Add files via upload

Author: syedmfuad

Diff for: app.R

@@ -0,0 +1,156 @@
+library(shiny)
+library(dplyr)
+library(raster)
+library(googledrive)
+
+# Define the UI
+ui <- fluidPage(
+  titlePanel("Spatial Production Crop, Country, and Output Selection"),
+  sidebarLayout(
+    sidebarPanel(
+      selectizeInput("countries", "Add Countries:", choices = c("NGA", "CMR", "TZA", "COD"), multiple = TRUE),
+      conditionalPanel(
+        condition = "input.countries.length > 0",
+        selectizeInput("crop", "Select Crop:", choices = c("WHEA", "RICE", "MAIZ", "BARL"), multiple = TRUE),
+        selectizeInput("output_type", "Select Output Type:", choices = c("PRODUCTIVITY", "YIELD"), multiple = TRUE)
+      ),
+      br(),
+      downloadButton("download_csv", "Download CSV")
+    ),
+    mainPanel(
+      dataTableOutput("result_table")
+    )
+  )
+)
+
+# Define the server logic
+server <- function(input, output) {
+  
+  
+  
+  read_raster_from_drive <- function(folder_url, crop_chosen, output) {
+    
+    #drive_auth(cache = ".secrets")
+    drive_auth(cache = ".secrets", email = TRUE, use_oob = TRUE)
+    
+    folder <- drive_get(as_id(folder_url))
+    files <- drive_ls(folder$id)
+    
+    file_name <- ifelse(output == "PRODUCTIVITY", 
+                        paste0("spam2017V2r1_SSA_P_", crop_chosen, "_A.tif"),
+                        ifelse(output == "YIELD", 
+                               paste0("spam2017V2r1_SSA_Y_", crop_chosen, "_A.tif"), ""))
+    
+    
+    #file_name <- paste0("spam2017V2r1_SSA_P_", crop_chosen, "_A.tif")
+    
+    file <- files[which(files$name == file_name),]
+    
+    if (length(file) == 0) {
+      print("File not found.")
+    } else {
+      
+      temp_file <- tempfile(fileext = ".tif")
+      x <- drive_download(as_id(file$id), path = temp_file)
+      
+      raster1 <- raster(here::here(x$local_path))
+      
+      return(raster1)
+      
+      file.remove(temp_file)
+      
+    }
+  }
+  
+  
+  
+  
+  # Function to extract data for a single country and crop
+  extractData <- function(country, crop, output_type) {
+    bd <- raster::getData('GADM', country = country, level = 1)
+    ad <- length(bd)
+    
+    thetahat <- vector("numeric", ad)
+    names1 <- vector("character", ad)
+    names2 <- vector("character", ad)
+    
+    folder_url <- ifelse(output_type == "PRODUCTIVITY", "https://drive.google.com/drive/folders/1FqeBF-y4iMMHIxCEybXAlwqPJ7KSJkd5",
+                         ifelse(output_type == "YIELD", "https://drive.google.com/drive/folders/11imEWGPvGsesshkPuwj3s7_lWHUiPleY", ""))
+    
+    raster1 <- read_raster_from_drive(folder_url=folder_url, crop_chosen=crop, output=output_type)
+    
+    #raster1 <- raster(here::here(x))
+    bd_raster <- crop(raster1, extent(bd))
+    bd_raster2 <- mask(bd_raster, bd)
+    
+    d <- extract(x = bd_raster2, y = bd, fun = mean, na.rm = TRUE, sp = TRUE)
+    thetahat <- d@data[, 11] # was 13 before
+    names1 <- d@data[, 2]
+    names2 <- d@data[, 4]
+    
+    data <- data.frame(Country = rep(country, ad),
+                       Crop = rep(crop, ad),
+                       stringsAsFactors = FALSE)
+    
+    data$District <- names2
+    data[[output_type]] <- thetahat
+    
+    data
+  }
+  
+  # Create a reactive data frame
+  result <- reactive({
+    countries <- input$countries
+    crops <- input$crop
+    output_types <- input$output_type
+    
+    data <- data.frame(Country = character(),
+                       Crop = character(),
+                       stringsAsFactors = FALSE)
+    
+    for (country in countries) {
+      for (crop in crops) {
+        row <- data.frame(Country = country,
+                          Crop = crop,
+                          stringsAsFactors = FALSE)
+        
+        for (output_type in output_types) {
+          extracted_data <- extractData(country, crop, output_type)
+          col_name <- output_type
+          
+          row <- do.call("rbind", replicate(n=nrow(extracted_data), row, simplify = FALSE)) #added this myself
+          
+          row <- row[1:nrow(extracted_data),]
+          
+          row$District <- extracted_data$District
+          row[[col_name]] <- extracted_data[[col_name]]
+          
+          row %>% relocate(District, .after=Country)
+          
+        }
+        
+        data <- rbind(data, row)
+      }
+    }
+    
+    data
+  })
+  
+  # Render the result table
+  output$result_table <- renderDataTable({
+    result()
+  })
+  
+  # Download the data as a CSV file
+  output$download_csv <- downloadHandler(
+    filename = function() {
+      paste("crop_country_data", Sys.Date(), ".csv", sep = "")
+    },
+    content = function(file) {
+      write.csv(result(), file, row.names = FALSE)
+    }
+  )
+}
+
+# Run the application
+shinyApp(ui = ui, server = server)