Overlapping Subplots: Optimizing Spacing with Matplotlib
In Matplotlib, generating a series of vertically-stacked subplots can present challenges in ensuring adequate spacing and preventing overlaps. Despite increasing the figure size, subplots may still overlap.
To address this issue, consider utilizing the following strategies:
Matplotlib.pyplot.tight_layout() Function
The matplotlib.pyplot.tight_layout() function automatically adjusts subplot spacing and arrangement to eliminate any overlaps.
import matplotlib.pyplot as plt fig, axes = plt.subplots(nrows=4, ncols=4, figsize=(8, 8)) fig.tight_layout() # Adjust subplot spacing and layout
Matplotlib.figure.Figure.tight_layout() Method
Alternatively, you can use the matplotlib.figure.Figure.tight_layout() method on the figure object directly:
import matplotlib.pyplot as plt fig = plt.figure(figsize=(10,60)) fig.tight_layout() # Adjust subplot spacing and layout within the figure for i, y_list in enumerate(y_lists): plt.subplot(len(titles), 1, i) plt.xlabel("Some X label") plt.ylabel("Some Y label") plt.title(titles[i]) plt.plot(x_lists[i],y_list) fig.savefig('out.png', dpi=100)
Benefits of Using Tight Layout:
- Optimizes spacing between subplots to prevent overlaps
- Maintains a consistent appearance across subplots
- Ensures legibility and readability of individual plots within a figure
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