Updated read functions

README.md

@@ -126,7 +126,7 @@ The function processes the provided CSV file by:
 - Combining the `Date` and `Time` columns to create a `DateTime` column and ordering the data chronologically.
 - Calculating initial ETR values from `Pm.-Det.` and `Fm-Det.` rows using `calc_etr()`.
 - Iterating through all rows with `Action == "P.+F. SP"` to calculate ETR values for both `Y.I.` and `Y.II.`
-- Optionally stopping at the recovery period if `remove_recovery = TRUE`.
+- Stopping at the recovery period if `remove_recovery = TRUE`.
 
 
 #### Return
@@ -179,7 +179,7 @@ The function processes the provided CSV file by:
 - Combining the `Date` and `Time` columns to create a `DateTime` column and ordering the data chronologically.  
 - Extracting the initial Pm.-Det. measurement at `PAR = 0` to calculate the first ETR value.  
 - Iterating through all rows with `Action == "P700 SP"` to calculate ETR values for Photosystem I (`Y.I.`).  
-- Optionally stopping at the recovery period if `remove_recovery = TRUE`.  
+- Stopping at the recovery period if `remove_recovery = TRUE`.  
 
 #### Return
 
@@ -236,7 +236,7 @@ The function processes the provided CSV file by:
 - Combining the `Date` and `Time` columns to create a `DateTime` column and ordering the data chronologically.  
 - Extracting the initial **Fm-Det.** measurement at `PAR = 0` to calculate the first ETR value.  
 - Iterating through all rows with `Action == "Fluo. SP"` to calculate ETR values for Photosystem II (`Y.II.`).  
-- Optionally stopping at the recovery period if `remove_recovery = TRUE`.  
+- Stopping at the recovery period if `remove_recovery = TRUE`.  
 
 #### Return
 
@@ -292,9 +292,12 @@ The function processes the provided CSV file by:
 - Validating the raw Junior-PAM data with `validate_junior_pam_data()`.
 - Renaming columns to standard names (`PAR`, `Y.II`.) if necessary.
 - Filtering rows where Type equals `"FO"` or `"F"`.
-- Converting and ordering the `DateTime` column.
+- Ordering by `Time (rel/ms)` column.
 - Iterating through all rows to calculate ETR values for `Y.II.` using `calc_etr()`.
-- Optionally stopping at the recovery period if `remove_recovery = TRUE`.
+- Stopping at the recovery period if `remove_recovery = TRUE`.
+
+To ensure the file is imported correctly, please export the CSV file using the default settings:
+![Plot](img/export_junior_pam.png)
 
 #### Return
 
@@ -963,7 +966,7 @@ plot_control_eilers_peeters_ETR_II <- plot_control(
 print(plot_control_eilers_peeters_ETR_II)
 ```
 
-![Plot](test-eilers_peeters_etr_II_modified_control_plot_20240925.jpg)
+![Plot](img/test-eilers_peeters_etr_II_modified_control_plot_20240925.jpg)
 
 ---
 
@@ -986,7 +989,7 @@ A plot displaying the original ETR and Yield values and the regression data from
 #### Examples
 
 ```r
-test_data_file <- file.path(getwd(), "data", "20240925.csv")
+test_data_file <- file.path(getwd(), "data", "dual_pam_data", "20240925.csv")
     data <- read_dual_pam_data(test_data_file)
 
