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server - Copy.R
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server - Copy.R
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#' Paper based Annex dashboard
#' Authors : Meklit Chernet, Turry Ouma, IITA
#' Last updated on : November 2021 (to include GH)
#'
#setwd("C:/Users/User/Documents/ACAI/paper based/PaperbasedDashboard_GH")
#C:\Users\User\Documents\ACAI\paper based\PaperbasedDashboard -v4 - Copy
#C:\Users\User\Documents\ACAI\paper based\PaperBasedAnnex - RW
library(tidyr)
require(plyr)
library(rgdal)
library(raster)
library(dismo)
library(maptools)
library(rgeos)
require(RColorBrewer)
require(graphics)
require(rasterVis)
library(sp)
library(shinyalert)
library(ggthemes)
require(ggplot2)
library(gridExtra)
library(hexbin)
library(viridis)
library(sf)
library(ggspatial)
require(ggrepel)
library(shiny)
library(shinyWidgets)
library(shinythemes)
library(plotly)
library(sf)
library(raster)
library(dplyr)
library(spData)
library(tmap)
library(leaflet)
library(cartogram)
library(grid)
library(formattable)
library(shinybusy)
library(DT)
# library(remotes)
# install_github("mtennekes/tmaptools")
# install_github("mtennekes/tmap")
#code that formats the datatable
# data_output <- function(df) {
# DT::datatable(df, rownames= FALSE, options = list( dom = 'Bfrtip', buttons = c('excel','pdf','print','colvis'),
# pageLength = nrow(df), drawCallback = JS(js), initComplete = DT::JS(
# "function(settings, json) {",
# "$(this.api().table().header()).css({'font-size': '20px','background-color': '#000000', 'color': '#fff'});",
#
# "}") ), list(extend = 'pdf',
# filename = 'CurrentTable',
# title = paste("My chTitle"),
# header = FALSE),
# extensions = c('Buttons','FixedColumns'))%>% formatStyle(columns = colnames(.$x$data), `font-size` = '18px')
# }
# data_output <- function(df) {
#
# datatable(head(iris, 20), options = list(
# initComplete = JS(
# "function(settings, json) {",
# "$(this.api().table().header()).css({'font-size': '5px', 'background-color': '#c2d1f0', 'color': '#fff'});",
# "}"))) %>% formatStyle(columns = colnames(.$x$data), `font-size` = '12px')
# }
### SHINY SERVER ###
server = function(input, output, session) {
#.............................................................................
# Show a modal on initiation of tool
#.............................................................................
shinyalert("Paper based Annex", "This tool contains tables and maps with advice on application rates of urea,
DAP & NPK fertilizer for cassava, as well as the expected root yield response. Response to fertilizer depends on soil
conditions and the time of planting.
<br>
<br>
<br>
Please wait....
<br>
<br>
(This window will automatically close when country data is loaded)
", type = "info", timer = 14500, size = 'm',
closeOnClickOutside = FALSE,
closeOnEsc = FALSE,
animation = TRUE,
html = TRUE,
showConfirmButton = FALSE,
showCancelButton = FALSE,
confirmButtonText = "OK",
confirmButtonCol = "#AEDEF4")
#.............................................................................
#spinner before maps are displayed
#.............................................................................
observeEvent(input$btn_go, {
shinybusy::show_modal_spinner(
spin = "cube-grid",
#spin = "fading-circle",
#spin = "fading-circle",
color = "#228B22",
#00FF00
text = "Please wait while the map loads..."
)
Sys.sleep(6)
remove_modal_spinner()
})
#.............................................................................
#render select input options
#.............................................................................
