Hi Ian
Thanks for your reply and help. I see your point. I guess it is only the
BoundaryNorm where it would make sense to have contourf use the boundary
levels from the norm. In my real problem described by the above example I
have long forgotten the levs variable when I arrive at the contourf point.
I will therefore instead just use levels=norm.boundaries.
Best regards,
Jesper
2014-03-28 15:17 GMT+01:00 Ian Thomas <ianthoma...@gmail.com>:
> On 28 March 2014 12:56, Jesper Larsen <jesper.webm...@gmail.com> wrote:
>
>> I believe the normalization behaviour is wrong for contourf at least when
>> using a BoundaryNorm. In the script below I am using the same norm to plot
>> the same data using contourf and pcolormesh. The color should change around
>> an x value of 0.15 but it is shifted somewhat for contourf. I do realize
>> that the pcolormesh is in principle shifted a little - but with a grid
>> spacing of 0.001 that should not matter. Please see the example script
>> below.
>>
>> Best regards,
>> Jesper
>>
>> """
>> Test inconsistent normalization behaviour for matplotlib
>> """
>> import numpy as np
>> import matplotlib.pyplot as plt
>> from matplotlib.colors import from_levels_and_colors
>>
>> # Make custom colormap and norm
>> levs = [0.0, 0.1, 0.2]
>> cols = [[0.00392156862745098, 0.23137254901960785, 0.07450980392156863],
>> [0.00392156862745098, 0.49019607843137253, 0.15294117647058825]]
>> extend = 'neither'
>> cmap, norm = from_levels_and_colors(levs, cols, extend)
>>
>> # Setup testdata
>> a = np.arange(0.05, 0.15, 0.001, dtype=np.float_)
>> a, b = np.meshgrid(a, a)0
>> plt.contourf(a, b, a, norm=norm, cmap=cmap, antialiased=False)
>> plt.savefig('contourf.png')
>> plt.clf()
>> plt.pcolormesh(a, b, a, norm=norm, cmap=cmap, antialiased=False)
>> plt.savefig('pcolormesh.png')
>>
>
> Jesper,
>
> Regardless of whether you specify a colormap and norm, if you want
> contourf to calculate contours at particular levels
> then you need to specify those levels. If you don't then contourf will
> choose the levels for you, and in your case these are chosen to be
> [0.045 0.06 0.075 0.09 0.105 0.12 0.135 0.15 ]
> which is why you see the color transition at x=0.105.
>
> To fix this, change your contourf line from
> plt.contourf(a, b, a, norm=norm, cmap=cmap, antialiased=False)
> to
> plt.contourf(a, b, a, norm=norm, cmap=cmap, antialiased=False, levels=levs)
> and you will get exactly what you want.
>
> Ian
>
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