Package 'bnviewer'

Interactive Visualization of Bayesian Networks

Description

Bayesian networks provide an intuitive framework for probabilistic reasoning and its graphical nature can be interpreted quite clearly. Graph based methods of machine learning are becoming more popular because they offer a richer model of knowledge that can be understood by a human in a graphical format. The 'bnviewer' is an R Package that allows the interactive visualization of Bayesian Networks. The aim of this package is to improve the Bayesian Networks visualization over the basic and static views offered by existing packages.

Details

Package:	bnviewer
Type:	Package
Version:	0.1.5
Date:	2020-07-22
License:	MIT + file LICENSE

Author(s)

Robson Fernandes
Institute of Mathematical and Computer Sciences
University of Sao Paulo - ICMC-USP

Maintainer: Robson Fernandes [email protected]

---

Bayesian Network to iGraph Model

Description

Converts Bayesian network structure based on package "bnlearn" and "bnviewer" to model based on package "igraph".

Usage

bn.to.igraph(bayesian.network)

Arguments

bayesian.network

Bayesian Network structure.

References

See online documentation http://robsonfernandes.net/bnviewer

---

Model to Bayesian Network Structure

Description

Creates a Bayesian Network structure based on a high level semantic model.

Usage

model.to.structure(model)

Arguments

model

Model string

References

See online documentation http://robsonfernandes.net/bnviewer

Examples

library(bnlearn)
library(bnviewer)


model.left.arrow.op1 = "  A <- (B,C,D);
                          B <- (E,F);
                          F <- (G);
                       "

model.left.arrow.op2 = "  A <= (B,C,D);
                          B <= (E,F);
                          F <= (G);
                       "


model.right.arrow.op1 = " A -> (B,C,D);
                          B -> (E,F);
                          F -> (G);
                        "

model.right.arrow.op2 = " A => (B,C,D);
                          B => (E,F);
                          F => (G);
                        "

structure = model.to.structure(model.left.arrow.op1)

viewer(structure,
       bayesianNetwork.width = "100%",
       bayesianNetwork.height = "80vh",
       bayesianNetwork.layout = "layout_on_grid",
       node.colors = list(background = "#f4bafd",
                         border = "#2b7ce9",
                         highlight = list(background = "#97c2fc",
                                          border = "#2b7ce9"))
      )

data.set = bnlearn::gaussian.test

bayesianNetwork.fit = bn.fit(structure, data = data.set)

print(bayesianNetwork.fit$A)

---

Interactive Bayesian Network Strength Viewer

Description

Show the strength of the probabilistic relationships expressed by the arcs of a Bayesian network, and use model averaging to build a network containing only the significant arcs.

Usage

strength.viewer(
  bayesianNetwork,
  bayesianNetwork.boot.strength,
  bayesianNetwork.background = NULL,
  bayesianNetwork.arc.strength.threshold.expression = NULL,
  bayesianNetwork.arc.strength.threshold.expression.color = NULL,
  bayesianNetwork.arc.strength.threshold.alternative.color = NULL,
  bayesianNetwork.arc.strength.label = FALSE,
  bayesianNetwork.arc.strength.label.prefix = "",
  bayesianNetwork.arc.strength.label.color = NULL,
  bayesianNetwork.arc.strength.tooltip = FALSE,
  bayesianNetwork.edge.scale.min = 1,
  bayesianNetwork.edge.scale.max = 5,
  bayesianNetwork.edge.scale.label.min = 14,
  bayesianNetwork.edge.scale.label.max = 14,
  bayesianNetwork.title = "",
  bayesianNetwork.subtitle = "",
  bayesianNetwork.footer = "",
  bayesianNetwork.enabled.interactive.mode = FALSE,
  bayesianNetwork.layout = "default",
  bayesianNetwork.width = "100%",
  bayesianNetwork.height = "500px",
  node.shape = NULL,
  node.label.prefix = "",
  node.colors = list(),
  node.font = list(),
  node.size = 10,
  edges.smooth = TRUE,
  edges.dashes = FALSE,
  edges.colors = list(),
  edges.width = 1,
  options.highlightNearest = TRUE,
  options.nodesIdSelection = FALSE,
  clusters.legend.title = "",
  clusters.legend.options = list(),
  clusters = list()
)

