A Very Simple Example
We are going to start with a very simple example of a spatial random field with an isotropic Gaussian covariance model and following parameters:
First, we set things up and create the axes for the field. We are going to
SRF class for the actual generation of the spatial random field.
SRF also needs a covariance model and we will simply take the
import gstools as gs x = y = range(100)
Now we create the covariance model with the parameters and
and hand it over to
SRF. By specifying a seed,
we make sure to create reproducible results:
model = gs.Gaussian(dim=2, var=1, len_scale=10) srf = gs.SRF(model, seed=20170519)
With these simple steps, everything is ready to create our first random field. We will create the field on a structured grid (as you might have guessed from the x and y), which makes it easier to plot.
field = srf.structured([x, y]) srf.plot()
Wow, that was pretty easy!
Total running time of the script: ( 0 minutes 0.768 seconds)