output$country <- renderUI({
pickerInput("country", "Select Country:",
choices = c("Nigeria", "Tanzania", "Rwanda", "Ghana"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
#})
observeEvent(input$country, {
if(input$country == "Nigeria" | input$country == "Tanzania" | input$country == "Rwanda" | input$country == "Ghana") {
output$usecase <- renderUI({
pickerInput("usecase", "Select use case",
choices = c("Fertilizer Recommendation", "Scheduled Planting"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1),
)
})
}
})
output$region <- renderUI({
pickerInput("region", "Select region(s)", choices = c("Geita", "Kagera","Kigoma","Lindi", "Mara", "Mtwara", "Mwanza","Pwani", "Shinyanga",
"Simiyu", "Tanga","Zanzibar South and Central"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
output$lga_Groups <- renderUI({
pickerInput("lga_Groups", "Select state",
choices = c("Abia", "Akwa Ibom","Anambra", "Benue", "Cross River", "Delta", "Ebonyi","Edo", "Ekiti",
"Enugu","Imo", "Kogi", "Kwara","Ogun", "Ondo", "Osun", "Oyo","Taraba"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
output$state <- renderUI({
pickerInput("state", "Select state",
choices = c("Amajyepfo", "Amajyaruguru","Umujyi wa Kigali", "Iburengerazuba", "Iburasirazuba"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
output$reg_ghana <- renderUI({
pickerInput("reg_ghana", "Select region",
choices = c("Savannah", "Ashanti","Ahafo", "Volta", "Central", "Eastern", "Bono East", "Bono"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
observeEvent(input$usecase, {
if(!is.null(input$region) | !is.null(input$lga_Groups) | !is.null(input$state) | !is.null(input$reg_ghana)) {
output$plntmth <- renderUI({
pickerInput("plntmth", "Select planting month",
choices = c("January", "February", "March", "April", "May", "June", "July", "August", "September",
"October", "November", "December"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
}
})
observeEvent(input$plntmth, {
if(!is.null(input$plntmth)) {
output$costs <- renderUI({
pickerInput("costs", "Would you like to specify your prices for cassava and fertilizers?",
choices = c("Yes", "No"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
}
})
observeEvent(input$plntmth, {
if(!is.null(input$plntmth)) {
output$selection <- renderUI({
pickerInput("selection", "Select variable to view",
choices = c("NPK 15:15:15 rate", "Expected yield response", "Urea rate"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
output$selection2 <- renderUI({
pickerInput("selection2", "Select variable to view",
choices = c("NPK 17:17:17 rate", "DAP rate", "Expected yield response", "Urea rate"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
output$selection3 <- renderUI({
pickerInput("selection3", "Select variable to view",
choices = c("NPK 15:20:20 rate", "NPK 11:22:21 rate", "NPK 25:10:10 rate", "NPK 12:30:17 rate", "Expected yield response", "Urea rate"),
selected = NULL,
multiple = TRUE,
options = pickerOptions(maxOptions = 1))
})
}
})
observeEvent(input$usecase, {
if(!is.null(input$usecase)) {
output$unit_loc <- renderUI({
selectInput("unit_loc", "Select unit of land",
choices = c("acre", "ha"))
})
}
})
observeEvent(input$usecase, {
if(!is.null(input$usecase)) {
output$unit_loc_rw <- renderUI({
selectInput("unit_loc_rw", "Select unit of land",
choices = c("are", "ha"))
})
}
})
observeEvent(input$unit_loc, {
if(!is.null(input$unit_loc)) {
output$FCY_ha <- renderUI({
selectInput("FCY_ha", "Select Your Current Yield (Tonnes)",
choices = c("0-7.5 t/ha", "7.5-15 t/ha", "15-22.5 t/ha", "22.5-30 t/ha", ">30 t/ha", ""),
selected = "")
})
output$FCY_acre <- renderUI({
selectInput("FCY_acre", "Select Your Current Yield (Tonnes)",
choices = c("0-3 t/acre", "3-6 t/acre", "6-9 t/acre", "9-12 t/acre", ">12 t/acre", ""),
selected = "")
})
}
})
observeEvent(input$unit_loc_rw, {
if(!is.null(input$unit_loc_rw)) {
output$FCY_ha_rw <- renderUI({
selectInput("FCY_ha_rw", "Select Your Current Yield (Tonnes)",
choices = c("0-7.5 t/ha", "7.5-15 t/ha", "15-22.5 t/ha", "22.5-30 t/ha", ">30 t/ha", ""),
selected = "")
})
