Matplotlib: scenarios when trying to plot a 3D scatter plot with alpha blending on a large dataset
I'm optimizing some code but I'm working with Matplotlib version 3.4.3 and trying to create a 3D scatter plot using a large dataset containing around 100,000 points. I've managed to plot the basic figure, but I'm working with issues when I try to add alpha blending for better visibility of overlapping points. Specifically, when I set the alpha parameter in the scatter call, I get the following behavior: ``` ValueError: 'alpha' must be a float between 0 and 1 ``` Here's the code I've written so far: ```python import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D # Generate sample data np.random.seed(0) x = np.random.rand(100000) y = np.random.rand(100000) z = np.random.rand(100000) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.scatter(x, y, z, alpha=0.5) plt.show() ``` I've confirmed that `alpha` is indeed a float (0.5) and is between 0 and 1. I suspect the scenario might relate to the size of the dataset or some interaction with the 3D plot, but I'm not sure. I've tried reducing the dataset to 10,000 points, and the plotting works fine with alpha blending applied. Is there a way to efficiently plot this large dataset with alpha blending without running into this behavior? Any suggestions would be greatly appreciated! This issue appeared after updating to Python 3.9. Is this even possible? I recently upgraded to Python 3.9. Thanks for taking the time to read this!