SciPy 2013

I’m hoping to host a matplotlib sprint during the final two days of
Scipy 2013 this year, and I hope to see as many as possible of you
there. I think it’s also really important to bring new developers
into sprints, because it’s such an efficient way to get people
familiar with the code base.

It might be helpful to start brainstorming now about which projects

we may want to tackle so that we can have as much in place as
possible by then and hit the ground running.

I've set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

Mike

I'm hoping to host a matplotlib sprint during the final two days of Scipy
2013 this year, and I hope to see as many as possible of you there. I
think it's also really important to bring new developers into sprints,
because it's such an efficient way to get people familiar with the code
base.

Being in Europe, it is very unlikely I'll come to Scipy this year, but I
think it is a great idea to organize a sprint during this period.

It might be helpful to start brainstorming now about which projects we may
want to tackle so that we can have as much in place as possible by then and
hit the ground running.

One of the things I think would be great to tackle is the replacement of
the Travis bot. Ideally, I'd like to see a pep8 check of each patch and a
daily build of the documentation on master in addition of the tests.

···

I've set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

Mike

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I’ll also try to set up some sort of remote communication tool (such
as Google Hangouts, or even just IRC) so that people can
“participate” in the sprint remotely.
Agreed. That’s definitely on my todo list. We’ve got some funding
through my employer to pay for continuous integration hosting –
it’s just taking a while to work its way through the system. Once
we have some sort of paid hosting system, we should be able to do a
lot more than Travis currently can.
Mike

···

On 03/22/2013 12:45 PM, Nelle Varoquaux
wrote:

            I'm hoping to host

a matplotlib sprint during the final two days of Scipy
2013 this year, and I hope to see as many as possible of
you there. I think it’s also really important to bring
new developers into sprints, because it’s such an
efficient way to get people familiar with the code base.

          Being in Europe, it is very unlikely I'll come

to Scipy this year, but I think it is a great idea to
organize a sprint during this period.

            It might be helpful

to start brainstorming now about which projects we may
want to tackle so that we can have as much in place as
possible by then and hit the ground running.

          One of the things I think would be great to

tackle is the replacement of the Travis bot. Ideally, I’d
like to see a pep8 check of each patch and a daily build
of the documentation on master in addition of the tests.

            I've set up a wiki page here:



            [https://github.com/matplotlib/matplotlib/wiki/Scipy-2013](https://github.com/matplotlib/matplotlib/wiki/Scipy-2013)



            Mike

          Everyone hates slow websites. So do we.

          Make your web apps faster with AppDynamics

          Download AppDynamics Lite for free today:

          [http://p.sf.net/sfu/appdyn_d2d_mar](http://p.sf.net/sfu/appdyn_d2d_mar)

          _______________________________________________

          Matplotlib-devel mailing list

          Matplotlib-devel@lists.sourceforge.net

          [https://lists.sourceforge.net/lists/listinfo/matplotlib-devel](https://lists.sourceforge.net/lists/listinfo/matplotlib-devel)

  I'm hoping to host a matplotlib sprint during the final two days of

Scipy 2013 this year, and I hope to see as many as possible of you there.
I think it's also really important to bring new developers into sprints,
because it's such an efficient way to get people familiar with the code
base.

Being in Europe, it is very unlikely I'll come to Scipy this year, but I
think it is a great idea to organize a sprint during this period.

I'll also try to set up some sort of remote communication tool (such as
Google Hangouts, or even just IRC) so that people can "participate" in the
sprint remotely.

There's a #matplotlib chanel on irc, where a dozen people hang out. That
could be a nice place to gather people during the sprint.

···

On 22 March 2013 18:06, Michael Droettboom <mdroe@...31...> wrote:

On 03/22/2013 12:45 PM, Nelle Varoquaux wrote:

It might be helpful to start brainstorming now about which projects we
may want to tackle so that we can have as much in place as possible by then
and hit the ground running.

