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* make analysis trip based * saving of full trip not needed anymore because trip files will be loaded in R anyways * R analysis using matsim r functions based on java analysis * save file in RStudio before commit * finish up analysis * analysis on inetrzonal drt legs * replace logging statement using logger * reduce complexity * checkstyle
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library(tidyverse) | ||
library(matsim) | ||
library(sf) | ||
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# input shp files and the corresponding crs are defined here | ||
CRS <- 25832 | ||
zone1shpFile <- "../../shared-svn/projects/KelRide/data/ServiceAreas/2021-autumn-possibleAreasForAutomatedVehicles/Altstadt.shp" | ||
zone2shpFile <- "../../shared-svn/projects/KelRide/data/ServiceAreas/2021-autumn-possibleAreasForAutomatedVehicles/Donaupark.shp" | ||
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# input legs or trips file is defined here | ||
it <- 999 | ||
directory <- "Y:/net/ils/matsim-kelheim/run-roadBlock/output/kelheim-v2.0-network-with-pt.xml.gz-seed5678-CORE/" | ||
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itDir <- paste0(directory,"ITERS/it.",it,"/") | ||
legsOrTripsFile <- paste0(itDir,list.files(path = itDir, pattern = "*legs_av*")) | ||
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zone1 <- st_read(zone1shpFile, crs=CRS) | ||
zone2 <- st_read(zone2shpFile, crs=CRS) | ||
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legsOrTripsTable <- read.csv2(legsOrTripsFile) %>% | ||
rename(start_x = "fromX", | ||
start_y = "fromY", | ||
end_x = "toX", | ||
end_y = "toY") | ||
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# filter for legs / trips starting and ending in zones | ||
departureInZone1 <- filterByRegion(legsOrTripsTable,zone1,crs=CRS,start.inshape = TRUE, end.inshape = FALSE) %>% | ||
mutate(leg_id = paste0(personId,departureTime)) | ||
arrivalInZone1 <- filterByRegion(legsOrTripsTable,zone1,crs=CRS,start.inshape = FALSE, end.inshape = TRUE) %>% | ||
mutate(leg_id = paste0(personId,departureTime)) | ||
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departureInZone2 <- filterByRegion(legsOrTripsTable,zone2,crs=CRS,start.inshape = TRUE, end.inshape = FALSE) %>% | ||
mutate(leg_id = paste0(personId,departureTime)) | ||
arrivalInZone2 <- filterByRegion(legsOrTripsTable,zone2,crs=CRS,start.inshape = FALSE, end.inshape = TRUE) %>% | ||
mutate(leg_id = paste0(personId,departureTime)) | ||
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#combine the above datasets to find legs / trips starting in one zone and ending in the other | ||
zone1ToZone2 <- semi_join(departureInZone1, arrivalInZone2, by="leg_id") | ||
zone2ToZone1 <- semi_join(departureInZone2, arrivalInZone1, by="leg_id") | ||
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interzonalLegs <- union(zone1ToZone2,zone2ToZone1) | ||
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meanTravTime <- mean(as.double(interzonalLegs$travelTime)) | ||
meanTravDist <- mean(as.double(interzonalLegs$travelDistance_m)) | ||
meanDirectTravDist <- mean(as.double(interzonalLegs$directTravelDistance_m)) | ||
meanWaitTime <- mean(as.double(interzonalLegs$waitTime)) | ||
interzonalLegsAbs <- nrow(interzonalLegs) | ||
totalNoLegs <- nrow(legsOrTripsTable) | ||
interzonalLegsRel <- interzonalLegsAbs / totalNoLegs | ||
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#save avg values into df | ||
avgValues <- setNames(data.frame(matrix(ncol = 6, nrow = 0)), c("meanTravTime[s]", "meanTravDist[m]", "meanDirectTravDist[m]", "meanWaitTime[s]","interzonalLegsAbsolute", "interzonalLegsRelative")) | ||
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avgValuesDataset <- data.frame(meanTravTime, meanTravDist,meanDirectTravDist,meanWaitTime,interzonalLegsAbs,interzonalLegsRel) | ||
names(avgValuesDataset) <- names(avgValues) | ||
avgValues <- rbind(avgValues,avgValuesDataset) | ||
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if(!file.exists(paste0(directory,"analysis-stop-2-stop"))) { | ||
print("creating analysis sub-directory") | ||
dir.create(paste0(directory,"analysis-stop-2-stop")) | ||
} | ||
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analysisDir <- paste0(directory,"/analysis-stop-2-stop/") | ||
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write.table(interzonalLegs,paste0(analysisDir,"drt_legs_av_interzonal_AS_DP.csv"),quote=FALSE, row.names=FALSE, dec=".", sep=";") | ||
write.table(avgValues,paste0(analysisDir,"avgValues_legs_interzonal_AS_DP.tsv"),quote=FALSE, row.names=FALSE, dec=".", sep="\t") |
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library(tidyverse) | ||
library(matsim) | ||
library(ggalluvial) | ||
library(lubridate) | ||
