Benchmarks (#227)

* added kriging surrogate with different hyper parameters

* fixed some issues in gek

docs/src/Salustowicz.md

@@ -58,9 +58,9 @@ Not's let's see Kriging Surrogate with different hyper parameter:
 kriging_surrogate1 = Kriging(x, y, lower_bound, upper_bound, p=0.9);
 kriging_surrogate2 = Kriging(x, y, lower_bound, upper_bound, p=1.5);
 kriging_surrogate3 = Kriging(x, y, lower_bound, upper_bound, p=1.9);
-scatter(x, y, label="Sampled points", xlims=(lower_bound, upper_bound), legend=:top)
-plot!(xs, salustowicz.(xs), label="True function", legend=:top)
-plot!(xs, kriging_surrogate1.(xs), label="kriging_surrogate1", ribbon=p->std_error_at_point(kriging_surrogate1, p), legend=:top)
-plot!(xs, kriging_surrogate2.(xs), label="kriging_surrogate2", ribbon=p->std_error_at_point(kriging_surrogate2, p), legend=:top)
-plot!(xs, kriging_surrogate3.(xs), label="kriging_surrogate3", ribbon=p->std_error_at_point(kriging_surrogate3, p), legend=:top)
+scatter(x, y, label="Sampled points", xlims=(lower_bound, upper_bound), legend=:topright)
+plot!(xs, salustowicz.(xs), label="True function", legend=:topright)
+plot!(xs, kriging_surrogate1.(xs), label="kriging_surrogate1", ribbon=p->std_error_at_point(kriging_surrogate1, p), legend=:topright)
+plot!(xs, kriging_surrogate2.(xs), label="kriging_surrogate2", ribbon=p->std_error_at_point(kriging_surrogate2, p), legend=:topright)
+plot!(xs, kriging_surrogate3.(xs), label="kriging_surrogate3", ribbon=p->std_error_at_point(kriging_surrogate3, p), legend=:topright)
 ```

docs/src/gek.md

@@ -37,10 +37,10 @@ plot!(f, label="True function", xlims=(lower_bound, upper_bound), legend=:top)
 With our sampled points we can build the Gradient Enhanced Kriging surrogate using the `GEK` function.
 
 ```@example GEK1D
-my_gek = GEK(x, y, lower_bound, upper_bound, p = 2.9);
+my_gek = GEK(x, y, lower_bound, upper_bound, p = 1.4);
 ```
 ```@example @GEK1D
-plot(x, y1, seriestype=:scatter, label="Sampled points", xlims=(lower_bound, upper_bound), legend=:top)
+scatter(x, y1, label="Sampled points", xlims=(lower_bound, upper_bound), legend=:top)
 plot!(f, label="True function",  xlims=(lower_bound, upper_bound), legend=:top)
 plot!(my_gek, label="Surrogate function", ribbon=p->std_error_at_point(my_gek, p), xlims=(lower_bound, upper_bound), legend=:top)
 ```
@@ -74,7 +74,7 @@ Let's define our bounds, this time we are working in two dimensions. In particul
 
 ```@example GEK_ND
 n_samples = 80
-lower_bound = [0, 0] 
+lower_bound = [0, 0]
 upper_bound = [10, 10]
 xys = sample(n_samples, lower_bound, upper_bound, SobolSample())
 y1 = leon.(xys);