Re: [Matplotlib-users] problem with x scale on error bar plot

[Gary R. <ga...@em...>]

My comment would be that I agree with Fl=E1vio for the specific case of e=
rrorbar plots. That is, when you have errorbars, you want them slightly i=
nset from the axes so that it's clear where they finish. I think this onl=
y applies to errorbar plots. So, if there's an easy way to have the scali=
ng differentiate, I'd say the endpoints should NOT always exceed the data=
 end points, but should for errorbar plots. I'm think changing the defaul=
t behaviour would upset lots of people.
Another idea might be to just add a command like autoscale(factor) or aut=
oscale(margin) or margin(inset) to specify on a per-case basis.

Gary

----- Original Message -----
From: John Hunter <jdh...@ac...>
Date: Wed, 22 Sep 2004 06:31:58 -0500
To: Fl=E1vio Code=E7o Coelho <fcc...@fi...>
Subject: Re: [Matplotlib-users] problem with x scale on error bar plot

> >>>>> "Fl=E1vio" =3D=3D Fl=E1vio Code=E7o Coelho <fcc...@fi...> =
writes:
>=20
>     Fl=E1vio> Hi john, I am getting a bad autoscale when I generate a
>     Fl=E1vio> two point y-error errorbar plot:
>=20
>     Fl=E1vio> As you can see in the figure attached the points are
>     Fl=E1vio> falling on the margin of the plot.
>=20
>     Fl=E1vio> I think a space before the first point and after the last
>     Fl=E1vio> point of the plot should be added automatically, since no
>     Fl=E1vio> one will want a plot like this by default.
>=20
> This is a fix that is trivial to implement.  But I would like to get
> some feedback because changing the default would affect every almost
> all matplotlib plots.
>=20
> The question is: should the autoscale endpoints always exceed the data
> end points, or are there some cases in which it is desirable for the
> datalim and viewlim to coincide?  In this case
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>     from matplotlib.matlab import *
>     plot([1,2], 'o')
>     show()
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> it seems like you want the viewlim to exceed the datalim.  In cases
> like
>=20
>     from matplotlib.matlab import *
>     t =3D linspace(0,1,100)
>     plot(t, sin(2*pi*t))
>     show()
>=20
> it looks to me like having the xlim at 0,1 is the best solution.
>=20
> To change the behavior, edit matplotlib/ticker.py and search for class
> MultipleLocator.  In the autoscale method, change
>=20
>         vmin =3D self.base.le(dmin)
>         vmax =3D self.base.ge(dmax)
>=20
> to
>         vmin =3D self.base.lt(dmin)
>         vmax =3D self.base.gt(dmax)
>=20
> and try both of the examples above in the le/ge case and in the lt/gt
> case.
>=20
> JDH
>=20
>=20
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--=20
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