How to show minor tick labels on a log-scale with Matplotlib?

In Matplotlib, displaying minor tick labels on a log-scale plot requires special formatting since log scales typically only show major ticks by default. We can achieve this by using the tick_params() method and FormatStrFormatter to control minor tick appearance.

Basic Log-Scale Plot with Minor Ticks

Here's how to create a log-scale plot and display minor tick labels ?

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter

# Set figure size
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create data points
x = np.linspace(-2, 2, 10)
y = np.exp(x)

# Plot the data
plt.plot(x, y)

# Get current axis and set log scale
ax = plt.gca()
ax.set_yscale('log')

# Enable minor tick labels and set formatter
plt.tick_params(axis='y', which='minor')
ax.yaxis.set_minor_formatter(FormatStrFormatter("%.1f"))

plt.show()

Step-by-Step Process

The key steps to show minor tick labels on a log-scale are ?

• Set the y-axis scale to logarithmic using set_yscale('log')
• Enable minor ticks with tick_params(axis='y', which='minor')
• Format minor tick labels using set_minor_formatter()
• Use FormatStrFormatter to specify the number format

Customizing Minor Tick Appearance

You can further customize the appearance of minor ticks ?

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter

# Create sample data
x = np.linspace(1, 100, 50)
y = x**2

plt.figure(figsize=(8, 6))
plt.plot(x, y, 'b-', linewidth=2)

ax = plt.gca()
ax.set_yscale('log')

# Customize minor tick appearance
plt.tick_params(axis='y', which='minor', labelsize=8, color='gray')
ax.yaxis.set_minor_formatter(FormatStrFormatter("%.0f"))

plt.xlabel('X values')
plt.ylabel('Y values (log scale)')
plt.title('Log Scale with Custom Minor Ticks')
plt.grid(True, which='both', alpha=0.3)

plt.show()

Key Parameters

Conclusion

To show minor tick labels on log-scale plots, use tick_params(which='minor') to enable them and set_minor_formatter() to control their appearance. This provides better readability for logarithmic data visualization.