♻️ refactor app.Rmd
This commit is contained in:
lukasadrion
248
src/app.Rmd
248
src/app.Rmd
@@ -12,6 +12,7 @@ library(httr)
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library(jsonlite)
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library(trajr)
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# UI Definition
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ui <- fluidPage(
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titlePanel("Flight Trajectory Analysis - GUI"),
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@@ -214,20 +215,7 @@ server <- function(input, output, session) {
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rv$current_route <- route_df
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# Create trajectory object
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lat_ref <- route_df$lat[1]
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lon_ref <- route_df$lon[1]
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meters_per_deg_lat <- 111320
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meters_per_deg_lon <- 111320 * cos(lat_ref * pi / 180)
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x_meters <- (route_df$lon - lon_ref) * meters_per_deg_lon
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y_meters <- (route_df$lat - lat_ref) * meters_per_deg_lat
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time_seconds <- route_df$time - route_df$time[1]
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rv$current_trj <- TrajFromCoords(
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data.frame(x = x_meters, y = y_meters, time = time_seconds),
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xCol = "x", yCol = "y", timeCol = "time"
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)
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rv$current_trj <- createTrajFromRoute(route_df)
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status(paste("Successfully analyzed", icao24, "with", nrow(route_df), "points"))
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# Switch to analysis tab
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@@ -266,41 +254,8 @@ server <- function(input, output, session) {
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trj <- rv$current_trj
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duration <- TrajDuration(trj)
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path_length <- TrajLength(trj)
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diffusion_distance <- TrajDistance(trj)
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straightness <- TrajStraightness(trj)
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mean_velocity <- path_length / duration
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fractal_dim <- tryCatch({
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min_step <- path_length / 100
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max_step <- path_length / 2
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if (min_step > 0 && max_step > min_step) {
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step_sizes <- exp(seq(log(min_step), log(max_step), length.out = 10))
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TrajFractalDimension(trj, stepSizes = step_sizes)
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} else {
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NA
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}
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}, error = function(e) NA)
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data.frame(
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Parameter = c(
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"Duration (s)", "Duration (min)",
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"Path Length (m)", "Path Length (km)",
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"Diffusion Distance (m)", "Diffusion Distance (km)",
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"Straightness Index",
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"Mean Velocity (m/s)", "Mean Velocity (km/h)",
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"Fractal Dimension"
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),
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Value = c(
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round(duration, 2), round(duration / 60, 2),
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round(path_length, 2), round(path_length / 1000, 2),
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round(diffusion_distance, 2), round(diffusion_distance / 1000, 2),
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round(straightness, 4),
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round(mean_velocity, 2), round(mean_velocity * 3.6, 2),
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round(fractal_dim, 4)
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)
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)
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data.frame <- calculateRouteCharacteristics(trj)
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data.frame
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})
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# Batch analysis
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@@ -337,19 +292,7 @@ server <- function(input, output, session) {
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route_df <- as.data.frame(track_data$path)
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colnames(route_df) <- c("time", "lat", "lon", "alt", "heading", "on_ground")
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lat_ref <- route_df$lat[1]
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lon_ref <- route_df$lon[1]
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meters_per_deg_lat <- 111320
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meters_per_deg_lon <- 111320 * cos(lat_ref * pi / 180)
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x_meters <- (route_df$lon - lon_ref) * meters_per_deg_lon
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y_meters <- (route_df$lat - lat_ref) * meters_per_deg_lat
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time_seconds <- route_df$time - route_df$time[1]
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trj <- TrajFromCoords(
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data.frame(x = x_meters, y = y_meters, time = time_seconds),
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xCol = "x", yCol = "y", timeCol = "time"
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)
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trj <- createTrajFromRoute(route_df)
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duration <- TrajDuration(trj)
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path_length <- TrajLength(trj)
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@@ -402,19 +345,55 @@ server <- function(input, output, session) {
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# Statistics summary table
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output$stats_summary_table <- renderTable({
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req(rv$trajectory_stats_df)
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calculateStatsSummary(rv$trajectory_stats_df)
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})
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params <- c("diffusion_distance_km", "straightness", "duration_min",
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"mean_velocity_kmh", "fractal_dimension")
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labels <- c("Diffusion Distance (km)", "Straightness", "Duration (min)",
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# Boxplots
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output$boxplots <- renderPlot({
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req(rv$trajectory_stats_df)
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createBoxplots(rv$trajectory_stats_df)
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})
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# Density plots
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output$density_plots <- renderPlot({
