On Thu, Dec 8, 2011 at 10:45 AM, Paul Hobson <pmhob...@gmail.com> wrote:
> Matplotlib gurus:
>
> I took at stab at the git work flow and incorporated my personal
> modifications to the boxplot function. Github's diff can be found
> here:
> https://github.com/phobson/matplotlib/compare/master...manual_boxplots
>
> In summary, if your data is MxN, you can manually specify medians and
> the confidence intervals around the medians using Nx1 and Nx2 arrays,
> respectively. Alternatively, you can use lists or tuples and use Nones
> if you want to specify those values only for some columns in your MxN
> data set. In other words, with an Mx5 data array, you can specify
> conf_intervals=[(ci1a,ci2a), (ci1b,ci2b), (ci1c,ci2c), None,
> (ci1e,ci2e)]. Within the conf_intervals "array", the CIs can be listed
> in any order as I use np.max() and np.min() to pull the upper and
> lower values, respectively.
>
> The motivation behind this is that sometimes I need the confidence
> levels to be different than 95%, and also that I compute those
> confidence intervals with a bootstrapping routine that is more robust
> than mpl-compatible one I submitted some time ago.
>
> I hope y'all find this to be a useful contribution. I'm an avid
> matplotlib user. It really is a wonderful tool.
>
> Cheers,
> paul h
>
>
Paul,
Interesting. I haven't had much time to really look over your changes, but
I have been wondering if the errorbar() and boxplot() functions could be
treated as two different ways to display similar information. Therefore,
perhaps their call signatures could be made more similar to each other.
What do you think?
Ben Root
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