One of the things I think would be great to tackle is the replacement of
the Travis bot. Ideally, I'd like to see a pep8 check of each patch and a
daily build of the documentation on master in addition of the tests.

Agreed. That's definitely on my todo list. We've got some funding
through my employer to pay for continuous integration hosting -- it's just
taking a while to work its way through the system. Once we have some sort
of paid hosting system, we should be able to do a lot more than Travis
currently can.

Mike

I've set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

Mike

------------------------------------------------------------------------------
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I'm hoping to host a matplotlib sprint during the final two days of Scipy
2013 this year, and I hope to see as many as possible of you there. I think
it's also really important to bring new developers into sprints, because
it's such an efficient way to get people familiar with the code base.

Awesome idea. I am for sure in. In fact, I work in Austin now; it'd
be great to actually meet some of you in person. We should share some
breakfast tacos or interior Mexican food!

Being in Europe, it is very unlikely I'll come to Scipy this year, but I
think it is a great idea to organize a sprint during this period.

I'll also try to set up some sort of remote communication tool (such as
Google Hangouts, or even just IRC) so that people can "participate" in the
sprint remotely.

There's a #matplotlib chanel on irc, where a dozen people hang out. That
could be a nice place to gather people during the sprint.

Is this on freenode? I joined it yesterday to scope it out but it was
pretty quiet.

It might be helpful to start brainstorming now about which projects we
may want to tackle so that we can have as much in place as possible by then
and hit the ground running.

One of the things I think would be great to tackle is the replacement of
the Travis bot. Ideally, I'd like to see a pep8 check of each patch and a
daily build of the documentation on master in addition of the tests.

Agreed. That's definitely on my todo list. We've got some funding
through my employer to pay for continuous integration hosting -- it's just
taking a while to work its way through the system. Once we have some sort
of paid hosting system, we should be able to do a lot more than Travis
currently can.

Mike

I've set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

I have edited the Wiki to confirm my attendance.

···

On Fri, Mar 22, 2013 at 12:11 PM, Nelle Varoquaux <nelle.varoquaux@...149...> wrote:

On 22 March 2013 18:06, Michael Droettboom <mdroe@...31...> wrote:

On 03/22/2013 12:45 PM, Nelle Varoquaux wrote:

--
Damon McDougall
http://www.damon-is-a-geek.com
Institute for Computational Engineering Sciences
201 E. 24th St.
Stop C0200
The University of Texas at Austin
Austin, TX 78712-1229

OOI Is anyone planning to run an advanced matplotlib tutorial this year?

I’ve added a few ideas to https://github.com/matplotlib/matplotlib/wiki/Scipy-2013 - some are more advanced than others and would need a bit of planning should we decide to run with them.

···

On 23 March 2013 17:06, Damon McDougall <damon.mcdougall@…149…> wrote:

On Fri, Mar 22, 2013 at 12:11 PM, Nelle Varoquaux

<nelle.varoquaux@…149…> wrote:

On 22 March 2013 18:06, Michael Droettboom <mdroe@…31…> wrote:

On 03/22/2013 12:45 PM, Nelle Varoquaux wrote:

I’m hoping to host a matplotlib sprint during the final two days of Scipy

2013 this year, and I hope to see as many as possible of you there. I think

it’s also really important to bring new developers into sprints, because

it’s such an efficient way to get people familiar with the code base.

Awesome idea. I am for sure in. In fact, I work in Austin now; it’d

be great to actually meet some of you in person. We should share some

breakfast tacos or interior Mexican food!

Being in Europe, it is very unlikely I’ll come to Scipy this year, but I

think it is a great idea to organize a sprint during this period.

I’ll also try to set up some sort of remote communication tool (such as

Google Hangouts, or even just IRC) so that people can “participate” in the

sprint remotely.

There’s a #matplotlib chanel on irc, where a dozen people hang out. That

could be a nice place to gather people during the sprint.

