Color mapping with colorbar in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this matplotlib color mapping code?

Consider the following code that creates a scatter plot with color mapping and a colorbar. What will be the color of the point at x=2, y=2?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.array([1, 2, 3, 4])
y = np.array([1, 2, 3, 4])
colors = np.array([10, 20, 30, 40])

plt.scatter(x, y, c=colors, cmap='viridis')
plt.colorbar()
plt.close()  # Close plot to avoid display in test

color_at_point = plt.cm.viridis((20 - 10) / (40 - 10))
print(color_at_point)

A [0.127568, 0.566949, 0.550556, 1.0]

B [0.229739, 0.322361, 0.545706, 1.0]

C [0.993248, 0.906157, 0.143936, 1.0]

D [0.267004, 0.004874, 0.329415, 1.0]

💡 Hint

The color mapping normalizes values between the minimum and maximum of the data array before applying the colormap.

The color value 20 is normalized between 10 (min) and 40 (max) as (20-10)/(40-10) = 0.3333. The viridis colormap at 0.3333 corresponds to the RGBA color approximately [0.127568, 0.566949, 0.550556, 1.0].

❓ data_output

intermediate

How many ticks will the colorbar show by default?

Given this code snippet that creates a scatter plot with a colorbar, how many tick marks will the colorbar display by default?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(5)
y = np.arange(5)
colors = np.array([5, 10, 15, 20, 25])

sc = plt.scatter(x, y, c=colors, cmap='plasma')
cbar = plt.colorbar(sc)
plt.close()

A 5

B 6

C 7

D 4

💡 Hint

Matplotlib colorbars by default show 6 ticks unless specified otherwise.

By default, matplotlib colorbars use 6 ticks to label the color scale, regardless of the number of points plotted.

❓ visualization

advanced

Which option produces a colorbar with discrete color segments?

You want to create a scatter plot with 4 distinct color segments in the colorbar, each representing a range of values. Which code snippet will produce this effect?

A

plt.scatter(x, y, c=colors, cmap='viridis')
plt.colorbar(ticks=[5, 10, 15, 20])

B

plt.scatter(x, y, c=colors, cmap='viridis', norm=plt.Normalize(vmin=5, vmax=20))
cbar = plt.colorbar(ticks=[5, 10, 15, 20])

C

plt.scatter(x, y, c=colors, cmap='viridis')
plt.colorbar(boundaries=[5, 10, 15, 20, 25])

D

from matplotlib.colors import BoundaryNorm
bounds = [5, 10, 15, 20, 25]
norm = BoundaryNorm(bounds, ncolors=256)
plt.scatter(x, y, c=colors, cmap='viridis', norm=norm)
plt.colorbar(ticks=bounds)

💡 Hint

Use BoundaryNorm to create discrete color segments matching boundaries.

BoundaryNorm with specified bounds creates discrete color segments. The colorbar ticks correspond to these boundaries, showing distinct color blocks.

🔧 Debug

advanced

What error does this code raise?

Examine this code that attempts to create a scatter plot with a colorbar. What error will it raise when run?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.array([1, 2, 3])
y = np.array([1, 2, 3])
colors = ['red', 'green', 'blue']

plt.scatter(x, y, c=colors, cmap='viridis')
plt.colorbar()
plt.close()

A AttributeError: 'list' object has no attribute 'shape'

B TypeError: Invalid RGBA argument

C ValueError: 'c' argument must be a sequence of numbers

D No error, plot displays correctly

💡 Hint

The 'c' parameter expects numeric values when a colormap is specified.

When using a colormap, the 'c' argument must be numeric. Passing color names as strings causes ValueError.

🚀 Application

expert

How to create a horizontal colorbar with label and custom ticks?

You want to create a scatter plot with a horizontal colorbar below the plot. The colorbar should have the label 'Intensity' and show ticks at 0, 0.5, and 1. Which code snippet achieves this?

A

sc = plt.scatter(x, y, c=colors, cmap='inferno')
cbar = plt.colorbar(sc, orientation='horizontal')
cbar.set_label('Intensity')
cbar.set_ticks([0, 0.5, 1])

B

sc = plt.scatter(x, y, c=colors, cmap='inferno')
cbar = plt.colorbar(sc)
cbar.set_label('Intensity')
cbar.set_ticks([0, 0.5, 1])

C

sc = plt.scatter(x, y, c=colors, cmap='inferno')
cbar = plt.colorbar(sc, orientation='horizontal')
cbar.set_label('Intensity')
cbar.set_ticks([1, 0.5, 0])

D

sc = plt.scatter(x, y, c=colors, cmap='inferno')
cbar = plt.colorbar(sc, orientation='vertical')
cbar.set_label('Intensity')
cbar.set_ticks([0, 0.5, 1])

💡 Hint

Set orientation='horizontal' in colorbar and use set_label and set_ticks methods.

Option A correctly sets the colorbar orientation to horizontal, adds the label 'Intensity', and sets ticks at 0, 0.5, and 1 in ascending order.