我将添加一些图并展示如何删除次要刻度:
OP:
from matplotlib import pyplot as plt
fig1, ax1 = plt.subplots()
ax1.plot([10, 100, 1000], [1,2,3])
ax1.set_xscale('log')
ax1.set_xticks([20, 300, 500])
plt.show()
要添加一些特定的刻度,正如tcaswell 指出的那样,您可以使用matplotlib.ticker.ScalarFormatter:
from matplotlib import pyplot as plt
import matplotlib.ticker
fig1, ax1 = plt.subplots()
ax1.plot([10, 100, 1000], [1,2,3])
ax1.set_xscale('log')
ax1.set_xticks([20, 300, 500])
ax1.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())
plt.show()
要删除次要刻度,您可以使用matplotlib.rcParams['xtick.minor.size']:
from matplotlib import pyplot as plt
import matplotlib.ticker
matplotlib.rcParams['xtick.minor.size'] = 0
matplotlib.rcParams['xtick.minor.width'] = 0
fig1, ax1 = plt.subplots()
ax1.plot([10, 100, 1000], [1,2,3])
ax1.set_xscale('log')
ax1.set_xticks([20, 300, 500])
ax1.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())
plt.show()
你可以改用ax1.get_xaxis().set_tick_params,它有同样的效果(但只修改当前轴,不像matplotlib.rcParams那样修改所有未来的数字):
from matplotlib import pyplot as plt
import matplotlib.ticker
fig1, ax1 = plt.subplots()
ax1.plot([10, 100, 1000], [1,2,3])
ax1.set_xscale('log')
ax1.set_xticks([20, 300, 500])
ax1.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())
ax1.get_xaxis().set_tick_params(which='minor', size=0)
ax1.get_xaxis().set_tick_params(which='minor', width=0)
plt.show()