Graphical interface for editing networks
drawnetwork allows the user to specify a Bayesian network through a point and click interface.
drawnetwork(nw,df,prior,trylist=vector("list",size(nw)),
unitscale=20,cexscale=8,
arrowlength=.25,nocalc=FALSE,
yr=c(0,350),xr=yr,...)nw |
an object of class |
df |
a data frame used for learning the network, see
|
prior |
a list containing parameter priors, generated by
|
trylist |
a list used internally for reusing learning of nodes,
see |
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 |
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. |
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).
A list with two elements that may be accessed using
getnetwork and gettrylist. The elements are
nw |
an object of class |
trylist |
an updated list used internally for reusing learning
of nodes, see |
Susanne Gammelgaard Bottcher,
Claus Dethlefsen rpackage.deal@gmail.com.
data(rats) rats.nw <- network(rats) rats.prior <- jointprior(rats.nw,12) rats.nw <- getnetwork(learn(rats.nw,rats,rats.prior)) ## Not run: newrat <- getnetwork(drawnetwork(rats.nw,rats,rats.prior))
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