output$FCY_are_rw <- renderUI({
selectInput("FCY_are_rw", "Select Your Current Yield (Tonnes)",
choices = c("0-3 t/are", "3-6 t/are", "6-9 t/are", "9-12 t/are", ">12 t/are", ""),
selected = "")
})
}
})
observeEvent(input$costs, {
if(input$costs == "Yes" ) {
output$CassavaPrice <- renderUI({
textInput("CassavaPrice", "Price of cassava per ton")
})
}
})
observeEvent(input$costs, {
if(input$costs == "Yes") {
output$NPK151515Price <- renderUI({
textInput("NPK151515Price", "Cost of NPK:15:15:15 per 50Kg bag")
})
}
})
observeEvent(input$costs, {
if(input$costs == "Yes") {
output$NPK171717Price <- renderUI({
textInput("NPK171717Price", "Cost of NPK:17:17:17 per 50Kg bag")
})
output$DAPPrice <- renderUI({
textInput("DAPPrice", "Cost of DAP per 50Kg bag")
})
}
})
observeEvent(input$costs, {
if(input$costs == "Yes") {
output$NPK112221Price <- renderUI({
textInput("NPK112221Price", "Cost of NPK:11:22:21 per 50Kg bag")
})
output$NPK251010Price <- renderUI({
textInput("NPK251010Price", "Cost of NPK:25:10:10 per 50Kg bag")
})
output$NPK152020Price <- renderUI({
textInput("NPK152020Price", "Cost of NPK:15:20:20 per 50Kg bag")
})
output$NPK123017Price <- renderUI({
textInput("NPK123017Price", "Cost of NPK:12:30:17 per 50Kg bag")
})
}
})
#ADD GHANA FERT HERE
observeEvent(input$costs, {
if(input$costs == "Yes") {
output$UreaPrice <- renderUI({
textInput("UreaPrice", "Cost of Urea per 50Kg bag")
})
}
})
observeEvent(input$costs, {
if(input$costs == "Yes") {
output$btn_go <- renderUI({
actionButton("btn_go", "Get Maps & Tables", icon("map"),
style="color: #fff; background-color: green; border-color: #2e6da4")
})
}else if(input$costs == "No"){
output$btn_go <- renderUI({
actionButton("btn_go", "Get Maps & Tables", icon("map"),
style="color: #fff; background-color: green; border-color: #2e6da4")
})
}
})
#.................................................................................................................
#######################################################################################
## Read the GIS layers
#######################################################################################
TownsNG <- readOGR(dsn = ".", layer = "Places_towns")
RiversNG <- readOGR(dsn = ".", layer = "Rivers")
boundaryNG <- readOGR(dsn=getwd(), layer="gadm36_NGA_1")
ngstate <- readOGR(dsn=getwd(), layer="gadm36_NGA_2")
boundaryTZ <- readOGR(dsn=getwd(), layer="gadm36_TZA_1")
tzRegion <- readOGR(dsn=getwd(), layer="gadm36_TZA_2")
boundaryRW <- readOGR(dsn=getwd(), layer="gadm36_RWA_1")
rwState <- readOGR(dsn=getwd(), layer="gadm36_RWA_2")
boundaryGH <- readOGR(dsn=getwd(), layer="gha_admbnda_adm1_gss_20210308")
ghRegions <- readOGR(dsn=getwd(), layer="gha_admbnda_adm2_gss_20210308")
###################################################################################################
## NG fertilizer recom for FCY 1:5
###################################################################################################
FR_NG_FCY1 <- readRDS("FRrecom_lga_level1_NG_2020.RDS")
FR_NG_FCY2 <- readRDS("FRrecom_lga_level2_NG_2020.RDS")
FR_NG_FCY3 <- readRDS("FRrecom_lga_level3_NG_2020.RDS")
FR_NG_FCY4 <- readRDS("FRrecom_lga_level4_NG_2020.RDS")
FR_NG_FCY5 <- readRDS("FRrecom_lga_level5_NG_2020.RDS")
###########################################################################
## TZ fertilizer recom for FCY 1:5
###########################################################################
FR_TZ_FCY1 <- readRDS("FRrecom_lga_level1_TZ_2020.RDS")
FR_TZ_FCY2 <- readRDS("FRrecom_lga_level2_TZ_2020.RDS")
FR_TZ_FCY3 <- readRDS("FRrecom_lga_level3_TZ_2020.RDS")
FR_TZ_FCY4 <- readRDS("FRrecom_lga_level4_TZ_2020.RDS")
FR_TZ_FCY5 <- readRDS("FRrecom_lga_level5_TZ_2020.RDS")
###########################################################################
## RW fertilizer recom for FCY 1:5
###########################################################################
FR_RW_FCY <- readRDS("RW_CassavaPaperBased.RDS")
FR_RW_FCY1 <- FR_RW_FCY[FR_RW_FCY$FCY == "level1", ]
FR_RW_FCY2 <- FR_RW_FCY[FR_RW_FCY$FCY == "level2", ]
FR_RW_FCY3 <- FR_RW_FCY[FR_RW_FCY$FCY == "level3", ]
