Merge branch 'master' of https://github.com/SciML/Surrogates.jl

SciML · Aug 30, 2020 · f5ba656 · f5ba656
2 parents 4bcb3fa + 09d9f3e
commit f5ba656
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diff --git a/docs/src/Salustowicz.md b/docs/src/Salustowicz.md
@@ -43,12 +43,10 @@ Now, let's fit Salustowicz Function with different Surrogates:
 
 ```@example salustowicz1D
 InverseDistance = InverseDistanceSurrogate(x, y, lower_bound, upper_bound)
-randomforest_surrogate = RandomForestSurrogate(x ,y ,lower_bound, upper_bound, num_round = 2)
 lobachevsky_surrogate = LobacheskySurrogate(x, y, lower_bound, upper_bound, alpha = 2.0, n = 6)
 scatter(x, y, label="Sampled points", xlims=(lower_bound, upper_bound), legend=:topright)
 plot!(xs, salustowicz.(xs), label="True function", legend=:topright)
 plot!(xs, InverseDistance.(xs), label="InverseDistanceSurrogate", legend=:topright)
-plot!(xs, randomforest_surrogate.(xs), label="RandomForest", legend=:topright)
 plot!(xs, lobachevsky_surrogate.(xs), label="Lobachesky", legend=:topright)
 ```
 

diff --git a/docs/src/polychaos.md b/docs/src/polychaos.md
@@ -5,7 +5,7 @@ with a different polynomial basis depending on the distribution of the data
 we are trying to fit. Under the hood, PolyChaos.jl has been used.
 It is possible to specify a type of polynomial for each dimension of the problem.
 
-```@example Inverse_Distance1D
+```@example polychaos
 using Surrogates
 using Plots
 default()

diff --git a/docs/src/variablefidelity.md b/docs/src/variablefidelity.md
@@ -13,7 +13,7 @@ default()
 n = 20
 lower_bound = 1.0
 upper_bound = 6.0
-x = sample(n,lower_bound,upper_bound,LowDiscrepancySample(2))
+x = sample(n,lower_bound,upper_bound,SobolSample())
 f = x -> 1/3*x
 y = f.(x)
 plot(x, y, seriestype=:scatter, label="Sampled points", xlims=(lower_bound, upper_bound), legend=:top)
@@ -24,7 +24,7 @@ plot!(f, label="True function",  xlims=(lower_bound, upper_bound), legend=:top)
 varfid = VariableFidelitySurrogate(x,y,lower_bound,upper_bound)
 ```
 
-```@example RadialBasisSurrogate
+```@example variablefid
 plot(x, y, seriestype=:scatter, label="Sampled points", xlims=(lower_bound, upper_bound), legend=:top)
 plot!(f, label="True function",  xlims=(lower_bound, upper_bound), legend=:top)
 plot!(varfid, label="Surrogate function",  xlims=(lower_bound, upper_bound), legend=:top)