How To Smooth By Interpolation When Using Pcolormesh?

I have a basemap of the world, and it's filled with data (lintrends_mean) using pcolormesh. Because the data has relatively large grid boxes, I'd like to smooth the plot. However,

Solution 1:

You have some variants:

1. Use special shading for pcolormesh.
2. Use imshow which allows to interpolated data.
3. Interpolate data with scipy.interpolate and plot with pcolormesh.

Look at the example:

import matplotlib.pylab as plt
import numpy as np
from scipy.interpolate import interp2d

data = np.random.random((30,30))
X = np.arange(0, 30, 1)
Y = np.arange(0, 30, 1)
X, Y = np.meshgrid(X, Y)

# colormesh original
plt.subplot(3, 2, 1)
plt.pcolormesh(X, Y, data, cmap='RdBu')

# pcolormesh with special shading
plt.subplot(3, 2, 2)
plt.pcolormesh(X, Y, data, cmap='RdBu',shading='gouraud')

# imshow bilinear interp.
plt.subplot(3, 2, 3)
plt.imshow(data, cmap='RdBu', interpolation = 'bilinear')

# imshow bicubic interp.
plt.subplot(3, 2, 4)
plt.imshow(data, cmap='RdBu', interpolation = 'bicubic')

# scipy interp. cubic
f = interp2d(X, Y, data, kind='cubic')
xnew = np.arange(0, 30, .1)
ynew = np.arange(0, 30, .1)
data1 = f(xnew,ynew)
Xn, Yn = np.meshgrid(xnew, ynew)
plt.subplot(3, 2, 5)
plt.pcolormesh(Xn, Yn, data1, cmap='RdBu')

plt.show()