minor improvements in R code

src/main/R/drtAnalysis/plotRunSummaries.R

@@ -0,0 +1,67 @@
+library(ggplot2) 
+library(dplyr)
+library(tidyr)
+
+mainDir <- "E:/matsim-kelheim/v3.1.1/output-KEXI-2.45-AV--0.0/"
+
+transposed_result <- read.csv(paste(mainDir, "results-deutsch.csv", sep=""), check.names = FALSE)
+#names(transposed_result) <- make.names(names(transposed_result), unique = TRUE, allow_ = FALSE)
+
+# Betriebszeiten umschreiben
+transposed_result$Betriebszeiten <- ifelse(transposed_result$Betriebszeiten == TRUE, "0h - 24h", "9h - 16h")
+
+
+results <- transposed_result %>%
+  gather(key = "parameter", value = "mean", -Geschwindigkeit, -Bediengebiet, -Flottengroeße, -Intermodal, -Betriebszeiten)
+
+
+plotByConfiguration <- function(parameterStr){
+
+  # Filtern der Daten für die gewünschten Parameter
+  plot_data <- results %>%
+    filter(parameter == parameterStr,
+           Intermodal == TRUE | Bediengebiet == "AV 2024")
+
+  # Funktion zum Anpassen der Facet-Labels
+  label_function <- function(value) {
+    paste(value, "m/s")
+  }
+
+  # Erstellen des Facet-Plots
+  ggplot(plot_data, aes(x = Flottengroeße, y = mean, color = Bediengebiet, linetype = as.factor(Betriebszeiten), group = interaction(Bediengebiet, Betriebszeiten))) +
+    geom_line(size = 1.2) +
+    geom_point(size = 3,
+               #aes(shape = as.factor(intermodal))
+    ) +
+    facet_wrap(~ Geschwindigkeit,
+               labeller = labeller(Geschwindigkeit = label_function)
+               ,scales = "free"
+    ) +
+    labs(title = paste(parameterStr, "nach Geschwindigkeit, Flottengröße, Bediengebiet und Betriebszeiten"),
+         x = "Flottengröße",
+         y = parameterStr,
+         color = "Bediengebiet",
+         linetype = "Betriebszeiten"
+         #,shape = "Intermodal"
+    ) +
+    #theme_dark() +
+    theme(
+      plot.title = element_text(size = 20, face = "bold"),  # Titelgröße anpassen
+      axis.title.x = element_text(size = 18),  # X-Achsentitelgröße anpassen
+      axis.title.y = element_text(size = 18),  # Y-Achsentitelgröße anpassen
+      axis.text = element_text(size = 14),  # Achsentextgröße anpassen
+      legend.title = element_text(size = 18),  # Legendentitelgröße anpassen
+      legend.text = element_text(size = 14),  # Legendtextgröße anpassen
+      strip.text = element_text(size = 18, face = "bold")  # Facet-Textgröße anpassen
+    )
+
+}
+
+unique(results$parameter)
+plotByConfiguration("Bediente Anfragen")
+plotByConfiguration("Mittl. Wartezeit")
+plotByConfiguration("Avg. ride distance [km]")
+plotByConfiguration("Empty ratio")
+plotByConfiguration("Total vehicle mileage [km]")
+plotByConfiguration("Avg. fare [MoneyUnit]" )
+plotByConfiguration("Pax per veh-km")

src/main/R/drtAnalysis/readValuesFromRunSummaries.R

@@ -112,84 +112,10 @@ print(transposed_result)
 
 write_csv(transposed_result, paste(mainDir, "results.csv", sep=""))
 