Arguments

bayesianNetwork	A Bayesian Network structure from Averaged Network
bayesianNetwork.boot.strength	A nonparametric bootstrap to assess arc strength and direction
bayesianNetwork.background	Bayesian network background
bayesianNetwork.arc.strength.threshold.expression	Logical expression of the force threshold of the arcs of the Bayesian network
bayesianNetwork.arc.strength.threshold.expression.color	Color applied to logical expression of the force threshold of the arcs of the Bayesian network
bayesianNetwork.arc.strength.threshold.alternative.color	Alternative color to logical expression of the force threshold of the arcs of the Bayesian network
bayesianNetwork.arc.strength.label	Enable Bayesian Network arc strength label
bayesianNetwork.arc.strength.label.prefix	Include Bayesian Network arc strength label prefix
bayesianNetwork.arc.strength.label.color	Set Bayesian Network arc strength label color
bayesianNetwork.arc.strength.tooltip	Enable Bayesian Network arc strength tooltip
bayesianNetwork.edge.scale.min	Set bayesian Network edge scale minimum
bayesianNetwork.edge.scale.max	Set bayesian Network edge scale maximum
bayesianNetwork.edge.scale.label.min	Set bayesian Network edge scale label minimum
bayesianNetwork.edge.scale.label.max	Set bayesian Network edge scale label maximum
bayesianNetwork.title	: String. Bayesian Network title
bayesianNetwork.subtitle	: String. Bayesian Network subtitle
bayesianNetwork.footer	: String. Bayesian Network footer
bayesianNetwork.enabled.interactive.mode	: Boolean. Enabled interactive viewer mode.
bayesianNetwork.layout	: String. A layout of a Bayesian Network layout_on_sphere layout_on_grid layout_in_circle layout_as_star layout_as_tree layout_with_sugiyama layout_with_kk layout_with_dh layout_with_lgl layout_with_mds layout_with_gem layout_nicely layout_components layout_hierarchical_direction_UD layout_hierarchical_direction_DU layout_hierarchical_direction_LR layout_hierarchical_direction_RL
bayesianNetwork.width	: String. Bayesian Network width
bayesianNetwork.height	: String. Bayesian Network height
node.shape	: String. A node shape of a Bayesian Network dot (default) circle ellipse database diamond square triangle box star text
node.label.prefix	: String. Adds a prefix to the node label
node.colors	: String | named list. Color for the node. Can be 'rgba(120,32,14,1)', '#97C2FC' (hexa notation on 7 char without transparency) or 'red'. Can be just one color, or a list with several elements: "background" : String. Default to '#97C2FC'. Background color for the node. "border" : String. Default to '#2B7CE9'. Border color for the node. "highlight" : String | named list, Color of the node when selected. "background" : String. Default to '#97C2FC'. Background color for the node when selected. "border" : String. Default to '#2B7CE9'. Border color for the node when selected.
node.font	Node Font : Array. Example list(color = "black", face="Arial")
node.size	Integer. Node Size.
edges.smooth	: Boolean. When true, the edge is drawn as a dynamic quadratic bezier curve.
edges.dashes	: Array or Boolean. Default to false. When true, the edge will be drawn as a dashed line.
edges.colors	: Named list or String. Default to named list. Color information of the edge in every situation. Can be 'rgba(120,32,14,1)', '#97C2FC' (hexa notation on 7 char without transparency) or 'red'. "color" : String. Default to '#848484. The color of the edge when it is not selected or hovered over (assuming hover is enabled in the interaction module). "highlight " : String. Default to '#848484'. The color the edge when it is selected. "hover" : String. Default to '#848484'. The color the edge when the mouse hovers over it (assuming hover is enabled in the interaction module). "inherit" : String or Boolean. Default to 'from'. When color, highlight or hover are defined, inherit is set to false! Supported options are: true, false, 'from','to','both'. "opacity" : Number. Default to 1.0. It can be useful to set the opacity of an edge without manually changing all the colors. The allowed range of the opacity option is between 0 and 1.
edges.width	: Number. Default to 1. Sets edge width.
options.highlightNearest	: Boolean. Default to true. Highlight nearest when clicking a node.
options.nodesIdSelection	: Boolean. Default to false. Add an id node selection creating an HTML select element.
clusters.legend.title	: Array. Get details in the example.
clusters.legend.options	: Array of Array. Get details in the example.
clusters	: Array of Array. Get details in the example.

