R/ec_soilfertility.R
In AGROFIMS/agdesign: Creation of fieldbooks for AGROFIMS platform
Defines functions
get_prodfert_mgmt
get_nutrient_mgmt
FertilizerRates_mgmt
NutrientRates_mgmt
fertilizerRates
nutrientRates
fertilizer_calculation
fertilizer_reshape
product_calculation
nutrient_reshape
productApplicationRates
getFert
get_fertilizer
get_ec_sf
Documented in
get_ec_sf
get_fertilizer
#' Get exp conditions , soil and fertilkity tab
#' @description get all input values related to the experiment conditions \code{soil and fertility} experiment condition tab,
#' provided by users when type in AGROFIMS.
#' @param allinputs shiny reactiveValuesList provided by AGROFIMS
#' @param napp \code{numeric} number of applications
#' @author Omar Benites
#'
get_ec_sf <- function(input){
if(length(input$soilfertility_to_collect_field)==0){
lbl <- c("Fertilizer_type", "Fertilizer_amount_kg/ha","Nutrient_amount_kg/ha")
dt <- data.frame()
} else {
lbl <- input$soilfertility_to_collect_field
lbl <- dplyr::case_when( lbl =="Fertilizer type"~ "Fertilizer_type",
lbl =="Fertilizer amount" ~ "Fertilizer_amount_kg/ha",
lbl=="Nutrient amount" ~"Nutrient_amount_kg/ha",
lbl=="Timing" ~ "Fertilizer_timing",
lbl=="Number of fertilizer applications" ~"Fertilizer_application_number",
lbl=="Nutrient type" ~"Nutrient_type",
lbl=="Fertilizer application technique" ~"Fertilizer_application_technique",
lbl=="Fertilizer implement type" ~"Fertilizer_implement_type",
lbl=="Fertilizer notes" ~"Fertilizer_notes",
TRUE ~ lbl)
lbl <- lbl
dt <- as.list(rep("", length(lbl)))
names(dt) <- lbl
}
out <- list(dt= dt, lbl= lbl)
##LABEL FOR TRAITLIST :remove all double underscore from soil_fertility labels
# lbl<- str_replace_all(string = lbl_soil, pattern = "__[:digit:]+$",replacement = "")
# lbl <- unique(lbl)
# out<- list(dt=dt, lbl= lbl)
#
}
#
# get_collectable_sf <- function(input){
#
# trait <- input$soilfertility_to_collect_field
# if(!is.null(trait)){
# #trait_values <- vector("list", length(trait))
# trait_values <- as.list(rep("", length(trait)))
# names(trait_values) <-
# } else {
#
# }
#
#
# }
#' Get fertilizer product names from Fertilizer and Nutrient dataset
#' @description Get fertilizer's names from Fertilizer and Nutrient dataset
#' @param .data Fertilizer and Nutrient dataset
#' @author Omar Benites
#'
get_fertilizer <- function(.data){
.data$name
}
#### Simple case #########################################
getFert <- function(treats, fertilizers, selected) {
treats <- treats %>% arrange_at(1)
fertilizers <- fertilizers[c("group","name",names(treats))]
factors <- t(as.matrix(treats))
f <- fertilizers[fertilizers$name == selected, -c(1:2)]
f <- as.matrix(f)/100
x <- as.vector(na.omit(factors / as.vector(f)))
m <- matrix(x)
colnames(m) <-selected
rownames(m) <- paste0("Level-", 1:nrow(m))
m <- as.data.frame(m,stringsAsFactors=FALSE) %>% tibble::rownames_to_column()
colnames(m)[1] <- c("Levels")
m[,1] <- paste0("Level_",names(treats),"_",treats[,1] )
m
}
#### End simple case #########################################
############################################ NUTRIENT AND FERTILIZERS ####################################################
# Product/Fertilizer Rates
productApplicationRates <- function(supply, treatment, price, minCost=TRUE){
name <- supply$name
supply <- t(as.matrix(supply[,-1]))
treatment <- as.matrix(treatment)
result <- matrix(nrow=ncol(supply), ncol=nrow(treatment))
price <- price * minCost
treatment <- treatment * 100
for (i in 1:nrow(treatment)) {
solution <- limSolve::linp(E=supply, F=treatment[i,], Cost=price)
if (solution$IsError) {
result[,i] <- -99
} else {
result[,i] <- solution$X
}
}
colnames(result) <- paste0("tr.", 1:ncol(result))
data.frame(name, result)
}
# Reshape nutrient data
nutrient_reshape<- function(df, name="A", values="B"){
out<- list()
nutrient<- unique(df[,name])
for(i in seq.int(nutrient) ){
out[[i]] <- df %>% dplyr::filter(SplitNutName==nutrient[i]) %>% dplyr::select_(values) %>% nth(1) %>% as.numeric()
out[[i]]<- as.data.frame(out[[i]],stringsAsFactors=FALSE)
names(out[[i]]) <- nutrient[i]
}
if(length(out)>1){
#https://stackoverflow.com/a/53893866/7340448
#How to cbind a list of data.frames of different lengths
#library(rowr)
out <- do.call(rowr::cbind.fill, c(out, fill = NA))
} else {
out <- out[[1]]
}
out
#out<- rbindlist(out)
}
#Product/Fertilizer calculation wrapper function for the DESIGN TAB
product_calculation <- function(allinputs, dfAll, index="1", indexEspLvl=indexEspLvl , design="frcbd"){
#Get labels
indexEspLvl<- filter_index_espLvl_design(index= index, indexEspLvl=indexEspLvl, design=design, designEspflvl="_lvl_espType_")
#Get especial levels
indexEspLvl_subfix <- get_index_espLvl_design(indexEspLvl, paste0(design,"_lvl_espType_"))
lookup <- paste0(design,"_")
#Table of nutrient details (eletype, mNumTiming)-----------------------------------------------------------------------------------------
nutrients_details <- get_nutrient_details_design(allinputs=allinputs, design=design, index =index, indexEspLvl = indexEspLvl)
#Split nutrient name and split number per each nutrient-------------------------------------------------------------------------------
split_nutrient_name <- lapply(X = seq.int(dfAll$splits), function(x) rep(dfAll$eleType[x], each =as.numeric(dfAll$splits[x]))) %>% unlist()
split_nutrient_number <- lapply(as.integer(dfAll$splits), function(x) seq.int(x)) %>% unlist()
nutrients_details <- nutrients_details %>%
mutate(SplitNutName = split_nutrient_name ) %>%
mutate(splitNutNum = split_nutrient_number)
#Customizeing nutrient_details
class(nutrients_details)<-"data.frame"
nutrient_elements <- nutrients_details[,c("SplitNutName", "nutAmount")]
nutrient_elements[,2] <- as.numeric(nutrient_elements[,2] )
## Get nutrient tables per each sub level #############################################
out_nut<- vector(mode="list", nrow(dfAll))
lookup <- paste0("^",design,"_")
#Create table of fertilizers
for (i in 1:nrow(dfAll)){
level <- dfAll[i,1]
type <- dfAll[i,2]
levels <- dfAll[i,3]
unit <- dfAll[i,4]
index <- dfAll[i,5]
if(as.numeric(levels)==0){
out_nut[[i]] <-data.frame(0,0,0,0,0,0,0,0,0,0,0,0,0,0, stringsAsFactors = FALSE)
} else {
#namefert <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"factorType_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out2 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT2_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out3 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT3_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out4 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT4_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out5 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT5_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out6 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT6_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out7 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT7_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out8 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT8_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out9 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT9_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out10 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT10_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out11 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT11_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out12 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT12_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out13 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT13_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out14 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT14_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out_nut[[i]] <-data.frame(out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
