Matplotlib Tick Locators

Introduction

In this tutorial, we will learn how to define the position of ticks in a matplotlib plot using tick locators. Tick locators help to make plots more readable by defining the position of the ticks on the x and y-axes. We will cover different types of tick locators and how to implement them in a matplotlib plot.

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Skills Graph

Importing Libraries

The first step is to import the necessary libraries. We will be using matplotlib.pyplot and matplotlib.ticker.

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

Setting up the Plot

Next, we will set up the plot by creating a figure and an array of subplots. We will also define a setup function that sets up common parameters for the axes in the example.

fig, axs = plt.subplots(8, 1, figsize=(8, 6))

def setup(ax, title):
    """Set up common parameters for the Axes in the example."""
    ## only show the bottom spine
    ax.yaxis.set_major_locator(ticker.NullLocator())
    ax.spines[['left', 'right', 'top']].set_visible(False)

    ax.xaxis.set_ticks_position('bottom')
    ax.tick_params(which='major', width=1.00, length=5)
    ax.tick_params(which='minor', width=0.75, length=2.5)
    ax.set_xlim(0, 5)
    ax.set_ylim(0, 1)
    ax.text(0.0, 0.2, title, transform=ax.transAxes,
            fontsize=14, fontname='Monospace', color='tab:blue')

Defining the Null Locator

The null locator is a locator that does not place any ticks on the axis. We can define the null locator using ticker.NullLocator().

setup(axs[0], title="NullLocator()")
axs[0].xaxis.set_major_locator(ticker.NullLocator())
axs[0].xaxis.set_minor_locator(ticker.NullLocator())

Defining the Multiple Locator

The multiple locator is a locator that places ticks at regular intervals. We can define the multiple locator using ticker.MultipleLocator().

setup(axs[1], title="MultipleLocator(0.5, offset=0.2)")
axs[1].xaxis.set_major_locator(ticker.MultipleLocator(0.5, offset=0.2))
axs[1].xaxis.set_minor_locator(ticker.MultipleLocator(0.1))

Defining the Fixed Locator

The fixed locator is a locator that places ticks at fixed locations. We can define the fixed locator using ticker.FixedLocator().

setup(axs[2], title="FixedLocator([0, 1, 5])")
axs[2].xaxis.set_major_locator(ticker.FixedLocator([0, 1, 5]))
axs[2].xaxis.set_minor_locator(ticker.FixedLocator(np.linspace(0.2, 0.8, 4)))

Defining the Linear Locator

The linear locator is a locator that places ticks at regular intervals on a linear scale. We can define the linear locator using ticker.LinearLocator().

setup(axs[3], title="LinearLocator(numticks=3)")
axs[3].xaxis.set_major_locator(ticker.LinearLocator(3))
axs[3].xaxis.set_minor_locator(ticker.LinearLocator(31))

Defining the Index Locator

The index locator is a locator that places ticks at regular intervals on an index scale. We can define the index locator using ticker.IndexLocator().

setup(axs[4], title="IndexLocator(base=0.5, offset=0.25)")
axs[4].plot([0]*5, color='white')
axs[4].xaxis.set_major_locator(ticker.IndexLocator(base=0.5, offset=0.25))

Defining the Auto Locator

The auto locator is a locator that automatically places ticks at regular intervals. We can define the auto locator using ticker.AutoLocator().

setup(axs[5], title="AutoLocator()")
axs[5].xaxis.set_major_locator(ticker.AutoLocator())
axs[5].xaxis.set_minor_locator(ticker.AutoMinorLocator())

Defining the MaxN Locator

The MaxN locator is a locator that places a maximum number of ticks on the axis. We can define the MaxN locator using ticker.MaxNLocator().

setup(axs[6], title="MaxNLocator(n=4)")
axs[6].xaxis.set_major_locator(ticker.MaxNLocator(4))
axs[6].xaxis.set_minor_locator(ticker.MaxNLocator(40))

Defining the Log Locator

The log locator is a locator that places ticks at regular intervals on a logarithmic scale. We can define the log locator using ticker.LogLocator().

setup(axs[7], title="LogLocator(base=10, numticks=15)")
axs[7].set_xlim(10**3, 10**10)
axs[7].set_xscale('log')
axs[7].xaxis.set_major_locator(ticker.LogLocator(base=10, numticks=15))

Displaying the Plot

Finally, we can display the plot using plt.show().

plt.tight_layout()
plt.show()

Summary

In this tutorial, we learned how to define the position of ticks in a matplotlib plot using tick locators. We covered different types of tick locators and how to implement them in a matplotlib plot. This can help to make plots more readable and informative.