Plots a heatmap of the relative transmission probabilities

Source: R/visualizeResults.R

The function nbHeatmap plots a heatmap of the transmission probabilities. The rows are the possible infectors and the columns are the possible infectees both ordered by <dateVar>. The darker the square the higher the probability that the pair represented by that square is a transmission link. If a cluster method is specified using clustMethod and cutoff, then stars will be drawn in the squares of the infectors in the top cluster.

nbHeatmap(
  df,
  indIDVar,
  dateVar,
  pVar,
  clustMethod = c("none", "n", "kd", "hc_absolute", "hc_relative"),
  cutoff = NA,
  blackAndWhite = FALSE,
  probBreaks = c(-0.01, 0.001, 0.005, 0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1)
)

Arguments

df

The name of the dateset with transmission probabilities (column pVar), individual IDs (columns <indIDVar>.1 and <indIDVar>.2), and the dates of observation (columns <dateVar>.1 and <dateVar>.2).

indIDVar

The name (in quotes) of the individual ID columns (data frame df must have variables called <indIDVar>.1 and <indIDVar>.2).

dateVar

The name (in quotes) of the columns with the dates that the individuals are observed (data frame df must have variables called <dateVar>.1 and <dateVar>.2).

pVar

The name (in quotes) of the column with transmission probabilities.

clustMethod

The method used to cluster the infectors; one of "none", "n", "kd", "hc_absolute", "hc_relative" where "none" or not specifying a value means use all pairs with no clustering (see clusterInfectors for detials on clustering methods).

cutoff

The cutoff for clustering (see clusterInfectors).

blackAndWhite

A logical. If TRUE, then the squares are colored in greyscale, if FALSE, then the squares are colored with shades of blue.

probBreaks

A numeric vector containing between 3 and 10 elements specifying the boundaries used to classify the probabilities and color the squares. The first element should be less than 0 and the last should be 1.

Details

Users have the option of specifying how the probabilities should be grouped into different color shades through the argument probBreaks. The probabilities are split into groups by using probBreaks as the breaks argument in cut with the default options. The length of the vector should be between 3 and 10 and the first element should be less than 0 and the last 1 so that all probabilities are guarenteed to be classified. The colors are defined with the code brewer.pal(length(probBreaks) - 1, "Blues") (where "Blues" is replaced by "Greys" if blackAndWhite is set to TRUE).

NOTE: This plot will take long to run and may not look good with larger outbreaks (>200 individuals)

Examples


# \donttest{
## Heatmap with no clustering in color with the default probability breaks
par(mar = c(0, 0, 1, 0))
nbHeatmap(nbResults, indIDVar = "individualID", dateVar = "infectionDate",
pVar = "pScaled", clustMethod = "none")

dev.off() 
#> null device 
#>           1 


## Adding stars for the top cluster, in black and white, changing the probability breaks
par(mar = c(0, 0, 1, 0))
nbHeatmap(nbResults, indIDVar = "individualID", dateVar = "infectionDate",
          pVar = "pScaled", clustMethod = "hc_absolute", cutoff = 0.05,
          blackAndWhite = TRUE, probBreaks = c(-0.01, 0.01, 0.1, 0.25, 0.5, 1))
dev.off()
#> null device 
#>           1 
# }