] add LocalFunctionApproximation
using LocalFunctionApproximation

using GridInterpolations # Make the grid interpolations module available
grid = RectangleGrid([0., 0.5, 1.],[0., 0.5, 1.])      # rectangular grid
grid_values = [8., 1., 6., 3., 5., 7., 4., 9., 2.]     # corresponding values at each grid point
gifa = LocalGIFunctionApproximator(grid, grid_values)  # create the function approximator using the grid and values

using NearestNeighbors, StaticArrays
points = [SVector(0.,0.), SVector(0.,1.), SVector(1.,1.), SVector(1.,0.)]   # the 4 corners of the unit square
nntree = KDTree(points)                                                     # create a KDTree using the points
vals = [1., 1., -1., -1]                                                    # values corresponding to points
k = 2                                                                       # the k parameter for knn approximator
knnfa = LocalNNFunctionApproximator(nntree, points, k)

point = rand(2)             # random 2D point
compute_value(gifa, point)  # obtain the value by interpolating the function at that point       
compute_value(knnfa, point) # do the same for the kNN approximator