matplotlib的colorbar中的小刻度

Question

I'm currently trying to set minor ticks in the colorbar but simply can't make it work. There are 3 approaches which I've tried (see code below), but all of them didn't appear to be working. Is it actually possible to have minor ticks in the colorbar?

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from matplotlib.ticker import FixedLocator, FormatStrFormatter

# fill grid
x = np.linspace(1,10,10)
y = np.linspace(1,10,10)

X, Y = np.meshgrid(x,y)
Z = np.abs(np.cos(X**2 - Y**2) * X**2 * Y)

# plot
f, ax = subplots(1)
p = plt.pcolormesh(X, Y, Z, norm=LogNorm(), vmin=1e-2, vmax=1e2)
cb = plt.colorbar(p, ax=ax, orientation='horizontal', aspect=10)

minor_ticks = np.arange(1,10,2)
#cb.set_ticks(minor_ticks, minor=True) # error: doesn't support keyword argument 'minor'
#cb.ax.xaxis.set_ticks(minor_ticks, minor=True) # plots an extremely small colorbar, with wrong ticks
#cb.ax.xaxis.set_minor_locator(FixedLocator(minor_ticks)) # nothing happens
plt.show()

Answer 1

You're on the right track, you just need cb.ax.minorticks_on() .

For example:

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

# fill grid
x = np.linspace(1,10,10)
y = np.linspace(1,10,10)

X, Y = np.meshgrid(x,y)
Z = np.abs(np.cos(X**2 - Y**2) * X**2 * Y)

# plot
f, ax = plt.subplots()
p = plt.pcolormesh(X, Y, Z, norm=LogNorm(), vmin=1e-2, vmax=1e2)
cb = plt.colorbar(p, ax=ax, orientation='horizontal', aspect=10)

cb.ax.minorticks_on()

plt.show()

---

If you want just the ticks that you specify, you still set them in the "normal" way, but be aware that the colorbar axes coordinate system ranges from 0-1 regardless of the range of your data.

For that reason, to set the specific values that you want, we need to call the normalize the tick locations using the same norm instance that the image is using.

For example:

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

# fill grid
x = np.linspace(1,10,10)
y = np.linspace(1,10,10)

X, Y = np.meshgrid(x,y)
Z = np.abs(np.cos(X**2 - Y**2) * X**2 * Y)

# plot
f, ax = plt.subplots()
p = plt.pcolormesh(X, Y, Z, norm=LogNorm(), vmin=1e-2, vmax=1e2)
cb = plt.colorbar(p, ax=ax, orientation='horizontal', aspect=10)

# We need to nomalize the tick locations so that they're in the range from 0-1...
minorticks = p.norm(np.arange(1, 10, 2))
cb.ax.xaxis.set_ticks(minorticks, minor=True)

plt.show()