plotData: Plot categorical functional data

Description

Plot categorical functional data

Usage

plotData(
  data,
  group = NULL,
  col = NULL,
  addId = TRUE,
  addBorder = TRUE,
  sort = FALSE,
  nCol = NULL
)

Value

a ggplot object that can be modified using ggplot2 package. On the plot, each row represents an individual over [0:Tmax]. The color at a given time gives the state of the individual.

Arguments

data: data.frame containing id, id of the trajectory, time, time at which a change occurs and state, associated state.
group: vector, of the same length as the number individuals of data, containing group index. Groups are displayed on separate plots. If group = NA, the corresponding individuals in data is ignored.
col: a vector containing color for each state (can be named)
addId: If TRUE, add id labels
addBorder: If TRUE, add black border to each individual
sort: If TRUE, id are sorted according to the duration in their first state
nCol: number of columns when group is given

Author

Cristian Preda, Quentin Grimonprez

Examples

Run this code

# Simulate the Jukes-Cantor model of nucleotide replacement
K <- 4
PJK <- matrix(1 / 3, nrow = K, ncol = K) - diag(rep(1 / 3, K))
lambda_PJK <- c(1, 1, 1, 1)
d_JK <- generate_Markov(n = 10, K = K, P = PJK, lambda = lambda_PJK, Tmax = 10)

# add a line with time Tmax at the end of each individual
d_JKT <- cut_data(d_JK, Tmax = 10)

plotData(d_JKT)

# modify the plot using ggplot2
library(ggplot2)
plotData(d_JKT, col = c("red", "blue", "green", "brown")) +
  labs(title = "Trajectories of a Markov process")


# use the group variable: create a group with the 3 first variables and one with the others
group <- rep(1:2, c(3, 7))
plotData(d_JKT, group = group)


# use the group variable: remove the id number 5 and 6
group[c(5, 6)] <- NA
plotData(d_JKT, group = group)