Question

How can I perform spatial interpolation using SciPy?

Answer 1

 SciPy provides functions for 1D and 2D interpolation, which can be useful for spatial data interpolation. Here's an example of 2D interpolation using scipy.interpolate.griddata:

import numpy as np
from scipy.interpolate import griddata
import matplotlib.pyplot as plt

# Sample data points
x = np.random.rand(100)
y = np.random.rand(100)
z = np.sin(x * 2 * np.pi) + np.cos(y * 2 * np.pi)

# Define a grid
xi, yi = np.meshgrid(np.linspace(0, 1, 100), np.linspace(0, 1, 100))

# Perform interpolation
zi = griddata((x, y), z, (xi, yi), method='cubic')

# Plot the interpolated surface
plt.contourf(xi, yi, zi, levels=20, cmap='RdYlBu')
plt.colorbar()
plt.show()