     eilers_peeters <- eilers_peeters_modified(eilers_peeters_generate_regression_ETR_II(data))
@@ -1003,7 +1006,7 @@ test_data_file <- file.path(getwd(), "data", "20240925.csv")
     )
 ```
 
-![combo Plot](test_combo_plot_control_etr_II.jpg)
+![combo Plot](img/test_combo_plot_control_etr_II.jpg)
 
 ---
 

examples/Example_compare_models.R

@@ -7,7 +7,7 @@ library("pam")
 #### read_dual_pam_data()####
 # raw data file directory
 script_dir <- dirname(sys.frame(1)$ofile)
-data_dir <- file.path(script_dir, "data", "bulk")
+data_dir <- file.path(script_dir, "data", "dual_pam_data", "bulk")
 
 #### compare_regression_models_ETR_II####
 compare_regression_models_ETR_II_result <- compare_regression_models_ETR_II(data_dir, read_dual_pam_data)

examples/Example_multiple_data.R

@@ -6,7 +6,7 @@ library("pam")
 
 #### raw data file directory####
 script_dir <- dirname(sys.frame(1)$ofile)
-data_dir <- file.path(script_dir, "data", "bulk")
+data_dir <- file.path(script_dir, "data", "dual_pam_data", "bulk")
 output_dir <- file.path(script_dir, "output")
 dir.create(output_dir, showWarnings = FALSE)
 output_path_pdf <- file.path(output_dir, "eilers_peters_plot_control.pdf")

src/R/compare_regression_models.R

@@ -116,7 +116,7 @@ compare_regression_models <- function(data_dir, etr_type, read_func) {
   for (file in csv_files) {
     title <- basename(file)
     data <- do.call(read_func, list(csv_path = file))
-    validate_data(data)
+    validate_intermediate_data(data)
 
     tryCatch(
       {

src/R/device_dual_pam.R

@@ -0,0 +1,170 @@
+#' Read and Process DualPAM Data
+#'
+#' Reads raw CSV files generated by DualPAM software, calculates electron transport rate (ETR) values, and returns a universal dataset.
+#'
+#' @param csv_path File path to the CSV file.
+#' @param remove_recovery Logical. Removes recovery measurements if \code{TRUE}. Default is \code{TRUE}.
+#' @param etr_factor Numeric. Factor for ETR calculation. Default is \code{0.84}.
+#' @param fraction_photosystem_I Numeric. Relative distribution of absorbed PAR to photosystem I. Default is \code{0.5}.
+#' @param fraction_photosystem_II Numeric. Relative distribution of absorbed PAR to photosystem II. Default is \code{0.5}.
+#'
+#' @details
+#' Calculates ETR using:
+#' \deqn{\text{ETR} = \text{PAR} \cdot \text{ETR-Factor} \cdot \text{Fraction of Photosystem (I or II)} \cdot \text{Yield (I or II)}}
+#'
+#' A detailed documentation can be found under \url{https://github.com/biotoolbox/pam?tab=readme-ov-file#read_dual_pam_data}
+#'
+#' @return A \code{data.table} containing:
+#' \itemize{
+#'   \item \code{par}: Photosynthetically active radiation.
+#'   \item \code{yield_1}: Yield for photosystem I.
+#'   \item \code{yield_2}: Yield for photosystem II.
+#'   \item \code{etr_1}: Calculated ETR for photosystem I.
+#'   \item \code{etr_2}: Calculated ETR for photosystem II.
+#' }
+#'
+#' @references{
+#'   Heinz Walz GmbH. (2024). \emph{DUAL-PAM-100 DUAL-PAM/F MANUAL, 5th Edition, April 2024, Chapter 7 (pp. 162-172).}
+#'   Heinz Walz GmbH, Effeltrich, Germany.
+#'   Available at: \url{https://www.walz.com/files/downloads/dualpamed05.pdf}
+#' }
+#' @examples
+#' path <- file.path(system.file("extdata/dual_pam_data", package = "pam"), "20240925.csv")
+#' data <- read_dual_pam_data(path)
+#' @export
+read_dual_pam_data <- function(
+  csv_path,
+  remove_recovery = TRUE,
+  etr_factor = 0.84,
+  fraction_photosystem_I = 0.5,
+  fraction_photosystem_II = 0.5
+) {
+  if (fraction_photosystem_I + fraction_photosystem_II != 1) {
