matplotlib的colorbar中的小刻度

Question

我目前正试图在颜色栏中设置小刻度,但根本无法使其工作.我尝试了3种方法(见下面的代码),但所有这些方法似乎都没有起作用.它实际上可能在颜色栏中有小的刻度吗？

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

你需要的是正确的轨道cb.ax.minorticks_on().

例如:

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()

如果您只想要指定的刻度,您仍然可以以"正常"方式设置它们,但请注意,无论数据范围如何,颜色条轴坐标系的范围都是0-1.

因此,要设置所需的特定值,我们需要使用norm图像使用的相同实例调用标记位置.

例如:

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()