#' @name summary
#' @title summary for hybrid models
#'
#' @description \code{summary.HM} is a method to print a summary with basic
#' description of nodes' states at a specific time (the time must
#' be present in the network data). The default value is Null,
#' that means it prints nodes' final states.
#'
#' @param object \code{HM} object
#'
#' @param stateVars \code{\link{vector}} containing the state variable to
#' summarize. The default value is NULL, which will print a
#' summary with all states.
#'
#' @param at the date (as character) that will be used to print the summary
#'
#' @param nodes \code{\link{vector}} containing the nodes of interest. The
#' default value is NULL, which will print a summary with all
#' nodes.
#'
#' @param ... arguments to be passed to methods.
#'
#' @references
#' [1] Fernando S. Marques, Jose H. H. Grisi-Filho, Marcos Amaku et al.
#' hybridModels: An R Package for the Stochastic Simulation of Disease Spreading
#' in Dynamic Network. In: Jounal of Statistical Software Volume 94, Issue 6
#' <doi:10.18637/jss.v094.i06>.
#'
#' @export
#'
#' @examples
#' # Parameters and initial conditions for an SIS model
#' # loading the data set
#' data(networkSample) # help("networkSample"), for more info
#' networkSample <- networkSample[which(networkSample$Day < "2012-03-20"),]
#'
#' var.names <- list(from = 'originID', to = 'destinationID', Time = 'Day',
#' arc = 'num.animals')
#'
#' prop.func <- c('beta * S * I / (S + I)', 'gamma * I')
#' state.var <- c('S', 'I')
#' state.change.matrix <- matrix(c(-1, 1, # S
#' 1, -1), # I
#' nrow = 2, ncol = 2, byrow = TRUE)
#'
#' model.parms <- c(beta = 0.1, gamma = 0.01)
#'
#' init.cond <- rep(100, length(unique(c(networkSample$originID,
#' networkSample$destinationID))))
#' names(init.cond) <- paste('S', unique(c(networkSample$originID,
#' networkSample$destinationID)), sep = '')
#' init.cond <- c(init.cond, c(I36811 = 10, I36812 = 10)) # adding infection
#'
#' # running simulations, check num of cores available (num.cores)
#' sim.results <- hybridModel(network = networkSample, var.names = var.names,
#' model.parms = model.parms, state.var = state.var,
#' prop.func = prop.func, init.cond = init.cond,
#' state.change.matrix = state.change.matrix,
#' sim.number = 4, num.cores = 2)
#'
#' summary(sim.results, stateVars = c('S', 'I'), nodes = c(36812, 36813))
#'
summary.HM <- function(object, at = NULL, stateVars = NULL, nodes = NULL, ...){
if (is.null(at)){
at = max(object$results$Day)
}
if (is.null(stateVars) & is.null(nodes)){
summ.result <- object$results[which(object$results$Day == at),]
return(summary(summ.result))
} else if(is.null(nodes)){
stateVars <- match.arg(stateVars, object$ssaObjet$state.var, several.ok = TRUE)
summ.result <- object$results[which(object$results$Day == at),
grep(paste("^", stateVars, sep='',
collapse="|"), colnames(object$results))]
return(summary(summ.result))
} else if(is.null(stateVars)){
nodes <- match.arg(as.character(nodes),
unique(sub(paste("^", object$ssaObjet$state.var, sep='',
collapse="|"), '',
colnames(object$results)[c(-1, -2)])),
several.ok = TRUE)
summ.result <- object$results[which(object$results$Day == at),
grep(paste("^",
apply(expand.grid(object$ssaObjet$state.var,
nodes), 1, paste,
collapse = ""), sep='',
collapse="|"), colnames(object$results))]
return(summary(summ.result))
} else{
stateVars <- match.arg(stateVars, object$ssaObjet$state.var, several.ok = TRUE)
nodes <- match.arg(as.character(nodes),
unique(sub(paste("^", object$ssaObjet$state.var, sep='',
collapse="|"), '',
colnames(object$results)[c(-1, -2)])),
several.ok = TRUE)
summ.result <- object$results[which(object$results$Day == at),
grep(paste("^",
apply(expand.grid(stateVars, nodes), 1,
paste, collapse = ""), sep='',
collapse="|"), colnames(object$results))]
return(summary(summ.result))
}
}
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