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#' Cumulative sum of germination by period of time for line graphic
#'
#' @description This function makes a data table with the cumulative sum of values of germination by days.
#' @details Need a summary by factor before use it with function SummaryBy.
#' @param Factor Factor which will be graph in time
#' @param SeedN Name of the column with the seed numbers
#' @param evalName Prefix of the evaluation variable
#' @param method Type of cumulative germination. "percentage" or "relative"
#' @param data Data with the germination evaluation process
#' @return Data frame with the germination by period
#' @importFrom stats sd
#' @import dplyr
#' @import tidyr
#' @export
#'
#' @examples
#'
#' \dontrun{
#'
#' library(GerminaR)
#' data <- prosopis
#' grt <- ger_intime(Factor = "temp"
#' , SeedN = "seeds"
#' , evalName = "D"
#' , method = "rel"
#' , data = data)
#'
#' head(grt, 10)
#'
#' fplot(data = grt
#' , type = "line"
#' , x = "evaluation"
#' , y = "mean"
#' , groups = "temp"
#' , sig = NULL)
#'
#' }
#'
ger_intime <- function(Factor
, SeedN
, evalName
, method = "percentage"
, data
){
n <- std <- r <- germination <- evaluation <- where <- NULL
# arguments ---------------------------------------------------------------
method <- match.arg(method, c("percentage", "relative"))
evf <- data %>% select(!starts_with({{evalName}}))
evd <- data %>% select(starts_with({{evalName}}))
sdn <- data[, SeedN]
# Cumulative --------------------------------------------------------------
# -------------------------------------------------------------------------
grs <- ger_GRS(evalName, data)
cal <- apply(cbind(evd), 1, cumsum )
if (method == "percentage") {
temp <- t(cal) * 100 / sdn
acum <- cbind(evf, temp)
} else if (method == "relative") {
temp <- t(cal) * 100 / grs
acum <- cbind(evf, temp)
}
# in-time -----------------------------------------------------------------
# -------------------------------------------------------------------------
git <- acum %>%
pivot_longer(names(evd)
, names_to = "evaluation"
, values_to = "germination"
, values_drop_na = TRUE
) %>%
group_by(.data[[Factor]], evaluation) %>%
summarise(mean = mean(germination, rm.na = TRUE)
, r = dplyr::n()
, std = sd(germination)
, min = min(germination)
, max = max(germination)
) %>%
ungroup() %>%
mutate(ste = std/sqrt(r)) %>%
mutate(evaluation = gsub("\\D", "", evaluation)) %>%
mutate(across(evaluation, ~ as.numeric(.))) %>%
arrange(evaluation) %>%
mutate(across( {{Factor}}, ~ as.factor(.)))
# result ------------------------------------------------------------------
git
}
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