Merge pull request #89 from TESTgroup-BNL/data_split_fix

A bug fix to correctly stratify cal/val datasets based on user-selected groupings.  The issue was identified by @asierrl who also illustrated a potential fix, which has been included in the bug fix along with new tests to check that samples are not duplicated between cal and val.

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: spectratrait
 Title: A simple add-on package to aid in the fitting of leaf-level spectra-trait PLSR models
-Version: 1.0.3
+Version: 1.0.5
 Authors@R:
   c(person(given = "Julien",
            family = "Lamour",

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+export("%notin%")
 export(VIP)
 export(VIPjh)
 export(create_data_split)
@@ -12,3 +13,8 @@ export(percent_rmse)
 export(pls_permutation)
 export(source_GitHubData)
 import(httr)
+importFrom(pls,plsr)
+importFrom(utils,flush.console)
+importFrom(utils,read.table)
+importFrom(utils,setTxtProgressBar)
+importFrom(utils,txtProgressBar)

R/create_data_split.R

@@ -15,26 +15,30 @@
 create_data_split <- function(dataset=NULL, approach=NULL, split_seed=123456789, prop=0.8,
                               group_variables=NULL) {
   set.seed(split_seed)
+
+  # outer if/else to stop if approach set to NULL
   if(!is.null(approach)) {
+
+    ## base R data split function
     if (approach=="base") {
       dataset$CalVal <- NA
       split_var <- group_variables
-      if(length(group_variables) > 1){
+      if(length(group_variables) > 1) {
         dataset$ID <- apply(dataset[, group_variables], MARGIN = 1, FUN = function(x) paste(x, collapse = " "))
       } else {
         dataset$ID <- dataset[, group_variables]
       }
       split_var_list <- unique(dataset$ID)
-      for(i in 1:length(split_var_list)){
-        temp <- row.names(dataset[ dataset$ID == split_var_list[i], ])
+      for(i in 1:length(split_var_list)) {
+        temp <- row.names(dataset[dataset$ID == split_var_list[i], ])
         ## there should probably be more than 4 obs I'm guessing, so this may need adjusting
-        if(length(temp) > 3){
+        if(length(temp) > 3) {
           Cal <- sample(temp,round(prop*length(temp)))
-          Val <- temp[!temp %in% Cal]
+          Val <- temp[temp %notin% Cal]
           dataset$CalVal[ row.names(dataset) %in% Cal ] <- "Cal"
           dataset$CalVal[ row.names(dataset) %in% Val ] <- "Val"
           p_cal <- length(Cal)/length(temp) * 100
-          message(paste0(split_var_list[i], "   ", "Cal", ": ", p_cal, "%"))
+          message(paste0(split_var_list[i], "   ", "Cal", ": ", round(p_cal,3), "%"))
         } else {
           message(paste(split_var_list[i], "Not enough observations"))
         }
@@ -44,16 +48,29 @@ create_data_split <- function(dataset=NULL, approach=NULL, split_seed=123456789,
       dataset <- dataset[!is.na(dataset$CalVal), ]
       cal.plsr.data <- dataset[dataset$CalVal== "Cal",]
       val.plsr.data <- dataset[dataset$CalVal== "Val",]
-    } else if (approach=="dplyr")
-      cal.plsr.data <- dataset %>% 
+
+      # Remove temporary CalVal column
+      cal.plsr.data <- cal.plsr.data[,-which(names(cal.plsr.data)=="CalVal")]
+      val.plsr.data <- val.plsr.data[,-which(names(val.plsr.data)=="CalVal")]
+
+      # dplyr based data split function
+    } else if (approach=="dplyr") {
+      dataset <- dataset %>% mutate(ids=row_number())
+      cal.plsr.data <- dataset %>%
         group_by_at(vars(all_of(group_variables))) %>% 
         slice(sample(1:n(), prop*n())) %>% 
         data.frame()
-    val.plsr.data <-dataset[!row.names(dataset) %in% row.names(cal.plsr.data),]
-
+      val.plsr.data <- dataset[dataset$ids %notin% cal.plsr.data$ids,]
+      cal.plsr.data <- cal.plsr.data[,-which(colnames(cal.plsr.data)=="ids")]
+      val.plsr.data <- val.plsr.data[,-which(colnames(val.plsr.data)=="ids")]
   } else {
-    stop("**** Please choose either base R or dplyr data split ****")
+    stop("**** Please set approach to either base R or dplyr data split ****")
+  }
+    output_list <- list(cal_data=cal.plsr.data, val_data=val.plsr.data)
+    return(output_list)
   }
-  output_list <- list(cal_data=cal.plsr.data, val_data=val.plsr.data)
-  return(output_list)
+
+  # if approach is set to NULL (i.e. not set) return error message
+  stop("**** Please set approach to either base R or dplyr data split ****")
+
 }

