Shifted colorbar matplotlib

colors, matplotlib, python

Solution

First off, there's more than one way to do this.

- Pass an instance of `DivergingNorm` as the `norm` kwarg.

- Use the `colors` kwarg to `contourf` and manually specify the colors

- Use a discrete colormap constructed with `matplotlib.colors.from_levels_and_colors`.

The simplest way is the first option. It is also the only option that allows you to use a continuous colormap.

The reason to use the first or third options is that they will work for any type of matplotlib plot that uses a colormap (e.g. `imshow`, `scatter`, etc).

The third option constructs a discrete colormap and normalization object from specific colors. It's basically identical to the second option, but it will a) work with other types of plots than contour plots, and b) avoids having to manually specify the number of contours.

As an example of the first option (I'll use `imshow` here because it makes more sense than `contourf` for random data, but `contourf` would have identical usage other than the `interpolation` option.):

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import DivergingNorm

data = np.random.random((10,10))
data = 10 * (data - 0.8)

fig, ax = plt.subplots()
im = ax.imshow(data, norm=DivergingNorm(0), cmap=plt.cm.seismic, interpolation='none')
fig.colorbar(im)
plt.show()

As an example of the third option (notice that this gives a discrete colormap instead of a continuous colormap):

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import from_levels_and_colors

data = np.random.random((10,10))
data = 10 * (data - 0.8)

num_levels = 20
vmin, vmax = data.min(), data.max()
midpoint = 0
levels = np.linspace(vmin, vmax, num_levels)
midp = np.mean(np.c_[levels[:-1], levels[1:]], axis=1)
vals = np.interp(midp, [vmin, midpoint, vmax], [0, 0.5, 1])
colors = plt.cm.seismic(vals)
cmap, norm = from_levels_and_colors(levels, colors)

fig, ax = plt.subplots()
im = ax.imshow(data, cmap=cmap, norm=norm, interpolation='none')
fig.colorbar(im)
plt.show()

Problem

I am trying to make a filled contour for a dataset. It should be fairly straightforward: ``` plt.contourf(x, y, z, label = 'blah', cm = matplotlib.cm.RdBu) ``` However, what do I do if my dataset is not symmetric about 0? Let's say I want to go from blue (negative values) to 0 (white), to red (positive values). If my dataset goes from -8 to 3, then the white part of the color bar, which should be at 0, is in fact slightly negative. Is there some way to shift the color bar?

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