我试图在matplotlib图中自定义次要刻度.请考虑以下代码：

import pylab as pl
from matplotlib.ticker import AutoMinorLocator

fig, ax = pl.subplots(figsize=(11., 7.4))

x = [1,2,3, 4]
y = [10, 45, 77, 55]
errorb = [20,66,58,11]

pl.xscale("log")

ax.xaxis.set_minor_locator(AutoMinorLocator(2))
ax.yaxis.set_minor_locator(AutoMinorLocator(2))

pl.tick_params(which='both', width=1)
pl.tick_params(which='minor', length=4, color='g')
pl.tick_params(axis ='both', which='major', length=8, labelsize =20, color='r' )

pl.errorbar(x, y, yerr=errorb)
#pl.plot(x, y)

pl.show()

据我所知,AutoMinorLocator(n)应该在每个主要刻度之间插入n个小刻度,这是在线性刻度上发生的,但根本无法弄清楚在日志刻度上放置次刻度的逻辑.最重要的是,当使用errorbar()然后使用简单的plot()时,有更多的小刻度.

最佳答案 AutoMinorLocator仅适用于线性比例：

从ticker documentation：

AutoMinorLocator

locator for minor ticks when the axis is linear and the major ticks are uniformly spaced. It subdivides the major tick interval into a specified number of minor intervals, defaulting to 4 or 5 depending on the major interval.

而AutoMinorLocator documentation：

Dynamically find minor tick positions based on the positions of major ticks. Assumes the scale is linear and major ticks are evenly spaced.

您可能希望将LogLocator用于您的目的.

例如,要将主刻度线放在基数10中,并将小标记放在第2点和第5点(或每个基数* i * [2,5]),您可以：

ax.xaxis.set_major_locator(LogLocator(base=10))
ax.xaxis.set_minor_locator(LogLocator(base=10,subs=[2.0,5.0]))
ax.yaxis.set_minor_locator(AutoMinorLocator(2))