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syedmfuadsyedmfuad
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Diff for: ‎rshiny.R

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library(shiny)
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library(readr)
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library(raster)
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# Define the UI
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ui <- fluidPage(
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titlePanel("Crop and Country Selection"),
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sidebarLayout(
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sidebarPanel(
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selectInput("crop", "Select Crop:", choices = c("WHEA", "RICE")),
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selectInput("country", "Select Country:", choices = c("NGA", "CMR")),
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selectInput("agricultural_output", "Select Output Type:", choices = c("PRODUCTIVITY", "YIELD")),
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br(),
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downloadButton("download_csv", "Download CSV")
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),
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mainPanel(
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textOutput("selected_options")
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)
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)
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)
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# Define the server logic
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server <- function(input, output) {
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# Display selected options
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output$selected_options <- renderText({
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paste("Selected Crop:", input$crop, "\n",
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"Selected Country:", input$country, "\n",
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"Selected Output Type:", input$agricultural_output)
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})
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# Create a reactive data frame
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data <- reactive({
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bd <- raster::getData('GADM', country=input$country, level=1)
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ad <- length(bd)
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thetahat=matrix(NA,ad,1)
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names=matrix(NA,ad,2)
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#x <- paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_prod.geotiff/spam2010V2r0_global_P_", input$crop, "_A.tif")
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x <- ifelse(input$agricultural_output == "PRODUCTIVITY", paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_prod.geotiff/spam2010V2r0_global_P_", input$crop, "_A.tif"),
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ifelse(input$agricultural_output == "YIELD", paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_yield.geotiff/spam2010V2r0_global_Y_", input$crop, "_A.tif"), ""))
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raster1 <- raster(here::here(x)) # load file
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# apply function
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bd_raster <- crop(raster1, extent(bd))
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#plot(bd_raster)
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bd_raster2 <- mask(bd_raster, bd)
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#plot(bd_raster2)
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#plot(bd, add=TRUE)
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d <- extract(x=bd_raster2, y=bd, fun=mean, na.rm=TRUE, sp=T)
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thetahat[,1]=d@data[,11] #was 13 before
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names[,1]=d@data[,2]
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names[,2]=d@data[,4]
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mat <- cbind(names, thetahat)
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data <- as.data.frame(mat)
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})
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# Download the data as a CSV file
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output$download_csv <- downloadHandler(
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filename = function() {
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paste("crop_country_data", Sys.Date(), ".csv", sep = "")
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},
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content = function(file) {
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write_csv(data(), file)
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}
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)
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}
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# Run the application
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shinyApp(ui = ui, server = server)

Diff for: ‎rshiny2.R

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library(shiny)
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library(readr)
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library(raster)
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library(DT)
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# Define the UI
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ui <- fluidPage(
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titlePanel("Crop and Country Selection"),
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sidebarLayout(
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sidebarPanel(
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selectInput("crop", "Select Crop:", choices = c("WHEA", "RICE", "MAIZ", "BARL", "PMIL", "SMIL")),
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selectInput("country", "Select Country:", choices = c("NGA", "CMR", "TZA", "COD", "AGO", "COG")),
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selectInput("agricultural_output", "Select Output Type:", choices = c("PRODUCTIVITY", "YIELD", "HARV_AREA", "PHYS_AREA", "VAL_PROD")),
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br(),
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downloadButton("download_csv", "Download CSV"),
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actionButton("generate_plot", "Generate Raster Plot"),
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plotOutput("raster_plot")
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),
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mainPanel(
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textOutput("selected_options"),
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dataTableOutput("data_table")
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)
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)
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)
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# Define the server logic
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server <- function(input, output) {
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# Display selected options
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output$selected_options <- renderText({
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paste("Selected Crop:", input$crop, "\n",
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"Selected Country:", input$country, "\n",
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"Selected Output Type:", input$agricultural_output)
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})
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# Create a reactive data frame
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data <- reactive({
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bd <- raster::getData('GADM', country = input$country, level = 1)
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ad <- length(bd)
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thetahat <- matrix(NA, ad, 1)
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names <- matrix(NA, ad, 2)
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x <- ifelse(input$agricultural_output == "PRODUCTIVITY",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_prod.geotiff/spam2010V2r0_global_P_", input$crop, "_A.tif"),
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ifelse(input$agricultural_output == "YIELD",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_yield.geotiff/spam2010V2r0_global_Y_", input$crop, "_A.tif"),
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ifelse(input$agricultural_output == "HARV_AREA",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_harv_area.geotiff/spam2010V2r0_global_H_", input$crop, "_A.tif"),
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ifelse(input$agricultural_output == "PHYS_AREA",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_phys_area.geotiff/spam2010V2r0_global_A_", input$crop, "_A.tif"), ""))))
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raster1 <- raster(here::here(x))
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bd_raster <- crop(raster1, extent(bd))
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bd_raster2 <- mask(bd_raster, bd)
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d <- extract(x = bd_raster2, y = bd, fun = mean, na.rm = TRUE, sp = TRUE)
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thetahat[, 1] <- d@data[, 11] #was 13 before
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names[, 1] <- d@data[, 2]
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names[, 2] <- d@data[, 4]
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mat <- cbind(names, thetahat)
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data <- as.data.frame(mat)
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data
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})
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# Render the data table
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output$data_table <- renderDataTable({
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data()
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})
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# Render the raster plot
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output$raster_plot <- renderPlot({
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bd <- raster::getData('GADM', country = input$country, level = 1)
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x <- ifelse(input$agricultural_output == "PRODUCTIVITY",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_prod.geotiff/spam2010V2r0_global_P_", input$crop, "_A.tif"),
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ifelse(input$agricultural_output == "YIELD",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_yield.geotiff/spam2010V2r0_global_Y_", input$crop, "_A.tif"),
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ifelse(input$agricultural_output == "HARV_AREA",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_harv_area.geotiff/spam2010V2r0_global_H_", input$crop, "_A.tif"),
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ifelse(input$agricultural_output == "PHYS_AREA",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_phys_area.geotiff/spam2010V2r0_global_A_", input$crop, "_A.tif"), ""))))
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raster1 <- raster(here::here(x))
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bd_raster <- crop(raster1, extent(bd))
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bd_raster2 <- mask(bd_raster, bd)
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if (input$generate_plot > 0) {
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plot(bd)
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plot(bd_raster2, add = TRUE)
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}
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})
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# Download the data as a CSV file
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output$download_csv <- downloadHandler(
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filename = function() {
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paste("crop_country_data", Sys.Date(), ".csv", sep = "")
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},
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content = function(file) {
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write_csv(data(), file)
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}
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)
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}
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# Run the application
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shinyApp(ui = ui, server = server)

