Add files via upload

Transport Shiny.R

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+library(shiny)
+library(shinythemes)
+
+ui <- fluidPage(
+ theme=shinytheme('cosmo'),
+ titlePanel("Data Processing App"),
+ sidebarLayout(
+ sidebarPanel(
+ # Explanatory text using HTML
+ HTML("<p>This app calculates the distance moved for each subsequent survey date and the total distance moved in meters.<p>
+ <p>Store all data in one folder and enter the path to this folder. Do not include quotation marks in the path name.<p>
+ <p>Files may be a combination of .csv or .xlsx. A .shp centerline must be included as well.<p>
+ <p>Specify the CRS value used to record tracer locations and ensure it matches the projection of the stream centerline. The default in WGS84 UTM Zone 18N.</p>
+ <p> Dates must begin with MM/DD/YY format but may include further time specifications.<p>
+ <p>After processing, results in the table can be downloaded.</p>"),
+ textInput("folder_path", "Enter Folder Path:", value = ""),
+ textInput("crs", "Enter CRS:", value = "32618"),
+ actionButton("process_data", "Process Data"),
+ downloadButton("download_transport", "Download Transport Table") # Add download button
+ ),
+ mainPanel(
+ tabsetPanel(
+ # Tab for displaying the output table
+ tabPanel("Output Table", tableOutput("table")),
+
+ # Tab for displaying the plot
+ tabPanel("Plot", plotlyOutput("plot"))
+ )
+ )
+ )
+)
+
+server <- function(input, output) {
+ transport_data <- reactiveVal(NULL)
+ plotly_obj <- reactiveVal(NULL)
+
+ observeEvent(input$process_data, {
+ # Get user inputs
+ folder_path <- input$folder_path
+ crs_string <- input$crs
+
+ library(data.table)
+ library(tools)
+ library(openxlsx)
+ library(sf)
+ library(lubridate)
+ library(ggplot2)
+ library(plotly)
+ library(viridis)
+
+ # Function to list files in folder
+ list_full = function(folder_path){
+ csv_files <<- list.files(folder_path, pattern='csv', full.names=T)
+ xlsx_files <<- list.files(folder_path, pattern='xlsx', full.names=T)
+ shapefiles <<- list.files(folder_path, pattern='shp', full.names=T)
+ }
+
+ #Call function to list files
+ list_full(folder_path)
+
+ # Function to read files in a folder
+ files = lapply(csv_files, fread)
+ Data = rbindlist(files)
+
+ # Include Excel files
+ if (length(xlsx_files)>0) {
+ excel = lapply(xlsx_files, read.xlsx)
+ excel = setDT(excel)
+ if (typeof(excel) == 'list') {
+ excel = rbindlist(excel)
+ Data = rbind(Data,excel)
+ }
+ }
+
+ # Test formatting
+ date_check = function(data) {
+ dates = as.character(data[,(substr(GPSTime,start=1,stop=8))])
+ pattern = "^\\d{2}/\\d{2}/\\d{2}$"
+ results = ifelse(sapply(dates, grepl, pattern=pattern), 0, 1)
+ if(c(1)%in%results){
+ stop("Error: At least one date is not in %m/%d/%y format.")}
+ }
+
+ date_check(Data)
+
+ # Read shapefile
+ centerline = read_sf(shapefiles[endsWith(shapefiles,'shp')])
+ centerline = st_set_crs(centerline, crs_string)
+
+ # Clean Data
+ Data = Data[,c('GPSTime','Latitude','Longitude','Northing','Easting','Comment')]
+
+ # Determine repeat observations
+ Data = Data[,count:=.N,by='Comment']
+
+ # Function to get Survey Dates from column with date and time
+ survey_dates = function (table) {
+ surveys = list((strsplit(Data$GPSTime,' ')))
+ surveys = rbindlist(surveys)
+ surveys = transpose(surveys)
+ surveys <<- unique(surveys$V1)
+ }
+
+ # Call survey date function
+ survey_dates(Data)
+
+ # Create sf object of Data
+ sf_Data = st_as_sf(Data,coords = c('Easting','Northing'),crs=crs_string)
+
+ # Snap tracers to centerline
+ Data = Data[,Location:=(st_snap(sf_Data$geometry,centerline,2))]
+
+ # Adjust table to output format
+ adjust_table = function(data) {
+ Movement = copy(data)
+ Movement = Movement[,Date:=(substr(GPSTime,start=1,stop=8))]
+ Movement = Movement[,c('Comment','Date','Location','count')]
+ Movement = unique(Movement,by=c('Comment','Date'))
+ Movement = dcast(Movement,formula = Comment ~ Date, value.var = 'Location', fun.aggregate = NULL)
+ date_order = order(as.Date(surveys,format="%m/%d/%y"))
+ surveys = surveys[date_order]
+ setcolorder(Movement,c('Comment',surveys))
+ Movement <<- Movement
+ }
+
+ adjust_table(Data)
+
+ # Define a function to calculate distances
+ distance <- function(data) {
+ Transport <- data.table()
+ comment <- data[['Comment']]
+ data <- data[, !'Comment', with = FALSE]
+ data <- st_as_sf(data)
+
+ num_cols <- ncol(data)
+
+ for (i in 1:(num_cols - 1)) {
+ for (j in (i + 1):num_cols) {
+ col1 <- data[[i]]
+ col2 <- data[[j]]
+ new_col_name <- paste0(names(data)[i], "_", names(data)[j], "_Distance")
+
+ # Initialize an empty vector to store distances
+ distances <- numeric(length(col1))
+
+ # Calculate distances for all pairs of values in col1 and col2
+ for (k in 1:length(col1)) {
+ distances[k] <- ifelse(st_is_empty(col1[k]) | st_is_empty(col2[k]), NA_real_, st_distance(col1[k], col2[k]))
+ }
+
+ # Add the distances to the Transport table
+ Transport[, (new_col_name) := distances]
+ }
+ }
+
+ # Combine comment and Transport into a single table
+ Transport <<- cbind(comment, Transport)
+ }
+ distance(Movement)
+
+ Transport = Transport[,TotalDistance:=rowSums(Transport[,2:16],na.rm=T)]
+
+ transport_data(Transport)
+
+ # Create the ggplot object
+ river_map <- ggplot() +
+ geom_sf(data = centerline) +
+ geom_sf(data = sf_Data, aes(color = as.character(year(as.Date(substr(GPSTime, start = 1, stop = 8), format = '%m/%d/%y'))))) +
+ scale_color_viridis(discrete = TRUE, option = "D") +
+ labs(x = 'Easting (m)', y = 'Northing (m)', color = 'Year') +
+ theme_bw()+theme(axis.text.x = element_text(angle=45, vjust=1, hjust=1))
+
+ # Convert ggplot to a Plotly plot
+ plotly_obj(ggplotly(river_map, width = 800, height = 600))
+
+ })
+ # For rendering a table, you can use:
+ output$table <- renderTable({
+ transport_data()
+ })
+
+ # Render the Plotly plot
+ output$plot <- renderPlotly({
+ plotly_obj()
+ })
+
+ # Define a download handler for the download button
+ output$download_transport <- downloadHandler(
+ filename = function() {
+ paste("Transport_Table_", Sys.Date(), ".csv", sep = "")
+ },
+ content = function(file) {
+ write.csv(transport_data(), file)
+ }
+ )
+}
+
+shinyApp(ui, server)