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AssessmentModule.R
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AssessmentModule.R
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################################################################################################################################
#############------------------------------------------------------------------------------------------------------#############
#############---------------------------------- Ascendance "Assess" Module ----------------------------------------#############
#############------------------------------------------------------------------------------------------------------#############
################################################################################################################################
#' This module generates the optimal curves overall and for individual focus areas.
coltime <- function(dat, names, colName = "X") {
if (length(names) == 0) {
colSum <- data.frame(X = as.difftime(rep(0, nrow(dat)), units = "secs"))
names(colSum) <- colName
colSum
} else {
colSum <- dat[,names[1], drop = FALSE]
for (i in 1:nrow(colSum)) {
colSum[i,] <- as.difftime(0, units = "secs")
}
for (i in names) {
colSum <- colSum + dat[,i, drop = FALSE]
}
names(colSum) <- colName
colSum
}
}
#' This module presents the global optimal curve along with various specific focus area curves
curveboxUI <- function(id, ID) {
ns <- NS(id)
box(width = 6, title = ID, fluidRow(column(12, plotOutput(ns("curve")))))
}
# the piebox server must be passed the focus area of the box in the argument 'ID'
curvebox <- function(input, output, session, ID, Path) {
load(Path)
rv <- reactiveValues()
rv$A <- A
dat <- A$opC[, (colnames(A$opC) == ID) | (colnames(A$opC) == "fp")]
Dat <- dat
dayafter <- dat$fp[dat$fp == max(dat$fp)] + as.difftime(1, units = "days")
x <- c(dat$fp[1], dat$fp[dat$fp > dat$fp[1]], dayafter, dayafter, dat$fp[1])
y <- c(as.difftime(0, units = "hours"), dat[[ID]][dat$fp >= dat$fp[1]],
as.difftime(0, units = "hours"), as.difftime(0, units = "hours"))
shade <- data.frame(x, y)
#####
faIndex <- colnames(A$tentr$start) %in% A$tdat$ID[A$tdat$fa == ID]
if (all(faIndex == FALSE)) {
} else {
dat <- A$Logged[,c("fp", ID)]
print(dat); print(ID)
colnames(dat) <- c("fp", "bcggplot")
pointdat <- dat[nrow(dat),]
output$curve <- renderPlot({
ggplot(data = Dat, aes(x = fp, y = ID)) + geom_polygon(data = shade, aes(x, y), alpha = .80) +
theme(axis.text.x = element_text(angle = 90, vjust = .5), panel.grid.minor.x = element_blank()) +
scale_x_datetime(breaks = Dat$fp, labels = format(Dat$fp +as.difftime(1, units = "days"), "%a %d"), name = NULL) +
scale_y_continuous(name = NULL) + geom_line(data = dat, aes(x = fp, y = bcggplot), color = "steelblue", size = 1.5) +
geom_point(data = pointdat, aes(x = fp, y = bcggplot), color = "steelblue", size = 4)
})
}
}
assessUI <- function(id) {
ns <- NS(id)
fluidRow(
column(11, offset = 1,
tabBox(title = "Global Assessment", width = 11,
tabPanel("Hours",
fluidRow(column(12, plotOutput(ns("hoursGlobal")))),
fluidRow(column(12, offset = 1))
),
tabPanel("Tasks", br(),
fluidRow(column(12, dataTableOutput(ns("priorGlobal")))),
fluidRow(column(5, offset = 2, h4("General")))
)
)
),
column(10, offset = 1,
lapply(unlist(A$fdat$fa), function(id) {curveboxUI(ns(id), id)})
)
)
}
assess <- function(input, output, session, Path) {
load(Path)
ns <- session$ns
dayafter <- A$opC$fp[A$opC$fp == max(A$opC$fp)] + as.difftime(1, units = "days")
x <- c(A$opC$fp[1], A$opC$fp[A$opC$fp > A$opC$fp[1]], dayafter, dayafter, A$opC$fp[1])
y <- c(as.difftime(0, units = "hours"), A$opC$full[A$opC$fp >= A$opC$fp[1]],
