plot.sisal: Plotting Sequential Input Selection Results
In sisal: Sequential Input Selection Algorithm

Description Usage Arguments Details Value Author(s) References See Also Examples

A plot method for class "sisal". Supports 3 plot types: error as a function of the number of variables, search graph, and color key of the search graph.

## S3 method for class 'sisal'
plot(x, which = 1, standardize = "inherit", ...,
     plotArgs = list(list(), list(mai = rep(0.1, 4))),
     xlim = c(x[["d"]], 0), ylim = NULL, ask = TRUE,
     dev.set = !ask, draw.node.labels = TRUE,
     draw.edge.labels = TRUE, draw.selected.labels = TRUE,
     rankdir = c("TB", "LR", "BT", "RL"),
     fillcolor.normal = "deepskyblue",
     fillcolor.pruned = "deeppink",
     fillcolor.selected = "chartreuse",
     fillcolor.levelbest = "gold",
     fillcolor.small = "moccasin", fillcolor.large = "black",
     fillcolor.NA = "white",
     bordercolor.normal = "black",
     bordercolor.special.levelbest = fillcolor.levelbest,
     bordercolor.special.selected = fillcolor.selected,
     color.by.error = FALSE,
     ramp.space = c("Lab", "rgb"), ramp.size = 128,
     error.limits = c(NA_real_, NA_real_),
     category.labels =
         c(normal = gettext("Other", domain="R-sisal"),
           pruned = gettext("Pruned", domain="R-sisal"),
           levelbest = gettext("Best\nin class", domain="R-sisal"),
           selected = gettext("Selected", domain="R-sisal"),
           special.levelbest = gettext("Best\n(no branching)",
                                       domain="R-sisal"),
           special.selected = gettext("Selected\n(no branching)",
                                      domain="R-sisal"),
           shape.normal=gettext("Other", domain="R-sisal"),
           shape.highlighted=gettext("Highlighted", domain="R-sisal")),
     integrate.colorkey = TRUE, colorkey.gap = 0.1,
     colorkey.space = c("right", "bottom", "left", "top"),
     colorkey.title.gp = gpar(fontface = "bold"),
     nodesep = 0.25, ranksep = 0.5,
     graph.attributes = character(0),
     node.attributes = character(0),
     edge.attributes = character(0))

