Creates a fraction of design space plot

## Usage

```
plot_fds(
genoutput,
model = NULL,
continuouslength = 1001,
plot = TRUE,
sample_size = 10000,
yaxis_max = NULL,
description = "Fraction of Design Space"
)
```

## Arguments

- genoutput
The design, or the output of the power evaluation functions. This can also be a list of several designs, which will result in all of them being plotted in a row (for easy comparison).

- model
Default `NULL`. The model, if `NULL` it defaults to the model used in `eval_design` or `gen_design`.

- continuouslength
Default `11`. The precision of the continuous variables. Decrease for faster (but less precise) plotting.

- plot
Default `TRUE`. Whether to plot the FDS, or just calculate the cumulative distribution function.

- sample_size
Default `10000`. Number of samples to take of the design space.

- yaxis_max
Default `NULL`. Manually set the maximum value of the prediction variance.

- description
Default `Fraction of Design Space`. The description to add to the plot. If a vector and multiple designs passed to genoutput, it will be the description for each plot.

## Value

Plots design diagnostics, and invisibly returns the vector of values representing the fraction of design space plot. If multiple designs are passed, this will return a list of all FDS vectors.

## Examples

```
#We can pass either the output of gen_design or eval_design to plot_correlations
#in order to obtain the correlation map. Passing the output of eval_design is useful
#if you want to plot the correlation map from an externally generated design.
#First generate the design:
candidatelist = expand.grid(X1 = c(1, -1), X2 = c(1, -1))
design = gen_design(candidatelist, ~(X1 + X2), 15)
plot_fds(design)
```