ena.plot.network: Plot an ENA network

Description

Plot an ENA network: nodes and edges

Usage

ena.plot.network(enaplot = NULL, network = NULL, colors = c(pos = "red",
  "blue"), show.all.nodes = T, threshold = 0, thin.lines.in.front = T,
  opacity = c(0.3, 1), saturation = c(0.25, 1), thickness = c(0, 1),
  node.size = c(3, 10), range = c(min(network), max(network)),
  labels = rownames(enaplot$enaset$node.positions), label.offset = NULL,
  label.font.size = enaplot$get("font.size"),
  label.font.color = enaplot$get("font.color"),
  label.font.family = enaplot$get("font.family"), legend.name = NULL,
  legend.include.edges = F, ...)

Arguments

enaplot

ENAplot object to use for plotting

network

dataframe or matrix containing the edge weights for the network graph; typically comes from ENAset$line.weights

colors

A String or vector of colors for positive and negative line weights. E.g. red or c(pos= red, neg = blue), default: c(pos= red, neg = blue)

show.all.nodes

A Logical variable, default: true

threshold

A vector of numeric min/max values, default: (0,1). Edge weights below the min value will not be displayed; edge weights above the max value will be shown at the max value.

thin.lines.in.front

A logical, default: true

opacity

A vector of numeric min/max values for opacity, default: (0.3,1)

saturation

A vector of numeric min/max values for saturation, default: (0.25, 1)

thickness

A vector of numeric min/max values for thickness, default: (0, 1)

node.size

A lower and upper bound used for scaling the size of the nodes, default c(0, 20)

range

A vector of min/max values. Options are numeric, set.min, set.max, plot.min, plot.max, default: (set.min, set.max). Determines the line weight that corresponds to the thinnest (min) and thickest (max) lines in the network graph

labels

A character vector of node labels, default: code names

label.offset

A numeric vector of an x and y value to offset labels from the coordinates of the points

label.font.size

An integer which determines the font size for graph labels, default: enaplot$font.size

label.font.color

A character which determines the color of label font, default: enaplot$font.color

label.font.family

A character which determines font type, choices: Arial, Courier New, Times New Roman, default: enaplot$font.family

legend.name

A character name to include in the legend. Not included in legend when NULL. Default: NULL

legend.include.edges

Logical value indicating if the edges should be included in the plot

...

Additional parameters

Value

The ENAplot provided to the function, with its plot updated to include the nodes and provided connecting lines.

Details

lots a network graph, including nodes (taken from codes in the ENAplot) and the edges (provided in network)

Examples

Run this code

# NOT RUN {
data(RS.data)

codeNames = c('Data','Technical.Constraints','Performance.Parameters',
  'Client.and.Consultant.Requests','Design.Reasoning','Collaboration');

accum = ena.accumulate.data(
  units = RS.data[,c("UserName","Condition")],
  conversation = RS.data[,c("Condition","GroupName")],
  metadata = RS.data[,c("CONFIDENCE.Change","CONFIDENCE.Pre","CONFIDENCE.Post")],
  codes = RS.data[,codeNames],
  window.size.back = 4
)

set = ena.make.set(
  enadata = accum,
  rotation.by = ena.rotate.by.mean,
  rotation.params = list(
      accum$metadata$Condition=="FirstGame",
      accum$metadata$Condition=="SecondGame"
  )
)

plot = ena.plot(set)

unitNames = set$enadata$units

### Subset rotated points and plot Condition 1 Group Mean
first.game = unitNames$Condition == "FirstGame"
first.game.points = set$points.rotated[first.game,]
plot = ena.plot.group(plot, first.game.points, labels = "FirstGame",
    colors = "red", confidence.interval = "box")

### Subset rotated points and plot Condition 2 Group Mean
second.game = unitNames$Condition == "SecondGame"
second.game.points = set$points.rotated[second.game,]
plot = ena.plot.group(plot, second.game.points, labels = "SecondGame",
    colors  = "blue", confidence.interval = "box")

### get mean network plots
first.game.lineweights = set$line.weights[first.game,]
first.game.mean = colMeans(first.game.lineweights)

second.game.lineweights = set$line.weights[second.game,]
second.game.mean = colMeans(second.game.lineweights)

subtracted.network = first.game.mean - second.game.mean
plot = ena.plot.network(plot, network = subtracted.network)
print(plot)

# }