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req(rv$trajectory_stats_df)
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createDensityPlots(rv$trajectory_stats_df)
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})
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# Histograms
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output$histograms <- renderPlot({
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req(rv$trajectory_stats_df)
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createHistograms(rv$trajectory_stats_df)
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})
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# Interpretation text
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output$interpretation_text <- renderText({
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req(rv$trajectory_stats_df)
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generateInterpretation(rv$trajectory_stats_df)
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})
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}
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# Helper function to get parameter names and labels
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getTrajectoryParams <- function() {
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list(
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params = c("diffusion_distance_km", "straightness", "duration_min",
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"mean_velocity_kmh", "fractal_dimension"),
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labels = c("Diffusion Distance (km)", "Straightness", "Duration (min)",
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"Mean Velocity (km/h)", "Fractal Dimension")
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)
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}
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stats_list <- lapply(seq_along(params), function(i) {
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x <- rv$trajectory_stats_df[[params[i]]]
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# Calculate statistics summary table
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calculateStatsSummary <- function(trajectory_stats_df) {
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p <- getTrajectoryParams()
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stats_list <- lapply(seq_along(p$params), function(i) {
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x <- trajectory_stats_df[[p$params[i]]]
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x <- x[!is.na(x)]
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if (length(x) < 2) return(NULL)
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data.frame(
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Parameter = labels[i],
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Parameter = p$labels[i],
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N = length(x),
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Mean = round(mean(x), 4),
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Variance = round(var(x), 4),
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@@ -426,77 +405,60 @@ server <- function(input, output, session) {
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})
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do.call(rbind, stats_list[!sapply(stats_list, is.null)])
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})
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}
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# Boxplots
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output$boxplots <- renderPlot({
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req(rv$trajectory_stats_df)
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params <- c("diffusion_distance_km", "straightness", "duration_min",
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"mean_velocity_kmh", "fractal_dimension")
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labels <- c("Diffusion Distance (km)", "Straightness", "Duration (min)",
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"Mean Velocity (km/h)", "Fractal Dimension")
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# Create boxplots for trajectory statistics
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createBoxplots <- function(trajectory_stats_df) {
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p <- getTrajectoryParams()
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par(mfrow = c(2, 3))
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for (i in seq_along(params)) {
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data <- rv$trajectory_stats_df[[params[i]]][!is.na(rv$trajectory_stats_df[[params[i]]])]
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for (i in seq_along(p$params)) {
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data <- trajectory_stats_df[[p$params[i]]][!is.na(trajectory_stats_df[[p$params[i]]])]
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if (length(data) >= 2) {
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boxplot(data, main = labels[i], ylab = labels[i], col = "lightblue", border = "darkblue")
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boxplot(data, main = p$labels[i], ylab = p$labels[i], col = "lightblue", border = "darkblue")
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points(1, mean(data), pch = 18, col = "red", cex = 1.5)
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}
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}
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par(mfrow = c(1, 1))
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})
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}
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# Density plots
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output$density_plots <- renderPlot({
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req(rv$trajectory_stats_df)
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params <- c("diffusion_distance_km", "straightness", "duration_min",
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"mean_velocity_kmh", "fractal_dimension")
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labels <- c("Diffusion Distance (km)", "Straightness", "Duration (min)",
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"Mean Velocity (km/h)", "Fractal Dimension")
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# Create density plots for trajectory statistics
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createDensityPlots <- function(trajectory_stats_df) {
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p <- getTrajectoryParams()
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par(mfrow = c(2, 3))
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for (i in seq_along(params)) {
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data <- rv$trajectory_stats_df[[params[i]]][!is.na(rv$trajectory_stats_df[[params[i]]])]
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for (i in seq_along(p$params)) {
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data <- trajectory_stats_df[[p$params[i]]][!is.na(trajectory_stats_df[[p$params[i]]])]
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if (length(data) >= 3) {
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dens <- density(data)
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plot(dens, main = paste("Density:", labels[i]), xlab = labels[i], col = "darkblue", lwd = 2)
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plot(dens, main = paste("Density:", p$labels[i]), xlab = p$labels[i], col = "darkblue", lwd = 2)
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polygon(dens, col = rgb(0, 0, 1, 0.3), border = "darkblue")
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abline(v = mean(data), col = "red", lwd = 2, lty = 2)
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abline(v = median(data), col = "green", lwd = 2, lty = 3)
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}
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}
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par(mfrow = c(1, 1))
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})