Diff for: ‎rshiny3.R

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library(shiny)
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library(dplyr)
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library(raster)
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# Define the UI
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ui <- fluidPage(
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titlePanel("Crop and Country Selection"),
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sidebarLayout(
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sidebarPanel(
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selectizeInput("countries", "Add Countries:", choices = c("NGA", "CMR", "TZA", "COD", "AGO", "COG"), multiple = TRUE),
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conditionalPanel(
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condition = "input.countries.length > 0",
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selectizeInput("crop", "Select Crop:", choices = c("WHEA", "RICE", "MAIZ", "BARL", "PMIL", "SMIL"), multiple = TRUE),
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selectizeInput("output_type", "Select Output Type:", choices = c("PRODUCTIVITY", "YIELD", "HARV_AREA"), multiple = TRUE)
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),
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br(),
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downloadButton("download_csv", "Download CSV")
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),
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mainPanel(
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dataTableOutput("result_table")
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)
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)
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)
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# Define the server logic
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server <- function(input, output) {
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# Function to extract data for a single country and crop
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extractData <- function(country, crop, output_type) {
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bd <- raster::getData('GADM', country = country, level = 1)
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ad <- length(bd)
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thetahat <- vector("numeric", ad)
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names1 <- vector("character", ad)
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names2 <- vector("character", ad)
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x <- ifelse(output_type == "PRODUCTIVITY",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_prod.geotiff/spam2010V2r0_global_P_", crop, "_A.tif"),
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ifelse(output_type == "YIELD",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_yield.geotiff/spam2010V2r0_global_Y_", crop, "_A.tif"),
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ifelse(output_type == "HARV_AREA",
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paste0("C:/Users/syedm/Desktop/soil/spam2010v2r0_global_harv_area.geotiff/spam2010V2r0_global_H_", crop, "_A.tif"), "")))
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raster1 <- raster(here::here(x))
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bd_raster <- crop(raster1, extent(bd))
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bd_raster2 <- mask(bd_raster, bd)
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d <- extract(x = bd_raster2, y = bd, fun = mean, na.rm = TRUE, sp = TRUE)
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thetahat <- d@data[, 11] # was 13 before
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names1 <- d@data[, 2]
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names2 <- d@data[, 4]
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data <- data.frame(Country = rep(country, ad),
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Crop = rep(crop, ad),
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stringsAsFactors = FALSE)
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data$District <- names2
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data[[output_type]] <- thetahat
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data
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}
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# Create a reactive data frame
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result <- reactive({
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countries <- input$countries
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crops <- input$crop
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output_types <- input$output_type
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data <- data.frame(Country = character(),
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Crop = character(),
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stringsAsFactors = FALSE)
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for (country in countries) {
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for (crop in crops) {
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row <- data.frame(Country = country,
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Crop = crop,
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stringsAsFactors = FALSE)
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for (output_type in output_types) {
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extracted_data <- extractData(country, crop, output_type)
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col_name <- output_type
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row <- do.call("rbind", replicate(n=nrow(extracted_data), row, simplify = FALSE)) #added this myself
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row <- row[1:nrow(extracted_data),]
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row$District <- extracted_data$District
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row[[col_name]] <- extracted_data[[col_name]]
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row %>% relocate(District, .after=Country)
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}
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data <- rbind(data, row)
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}
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}
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data
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})
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# Render the result table
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output$result_table <- renderDataTable({
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result()
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})
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# Download the data as a CSV file
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output$download_csv <- downloadHandler(
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filename = function() {
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paste("crop_country_data", Sys.Date(), ".csv", sep = "")
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},
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content = function(file) {
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write.csv(result(), file, row.names = FALSE)
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}
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)
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}
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# Run the application
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shinyApp(ui = ui, server = server)

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