In python's matplotlib, how can I make the logarithm x-axis ticks as the attached picture shows (i.e., major ticks with labels at every 0.5 spacing from 1 to 4.5; minor ticks without labels at every 0.1 spacing):
I've tried some methods such as
ax1.set_xticks([1.5,2,2.5,3,3.5,4,4.5])
ax1.xaxis.set_major_formatter(FormatStrFormatter('%.1f'))
ax1.xaxis.set_minor_locator(LogLocator(base=1,subs=(0.1,)))
But it doesn't give me the right solution.
You can set the location of the ticks using a MultipleLocator. You can set a different multiple for the major and minor ticks using ax.xaxis.set_major_locator and ax.xaxis.set_minor_locator.
As for the formatting of the tick labels: you can set the major tick format using ax.xaxis.set_major_formatter with a ScalarFormatter and turn off the minor tick labels using ax.xaxis.set_minor_formatter with a NullFormatter.
For example:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
# set the xaxis to a logarithmic scale
ax.set_xscale('log')
# set the desired axis limits
ax.set_xlim(1, 4.5)
# set the spacing of the major ticks to 0.5
ax.xaxis.set_major_locator(plt.MultipleLocator(0.5))
# set the format of the major tick labels
ax.xaxis.set_major_formatter(plt.ScalarFormatter())
# set the spacing of the minor ticks to 0.1
ax.xaxis.set_minor_locator(plt.MultipleLocator(0.1))
# turn off the minor tick labels
ax.xaxis.set_minor_formatter(plt.NullFormatter())
plt.show()
import numpy as np
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.semilogx()
a, b = 1, 4.5
step_minor, step_major = 0.1, 0.5
minor_xticks = np.arange(a, b + step_minor, step_minor)
ax.set_xticks(minor_xticks, minor=True)
ax.set_xticklabels(["" for _ in minor_xticks], minor=True)
xticks = np.arange(a, b + step_major, step_major)
ax.set_xticks(xticks)
ax.set_xticklabels(xticks)
ax.set_xlim([a, b])
plt.show()
ax.semilogx() is a plotting function (i.e. analogous to ax.plot()), which also sets the scale of the x-axis to logarithmic. If all you want to do is change the x-axis scale, there is a dedicated function for that: ax.set_xscale('log')