as.difftime(0, units = "hours"), as.difftime(0, units = "hours"))
shade <- data.frame(x, y)
if (5 > 8) {
tentr <- as.list(rep(Sys.time(), length(A$tdat$ID)))
names(tentr) <- colnames(A$opC)[colnames(A$opC) %in% A$tdat$ID]
tentr <- data.frame(tentr, stringsAsFactors = FALSE)
colnames(tentr) <- colnames(A$opC)[colnames(A$opC) %in% A$tdat$ID]
tentr <- lapply(1:2, function(x) { tentr })
names(tentr) <- c("start", "end")
auto <- as.list(rep("", length(A$tdat$tasks)))
names(auto) <- colnames(A$opC)[colnames(A$opC) %in% A$tdat$ID]
auto <- data.frame(auto, stringsAsFactors = FALSE)
colnames(auto) <- colnames(A$opC)[colnames(A$opC) %in% A$tdat$ID]
eff <- as.list(rep(0, length(A$tdat$tasks)))
names(eff) <- colnames(A$opC)[colnames(A$opC) %in% A$tdat$ID]
eff <- data.frame(eff, stringsAsFactors = FALSE)
colnames(eff) <- colnames(A$opC)[colnames(A$opC) %in% A$tdat$ID]
dummy <- list()
dummy$auto <- auto; dummy$start <- tentr$start; dummy$end <- tentr$end; dummy$eff <- eff
A$tentr <- dummy
timediff <- (A$fps[[1]][2] - A$fps[[1]][1])/2
latemail <- function(N, st=A$fps[[1]][1], et= as.POSIXct(A$fps[[1]][2])+ as.difftime(7, units = "hours")-timediff) {
st <- as.POSIXct(as.Date(st)) + as.difftime(7, units = "hours")
et <- as.POSIXct(as.Date(et)) + as.difftime(7, units = "hours")
dt <- as.numeric(difftime(et,st,unit="sec"))
ev <- sort(runif(N, 0, dt))
rt <- st + ev
}
simulate_data <- function(N, meanHour = .4, stdHour = .05, meanEff = .5, stdEff = .1) {
lapply(1:N, function(x) {
A$tentr$auto <- rbind(A$tentr$auto, as.list(rep("", ncol(A$tentr$start))))
A$tentr$start <- rbind(A$tentr$start, as.list(rep(Sys.time(), ncol(A$tentr$start))))
A$tentr$end <- rbind(A$tentr$end, as.list(rep(Sys.time(), ncol(A$tentr$start))))
A$tentr$eff <- rbind(A$tentr$eff, as.list(rep(0, ncol(A$tentr$start))))
start <- latemail(length(A$tdat$ID))
end <- start + as.difftime(rnorm(length(A$tdat$ID), meanHour, stdHour), units = "hours")
effEst <- rnorm(length(A$tdat$ID), meanEff, stdEff)
start <- as.list(start)
names(start) <- colnames(A$tentr$start)
end <- as.list(end)
names(end) <- colnames(A$tentr$end)
effEst <- as.list(effEst)
names(effEst) <- colnames(A$tentr$eff)
A$tentr$start[x,] <- as.data.frame(start, optional = TRUE)
A$tentr$end[x,] <- as.data.frame(end, optional = TRUE)
A$tentr$eff[x,] <- as.data.frame(effEst, optional = TRUE)
})
}
simulate_data(10)
}
now <- Sys.time()
Logged <- A$tentr$end - A$tentr$start
difftime_start <- Logged; difftime_end <- Logged
dum <- difftime_start
dum[] <- lapply(1:ncol(difftime_start), function(x) {
lapply(1:nrow(difftime_start), function(y) {
dum[y,x] <- dum[y,x] != as.difftime(0, units = "hours")
})
})
if (nrow(Logged) == 1 | nrow(Logged) == 2) {
for (i in as.character(rev(unlist(A$cdat$ID)))) {
focusIncat <- A$cdat$fa[A$cdat$ID == i]
catIncat <- A$cdat$cat[A$cdat$ID == i]
taskIDsInCat <- as.character(A$tdat$ID[(A$tdat$fa %in% focusIncat) & (A$tdat$cat %in% catIncat)])
Logged <- cbind(coltime(Logged, taskIDsInCat, i), Logged)
}
for (i in rev(unlist(A$fdat$fa))) {
taskIDsInFa <- as.character(A$tdat$ID[A$tdat$fa %in% i])
Logged <- cbind(coltime(Logged, taskIDsInFa, i), Logged)
}
Logged <- cbind(coltime(Logged, as.character(unlist(A$tdat$ID)), colName = "full"), Logged)
Logged[] <- lapply(1:ncol(Logged), function(x) {
lapply(1:nrow(Logged), function(y) {
a <- Logged[y,x]
units(a) <- "hours"
a
})
})
Logged[] <- lapply(1:ncol(Logged), function(x) {
Logged[,x] <- unlist(Logged[,x])
})
Logged <- cbind(fp = as.POSIXct(A$fps[[1]][1]) + as.difftime(7, units = "hours"), Logged)
Ender <- Logged[nrow(Logged),]; Ender$fp <- now
Logged <- rbind(Logged, Ender)
A$Logged <- Logged; save(A, file = Path)
pointdat <- Logged[nrow(Logged),c("fp", "full")]
