Re: [Matplotlib-users] strange behaviour with fill_between

[Francesco M. <fra...@gm...>]

Dear Eric,

sorry for the delay in replying, and thanking: I forgot the mail after
reading it.

2012/8/30 Eric Firing <ef...@ha...>:
> On 2012/08/27 5:10 AM, Francesco Montesano wrote:
>> Dear matplotlibers,
>>
>> I encountered a bug (?) in fill_between when using logarithmic scales and
>> the last part of y and yerr arrays as set to zero: a diagonal stripe going from
>> the rightmost non zero value to the first value is drawn.
>> It's visible in the right panel of the attached figure, while is not
>> present if the plot is linear (left panel).
>> If xaxis is log and yaxis is linear the plot is correctly drawn.
>>
>> I'm using mpl.__version__ = '1.1.1rc' under Kubuntu 12.04 with Python 2.7.3
>>
>> The plot has been created with the script below.
>>
>> Is this a bug or am I missing something?
>
> I don't think it is exactly a bug, but I don't know why the fill region
> is appearing as it does.  The underlying problem is that fill_between is
> doing what it is told to do without knowing that it is going to be
> plotted on a log axis.
I think that also most of the other plotting functions (e.g. errorbar)
do not know about the scale used on the axis, but they behave
correctly. Am I right?


> A good workaround is to change your call to fill_between to look like this:
> positive = y - yerr > 0
> ax2.fill_between( x,y-yerr,y+yerr, where=positive, color='b', alpha=0.4)
>
> Alternatively, you could use np.clip to put a floor under y - yerr and y
> + yerr.

The workaround works fine, but I dare say that it's not THE solution.
I think that the problem lies in the way PolyCollection is drawn when
y=yerr=0 (and probably also if y+- yerr <=0) if the yaxis is log. I
have no clue where to look in the source to go deeper in the problem.

cheers,
Fra

> Eric
>
>>
>> Cheers
>> Francesco
>>
>>
>> ##### error_fill_between.py ######
>> import matplotlib.pyplot as plt
>> import numpy as np
>>
>> #values to plot
>> x = np.linspace( 1, 10, num=100 )
>> y = np.exp( -x**2 )
>> y[50:] = 0
>> yerr = y* np.random.rand(100)
>>
>> #figure
>> fig = plt.figure()
>>
>> ax1 = fig.add_subplot(121)  #first axes: linear
>> ax1.errorbar( x,y,yerr, c='r' )
>> ax1.fill_between( x,y-yerr,y+yerr, color='b', alpha=0.4 )
>>
>> ax2 = fig.add_subplot(122)  #second axes: logarithmic
>> ax2.errorbar( x,y,yerr, c='r' )
>> ax2.fill_between( x,y-yerr,y+yerr, color='b', alpha=0.4 )
>> ax2.set_xscale( "log" )
>> ax2.set_yscale( "log" )
>>
>> plt.show()
>> ###### end script  #########
>>
>>
>>
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>
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