
> be
> > something along the lines of:
>
> > - checkout or clone current flask site
> > - do changes
> > - freeze
> > - push to gh-pages
>
> > This seems do-able to me, but I sense that others aren't happy about the
> extra
> > step, and I am open to the idea that other frameworks could do it better,
> > perhaps at the cost of the more "interactive" back end allowed by flask.
> At the
> > end of the day, it doesn't really matter so much as long as updating /
> adding
> > content is relatively straight forward and pain free. Looking forward to
> more
> > discussion on this.
>
> > On Mon, Aug 3, 2015 at 6:33 AM, vanessa sochat <vsochat at stanford.edu>
> wrote:
>
> > This week we should perhaps vote/decide on a final framework to port
> the
> > nipy site into? I'm open to giving a go at whatever the group thinks
> is
> > best :)
>
> > On Mon, Aug 3, 2015 at 6:11 AM, Ariel Rokem <arokem at gmail.com>
> wrote:
>
>
> > On Wed, Jul 29, 2015 at 8:38 PM, David Moreno-Dominguez <
> > d.mor.dom at gmail.com> wrote:
>
> > Doesnt Dipy already do this? (be open source and compute FA
> images
> > [and much more] from any dwi dataset)
>
>
> > Absolutely - I was being ironic.
>
> > But I will admit that irony doesn't travel well by email.
> >
>
> > On Wed, Jul 29, 2015 at 8:06 PM, Ariel Rokem <
> arokem at gmail.com>
> > wrote:
>
> > > On Mon, Jul 27, 2015 at 10:44 AM, Gael Varoquaux
> > > <gael.varoquaux at normalesup.org> wrote:
>
> > >> On Mon, Jul 27, 2015 at 08:56:08AM -0700, Ariel Rokem
> wrote:
> > >> > PS: Vanessa: Nilearn is not only for fMRI. It's for
> > statistical
> > >> > analysis
> > >> > of images. It is also used for anatomical images:
> > >> > http://nilearn.github.io/auto_examples/decoding/
> > plot_oasis_vbm.html
> > >> > If we could get a preprocessed, openly downloadable
> set of
> > images of
> > >> > eg
> > >> > FA, we would do an example with diffusion too.
>
> > >> > Completely off-topic, but I can't resist: if only there
> was an
> > >> > open-source project that computed FA images from freely
> > available
> > >> > diffusion MRI data-sets!
>
> > >> Well, you're welcome to help us with preprocessing and
> pitching
> > a
> > >> relevant prediction problem from this data. I know
> nothing about
> > >> diffusion and nothing about the datasets you are talking
> about.
> > In my
> > >> experience, writing a relevant example requires
> understanding
> > the data
> > >> and the questions. If you, or someone else, gets us to
> the point
> > where
> > >> there is a set of nifti images of FA with condition A and
> > condition B,
> > >> and helps us write the story, than we have an example.
>
>
> > > Hmm. Interesting idea. I am looking around for something
> along
> > these lines.
> > > I think that there are some freely available data-sets
> that are
> > already
> > > preprocessed, so could be used in this way. Let me think
> about
> > how to go
> > > about this.
>
>
> > >> Gaël
> > >> _______________________________________________
> > >> Neuroimaging mailing list
> > >> Neuroimaging at python.org
> > >> https://mail.python.org/mailman/listinfo/neuroimaging
>
>
>
> > > _______________________________________________
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>
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>
>
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> --
> Gael Varoquaux
> Researcher, INRIA Parietal
> NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France
> Phone: ++ 33-1-69-08-79-68
> http://gael-varoquaux.info http://twitter.com/GaelVaroquaux
> _______________________________________________
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>
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