matplotlib-devel Mailing List for matplotlib

I've made a second notebook that uses the IPython interactive machinery to
let anyone play with the parameters and explore different ways of setting
them. you can download the notebook with that here:
http://nbviewer.ipython.org/gist/mwaskom/842d1497b6892d081bfb (I made it
using IPython 3.0rc1; I'm not certain if it will work on the 2.x series;
sorry if that is the case).
This stays with the general approach in the original notebook of using a
linear ramp for chroma, which again maybe is not what we want. But it
should let you get a better sense for the parameter space.
As I said in the email to Olga, I think (a) I would advocate fairly
strongly that matplotlib should design a custom colormap as its default,
and (b) I think this approach (a cubehelix-like map in Hcl space) is a
principled way of doing so (though maybe not optimal). But both of those
points are independent of whether you end up going with the particular
parameters that I used to generate the original proposal -- I have my own
domain on which to impose my personal aesthetic preferences, and I don't
need to take over matplotlib too :)
(But I do think it's worth distinguishing the matplotlib default from the
matlab default.)
Michael

Cool! I knew there had been some useful tools posted on the earlier thread
but didn't have time to dig them out.
Interesting observation about the colorfulness. I don't know enough about
all the transformations involved to full account for that, but I added some
stuff to the notebook to figure out how much of that might be caused by
straying out of gamut. It looks like the map I created does a pretty good
job and is only getting clamped at the very low end and near the high end,
so I don't think it's a complete explanation for the undulating
"colorfulness":
http://nbviewer.ipython.org/gist/mwaskom/6a43a3b94eca4a9e2e8b
By means of disclosure, I did this before having coffee, so it might be
wrong...

On 2015年02月18日 6:31 AM, Benjamin Root wrote:
> The problem I have with hcl is that while it is technically "colorful"
> (or whatever the term may be), only the reds really come out because the
> other colors are only used when either really light or really dark.
> Perhaps squashing the brightness range a bit and let the natural
> lightness of yellow and the natural darkness of blue come through on
> their own. (does that even make any sense to anybody else? it makes
> sense in my head, but I am certainly am not an expert in color perception)
>
> Ben Root
>
> P.S. - Of course, my own color perception weirdness might be at play
> here and the colormap looks perfectly fine to everybody else...
My own reaction to it is that it seems like a nicely *functional* 
colormap, one I would want to have available and probably would 
sometimes use, but it is not particularly aesthetically *pleasing*. I 
think this is consistent with Olga's earlier post as well.
Eric

The problem I have with hcl is that while it is technically "colorful" (or
whatever the term may be), only the reds really come out because the other
colors are only used when either really light or really dark. Perhaps
squashing the brightness range a bit and let the natural lightness of
yellow and the natural darkness of blue come through on their own. (does
that even make any sense to anybody else? it makes sense in my head, but I
am certainly am not an expert in color perception)
Ben Root
P.S. - Of course, my own color perception weirdness might be at play here
and the colormap looks perfectly fine to everybody else...
On Wed, Feb 18, 2015 at 11:17 AM, Maximilian Albert <
max...@gm...> wrote:
> 2015年02月17日 1:23 GMT+01:00 Michael Waskom <mw...@st...>:
>
>> See [here](http://nbviewer.ipython.org/gist/mwaskom/6a43a3b94eca4a9e2e8b)
>> for a quick and dirty implementation that should get a general idea. This
>> probably ins't the best way to do it -- anyone should feel free to build on
>> this.
>>
>
> This is very neat! Great job. Incidentally, when I stumbled upon the
> earthobservatory blog a while ago this particular colormap also caught my
> eye as a potential candidate, so I'm glad you suggested it as a starting
> point for a new matplotlib default.
>
> Out of curiosity, I applied Nathaniel's "viscm" function (from the
> previous thread) to the colormap from your notebook (screenshot attached).
> Interestingly, while it confirms that the lightness and hue angle increase
> more or less linearly, the "colourfulness" goes up and down in waves, even
> though you designed the chroma to increase linearly, too. I'm not sure
> whether this is because "colourfulness" and "chroma" are actually two
> different concepts, or whether it has to do with inaccuracies and/or
> clamping during the conversion between various colour spaces. It could also
> be the case that the colormath and pycam02ucs modules use different
> conversion formulas (in which case it would be good to know which is "more
> accurate"; not sure there is even an objective measure for "accuracy" in
> this case). Also, there seems to be something strange going on at the dark
> (blue) end of the colormap, but this could again be due to clamping.
>
> I'd love to play a bit more with your example notebook but not sure I'll
> be able to do so before the weekend (or early next week).
>
> Cheers,
> Max
>
>
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Hi,
I posted on the user list a while back about saving editable text using the
postscript backend [1]. There I was informed that this was changed a few
years ago to individually place glyphs. It looks to me, that this change
was about correctly supporting unicode in this backend [2].
Would the project be open to changing this to produce text runs when all of
the characters are ascii? This way, the general unicode case should still
work but runs of text where the special handling is not necessary should
result in editable text. I'm happy to work up a patch, but I don't want to
spend the time if there is no hope of it being merged.
My use case is to be able to make some tweaks to figures post mpl. In my
case this tends to be to either combine figures from several sources into a
single coherent figure or to adjust the figure size or spacing slightly so
the final figure fits into the space available. All of this can be done in
mpl directly, but in terms of effective use of my time, opening the figure
in Corel Draw, Inkscape or Illustrator is much faster since I can get the
figure 90% of the way there quickly and easily using mpl.
Eric
1. http://thread.gmane.org/gmane.comp.python.matplotlib.general/34816
2.
https://github.com/matplotlib/matplotlib/commit/80321a3b489994748b79e41bc34a65f836a9a03f