}
names(out_nut[[i]]) <- c("N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
#end create table of fertilizers
nutfert <- data.table::rbindlist(out_nut) %>% as.data.frame(stringsAsFactors=FALSE)
temp4 <- list()
#OLD CODE
# for(i in 1:nrow(dfAll)){
# splits <- as.numeric(dfAll$splits)[i]
# temp4[[i]] <- nutfert[rep(i,splits), ]
# #sapply(df, rep.int,2) %>% as.data.frame(stringsAsFactors=FALSE) method 2
# }
# END OLD CODE
#NEW CODE
#Create matrix with zeros and 1 row
d0 <- data.frame(matrix(0, ncol = ncol(nutfert), nrow =1))
names(d0) <- names(nutfert)
for(i in 1:nrow(dfAll)){
if(as.numeric(dfAll$levels[i])==0){
splits <- as.numeric(dfAll$splits)[i]
temp4[[i]] <- d0[rep(i,splits), ]
i <- i-1
}else {
splits <- as.numeric(dfAll$splits)[i]
temp4[[i]] <- nutfert[rep(i,splits), ]
}
}
#END NEW CODE
nutfert <- data.table::rbindlist(temp4) %>% as.data.frame(stringsAsFactors=FALSE)
nutfert$name <- paste(nutrients_details$mNutProduct)
nutfert <- nutfert[,c(15, 1:14)]
names(nutfert) <- c("name", "Nitrogen","Phosphorus","Potassium","Calcium","Magnesium",
"Sulfur", "Moldbenum", "Zinc", "Boron", "Copper","Iron", "Manganese", "Nickel", "Chlorine")
fertilizers <- nutfert
##End Get nutrient tables per each sub level ###########################################
#Get treatments ######################################################################
treatments <- as.list(as.numeric(nutrients_details$nutAmount))
names(treatments) <- nutrients_details$SplitNutName
#End get treatments##################################################################
#aaaaaa=list(treatments=treatments,fertilizers = fertilizers)
#saveRDS(object = aaaaaa,file= "/home/obenites/AGROFIMS/agdesign/tests/testthat/userInput/nut_calculation_design_5.rds")
out <- fertilizerRates(fertilizers= fertilizers, treatments = treatments)
#out <- unlist(out)
nutSplitNames <- paste(nutrients_details$SplitNutName,nutrients_details$nutAmount,nutrients_details$splitNutNum, sep="_")
fertRate <- data.frame(Product=nutrients_details$mNutProduct, Nutrient=nutSplitNames ,Rates = out)
}
#Reshape fertilizer/product data
fertilizer_reshape<- function(df){
out<- data.frame(t(as.numeric(df$mProdAmount)),stringsAsFactors = FALSE)
names(out) <- paste(df$factorType,df$splitFertNum, 1:nrow(df),sep = "_")
out
}
#Fertilizer calculation for the DESIGN TAB
fertilizer_calculation<- function(allinputs, dfAll, index="1", indexEspLvl=indexEspLvl , design="frcbd"){
#Get labels
indexEspLvl<- filter_index_espLvl_design(index= index, indexEspLvl=indexEspLvl, design=design, designEspflvl="_lvl_espType_")
#Get especial levels
indexEspLvl_subfix <- get_index_espLvl_design(indexEspLvl, paste0(design,"_lvl_espType_"))
#lookup <- paste0(design,"_")
#Table of nutrient details (eletype, mNumTiming)-----------------------------------------------------------------------------------------
fertilizer_details <- get_fertilizer_details_design(allinputs, design, index, indexEspLvl)
class(fertilizer_details)<- "data.frame"
## Split nutrient name and split number per each nutrient-------------------------------------------------------------------------------
split_fert_name <- lapply(X = seq.int(dfAll$splits), function(x) rep(dfAll$eleType[x], each =as.numeric(dfAll$splits[x]))) %>% unlist()
split_fert_number <- lapply(as.integer(dfAll$splits), function(x) seq.int(x)) %>% unlist()
fertilizer_details <- fertilizer_details %>%
mutate(splitFertNum = split_fert_number) %>%
mutate(SplitFertName = split_fert_name )
fertilizer_details[,"mProdAmount"] <- as.numeric(fertilizer_details[,"mProdAmount"])
## NEW CODE: GET FERTILIZER_AVAILABLE TABLE
#First input
# fact <- lapply(seq.int(unique(fertilizer_details$factorType)),
# function(x) fertilizer_details %>% dplyr::filter(factorType==fertilizer_details$factorType[x])
# %>% dplyr::select(mProdAmount) %>% nth(1))
# names(fact) <- unique(fertilizer_details$factorType)
## END NEW CODE
## FACT (TREATMENT): Fertilizer Application Product
fact<- as.list(as.numeric(fertilizer_details$mProdAmount))
names(fact) <- paste(fertilizer_details$factorType,fertilizer_details$mProdAmount,
fertilizer_details$splitFertNum, sep="_")
## NEW CODE: GET FERTILIZER_AVAILABLE TABLE
out_fert<- vector(mode="list", nrow(dfAll))
lookup <- paste0("^",design,"_")
for (i in 1:nrow(dfAll)){
level <- dfAll[i,1]
type <- dfAll[i,2]
levels <- dfAll[i,3]
unit <- dfAll[i,4]
index <- dfAll[i,5]
print(paste(level,index,i))
#frcbd_factorType_1_1_1
namefert <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"factorType_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out2 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT2_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out3 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT3_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out4 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT4_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out5 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT5_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out6 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT6_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out7 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT7_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out8 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT8_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out9 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT9_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out10 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT10_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out11 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT11_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out12 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT12_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out13 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT13_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out14 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT14_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out_fert[[i]] <-data.frame(namefert, out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
names(out_fert[[i]]) <- c("name","N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
