在matplotlib中以科学计数法更改偏移的颜色

Question

I am plotting some curves using twin-axis and also scientific notation. I have set some color to the label but the setting don't seem to affect the power indicator of the scientific notation of its axis. Is there any trick?

Example

Here is my code:

fig = pylab.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twinx()

# Plotting the data
plot_ax1, = ax1.plot()
plot_ax2, = ax2.plot()

# Setting the label colors
ax2.yaxis.set_offset_position('right') # To set the power indicator of ax2 
ax1.yaxis.label.set_color(plot_ax1.get_color())
ax2.yaxis.label.set_color(plot_ax2.get_color())

# Setting the ticker properties     
tkw = dict(size=4, width=1.5)
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
ax2.ticklabel_format(style='sci', scilimits=(0,0), axis='y')        
ax1.tick_params(axis='y', colors=plot_ax1.get_color(), **tkw)
ax2.tick_params(axis='y', colors=plot_ax2.get_color(), **tkw)
ax1.tick_params(axis='x', **tkw)

# Setting the legend
lines = [plot_ax1, plot_ax2]
ax1.legend(lines, [l.get_label() for l in lines],'upper left')

Answer 1

It's probably just an oversight that tick_params doesn't already do this, but you can simply set it manually.

For example, just add these two lines to your example code:

ax1.yaxis.get_offset_text().set_color(plot_ax1.get_color())
ax2.yaxis.get_offset_text().set_color(plot_ax2.get_color())

As a more complete example, using your code snippet above and some random data:

import matplotlib.pyplot as plt
import numpy as np

numdata = 100
t = np.linspace(0.05, 0.11, numdata)
x1 = np.cumsum(np.random.random(numdata) - 0.5) * 40000
x2 = np.cumsum(np.random.random(numdata) - 0.5) * 0.002

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twinx()

# Plotting the data
plot_ax1, = ax1.plot(t, x1, 'r-', label='x1')
plot_ax2, = ax2.plot(t, x2, 'g-', label='x2')

# Setting the label colors
ax2.yaxis.set_offset_position('right') # To set the power indicator of ax2 
ax1.yaxis.label.set_color(plot_ax1.get_color())
ax2.yaxis.label.set_color(plot_ax2.get_color())

# Setting the ticker properties     
tkw = dict(size=4, width=1.5)
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
ax2.ticklabel_format(style='sci', scilimits=(0,0), axis='y')        
ax1.tick_params(axis='y', colors=plot_ax1.get_color(), **tkw)
ax2.tick_params(axis='y', colors=plot_ax2.get_color(), **tkw)

ax1.yaxis.get_offset_text().set_color(plot_ax1.get_color())
ax2.yaxis.get_offset_text().set_color(plot_ax2.get_color())

ax1.tick_params(axis='x', **tkw)

# Setting the legend
lines = [plot_ax1, plot_ax2]
ax1.legend(lines, [l.get_label() for l in lines],'upper left')

plt.show()