Is this on freenode? I joined it yesterday to scope it out but it was

pretty quiet.

It might be helpful to start brainstorming now about which projects we

may want to tackle so that we can have as much in place as possible by then

and hit the ground running.

One of the things I think would be great to tackle is the replacement of

the Travis bot. Ideally, I’d like to see a pep8 check of each patch and a

daily build of the documentation on master in addition of the tests.

Agreed. That’s definitely on my todo list. We’ve got some funding

through my employer to pay for continuous integration hosting – it’s just

taking a while to work its way through the system. Once we have some sort

of paid hosting system, we should be able to do a lot more than Travis

currently can.

Mike

I’ve set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

I have edited the Wiki to confirm my attendance.

Damon McDougall

http://www.damon-is-a-geek.com

Institute for Computational Engineering Sciences

201 E. 24th St.

Stop C0200

The University of Texas at Austin

Austin, TX 78712-1229


Everyone hates slow websites. So do we.

Make your web apps faster with AppDynamics

Download AppDynamics Lite for free today:

http://p.sf.net/sfu/appdyn_d2d_mar


Matplotlib-devel mailing list

Matplotlib-devel@lists.sourceforge.net

https://lists.sourceforge.net/lists/listinfo/matplotlib-devel

I am putting together a beginners tutorial proposal that I will submit soon, depending on the feedback from the Guinea Pigs— uhm, I mean, coworkers tomorrow.

Ben Root

I am putting together a beginners tutorial proposal that I will submit soon

That’s great to hear! Are you planning on making the tutorial material part of mpl’s docs or using the content that is already out there?

···

On 25 March 2013 16:16, Benjamin Root <ben.root@…553…> wrote:

I am putting together a beginners tutorial proposal that I will submit soon, depending on the feedback from the Guinea Pigs— uhm, I mean, coworkers tomorrow.

Ben Root

It is all new stuff, but I have been taking inspirations from other tutorials I have seen and said to myself “You are all teaching it wrong!” :stuck_out_tongue:

I am ignoring pylab (risky, I know), starting with a very basic NumPy primer, and then moving on to teach matplotlib from the perspective of “here are what the parts of a plot are called and what they are for, and see what happens when we put those parts together”. It is an ingredients approach, essentially.

Hopefully, aspects of it will be useful for the docs when it is finished. I am also hoping that having a ipython notebook version of it will help others to improve it for future conferences (there should always be an intro to matplotlib tutorial at SciPy).

Ben Root

I think there is something to be said for not starting from pylab.
Answering questions on SO, a good chunk of them (by volume) can be
traced back to not understanding the magic that pylab is doing for you
in the background or not even knowing magic is being done for you.
Starting from pylab makes easy stuff trivial, but slightly more
complicated things a much bigger lift to figure out how to do (as
compared to the conceptual difference in how hard they are).

A tutorial that starts from the POV of building the figure out of
parts sounds like a good idea to me. At a minimum, a key with the
different parts of the figure labeled with what family of classes
control them would be great (or if something like that already exists
make it easier to find;))

Tom

···

On Mon, Mar 25, 2013 at 12:03 PM, Benjamin Root <ben.root@...553...> wrote:

On Mon, Mar 25, 2013 at 12:46 PM, Phil Elson <pelson.pub@...149...> wrote:

>I am putting together a beginners tutorial proposal that I will submit
> soon

That's great to hear! Are you planning on making the tutorial material
part of mpl's docs or using the content that is already out there?

It is all new stuff, but I have been taking inspirations from other
tutorials I have seen and said to myself "You are all teaching it wrong!"
:stuck_out_tongue:

I am ignoring pylab (risky, I know), starting with a *very* basic NumPy
primer, and then moving on to teach matplotlib from the perspective of "here
are what the parts of a plot are called and what they are for, and see what
happens when we put those parts together". It is an ingredients approach,
essentially.