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}
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# Histograms
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output$histograms <- renderPlot({
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req(rv$trajectory_stats_df)
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params <- c("diffusion_distance_km", "straightness", "duration_min",
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"mean_velocity_kmh", "fractal_dimension")
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labels <- c("Diffusion Distance (km)", "Straightness", "Duration (min)",
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"Mean Velocity (km/h)", "Fractal Dimension")
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# Create histograms for trajectory statistics
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createHistograms <- function(trajectory_stats_df) {
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p <- getTrajectoryParams()
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par(mfrow = c(2, 3))
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for (i in seq_along(params)) {
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data <- rv$trajectory_stats_df[[params[i]]][!is.na(rv$trajectory_stats_df[[params[i]]])]
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for (i in seq_along(p$params)) {
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data <- trajectory_stats_df[[p$params[i]]][!is.na(trajectory_stats_df[[p$params[i]]])]
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if (length(data) >= 3) {
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hist(data, probability = TRUE, main = paste("Histogram:", labels[i]),
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xlab = labels[i], col = "lightgray", border = "darkgray")
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hist(data, probability = TRUE, main = paste("Histogram:", p$labels[i]),
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xlab = p$labels[i], col = "lightgray", border = "darkgray")
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lines(density(data), col = "red", lwd = 2)
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}
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}
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par(mfrow = c(1, 1))
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})
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}
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# Interpretation text
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output$interpretation_text <- renderText({
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req(rv$trajectory_stats_df)
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df <- rv$trajectory_stats_df
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# Generate interpretation text for trajectory statistics
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generateInterpretation <- function(trajectory_stats_df) {
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df <- trajectory_stats_df
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text <- "========== INTERPRETATION OF TRAJECTORY PARAMETERS ==========\n\n"
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@@ -549,9 +511,73 @@ server <- function(input, output, session) {
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text <- paste0(text, "========== END OF ANALYSIS ==========")
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text
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}
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createTrajFromRoute <- function(route_df) {
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tryCatch({
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lat_ref <- route_df$lat[1]
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lon_ref <- route_df$lon[1]
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meters_per_deg_lat <- 111320
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meters_per_deg_lon <- 111320 * cos(lat_ref * pi / 180)
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x_meters <- (route_df$lon - lon_ref) * meters_per_deg_lon
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y_meters <- (route_df$lat - lat_ref) * meters_per_deg_lat
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time_seconds <- route_df$time - route_df$time[1]
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trj <- TrajFromCoords(
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data.frame(x = x_meters, y = y_meters, time = time_seconds),
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xCol = "x", yCol = "y", timeCol = "time"
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)
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return(trj)
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}, error = function(e) {
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status(paste("Error creating trajectory object:", e$message))
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})
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}
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calculateRouteCharacteristics <- function(trj) {
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duration <- TrajDuration(trj)
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path_length <- TrajLength(trj)
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diffusion_distance <- TrajDistance(trj)
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straightness <- TrajStraightness(trj)
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mean_velocity <- path_length / duration
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fractal_dim <- tryCatch({
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min_step <- path_length / 100
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max_step <- path_length / 2
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if (min_step > 0 && max_step > min_step) {
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step_sizes <- exp(seq(log(min_step), log(max_step), length.out = 10))
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TrajFractalDimension(trj, stepSizes = step_sizes)
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} else {
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NA
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}
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}, error = function(e) NA)
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return (data.frame(
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Parameter = c(
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"Duration (s)", "Duration (min)",
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"Path Length (km)",
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"Duffusion Distance (m)",
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"Diffusion Distance (km)",
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"Straightness Index",
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"Mean Velocity (km/h)",
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"Fractal Dimension"
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),
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Value = c(
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duration_s = round(duration, 2),
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duration_min = round(duration / 60, 2),
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path_length_km = round(path_length / 1000, 2),
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diffusion_distance_m = round(diffusion_distance, 2),
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diffusion_distance_km = round(diffusion_distance / 1000, 2),
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straightness_index = round(straightness, 4),
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mean_velocity_kmh = round(mean_velocity *3.6, 2),
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fractal_dimension = round(fractal_dim, 4)
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)
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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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```
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