2015年02月17日 1:23 GMT+01:00 Michael Waskom <mw...@st...>:
> See [here](http://nbviewer.ipython.org/gist/mwaskom/6a43a3b94eca4a9e2e8b)
> for a quick and dirty implementation that should get a general idea. This
> probably ins't the best way to do it -- anyone should feel free to build on
> this.
>
This is very neat! Great job. Incidentally, when I stumbled upon the
earthobservatory blog a while ago this particular colormap also caught my
eye as a potential candidate, so I'm glad you suggested it as a starting
point for a new matplotlib default.
Out of curiosity, I applied Nathaniel's "viscm" function (from the previous
thread) to the colormap from your notebook (screenshot attached).
Interestingly, while it confirms that the lightness and hue angle increase
more or less linearly, the "colourfulness" goes up and down in waves, even
though you designed the chroma to increase linearly, too. I'm not sure
whether this is because "colourfulness" and "chroma" are actually two
different concepts, or whether it has to do with inaccuracies and/or
clamping during the conversion between various colour spaces. It could also
be the case that the colormath and pycam02ucs modules use different
conversion formulas (in which case it would be good to know which is "more
accurate"; not sure there is even an objective measure for "accuracy" in
this case). Also, there seems to be something strange going on at the dark
(blue) end of the colormap, but this could again be due to clamping.
I'd love to play a bit more with your example notebook but not sure I'll be
able to do so before the weekend (or early next week).
Cheers,
Max

Hey Olga,
On Tue, Feb 17, 2015 at 6:24 PM, Olga Botvinnik <obo...@uc...> wrote:
> Out of curiosity, what are the advantages of the HCL colormap over YlGnBu
> for continuous values? I'm biased towards YlGnBu because green is my
> favorite color and want to know what makes HCL objectively better for
> perceiving values.
>
Perceptually, the luminance ramp is probably a bit more linear, but that's
not a huge deal. The main functional advantage to using *some* kind of Hcl
based map is that it lets matplotlib tweak more parameters. This particular
Hcl map has a bit more hue variation than YlBuGn, and I think the
saturation channel is doing something different than what the colorbrewer
maps do. So it appears a little bit more "colorful", which I think was one
of the objectives.
I think there's some argument for matplotlib creating a novel colormap for
its default rather than just using one of the preset colorbrewer ones. It
would be nice to have a bit more well-defined visual identity, and having
people say "oh hey that's the matplotlib colormap, it looks really nice!"
might have good marketing benefits. I like the colorbrewer palettes and use
them often, but it seems kind of boring to take an existing colormap that
lots of packages have and make it the default.
> I added YlGnBu_r versions of those plots just below yours:
> http://nbviewer.ipython.org/gist/olgabot/6a619ef21c178801ff77
>
> It seems it's a little more "extreme" than HCL, as in it lights are
> lighter and its darks are darker. From the color research, is this less
> desirable?
>
Well, that could be changed in the Hcl version by setting different
endpoints for the lightness ramp. I was trying to get something similar to
parula, which doesn't cover as extreme of a lightness range and is more
saturated on both ends than the color brewer palettes. I would imagine the
reasoning for this is that it might let the map represent categorical or
divergent data a little bit better without much cost to sequential data,
but I am not sure.
Also, if you map a line or scatter plot with YlGnBu, the lightest colors
might not be visible on a white background, whereas I think the yellow I
used would be ok. This might be something to keep in mind as the map that
gets chosen will likely be the default for plt.scatter.
But like I said, I didn't spend much time thinking about exactly where the
endpoints should be, so it's possible one would want more dynamic luminance
range.
Michael
> On Mon Feb 16 2015 at 9:28:56 PM Benjamin Root <ben...@ou...> wrote:
>
>> Do remember that I have a PR to add linestyle cycling, which would
>> greatly mitigate problems for colorblindness and non-color publications.
>>
>> I also prefer it for slideshows as projectors at conferences tend to have
>> crappy colors anyway (was at a radar conference when the projector's red
>> crapped out while the presenter was building up suspense about the really,
>> really impressive radar image of a supercell on the next slide)
>>
>> Ben Root
>> On Feb 16, 2015 7:24 PM, "Michael Waskom" <mw...@st...> wrote:
>>
>>> See [here](http://nbviewer.ipython.org/gist/mwaskom/6a43a3b94eca4a9e2e8b)
>>> for a quick and dirty implementation that should get a general idea. This
>>> probably ins't the best way to do it -- anyone should feel free to build on
>>> this.
>>>
>>> On Mon, Feb 16, 2015 at 3:38 PM, Eric Firing <ef...@ha...> wrote:
>>>
>>>> On 2015年02月16日 1:29 PM, Michael Waskom wrote:
>>>>
>>>> Nathaniel's January 9 message in that thread (can't figure out how to
>>>>> link to it in the archives) had a suggestion that I thought was very
>>>>> promising, to do something similar to Parula but rotate around the hue
>>>>> circle the other direction so that the hues would go blue - purple -
>>>>> red
>>>>> - yellow. I don't think we've seen an example of exactly what it would
>>>>> look like, but I reckon it would be similar to the middle colormap here
>>>>> http://earthobservatory.nasa.gov/blogs/elegantfigures/
>>>>> files/2013/08/three_perceptual_palettes_618.png
>>>>> (from the elegant figures block series linked above), which I've always
>>>>> found quite attractive.
>>>>>
>>>>
>>>> Certainly it can be considered--but we have to have a real
>>>> implementation.
>>>>
>>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
>>> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
>>> with Interactivity, Sharing, Native Excel Exports, App Integration & more
>>> Get technology previously reserved for billion-dollar corporations, FREE
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>>>
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>>
>