Hopefully, aspects of it will be useful for the docs when it is finished. I
am also hoping that having a ipython notebook version of it will help others
to improve it for future conferences (there should always be an intro to
matplotlib tutorial at SciPy).

Ben Root

------------------------------------------------------------------------------
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--
Thomas A Caswell
PhD Candidate University of Chicago
Nagel and Gardel labs
tcaswell@...1038...
jfi.uchicago.edu/~tcaswell
o: 773.702.7204

That seems like a good approach to me. Thanks for doing this. I just
submitted a tutorial, but it assumes people know how to make a line
plot already. Perhaps I should learn from this assumption and
communicate better on this list and garner interest about what people
would like to see a priori.

Thanks for putting this together, Ben. Out of interest, are you
diving straight into the pyplot state machine, or are you taking the
more object oriented approach of setting up the canvas and figure
object explicitly? I use the OO approach all the time, but I only use
the non-interactive backends like Agg and PDF.

On a not-too-orthogonal note, I'd personally like to see a tutorial on
hooking in mpl into other GUI-like applications. Paraview seems to do
this a little, but I'd like to see someone do a soup-to-nuts
walkthrough for it, just because I have no experience doing this; I'm
a terminal hermit.

Best wishes,
Damon

···

On Mon, Mar 25, 2013 at 12:17 PM, Thomas A Caswell <tcaswell@...1038...> wrote:

I think there is something to be said for not starting from pylab.
Answering questions on SO, a good chunk of them (by volume) can be
traced back to not understanding the magic that pylab is doing for you
in the background or not even knowing magic is being done for you.
Starting from pylab makes easy stuff trivial, but slightly more
complicated things a much bigger lift to figure out how to do (as
compared to the conceptual difference in how hard they are).

A tutorial that starts from the POV of building the figure out of
parts sounds like a good idea to me. At a minimum, a key with the
different parts of the figure labeled with what family of classes
control them would be great (or if something like that already exists
make it easier to find;))

Tom

On Mon, Mar 25, 2013 at 12:03 PM, Benjamin Root <ben.root@...553...> wrote:

On Mon, Mar 25, 2013 at 12:46 PM, Phil Elson <pelson.pub@...149...> wrote:

>I am putting together a beginners tutorial proposal that I will submit
> soon

That's great to hear! Are you planning on making the tutorial material
part of mpl's docs or using the content that is already out there?

It is all new stuff, but I have been taking inspirations from other
tutorials I have seen and said to myself "You are all teaching it wrong!"
:stuck_out_tongue:

I am ignoring pylab (risky, I know), starting with a *very* basic NumPy
primer, and then moving on to teach matplotlib from the perspective of "here
are what the parts of a plot are called and what they are for, and see what
happens when we put those parts together". It is an ingredients approach,
essentially.

Hopefully, aspects of it will be useful for the docs when it is finished. I
am also hoping that having a ipython notebook version of it will help others
to improve it for future conferences (there should always be an intro to
matplotlib tutorial at SciPy).

Ben Root

--
Damon McDougall
http://www.damon-is-a-geek.com
Institute for Computational Engineering Sciences
201 E. 24th St.
Stop C0200
The University of Texas at Austin
Austin, TX 78712-1229

One idea I've been using is to show explicitly what's going on in the background when you're using defaults by instantiating all the default settings:

http://www.loria.fr/~rougier/teaching/matplotlib/#using-defaults

versus

http://www.loria.fr/~rougier/teaching/matplotlib/#instantiating-defaults

Nicolas

···

On Mar 25, 2013, at 18:43 , Damon McDougall wrote:

On Mon, Mar 25, 2013 at 12:17 PM, Thomas A Caswell > <tcaswell@...1038...> wrote:

I think there is something to be said for not starting from pylab.
Answering questions on SO, a good chunk of them (by volume) can be
traced back to not understanding the magic that pylab is doing for you
in the background or not even knowing magic is being done for you.
Starting from pylab makes easy stuff trivial, but slightly more
complicated things a much bigger lift to figure out how to do (as
compared to the conceptual difference in how hard they are).

