Problem

When Overlaying multiple sets using scatter and alpha a previously plotted set can become occluded entirely if the density is too high as the summed alpha goes to full occlusion.
Using low alphas for pointclouds leads to outliars being *almost invisible.

Objective:

Introduce a parameter to cap the maximum alpha value in scatter plots to maintain visibility of underlying sets when overlaying multiple point clouds.

Use Case:

Overlaying point clouds from different datasets without obscuring underlying data, avoiding the need to manipulate z-order.

Implementation Details

•	Parameter: max_alpha
•	Type: Float (range: 0.0 to 1.0)
•	Default: None (no cap on alpha)
•	Function: Limits the cumulative alpha value for overlapping points.

Benefits

Enhanced Visualization: Maintains clarity and readability of plots with multiple overlaid datasets.
Flexibility: Users can control transparency to prevent complete opacity in densely populated areas.

Example Usage

import matplotlib.pyplot as plt

Sample data

x1, y1 = [1, 2, 3], [4, 5, 6]
x2, y2 = [2, 3, 4], [5, 6, 7]

Scatter plot with max_alpha

plt.scatter(x1, y1, alpha=0.5, max_alpha=0.8)
plt.scatter(x2, y2, alpha=0.5, max_alpha=0.8)
plt.show()

Conclusion

Implementing a max_alpha parameter in Matplotlib’s scatter plot functionality will provide greater control over data visualization, ensuring that underlying datasets remain visible even when multiple layers are overlaid.

Proposed solution

No response