fert_available<- data.table::rbindlist(out_fert) %>% as.data.frame(stringsAsFactors=FALSE)
#fert_available$name <- paste(fert_available$name, dfAll$levels, dfAll$splits, sep = "_")
temp <- list()
for(i in 1:nrow(dfAll)){
splits <- as.numeric(dfAll$splits)[i]
temp[[i]] <- fert_available[rep(i,splits), ]
#sapply(df, rep.int,2) %>% as.data.frame(stringsAsFactors=FALSE) method 2
}
fert_available<- data.table::rbindlist(temp) %>% as.data.frame(stringsAsFactors=FALSE)
fert_available$name <- paste(fert_available$name, fertilizer_details$mProdAmount,
fertilizer_details$splitFertNum, sep = "_")
## END NEW CODE : GET FERTILIZER_AVAILABLE TABLE
### FORMER CODE
# fert_available <- dt_fernut %>% dplyr::filter(name %in% unique(fertilizer_details$factorType))
# names(fert_available) <- c("group", "name", "Nitrogen","Phosphorus","Potassium","Calcium","Magnesium",
# "Sulfur", "Moldbenum", "Zinc", "Boron", "Copper","Iron", "Manganese", "Nickel", "Chlorine")
# fert_available <- tibble::as_tibble(fert_available) %>% dplyr::select(-group)
### END CODE
#Output
out <- nutrientRates(fert_available, fact)
for(i in seq.int(out)){
#rownames(out[[i]]) <- paste0(names(out)[i],"_",rownames(out[[i]]))
rownames(out[[i]]) <- paste0(names(out)[i])
}
out <- lapply(seq.int(out), function(x) as.data.frame(out[[x]],stringsAsFactors=FALSE))
out <- lapply(seq.int(out), function(x) tibble::rownames_to_column(out[[x]]) )
out <- data.table::rbindlist(out,use.names = TRUE)
out <- as.data.frame(out, stringsAsFactors=FALSE)
}
# Nutrient Rates (output)
nutrientRates <- function(fertilizers, treatments) {
m <- match(names(treatments), fertilizers$name)
#stopifnot(!any(is.na(m)))
fertilizers <- fertilizers[m, ]
f <- as.matrix(fertilizers[,-1]) # for easy multiplication
out <- list()
for (i in 1:length(treatments)) {
treat <- unlist(treatments[[i]])
r <- f[rep(i, length(treat)), ,drop=FALSE] * treat / 100
rownames(r) <- round(treat,1)
out[[ fertilizers$name[i] ]] <- r
}
out
}
# Fertilizer/Product Rates (output)
# fertilizerRates <- function(fertilizers, treatments) {
# out <- list()
# for (i in 1:length(treatments)) {
# j <- colnames(fertilizers) == names(treatments[i])
# #stopifnot(any(j)) # no match
# fert <- fertilizers[i,j]
# k <- which(fert > 0)
# #stopifnot(length(k)==1) # one, and only one, product must have the nutrient!
# out[[ i ]] <- unlist(treatments[i]) / (fert[k] / 100)
# if(length(out[[ i ]])==0 ){ out[[ i ]]<- "" }
# names(out[[i]])<-NULL
# }
# names(out) <- names(treatments)
# out
# }
#NEW CODE
# Fertilizer/Product Rates (output)
fertilizerRates <- function(fertilizers, treatments) {
fertilizers<- fertilizers[,-1]
out_product <- vector(mode= "numeric", length=length(treatments))
for(i in 1:length(treatments)){
if(treatments[[i]]==0){
out_product[i] <- 0
} else {
out_product[i] <- treatments[[i]]/(fertilizers[i,names(treatments)[i]]/100)
}
}
out_product
}
# Fertilizer/Product Rates (output) for Management Practices
#fertilizerRates_mgmt <- function(fertilizers, treatments) {
NutrientRates_mgmt <- function(fertilizers, treatments) {
prod_names <- treatments$name
out <- (fertilizers[,-c(1,2)]*treatments[,-c(1,2)])/100
out$name <- prod_names
nc <- ncol(out)
out <- out[, c(nc, 1:(nc-1))]
out
}
# Fertilizer/Product Rates (output) for Management Practices
#NutrientRates_mgmt <- function(fertilizers, treatments) {
FertilizerRates_mgmt <- function(fertilizers, treatments) {
#out<- vector(mode="list", length = nrow(treatments))
#for(i in 1:nrow(treatments)){
out <- treatments[ rep(1, nrow(fertilizers)),]/(fertilizers[,-1]/100)
print("--fertil mgmt--")
#print(out)
out <- replace(out, is.na(out), 0) #change nan values by 0
is.na(out) <- do.call(cbind,lapply(out, is.infinite)) #change inf values by 0
#}
out
#out <- data.table::rbindlist(out) %>% as.data.frame(stringsAsFactors=FALSE)
}
# Get nutrient management calculation and metadata
#
get_nutrient_mgmt <- function(allinputs, addId="mgp_nut_1", calc=TRUE){
#allinputs <- allinputs #AllInputs()
indexSoilMagp<- getAddInputId(addId = addId, pattern= "mgp_nut_", replacement="")
#out<<-get_nutrient_details_magm(allinputs, indexSoilMagp= nutIndexSoilMagp)
dt <- allinputs %>% dplyr::filter(!str_detect(id, "add")) %>%
dplyr::filter(!str_detect(id, "button")) %>%
dplyr::filter(!str_detect(id, "_sel_factor_")) %>%
dplyr::filter(!str_detect(id, "-selectized"))
#UNIT
nutUnit <- dt %>% dplyr::filter(str_detect(id, paste0("^","sfNutUnit","$"))) %>% nth(2)
#Product
nutProd <- dt %>% dplyr::filter(str_detect(id, paste0("^","sfNutrientProduct_")))
#NUTRIENT SPLIT ##########################################################################
out_nut_mgmt <- list()
for(i in seq.int(indexSoilMagp) ){
out1 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit1_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out2 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit2_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out3 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit3_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out4 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit4_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out5 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit5_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out6 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit6_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out7 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit7_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out8 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit8_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out9 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit9_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out10 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit10_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out11 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit11_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out12 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit12_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out13 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit13_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out14 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit14_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out_nut_mgmt[[i]] <-data.frame(out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
names(out_nut_mgmt[[i]]) <- c("N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
nut_mgmt<-data.table::rbindlist(out_nut_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
#nut_mgmt$N <- c(25,36)
treatments<-nut_mgmt
##########################################################################################
#NUTRIENT CHOSE PRODUCT #################################################################
out_prod_mgmt <- list()
indexSoilProd <- lapply(1:length(nutProd$values), function(x) strsplit(nutProd$values, ", ")[[x]] %>% seq.int())
indexCum <- lapply( 1:length(indexSoilMagp), function(x)paste0(indexSoilMagp[x], "_", indexSoilProd[[x]]) ) %>% unlist()