A tutorial that starts from the POV of building the figure out of
parts sounds like a good idea to me. At a minimum, a key with the
different parts of the figure labeled with what family of classes
control them would be great (or if something like that already exists
make it easier to find;))

Tom

On Mon, Mar 25, 2013 at 12:03 PM, Benjamin Root <ben.root@...553...> wrote:

On Mon, Mar 25, 2013 at 12:46 PM, Phil Elson <pelson.pub@...149...> wrote:

I am putting together a beginners tutorial proposal that I will submit
soon

That's great to hear! Are you planning on making the tutorial material
part of mpl's docs or using the content that is already out there?

It is all new stuff, but I have been taking inspirations from other
tutorials I have seen and said to myself "You are all teaching it wrong!"
:stuck_out_tongue:

I am ignoring pylab (risky, I know), starting with a *very* basic NumPy
primer, and then moving on to teach matplotlib from the perspective of "here
are what the parts of a plot are called and what they are for, and see what
happens when we put those parts together". It is an ingredients approach,
essentially.

Hopefully, aspects of it will be useful for the docs when it is finished. I
am also hoping that having a ipython notebook version of it will help others
to improve it for future conferences (there should always be an intro to
matplotlib tutorial at SciPy).

Ben Root

That seems like a good approach to me. Thanks for doing this. I just
submitted a tutorial, but it assumes people know how to make a line
plot already. Perhaps I should learn from this assumption and
communicate better on this list and garner interest about what people
would like to see a priori.

Thanks for putting this together, Ben. Out of interest, are you
diving straight into the pyplot state machine, or are you taking the
more object oriented approach of setting up the canvas and figure
object explicitly? I use the OO approach all the time, but I only use
the non-interactive backends like Agg and PDF.

On a not-too-orthogonal note, I'd personally like to see a tutorial on
hooking in mpl into other GUI-like applications. Paraview seems to do
this a little, but I'd like to see someone do a soup-to-nuts
walkthrough for it, just because I have no experience doing this; I'm
a terminal hermit.

Best wishes,
Damon

--
Damon McDougall
http://www.damon-is-a-geek.com
Institute for Computational Engineering Sciences
201 E. 24th St.
Stop C0200
The University of Texas at Austin
Austin, TX 78712-1229

------------------------------------------------------------------------------
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These are fantastic slides. It would be great to include them in some form for a replacement for some parts of the docs that are getting a little long in the tooth.

I particularly like the reference section -- we have some of that in the main docs, but not enough. I think as Nelle Varaquoax and others are moving forward on the documentation reorganization, some of those figures, such as the marker style reference, would make fantastic additions.

Mike

···

On 03/25/2013 02:21 PM, Nicolas Rougier wrote:

One idea I've been using is to show explicitly what's going on in the background when you're using defaults by instantiating all the default settings:

http://www.loria.fr/~rougier/teaching/matplotlib/#using-defaults

versus

http://www.loria.fr/~rougier/teaching/matplotlib/#instantiating-defaults

Nicolas

On Mar 25, 2013, at 18:43 , Damon McDougall wrote:

On Mon, Mar 25, 2013 at 12:17 PM, Thomas A Caswell >> <tcaswell@...1038...> wrote:

I think there is something to be said for not starting from pylab.
Answering questions on SO, a good chunk of them (by volume) can be
traced back to not understanding the magic that pylab is doing for you
in the background or not even knowing magic is being done for you.
Starting from pylab makes easy stuff trivial, but slightly more
complicated things a much bigger lift to figure out how to do (as
compared to the conceptual difference in how hard they are).

