Image extent and aspect ratio in Matplotlib - Mini Project: Build & Apply

Image extent and aspect ratio

📖 Scenario: You are working with images in data science and want to control how an image is displayed on a plot. Sometimes, you want to change the size and shape of the image on the plot by adjusting its extent and aspect ratio.

🎯 Goal: You will load a simple image as a 2D array, then plot it using matplotlib. You will set the image extent to control its position and size on the plot, and adjust the aspect ratio to control how the image scales.

📋 What You'll Learn

Create a 2D numpy array representing an image

Define an extent variable to control image boundaries on the plot

Use matplotlib's imshow with the extent and aspect parameters

Print or display the final plot showing the image with the specified extent and aspect ratio

💡 Why This Matters

🌍 Real World

In data science, controlling image extent and aspect ratio helps when visualizing images alongside other data or fitting images into specific plot areas.

💼 Career

Data scientists often need to customize image plots for reports, presentations, or dashboards to communicate insights clearly.

1

Create a 2D image array

Create a 2D numpy array called image with these exact values: [[1, 2], [3, 4]].

Matplotlib

# Create the 2D numpy array called image
# Your code here

Hint

Use np.array to create the 2D array with the exact values.

2

Define the image extent

Create a variable called extent and set it to the list [0, 4, 0, 2] to control the image boundaries on the plot.

Matplotlib

import numpy as np
image = np.array([[1, 2], [3, 4]])
# Define the extent list for the image
# Your code here

Hint

The extent list has four numbers: left, right, bottom, top.

3

Plot the image with extent and aspect ratio

Use matplotlib.pyplot.imshow to plot the image with the extent variable and set aspect='auto'.

Matplotlib

import numpy as np
import matplotlib.pyplot as plt
image = np.array([[1, 2], [3, 4]])
extent = [0, 4, 0, 2]
# Plot the image with extent and aspect='auto'
# Your code here

Hint

Use plt.imshow with the extent and aspect parameters.

4

Display the plot

Use plt.show() to display the image plot with the specified extent and aspect ratio.

Matplotlib

import numpy as np
import matplotlib.pyplot as plt
image = np.array([[1, 2], [3, 4]])
extent = [0, 4, 0, 2]
plt.imshow(image, extent=extent, aspect='auto')
# Display the plot
# Your code here

Hint

Call plt.show() to open the plot window.

Practice

1. What does the extent parameter control when displaying an image with matplotlib.pyplot.imshow()?

easy

A. The color map used for the image

B. The position and size of the image on the plot axes

C. The resolution of the image

D. The file format of the image

Solution

1. Step 1: Understand the role of extent

   The extent parameter defines the bounding box in data coordinates that the image will fill on the axes.

2. Step 2: Compare with other options

   Color map, resolution, and file format are unrelated to extent. They control different aspects of image display or file handling.

3. Final Answer:

   The position and size of the image on the plot axes -> Option B

4. Quick Check:

   Extent = position and size [OK]

Hint: Extent sets image box on axes, not colors or file type [OK]

Common Mistakes:

• Confusing extent with color map
• Thinking extent changes image resolution
• Assuming extent controls file format

2. Which of the following is the correct way to keep the image aspect ratio fixed when using imshow()?

easy

A. plt.imshow(img, aspect='equal')

B. plt.imshow(img, cmap='gray')

C. plt.imshow(img, extent=[0,1,0,1])

D. plt.imshow(img, aspect='auto')

Solution

1. Step 1: Identify aspect ratio options

   The aspect parameter controls image stretching. 'equal' keeps the aspect ratio fixed.

2. Step 2: Check other options

   'auto' allows stretching, extent sets position, and cmap sets colors, not aspect ratio.

3. Final Answer:

   plt.imshow(img, aspect='equal') -> Option A

4. Quick Check:

   Aspect='equal' fixes ratio [OK]

Hint: Use aspect='equal' to keep image shape correct [OK]

Common Mistakes:

• Using aspect='auto' which stretches image
• Confusing extent with aspect ratio
• Setting cmap instead of aspect

3. What will be the effect of this code snippet?

import matplotlib.pyplot as plt
import numpy as np
img = np.ones((10, 20))
plt.imshow(img, extent=[0, 5, 0, 10], aspect='auto')
plt.show()

medium

A. Image will be shown with default extent and fixed aspect ratio

B. Image will keep original shape and size ignoring extent

C. Code will raise an error due to wrong extent format

D. Image will stretch to fill x from 0 to 5 and y from 0 to 10, possibly distorted

Solution

1. Step 1: Analyze extent parameter

   The extent=[0,5,0,10] sets the image to cover x-axis 0 to 5 and y-axis 0 to 10 on the plot.

2. Step 2: Analyze aspect='auto'

   Aspect='auto' allows the image to stretch to fill the extent box, so the image shape may distort.

3. Final Answer:

   Image will stretch to fill x from 0 to 5 and y from 0 to 10, possibly distorted -> Option D

4. Quick Check:

   Extent sets size, aspect='auto' allows stretch [OK]

Hint: Extent sets size; aspect='auto' allows distortion [OK]

Common Mistakes:

• Assuming extent is ignored
• Expecting fixed aspect ratio with aspect='auto'
• Thinking code raises error

4. Identify the error in this code that tries to display an image with fixed aspect ratio:

import matplotlib.pyplot as plt
import numpy as np
img = np.random.rand(5,5)
plt.imshow(img, extent=[0,5,0], aspect='equal')
plt.show()

medium

A. The aspect='equal' is invalid and causes error

B. The image array shape is incompatible with imshow

C. The extent list has incorrect length; it should have 4 values

D. Missing plt.axis('equal') to fix aspect ratio

Solution

1. Step 1: Check extent parameter format

   Extent must be a list of 4 numbers: [xmin, xmax, ymin, ymax]. Here it has only 3 values, causing an error.

2. Step 2: Verify other parameters

   Aspect='equal' is valid. Image shape is fine. plt.axis('equal') is optional when aspect is set.

3. Final Answer:

   The extent list has incorrect length; it should have 4 values -> Option C

4. Quick Check:

   Extent needs 4 numbers [OK]

Hint: Extent must have 4 numbers: xmin, xmax, ymin, ymax [OK]

Common Mistakes:

• Using extent with less than 4 values
• Confusing aspect parameter validity
• Thinking plt.axis('equal') is required

5. You want to overlay a heatmap image on a scatter plot with x values from 0 to 10 and y values from 0 to 5. Which extent and aspect settings correctly align the image without distortion?

hard

A. extent=[0,10,0,5], aspect='equal'

B. extent=[0,5,0,10], aspect='auto'

C. extent=[0,10,0,5], aspect='auto'

D. extent=[0,5,0,10], aspect='equal'

Solution

1. Step 1: Match extent to data range

   The scatter plot x ranges 0-10 and y ranges 0-5, so extent must be [0,10,0,5] to align image correctly.

2. Step 2: Choose aspect to avoid distortion

   Aspect='equal' keeps the image shape correct, preventing distortion when overlaying.

3. Final Answer:

   extent=[0,10,0,5], aspect='equal' -> Option A

4. Quick Check:

   Extent matches data, aspect='equal' fixes shape [OK]

Hint: Match extent to data limits and use aspect='equal' [OK]

Common Mistakes:

• Swapping x and y in extent
• Using aspect='auto' causing distortion
• Ignoring data range when setting extent