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I am trying to plot 2 distinct colormeshes on the same figure. They are mutually exclusive, so there are no overlaps. This is my code:

sm3 = ScalarMappable (cmap='Blues', norm=Normalize(vmin=0, vmax=1))
sm3.set_array([])
p3 = ax.pcolormesh ( E_mm_n, E_mm_a, Z_gg, cmap="Blues"   , shading="auto") 
                
sm4 = ScalarMappable (cmap='Purples', norm=Normalize(vmin=0, vmax=1))
sm4.set_array([])
p4 = ax.pcolormesh ( E_mm_n, E_mm_a, Z_gc, cmap="Purples" , shading="auto") 

Everytime I make this plot, all I see is the plot defined by p4. I never see the information in p3. How can I make sure both colormeshes are visible? Also, Z_gg and Z_gc are mutually exclusive, so they should be right next to one another, with no overlaps.

With the above code, I see the following figure: enter image description here

When I comment out the sm4 and p4 lines, i get the following figure: enter image description here

How can i get both the blue and purple on the same plot? I would appreciate any advice you have for me!

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1 Answer 1

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I think the issue is that your E_mm_n, E_mm_a parameters are the same in both calls, and so it thinks the first QuadMesh is behind the second. When I do this

Z = np.random.rand(6, 10)
x = np.arange(-0.5, 10, 1)  # len = 11
y = np.arange(4.5, 11, 1)  # len = 7
X, Y = np.meshgrid(x, y)

X1 = X + 0.4 * Y  # tilt the coordinates.
Y1 = Y + 0.3 * X

X2 = X + 0.4 * Y  # tilt the coordinates.
Y2 = Y + 0.3 - X

ax.pcolormesh(X1, Y1, Z, cmap="Purples")
ax.pcolormesh(X2, Y2, Z, cmap="Blues")    

It displays enter image description here

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  • $\begingroup$ Thank you for your answer @brewmaster321! I do need to plot them on the same plot. How can I only plot the subset in that case? $\endgroup$
    – megamence
    Commented Apr 12, 2023 at 12:39
  • $\begingroup$ The X and Y coordinates for the two calls to pcolormesh need to be disjoint - right now they overlap completely. From the docs X and Y are the coordinates of the corners of quadrilaterals of a pcolormesh - it's basically drawing one quadilateral on top of the other. If you can partition your E_mm_n, E_mm_a, into one subset for the blue data points and one subset for the purple that should do the trick. $\endgroup$ Commented Apr 12, 2023 at 12:48

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