for(i in seq.int(indexCum) ){
#for(j in 1:length(indexSoilProd[i]) ){
splitId <- indexCum[i] %>% str_replace("_.","")
prodname <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit0_",indexCum[i] ))) %>% nth(2)
out1 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit1_", indexCum[i] ))) %>% nth(2) %>% as.numeric()
out2 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit2_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out3 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit3_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out4 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit4_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out5 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit5_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out6 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit6_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out7 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit7_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out8 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit8_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out9 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit9_", indexCum[i] ))) %>% nth(2)%>% as.numeric()
out10 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit10_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out11 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit11_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out12 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit12_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out13 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit13_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out14 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit14_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out_prod_mgmt[[i]] <-data.frame(splitId, prodname, out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
#names(out_prod_mgmt[[j]]) <- c("name", "N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
#}
}
prod_mgmt <- data.table::rbindlist(out_prod_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
#prod_mgmt$N <- c(90,89)
fertilizers <- prod_mgmt
names(fertilizers) <- c("splitId","name", "N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
#outrate<- try({fertilizerRates_mgmt(fertilizers=fertilizers, treatments= treatments)})
if(calc){
outrate<- list()
for(i in seq.int(unique(prod_mgmt$splitId)) ){
fertilizers2 <- fertilizers %>% dplyr::filter(splitId==i) %>% dplyr::select(-splitId)
treatments2 <- treatments[i,]
outrate[[i]] <- try({FertilizerRates_mgmt(fertilizers=fertilizers2, treatments= treatments2)})
}
outrate<- data.table::rbindlist(outrate) %>% as.data.frame(stringsAsFactors=FALSE)
out <- list(outrate= outrate, fertilizers= fertilizers,treatments= treatments, splitId= prod_mgmt$splitId)
} else {
out <- list(fertilizers= fertilizers,treatments= treatments )
}
out
}
# Get product/fertilizer management
#
get_prodfert_mgmt <- function(allinputs, addId="mgp_pro_1", splitId){
indexSoilMagp <- getAddInputId(addId = addId, pattern= "mgp_pro_", replacement="")
splitId <- getAddInputId(splitId,"mgp_proidx_", "")
#out<<-get_nutrient_details_magm(allinputs, indexSoilMagp= nutIndexSoilMagp)
dt <- allinputs %>% dplyr::filter(!str_detect(id, "add")) %>%
dplyr::filter(!str_detect(id, "button")) %>%
dplyr::filter(!str_detect(id, "_sel_factor_")) %>%
dplyr::filter(!str_detect(id, "-selectized"))
#Product/Fertilizer data
out_treatment_mgmt <- list()
for(i in seq.int(splitId)){
splitIdVal <- splitId[i]
out0 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit0_",splitId[i])) ) %>% dplyr::nth(2)
prodfert <- dt %>% dplyr::filter(str_detect(id, paste0("txtsfProductValue_",splitId[i])) ) %>% dplyr::nth(2)%>% as.numeric()
out_treatment_mgmt[[i]] <-data.frame(splitIdVal, out0, prodfert, stringsAsFactors = FALSE)
names(out_treatment_mgmt[[i]]) <- c("splitId", "name", "product")
}
treatment_mgmt <- data.table::rbindlist(out_treatment_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
#Product/Fertilizer split data
out_prodfersplit_mgmt <- list()
for(i in seq.int(splitId)){
splitIdFerVal <- splitId[i]
out0 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit0_",splitId[i])) ) %>% nth(2)
out1 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit1_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out2 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit2_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out3 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit3_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out4 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit4_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out5 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit5_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out6 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit6_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out7 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit7_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out8 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit8_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out9 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit9_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out10 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit10_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out11 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit11_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out12 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit12_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out13 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit13_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out14 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit14_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out_prodfersplit_mgmt[[i]] <-data.frame(splitIdFerVal, out0, out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
names(out_prodfersplit_mgmt[[i]]) <- c("splitId", "name","N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
prodfert_mgmt <- data.table::rbindlist(out_prodfersplit_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
out <- list(treatment_mgmt= treatment_mgmt, prodfert_mgmt= prodfert_mgmt)
}
# Get protocol-calculation table ------------------------------------------
AGROFIMS/agdesign documentation built on June 11, 2020, 12:02 p.m.
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Defines functions get_prodfert_mgmt get_nutrient_mgmt FertilizerRates_mgmt NutrientRates_mgmt fertilizerRates nutrientRates fertilizer_calculation fertilizer_reshape product_calculation nutrient_reshape productApplicationRates getFert get_fertilizer get_ec_sf
Documented in get_ec_sf get_fertilizer
#' Get exp conditions , soil and fertilkity tab
#' @description get all input values related to the experiment conditions \code{soil and fertility} experiment condition tab,
#' provided by users when type in AGROFIMS.
