R/isolate_full_dataset.R

In andrewstiegler/telemetRy: Functions for Importing and Manipulating DSI Telemetry Data

#' Isolate parameters from complete telemetry dataframe.
#'
#' @description
#' These functions take the output of DSI_export_to_dataframe and outputs a new
#' dataframe for the specified parameter.
#' @param data A dataframe which is the output from DSI_export_to_dataframe.
#' @param parameter Name of a parameter to isolate in the dataframe.
#' @param mean_col A boolean for including a new column with the group mean for
#' the selected parameter.
#' @return A dataframe with the Time and elapsed_time columns from the input,
#' and a column for each subject appended with the parameter (i.e. SBP).
#' Additionally an optional column for the mean of all subjects in the dataset.
#' @describeIn isolate_parameter Isolate parameter from complete telemetry
#' dataframe export.
#' @examples
#' isolate_parameter(sample_BP_data, parameter = SBP)
#' isolate_parameter(sample_BP_data, parameter = MAP, mean_col = TRUE)
#'
# isolate_sbp function takes DSI_export_to_dataframe output and isolates SBP
# keeps time columns, each SN gets an SBP column named "SNSBP"

isolate_parameter <- function (data, parameter, mean_col=FALSE) {

    quo_parameter <- enquo(parameter)

    if (sum(grepl(".id", colnames(data))) != 0) {
        data_idcol <- data$.id %>% unique()

        data_idcol <- (data %>% select(.data$.id) %>% unique())[[1]]

        parameter_joined <- list()

        for (isolate_iterator in 1:length(data_idcol)){
            parameter_next <- filter(data, .data$.id ==
                                         data_idcol[[isolate_iterator]]) %>%
                select(.data$Time, !! quo_parameter)
            colnames(parameter_next)[2] <- paste(data_idcol[[isolate_iterator]],
                                                 quo_get_expr(enquo(parameter)),
                                                 sep="")
            parameter_joined[[isolate_iterator]] <- parameter_next
            isolate_iterator <- isolate_iterator + 1
        }

        parameter_joined_full <- parameter_joined %>% reduce(left_join, by="Time")
        if (mean_col == TRUE) {
            parameter_joined_full$mean <-
                rowMeans(parameter_joined_full %>% select(-1), na.rm= TRUE)
        }

        parameter_joined_full$elapsed_time[1] <- 0

        for (elapsed_iterator in 2:length(parameter_joined_full$Time)){
            parameter_joined_full$elapsed_time[elapsed_iterator] =
                as.numeric(parameter_joined_full$Time[elapsed_iterator]) -
                as.numeric(parameter_joined_full$Time[1])
            elapsed_iterator <- elapsed_iterator+1
        }
    }

    if (sum(grepl(".id", colnames(data))) == 0) {
        parameter_joined_full <- data %>%
            select(1, grep(quo_get_expr(enquo(parameter)),
                                 colnames(data)))
        if (mean_col == TRUE) {
            parameter_joined_full$mean <-
                rowMeans(parameter_joined_full %>% select(-1:-3), na.rm= TRUE)
        }
    }
    return (parameter_joined_full)
}