I know that this question has been asked before, but I tried all the possible solutions and none of them worked for me.
from numpy import array, log, pi
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import matplotlib.ticker as mticker
plt.rc('axes.formatter', useoffset=False)
tc = array([7499680.0, 12508380.0, 23858280.0, 34877020.0, 53970660.0, 89248580.0, 161032860.0, 326814160.0, 784460200.0])
theta = array([70, 60, 50, 45, 40, 35, 30, 25, 20])
plt.scatter(theta,tc)
ax=plt.gca()
ax.set_xscale('log')
ax.set_yscale('log')
ax.xaxis.set_major_formatter(mticker.ScalarFormatter())
ax.xaxis.get_major_formatter().set_scientific(False)
ax.xaxis.get_major_formatter().set_useOffset(False)
plt.show()
Those are minor ticks on the x-axis (ie they are not on integer powers of 10), not major ticks. matplotlib<\/code> automatically detemines if it should label the major or minor ticks - in this case because you don't have any major ticks displayed in the x range, the minor ticks are being labelled).
So, you need to use the
set_minor_formatter<\/code> method:
ax.xaxis.set_minor_formatter(mticker.ScalarFormatter())
The following can be used as a workaround ( original answer<\/a> ):
from matplotlib.ticker import StrMethodFormatter, NullFormatter
ax.yaxis.set_major_formatter(StrMethodFormatter('{x:.0f}'))
ax.yaxis.set_minor_formatter(NullFormatter())
If you want to set just the xaxis to no longer use scientific notation you need to change the fromatter and then you can set it to plain.
ax.xaxis.set_minor_formatter(mticker.ScalarFormatter())
ax.ticklabel_format(style='plain', axis='x')
如果你想同时禁用偏移量和科学记数法,你可以使用ax.ticklabel_format(useOffset=False, style='plain')<\/code>
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