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

 image.FEM R Documentation

## Image Plot of a 2D FEM object

### 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

```## 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`

### Examples

```library(fdaPDE)
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)
```

fdaPDE documentation built on Nov. 10, 2022, 5:06 p.m.