#' @param allinputs shiny reactiveValuesList provided by AGROFIMS
#' @param napp \code{numeric} number of applications
#' @author Omar Benites
#'
get_ec_sf <- function(input){
if(length(input$soilfertility_to_collect_field)==0){
lbl <- c("Fertilizer_type", "Fertilizer_amount_kg/ha","Nutrient_amount_kg/ha")
dt <- data.frame()
} else {
lbl <- input$soilfertility_to_collect_field
lbl <- dplyr::case_when( lbl =="Fertilizer type"~ "Fertilizer_type",
lbl =="Fertilizer amount" ~ "Fertilizer_amount_kg/ha",
lbl=="Nutrient amount" ~"Nutrient_amount_kg/ha",
lbl=="Timing" ~ "Fertilizer_timing",
lbl=="Number of fertilizer applications" ~"Fertilizer_application_number",
lbl=="Nutrient type" ~"Nutrient_type",
lbl=="Fertilizer application technique" ~"Fertilizer_application_technique",
lbl=="Fertilizer implement type" ~"Fertilizer_implement_type",
lbl=="Fertilizer notes" ~"Fertilizer_notes",
TRUE ~ lbl)
lbl <- lbl
dt <- as.list(rep("", length(lbl)))
names(dt) <- lbl
}
out <- list(dt= dt, lbl= lbl)
##LABEL FOR TRAITLIST :remove all double underscore from soil_fertility labels
# lbl<- str_replace_all(string = lbl_soil, pattern = "__[:digit:]+$",replacement = "")
# lbl <- unique(lbl)
# out<- list(dt=dt, lbl= lbl)
#
}
#
# get_collectable_sf <- function(input){
#
# trait <- input$soilfertility_to_collect_field
# if(!is.null(trait)){
# #trait_values <- vector("list", length(trait))
# trait_values <- as.list(rep("", length(trait)))
# names(trait_values) <-
# } else {
#
# }
#
#
# }
#' Get fertilizer product names from Fertilizer and Nutrient dataset
#' @description Get fertilizer's names from Fertilizer and Nutrient dataset
#' @param .data Fertilizer and Nutrient dataset
#' @author Omar Benites
#'
get_fertilizer <- function(.data){
.data$name
}
#### Simple case #########################################
getFert <- function(treats, fertilizers, selected) {
treats <- treats %>% arrange_at(1)
fertilizers <- fertilizers[c("group","name",names(treats))]
factors <- t(as.matrix(treats))
f <- fertilizers[fertilizers$name == selected, -c(1:2)]
f <- as.matrix(f)/100
x <- as.vector(na.omit(factors / as.vector(f)))
m <- matrix(x)
colnames(m) <-selected
rownames(m) <- paste0("Level-", 1:nrow(m))
m <- as.data.frame(m,stringsAsFactors=FALSE) %>% tibble::rownames_to_column()
colnames(m)[1] <- c("Levels")
m[,1] <- paste0("Level_",names(treats),"_",treats[,1] )
m
}
#### End simple case #########################################
############################################ NUTRIENT AND FERTILIZERS ####################################################
# Product/Fertilizer Rates
productApplicationRates <- function(supply, treatment, price, minCost=TRUE){
name <- supply$name
supply <- t(as.matrix(supply[,-1]))
treatment <- as.matrix(treatment)
result <- matrix(nrow=ncol(supply), ncol=nrow(treatment))
price <- price * minCost
treatment <- treatment * 100
for (i in 1:nrow(treatment)) {
solution <- limSolve::linp(E=supply, F=treatment[i,], Cost=price)
if (solution$IsError) {
result[,i] <- -99
} else {
result[,i] <- solution$X
}
}
colnames(result) <- paste0("tr.", 1:ncol(result))
data.frame(name, result)
}
# Reshape nutrient data
nutrient_reshape<- function(df, name="A", values="B"){
out<- list()
nutrient<- unique(df[,name])
for(i in seq.int(nutrient) ){
out[[i]] <- df %>% dplyr::filter(SplitNutName==nutrient[i]) %>% dplyr::select_(values) %>% nth(1) %>% as.numeric()
out[[i]]<- as.data.frame(out[[i]],stringsAsFactors=FALSE)
names(out[[i]]) <- nutrient[i]
}
if(length(out)>1){
#https://stackoverflow.com/a/53893866/7340448
#How to cbind a list of data.frames of different lengths
#library(rowr)
out <- do.call(rowr::cbind.fill, c(out, fill = NA))
} else {
out <- out[[1]]
}
out
#out<- rbindlist(out)
}
#Product/Fertilizer calculation wrapper function for the DESIGN TAB
product_calculation <- function(allinputs, dfAll, index="1", indexEspLvl=indexEspLvl , design="frcbd"){
#Get labels
indexEspLvl<- filter_index_espLvl_design(index= index, indexEspLvl=indexEspLvl, design=design, designEspflvl="_lvl_espType_")
#Get especial levels
indexEspLvl_subfix <- get_index_espLvl_design(indexEspLvl, paste0(design,"_lvl_espType_"))
lookup <- paste0(design,"_")
#Table of nutrient details (eletype, mNumTiming)-----------------------------------------------------------------------------------------
nutrients_details <- get_nutrient_details_design(allinputs=allinputs, design=design, index =index, indexEspLvl = indexEspLvl)
#Split nutrient name and split number per each nutrient-------------------------------------------------------------------------------
split_nutrient_name <- lapply(X = seq.int(dfAll$splits), function(x) rep(dfAll$eleType[x], each =as.numeric(dfAll$splits[x]))) %>% unlist()
split_nutrient_number <- lapply(as.integer(dfAll$splits), function(x) seq.int(x)) %>% unlist()
nutrients_details <- nutrients_details %>%
mutate(SplitNutName = split_nutrient_name ) %>%
mutate(splitNutNum = split_nutrient_number)
#Customizeing nutrient_details
class(nutrients_details)<-"data.frame"
nutrient_elements <- nutrients_details[,c("SplitNutName", "nutAmount")]
nutrient_elements[,2] <- as.numeric(nutrient_elements[,2] )
## Get nutrient tables per each sub level #############################################
out_nut<- vector(mode="list", nrow(dfAll))
lookup <- paste0("^",design,"_")
#Create table of fertilizers
for (i in 1:nrow(dfAll)){
level <- dfAll[i,1]
type <- dfAll[i,2]
levels <- dfAll[i,3]
unit <- dfAll[i,4]
index <- dfAll[i,5]
if(as.numeric(levels)==0){
out_nut[[i]] <-data.frame(0,0,0,0,0,0,0,0,0,0,0,0,0,0, stringsAsFactors = FALSE)
} else {
#namefert <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"factorType_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out2 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT2_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out3 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT3_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out4 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT4_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out5 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT5_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out6 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT6_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out7 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT7_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out8 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT8_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out9 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT9_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out10 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT10_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out11 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT11_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out12 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT12_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out13 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT13_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out14 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputNutDT14_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out_nut[[i]] <-data.frame(out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
