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Image colormaps in Matplotlib - Cheat Sheet & Quick Revision

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Recall & Review
beginner
What is a colormap in image visualization?
A colormap is a set of colors used to map data values to colors in an image, helping to visualize data intensity or categories clearly.
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beginner
Name two common types of colormaps in matplotlib.
Two common types are 'Sequential' colormaps, which show a progression from low to high values, and 'Diverging' colormaps, which highlight deviation from a midpoint.
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beginner
How do you apply a colormap to an image in matplotlib?
Use the 'cmap' parameter in functions like imshow(), for example: plt.imshow(image, cmap='viridis').
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intermediate
What does the 'viridis' colormap represent?
'Viridis' is a popular sequential colormap that smoothly changes from dark blue to yellow, designed to be perceptually uniform and colorblind-friendly.
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intermediate
Why is choosing the right colormap important in data visualization?
The right colormap ensures data patterns are clear, prevents misinterpretation, and makes visualizations accessible to people with color vision differences.
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Which matplotlib function is commonly used to display an image with a colormap?
Aplot()
Bscatter()
Cimshow()
Dhist()
What type of colormap is best for data that diverges around a midpoint?
ADiverging
BRandom
CCategorical
DSequential
Which colormap is designed to be colorblind-friendly and perceptually uniform?
Ajet
Bviridis
Chot
Dcool
How do you specify a colormap when plotting an image in matplotlib?
Apalette='viridis'
Bcolor='viridis'
Cmap='viridis'
Dcmap='viridis'
What is the main purpose of using colormaps in image data?
ATo map data values to colors for better understanding
BTo reduce image size
CTo add random colors
DTo change image format
Explain what a colormap is and why it is useful in image visualization.
Think about how colors help show differences in data values.
You got /3 concepts.
    Describe how to apply a colormap to an image using matplotlib and name a popular colormap.
    Remember the function and parameter names.
    You got /3 concepts.

      Practice

      (1/5)
      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