References

See online documentation http://robsonfernandes.net/bnviewer

Examples

library(bnlearn)
library(bnviewer)

bayesianNetwork.boot.strength = boot.strength(coronary, R = 20, algorithm = "hc")

avg.bayesianNetwork = averaged.network(bayesianNetwork.boot.strength, threshold = 0.2)

strength.viewer(
  avg.bayesianNetwork,
  bayesianNetwork.boot.strength,
  bayesianNetwork.background = "white",
  bayesianNetwork.arc.strength.threshold.expression = c("@threshold > 0 & @threshold < 0.5",
                                                        "@threshold >= 0.5 & @threshold < 0.6",
                                                        "@threshold >= 0.6 & @threshold <= 1"),

  bayesianNetwork.arc.strength.threshold.expression.color  = c("red", "yellow", "green"),
  bayesianNetwork.arc.strength.threshold.alternative.color =  "white",

  bayesianNetwork.arc.strength.label = TRUE,
  bayesianNetwork.arc.strength.label.prefix = "",
  bayesianNetwork.arc.strength.label.color = "black",

  bayesianNetwork.arc.strength.tooltip = TRUE,

  bayesianNetwork.edge.scale.min = 1,
  bayesianNetwork.edge.scale.max = 3,

  bayesianNetwork.edge.scale.label.min = 14,
  bayesianNetwork.edge.scale.label.max = 14,

  bayesianNetwork.width = "100%",
  bayesianNetwork.height = "800px",
  bayesianNetwork.layout = "layout_with_sugiyama",
  node.colors = list(background = "#97c2fc",
                     border = "#2b7ce9",
                     highlight = list(background = "#e91eba",
                                      border = "#2b7ce9")),

  node.font = list(color = "black", face="Arial"),
  edges.dashes = FALSE,

  bayesianNetwork.title="Bayesian Network Strength Analysis - Coronary",
  bayesianNetwork.subtitle = "Coronary heart disease data set",
  bayesianNetwork.footer = "Fig. 1 - Layout with Sugiyama"
)

---

Interactive Bayesian Network Viewer

Description

Interactive Bayesian Network Viewer

Usage

viewer(
  bayesianNetwork,
  bayesianNetwork.background = NULL,
  bayesianNetwork.title = "",
  bayesianNetwork.subtitle = "",
  bayesianNetwork.footer = "",
  bayesianNetwork.enabled.interactive.mode = FALSE,
  bayesianNetwork.layout = "default",
  bayesianNetwork.width = "100%",
  bayesianNetwork.height = "500px",
  bayesianNetwork.data = NULL,
  bayesianNetwork.correlation.show = FALSE,
  bayesianNetwork.correlation.method = "pearson",
  node.shape = NULL,
  node.label.prefix = "",
  node.colors = list(),
  node.font = list(),
  edges.smooth = TRUE,
  edges.dashes = FALSE,
  edges.width = 1,
  edges.font.size = 18,
  edges.font.color = "black",
  edges.shadow = FALSE,
  options.highlightNearest = TRUE,
  options.nodesIdSelection = FALSE,
  clusters.legend.title = "",
  clusters.legend.options = list(),
  clusters = list()
)

