deal (version 1.2-42)

drawnetwork: Graphical interface for editing networks

Description

drawnetwork allows the user to specify a Bayesian network through a point and click interface.

Usage

drawnetwork(nw,df,prior,trylist=vector("list",size(nw)),
            unitscale=20,cexscale=8,
            arrowlength=.25,nocalc=FALSE,
            yr=c(0,350),xr=yr,...)

Value

A list with two elements that may be accessed using

getnetwork and gettrylist. The elements are

nw

an object of class network with the final network.

trylist

an updated list used internally for reusing learning of nodes, see maketrylist.

Arguments

nw

an object of class network to be edited.

df

a data frame used for learning the network, see network.

prior

a list containing parameter priors, generated by jointprior.

trylist

a list used internally for reusing learning of nodes, see maketrylist.

cexscale

a numeric passed to the plot method for network objects. Measures the scaled size of text and symbols.

arrowlength

a numeric passed to the plot method for network objects. Measures the length of the edges of the arrowheads.

nocalc

a logical. If TRUE, no learning procedure is called, see eg. rnetwork.

unitscale

a numeric passed to the plot method for network objects. Scale parameter for chopping off arrow heads.

xr

a numeric vector with two components containing the range on x-axis.

yr

a numeric vector with two components containing the range on y-axis.

...

additional plot arguments, passed to the plot method for network objects.

Author

Susanne Gammelgaard Bottcher,
Claus Dethlefsen .

Details

To insert an arrow from node 'A' to node 'B', first click node 'A' and then click node 'B'. When the graph is finished, click 'stop'.

To specify that an arrow must not be present, press 'ban' (a toggle) and draw the arrow. This is shown as a red dashed arrow. It is possible to ban both directions between nodes. The ban list is stored with the network in the property banlist. It is a matrix with two columns. Each row is the 'from' node index and the 'to' node index, where the indices are the column number in the data frame.

Note that the network score changes as the network is re-learned whenever a change is made (unless nocalc is TRUE).

See Also

network

Examples

data(rats)
rats.nw    <- network(rats)
rats.prior <- jointprior(rats.nw,12)
rats.nw    <- getnetwork(learn(rats.nw,rats,rats.prior))

if (FALSE) newrat  <- getnetwork(drawnetwork(rats.nw,rats,rats.prior))