editrules.plotting {editrules}

Graphical representation of edits

Description

Plots a graph, showing which variables occur in what edits. By default, squares represent edits, circles represent variables and an edge connecing a variable with an edit indicates that the edit contains the variable.

Usage

## S3 method for class 'editmatrix'
plot(
  x,
  nodetype = "all",
  rules = editnames(x),
  vars = getVars(x),
  violated = logical(nedits(x)),
  adapt = logical(length(getVars(x))),
  nabbreviate = 5,
  layout = igraph::layout.fruchterman.reingold,
  edgecolor = "steelblue",
  rulecolor = "khaki1",
  varcolor = "lightblue1",
  violatedcolor = "sienna1",
  adaptcolor = "sienna1",
  ...
)

## S3 method for class 'editarray'
plot(
  x,
  nodetype = "all",
  rules = editnames(x),
  vars = getVars(x),
  violated = logical(nedits(x)),
  adapt = logical(length(getVars(x))),
  nabbreviate = 5,
  layout = igraph::layout.fruchterman.reingold,
  edgecolor = "steelblue",
  rulecolor = "khaki1",
  varcolor = "lightblue1",
  violatedcolor = "sienna1",
  adaptcolor = "sienna1",
  ...
)

## S3 method for class 'editset'
plot(
  x,
  nodetype = "all",
  rules = editnames(x),
  vars = getVars(x),
  violated = logical(nedits(x)),
  adapt = logical(length(getVars(x))),
  nabbreviate = 5,
  layout = igraph::layout.fruchterman.reingold,
  edgecolor = "steelblue",
  rulecolor = "khaki1",
  varcolor = "lightblue1",
  violatedcolor = "sienna1",
  adaptcolor = "sienna1",
  ...
)

Arguments

x

object of class editmatrix

nodetype

'rules', 'vars' or 'all'.

rules

selection of edits

vars

selection of variables

violated

A named logical vector of length nrow(E). Ingnored when nodetype='vars'

adapt

A named logical vector of length(getVars(E)). Ignored when nodetype='rules'

nabbreviate

integer To how many characters should variable and edit names be abbreviated?

layout

an igraph layout function. See ?igraph::layout

edgecolor

Color of edges and node frames

rulecolor

Color of rule nodes (ignored when nodetype='vars')

varcolor

Color of variable nodes (ignored when nodetype='rules')

violatedcolor

Color of nodes corresponding to violated edits (ignored when nodetype='vars')

adaptcolor

Color of nodes corresponding to variables to adapt (ignored when nodetype='rules')

...

further arguments to be passed to plot.

Details

Depending on the chosen nodetype, this function can plot three types of graphs based on an edit set.

• If nodetype="all" (default), the full bipartite graph is plotted. Each variable is represented by a square node while each edit is represented by a circular node. An edge is drawn when a variable occurs in an edit.

• If nodetype="vars" the variable graph is drawn. Each node represents a variable, and an edge is drawn between two nodes if the variables occur together in at least one edit. The edge width relates to the number of edits connecting two variables.

• If nodetype="rules" the rule graph is drawn. Each node represents an edit rule and an edge is drawn between two nodes if they share at least one variable. The edge width relates to the number of edits connecting the two edit rules.

The boolean vectors violated and adapt can be used to color violated edits or variables which have to be adapted. The vectors must have named elements, so variables and edit names can be matched.

The function works by coercing an editmatrix to an igraph object, and therefore relies on the plotting capabilities of the igraph package. For more finetuning, use as.igraph and see ?igraph.plotting.

The default layout generated by the Fruchterman-Reingold algorithm. The resulting layout is one of several optimal layouts, generated randomly (using a attration-repulsion model between the nodes). To reproduce layouts, use fix a randseed before calling the plot function.

References

Csardi G, Nepusz T: The igraph software package for complex network research, InterJournal, Complex Systems 1695. 2006. http://igraph.sf.net

See Also

as.igraph, adjacency, igraph.plotting

Examples

## Examples with linear (in)equality edits

# load predefined edits from package
data(edits)
edits

# convert to editmatrix
E <- editmatrix(edits)

## Not run:
# (Note to reader: the Not run directive only prevents the examle commands from
# running when package is built)

# Total edit graph
plot(E)

# Graph with dependent edits
plot(E, nodetype="rules")

# Graph with dependent variables
plot(E, nodetype="vars")

# Total edit graph, but with curved lines (option from igraph package)
plot(E, edge.curved=TRUE)


# graph, plotting just the connections caused by variable 't'
plot(E,vars='t')

## End(Not run) 

# here's an example with a broken record.
r <- c(ct = 100, ch = 30, cp = 70, p=30,t=130 ) 
violatedEdits(E,r)
errorLocalizer(E,r)$searchBest()$adapt

# we color the violated edits and the variables that have to be adapted

## Not run
set.seed(1) # (for reprodicibility)
plot(E,
     adapt=errorLocalizer(E,r)$searchBest()$adapt,   
     violated=violatedEdits(E,r))
## End(Not run) 



# extract total graph (as igraph object)
as.igraph(E)

# extract graph with edges related to variable 't' and 'ch'
as.igraph(E,vars=c('t','ch'))

# extract total adjacency matrix
adjacency(E)

# extract adjacency matrix related to variables t and 'ch'
adjacency(E,vars=c('t','ch'))

## Examples with categorical edits

# generate an editarray:
E <- editarray(expression(
    age %in% c('<15','16-65','>65'),
    employment %in% c('unemployed','employed','retired'),
    salary %in% c('none','low','medium','high'),
    if (age == '<15') employment=='unemployed',
    if (salary != 'none') employment != 'unemployed',
    if (employment == 'unemployed') salary == 'none'))


## Not run:
# plot total edit graph
plot(E)

# plot with a different layout
plot(E,layout=layout.circle)

# plot edit graph, just the connections caused by 'salary'
plot(E,vars='salary')

## End(Not run)

# extract edit graph
as.igraph(E)

# extract edit graph, just the connections caused by 'salary'
as.igraph(E,vars='salary')

# extract adjacency matrix
adjacency(E)

# extract adjacency matrix, only caused by 'employment'
adjacency(E,vars='employment')