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#' @title Total Volumen of Activity for Whole Dataset
#' @description Calculate total volume of activity level, which includes
#' \code{TLAC} (total log transfored activity counts),
#' \code{TAC} (total activity counts).
#'
#' @param count.data \code{data.frame} of dimension n*1442 containing the 1440 minute activity data for all n subject days.
#' The first two columns have to be ID and Day.
#' @param weartime \code{data.frame} with dimension of \code{count.data}.
#' The first two columns have to be ID and Day.
#' @param logtransform if \code{TRUE}, then calcualte \code{TLAC}. Or calculate \code{TAC}.
#' @param log.multiplier \code{number} The coefficient used in the log transformation of the ENMO data, i.e. log( log.multiplier * ENMO + 1). Defaut is 9250.
#'
#'
#' @return A dataframe with some of the following columns
#' \item{ID}{identifier of the person}
#' \item{Day}{indicator of which day of activity it is, can be a numeric vector of sequence 1,2,... or a string of date}
#' \item{TAC}{total activity count}
#' \item{TLAC}{total log activity count}
#'
#'
#' @export
#' @details log transormation is defined as log(x+1).
#'
#'
Tvol2 = function(
count.data,
weartime,
logtransform = FALSE,
log.multiplier=9250
){
if(missing(weartime)){
print("No weartime supplied, calculated based on defualt from 05:00 to 23:00")
weartime = wear_flag(count.data = count.data)
}
uwear = unique(unlist(c(weartime[,-c(1,2)])))
uwear = as.integer(uwear)
if (!all(uwear %in% c(0, 1))) {
stop("weartime matrix has non 0-1 data! Set NA to 0 if missing")
}
count.mat = as.matrix(count.data[,-c(1:2)])
wear.mat = as.matrix(weartime[,-c(1:2)])
if(logtransform){
count.mat = log(count.mat*log.multiplier + 1)
}
adj.ct = count.mat * wear.mat
tvol = as.data.frame(cbind(count.data[,c(1:2)],apply(adj.ct, 1, sum)))
if(logtransform){
names(tvol) = c("ID","Day","TLAC")
}
if(!logtransform){
names(tvol) = c("ID","Day","TAC")
}
return(tvol = tvol)
}
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