A tutorial that starts from the POV of building the figure out of
parts sounds like a good idea to me. At a minimum, a key with the
different parts of the figure labeled with what family of classes
control them would be great (or if something like that already exists
make it easier to find;))

Tom

On Mon, Mar 25, 2013 at 12:03 PM, Benjamin Root <ben.root@...553...> wrote:

On Mon, Mar 25, 2013 at 12:46 PM, Phil Elson <pelson.pub@...149...> wrote:

I am putting together a beginners tutorial proposal that I will submit
soon

That's great to hear! Are you planning on making the tutorial material
part of mpl's docs or using the content that is already out there?

It is all new stuff, but I have been taking inspirations from other
tutorials I have seen and said to myself "You are all teaching it wrong!"
:stuck_out_tongue:

I am ignoring pylab (risky, I know), starting with a *very* basic NumPy
primer, and then moving on to teach matplotlib from the perspective of "here
are what the parts of a plot are called and what they are for, and see what
happens when we put those parts together". It is an ingredients approach,
essentially.

Hopefully, aspects of it will be useful for the docs when it is finished. I
am also hoping that having a ipython notebook version of it will help others
to improve it for future conferences (there should always be an intro to
matplotlib tutorial at SciPy).

Ben Root

That seems like a good approach to me. Thanks for doing this. I just
submitted a tutorial, but it assumes people know how to make a line
plot already. Perhaps I should learn from this assumption and
communicate better on this list and garner interest about what people
would like to see a priori.

Thanks for putting this together, Ben. Out of interest, are you
diving straight into the pyplot state machine, or are you taking the
more object oriented approach of setting up the canvas and figure
object explicitly? I use the OO approach all the time, but I only use
the non-interactive backends like Agg and PDF.

On a not-too-orthogonal note, I'd personally like to see a tutorial on
hooking in mpl into other GUI-like applications. Paraview seems to do
this a little, but I'd like to see someone do a soup-to-nuts
walkthrough for it, just because I have no experience doing this; I'm
a terminal hermit.

Best wishes,
Damon

--
Damon McDougall
http://www.damon-is-a-geek.com
Institute for Computational Engineering Sciences
201 E. 24th St.
Stop C0200
The University of Texas at Austin
Austin, TX 78712-1229

------------------------------------------------------------------------------
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Download AppDynamics Lite for free today:
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Benjamin Root writes:
>
> >I am putting together a beginners tutorial proposal that I will submit
> soon
>
> That's great to hear! Are you planning on making the tutorial material
> part of mpl's docs or using the content that is already out there?
>
> It is all new stuff, but I have been taking inspirations from other tutorials
> I have seen and said to myself "You are all teaching it wrong!" :stuck_out_tongue:
>
> I am ignoring pylab (risky, I know), starting with a *very* basic NumPy
> primer, and then moving on to teach matplotlib from the perspective of "here
> are what the parts of a plot are called and what they are for, and see what
> happens when we put those parts together". It is an ingredients approach,
> essentially.

Just for the record: over the last few years I have assembled a
document which is more a collection of facts and tricks on
Numpy/Scipy/Matplotlib which seems orthogonal to your goals. I am
trying to get students in numerical analysis or similar courses
operational as quickly as possible. So I am taking pylab as a
baseline. (So really a Matlab replacement, although most students
will not have had any close contact with Matlab...)

Any comments are welcome. Some more nice matplotlib examples are on
my wish list, but I have not found time yet...

PDF: http://math.jacobs-university.de/oliver/teaching/numpy-intro/numpy-intro.pdf
HTML: http://math.jacobs-university.de/oliver/teaching/numpy-intro/numpy-intro/index.html
Sources: http://math.jacobs-university.de/oliver/teaching/numpy-intro/

I have been argued back and forth with myself whether I should make it
more pythonic (as most of the "official" matplotlib examples are), but
then on the ground where class time is precious, I came to appreciate
the simplicity of pylab-style code.