+
 #####################################################################
 ######PLOTS####
 
-# Filtern der Daten für die gewünschten Parameter
-#plot_data <- results %>%
-#  filter(parameter %in% c("Handled Requests"))
-
-## Erstellen des interaktiven dreidimensionalen Plots
-#plot <- plot_ly(plot_data, 
-#                x = ~speed, 
-#                y = ~fleetSize, 
-#                z =  ~mean, 
-#                color = ~area, 
-#                type = "scatter3d", 
-#                mode = "markers",
-#                marker = list(size = 5)) %>%
-#  add_markers() %>%
-#  layout(title = "Handled Requests by speed, area and Fleet Size",
-#         scene = list(xaxis = list(title = "Speed"),
-#                      yaxis = list(title = "Fleet Size"),
-#                      zaxis = list(title = "Handled Requests")))
-#
-## Plot anzeigen
-#plot
-
-# Erstellen des interaktiven dreidimensionalen Plots mit Mesh
-plot <- plot_ly(plot_data) %>%
-  add_mesh(x = ~speed, 
-           y = ~fleetSize, 
-           z = ~mean,
-           color = ~area,
-           opacity = 0.6,  # Opazität der Flächen
-           text = ~paste("Area:", area),
-           colors = c("#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "#9467bd", "#8c564b", "#e377c2", "#7f7f7f", "#bcbd22", "#17becf"),  # Farben für jede Area
-           showscale = TRUE) %>%
-  layout(title = "Handled Requests by speed, fleetSize and area",
-         scene = list(xaxis = list(title = "Speed"),
-                      yaxis = list(title = "Fleet Size"),
-                      zaxis = list(title = "Mean Handled Requests")))
-
-# Plot anzeigen
-plot
-
-#mesh_data <- plot_data %>%
-#  group_by(area) %>%
-#  summarise(speed = mean(speed),
-#            fleetSize = mean(fleetSize),
-#            mean = mean(mean)) %>%
-#  arrange(area)
-
-## Erstellen des interaktiven dreidimensionalen Plots mit Meshes für jede Area
-#plot <- plot_ly(plot_data) %>%
-#  add_trace(x = ~speed, 
-#            y = ~fleetSize, 
-#            z = ~mean,
-#            color = ~area,
-#            type = "scatter3d",
-#            mode = "markers",
-#            marker = list(size = 5)) %>%
-#  add_trace(data = mesh_data,
-#            x = ~speed,
-#            y = ~fleetSize,
-#           z = ~mean,
-#            color = ~area,
-#            type = "mesh3d",
-#            opacity = 0.6,  # Opazität der Flächen
-#            colorscale = "Viridis",  # Farbskala für die Flächen
-#            showscale = TRUE) %>%
-#  layout(title = "Handled Requests by speed, fleetSize and area",
-#         scene = list(xaxis = list(title = "Speed"),
-#                      yaxis = list(title = "Fleet Size"),
-#                      zaxis = list(title = "Mean Handled Requests")))
-
-## Plot anzeigen
-#plot
-
-
-###########################
 plotByConfiguration <- function(parameterStr){
 
   # Filtern der Daten für die gewünschten Parameter

src/main/R/drtDemandAnalysis/VIA-data/KEXI-shiny-dashboard.R

@@ -16,16 +16,16 @@ library(zoo) #for moving averages
 #### read data.
 
 #input files
-requests_file <- "D:/svn/shared-svn/projects/KelRide/data/KEXI/VIA_data_2024_05_22/Fahrtanfragen-2024-05-22.csv"
-shifts_file <- "D:/svn/shared-svn/projects/KelRide/data/KEXI/VIA_data_2024_05_22/Fahrerschichten-2024-05-22.csv"
+requests_file <- "D:/shared-svn/projects/KelRide/data/KEXI/VIA_data/raw-data/Fahrtanfragen.csv"
+shifts_file <- "D:/shared-svn/projects/KelRide/data/KEXI/VIA_data/raw-data/Fahrerschichten.csv"
 
 #parse data
-data <- read.csv2(requests_file, sep = ",", stringsAsFactors = FALSE, header = TRUE, encoding = "UTF-8")
+data <- read.csv2(requests_file, sep = ";", stringsAsFactors = FALSE, header = TRUE, encoding = "UTF-8")
 #data_fahrerschichten  <- read.csv2(shifts_file, sep = ",", stringsAsFactors = FALSE, header = TRUE, encoding = "UTF-8") %>% 
 #  mutate(time = ymd_hms(Datum),
 #         date = date(time))
 
-data_fahrerschichten <- read.csv2(shifts_file, sep = ",", stringsAsFactors = FALSE, header = TRUE, encoding = "UTF-8") %>% 
+data_fahrerschichten <- read.csv2(shifts_file, sep = ";", stringsAsFactors = FALSE, header = TRUE, encoding = "UTF-8") %>% 
   mutate(Start = ymd_hms(Schichtstart),
          Ende = ymd_hms(Schichtende),
          Dauer_h = as.numeric(Ende - Start, units="hours"),

src/main/R/modeAnalysis-kexiArea.R

@@ -1,7 +1,7 @@
 library(sf)
 library(matsim)
-
-
+library(tidyverse)
+library(plotly)
 
 drtArea <- st_read("D:/public-svn/matsim/scenarios/countries/de/kelheim/shp/prepare-network/av-and-drt-area.shp")
 
@@ -20,7 +20,9 @@ largeAV_filtered <- largeAVTrips %>%
 
 
 #base
-plot_mainmode_piechart(base_filtered)
+p <- plot_mainmode_piechart(base_filtered)
+p2 <- p %>% layout(title = "Base Case")
+p2
 
 #base vs KEXI
 plot_compare_mainmode_barchart(base_filtered, kexi_filtered)
@@ -33,4 +35,4 @@ plot_compare_mainmode_barchart(base_filtered, largeAV_filtered)
 plot_compare_mainmode_sankey(base_filtered, largeAV_filtered, show_onlychanges = TRUE)
 plot_mainmode_piechart(largeAV_filtered)
 
-
+matsim::plot_map_trips(kexi_filtered, crs = 25832)