FR_RW_FCY4 <- FR_RW_FCY[FR_RW_FCY$FCY == "level4", ]
FR_RW_FCY5 <- FR_RW_FCY[FR_RW_FCY$FCY == "level5", ]
###########################################################################
## GH fertilizer recom for FCY 1:5
###########################################################################
FR_GH_FCY <- readRDS("GH_FR_CassavaPaperBased.RDS")
FR_GH_FCY1 <- FR_GH_FCY[FR_GH_FCY$FCY == "level1", ]
FR_GH_FCY2 <- FR_GH_FCY[FR_GH_FCY$FCY == "level2", ]
FR_GH_FCY3 <- FR_GH_FCY[FR_GH_FCY$FCY == "level3", ]
FR_GH_FCY4 <- FR_GH_FCY[FR_GH_FCY$FCY == "level4", ]
FR_GH_FCY5 <- FR_GH_FCY[FR_GH_FCY$FCY == "level5", ]
###########################################################################
## adding planting month
###########################################################################
addplm <- function(ds, country){
ds$respY <- ds$TargetY - ds$CurrentY
ds$groRev <- ds$NR + ds$TC
ds$plm <- as.factor(ds$plw)
levels(ds$plm)[levels(ds$plm) %in% 1:4] <- "January"
levels(ds$plm)[levels(ds$plm) %in% 5:8] <- "February"
levels(ds$plm)[levels(ds$plm) %in% 9:13] <- "March"
levels(ds$plm)[levels(ds$plm) %in% 14:17] <- "April"
levels(ds$plm)[levels(ds$plm) %in% 18:22] <- "May"
levels(ds$plm)[levels(ds$plm) %in% 23:26] <- "June"
levels(ds$plm)[levels(ds$plm) %in% 27:30] <- "July"
levels(ds$plm)[levels(ds$plm) %in% 31:35] <- "August"
levels(ds$plm)[levels(ds$plm) %in% 36:39] <- "September"
levels(ds$plm)[levels(ds$plm) %in% 40:43] <- "October"
levels(ds$plm)[levels(ds$plm) %in% 44:48] <- "November"
levels(ds$plm)[levels(ds$plm) %in% 49:53] <- "December"
if(country=="NG"){
ds$rateUrea <- ds$urea
ds$rateNPK151515 <- ds$NPK15_15_15
}else{
ds$rateUrea <- ds$urea
ds$rateNPK171717 <- ds$NPK17_17_17
ds$rateDAP <- ds$DAP
}
return(ds)
}
FR_NG_FCY1_plm <- addplm(ds=FR_NG_FCY1, country = "NG") ## NG if user current yield is level 1
FR_NG_FCY2_plm <- addplm(ds=FR_NG_FCY2, country = "NG") ## NG if user current yield is level 2
FR_NG_FCY3_plm <- addplm(ds=FR_NG_FCY3, country = "NG") ## NG if user current yield is level 3
FR_NG_FCY4_plm <- addplm(ds=FR_NG_FCY4, country = "NG") ## NG if user current yield is level 4
FR_NG_FCY5_plm <- addplm(ds=FR_NG_FCY5, country = "NG") ## NG if user current yield is level 5
FR_TZ_FCY1_plm <- addplm(ds=FR_TZ_FCY1, country = "TZ") ## TZ if user current yield is level 1
FR_TZ_FCY2_plm <- addplm(ds=FR_TZ_FCY2, country = "TZ") ## TZ if user current yield is level 2
FR_TZ_FCY3_plm <- addplm(ds=FR_TZ_FCY3, country = "TZ") ## TZ if user current yield is level 3
FR_TZ_FCY4_plm <- addplm(ds=FR_TZ_FCY4, country = "TZ") ## TZ if user current yield is level 4
FR_TZ_FCY5_plm <- addplm(ds=FR_TZ_FCY5, country = "TZ") ## TZ if user current yield is level 5
FR_RW_FCY1_plm <- addplm(ds=FR_RW_FCY1, country = "RW") ## RW if user current yield is level 1
FR_RW_FCY2_plm <- addplm(ds=FR_RW_FCY2, country = "RW") ## RW if user current yield is level 2
FR_RW_FCY3_plm <- addplm(ds=FR_RW_FCY3, country = "RW") ## RW if user current yield is level 3
FR_RW_FCY4_plm <- addplm(ds=FR_RW_FCY4, country = "RW") ## RW if user current yield is level 4
FR_RW_FCY5_plm <- addplm(ds=FR_RW_FCY5, country = "RW") ## RW if user current yield is level 5
FR_GH_FCY1_plm <- addplm(ds=FR_GH_FCY1, country = "GH") ## GH if user current yield is level 1
FR_GH_FCY2_plm <- addplm(ds=FR_GH_FCY2, country = "GH") ## GH if user current yield is level 2
FR_GH_FCY3_plm <- addplm(ds=FR_GH_FCY3, country = "GH") ## GH if user current yield is level 3
FR_GH_FCY4_plm <- addplm(ds=FR_GH_FCY4, country = "GH") ## GH if user current yield is level 4
FR_GH_FCY5_plm <- addplm(ds=FR_GH_FCY5, country = "GH") ## GH if user current yield is level 5
###########################################################################
## select FCY and read the corresponding file
## NG: Subsetting for the user defined Region and selecting a coordinate to put the state name in the map
###########################################################################
#.................................................................................................................
