python colorbar刻度_python – matplotlib的colorbar中的小刻度

你走在正确的轨道上,你只需要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()

如果只需要指定的刻度,则仍然以“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均为0-1.

因此,要设置所需的特定值,我们需要使用图像使用的相同标准实例来调用标记位置.

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()