Creating Inset Zoomed Plots in Matplotlib for Detailed Comparison

When comparing experiments, it is often necessary to zoom into a specific region of a plot to observe finer details.

Tool : Python's Matplotlib library.

Steps :

1. Import dependencies

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
from matplotlib.patches import ConnectionPatch

2. Prepare data

The reward array reward_demaddpg[] stores 300 reward results from the DEMADDPG algorithm. The x‑axis is set up as:

MAX_EPISODES = 300
x_axis_data = []
for l in range(MAX_EPISODES):
    x_axis_data.append(l)

Five reward series corresponding to different learning rates are plotted.

3. Plot the main figure

fig, ax = plt.subplots(1, 1)
ax.plot(x_axis_data, reward_demaddpg5, color='#4169E1', alpha=0.8, label='$1*10^{-5}$')
ax.plot(x_axis_data, reward_demaddpg10, color='#848484', alpha=0.8, label='$5*10^{-6}$')
ax.plot(x_axis_data, reward_demaddpg15, color='#FF774A', alpha=0.8, label='$1*10^{-6}$')
ax.plot(x_axis_data, reward_demaddpg20, color='#575B20', alpha=0.8, label='$5*10^{-7}$')
ax.plot(x_axis_data, reward_demaddpg25, color='#B84D37', alpha=0.8, label='$1*10^{-7}$')
ax.legend(loc="lower right")
ax.set_xlabel('Episodes')
ax.set_ylabel('Total reward')

4. Embed an inset axes for the zoomed region

axins = inset_axes(ax, width="40%", height="30%", loc='lower left',
                   bbox_to_anchor=(0.3, 0.1, 1, 1),
                   bbox_transform=ax.transAxes)

The parameters are explained: ax is the parent axes, width and height define the size of the inset, loc its position, bbox_to_anchor the bounding box, and bbox_transform the coordinate transformation.

A more concise way to create the inset is:

axins = ax.inset_axes((0.2, 0.2, 0.4, 0.3))

5. Plot the same data inside the inset

axins.plot(x_axis_data, reward_demaddpg5, color='#4169E1', alpha=0.8, label='$1*10^{-5}$')
axins.plot(x_axis_data, reward_demaddpg10, color='#848484', alpha=0.8, label='$5*10^{-6}$')
axins.plot(x_axis_data, reward_demaddpg15, color='#FF774A', alpha=0.8, label='$1*10^{-6}$')
axins.plot(x_axis_data, reward_demaddpg20, color='#575B20', alpha=0.8, label='$5*10^{-7}$')
axins.plot(x_axis_data, reward_demaddpg25, color='#B84D37', alpha=0.8, label='$1*10^{-7}$')

6. Set the zoomed region limits

# Set zoom region
zone_left = 100
zone_right = 150

# Axis expansion ratios
x_ratio = 0
y_ratio = 0.05

xlim0 = x_axis_data[zone_left]-(x_axis_data[zone_right]-x_axis_data[zone_left])*x_ratio
xlim1 = x_axis_data[zone_right]+(x_axis_data[zone_right]-x_axis_data[zone_left])*x_ratio

y = np.hstack((reward_demaddpg5[zone_left:zone_right],
               reward_demaddpg10[zone_left:zone_right],
               reward_demaddpg15[zone_left:zone_right],
               reward_demaddpg20[zone_left:zone_right],
               reward_demaddpg25[zone_left:zone_right]))
ylim0 = np.min(y)-(np.max(y)-np.min(y))*y_ratio
ylim1 = np.max(y)+(np.max(y)-np.min(y))*y_ratio

axins.set_xlim(xlim0, xlim1)
axins.set_ylim(ylim0, ylim1)

7. Connect the inset with the main plot using ConnectionPatch

# Draw rectangle on main plot
tx0 = xlim0
tx1 = xlim1
ty0 = ylim0
ty1 = ylim1
sx = [tx0, tx1, tx1, tx0, tx0]
sy = [ty0, ty0, ty1, ty1, ty0]
ax.plot(sx, sy, "black")

# Draw connecting lines
xy = (xlim0, ylim0)
xy2 = (xlim0, ylim1)
con = ConnectionPatch(xyA=xy2, xyB=xy, coordsA="data", coordsB="data",
                      axesA=axins, axesB=ax)
axins.add_artist(con)

xy = (xlim1, ylim0)
xy2 = (xlim1, ylim1)
con = ConnectionPatch(xyA=xy2, xyB=xy, coordsA="data", coordsB="data",
                      axesA=axins, axesB=ax)
axins.add_artist(con)

The rectangle and connecting lines highlight the zoomed area, and the final figure shows the main curve with an enlarged inset.

This method provides a simple way to create detailed zoomed sub‑plots in Matplotlib.