}
names(out_nut[[i]]) <- c("N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
#end create table of fertilizers
nutfert <- data.table::rbindlist(out_nut) %>% as.data.frame(stringsAsFactors=FALSE)
temp4 <- list()
#OLD CODE
# for(i in 1:nrow(dfAll)){
# splits <- as.numeric(dfAll$splits)[i]
# temp4[[i]] <- nutfert[rep(i,splits), ]
# #sapply(df, rep.int,2) %>% as.data.frame(stringsAsFactors=FALSE) method 2
# }
# END OLD CODE
#NEW CODE
#Create matrix with zeros and 1 row
d0 <- data.frame(matrix(0, ncol = ncol(nutfert), nrow =1))
names(d0) <- names(nutfert)
for(i in 1:nrow(dfAll)){
if(as.numeric(dfAll$levels[i])==0){
splits <- as.numeric(dfAll$splits)[i]
temp4[[i]] <- d0[rep(i,splits), ]
i <- i-1
}else {
splits <- as.numeric(dfAll$splits)[i]
temp4[[i]] <- nutfert[rep(i,splits), ]
}
}
#END NEW CODE
nutfert <- data.table::rbindlist(temp4) %>% as.data.frame(stringsAsFactors=FALSE)
nutfert$name <- paste(nutrients_details$mNutProduct)
nutfert <- nutfert[,c(15, 1:14)]
names(nutfert) <- c("name", "Nitrogen","Phosphorus","Potassium","Calcium","Magnesium",
"Sulfur", "Moldbenum", "Zinc", "Boron", "Copper","Iron", "Manganese", "Nickel", "Chlorine")
fertilizers <- nutfert
##End Get nutrient tables per each sub level ###########################################
#Get treatments ######################################################################
treatments <- as.list(as.numeric(nutrients_details$nutAmount))
names(treatments) <- nutrients_details$SplitNutName
#End get treatments##################################################################
#aaaaaa=list(treatments=treatments,fertilizers = fertilizers)
#saveRDS(object = aaaaaa,file= "/home/obenites/AGROFIMS/agdesign/tests/testthat/userInput/nut_calculation_design_5.rds")
out <- fertilizerRates(fertilizers= fertilizers, treatments = treatments)
#out <- unlist(out)
nutSplitNames <- paste(nutrients_details$SplitNutName,nutrients_details$nutAmount,nutrients_details$splitNutNum, sep="_")
fertRate <- data.frame(Product=nutrients_details$mNutProduct, Nutrient=nutSplitNames ,Rates = out)
}
#Reshape fertilizer/product data
fertilizer_reshape<- function(df){
out<- data.frame(t(as.numeric(df$mProdAmount)),stringsAsFactors = FALSE)
names(out) <- paste(df$factorType,df$splitFertNum, 1:nrow(df),sep = "_")
out
}
#Fertilizer calculation for the DESIGN TAB
fertilizer_calculation<- function(allinputs, dfAll, index="1", indexEspLvl=indexEspLvl , design="frcbd"){
#Get labels
indexEspLvl<- filter_index_espLvl_design(index= index, indexEspLvl=indexEspLvl, design=design, designEspflvl="_lvl_espType_")
#Get especial levels
indexEspLvl_subfix <- get_index_espLvl_design(indexEspLvl, paste0(design,"_lvl_espType_"))
#lookup <- paste0(design,"_")
#Table of nutrient details (eletype, mNumTiming)-----------------------------------------------------------------------------------------
fertilizer_details <- get_fertilizer_details_design(allinputs, design, index, indexEspLvl)
class(fertilizer_details)<- "data.frame"
## Split nutrient name and split number per each nutrient-------------------------------------------------------------------------------
split_fert_name <- lapply(X = seq.int(dfAll$splits), function(x) rep(dfAll$eleType[x], each =as.numeric(dfAll$splits[x]))) %>% unlist()
split_fert_number <- lapply(as.integer(dfAll$splits), function(x) seq.int(x)) %>% unlist()
fertilizer_details <- fertilizer_details %>%
mutate(splitFertNum = split_fert_number) %>%
mutate(SplitFertName = split_fert_name )
fertilizer_details[,"mProdAmount"] <- as.numeric(fertilizer_details[,"mProdAmount"])
## NEW CODE: GET FERTILIZER_AVAILABLE TABLE
#First input
# fact <- lapply(seq.int(unique(fertilizer_details$factorType)),
# function(x) fertilizer_details %>% dplyr::filter(factorType==fertilizer_details$factorType[x])
# %>% dplyr::select(mProdAmount) %>% nth(1))
# names(fact) <- unique(fertilizer_details$factorType)
## END NEW CODE
## FACT (TREATMENT): Fertilizer Application Product
fact<- as.list(as.numeric(fertilizer_details$mProdAmount))
names(fact) <- paste(fertilizer_details$factorType,fertilizer_details$mProdAmount,
fertilizer_details$splitFertNum, sep="_")
## NEW CODE: GET FERTILIZER_AVAILABLE TABLE
out_fert<- vector(mode="list", nrow(dfAll))
lookup <- paste0("^",design,"_")
for (i in 1:nrow(dfAll)){
level <- dfAll[i,1]
type <- dfAll[i,2]
levels <- dfAll[i,3]
unit <- dfAll[i,4]
index <- dfAll[i,5]
print(paste(level,index,i))
#frcbd_factorType_1_1_1
namefert <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"factorType_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out1 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT1_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out2 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT2_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out3 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT3_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out4 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT4_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out5 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT5_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out6 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT6_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out7 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT7_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out8 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT8_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out9 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT9_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out10 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT10_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out11 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT11_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out12 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT12_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out13 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT13_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out14 <- allinputs %>% dplyr::filter(str_detect(id, paste0(lookup,"outputFerDT14_",level,"_",index,"_",i,"$"))) %>% dplyr::nth(2)%>% as.numeric()
out_fert[[i]] <-data.frame(namefert, out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
