Merge pull request #184 from MLH-Fellowship/example

fix issues with plot in lobachesky example

docs/src/lobachesky.md

@@ -2,19 +2,20 @@
 
 Lobachevsky splines function is a function that used for univariate and multivariate scattered interpolation. Introduced by Lobachevsky in 1842 to investigate errors in astronomical measurements.
 
-We are going to use a Lobachevsky surrogate to optimize $3 * x + log(x)$.
+We are going to use a Lobachevsky surrogate to optimize $f(x)=sin(x)+sin(10/3 * x)$.
 
 First of all import `Surrogates` and `Plots`.
 ```@example LobachevskySurrogate_tutorial
 using Surrogates
 using Plots
+default()
 ```
 ### Sampling
 
 We choose to sample f in 4 points between 0 and 4 using the `sample` function. The sampling points are chosen using a Sobol sequence, this can be done by passing `SobolSample()` to the `sample` function.
 
 ```@example LobachevskySurrogate_tutorial
-f(x) = 3*x + log(x)
+f(x) = sin(x) + sin(10/3 * x)
 n_samples = 5
 lower_bound = 1.0
 upper_bound = 4.0
@@ -25,7 +26,7 @@ plot!(f, label="True function", xlims=(lower_bound, upper_bound))
 ```
 ### Building a surrogate
 
-With our sampled points we can build the Random forests surrogate using the `LobachevskySurrogate` function.
+With our sampled points we can build the Lobachevsky surrogate using the `LobachevskySurrogate` function.
 
 `lobachevsky_surrogate` behaves like an ordinary function which we can simply plot. Alpha is the shape parameters and n specify how close you want lobachevsky function to radial basis function.
 

docs/src/randomforest.md

@@ -8,6 +8,7 @@ First of all import `Surrogates` and `Plots`.
 ```@example RandomForestSurrogate_tutorial
 using Surrogates
 using Plots
+default()
 ```
 ### Sampling