Viewing angle control in Matplotlib - Step-by-Step Execution

Concept Flow - Viewing angle control

Create 3D plot

↓

Set viewing angle: azim, elev

↓

Render plot with new angle

↓

Visualize rotated 3D data

We create a 3D plot, set the viewing angles (azimuth and elevation), then render the plot to see the rotated view.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
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=30, azim=45)
plt.show()

This code creates a 3D scatter plot and sets the viewing angle to elevation 30° and azimuth 45°.

Execution Table

Step	Action	Parameter	Effect on View	Output
1	Create figure	fig = plt.figure()	Prepare canvas	Empty 3D plot ready
2	Add 3D subplot	ax = fig.add_subplot(111, projection='3d')	3D axes created	Axes ready for 3D data
3	Plot points	ax.scatter([1,2,3], [4,5,6], [7,8,9])	Points placed in 3D space	Points visible in default view
4	Set view angle	ax.view_init(elev=30, azim=45)	Rotate view to elev=30°, azim=45°	View changes to new angle
5	Show plot	plt.show()	Render plot window	3D scatter plot displayed with new angle
6	Exit	Plot window closed	End of visualization	Execution stops

💡 Plot window closed by user, ending visualization

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	Final
fig	None	Figure object created	Figure object created	Figure object created	Figure object created
ax	None	3D Axes object created	3D Axes with points plotted	3D Axes with view angle set	3D Axes with view angle set

Key Moments - 2 Insights

Why does changing azim and elev in view_init rotate the plot instead of moving the points?

Because view_init changes the camera angle, not the data coordinates. The points stay fixed; only the viewpoint changes (see execution_table step 4).

What happens if you call view_init before plotting points?

The view angle is set before points are drawn, so the final plot still shows points from that angle (the order does not affect the final view, see variable_tracker).

Visual Quiz - 3 Questions

Look at the execution table at step 4. What does ax.view_init(elev=30, azim=45) do?

A It changes the viewing angle of the plot

B It moves the points to new coordinates

C It changes the color of the points

D It creates a new figure

💡 Hint

Refer to the 'Effect on View' column in step 4 of the execution_table

According to variable_tracker, what is the state of 'ax' after step 3?

A 3D Axes object created

B 3D Axes with points plotted

C None

D 3D Axes with view angle set

💡 Hint

Check the 'ax' row under 'After Step 3' in variable_tracker

If you change elev to 90 in view_init, what will happen to the plot view?

A The plot will be viewed from the side

B The plot will be viewed from below

C The plot will be viewed from directly above

D The plot will not change

💡 Hint

Elevation controls vertical angle; 90 means looking straight down (see concept_flow)

Concept Snapshot

Viewing angle control in matplotlib 3D plots:
- Use ax.view_init(elev, azim) to set elevation and azimuth angles
- Elevation (elev) is vertical angle in degrees
- Azimuth (azim) is horizontal rotation in degrees
- Changes the camera view, not the data
- Call before plt.show() to see effect

Full Transcript

This lesson shows how to control the viewing angle of a 3D plot in matplotlib. We start by creating a figure and adding 3D axes. Then we plot points in 3D space. Using ax.view_init with elevation and azimuth angles, we rotate the camera view around the data. Finally, we render the plot with plt.show(). The points stay fixed; only the viewpoint changes. This helps us see the data from different angles easily.

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