Axes Zoom Effect: Mastering Matplotlib's Zoom Capabilities

Introduction

This tutorial will guide you on how to create a zoom effect using matplotlib. The zoom effect will allow you to connect and zoom in on two different axes.

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Importing Required Libraries

In this step, we will import the necessary libraries required for this tutorial. We will import matplotlib, and the relevant libraries from mpl_toolkits.axes_grid1.

import matplotlib.pyplot as plt

from matplotlib.transforms import (Bbox, TransformedBbox,
                                   blended_transform_factory)
from mpl_toolkits.axes_grid1.inset_locator import (BboxConnector,
                                                   BboxConnectorPatch,
                                                   BboxPatch)

Defining the Connection Between the Axes

In this step, we will define the connection between the two axes. This function takes in two axes as inputs, as well as the minimum and maximum values for the x-axis. It then creates a bounding box and connects the two axes.

def zoom_effect01(ax1, ax2, xmin, xmax, **kwargs):
    bbox = Bbox.from_extents(xmin, 0, xmax, 1)

    mybbox1 = TransformedBbox(bbox, ax1.get_xaxis_transform())
    mybbox2 = TransformedBbox(bbox, ax2.get_xaxis_transform())

    prop_patches = {**kwargs, "ec": "none", "alpha": 0.2}

    c1, c2, bbox_patch1, bbox_patch2, p = connect_bbox(
        mybbox1, mybbox2,
        loc1a=3, loc2a=2, loc1b=4, loc2b=1,
        prop_lines=kwargs, prop_patches=prop_patches)

    ax1.add_patch(bbox_patch1)
    ax2.add_patch(bbox_patch2)
    ax2.add_patch(c1)
    ax2.add_patch(c2)
    ax2.add_patch(p)

    return c1, c2, bbox_patch1, bbox_patch2, p

Creating the Second Zoomed Axis

In this step, we will create the second zoomed axis. This function takes in two axes as inputs. It then creates a bounding box for the second axis and connects it to the first axis.

def zoom_effect02(ax1, ax2, **kwargs):
    tt = ax1.transScale + (ax1.transLimits + ax2.transAxes)
    trans = blended_transform_factory(ax2.transData, tt)

    mybbox1 = ax1.bbox
    mybbox2 = TransformedBbox(ax1.viewLim, trans)

    prop_patches = {**kwargs, "ec": "none", "alpha": 0.2}

    c1, c2, bbox_patch1, bbox_patch2, p = connect_bbox(
        mybbox1, mybbox2,
        loc1a=3, loc2a=2, loc1b=4, loc2b=1,
        prop_lines=kwargs, prop_patches=prop_patches)

    ax1.add_patch(bbox_patch1)
    ax2.add_patch(bbox_patch2)
    ax2.add_patch(c1)
    ax2.add_patch(c2)
    ax2.add_patch(p)

    return c1, c2, bbox_patch1, bbox_patch2, p

Connecting the Axes

In this step, we will connect the axes and create the zoom effect. We will create a figure with four axes and connect them using the zoom_effect01 and zoom_effect02 functions.

axs = plt.figure().subplot_mosaic([
    ["zoom1", "zoom2"],
    ["main", "main"],
])

axs["main"].set(xlim=(0, 5))
zoom_effect01(axs["zoom1"], axs["main"], 0.2, 0.8)
axs["zoom2"].set(xlim=(2, 3))
zoom_effect02(axs["zoom2"], axs["main"])

plt.show()

Summary

In this tutorial, we learned how to create a zoom effect using matplotlib. We first defined a function to connect the axes, and then created a second function to create the second zoomed axis. Finally, we connected the axes and created the zoom effect.

Axes Zoom Effect