Regards,
Marcel

···

On Mon, Mar 25, 2013 at 12:46 PM, Phil Elson <pelson.pub@...149...> wrote:

---------------------------------------------------------------------
Marcel Oliver Phone: +49-421-200-3212
School of Engineering and Science Fax: +49-421-200-3103
Jacobs University m.oliver@...1105...
Campus Ring 1 oliver@...1106...
28759 Bremen, Germany http://math.jacobs-university.de/oliver
---------------------------------------------------------------------

Getting a bit back on the original topic of the SciPy sprints, there are some things I have learned from last year’s sprints. First off, there are going to be a lot of newbies there who do not even have a developer setup, let alone a source install of matplotlib. Myself and a few other people spent several hours fumbling around with getting the Mac users set up properly. With me not being a Mac user, I felt very helpless. We need to be better prepared for these users (as well as the Windows users).

Second, working on matplotlib isn’t very “sexy” (at least, insofar as working on ipython, or one of the scikits). Most of the attendees are specialized scientists who only cares enough about matplotlib to produce “the plot” for their work. Getting attendees to join your sprint is a hard sell. This is not meant to discourage you, but rather to help better frame what the tasks and goals should be for matplotlib at the sprints.

I wish I was this prepared last year. You are off to a much better start than I was.

Cheers!
Ben Root

···

On Fri, Mar 22, 2013 at 12:35 PM, Michael Droettboom <mdroe@…31…> wrote:

I'm hoping to host a matplotlib sprint during the final two days of

Scipy 2013 this year, and I hope to see as many as possible of you
there. I think it’s also really important to bring new developers
into sprints, because it’s such an efficient way to get people
familiar with the code base.

It might be helpful to start brainstorming now about which projects

we may want to tackle so that we can have as much in place as
possible by then and hit the ground running.

I've set up a wiki page here:




[https://github.com/matplotlib/matplotlib/wiki/Scipy-2013](https://github.com/matplotlib/matplotlib/wiki/Scipy-2013)

Ben,

This is incredibly useful information. I have never been to a sprint
before so this valuable knowledge to have. Since I'm a mac user,
perhaps I could put together a 'source install walkthrough' or
something? That might help us save some time fumbling at the
beginning of the sprint.

···

On Tue, Mar 26, 2013 at 8:25 AM, Benjamin Root <ben.root@...553...> wrote:

On Fri, Mar 22, 2013 at 12:35 PM, Michael Droettboom <mdroe@...31...> > wrote:

I'm hoping to host a matplotlib sprint during the final two days of Scipy
2013 this year, and I hope to see as many as possible of you there. I think
it's also really important to bring new developers into sprints, because
it's such an efficient way to get people familiar with the code base.

It might be helpful to start brainstorming now about which projects we may
want to tackle so that we can have as much in place as possible by then and
hit the ground running.

I've set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

Getting a bit back on the original topic of the SciPy sprints, there are
some things I have learned from last year's sprints. First off, there are
going to be a lot of newbies there who do not even have a developer setup,
let alone a source install of matplotlib. Myself and a few other people
spent several hours fumbling around with getting the Mac users set up
properly. With me not being a Mac user, I felt very helpless. We need to
be better prepared for these users (as well as the Windows users).

Second, working on matplotlib isn't very "sexy" (at least, insofar as
working on ipython, or one of the scikits). Most of the attendees are
specialized scientists who only cares enough about matplotlib to produce
"the plot" for their work. Getting attendees to join your sprint is a hard
sell. This is not meant to discourage you, but rather to help better frame
what the tasks and goals should be for matplotlib at the sprints.

I wish I was this prepared last year. You are off to a much better start
than I was.

Cheers!
Ben Root

--
Damon McDougall
http://www.damon-is-a-geek.com
Institute for Computational Engineering Sciences
201 E. 24th St.
Stop C0200
The University of Texas at Austin
Austin, TX 78712-1229

Damon -- I think that would be very helpful. I can do the same for major Linux distros. Sadly,Windows is much more complex and I'm not even terribly up on current best practices there. Any volunteers?