R/pls_permutation.R

@@ -12,6 +12,9 @@
 ##' @return output a list containing the PRESS and coef_array.
 ##' output <- list(PRESS=press.out, coef_array=coefs)
 ##' 
+##' @importFrom pls plsr 
+##' @importFrom utils flush.console read.table setTxtProgressBar txtProgressBar
+##' 
 ##' @author Julien Lamour, Shawn P. Serbin
 ##' @export
 pls_permutation <- function(dataset=NULL, maxComps=20, iterations=20, prop=0.70,
@@ -25,8 +28,8 @@ pls_permutation <- function(dataset=NULL, maxComps=20, iterations=20, prop=0.70,
 
   if (verbose) {
     j <- 1 # <--- Numeric counter for progress bar
-    pb <- utils::txtProgressBar(min = 0, max = iterations, 
-                                char="*",width=70,style = 3)
+    pb <- txtProgressBar(min = 0, max = iterations, 
+                         char="*",width=70,style = 3)
   }
 
   for (i in seq_along(1:iterations)) {

R/utils.R

@@ -53,6 +53,12 @@ percent_rmse <- function(plsr_dataset = NULL, inVar = NULL,
   return(output)
 }
 
+
+##' Not %in% function
+##'
+##' @export
+`%notin%` <- Negate(`%in%`)
+
 ##' Function to check for installed package
 ##' not presently used
 testForPackage <- function(pkg) {

inst/scripts/spectra-trait_kit_sla_plsr_example.R

@@ -85,7 +85,9 @@ sample_info <- dat_raw[,names(dat_raw) %notin% seq(350,2500,1)]
 head(sample_info)
 
 sample_info2 <- sample_info %>%
-  select(Plant_Species=species,Growth_Form=`growth form`,timestamp,SLA_g_cm=`SLA (g/cm )`)
+  select(Plant_Species=species,Growth_Form=`growth form`,timestamp,
+         SLA_g_cm=`SLA (g/cm )`) %>%
+  mutate(SLA_g_cm=as.numeric(SLA_g_cm)) # ensure SLA is numeric
 head(sample_info2)
 
 plsr_data <- data.frame(sample_info2,Spectra)

tests/testthat.R

@@ -1,4 +1,5 @@
 library(testthat)
+library(dplyr)
 library(spectratrait)
 
 test_check("spectratrait")

tests/testthat/test.create_data_split.R

@@ -0,0 +1,33 @@
+context("Test that the create data split function has the expected behavior")
+
+test_that("Generating a data split using the dplyr approach doesn't throw an error or generate duplicates between cal. and val. data", {
+  plot<- rep(c("plot1", "plot2", "plot3"),each=42)
+  season<- rep(1:6, 21)
+  disease<- c(rep(0,84), rep(1,42))
+  d<- seq(1:126)
+  df <- data.frame(plot,season,disease,d)
+  df <- df %>% mutate(id=row_number())
+
+  split_data <- spectratrait::create_data_split(dataset=df, approach="dplyr", 
+                                                split_seed=7529075, prop=0.8, 
+                                                group_variables=c("plot", 
+                                                                "season", 
+                                                                "disease"))
+  expect_false(sum(split_data$cal_data$id %in% split_data$val_data$id)>0)
+})
+
+test_that("Generating a data split using the base approach doesn't throw an error or generate duplicates between cal. and val. data", {
+  plot<- rep(c("plot1", "plot2", "plot3"),each=42)
+  season<- rep(1:6, 21)
+  disease<- c(rep(0,84), rep(1,42))
+  d<- seq(1:126)
+  df <- data.frame(plot,season,disease,d)
+  df <- df %>% mutate(id=row_number())
+
+  split_data <- spectratrait::create_data_split(dataset=df, approach="base", 
+                                                split_seed=7529075, prop=0.8, 
+                                                group_variables=c("plot", 
+                                                                  "season", 
+                                                                  "disease"))
+  expect_false(sum(split_data$cal_data$id %in% split_data$val_data$id)>0)
+})

vignettes/kit_sla_plsr_example.Rmd

@@ -3,10 +3,10 @@ title: Spectra-trait PLSR example using leaf-level spectra and specific leaf are
 author: "Shawn P. Serbin, Julien Lamour, & Jeremiah Anderson"
 output:
   github_document: default
-  html_document:
-    df_print: paged
   html_notebook: default
   pdf_document: default
+  html_document:
+    df_print: paged
 params:
   date: !r Sys.Date()
 ---
@@ -80,7 +80,9 @@ sample_info <- dat_raw[,names(dat_raw) %notin% seq(350,2500,1)]
 head(sample_info)
 
 sample_info2 <- sample_info %>%
-  select(Plant_Species=species,Growth_Form=`growth form`,timestamp,SLA_g_cm=`SLA (g/cm )`)
+  select(Plant_Species=species,Growth_Form=`growth form`,timestamp,
+         SLA_g_cm=`SLA (g/cm )`) %>%
+  mutate(SLA_g_cm=as.numeric(SLA_g_cm)) # ensure SLA is numeric
 head(sample_info2)
 
 plsr_data <- data.frame(sample_info2,Spectra)