Re: [matplotlib-devel] release strategy and the color revolution

2015-03-01 Thread jni
Hi everyone,
As someone working with images, I think for displaying images you want a
colormap that spans as much as possible of the luminance range. The colormap
suggested by Michael Waskom would be quite perfect as-is. (recap: middle
colormap here:
http://earthobservatory.nasa.gov/blogs/elegantfigures/files/2013/08/three_perceptual_palettes_618.png)

I understand the concern that a colormap should be able to display things on
dark and light backgrounds, but this applies only to plots, not to images.
Tom Caswell emphasised the distinction between colormaps for continuous
variables and color cycles for categorical variables. There should also be a
distinction between image display and plotting. For image display, please
consider using a colormap with a wide luminance range.

Thanks!



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Re: [matplotlib-devel] release strategy and the color revolution

2015-03-02 Thread jni
Hi Pierre,

Could you please elaborate a bit on this
> usecase. I was thinking, naively, that when plotting a grayscale image,
> one would simply used a gray colormap.
>

Using a colormap with hue and saturation gives you better contrast than
pure grayscale. For natural images, that is, photographs of human-scale
objects, indeed grayscale is a good choice, because that is how we are used
to looking at those images. But for looking at physical quantities, for
example, using a colormap with hue and saturation as well as lightness is
useful. Here are some examples:
http://www.gnuplotting.org/color-maps-from-colorbrewer/
https://www.mrao.cam.ac.uk/~dag/CUBEHELIX/

See also a "boundary probability map" for a natural image here (panel B,
top right):
http://www.frontiersin.org/files/Articles/74212/fninf-08-00034-r2/image_m/fninf-08-00034-g001.jpg
Having the colormap makes it easier to place the intermediate levels of the
probability map.

Again, restricting the lightness range for these maps would be problematic,
to say the least.

Juan.




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Re: [matplotlib-devel] Alternative way of specifying plot layout

2015-03-18 Thread jni . soma
I love this layout spec idea! Gridspec is a pain in the ass. Bonus points for 
actually drawing the letter e.g. on the top left corner of each panel, so that 
the figures are ready for publication.

On Thu, Mar 19, 2015 at 5:04 AM, Benjamin Root  wrote:

> I like that. Furthermore, now that we build and push the docs with every
> merge in master, there is less reason to not do it that way.
> On Wed, Mar 18, 2015 at 1:56 PM, Thomas Caswell  wrote:
>> Currently we are doing MEPs on the wiki (
>> https://github.com/matplotlib/matplotlib/wiki/MEPTemplate) , but I would
>> like to move them to be in the docs (make a MEP folder next to 'users'?) as
>> the visibility on the wiki is low, there isn't a great way to leave line
>> comments, and we should have these documents in the official docs
>> eventually.
>>
>> Tom
>>
>> On Wed, Mar 18, 2015 at 1:45 PM Nicolas P. Rougier <
>> [email protected]> wrote:
>>
>>>
>>> Yes, a MEP makes sense to discuss the proposal.
>>> What's the procedure to open a MEP (i.e. where) ?
>>>
>>> Nicolas
>>>
>>>
>>> > On 18 Mar 2015, at 18:44, Benjamin Root  wrote:
>>> >
>>> > Also, perhaps it makes sense to make this a MEP to finalize and
>>> document the spec?
>>> >
>>> > On Wed, Mar 18, 2015 at 1:42 PM, Benjamin Root  wrote:
>>> > That is neat. I would be sure to put in some "..seealso::" lines in
>>> places like plt.subplots and GridSpec and such.
>>> >
>>> > A thought... could this perhaps be extended somehow to specify
>>> colorbars in the layout? I am not sure how I would do that, but if we could
>>> come up with a way to do it, *that* would make this a killer feature. But
>>> even without that, this is still pretty useful.
>>> >
>>> > On Wed, Mar 18, 2015 at 1:20 PM, Thomas Caswell 
>>> wrote:
>>> > Cool.  I think it make sense to put this in to `pyplot.py` next to
>>> `subplots`
>>> >
>>> > Tom
>>> >
>>> > On Wed, Mar 18, 2015 at 1:14 PM Nicolas P. Rougier <
>>> [email protected]> wrote:
>>> >
>>> > Hi,
>>> >
>>> > I've been experimenting with a simple idea for specifying plot layout
>>> in a rather intuitive way.
>>> > The idea is simply to "draw" your layout using strings.
>>> >
>>> > Examples:
>>> >
>>> > layout = ["AB"]
>>> > -> means two plots side by side with equal width
>>> >
>>> > layout = ["AAAB"]
>>> > -> means two plots side by side A being 3 times wider than B
>>> >
>>> > layout = ["AB",
>>> >   "CC"]
>>> > -> means two plots (A & B) side by side and C below with full width
>>> >
>>> > layout = ["AB",
>>> >   "C "]
>>> > -> means two plots (A & B) side by side and C below A (same width)
>>> >
>>> > etc... (have a look at sources)
>>> >
>>> > I guess you cannot express every layout but it might work for most
>>> common ones.
>>> >
>>> > If you think this might a good addition I can try to make a PR but I'm
>>> not sure where to insert it.
>>> > My idea would be to have a layout function such that you can write:
>>> >
>>> > A,B,C = plt.layout(["AB", "CC"], border=0.01)
>>> > A.plot(...)
>>> > B.plot(...)
>>> > C.plot(...)
>>> >
>>> >
>>> > Nicolas
>>> >
>>> >
>>> > 
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