+    stop("The sum of fraction_photosystem_I and fraction_photosystem_II must be equal 1.")
+  }
+
+  tryCatch(
+    {
+      data <- utils::read.csv(csv_path, sep = ";", dec = ".")
+      data <- data.table::as.data.table(data)
+
+      validate_dual_pam_data(data)
+      data <- data[data$ID == "SP", ]
+
+      date_time_col_values <- c()
+      for (i in seq_len(nrow(data))) {
+        row <- data[i, ]
+
+        date_time_row_value <- as.POSIXct(
+          paste(row$Date, row$Time, sep = " "),
+          tz = "GMT", "%d.%m.%y %H:%M:%S"
+        )
+        date_time_col_values <- c(date_time_col_values, date_time_row_value)
+      }
+
+      data$DateTime <- date_time_col_values
+      data <- data[order(data$DateTime), ]
+
+      pm_det_row <- subset(data, data$PAR == 0 & data$Action == "Pm.-Det.")
+      yield_1_first <- pm_det_row$Y.I.
+      recalc_etr_1 <- calc_etr(yield_1_first, 0, etr_factor, fraction_photosystem_I)
+
+      fm_det_row <- subset(data, data$PAR == 0 & data$Action == "Fm-Det.")
+      yield_2_first <- fm_det_row$Y.II.
+      recalc_etr_2 <- calc_etr(yield_2_first, 0, etr_factor, fraction_photosystem_II)
+
+
+      result <- data.table::data.table(
+        par = numeric(),
+        yield_1 = numeric(),
+        yield_2 = numeric(),
+        etr_1 = numeric(),
+        etr_2 = numeric()
+      )
+      new_row <- list(
+        par = 0,
+        yield_1 = yield_1_first,
+        yield_2 = yield_2_first,
+        etr_1 = recalc_etr_1,
+        etr_2 = recalc_etr_2
+      )
+      result <- rbind(result, new_row)
+
+      last_par <- as.numeric(0)
+      for (i in seq_len(nrow(data))) {
+        row <- data[i, ]
+        current_par <- row$PAR
+
+        if (row$Action != "P.+F. SP") {
+          next
+        }
+
+        if (remove_recovery && last_par != 0 && current_par < last_par) {
+          break
+        }
+
+        yield_1 <- row$Y.I.
+        recalc_etr_1 <- calc_etr(yield_1, current_par, etr_factor, fraction_photosystem_I)
+
+        yield_2 <- row$Y.II.
+        recalc_etr_2 <- calc_etr(yield_2, current_par, etr_factor, fraction_photosystem_II)
+
+        new_row <- list(
+          par = current_par,
+          yield_1 = yield_1,
+          yield_2 = yield_2,
+          etr_1 = recalc_etr_1,
+          etr_2 = recalc_etr_2
+        )
+        result <- rbind(result, new_row)
+
+        last_par <- current_par
+      }
+
+      validate_intermediate_data(result)
+      return(result)
+    },
+    warning = function(w) {
+      stop("Warning in file: ", csv_path, " Warning: ", w)
+    },
+    error = function(e) {
+      stop("Error in file: ", csv_path, " Error: ", e)
+    }
+  )
+}
+
+validate_dual_pam_data <- function(data) {
+  validate_data_not_empty(data)
+
+  if (!"ID" %in% colnames(data)) {
+    stop("required col 'ID' not found")
+  }
+
+  if (!"PAR" %in% colnames(data)) {
+    stop("required col 'PAR' not found")
+  }
+
+  if (!"Y.I." %in% colnames(data) && !"Y.II." %in% colnames(data)) {
+    stop("required col 'Y(I)' and 'Y(II)' not found")
+  }
+
+  if (!"Action" %in% colnames(data)) {
+    stop("required col 'Action' not found")
+  }
+
+  if (!"Date" %in% colnames(data)) {
+    stop("required col 'Date' not found")
+  }
+
+  if (!"Time" %in% colnames(data)) {
+    stop("required col 'Time' not found")
+  }
+
+  if (!"Pm.-Det." %in% data[["Action"]]) {
+    stop("required value 'Pm' not found in column 'Action'")
+  }
+
+  if (!"Fm-Det." %in% data[["Action"]]) {
+    stop("required value 'Fm' not found in column 'Action'")
+  }
+}