Arguments

bayesianNetwork	A Bayesian Network structure. (Example : hill-climbing (HC)).
bayesianNetwork.background	Bayesian network background
bayesianNetwork.title	: String. Bayesian Network title
bayesianNetwork.subtitle	: String. Bayesian Network subtitle
bayesianNetwork.footer	: String. Bayesian Network footer
bayesianNetwork.enabled.interactive.mode	: Boolean. Enabled interactive viewer mode.
bayesianNetwork.layout	: String. A layout of a Bayesian Network. The hierarchical layout the available options are: UD, DU, LR, RL. To simplify: up-down, down-up, left-right, right-left. layout_on_sphere layout_on_grid layout_in_circle layout_as_star layout_as_tree layout_with_sugiyama layout_with_kk layout_with_dh layout_with_lgl layout_with_mds layout_with_gem layout_nicely layout_components layout_hierarchical_direction_UD layout_hierarchical_direction_DU layout_hierarchical_direction_LR layout_hierarchical_direction_RL
bayesianNetwork.width	: String. Bayesian Network width
bayesianNetwork.height	: String. Bayesian Network height
bayesianNetwork.data	: List. Data Set.
bayesianNetwork.correlation.show	: Boolean. When true, show Correlation Coefficient. Default (FALSE).
bayesianNetwork.correlation.method	: String. Correlation Coefficient. One of "pearson" (default), "kendall", or "spearman"
node.shape	: String. A node shape of a Bayesian Network dot (default) circle ellipse database diamond square triangle box star text
node.label.prefix	: String. Adds a prefix to the node label
node.colors	: String | named list. Color for the node. Can be 'rgba(120,32,14,1)', '#97C2FC' (hexa notation on 7 char without transparency) or 'red'. Can be just one color, or a list with several elements: "background" : String. Default to '#97C2FC'. Background color for the node. "border" : String. Default to '#2B7CE9'. Border color for the node. "highlight" : String | named list, Color of the node when selected. "background" : String. Default to '#97C2FC'. Background color for the node when selected. "border" : String. Default to '#2B7CE9'. Border color for the node when selected.
node.font	: Array. Example list(color = "black", face="Arial")
edges.smooth	: Boolean. When true, the edge is drawn as a dynamic quadratic bezier curve.
edges.dashes	: Array or Boolean. Default to false. When true, the edge will be drawn as a dashed line.
edges.width	: Number. Sets edge width. Default to 1.
edges.font.size	: Number. Font Size. Default to 18.
edges.font.color	: String. Font Color. Default to 'black'.
edges.shadow	: Boolean. Shadow. Default to FALSE.
options.highlightNearest	: Boolean. Default to true. Highlight nearest when clicking a node.
options.nodesIdSelection	: Boolean. Default to false. Add an id node selection creating an HTML select element.
clusters.legend.title	: Array. Get details in the example.
clusters.legend.options	: Array of Array. Get details in the example.
clusters	: Array of Array. Get details in the example.

References

See online documentation http://robsonfernandes.net/bnviewer

See the code fontAwesome for icons in groups and nodes https://fontawesome.com/v4.7.0/cheatsheet/

Examples

library(bnlearn)
library(bnviewer)

data("alarm")
bayesianNetwork = hc(alarm)

viewer(bayesianNetwork,
       bayesianNetwork.background = "-webkit-radial-gradient(center, ellipse cover,
                                                             rgba(255,255,255,1) 0%,
                                                             rgba(246,246,246,1) 47%,
                                                             rgba(237,237,237,1) 100%)",
       bayesianNetwork.width = "100%",
       bayesianNetwork.height = "100vh",
       bayesianNetwork.layout = "layout_components",
       bayesianNetwork.title="<br>Discrete Bayesian Network - Alarm",
       bayesianNetwork.subtitle = "Monitoring of emergency care patients",

       node.colors = list(background = "white",
                          border = "black",
                          highlight = list(background = "#e91eba",
                                           border = "black")),
       node.font = list(color = "black", face="Arial"),

       clusters.legend.title = list(text = "<b>Legend</b> <br> Variable Categories",
                                    style = "font-size:18px;
                                             font-family:Arial;
                                             color:black;
                                             text-align:center;"),
       clusters.legend.options = list(
         list(label = "Pressure",
              shape = "icon",
              icon = list(code = "f1ce",
                          size = 50,
                          color = "#e91e63")),
         list(label = "Volume",
              shape = "icon",
              icon = list(code = "f140",
                          size = 50,
                          color = "#03a9f4")),
         list(label = "Ventilation",
              shape = "icon",
              icon = list(code = "f192",
                          size = 50,
                          color = "#4caf50")),
         list(label = "Saturation",
              shape = "icon",
              icon = list(code = "f10c",
                          size = 50,
                          color = "#ffc107"))
       ),

       clusters = list(
         list(label = "Pressure",
              shape = "icon",
              icon = list(code = "f1ce", color = "#e91e63"),
              nodes = list("CVP","BP","HRBP","PAP","PRSS")),
         list(label = "Volume",
              shape = "icon",
              icon = list(code = "f140", color = "#03a9f4"),
              nodes = list("MINV","MVS","LVV","STKV")),
         list(label = "Ventilation",
              shape = "icon",
              icon = list(code = "f192", color = "#4caf50"),
              nodes = list("VALV","VLNG","VTUB","VMCH")),
         list(label = "Saturation",
              shape = "icon",
              icon = list(code = "f10c", color = "#ffc107"),
              nodes = list("HRSA","SAO2","PVS"))
       )
)

---