Image colormaps in Matplotlib - Mini Project: Build & Apply

Image colormaps

📖 Scenario: You are working with a grayscale image represented as a 2D array of pixel brightness values. You want to visualize this image using different color styles called colormaps to better understand the details.

🎯 Goal: Create a small 2D array representing a grayscale image, set a colormap name, apply the colormap to the image using matplotlib, and display the colored image.

📋 What You'll Learn

Create a 2D numpy array called image with the exact values [[0, 50, 100], [150, 200, 255]]

Create a variable called cmap_name and set it to the string 'viridis'

Use matplotlib's imshow function with the cmap parameter set to cmap_name to display the image

Use plt.colorbar() to show the color scale next to the image

Use plt.show() to display the final image

💡 Why This Matters

🌍 Real World

Scientists and engineers often use colormaps to visualize grayscale images such as medical scans, satellite photos, or heatmaps to better understand patterns and details.

💼 Career

Knowing how to apply colormaps is useful for data scientists and analysts who need to present image data clearly and effectively in reports and dashboards.

1

Create the grayscale image array

Create a 2D numpy array called image with these exact values: [[0, 50, 100], [150, 200, 255]]

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

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

Hint

Use np.array and pass the list of lists with the exact numbers.

2

Set the colormap name

Create a variable called cmap_name and set it to the string 'viridis'

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

image = np.array([[0, 50, 100], [150, 200, 255]])

# Set the colormap name to 'viridis'
# Your code here

Hint

Assign the string 'viridis' to the variable cmap_name.

3

Display the image with the colormap

Use plt.imshow with the image array and set the cmap parameter to cmap_name to display the colored image

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

image = np.array([[0, 50, 100], [150, 200, 255]])
cmap_name = 'viridis'

# Use plt.imshow to display the image with the colormap
# Your code here

Hint

Call plt.imshow with image and cmap=cmap_name.

4

Show the colorbar and display the image

Add plt.colorbar() to show the color scale and then call plt.show() to display the image

Matplotlib

import numpy as np
import matplotlib.pyplot as plt

image = np.array([[0, 50, 100], [150, 200, 255]])
cmap_name = 'viridis'

plt.imshow(image, cmap=cmap_name)

# Add plt.colorbar() and plt.show() below
# Your code here

Hint

Call plt.colorbar() before plt.show() to add the color scale.

Practice

1. What does the cmap parameter do in plt.imshow() when displaying an image?

easy

A. It changes how numbers map to colors in the image.

B. It changes the image size.

C. It adds a title to the image.

D. It saves the image to a file.

Solution

1. Step 1: Understand the role of cmap in plt.imshow()

   The cmap parameter controls the colormap, which maps numeric values to colors in the image.

2. Step 2: Identify what cmap affects visually

   Changing cmap changes the colors shown, helping interpret data better.

3. Final Answer:

   It changes how numbers map to colors in the image. -> Option A

4. Quick Check:

   Colormap = color mapping [OK]

Hint: Remember: cmap controls colors, not size or titles [OK]

Common Mistakes:

• Thinking cmap changes image size
• Confusing cmap with adding titles
• Assuming cmap saves the image

2. Which of the following is the correct way to apply the 'viridis' colormap to an image using matplotlib?

easy

A. plt.imshow(image, color='viridis')

B. plt.imshow(image, cmap='viridis')

C. plt.imshow(image, cmap=viridis)

D. plt.imshow(image, colormap='viridis')

Solution

1. Step 1: Recall the correct parameter name for colormap

   The parameter to set colormap in plt.imshow() is cmap, and it expects a string name.

2. Step 2: Check the syntax for passing the colormap

   Passing cmap='viridis' is correct. Using color or colormap is incorrect, and omitting quotes causes an error.

