bbnet (version 1.1.0)

bbn.network.diagram: Create Network Diagram from Bayesian Belief Network Data

Description

bbn.network.diagram() generates a network diagram from a specified Bayesian Belief Network (BBN), allowing for the visualization of the relationships and interactions between nodes.

Usage

bbn.network.diagram(
  bbn.network,
  font.size = 0.7,
  arrow.size = 4,
  arrange = layout_on_sphere
)

Value

A plot of the network diagram, illustrating the interactions (both positive and negative) between nodes.

Arguments

bbn.network

A dataframe, with a first column called id that consists of an s and a 2 digit number relating to the node number. The second column called node.type is an integer value from 1-4. This sets the colour of the node in the network (sticking to a maximum of four colours). The third column is the same as the first column in the standard BBN interaction matrix or dataframe, other than it is titled node.name. It is important to use these column names (including capitals and dot notation). The remainder of the columns are exactly as the standard BBN interaction matrix or dataframe.

font.size

Changes the font in the figure produced. Default = 0.7. The value here is a multiplier of the default font size used in the igraph package and does not correspond to the font.size argument in bbn.timeseries.

arrow.size

Changes the size of the arrows. Default = 4. Note, sizes do vary based on interaction strength, so this is a multiplier for visualisation purposes. Negative interactions are shown by red arrows, and positive interactions by black arrows.

arrange

this describes how the final diagram looks. Default is layout_on_sphere but layout_on_grid provides the same layout as in bbn.visualise and ensures nodes are structured in the order specified in the network. Other layouts, including layout_on_sphere are more randomly determined, and better/clearer diagrams may occur if you run these multiple times. Other options are from the igraph package: layout.sphere layout.circle layout.random layout.fruchterman.reingold

Details

The diagram is created using edge and node data derived from the BBN, with edges representing interactions (positive or negative) between nodes.

bbn.network.diagram() visualises all nodes and interactions in a network, in a similar manner to bbn.visualise, other than this is the full network.

Examples

data(my_network)
bbn.network.diagram(bbn.network = my_network, font.size=0.7,
  arrow.size=4, arrange = layout_on_sphere)