Viewing angle control in Matplotlib - Mini Project: Build & Apply

Viewing angle control

📖 Scenario: You are working with 3D data visualization to better understand shapes from different perspectives. Changing the viewing angle helps you see the data clearly.

🎯 Goal: You will create a 3D plot of a simple shape and learn how to control the viewing angle using matplotlib.

📋 What You'll Learn

Create 3D data points for a cube

Set up a viewing angle with elevation and azimuth

Plot the cube with the specified viewing angle

Display the plot

💡 Why This Matters

🌍 Real World

3D visualization helps engineers, scientists, and data analysts understand shapes and spatial data from different perspectives.

💼 Career

Knowing how to control viewing angles in 3D plots is useful for data visualization roles and any job involving 3D data analysis.

1

Create 3D data points for a cube

Create a list called cube_points containing these 8 tuples representing the corners of a cube: (0, 0, 0), (1, 0, 0), (1, 1, 0), (0, 1, 0), (0, 0, 1), (1, 0, 1), (1, 1, 1), (0, 1, 1).

Matplotlib

# Create the list cube_points with the 8 cube corner tuples
# Your code here

Hint

Use a list with tuples for each corner point.

2

Set viewing angle variables

Create two variables: elevation and azimuth. Set elevation to 30 and azimuth to 45.

Matplotlib

cube_points = [(0, 0, 0), (1, 0, 0), (1, 1, 0), (0, 1, 0), (0, 0, 1), (1, 0, 1), (1, 1, 1), (0, 1, 1)]
# Set elevation to 30 and azimuth to 45
# Your code here

Hint

Use simple variable assignments for elevation and azimuth angles.

3

Plot the cube with the viewing angle

Import matplotlib.pyplot as plt and Axes3D from mpl_toolkits.mplot3d. Create a 3D plot, unpack cube_points into x, y, and z lists, plot the points using ax.scatter, set the viewing angle using ax.view_init(elev=elevation, azim=azimuth).

Matplotlib

cube_points = [(0, 0, 0), (1, 0, 0), (1, 1, 0), (0, 1, 0), (0, 0, 1), (1, 0, 1), (1, 1, 1), (0, 1, 1)]
elevation = 30
azimuth = 45
# Import matplotlib and create 3D plot
# Unpack cube_points into x, y, z
# Plot points and set viewing angle
# Your code here

Hint

Use zip(*cube_points) to separate coordinates and ax.view_init to set the angle.

4

Display the 3D plot

Use plt.show() to display the 3D plot with the cube and the specified viewing angle.

Matplotlib

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

cube_points = [(0, 0, 0), (1, 0, 0), (1, 1, 0), (0, 1, 0), (0, 0, 1), (1, 0, 1), (1, 1, 1), (0, 1, 1)]
elevation = 30
azimuth = 45

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x, y, z = zip(*cube_points)
ax.scatter(x, y, z)
ax.view_init(elev=elevation, azim=azimuth)
# Show the plot
# Your code here

Hint

Use plt.show() to display the figure window.

Practice

1. What does the ax.view_init(elev, azim) function do in matplotlib 3D plots?

easy

A. It sets the vertical and horizontal viewing angles of the 3D plot.

B. It changes the color of the 3D plot.

C. It adds labels to the axes of the 3D plot.

D. It saves the 3D plot as an image file.

Solution

1. Step 1: Understand the function purpose

   The ax.view_init function is used to control the viewing angle of 3D plots in matplotlib.

2. Step 2: Identify parameters meaning

   The parameters elev and azim set the vertical and horizontal angles respectively.

3. Final Answer:

   It sets the vertical and horizontal viewing angles of the 3D plot. -> Option A

4. Quick Check:

   Viewing angle control = ax.view_init(elev, azim) [OK]

Hint: Remember elev = vertical, azim = horizontal angles [OK]

Common Mistakes:

• Confusing view_init with color or label functions
• Mixing up elev and azim parameters
• Thinking it saves the plot instead of changing view

2. Which of the following is the correct syntax to set the elevation to 30 and azimuth to 45 in a matplotlib 3D plot?

easy

A. ax.view_init(azim=30, elev=45)

B. ax.view_init(elev=45, azim=30)

C. ax.view_init(45, 30)

D. ax.view_init(30, 45)

Solution

1. Step 1: Recall parameter order in view_init

   The view_init method takes elev first, then azim.

2. Step 2: Match values to parameters

   Elevation should be 30 and azimuth 45, so ax.view_init(30, 45) is correct.