#Dashboard activity starts here
#.............................................................................
## Determine platform type and set working directory accordingly
observeEvent(input$btn_go, {
#define reactive values
country <- input$country
FCY_ha <- input$FCY_ha
print(FCY_ha)
FCY_acre <- input$FCY_acre
FCY_are_rw <- input$FCY_are_rw
FCY_ha_rw <- input$FCY_ha_rw
print(FCY_acre)
Selection <- input$selection
Selection2 <- input$selection2
Selection3 <- input$selection3
usecase <- input$usecase
plantMonth <- input$plntmth
state <- input$state
region <- input$region
lga_Groups <- input$lga_Groups
reg_ghana <- input$reg_ghana
plantMonth <- input$plntmth
cities <- input$city
unit <- input$unit_loc
unit_rw <- input$unit_loc_rw
UreaPrice <- as.numeric(input$UreaPrice)
DAPPrice <- as.numeric(input$DAPPrice)
NPK151515Price <- as.numeric(input$NPK151515Price)
NPK171717Price <- as.numeric(input$NPK171717Price)
NPK112221Price <- as.numeric(input$NPK112221Price)
NPK251010Price <- as.numeric(input$NPK251010Price)
NPK152020Price <- as.numeric(input$NPK152020Price)
NPK123017Price <- as.numeric(input$NPK123017Price)
CassavaPrice <- as.numeric(input$CassavaPrice)
lgaGroups <- input$lga_Groups
costs <- input$costs
print(unit)
print(unit_rw)
print(plantMonth)
#specify yield categories
if (country != 'Rwanda'){
if(unit == 'ha'){
yield_level <- ifelse( FCY_ha == "0-7.5 t/ha", "a low yield level",
ifelse( FCY_ha == "7.5-15 t/ha","a normal yield level",
ifelse( FCY_ha == "15-22.5 t/ha","a medium yield level",
ifelse( FCY_ha == "22.5-30 t/ha","a high yield level",
ifelse( FCY_ha == ">30 t/ha","a very high yield level"
)))))
}else if(unit == 'acre'){
yield_level <- ifelse( FCY_acre == "0-3 t/acre","a low yield level",
ifelse( FCY_acre == "3-6 t/acre","a normal yield level",
ifelse( FCY_acre == "6-9 t/acre","a medium yield level",
ifelse( FCY_acre == "9-12 t/acre","a high yield level",
ifelse( FCY_acre == ">12 t/acre","a very high yield level")
))))
}
} else if (country == 'Rwanda'){
#MEKLIT HERE
if(unit_rw == 'are'){
yield_level <- ifelse( FCY_are_rw == "0-7.5 t/are","a low yield level",
ifelse( FCY_are_rw == "3-6 t/are","a normal yield level",
ifelse( FCY_are_rw == "6-9 t/are","a medium yield level",
ifelse( FCY_are_rw == "9-12 t/are","a high yield level",
ifelse( FCY_are_rw == ">12 t/are","a very high yield level")
))))
}else if(unit_rw == 'ha'){
yield_level <- ifelse( FCY_ha_rw == "0-7.5 t/ha","a low yield level",
ifelse( FCY_ha_rw == "3-6 t/ha","a normal yield level",
ifelse( FCY_ha_rw == "6-9 t/ha","a medium yield level",
ifelse( FCY_ha_rw == "9-12 t/ha","a high yield level",
ifelse( FCY_ha_rw == ">12 t/ha","a very high yield level")
))))
}
}
print(yield_level)
#lga_Groups = "Abia"
if(country == 'Nigeria'){
lgaGroups <- input$lga_Groups
}else if (country == "Tanzania"){
lgaGroups <- input$region
}else if(country == "Rwanda"){
lgaGroups <- input$state
}else if(country == "Ghana"){
lgaGroups <- input$reg_ghana
}
if(country == 'Nigeria'){
lgaGroups2 <- input$lga_Groups
}else if (country == "Tanzania"){
lgaGroups2 <- input$region
