Matplotlib Half color axis

Question

I am using matplotlib to make some plots and I have run into a few difficulties that I need help with.

problem 1) In order to keep a consistent colorscheme I need to only use half of the color axis. There are only positive values, so I want the zero values to be green, the mid values to be yellow and the highest values to be red. The color scheme that most closely matches this is gist_rainbow_r, but I only want the top half of it.

problem 2) I can't seem to figure out how to get the colorbar on the right hand side of the plot to show up or how to get it to let me label the axes.

If it helps, I am using the latest version of Anaconda wth the latext version of matplotlib

cmap = plt.get_cmap('gist_rainbow_r')
edosfig2 = plt.figure(2)
edossub2 = edosfig.add_subplot(1,1,1)
edossub2 = plt.contourf(eVec,kints,smallEDOS,cmap=cmap)
edosfig2.show()

Answer 1

If you have a specific set of colors that you want to use for you colormap, you can build it based on those. For example:

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

cmap = LinearSegmentedColormap.from_list('name', ['green', 'yellow', 'red'])

# Generate some data similar to yours
y, x = np.mgrid[-200:1900, -300:2000]
z = np.cos(np.hypot(x, y) / 100) + 1

fig, ax = plt.subplots()

cax = ax.contourf(x, y, z, cmap=cmap)
cbar = fig.colorbar(cax)
cbar.set_label('Z-Values')

plt.show()

---

However, if you did just want the top half of some particularly complex colormap, you can copy a portion of it by evaluating the colormap over the range you're interested in. For example, if you wanted the "top" half, you'd evaluate it from 0.5 to 1:

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

# Evaluate an existing colormap from 0.5 (midpoint) to 1 (upper end)
cmap = plt.get_cmap('gist_earth')
colors = cmap(np.linspace(0.5, 1, cmap.N // 2))

# Create a new colormap from those colors
cmap2 = LinearSegmentedColormap.from_list('Upper Half', colors)

y, x = np.mgrid[-200:1900, -300:2000]
z = np.cos(np.hypot(x, y) / 100) + 1

fig, axes = plt.subplots(ncols=2)
for ax, cmap in zip(axes.flat, [cmap, cmap2]):
    cax = ax.imshow(z, cmap=cmap, origin='lower',
                    extent=[x.min(), x.max(), y.min(), y.max()])
    cbar = fig.colorbar(cax, ax=ax, orientation='horizontal')
    cbar.set_label(cmap.name)

plt.show()