Matplotlib: Issues with displaying a colorbar for a contour plot with masked data
I tried several approaches but none seem to work... I am trying to create a contour plot in Matplotlib using masked data, but I am facing issues with displaying the colorbar correctly. My data contains some invalid values that I mask using `numpy.ma.masked_where`. When I create the contour plot, the colorbar seems to not reflect the range of the valid data and instead shows the full range of the colormap, which is misleading. Here’s a minimal example of what I’m doing: ```python import numpy as np import matplotlib.pyplot as plt # Create some data x = np.linspace(-5, 5, 100) y = np.linspace(-5, 5, 100) X, Y = np.meshgrid(x, y) Z = np.sin(np.sqrt(X**2 + Y**2)) # Mask some part of the data Z_masked = np.ma.masked_where(Z < 0, Z) # Create the contour plot contour = plt.contourf(X, Y, Z_masked, cmap='viridis') # Add the colorbar plt.colorbar(contour) plt.show() ``` When I run this code, the colorbar shows colors that correspond to values below zero, which are masked. I expected that the colorbar would only represent the range of the displayed data (0 to the maximum value of the non-masked region) instead of the full range of the colormap from the masked values. I’ve tried using `contour.set_clim` to manually set the limits of the colorbar based on `Z_masked`, but it doesn't seem to help. Additionally, I've checked the version of Matplotlib I’m using, which is 3.6.2, and I’m not sure if this is a known issue or if I’m missing something fundamental. Any insights or suggestions on how to properly display the colorbar for masked data would be greatly appreciated! This is part of a larger API I'm building. For context: I'm using Python on macOS. I'd really appreciate any guidance on this.