Rcparams for global defaults in Matplotlib - Time & Space Complexity

Time Complexity: Rcparams for global defaults

O(n)

Understanding Time Complexity

We want to understand how changing global settings in matplotlib affects the time it takes to create plots.

Specifically, how does setting global defaults with rcParams impact performance as we make more plots?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt

plt.rcParams['lines.linewidth'] = 2
plt.rcParams['axes.titlesize'] = 'large'

for i in range(n):
    plt.plot([1, 2, 3], [i, i+1, i+2])
    plt.title(f'Plot {i}')
    plt.show()

This code sets global style defaults once, then creates and shows n plots using those defaults.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Loop creating and displaying n plots.
• How many times: n times, once per plot.

How Execution Grows With Input

Each plot creation and display takes roughly the same time, so total time grows as we add more plots.

Input Size (n)	Approx. Operations
10	10 plot creations and displays
100	100 plot creations and displays
1000	1000 plot creations and displays

Pattern observation: The total work grows linearly as the number of plots increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to run the code grows in direct proportion to the number of plots created.

Common Mistake

[X] Wrong: "Setting rcParams inside the loop will not affect performance."

[OK] Correct: Changing rcParams inside the loop repeats the global setting step each time, adding extra work and slowing down the process.

Interview Connect

Understanding how global settings affect repeated operations helps you write efficient plotting code and shows you can think about performance in real tasks.

Self-Check

"What if we set rcParams inside the loop before each plot? How would the time complexity change?"