names(out_fert[[i]]) <- c("name","N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
fert_available<- data.table::rbindlist(out_fert) %>% as.data.frame(stringsAsFactors=FALSE)
#fert_available$name <- paste(fert_available$name, dfAll$levels, dfAll$splits, sep = "_")
temp <- list()
for(i in 1:nrow(dfAll)){
splits <- as.numeric(dfAll$splits)[i]
temp[[i]] <- fert_available[rep(i,splits), ]
#sapply(df, rep.int,2) %>% as.data.frame(stringsAsFactors=FALSE) method 2
}
fert_available<- data.table::rbindlist(temp) %>% as.data.frame(stringsAsFactors=FALSE)
fert_available$name <- paste(fert_available$name, fertilizer_details$mProdAmount,
fertilizer_details$splitFertNum, sep = "_")
## END NEW CODE : GET FERTILIZER_AVAILABLE TABLE
### FORMER CODE
# fert_available <- dt_fernut %>% dplyr::filter(name %in% unique(fertilizer_details$factorType))
# names(fert_available) <- c("group", "name", "Nitrogen","Phosphorus","Potassium","Calcium","Magnesium",
# "Sulfur", "Moldbenum", "Zinc", "Boron", "Copper","Iron", "Manganese", "Nickel", "Chlorine")
# fert_available <- tibble::as_tibble(fert_available) %>% dplyr::select(-group)
### END CODE
#Output
out <- nutrientRates(fert_available, fact)
for(i in seq.int(out)){
#rownames(out[[i]]) <- paste0(names(out)[i],"_",rownames(out[[i]]))
rownames(out[[i]]) <- paste0(names(out)[i])
}
out <- lapply(seq.int(out), function(x) as.data.frame(out[[x]],stringsAsFactors=FALSE))
out <- lapply(seq.int(out), function(x) tibble::rownames_to_column(out[[x]]) )
out <- data.table::rbindlist(out,use.names = TRUE)
out <- as.data.frame(out, stringsAsFactors=FALSE)
}
# Nutrient Rates (output)
nutrientRates <- function(fertilizers, treatments) {
m <- match(names(treatments), fertilizers$name)
#stopifnot(!any(is.na(m)))
fertilizers <- fertilizers[m, ]
f <- as.matrix(fertilizers[,-1]) # for easy multiplication
out <- list()
for (i in 1:length(treatments)) {
treat <- unlist(treatments[[i]])
r <- f[rep(i, length(treat)), ,drop=FALSE] * treat / 100
rownames(r) <- round(treat,1)
out[[ fertilizers$name[i] ]] <- r
}
out
}
# Fertilizer/Product Rates (output)
# fertilizerRates <- function(fertilizers, treatments) {
# out <- list()
# for (i in 1:length(treatments)) {
# j <- colnames(fertilizers) == names(treatments[i])
# #stopifnot(any(j)) # no match
# fert <- fertilizers[i,j]
# k <- which(fert > 0)
# #stopifnot(length(k)==1) # one, and only one, product must have the nutrient!
# out[[ i ]] <- unlist(treatments[i]) / (fert[k] / 100)
# if(length(out[[ i ]])==0 ){ out[[ i ]]<- "" }
# names(out[[i]])<-NULL
# }
# names(out) <- names(treatments)
# out
# }
#NEW CODE
# Fertilizer/Product Rates (output)
fertilizerRates <- function(fertilizers, treatments) {
fertilizers<- fertilizers[,-1]
out_product <- vector(mode= "numeric", length=length(treatments))
for(i in 1:length(treatments)){
if(treatments[[i]]==0){
out_product[i] <- 0
} else {
out_product[i] <- treatments[[i]]/(fertilizers[i,names(treatments)[i]]/100)
}
}
out_product
}
# Fertilizer/Product Rates (output) for Management Practices
#fertilizerRates_mgmt <- function(fertilizers, treatments) {
NutrientRates_mgmt <- function(fertilizers, treatments) {
prod_names <- treatments$name
out <- (fertilizers[,-c(1,2)]*treatments[,-c(1,2)])/100
out$name <- prod_names
nc <- ncol(out)
out <- out[, c(nc, 1:(nc-1))]
out
}
# Fertilizer/Product Rates (output) for Management Practices
#NutrientRates_mgmt <- function(fertilizers, treatments) {
FertilizerRates_mgmt <- function(fertilizers, treatments) {
#out<- vector(mode="list", length = nrow(treatments))
#for(i in 1:nrow(treatments)){
out <- treatments[ rep(1, nrow(fertilizers)),]/(fertilizers[,-1]/100)
print("--fertil mgmt--")
#print(out)
out <- replace(out, is.na(out), 0) #change nan values by 0
is.na(out) <- do.call(cbind,lapply(out, is.infinite)) #change inf values by 0
#}
out
#out <- data.table::rbindlist(out) %>% as.data.frame(stringsAsFactors=FALSE)
}
# Get nutrient management calculation and metadata
#
get_nutrient_mgmt <- function(allinputs, addId="mgp_nut_1", calc=TRUE){
#allinputs <- allinputs #AllInputs()
indexSoilMagp<- getAddInputId(addId = addId, pattern= "mgp_nut_", replacement="")
#out<<-get_nutrient_details_magm(allinputs, indexSoilMagp= nutIndexSoilMagp)
dt <- allinputs %>% dplyr::filter(!str_detect(id, "add")) %>%
dplyr::filter(!str_detect(id, "button")) %>%
dplyr::filter(!str_detect(id, "_sel_factor_")) %>%
dplyr::filter(!str_detect(id, "-selectized"))
#UNIT
nutUnit <- dt %>% dplyr::filter(str_detect(id, paste0("^","sfNutUnit","$"))) %>% nth(2)
#Product
nutProd <- dt %>% dplyr::filter(str_detect(id, paste0("^","sfNutrientProduct_")))
#NUTRIENT SPLIT ##########################################################################
out_nut_mgmt <- list()
for(i in seq.int(indexSoilMagp) ){
out1 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit1_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out2 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit2_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out3 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit3_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out4 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit4_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out5 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit5_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out6 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit6_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out7 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit7_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out8 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit8_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out9 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit9_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out10 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit10_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out11 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit11_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out12 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit12_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out13 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit13_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out14 <- dt %>% dplyr::filter(str_detect(id, paste0("sfNutrientSplit14_",indexSoilMagp[i]))) %>% nth(2)%>% as.numeric()
out_nut_mgmt[[i]] <-data.frame(out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
names(out_nut_mgmt[[i]]) <- c("N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
nut_mgmt<-data.table::rbindlist(out_nut_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
#nut_mgmt$N <- c(25,36)
treatments<-nut_mgmt
##########################################################################################
