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Fix: mismatch in randomization for Row-column design
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,106 @@ | ||
| validateTreatments <- function(data) { | ||
| # Group the data by LOCATION, REP, and then TREATMENT, and count the occurrences | ||
| treatment_counts <- aggregate(ID ~ LOCATION + REP + ENTRY, data=data, FUN=length) | ||
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| # Identify any treatment counts greater than 1, indicating duplicates within a LOCATION and REP | ||
| duplicates <- treatment_counts[treatment_counts$ID > 1, ] | ||
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| if (nrow(duplicates) > 0) { | ||
| stop("There are duplicates within REP for some LOCATIONs:\n") | ||
| } else { | ||
| # Check if all treatments are present exactly once within each REP for each LOCATION | ||
| unique_treatments_per_location_rep <- aggregate(ENTRY ~ LOCATION + REP, data=data, function(x) length(unique(x))) | ||
| expected_treatments_count <- unique(unique_treatments_per_location_rep$ENTRY) | ||
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| # if (length(expected_treatments_count) != 1) { | ||
| # stop("Not all treatments are present exactly once within each REP for each LOCATION. Here are the details:\n") | ||
| # } | ||
| } | ||
| } | ||
| # | ||
| # library(blocksdesign) | ||
| # # When producing a randomization for a resolvable row-column design | ||
| # # with 36 entries, 6 reps, 2 rows, and a random seed of 20243, each entry | ||
| # # does not appear in every replicate. | ||
| # # set.seed(20243) | ||
| # nt <- 36 | ||
| # r <- 6 | ||
| # b <- 2 | ||
| # l <- 1 | ||
| # k <- 2 #nrows | ||
| # nincblock <- nt*r/k | ||
| # N <- nt * r | ||
| # locationNames <- "FARGO" | ||
| # square <- FALSE | ||
| # if (sqrt(nt) == round(sqrt(nt))) square <- TRUE | ||
| # outIBD_loc <- vector(mode = "list", length = l) | ||
| # for (i in 1:l) { | ||
| # if (square) { | ||
| # mydes <- blocksdesign::blocks(treatments = nt, replicates = r + 1, blocks = list(r + 1, b), seed = NULL) | ||
| # ##### Dropping the cyclical REP ###### | ||
| # rep_to_drop <- mydes$Design %>% | ||
| # dplyr::group_by(Level_1, Level_2) %>% | ||
| # dplyr::mutate(treatments = as.numeric(treatments)) %>% | ||
| # dplyr::summarise(dif = sum(diff(sort(treatments)))/(dplyr::n()-1)) %>% | ||
| # dplyr::filter(dif == 1) %>% | ||
| # dplyr::pull(Level_1) %>% | ||
| # unique() | ||
| # print(rep_to_drop) | ||
| # if (length(rep_to_drop) > 0) { | ||
| # mydes$Design <- mydes$Design %>% | ||
| # dplyr::filter(Level_1 != rep_to_drop) %>% | ||
| # dplyr::mutate(Level_1 = rep(paste0("B", 1:r), each = nt)) | ||
| # } else { | ||
| # mydes$Design <- mydes$Design %>% | ||
| # dplyr::filter(Level_1 != paste0("B", r + 1)) | ||
| # } | ||
| # } else { | ||
| # mydes <- blocksdesign::blocks(treatments = nt, replicates = r, blocks = list(r, b), seed = NULL) | ||
| # } | ||
| # # mydes <- blocksdesign::blocks(treatments = nt, replicates = r, blocks = list(r, b), seed = NULL) | ||
| # ibd_plots <- list(1:216) | ||
| # matdf <- base::data.frame(list(LOCATION = rep(locationNames[i], each = N))) | ||
| # matdf$PLOT <- as.numeric(unlist(ibd_plots[[i]])) | ||
| # matdf$BLOCK <- rep(c(1:r), each = nt) | ||
| # matdf$iBLOCK <- rep(c(1:b), each = k) | ||
| # matdf$UNIT <- rep(c(1:k), nincblock) | ||
| # matdf$TREATMENT <- mydes$Design[,4] | ||
| # colnames(matdf) <- c("LOCATION","PLOT", "REP", "IBLOCK", "UNIT", "ENTRY") | ||
| # outIBD_loc[[i]] <- matdf | ||
| # } | ||
| # OutIBD <- dplyr::bind_rows(outIBD_loc) | ||
| # OutIBD <- as.data.frame(OutIBD) | ||
| # OutIBD$ENTRY <- as.numeric(OutIBD$ENTRY) | ||
| # OutIBD_test <- OutIBD | ||
| # OutIBD_test$ID <- 1:nrow(OutIBD_test) | ||
| # lookup <- FALSE | ||
| # if(lookup) { | ||
| # OutIBD <- dplyr::inner_join(OutIBD, dataLookUp, by = "ENTRY") | ||
| # OutIBD <- OutIBD[,-6] | ||
| # colnames(OutIBD) <- c("LOCATION","PLOT", "REP", "IBLOCK", "UNIT", "TREATMENT") | ||
| # OutIBD <- dplyr::inner_join(OutIBD, data_up, by = "TREATMENT") | ||
| # OutIBD <- OutIBD[, c(1:5,7,6)] | ||
| # colnames(OutIBD) <- c("LOCATION","PLOT", "REP", "IBLOCK", "UNIT", "ENTRY", "TREATMENT") | ||
| # } | ||
| # ID <- 1:nrow(OutIBD) | ||
| # OutIBD_new <- cbind(ID, OutIBD) | ||
| # | ||
| # | ||
| # # Load the data frame (replace this with your actual data loading code) | ||
| # data1 <- read.csv("OutIBD_before_merging.csv") | ||
| # View(data1) | ||
| # data <- OutIBD_test | ||
| # | ||
| # # Example usage: | ||
| # validateTreatments(data) | ||
| # | ||
| # | ||
| # data1 <- read.csv("IBD_row_example.csv") | ||
| # View(data1) | ||
| # | ||
| # data1 <- read.csv("IBD_row_example_before_drop_rep.csv") | ||
| # View(data1) | ||
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