Dear all,

I made a pull request for this: #3753, at

https://github.com/matplotlib/matplotlib/pull/3753

Cheers,
Fabio

On 11/03/2014 01:30 PM, Fabio Zanini wrote:
> @Pierre: Yeah, my code looks 99% the same like yours. I'll make a PR
> starting from a mix of both - probably closer to yours than to mine :-P
> 
> @Jens: symlog extends to infinity, logit has a compact range, that's why
> it's not exactly the same.
> 
> Ok I'll make a pull request. Shall I start with a test that fails, then
> add the function and show it succeeds? or shall I start directly with
> the code and add a test later on?
> 
> Cheers,
> Fabio
> 
> On 11/03/2014 12:58 PM, Thomas Caswell wrote:
>> Please create a pull request.
>>
>> This sounds reasonable to me, but I have never seen a plot with that
>> scale and don't really understand it from your description. Seeing the
>> code usually clarifies things.
>>
>> Tom
>>
>> On Mon, Nov 3, 2014, 05:58 Fabio Zanini <fabio.zan...@tuebingen.mpg.de
>> <mailto:fabio.zan...@tuebingen.mpg.de>> wrote:
>>
>>     Dear all,
>>
>>     I've been using matplotlib with great satisfaction for a few years, but
>>     one feature I've been missing is a "logit" scale. This is essentially a
>>     nonlinear scale that is log both towards 0+ and log towards 1-. It is
>>     useful when one has frequencies in a population (i.e. floats between 0
>>     and 1) and both rare events and very common ones are interesting.
>>
>>     For instance, say you ask about the fraction of people with blue eyes in
>>     various world populations, you want to spot even tiny deviations from
>>     zero or one.
>>
>>     I have coded a scale according to matplotlib's documentation and it
>>     works well, so I was wondering whether you are interested into merging
>>     it into the the main repository. I think it'd be useful because lots of
>>     people have such frequency data, especially now that matplotlib is
>>     becoming popular in the biology/social sciences research communities.
>>
>>     If there is interest, I'll just start a pull request on github and try
>>     to adapt the code to your coding style. It's already PEP8 and similia.
>>
>>     Thanks. Cheers,
>>     Fabio
>>
>>     
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> 

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