#NUTRIENT CHOSE PRODUCT #################################################################
out_prod_mgmt <- list()
indexSoilProd <- lapply(1:length(nutProd$values), function(x) strsplit(nutProd$values, ", ")[[x]] %>% seq.int())
indexCum <- lapply( 1:length(indexSoilMagp), function(x)paste0(indexSoilMagp[x], "_", indexSoilProd[[x]]) ) %>% unlist()
for(i in seq.int(indexCum) ){
#for(j in 1:length(indexSoilProd[i]) ){
splitId <- indexCum[i] %>% str_replace("_.","")
prodname <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit0_",indexCum[i] ))) %>% nth(2)
out1 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit1_", indexCum[i] ))) %>% nth(2) %>% as.numeric()
out2 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit2_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out3 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit3_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out4 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit4_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out5 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit5_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out6 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit6_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out7 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit7_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out8 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit8_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out9 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit9_", indexCum[i] ))) %>% nth(2)%>% as.numeric()
out10 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit10_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out11 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit11_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out12 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit12_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out13 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit13_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out14 <- dt %>% dplyr::filter(str_detect(id, paste0("nutrientProductSplit14_",indexCum[i] ))) %>% nth(2)%>% as.numeric()
out_prod_mgmt[[i]] <-data.frame(splitId, prodname, out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
#names(out_prod_mgmt[[j]]) <- c("name", "N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
#}
}
prod_mgmt <- data.table::rbindlist(out_prod_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
#prod_mgmt$N <- c(90,89)
fertilizers <- prod_mgmt
names(fertilizers) <- c("splitId","name", "N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
#outrate<- try({fertilizerRates_mgmt(fertilizers=fertilizers, treatments= treatments)})
if(calc){
outrate<- list()
for(i in seq.int(unique(prod_mgmt$splitId)) ){
fertilizers2 <- fertilizers %>% dplyr::filter(splitId==i) %>% dplyr::select(-splitId)
treatments2 <- treatments[i,]
outrate[[i]] <- try({FertilizerRates_mgmt(fertilizers=fertilizers2, treatments= treatments2)})
}
outrate<- data.table::rbindlist(outrate) %>% as.data.frame(stringsAsFactors=FALSE)
out <- list(outrate= outrate, fertilizers= fertilizers,treatments= treatments, splitId= prod_mgmt$splitId)
} else {
out <- list(fertilizers= fertilizers,treatments= treatments )
}
out
}
# Get product/fertilizer management
#
get_prodfert_mgmt <- function(allinputs, addId="mgp_pro_1", splitId){
indexSoilMagp <- getAddInputId(addId = addId, pattern= "mgp_pro_", replacement="")
splitId <- getAddInputId(splitId,"mgp_proidx_", "")
#out<<-get_nutrient_details_magm(allinputs, indexSoilMagp= nutIndexSoilMagp)
dt <- allinputs %>% dplyr::filter(!str_detect(id, "add")) %>%
dplyr::filter(!str_detect(id, "button")) %>%
dplyr::filter(!str_detect(id, "_sel_factor_")) %>%
dplyr::filter(!str_detect(id, "-selectized"))
#Product/Fertilizer data
out_treatment_mgmt <- list()
for(i in seq.int(splitId)){
splitIdVal <- splitId[i]
out0 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit0_",splitId[i])) ) %>% dplyr::nth(2)
prodfert <- dt %>% dplyr::filter(str_detect(id, paste0("txtsfProductValue_",splitId[i])) ) %>% dplyr::nth(2)%>% as.numeric()
out_treatment_mgmt[[i]] <-data.frame(splitIdVal, out0, prodfert, stringsAsFactors = FALSE)
names(out_treatment_mgmt[[i]]) <- c("splitId", "name", "product")
}
treatment_mgmt <- data.table::rbindlist(out_treatment_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
#Product/Fertilizer split data
out_prodfersplit_mgmt <- list()
for(i in seq.int(splitId)){
splitIdFerVal <- splitId[i]
out0 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit0_",splitId[i])) ) %>% nth(2)
out1 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit1_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out2 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit2_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out3 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit3_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out4 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit4_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out5 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit5_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out6 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit6_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out7 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit7_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out8 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit8_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out9 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit9_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out10 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit10_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out11 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit11_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out12 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit12_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out13 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit13_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out14 <- dt %>% dplyr::filter(str_detect(id, paste0("productProductSplit14_",splitId[i])) ) %>% nth(2)%>% as.numeric()
out_prodfersplit_mgmt[[i]] <-data.frame(splitIdFerVal, out0, out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14, stringsAsFactors = FALSE)
names(out_prodfersplit_mgmt[[i]]) <- c("splitId", "name","N", "P", "K", "Ca", "Mg", "S" , "Mb" , "Zn", "B", "Cu", "Fe", "Mn", "Ni","Cl" )
}
prodfert_mgmt <- data.table::rbindlist(out_prodfersplit_mgmt) %>% as.data.frame(stringsAsFactors=FALSE)
out <- list(treatment_mgmt= treatment_mgmt, prodfert_mgmt= prodfert_mgmt)
}
# Get protocol-calculation table ------------------------------------------
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