}else if(country == "Rwanda"){
lgaGroups2 <- input$state
}else if(country == "Ghana"){
lgaGroups2 <- input$reg_ghana
}
if(country == 'Nigeria'){
if (unit == "ha"){
FCY <- FCY_ha
if(FCY == "7.5-15 t/ha" ){
ds <- FR_NG_FCY2_plm
}else if(FCY == "0-7.5 t/ha" ){
ds <- FR_NG_FCY1_plm
}else if(FCY == "15-22.5 t/ha" ){
ds <- FR_NG_FCY3_plm
}else if(FCY == "22.5-30 t/ha"){
ds <- FR_NG_FCY4_plm
}else if(FCY == ">30 t/ha" ){
ds <- FR_NG_FCY5_plm
}
}else if(unit == "acre"){
FCY <- FCY_acre
if(FCY == "3-6 t/acre" ){
ds <- FR_NG_FCY2_plm
}else if(FCY == "0-3 t/acre" ){
ds <- FR_NG_FCY1_plm
}else if(FCY == "6-9 t/acre" ){
ds <- FR_NG_FCY3_plm
}else if(FCY == "9-12 t/acre" ){
ds <- FR_NG_FCY4_plm
}else if(FCY == ">12 t/acre" ){
ds <- FR_NG_FCY5_plm
}
}
#######################################################################################################
#Subset by state for every filter option presented by users
Oyo <- droplevels(ds[ds$STATE == "Oyo", ])
Oyolabel <- data.frame(state= c("Oyo"), lon=c(3.3), lat=c(9))
Ogun <- droplevels(ds[ds$STATE == "Ogun", ])
Ogunlabel <- data.frame(state= c("Ogun"), lon=c(3.4), lat=c(7.65))
Kogi <- droplevels(ds[ds$STATE == "Kogi", ])
Kogilabel <- data.frame(state= c("Kogi"), lon=c(6.63), lat=c(8.56))
Kwara <- droplevels(ds[ds$STATE %in% c("Kwara"), ])
Kwaralabel <- data.frame(state= c( "Kwara"), lon=c(4.9), lat=c(9.5))
Taraba <- droplevels(ds[ds$STATE %in% c("Taraba"), ])
Tarabalabel <- data.frame(state= c( "Taraba"), lon=c(10.2), lat=c(9.05))
CrossRiver <- droplevels(ds[ds$STATE %in% c("Cross River"), ])
Crossriver_label <- data.frame(state= c("Cross River"), lon=c(8), lat=c(8.2) )
Benue <- droplevels(ds[ds$STATE %in% c("Benue"), ])
Benue_label <- data.frame(state= c("Benue"), lon=c(9.5), lat=c(8))
Edo <- droplevels(ds[ds$STATE %in% c("Edo"), ])
Edolabel <- data.frame(state= c("Edo"), lon=c(5.3), lat=c(7))
Delta <- droplevels(ds[ds$STATE %in% c("Delta"), ])
Deltalabel <- data.frame(state= c("Delta"), lon=c(6), lat=c(5))
Akwa_Ibom <- droplevels(ds[ds$STATE %in% c("Akwa Ibom"), ])
Akwa_Ibomlabel <- data.frame(state= c( "Akwa Ibom"), lon=c(8), lat=c(5.45))
Imo <- droplevels(ds[ds$STATE %in% c("Imo"), ])
Imolabel <- data.frame(state= c( "Imo"), lon=c(6.9), lat=c(5.9))
Abia <- droplevels(ds[ds$STATE %in% c("Abia"), ])
Abialabel <- data.frame(state= c( "Abia"), lon=c(7.7), lat=c(5.9))
Ondo <- droplevels(ds[ds$STATE %in% c("Ondo"), ])
Ondolabel <- data.frame(state= c( "Ondo"), lon=c(5.3), lat=c(6.6))
Ekiti <- droplevels(ds[ds$STATE %in% c("Ekiti"), ])
Ekitilabel <- data.frame(state= c( "Ekiti"), lon=c(5.3), lat=c(8.1))
Osun <- droplevels(ds[ds$STATE == "Osun", ])
Osunlabel <- data.frame(state= c("Osun"), lon=c(4.2), lat=c(8.05))
Anambra <- droplevels(ds[ds$STATE %in% c("Anambra"), ])
Anambralabel <- data.frame(state= c( "Anambra"), lon=c(7.15), lat=c(6.45))
Ebonyi <- droplevels(ds[ds$STATE %in% c("Ebonyi"), ])
Ebonyilabel <- data.frame(state= c( "Ebonyi"), lon=c(7.83), lat=c(6.67))
Anambra <- droplevels(ds[ds$STATE %in% c("Anambra"), ])
Anambra_label <- data.frame(state= c("Anambra"), lon=c(6.7), lat=c(5.9))