3. Final Answer:

   ax.view_init(30, 45) -> Option D

4. Quick Check:

   elev=30, azim=45 means ax.view_init(30, 45) [OK]

Hint: Remember order: elev first, then azim [OK]

Common Mistakes:

• Swapping elev and azim values
• Using keyword arguments incorrectly
• Passing azim before elev

3. What will be the effect of this code snippet on the 3D plot's view?

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.view_init(elev=90, azim=0)
plt.show()

medium

A. The plot is viewed from the side at 90 degrees azimuth.

B. The plot is viewed from directly above (top-down view).

C. The plot is viewed from the front with default angles.

D. The plot will raise an error due to invalid angles.

Solution

1. Step 1: Analyze elev=90 effect

   Elevation of 90 degrees means the camera is directly above the plot looking down.

2. Step 2: Analyze azim=0 effect

   Azimuth 0 means no horizontal rotation, so the view is straight down from above.

3. Final Answer:

   The plot is viewed from directly above (top-down view). -> Option B

4. Quick Check:

   elev=90 means top-down view [OK]

Hint: elev=90 means looking straight down [OK]

Common Mistakes:

• Thinking azim=0 changes vertical angle
• Assuming default view instead of top-down
• Believing this causes an error

4. Identify the error in this code that tries to set the viewing angle:

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.view_init(azim=45, elev=30)
plt.show()

medium

A. The projection='3d' is missing in add_subplot.

B. The plt.show() is missing parentheses.

C. The parameters elev and azim are swapped; elev must come first without keywords.

D. There is no error; the code runs correctly.

Solution

1. Step 1: Check parameter usage in view_init

   The view_init method does not accept keyword arguments for elev and azim in this order; it expects positional arguments.

2. Step 2: Identify correct parameter order

   Correct usage is ax.view_init(30, 45) where elev=30 and azim=45 as positional arguments.

3. Final Answer:

   The parameters elev and azim are swapped; elev must come first without keywords. -> Option C

4. Quick Check:

   view_init requires positional elev, azim [OK]

Hint: Use positional args: elev first, azim second [OK]

Common Mistakes:

• Using keyword arguments in wrong order
• Omitting projection='3d' (not the error here)
• Forgetting plt.show() parentheses

5. You want to create a 3D scatter plot and set the view so the plot looks rotated 45 degrees horizontally and tilted 30 degrees vertically. Which code snippet correctly achieves this and also labels the axes?

hard

A. fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter([1,2,3], [4,5,6], [7,8,9])
ax.view_init(30, 45)
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.set_zlabel('Z axis')
plt.show()

B. fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter([1,2,3], [4,5,6], [7,8,9])
ax.view_init(45, 30)
plt.show()

C. fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter([1,2,3], [4,5,6], [7,8,9])
ax.view_init(elev=45, azim=30)
plt.show()

D. fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter([1,2,3], [4,5,6], [7,8,9])
ax.view_init(45, 30)
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.set_zlabel('Z axis')
plt.show()

Solution

1. Step 1: Check subplot creation for 3D

   Only options A, C, and D use projection='3d', which is required for 3D plots.

2. Step 2: Verify view_init parameters

   The question wants elevation 30 and azimuth 45, so ax.view_init(30, 45) is correct. fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.scatter([1,2,3], [4,5,6], [7,8,9]) ax.view_init(30, 45) ax.set_xlabel('X axis') ax.set_ylabel('Y axis') ax.set_zlabel('Z axis') plt.show() matches this.

3. Step 3: Confirm axis labels are set

   fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.scatter([1,2,3], [4,5,6], [7,8,9]) ax.view_init(30, 45) ax.set_xlabel('X axis') ax.set_ylabel('Y axis') ax.set_zlabel('Z axis') plt.show() sets all three axis labels correctly with set_xlabel, set_ylabel, and set_zlabel.

4. Final Answer:

   Option A correctly sets view angles and labels axes. -> Option A

5. Quick Check:

   3D plot + view_init(30,45) + axis labels = fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.scatter([1,2,3], [4,5,6], [7,8,9]) ax.view_init(30, 45) ax.set_xlabel('X axis') ax.set_ylabel('Y axis') ax.set_zlabel('Z axis') plt.show() [OK]

Hint: Use projection='3d', view_init(30,45), then label axes [OK]

Common Mistakes:

• Missing projection='3d' for 3D plots
• Swapping elev and azim values
• Not labeling all three axes