Mike

···

On 03/26/2013 10:57 AM, Damon McDougall wrote:

On Tue, Mar 26, 2013 at 8:25 AM, Benjamin Root <ben.root@...553...> wrote:

On Fri, Mar 22, 2013 at 12:35 PM, Michael Droettboom <mdroe@...31...> >> wrote:

I'm hoping to host a matplotlib sprint during the final two days of Scipy
2013 this year, and I hope to see as many as possible of you there. I think
it's also really important to bring new developers into sprints, because
it's such an efficient way to get people familiar with the code base.

It might be helpful to start brainstorming now about which projects we may
want to tackle so that we can have as much in place as possible by then and
hit the ground running.

I've set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

Getting a bit back on the original topic of the SciPy sprints, there are
some things I have learned from last year's sprints. First off, there are
going to be a lot of newbies there who do not even have a developer setup,
let alone a source install of matplotlib. Myself and a few other people
spent several hours fumbling around with getting the Mac users set up
properly. With me not being a Mac user, I felt very helpless. We need to
be better prepared for these users (as well as the Windows users).

Second, working on matplotlib isn't very "sexy" (at least, insofar as
working on ipython, or one of the scikits). Most of the attendees are
specialized scientists who only cares enough about matplotlib to produce
"the plot" for their work. Getting attendees to join your sprint is a hard
sell. This is not meant to discourage you, but rather to help better frame
what the tasks and goals should be for matplotlib at the sprints.

I wish I was this prepared last year. You are off to a much better start
than I was.

Cheers!
Ben Root

Ben,

This is incredibly useful information. I have never been to a sprint
before so this valuable knowledge to have. Since I'm a mac user,
perhaps I could put together a 'source install walkthrough' or
something? That might help us save some time fumbling at the
beginning of the sprint.

Also -- should we set up a shared place (either a git repo or just a wiki page) to collaborate on any of these materials?

Mike

···

On 03/26/2013 11:18 AM, Michael Droettboom wrote:

On 03/26/2013 10:57 AM, Damon McDougall wrote:

On Tue, Mar 26, 2013 at 8:25 AM, Benjamin Root <ben.root@...553...> wrote:

On Fri, Mar 22, 2013 at 12:35 PM, Michael Droettboom <mdroe@...31...> >>> wrote:

I'm hoping to host a matplotlib sprint during the final two days of Scipy
2013 this year, and I hope to see as many as possible of you there. I think
it's also really important to bring new developers into sprints, because
it's such an efficient way to get people familiar with the code base.

It might be helpful to start brainstorming now about which projects we may
want to tackle so that we can have as much in place as possible by then and
hit the ground running.

I've set up a wiki page here:

https://github.com/matplotlib/matplotlib/wiki/Scipy-2013

Getting a bit back on the original topic of the SciPy sprints, there are
some things I have learned from last year's sprints. First off, there are
going to be a lot of newbies there who do not even have a developer setup,
let alone a source install of matplotlib. Myself and a few other people
spent several hours fumbling around with getting the Mac users set up
properly. With me not being a Mac user, I felt very helpless. We need to
be better prepared for these users (as well as the Windows users).

Second, working on matplotlib isn't very "sexy" (at least, insofar as
working on ipython, or one of the scikits). Most of the attendees are
specialized scientists who only cares enough about matplotlib to produce
"the plot" for their work. Getting attendees to join your sprint is a hard
sell. This is not meant to discourage you, but rather to help better frame
what the tasks and goals should be for matplotlib at the sprints.

I wish I was this prepared last year. You are off to a much better start
than I was.

Cheers!
Ben Root

Ben,

This is incredibly useful information. I have never been to a sprint
before so this valuable knowledge to have. Since I'm a mac user,
perhaps I could put together a 'source install walkthrough' or
something? That might help us save some time fumbling at the
beginning of the sprint.

Damon -- I think that would be very helpful. I can do the same for major Linux distros. Sadly,Windows is much more complex and I'm not even terribly up on current best practices there. Any volunteers?