} else {
Starter <- difftime_start[1,]
difftime_start <- difftime_start[2:nrow(difftime_start),]
Ender <- difftime_end[1,]
difftime_end <- difftime_end[2:nrow(difftime_end),]
Logged <- Logged[2:nrow(Logged),]
startTimes <- as.POSIXct(A$tentr$start[dum == TRUE]); endTimes <- as.POSIXct(A$tentr$end[dum == TRUE])
startOrder <- order(startTimes)
startTimes <- startTimes[startOrder]; endTimes <- endTimes[startOrder]
difftime_start <- difftime_start[startOrder,]
difftime_end <- difftime_end[startOrder,]
startIndex <- seq(length.out = nrow(difftime_start), by = 2)
difftime_startC <- difftime_start
endIndex <- seq(length.out = nrow(difftime_end), by = 2)+1
difftime_endC <- difftime_end
cumtime <- function(x) {
for (i in 1:(length(x)-1)) {
x[i+1] <- x[i] + x[i+1]
}
x
}
difftime_startC[] <- lapply(1:ncol(difftime_startC), function(x) {
cumtime(unlist(difftime_startC[,x]))
})
difftime_endC[] <- lapply(1:ncol(difftime_endC), function(x) {
cumtime(unlist(difftime_endC[,x]))
})
difftime_startC <- cbind(difftime_startC, index = startIndex)
difftime_endC <- cbind(difftime_endC, index = endIndex)
difftime_startC <- cbind(fp = startTimes, difftime_startC)
difftime_endC <- cbind(fp = endTimes, difftime_endC)
Logged <- rbind(difftime_startC, difftime_endC)
Logged <- Logged[order(Logged$index),1:(ncol(Logged)-1)]
startDate <- as.POSIXct(A$fps[[1]][1]) + as.difftime(7, units = "hours")
Starter <- cbind(fp = startDate, Starter)
Ender <- cbind(fp = now, Logged[nrow(Logged), 2:ncol(Logged)])
Logged <- rbind(Starter, Logged)
Logged <- rbind(Logged, Ender)
loggedTimes <- Logged$fp
Logged <- Logged[,2:ncol(Logged)]
for (i in as.character(rev(unlist(A$cdat$ID)))) {
focusIncat <- A$cdat$fa[A$cdat$ID == i]
catIncat <- A$cdat$cat[A$cdat$ID == i]
taskIDsInCat <- as.character(A$tdat$ID[(A$tdat$fa %in% focusIncat) & (A$tdat$cat %in% catIncat)])
Logged <- cbind(coltime(Logged, taskIDsInCat, i), Logged)
}
for (i in rev(unlist(A$fdat$fa))) {
taskIDsInFa <- as.character(A$tdat$ID[A$tdat$fa %in% i])
Logged <- cbind(coltime(Logged, taskIDsInFa, i), Logged)
}
Logged <- cbind(coltime(Logged, as.character(unlist(A$tdat$ID)), colName = "full"), Logged)
Logged[] <- lapply(1:ncol(Logged), function(x) {
lapply(1:nrow(Logged), function(y) {
a <- Logged[y,x]
units(a) <- "hours"
a
})
})
Logged[] <- lapply(1:ncol(Logged), function(x) {
Logged[,x] <- unlist(Logged[,x])
})
Logged <- cbind(fp = loggedTimes, Logged)
A$Logged <- Logged; save(A, file = Path)
pointdat <- Logged[nrow(Logged),c("fp", "full")]
}
output$hoursGlobal <- renderPlot({
ggplot(data = A$opC, aes(x = fp, y = full)) +
geom_polygon(data = shade, aes(x, y), alpha = .80) +
theme(axis.text.x = element_text(angle = 90, vjust = .5), panel.grid.minor.x = element_blank()) +
scale_x_datetime(breaks = A$opC$fp, labels = format(A$opC$fp+as.difftime(1, units = "days"), "%a %d"), name = NULL) +
scale_y_continuous(name = NULL) +
geom_line(data = Logged, aes(x = fp, y = full), color = "steelblue", size = 1.5) +
geom_point(data = pointdat, aes(x = fp, y = full), color = "steelblue", size = 4)
})
output$priorGlobal <- renderDataTable(options = list(pageLength = 10), {
dat <- A$tdat
dat$end <- as.list(as.POSIXct(unlist(dat$end), origin = "1970-01-01 00:00.00 UTC") + as.difftime(7, units = "hours")) %>% I
dat$end <- format(dat$end, '%Y-%m-%d')
dat$start <- as.list(as.POSIXct(unlist(dat$start), origin = "1970-01-01 00:00.00 UTC") + as.difftime(7, units = "hours")) %>% I
dat$start <- format(dat$start, '%Y-%m-%d')
newcol <- dat$est %>% unlist %>% as.difftime( . , units = "mins")
units(newcol) <- "hours"
dat$est <- newcol %>% as.list
dat
})
lapply(unlist(A$fdat$fa), function(id) {
callModule(curvebox, id, ID = id, Path = Path)
})
}