Enugu <- droplevels(ds[ds$STATE %in% c("Enugu"), ])
Enugulabel <- data.frame(state= c("Enugu"), lon=c(7), lat=c(7.1))
Ebonyi <- droplevels(ds[ds$STATE %in% c("Ebonyi"), ])
Ebonyilabel <- data.frame(state= c("Ebonyi"), lon=c(8.25), lat=c(6.9))
#specify other key values for getting recommendations
if(lgaGroups == "Benue"){
cities <- c("Makurdi")
LGApoints <- Benue
stateLabel <- Benue_label
textangle <- 0
couple = "One"
}else if(lgaGroups =="Cross River"){
cities <- c("Calabar")
LGApoints <- Benue
stateLabel <- Benue_label
textangle <- 0
couple = "One"
}else if(lgaGroups =="Enugu"){
cities <- c("Enugu")
LGApoints <- Enugu
stateLabel <- Enugulabel
textangle <- 0
couple = "One"
}else if(lgaGroups =="Delta"){
cities = c("Asaba")
LGApoints <- Delta
stateLabel <- Deltalabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Edo"){
cities = c("Benin City")
LGApoints <- Edo
stateLabel <- Edolabel
textangle <- 0
couple <- "One"
} else if(lgaGroups == "Imo"){
cities = c("Owerri")
LGApoints <- Imo
stateLabel <- Imolabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Abia"){
cities = c("Umuahia")
LGApoints <- Abia
stateLabel <- Abialabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Akwa Ibom"){
cities = c("Uyo")
LGApoints <- Akwa_Ibom
stateLabel <- Akwa_Ibomlabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Ekiti"){
cities = c("Ado Ekiti")
LGApoints <- Ekiti
stateLabel <- Ekitilabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Ondo"){
cities = c("Akure")
LGApoints <- Ondo
stateLabel <- Ondolabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Osun"){
cities = c("Osogbo")
LGApoints <- Osun
stateLabel <- Osunlabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Anambra"){
cities = c("Awka")
LGApoints <- Anambra
stateLabel <- Anambralabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Ebonyi"){
cities = c("Ebonyi")
LGApoints <- Ebonyi
stateLabel <- Ebonyilabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Taraba"){
cities = "Taraba"
LGApoints <- Taraba
stateLabel <- Tarabalabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Kogi"){
cities = "Kogi"
LGApoints <- Taraba
stateLabel <- Tarabalabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Kwara"){
cities = "Kwara"
LGApoints <- Kwara
stateLabel <- Kwaralabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Oyo"){
cities = "Oyo"
LGApoints <- Oyo
stateLabel <- Oyolabel
textangle <- 0
couple <- "One"
}else if(lgaGroups == "Ogun"){
cities = "Abeokuta"
LGApoints == Ogun
stateLabel <- Ogunlabel
textangle <- 0
couple <- "One"
}
#filter by month and couple and state
#plantMonth = "January"
plotData <- droplevels(LGApoints[LGApoints$plm == plantMonth, ])
if(couple == "Two"){
lgaGroups <- c(strsplit(lgaGroups, "_")[[1]][1], strsplit(lgaGroups, "_")[[1]][2])
}
if(couple == "Three"){
lgaGroups <- c(strsplit(lgaGroups, "_")[[1]][1], strsplit(lgaGroups, "_")[[1]][2], strsplit(lgaGroups, "_")[[1]][3])
}
plotData <- droplevels(plotData[plotData$STATE %in% lgaGroups, ])
#incorporate GIS layers
AOI <- lgaGroups
AOIMapS <- subset(boundaryNG, NAME_1 %in% AOI )
