# image.FEM: Image Plot of a 2D FEM object In fdaPDE: Statistical Analysis of Functional and Spatial Data, Based on Regression with PDE Regularization

## Description

Image plot of a `FEM` object, generated by the function `FEM` or returned by `smooth.FEM` and `FPCA.FEM`. Only FEM objects defined over a 2D mesh can be plotted with this method.

## Usage

 ```1 2``` ```## S3 method for class 'FEM' image(x, num_refinements, ...) ```

## Arguments

 `x` A 2D-mesh `FEM` object. `num_refinements` A natural number specifying how many bisections should by applied to each triangular element for plotting purposes. This functionality is useful where a discretization with 2nd order Finite Element is applied. `...` Arguments representing graphical options to be passed to plot3d.

`FEM` `plot.FEM`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```library(fdaPDE) ## Upload the horseshoe2D data data(horseshoe2D) boundary_nodes = horseshoe2D\$boundary_nodes boundary_segments = horseshoe2D\$boundary_segments locations = horseshoe2D\$locations ## Create the 2D mesh mesh = create.mesh.2D(nodes = rbind(boundary_nodes, locations), segments = boundary_segments) ## Create the FEM basis FEMbasis = create.FEM.basis(mesh) ## Compute the coeff vector evaluating the desired function at the mesh nodes ## In this case we consider the fs.test() function introduced by Wood et al. 2008 coeff = fs.test(mesh\$nodes[,1], mesh\$nodes[,2]) ## Create the FEM object FEMfunction = FEM(coeff, FEMbasis) ## Plot the FEM function image(FEMfunction) ```