"""
Creating Fancier Fields
-----------------------
Only using Gaussian covariance fields gets boring. Now we are going to create
much rougher random fields by using an exponential covariance model and we are going to make them anisotropic.
The code is very similar to the previous examples, but with a different
covariance model class :any:`Exponential`. As model parameters we a using
following
- variance :math:`\sigma^2=1`
- correlation length :math:`\lambda=(12, 3)^T`
- rotation angle :math:`\theta=\pi/8`
"""
import numpy as np
import gstools as gs
x = y = np.arange(100)
model = gs.Exponential(dim=2, var=1, len_scale=[12.0, 3.0], angles=np.pi / 8)
srf = gs.SRF(model, seed=20170519)
srf.structured([x, y])
srf.plot()
###############################################################################
# The anisotropy ratio could also have been set with
model = gs.Exponential(dim=2, var=1, len_scale=12, anis=0.25, angles=np.pi / 8)