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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