`x`	an object of class `"sisal"`.
`which`	which plots to draw. A `numeric` `vector` containing a subset of the following numbers: 1 error vs. number of inputs. 2 search graph. A directed acyclic graph (DAG). 3 node shape and color keys for the search graph. Requires that plot 2 is drawn, too. The default is to draw plot number 1. For drawing plot number 2, Bioconductor packages `"graph"` and `"Rgraphviz"` must be installed. Some other arguments of this method only apply to specific plots.
`standardize`	`"inherit"` or a `logical` flag. If `TRUE`, the error values in plot 1 correspond to standardized data (see `standardize` in `sisal`). If `FALSE`, the original scale of the data is used instead. If `"inherit"` (the default), the value of this argument is copied from `x`.
`...`	arguments passed to `plot` and `matplot`. These are used in all plots where `plot` or `matplot` do the actual drawing. For more fine-grained control and passing arguments to other graphical functions, use the `plotArgs` argument.
`plotArgs`	arguments passed to graphical functions. A `list` where `plotArgs[[k]]` (if present) are named `list`s of arguments passed to plot number `k`. See ‘Details’.
`xlim`	the x limits `c(x1, x2)` of plot 1. A `numeric` `vector`. Defaults to showing the whole range, i.e. everything between no input variables at all (except possibly an intercept) and the maximum number of inputs.
`ylim`	the y limits `c(x1, x2)` of plot 1. A `numeric` `vector`. If `NULL` (the default), adjusts to the range of y values corresponding to x values delimited by `xlim`.
`ask`	a `logical` flag. If `TRUE` (the default) and `!dev.set`, prompts the user before replacing a plot drawn with this function with another one. The user will not be alerted as long as there are free slots in the plot layout (see `mfrow` and `mfcol` in `par`).
`dev.set`	a `logical` flag. If `TRUE`, the function calls `dev.set` for switching to the next available graphical device when it runs out of free slots in the plot layout. If `FALSE`, the same graphical device is used for all the plots. The default value is `!ask`.
`draw.node.labels`	a `logical` flag. If `TRUE`, label the nodes of the search graph plot representing one input variable.
`draw.edge.labels`	a `logical` flag. If `TRUE`, label the edges of the search graph plot with the identity of the removed input variable.
`draw.selected.labels`	a `logical` flag. If `TRUE`, label the nodes of the search graph plot representing the L.v and L.f input variable sets of `sisal`.
`rankdir`	the drawing direction of plot number 2 (search graph). A `character` string, one of `"TB"` (top to bottom, the default), `"LR"` (left to right), `"BT"` (bottom to top), or `"RL"` (right to left).
`fillcolor.normal`	fill color for normal nodes in plot number 2.
`fillcolor.pruned`	fill color for pruned (unevaluated) nodes in plot 2. If `color.by.error` is `TRUE`, this color is used as the border color.
`fillcolor.selected`	fill color for nodes representing the L.v and L.f input variable sets of `sisal` in plot 2. If `color.by.error` is `TRUE`, this color is used as the border color.
`fillcolor.levelbest`	fill color for nodes with the smallest validation error using a given number of input variables in plot 2. If `color.by.error` is `TRUE`, this color is used as the border color.
`fillcolor.small`	if `color.by.error` is `TRUE`, fill color for nodes with small validation error in plot 2.
`fillcolor.large`	if `color.by.error` is `TRUE`, fill color for nodes with large validation error in plot 2.
`fillcolor.NA`	if `color.by.error` is `TRUE`, fill color for pruned (unevaluated) nodes in plot 2.
`bordercolor.normal`	border color for normal nodes in plot 2.
`bordercolor.special.levelbest`	border color for special nodes in plot 2. If branching (`hbranches > 1`) reduces validation error with a given number of input variables, the “no branching” node is marked with this border color. If `pruning.keep.best` is `FALSE`, the comparison may not be possible for all sizes of the input variable set.
`bordercolor.special.selected`	border color for another kind of special nodes in plot 2. The “no branching” L.v or L.f node, if different from the corresponding node in the solution where branching is allowed, is marked with this border color. If `pruning.keep.best` is `FALSE`, these alternative L.v and L.f nodes may not be defined, in which case the special color will not be used. If `color.by.error` is `TRUE`, this border color is also used to mark nodes that would be marked with `fillcolor.selected` in the case where `color.by.error` is `FALSE`.
`color.by.error`	a `logical` flag. If `TRUE` nodes in plot 2 are colored using a color gradient between `fillcolor.small` and `fillcolor.large` according to the validation error in the node. If `FALSE`, the nodes are colored by category (normal, pruned, selected, levelbest).
`ramp.space`	color space to be used in plots number 2 and 3 if `color.by.error` is `TRUE`. Either `"Lab"` (the default) or `"rgb"`. See `colorRamp`.
`ramp.size`	the number of colors to be used in the color gradient of plot number 3 if `color.by.error` is `TRUE`. See `colorRampPalette`.
`error.limits`	a `numeric` `vector` giving the minimum (first value) and maximum (second value) validation error. These are used as the endpoints of the color gradient used in plots number 2 and 3 if `color.by.error` is `TRUE`.
`category.labels`	text labels to be used in plot number 3 if `color.by.error` is `FALSE`. A `character` `vector` with elements named `"normal"`, `"pruned"`, `"levelbest"` and `"selected"`. See the corresponding arguments with the name prefix `"fillcolor"`. The vector must also have elements named `"special.levelbest"` and `"special.selected"`. See the corresponding arguments with the name prefix `"bordercolor"`. The final required elements are `"shape.normal"` and `"shape.highlighted"`, which correspond to rectangular and circular nodes, respectively. Circular shape highlights nodes that have the lowest validation error considering the number of inputs used. Also highlighted is each node with the lowest validation error per number of variables but without using branches, if available and different from the unrestricted best node.
`integrate.colorkey`	a `logical` flag. If `TRUE`, plots 2 (graph) and 3 (color and shape key for the graph) will be integrated if possible. This involves a version requirement on the `"Rgraphviz"` package. If `FALSE` or the version requirement is not met, the plots will be drawn separately.
`colorkey.gap`	a `numeric` value giving the space (in inches) between the graph and the color key when plot 2 and 3 are integrated (`integrate.colorkey`).
`colorkey.space`	location of the color and shape key (plot 3) relative to the graph (plot 2). One of `"bottom"`, `"right"`, `"top"` and `"left"`.
`colorkey.title.gp`	graphical parameters for the titles in plot 3. See `gpar`.
`nodesep`	a Graphviz attribute giving the minimum space in inches between adjacent nodes representing the same number of input variables. This `numeric` value applies to plot number 2.
`ranksep`	a Graphviz attribute giving the minimum space in inches between adjacent rows or columns of nodes, where a row or column consists of nodes representing the same number of input variables. This `numeric` value applies to plot number 2.
`graph.attributes`	a named `character` `vector` of extra Graphviz graph attributes. Applies to plot number 2.
`node.attributes`	a named `character` `vector` of extra Graphviz node attributes. Applies to plot number 2.
`edge.attributes`	a named `character` `vector` of extra Graphviz edge attributes. Applies to plot number 2.

In argument plotArgs, plotArgs[[1]] is passed to matplot, plotArgs[[2]] to the plot method for class "Ragraph", and plotArgs[[3]] to draw.colorkey$key.

For possible color values, see col2rgb.

When 2 %in% which, the function invisibly returns a graph of class "graphNEL" representing the search graph of a run of sisal. Otherwise NULL.

Mikko Korpela

For information about graph, node and edge attributes for plot number 2, see the Graphviz web site: http://www.graphviz.org/.

sisal

library(graphics)
foo <- testSisal(dataset="toy", Mtimes=10)
## Plotting the search graph requires "Rgraphviz" and "graph"
if (requireNamespace("Rgraphviz", quietly=TRUE) &&
    requireNamespace("graph", quietly=TRUE)) {
    plot(foo, which=2)
}
## Default output is a mean squared error plot
plot(foo)

Dataset is "toy"
See ?toy.learn for a description of the data
Adding noise with standard deviation 0.200000
Calling sisal

pruning.criterion=round robin, Mtimes=10, kfold=10, hbranches=1, max.width=1, 
q=0.165, standardize=TRUE, pruning.keep.best=TRUE, pruning.reverse=FALSE, 
use.ridge=FALSE, sp=-1
There are 10 variables and 1000 samples.
There are no missing values.
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