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setwd("Y:/net/ils/matsim-kelheim/run-roadBlock/output/") | ||
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baseDir <- "Y:/net/ils/matsim-kelheim/run-roadBlock/output/kelheim-v2.0-network-with-pt.xml.gz-seed5678-CORE/" | ||
policyDir <- "Y:/net/ils/matsim-kelheim/run-roadBlock/output/output-casekelheim-v2.0-network-with-pt_blocked-RegensburgerStr.xml.gz-seed5678-CORE/" | ||
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tsvFile <- "analysis-road-usage/blocked_infrastructure_trip_comparison.tsv" | ||
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ifelse(endsWith(policyDir, "/"),tsvFile <- tsvFile, tsvFile <- paste0("/",tsvFile)) | ||
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affectedTrips <- read.csv2(paste0(policyDir,tsvFile), stringsAsFactors = FALSE, header = TRUE, encoding = "UTF-8", sep="\t") | ||
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tripsBase <- readTripsTable(pathToMATSimOutputDirectory = baseDir) | ||
tripsPolicy <- readTripsTable(pathToMATSimOutputDirectory = policyDir) | ||
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# filter trips with usage of blocked infrastructure in base case only | ||
tripsBase <- tripsBase %>% | ||
filter(trip_id %in% affectedTrips$trip_id) | ||
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tripsPolicy <- tripsPolicy %>% | ||
filter(trip_id %in% affectedTrips$trip_id) | ||
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# join relevant trips by id and join + filter important stats only | ||
tripsCombined <- left_join(tripsBase, tripsPolicy, by = "trip_id") %>% | ||
filter(trip_number.x == trip_number.y) %>% | ||
select(trip_id, | ||
trav_time.x, | ||
trav_time.y, | ||
traveled_distance.x, | ||
traveled_distance.y, | ||
modes.x, | ||
modes.y, | ||
main_mode.x, | ||
main_mode.y, | ||
wait_time.x, | ||
wait_time.y, | ||
euclidean_distance.x, | ||
euclidean_distance.y) %>% | ||
rename("trav_time_base" = trav_time.x, | ||
"trav_time_policy" = trav_time.y, | ||
"traveled_distance_base" = traveled_distance.x, | ||
"traveled_distance_policy" = traveled_distance.y, | ||
"modes_base" = modes.x, | ||
"modes_policy" = modes.y, | ||
"main_mode_base" = main_mode.x, | ||
"main_mode_policy" = main_mode.y, | ||
"wait_time_base" = wait_time.x, | ||
"wait_time_policy" = wait_time.y, | ||
"euclidean_distance_base" = euclidean_distance.x, | ||
"euclidean_distance_policy" = euclidean_distance.y) | ||
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tripsCombined <- tripsCombined %>% | ||
mutate(trav_time_diff_s = trav_time_policy - trav_time_base, | ||
traveled_distance_diff_m = traveled_distance_policy - traveled_distance_base, | ||
trav_time_base = seconds(trav_time_base), | ||
trav_time_policy = seconds(trav_time_policy), | ||
wait_time_base = seconds(wait_time_base), | ||
wait_time_policy = seconds(wait_time_policy)) | ||
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meanTravTimeBase <- mean(tripsCombined$trav_time_base) | ||
meanTravTimePolicy <- mean(tripsCombined$trav_time_policy) | ||
meanTravDistBase <- mean(tripsCombined$traveled_distance_base) | ||
meanTravDistPolicy <- mean(tripsCombined$traveled_distance_policy) | ||
meanEuclDistBase <- mean(tripsCombined$euclidean_distance_base) | ||
meanEuclDistPolicy <- mean(tripsCombined$euclidean_distance_policy) | ||
meanWaitTimeBase <- mean(tripsCombined$wait_time_base) | ||
meanWaitTimePolicy <- mean(tripsCombined$wait_time_policy) | ||
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tripsChangedMainMode <- tripsCombined %>% | ||
filter(main_mode_base != main_mode_policy) | ||
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noTripsChangedMainMode <- nrow(tripsChangedMainMode) | ||
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#save avg values into df | ||
avgValues <- setNames(data.frame(matrix(ncol = 9, nrow = 0)), c("meanTravTimeBase[s]", "meanTravTimePolicy[s]", "meanTravDistBase[m]", "meanTravDistPolicy[m]", "meanEuclDistBase[m]", | ||
"meanEuclDistPolicy[m]", "meanWaitTimeBase[s]", "meanWaitTimePolicy[s]","nrTripsChangedMainMode")) | ||
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avgValuesDataset <- data.frame(meanTravTimeBase, meanTravTimePolicy,meanTravDistBase,meanTravDistPolicy,meanEuclDistBase,meanEuclDistPolicy,meanWaitTimeBase,meanWaitTimePolicy,noTripsChangedMainMode) | ||
names(avgValuesDataset) <- names(avgValues) | ||
avgValues <- rbind(avgValues,avgValuesDataset) | ||
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tsvFileName <- paste0("avg_params_blocked_infrastructure_agents.tsv") | ||
write.table(avgValues,paste0(policyDir,"analysis-road-usage/",tsvFileName),quote=FALSE, row.names=FALSE, dec=".", sep="\t") | ||
print(paste0("avg values for agents affected by blocked infrastructure ",policyDir,"analysis-road-usage/",tsvFileName)) | ||
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