我认为你仍然需要MultipleLocator而不是LogLocator，因为你想要的刻度位置仍然是“on every integer that is multiple of base in the view interval”而不是“subs[j] * base**i”。例如：

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator

x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
y = [0.32, 0.30, 0.28, 0.26, 0.24, 0.22, 0.20, 0.18, 0.16, 0.14, 0.12, 0.10]
fig = plt.figure(figsize=(8, 12))
ax1 = fig.add_subplot(111)
x_major = MultipleLocator(4)
x_minor = MultipleLocator(1)
ax1.xaxis.set_major_locator(x_major)
ax1.xaxis.set_minor_locator(x_minor)
ax1.set_yscale("log")
# You would need to erase default major ticklabels
ax1.set_yticklabels(['']*len(ax1.get_yticklabels()))
y_major = MultipleLocator(0.1)
y_minor = MultipleLocator(0.01)
ax1.yaxis.set_major_locator(y_major)
ax1.yaxis.set_minor_locator(y_minor)
ax1.plot(x, y)
plt.show()

LogLocator始终将主记号标签放在“every base**i”处。因此，不可能将其用于所需的主要刻度标签。您可以使用参数subs作为次要刻度标签，如下所示：

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, LogLocator

x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
y = [0.32, 0.30, 0.28, 0.26, 0.24, 0.22, 0.20, 0.18, 0.16, 0.14, 0.12, 0.10]
fig = plt.figure()
ax1 = fig.add_subplot(111)
x_major = MultipleLocator(4)
x_minor = MultipleLocator(1)
ax1.xaxis.set_major_locator(x_major)
ax1.xaxis.set_minor_locator(x_minor)
ax1.set_yscale("log")
y_major = LogLocator(base=10)
y_minor = LogLocator(base=10, subs=[1.1, 1.2, 1.3])
ax1.yaxis.set_major_locator(y_major)
ax1.yaxis.set_minor_locator(y_minor)
ax1.plot(x, y)
plt.show()