Universal Kriging Example
In this example we apply a regional linear trend to the kriging system.
import matplotlib.pyplot as plt import numpy as np from pykrige.uk import UniversalKriging data = np.array( [ [0.3, 1.2, 0.47], [1.9, 0.6, 0.56], [1.1, 3.2, 0.74], [3.3, 4.4, 1.47], [4.7, 3.8, 1.74], ] ) gridx = np.arange(0.0, 5.5, 0.5) gridy = np.arange(0.0, 5.5, 0.5)
Create the universal kriging object. Required inputs are the X-coordinates of the data points, the Y-coordinates of the data points, and the Z-values of the data points. Variogram is handled as in the ordinary kriging case. drift_terms is a list of the drift terms to include; currently supported terms are ‘regional_linear’, ‘point_log’, and ‘external_Z’. Refer to UniversalKriging.__doc__ for more information.
UK = UniversalKriging( data[:, 0], data[:, 1], data[:, 2], variogram_model="linear", drift_terms=["regional_linear"], )
Creates the kriged grid and the variance grid. Allows for kriging on a rectangular grid of points, on a masked rectangular grid of points, or with arbitrary points. (See UniversalKriging.__doc__ for more information.)
z, ss = UK.execute("grid", gridx, gridy) plt.imshow(z) plt.show()
Total running time of the script: ( 0 minutes 0.149 seconds)