Grid Lines below the contour in Matplotlib

Question

I have one question about the grid lines matplotlib. I am not sure if this is possible to do or not. I am plotting the following graph as shown in the image.

I won't give the entire code, since it is involving reading of files.

However the important part of code is here -

X, Y = np.meshgrid(smallX, smallY)
Z = np.zeros((len(X),len(X[0])))
plt.contourf(X, Y, Z, levels, cmap=cm.gray_r, zorder = 1)
plt.colorbar()
...
# Set Border width zero
[i.set_linewidth(0) for i in ax.spines.itervalues()]

gridLineWidth=0.1
ax.set_axisbelow(False)
gridlines = ax.get_xgridlines()+ax.get_ygridlines()
#ax.set_axisbelow(True)

plt.setp(gridlines, 'zorder', 5)

ax.yaxis.grid(True, linewidth=gridLineWidth, linestyle='-', color='0.6')
ax.xaxis.grid(False)
ax.xaxis.set_ticks_position('none')
ax.yaxis.set_ticks_position('none')

Now, my questions is like this -

If I put the grid lines below the contour, they disappear since they are below it. If I put the grid line above the contour, they looks like what they are looking now. However, what I would like to have is the grid lines should be visible, but should be below the black portion of the contour. I am not sure if that is possible.

Thank You !

Answer 1

In addition to specifying the z-order of the contours and the gridlines, you could also try masking the zero values of your contoured data.

Here's a small example:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(-2*np.pi, 2*np.pi, 0.1)
y = np.arange(-2*np.pi, 2*np.pi, 0.1)
X, Y = np.meshgrid(x, y)

Z = np.sin(X) - np.cos(Y)
Z = np.ma.masked_less(Z, 0) # you use mask_equal(yourData, yourMagicValue)

fig, ax = plt.subplots()
ax.contourf(Z, zorder=5, cmap=plt.cm.coolwarm)
ax.xaxis.grid(True, zorder=0)
ax.yaxis.grid(True, zorder=0)

And the output: