Figure size for publication in Matplotlib - Time & Space Complexity

Time Complexity: Figure size for publication

O(width * height)

Understanding Time Complexity

When creating figures for publication, setting the figure size affects how matplotlib draws the image.

We want to understand how the time to create a figure changes as the figure size changes.

Scenario Under Consideration

Analyze the time complexity of this matplotlib code snippet.

import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(width, height))
ax.plot(x, y)
plt.savefig('figure.png')
plt.close(fig)

This code creates a figure with a given size, plots data, saves the image, and closes the figure.

Identify Repeating Operations

Look for operations that repeat or scale with input.

• Primary operation: Drawing pixels to fill the figure area.
• How many times: Proportional to the number of pixels, which depends on width x height.

How Execution Grows With Input

The time to draw the figure grows as the figure size increases because more pixels need to be processed.

Input Size (width x height)	Approx. Operations
100 x 100 = 10,000	10,000 pixel operations
200 x 200 = 40,000	40,000 pixel operations
500 x 500 = 250,000	250,000 pixel operations

Pattern observation: Doubling width and height quadruples the number of pixels and work.

Final Time Complexity

Time Complexity: O(width * height)

This means the time to create and save the figure grows roughly with the total number of pixels in the figure.

Common Mistake

[X] Wrong: "The figure size does not affect how long it takes to create the plot."

[OK] Correct: Larger figures have more pixels to draw, so they take more time to render and save.

Interview Connect

Understanding how figure size affects drawing time helps you manage performance when creating visuals for reports or presentations.

Self-Check

What if we add many data points to the plot? How would the time complexity change?