AOIMap <- subset(ngstate, NAME_1 %in% AOI )
AOIMap <- AOIMap[,c("NAME_1", "NAME_2")]
LGAnames <- as.data.frame(AOIMap)
LGAnames <- cbind(LGAnames, coordinates(AOIMap))
colnames(LGAnames) <- c("STATE","LGA","long","lat" )
LGAnames <- LGAnames[!LGAnames$LGA %in% c("IbadanNorth-West","IbadanNorth-East","IbadanSouth-West", "IbadanSouth-East"),]
LGAnames$LGA <- gsub("Egbado /", "", LGAnames$LGA )
crop_ngstate <- subset(ngstate, NAME_1 %in% AOI )
towns <- as.data.frame(TownsNG)
towns <- towns[towns$name %in% cities & towns$fclass %in% c("town", "city"),]
crop_RiversNG <- crop(RiversNG, extent(crop_ngstate))
crop_RiversNG <- crop_RiversNG[crop_RiversNG$fclass == "river", ]
LGAaverage <- ddply(plotData, .(LGA, STATE), summarize,
LGAUrea = round(mean(rateUrea), digits=0),
LGANPK151515 = round(mean(rateNPK151515), digits=0),
LGAdY = round(mean(respY), digits=0))
dss <- LGAaverage
dss$LGAUrea <- dss$LGAUrea / 2.47105
dss$LGANPK151515 <- dss$LGANPK151515 / 2.47105
dss$LGAdY <- dss$LGAdY / 2.47105
if(unit == 'acre'){
LGAaverage <- dss
}
plotData <- merge(plotData, LGAaverage, by=c("LGA", "STATE"))
if(unit == "ha"){
plotData$Urea <- round(plotData$LGAUrea/25)*25
plotData$NPK15_15_15 <- round(plotData$LGANPK151515/50)*50
plotData$dY <- round(plotData$LGAdY/2)*2
}else{
plotData$Urea <- round(plotData$LGAUrea/10)*10
plotData$NPK15_15_15 <- round(plotData$LGANPK151515/20)*20
plotData$dY <- round(plotData$LGAdY/1)*1
}
#csv tables naming
fileNameCsv <- paste("tables", ".csv", sep="")
AOIMap2 <- merge(AOIMap, unique(plotData[, c("LGA", "Urea", "NPK15_15_15","dY", "LGAdY")]),by.x="NAME_2" ,by.y="LGA")
AOIMap2$month <- plantMonth
AOIMap2 <- AOIMap2[!is.na(AOIMap2$Urea), ]
plotData$month <- plantMonth
#generate table
Currency <- "Naira"
tt <- unique(as.data.frame(plotData[, c("STATE","LGA", "Urea", "NPK15_15_15", "LGAdY", "month")]))
tt$LGAdY <- round(tt$LGAdY, digits = 1)
tt <- tt[order(tt$STATE, tt$LGA, tt$month), ]
tt2 <- dplyr::select(tt, c(STATE, LGA, Urea, NPK15_15_15,LGAdY))
colnames(tt2) <- c("State","LGA", "Urea (kg/ha)", "NPK 15:15:15 (kg/ha)", "Expected yield increase (t)")
#subset by cost information in a reactive environment
if(costs == "No"){
output$tabletext_naira <- renderText({
paste("AKILIMO advice for planting in ", plantMonth, ". Your current yield is ", FCY, ".", sep="")
})
output$mytable <- renderDT({tt2},
rownames = FALSE,
extensions = c('Buttons','FixedColumns'),
options = list(dom = 'Bfrtip',
pageLength = nrow(tt2),
initComplete = DT::JS(
"function(settings, json) {",
"$(this.api().table().header()).css({'background-color': 'black', 'color': '#fff'});",
"}"),
buttons = list(
list(extend = 'excel',
filename = paste('AKILIMO advice', '_', lgaGroups2, '_', plantMonth),
title = paste("AKILIMO advice for planting in ", plantMonth, ". Your current yield is between ", FCY, ".", sep="")),
list(extend = 'pdf',
filename = paste('AKILIMO advice', '_', lgaGroups2, '_', plantMonth),
title = paste("AKILIMO advice for planting in ", plantMonth, ". Your current yield is between ", FCY, ".", sep=""),
header = TRUE)