Out of curiosity, what are the advantages of the HCL colormap over YlGnBu
for continuous values? I'm biased towards YlGnBu because green is my
favorite color and want to know what makes HCL objectively better for
perceiving values.
I added YlGnBu_r versions of those plots just below yours:
http://nbviewer.ipython.org/gist/olgabot/6a619ef21c178801ff77
It seems it's a little more "extreme" than HCL, as in it lights are lighter
and its darks are darker. From the color research, is this less desirable?
On Mon Feb 16 2015 at 9:28:56 PM Benjamin Root <ben...@ou...> wrote:
> Do remember that I have a PR to add linestyle cycling, which would greatly
> mitigate problems for colorblindness and non-color publications.
>
> I also prefer it for slideshows as projectors at conferences tend to have
> crappy colors anyway (was at a radar conference when the projector's red
> crapped out while the presenter was building up suspense about the really,
> really impressive radar image of a supercell on the next slide)
>
> Ben Root
> On Feb 16, 2015 7:24 PM, "Michael Waskom" <mw...@st...> wrote:
>
>> See [here](http://nbviewer.ipython.org/gist/mwaskom/6a43a3b94eca4a9e2e8b)
>> for a quick and dirty implementation that should get a general idea. This
>> probably ins't the best way to do it -- anyone should feel free to build on
>> this.
>>
>> On Mon, Feb 16, 2015 at 3:38 PM, Eric Firing <ef...@ha...> wrote:
>>
>>> On 2015年02月16日 1:29 PM, Michael Waskom wrote:
>>>
>>> Nathaniel's January 9 message in that thread (can't figure out how to
>>>> link to it in the archives) had a suggestion that I thought was very
>>>> promising, to do something similar to Parula but rotate around the hue
>>>> circle the other direction so that the hues would go blue - purple - red
>>>> - yellow. I don't think we've seen an example of exactly what it would
>>>> look like, but I reckon it would be similar to the middle colormap here
>>>> http://earthobservatory.nasa.gov/blogs/elegantfigures/
>>>> files/2013/08/three_perceptual_palettes_618.png
>>>> (from the elegant figures block series linked above), which I've always
>>>> found quite attractive.
>>>>
>>>
>>> Certainly it can be considered--but we have to have a real
>>> implementation.
>>>
>>>
>>
>>
>> ------------------------------------------------------------------------------
>> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
>> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
>> with Interactivity, Sharing, Native Excel Exports, App Integration & more
>> Get technology previously reserved for billion-dollar corporations, FREE
>>
>> http://pubads.g.doubleclick.net/gampad/clk?id=190641631&iu=/4140/ostg.clktrk
>> _______________________________________________
>> Matplotlib-devel mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>>
>> ------------------------------------------------------------
> ------------------
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> with Interactivity, Sharing, Native Excel Exports, App Integration & more
> Get technology previously reserved for billion-dollar corporations, FREE
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