Image extent and aspect ratio in Matplotlib - Step-by-Step Execution

Concept Flow - Image extent and aspect ratio

Create image data

↓

Call imshow() with extent

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Set aspect ratio

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Render image on plot

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Display axes with adjusted limits and ratio

This flow shows how image data is created, displayed with a specified extent, and how the aspect ratio controls the shape of the image on the plot.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
import numpy as np
img = np.arange(16).reshape(4,4)
plt.imshow(img, extent=[0,4,0,2], aspect='auto')
plt.show()

This code creates a 4x4 image and displays it stretched to fit the extent [0,4] in x and [0,2] in y with automatic aspect ratio.

Execution Table

Step	Action	Parameter/Value	Effect on Plot	Result
1	Create image data	4x4 array with values 0 to 15	Image data ready	Image array created
2	Call imshow()	img, extent=[0,4,0,2], aspect='auto'	Image placed with x from 0 to 4, y from 0 to 2	Image stretched to fit extent
3	Set aspect ratio	'auto'	Image pixels scaled to fill extent area	Image shape distorted to fit axes limits
4	Render image	N/A	Image displayed on plot	Image visible with stretched shape
5	Show plot	plt.show()	Plot window opens	User sees image with specified extent and aspect

💡 Execution stops after plot window is displayed and user closes it.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
img	undefined	4x4 numpy array with values 0-15	Same array passed to imshow	Same array displayed with extent	Displayed image data unchanged
extent	undefined	undefined	[0,4,0,2]	Used to set axes limits	Axes limits set to extent
aspect	undefined	undefined	'auto'	Controls pixel scaling	Aspect ratio applied

Key Moments - 2 Insights

Why does the image look stretched when using extent with aspect='auto'?

Because aspect='auto' scales the image to fill the axes limits set by extent, the pixels are not forced to be square, causing stretching as shown in execution_table step 3.

What does the extent parameter control in imshow?

Extent sets the data limits for the image axes (x and y ranges), changing where the image is placed and how large it appears, as seen in execution_table step 2.

Visual Quiz - 3 Questions

Look at the execution table, what is the extent value used in step 2?

A [0,4,0,2]

B [0,2,0,4]

C [0,1,0,1]

D [1,4,1,2]

💡 Hint

Check the 'Parameter/Value' column in step 2 of the execution_table.

At which step does the image get stretched to fit the axes limits?

A Step 1

B Step 3

C Step 4

D Step 5

💡 Hint

Look at the 'Effect on Plot' column describing aspect ratio application.

If aspect='equal' was used instead of 'auto', how would the image shape change?

A Image would be stretched more

B Image would disappear

C Image pixels would be square, preserving shape

D Extent would be ignored

💡 Hint

Aspect ratio controls pixel scaling; 'equal' keeps pixels square.

Concept Snapshot

imshow(image, extent=[xmin,xmax,ymin,ymax], aspect='auto'|'equal')
- extent sets image axes limits
- aspect='auto' stretches image to fill extent
- aspect='equal' keeps pixel shape square
- Changing extent changes image size on plot
- Aspect ratio controls image distortion

Full Transcript

This lesson shows how matplotlib's imshow function uses the extent parameter to set the image's position and size on the plot axes. The aspect parameter controls whether the image pixels keep their shape or stretch to fill the axes. We create a 4x4 image array, display it with extent [0,4,0,2], and aspect='auto', which stretches the image to fill the rectangular area. The execution table traces each step from data creation to rendering. Key moments clarify why the image stretches and what extent does. The quiz tests understanding of extent values, when stretching happens, and the effect of aspect ratio settings.