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myDefaultModel = ExponentialModel(scale=[1], amplitude=[1], no spatial correlation)
myModel = ExponentialModel(scale=[1], amplitude=[2], no spatial correlation)
covariance matrix at t = 1.0 : [[ 1.47152 ]]
covariance matrix at t = -1.0 : [[ 1.47152 ]]
covariance matrix at t = 15.0 : [[ 1.22361e-06 ]]
discretized covariance over the time grid= RegularGrid(start=0, step=0.333333, n=4) is= [[ 4 2.86613 2.05367 1.47152 ]
[ 2.86613 4 2.86613 2.05367 ]
[ 2.05367 2.86613 4 2.86613 ]
[ 1.47152 2.05367 2.86613 4 ]]
myHighModel = ExponentialModel(scale=[1], amplitude=[1,2,3], spatial correlation=
[[ 1 1 0 ]
[ 1 1 0.25 ]
[ 0 0.25 1 ]])
covariance matrix at t = 1.0 : [[ 0.367879 0.735759 0 ]
[ 0.735759 1.47152 0.551819 ]
[ 0 0.551819 3.31091 ]]
covariance matrix at t = -1.0 : [[ 0.367879 0.735759 0 ]
[ 0.735759 1.47152 0.551819 ]
[ 0 0.551819 3.31091 ]]
covariance matrix at t = 15.0 : [[ 3.05902e-07 6.11805e-07 0 ]
[ 6.11805e-07 1.22361e-06 4.58853e-07 ]
[ 0 4.58853e-07 2.75312e-06 ]]
discretized covariance over the time grid= RegularGrid(start=0, step=0.333333, n=4) is= 12x12
[[ 1 2 0 0.716531 1.43306 0 0.513417 1.02683 0 0.367879 0.735759 0 ]
[ 2 4 1.5 1.43306 2.86613 1.0748 1.02683 2.05367 0.770126 0.735759 1.47152 0.551819 ]
[ 0 1.5 9 0 1.0748 6.44878 0 0.770126 4.62075 0 0.551819 3.31091 ]
[ 0.716531 1.43306 0 1 2 0 0.716531 1.43306 0 0.513417 1.02683 0 ]
[ 1.43306 2.86613 1.0748 2 4 1.5 1.43306 2.86613 1.0748 1.02683 2.05367 0.770126 ]
[ 0 1.0748 6.44878 0 1.5 9 0 1.0748 6.44878 0 0.770126 4.62075 ]
[ 0.513417 1.02683 0 0.716531 1.43306 0 1 2 0 0.716531 1.43306 0 ]
[ 1.02683 2.05367 0.770126 1.43306 2.86613 1.0748 2 4 1.5 1.43306 2.86613 1.0748 ]
[ 0 0.770126 4.62075 0 1.0748 6.44878 0 1.5 9 0 1.0748 6.44878 ]
[ 0.367879 0.735759 0 0.513417 1.02683 0 0.716531 1.43306 0 1 2 0 ]
[ 0.735759 1.47152 0.551819 1.02683 2.05367 0.770126 1.43306 2.86613 1.0748 2 4 1.5 ]
[ 0 0.551819 3.31091 0 0.770126 4.62075 0 1.0748 6.44878 0 1.5 9 ]]
parameters= [1,1,2,3] [scale_0,amplitude_0,amplitude_1,amplitude_2]
marginal= ExponentialModel(scale=[1], amplitude=[1,3], no spatial correlation) marginal.parameter= [1,1e-12,1] [scale_0,nuggetFactor,amplitude_0]
[1,1,1,1e-12,2,2]
[1,1,1,1e-12,2,0.5]
ok
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