Matplotlib Logarithmic Axis Plotting Tutorial

Introduction

This step-by-step tutorial will guide you through the process of creating plots with logarithmic axes using Python Matplotlib. This tutorial will cover the following topics:

Semilogy Plot
Semilogx Plot
Loglog Plot
Errorbars Plot

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Semilogy Plot

The semilogy plot is a plot with a logarithmic scale on the y-axis. It is useful for visualizing data that has a large range of values.

import matplotlib.pyplot as plt
import numpy as np

## Data for plotting
t = np.arange(0.01, 20.0, 0.01)

## Create figure
fig, ax1 = plt.subplots()

## Plot data on semilogy plot
ax1.semilogy(t, np.exp(-t / 5.0))

## Add title and grid to plot
ax1.set(title='Semilogy Plot')
ax1.grid()

## Display plot
plt.show()

Semilogx Plot

The semilogx plot is a plot with a logarithmic scale on the x-axis. It is useful for visualizing data that has a large range of values on the x-axis.

import matplotlib.pyplot as plt
import numpy as np

## Data for plotting
t = np.arange(0.01, 20.0, 0.01)

## Create figure
fig, ax2 = plt.subplots()

## Plot data on semilogx plot
ax2.semilogx(t, np.sin(2 * np.pi * t))

## Add title and grid to plot
ax2.set(title='Semilogx Plot')
ax2.grid()

## Display plot
plt.show()

Loglog Plot

The loglog plot is a plot with a logarithmic scale on both the x-axis and y-axis. It is useful for visualizing data that has a large range of values on both axes.

import matplotlib.pyplot as plt
import numpy as np

## Data for plotting
t = np.arange(0.01, 20.0, 0.01)

## Create figure
fig, ax3 = plt.subplots()

## Plot data on loglog plot
ax3.loglog(t, 20 * np.exp(-t / 10.0))

## Set x-axis scale to base 2
ax3.set_xscale('log', base=2)

## Add title and grid to plot
ax3.set(title='Loglog Plot')
ax3.grid()

## Display plot
plt.show()

Errorbars Plot

The errorbars plot is a plot that shows error bars for each data point. If a data point has a negative value, it will be clipped to 0.1.

import matplotlib.pyplot as plt
import numpy as np

## Data for plotting
x = 10.0**np.linspace(0.0, 2.0, 20)
y = x**2.0

## Create figure
fig, ax4 = plt.subplots()

## Set x-axis and y-axis to logarithmic scale
ax4.set_xscale("log", nonpositive='clip')
ax4.set_yscale("log", nonpositive='clip')

## Plot data with error bars
ax4.errorbar(x, y, xerr=0.1 * x, yerr=5.0 + 0.75 * y)

## Set title and y-axis limit
ax4.set(title='Errorbars Plot')
ax4.set_ylim(bottom=0.1)

## Display plot
plt.show()

Summary

Python Matplotlib is a powerful tool for creating data visualizations. This tutorial covered how to create plots with logarithmic axes using semilogy, semilogx, loglog, and errorbars plots. By using these types of plots, you can effectively visualize data that has a large range of values.

Matplotlib Logarithmic Axis Plotting