Discrete fields

Here we transform a field to a discrete field with values. If we do not give thresholds, the pairwise means of the given values are taken as thresholds. If thresholds are given, arbitrary values can be applied to the field.

See transform.discrete

import numpy as np

import gstools as gs

# Structured field with a size of 100x100 and a grid-size of 0.5x0.5
x = y = np.arange(200) * 0.5
model = gs.Gaussian(dim=2, var=1, len_scale=5)
srf = gs.SRF(model, seed=20170519)
srf.structured([x, y])

Create 5 equidistanly spaced values, thresholds are the arithmetic means

values1 = np.linspace(np.min(srf.field), np.max(srf.field), 5)
srf.transform("discrete", store="f1", values=values1)
Field 2D structured: (200, 200)

Calculate thresholds for equal shares but apply different values to the separated classes

values2 = [0, -1, 2, -3, 4]
srf.transform("discrete", store="f2", values=values2, thresholds="equal")
Field 2D structured: (200, 200)

Create user defined thresholds and apply different values to the separated classes

values3 = [0, 1, 10]
thresholds = [-1, 1]
srf.transform("discrete", store="f3", values=values3, thresholds=thresholds)
Field 2D structured: (200, 200)

Total running time of the script: ( 0 minutes 3.243 seconds)

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