3. Final Answer:

   plt.imshow(image, cmap='viridis') -> Option B

4. Quick Check:

   Use cmap='name' syntax [OK]

Hint: Use cmap='colormap_name' exactly [OK]

Common Mistakes:

• Using color instead of cmap
• Forgetting quotes around colormap name
• Using colormap instead of cmap

3. What will the following code display?

import matplotlib.pyplot as plt
import numpy as np
image = np.array([[0, 1], [2, 3]])
plt.imshow(image, cmap='gray')
plt.colorbar()
plt.show()

medium

A. A 2x2 image with shades of gray from black (0) to white (3) and a colorbar showing values 0 to 3.

B. A 2x2 image with random colors and no colorbar.

C. A 2x2 image with rainbow colors and a colorbar showing values 0 to 1.

D. An error because 'gray' is not a valid colormap.

Solution

1. Step 1: Understand the image data and colormap

   The image is a 2x2 array with values 0 to 3. The 'gray' colormap maps low values to black and high values to white.

2. Step 2: Analyze the colorbar and display

   The colorbar shows the numeric range from 0 to 3, matching the image values. The image colors range from black (0) to white (3).

3. Final Answer:

   A 2x2 image with shades of gray from black (0) to white (3) and a colorbar showing values 0 to 3. -> Option A

4. Quick Check:

   Gray cmap maps 0-3 to black-white [OK]

Hint: Gray cmap means black to white shades [OK]

Common Mistakes:

• Thinking 'gray' is invalid
• Ignoring the colorbar range
• Assuming rainbow colors with 'gray'

4. The code below is intended to show an image with the 'hot' colormap and a colorbar, but it raises an error. What is the problem?

import matplotlib.pyplot as plt
import numpy as np
image = np.random.rand(3,3)
plt.imshow(image, cmap=hot)
plt.colorbar()
plt.show()

medium

A. plt.colorbar() must be called before plt.imshow().

B. The image array shape is invalid for imshow.

C. The colormap name 'hot' should be a string: cmap='hot'.

D. np.random.rand() cannot be used for images.

Solution

1. Step 1: Check the cmap parameter usage

   The colormap name must be a string. Here, hot is used without quotes, causing a NameError.

2. Step 2: Verify other code parts

   The image shape is valid, and colorbar usage is correct. np.random.rand() is valid for image data.

3. Final Answer:

   The colormap name 'hot' should be a string: cmap='hot'. -> Option C

4. Quick Check:

   Colormap names need quotes [OK]

Hint: Always put colormap names in quotes [OK]

Common Mistakes:

• Forgetting quotes around colormap name
• Thinking image shape is wrong
• Misordering colorbar and imshow

5. You have a 5x5 numpy array with values from 0 to 24. You want to display it using plt.imshow() with the 'coolwarm' colormap but only show colors for values between 5 and 20. Which code snippet correctly applies this?

hard

A. plt.imshow(data, cmap='coolwarm'); plt.colorbar(vmin=5, vmax=20)

B. plt.imshow(data, cmap='coolwarm', min=5, max=20); plt.colorbar()

C. plt.imshow(data, cmap='coolwarm', clip=(5,20)); plt.colorbar()

D. plt.imshow(data, cmap='coolwarm', vmin=5, vmax=20); plt.colorbar()

Solution

1. Step 1: Understand how to limit color range in imshow

   Use vmin and vmax parameters to set the data range for colormap scaling.

2. Step 2: Check each option for correct syntax

   plt.imshow(data, cmap='coolwarm', vmin=5, vmax=20); plt.colorbar() uses vmin=5 and vmax=20, which is correct. Other options use invalid parameters or place them incorrectly.

3. Final Answer:

   plt.imshow(data, cmap='coolwarm', vmin=5, vmax=20); plt.colorbar() -> Option D

4. Quick Check:

   Use vmin and vmax to clip colors [OK]

Hint: Use vmin and vmax to set color limits [OK]

Common Mistakes:

• Using min/max instead of vmin/vmax
• Trying to clip with non-existent parameters
• Passing vmin/vmax to colorbar instead of imshow