Overlaying data on images in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to display an image using matplotlib.

Matplotlib

import matplotlib.pyplot as plt
import matplotlib.image as mpimg

img = mpimg.imread('image.png')
plt.[1](img)
plt.show()

Drag options to blanks, or click blank then click option'

Abar

Bplot

Cscatter

Dimshow

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.plot instead of plt.imshow

Trying to use plt.scatter for images

The imshow function is used to display images in matplotlib.

2fill in blank

medium

Complete the code to overlay a red circle on the image at coordinates (50, 50).

Matplotlib

import matplotlib.pyplot as plt
import matplotlib.patches as patches

fig, ax = plt.subplots()
ax.imshow(img)
circle = patches.Circle((50, 50), radius=10, color=[1], fill=False)
ax.add_patch(circle)
plt.show()

Drag options to blanks, or click blank then click option'

A'red'

B'yellow'

C'blue'

D'green'

Attempts:

3 left

💡 Hint

Common Mistakes

Using color names without quotes

Choosing a color other than red

The color 'red' is used to draw the circle in red.

3fill in blank

hard

Fix the error in the code to correctly overlay text on the image at position (100, 100).

Matplotlib

fig, ax = plt.subplots()
ax.imshow(img)
ax.text(100, 100, 'Hello', color=[1])
plt.show()

Drag options to blanks, or click blank then click option'

Ared

Bblue

C'red'

D'blue'

Attempts:

3 left

💡 Hint

Common Mistakes

Using color names without quotes causing errors

Using invalid color names

The color value must be a string in quotes, like 'red'.

4fill in blank

hard

Fill both blanks to create a scatter plot overlay on the image with blue points at x and y coordinates.

Matplotlib

fig, ax = plt.subplots()
ax.imshow(img)
ax.scatter([1], [2], color='blue')
plt.show()

Drag options to blanks, or click blank then click option'

Ax_coords

By_coords

Cimg

Dpoints

Attempts:

3 left

💡 Hint

Common Mistakes

Using the image variable instead of coordinate lists

Swapping x and y coordinates

The scatter plot needs x and y coordinate lists to plot points on the image.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each word to its length if the length is greater than 3.

Matplotlib

word_lengths = { [1]: [2] for [3] in words if len([3]) > 3 }

Drag options to blanks, or click blank then click option'

Aword

Blen(word)

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names inconsistently

Not using len() to get word length

The dictionary comprehension maps each word to its length using len(word). The loop variable is word.

Practice

1. What is the main purpose of using plt.imshow() in matplotlib when overlaying data on images?

easy

A. To save the plot as an image file

B. To display an image as the background for plotting data on top

C. To create a scatter plot of data points

D. To clear the current figure before plotting

Solution

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

   This function is used to display images in matplotlib, which can serve as a background for other plots.

2. Step 2: Identify its use in overlaying data

   By showing an image first, you can then plot data points or lines on top to combine visual and numeric information.

3. Final Answer:

   To display an image as the background for plotting data on top -> Option B

4. Quick Check:

   plt.imshow() shows images [OK]

Hint: Remember: imshow shows images, not plots [OK]

Common Mistakes:

• Confusing imshow with scatter plot functions
• Thinking imshow saves images
• Using imshow to clear figures

2. Which of the following is the correct way to overlay a red scatter plot on an image using matplotlib?

easy

A. plt.scatter(x, y)
plt.show()
plt.imshow(image)

B. plt.scatter(x, y, color='red')
plt.imshow(image)
plt.show()

C. plt.imshow(image)
plt.scatter(x, y, color='red')
plt.show()

D. plt.imshow(image, color='red')
plt.scatter(x, y)
plt.show()

Solution

1. Step 1: Order of plotting matters

   The image must be shown first with plt.imshow() so that scatter points appear on top.

2. Step 2: Correct syntax for scatter color

   Use color='red' inside plt.scatter() to make points red.

3. Final Answer:

   plt.imshow(image) then plt.scatter(x, y, color='red') -> Option C

4. Quick Check:

   Image first, then scatter with color [OK]

Hint: Show image before scatter to overlay correctly [OK]

Common Mistakes:

• Plotting scatter before image hides points
• Passing color to imshow instead of scatter
• Calling plt.show() too early

3. What will be the output of the following code?

import matplotlib.pyplot as plt
import numpy as np

image = np.zeros((5,5))
x = [1, 3]
y = [2, 4]

plt.imshow(image, cmap='gray')
plt.scatter(x, y, color='blue')
plt.show()

medium

A. A white 5x5 image with two blue points at coordinates (1,2) and (3,4)

B. An error because x and y coordinates are swapped

C. A black 5x5 image with two red points at coordinates (2,1) and (4,3)

D. A black 5x5 image with two blue points at coordinates (1,2) and (3,4)

Solution

1. Step 1: Understand the image array

   The image is a 5x5 array of zeros, so it appears black with cmap='gray'.

2. Step 2: Plot scatter points

   Points at (x=1, y=2) and (x=3, y=4) are plotted in blue on top of the image.

3. Final Answer:

   A black 5x5 image with two blue points at coordinates (1,2) and (3,4) -> Option D

4. Quick Check:

   Zeros = black image, scatter color blue [OK]

Hint: Remember: imshow shows array as image, scatter uses x,y coords [OK]

Common Mistakes:

• Confusing x and y coordinates
• Assuming zeros array is white
• Mixing up scatter point colors

4. The following code is intended to overlay a green line on an image, but the line does not appear. What is the error?

import matplotlib.pyplot as plt
import numpy as np

image = np.ones((10,10))
plt.imshow(image)
plt.plot([1, 8], [1, 8], color='green')
plt.show()

medium

A. The image is white and the green line is not visible due to default alpha

B. The plot command should be called before imshow

C. The color argument should be 'c' instead of 'color'

D. The coordinates for the line are outside the image bounds

Solution

1. Step 1: Analyze the image color

   The image is an array of ones, which appears white by default.

2. Step 2: Check line visibility

   A green line on a white background may be hard to see if the line is thin and no linewidth is set.

3. Final Answer:

   The image is white and the green line is not visible due to default alpha -> Option A

4. Quick Check:

   White background hides thin green line [OK]

Hint: Check background and line colors for visibility [OK]

Common Mistakes:

• Plotting line before image hides image
• Using wrong color argument name
• Assuming coordinates are out of bounds

5. You want to overlay a heatmap of data values on top of a grayscale image using matplotlib. Which approach correctly combines the image and heatmap with transparency so both are visible?

hard

A. plt.imshow(image, cmap='gray')
plt.imshow(data, cmap='hot', alpha=0.5)
plt.show()

B. plt.imshow(data, cmap='hot')
plt.imshow(image, cmap='gray', alpha=0.5)
plt.show()

C. plt.imshow(image, cmap='gray', alpha=0.5)
plt.imshow(data, cmap='hot')
plt.show()

D. plt.imshow(image, cmap='hot')
plt.imshow(data, cmap='gray', alpha=0.5)
plt.show()

Solution

1. Step 1: Display base grayscale image first

   Use plt.imshow(image, cmap='gray') to show the background image.

2. Step 2: Overlay heatmap with transparency

   Plot data with cmap='hot' and alpha=0.5 to make it semi-transparent over the image.

3. Final Answer:

   Show grayscale image first, then heatmap with alpha=0.5 -> Option A

4. Quick Check:

   Base image first, overlay with alpha [OK]

Hint: Show base image first, overlay heatmap with alpha transparency [OK]

Common Mistakes:

• Plotting heatmap before image hides heatmap
• Not using alpha causes full coverage
• Swapping colormaps between image and data