Unequal subplot sizes in Matplotlib - Time & Space Complexity
We want to understand how the time to create plots changes when we use subplots of different sizes in matplotlib.
How does the number and size of subplots affect the work matplotlib does?
Analyze the time complexity of the following code snippet.
import matplotlib.pyplot as plt
fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.1, 0.6, 0.8]) # Large subplot
ax2 = fig.add_axes([0.75, 0.1, 0.2, 0.3]) # Smaller subplot
ax1.plot(range(100))
ax2.plot(range(50))
plt.show()
This code creates a figure with two subplots of different sizes and plots data on each.
Identify the loops, recursion, array traversals that repeat.
- Primary operation: Plotting data points on each subplot.
- How many times: Once per data point in each subplot (100 points in first, 50 in second).
As the number of points to plot increases, the work grows roughly in direct proportion.
| Input Size (n) | Approx. Operations |
|---|---|
| 10 | About 10 operations per subplot |
| 100 | About 100 operations per subplot |
| 1000 | About 1000 operations per subplot |
Pattern observation: Doubling the number of points roughly doubles the work needed to plot.
Time Complexity: O(n)
This means the time to draw the plots grows linearly with the number of points plotted.
[X] Wrong: "Making one subplot bigger will make the whole plotting time much slower regardless of data size."
[OK] Correct: The size of the subplot affects drawing area but the main time cost comes from how many data points are plotted, not the subplot size alone.
Understanding how plotting time grows helps you explain performance in data visualization tasks clearly and confidently.
"What if we added a third subplot with twice as many points as the largest one? How would the time complexity change?"
Practice
matplotlib?Solution
Step 1: Understand subplot size purpose
Unequal subplot sizes allow some plots to be larger, drawing more attention.Step 2: Compare options
Only To highlight important charts by giving them more space mentions highlighting important charts by size, which is the main advantage.Final Answer:
To highlight important charts by giving them more space -> Option CQuick Check:
Unequal sizes highlight key charts [OK]
- Thinking all subplots must be equal size
- Confusing size with color or number of plots
- Assuming unequal sizes reduce charts
gridspec_kw in plt.subplots()?Solution
Step 1: Identify correct parameter for horizontal subplots
For 1 row and 2 columns, use 'width_ratios' to set horizontal size ratios.Step 2: Match ratios to subplot layout
plt.subplots(1, 2, gridspec_kw={'width_ratios': [2, 1]}) uses 1 row, 2 columns with width_ratios, which is correct syntax.Final Answer:
plt.subplots(1, 2, gridspec_kw={'width_ratios': [2, 1]}) -> Option AQuick Check:
Width ratios for columns = plt.subplots(1, 2, gridspec_kw={'width_ratios': [2, 1]}) [OK]
- Mixing width_ratios with rows instead of columns
- Using height_ratios for horizontal layout
- Wrong number of rows and columns in function
fig, axs = plt.subplots(1, 2, gridspec_kw={'width_ratios': [3, 1]})Solution
Step 1: Understand width_ratios parameter
The list [3, 1] means the first subplot width is 3 units, second is 1 unit.Step 2: Interpret ratio meaning
This means the first subplot is 3 times wider than the second subplot.Final Answer:
The first subplot is 3 times wider than the second -> Option DQuick Check:
Width ratio 3:1 means first is 3x wider [OK]
- Assuming equal widths despite ratios
- Reversing which subplot is wider
- Ignoring the ratio values
fig, axs = plt.subplots(2, 1, gridspec_kw={'width_ratios': [1, 2]})Solution
Step 1: Check subplot layout
2 rows and 1 column means vertical stacking of subplots.Step 2: Verify correct ratio parameter
For vertical layout, use 'height_ratios', not 'width_ratios'.Final Answer:
Using width_ratios for vertical subplots instead of height_ratios -> Option BQuick Check:
Vertical layout needs height_ratios [OK]
- Confusing width_ratios and height_ratios
- Ignoring subplot grid shape
- Assuming plt.show() affects subplot sizes
Solution
Step 1: Determine subplot layout
One row and three columns means horizontal layout.Step 2: Choose correct ratio parameter
For horizontal layout, use 'width_ratios' to set widths.Step 3: Set ratios to make middle subplot twice as wide
Use [1, 2, 1] so middle subplot is twice the width of others.Final Answer:
plt.subplots(1, 3, gridspec_kw={'width_ratios': [1, 2, 1]}) -> Option AQuick Check:
Horizontal layout with width_ratios = plt.subplots(1, 3, gridspec_kw={'width_ratios': [1, 2, 1]}) [OK]
- Using height_ratios for horizontal layout
- Setting wrong number of rows and columns
- Reversing ratio order
Ready to prove it?
Pass the test and this pattern moves unknown
