projects/brazil/config/UF/scripts/traffic.R

In ibarraespinosa/vein: Vehicular Emissions Inventories

year <- as.numeric(substr(x = getwd(), start = nchar(getwd()) - 6, stop = nchar(getwd()) - 3))

k_D                <- 1
k_E                <- 1
k_G                <- 1

# n_veh

n_PC <- metadata$vehicles[grep(pattern = "PC", x = metadata$vehicles)]
n_LCV <- metadata$vehicles[grep(pattern = "LCV", x = metadata$vehicles)]
n_TRUCKS <- metadata$vehicles[grep(pattern = "TRUCKS", x = metadata$vehicles)]
n_BUS <- metadata$vehicles[grep(pattern = "BUS", x = metadata$vehicles)]
n_MC <- metadata$vehicles[grep(pattern = "MC", x = metadata$vehicles)]
n_veh <- list(PC = n_PC, 
              LCV = n_LCV, 
              TRUCKS = n_TRUCKS, 
              BUS = n_BUS, 
              MC = n_MC)

inte <- intersect(metadata$vehicles, names(veh))
if(length(inte) != length(metadata$vehicles)){
  
  
  switch (language,
          "portuguese" = cat( "veh precisa ter mesmos veiculos de metadata$vehicles:\n"),
          "english" = cat( "veh needs the same vehicles as metadata$vehicles:\n"),
          "spanish" = cat( "veh necesita los mismos vehiculos de metadata$vehicles:\n"))
  
  
  stop()
}

# apagando arquivos
switch (language,
        "portuguese" = message("Apagando veh/*.rds\n"),
        "english" = message("Deleting veh/*.rds\n"),
        "spanish" = message("Borrando veh/*.rds\n"))

arquivos <- list.files(path = "veh", pattern = ".rds", full.names = TRUE)
file.remove(arquivos)

# fleet age
veh[is.na(veh)] <- 0

# plotting
switch (language,
        "portuguese" = cat("Plotando fluxos\n"),
        "english" = cat("Plotting traffic flows\n"),
        "spanish" = cat("Plotando flujos\n"))

# identicar nomes de grupos
nveh <- names(veh)
n_PC <- nveh[grep(pattern = "PC", x = nveh)]
n_LCV <- nveh[grep(pattern = "LCV", x = nveh)]
n_TRUCKS <- nveh[grep(pattern = "TRUCKS", x = nveh)]
n_BUS <- nveh[grep(pattern = "BUS", x = nveh)]
n_MC <- nveh[grep(pattern = "MC", x = nveh)]

if(survival) {
  for(i in seq_along(metadata$vehicles)) {
    veh[[metadata$vehicles[i]]] <-   age(x = veh[[metadata$vehicles[i]]], 
                                         type = metadata$survival[i], 
                                         a = metadata$survival_param_a[i],
                                         b = metadata$survival_param_b[i])
  }
}

# PC ####
#
# calculate proportion in PC 
#

kPC_G <- sum(veh$PC_G)/sum(veh[, n_PC])
kPC_E <- sum(veh$PC_E)/sum(veh[, n_PC])
kPC_FG <- sum(veh$PC_FG)/sum(veh[, n_PC])
kPC_FE <- sum(veh$PC_FE)/sum(veh[, n_PC])
kPC <- c(kPC_G, kPC_E, kPC_FG, kPC_FE)
l_PC <- list()

cat(paste0(
  "PC_G  is ", round(kPC_G, 3), " of PC\n",
  "PC_E  is ", round(kPC_E, 3), " of PC\n",
  "PC_FG is ", round(kPC_FG, 3), " of PC\n",
  "PC_FE is ", round(kPC_FE, 3), " of PC\n",
  "sum: ", kPC_G + kPC_E + kPC_FG +  kPC_FE, "\n\n"))

# fuel
kf <- c(k_G, k_E, k_G, k_E)

for(i in seq_along(n_PC)) {
  x <- veh[[n_PC[i]]]*kf[i]
  x <- Vehicles(matrix(x, ncol = length(x)))
  saveRDS(x, paste0("veh/", n_PC[i], ".rds"))
  l_PC[[i]] <- unlist(x)
}
dfpc <- as.data.frame(do.call("cbind", l_PC))
names(dfpc) <- n_PC

# LCV ####
#
# calculate proportion in LCV
#

kLCV_G <- sum(veh$LCV_G)/sum(veh[, n_LCV])
kLCV_E <- sum(veh$LCV_E)/sum(veh[, n_LCV])
kLCV_FG <- sum(veh$LCV_FG)/sum(veh[, n_LCV])
kLCV_FE <- sum(veh$LCV_FE)/sum(veh[, n_LCV])
kLCV_D <- sum(veh$LCV_D)/sum(veh[, n_LCV])
kLCV <- c(kLCV_G, kLCV_E, kLCV_FG, kLCV_FE, kLCV_D) 
l_LCV <- list()

cat(paste0(
  "LCV_G  é ", round(kLCV_G, 3), " de LCV\n",
  "LCV_E  é ", round(kLCV_E, 3), " de LCV\n",
  "LCV_FG é ", round(kLCV_FG, 3), " de LCV\n",
  "LCV_FE é ", round(kLCV_FE, 3), " de LCV\n",
  "LCV_D  é ", round(kLCV_D, 3), " de LCV\n\n",
  "sum: ", kLCV_G + kLCV_FG +  kLCV_FE +  kLCV_E + kLCV_D, "\n"))

# fuel
kf <- c(k_G, k_E, k_G, k_E, k_D)

for(i in seq_along(n_LCV)) {
  x <- veh[[n_LCV[i]]]*kf[i]
  x <- Vehicles(matrix(x, ncol = length(x)))
  saveRDS(x, paste0("veh/", n_LCV[i], ".rds"))
  l_LCV[[i]] <- unlist(x)
}
dflcv <- as.data.frame(do.call("cbind", l_LCV))
names(dflcv) <- n_LCV

# TRUCKS ####
#
# calculate proportion in TRUCKS
#

kTRUCKS_SL_D <- sum(veh$TRUCKS_SL_D)/sum(veh[, n_TRUCKS])
kTRUCKS_L_D <- sum(veh$TRUCKS_L_D)/sum(veh[, n_TRUCKS])
kTRUCKS_M_D <- sum(veh$TRUCKS_M_D)/sum(veh[, n_TRUCKS])
kTRUCKS_SH_D <- sum(veh$TRUCKS_SH_D)/sum(veh[, n_TRUCKS])
kTRUCKS_H_D <- sum(veh$TRUCKS_H_D)/sum(veh[, n_TRUCKS])
kTRUCKS <- c(kTRUCKS_SL_D, kTRUCKS_L_D, kTRUCKS_M_D, kTRUCKS_SH_D, kTRUCKS_H_D)
l_TRUCKS <- list()

cat(paste0(
  "TRUCKS_G  é ", round(kTRUCKS_SL_D, 3), " de TRUCKS\n",
  "TRUCKS_FG é ", round(kTRUCKS_L_D, 3), " de TRUCKS\n",
  "TRUCKS_FE é ", round(kTRUCKS_M_D, 3), " de TRUCKS\n",
  "TRUCKS_E  é ", round(kTRUCKS_SH_D, 3), " de TRUCKS\n",
  "TRUCKS_D  é ", round(kTRUCKS_H_D, 3), " de TRUCKS\n\n",
  "sum: ", kTRUCKS_SL_D + kTRUCKS_L_D +  kTRUCKS_M_D +  kTRUCKS_SH_D + kTRUCKS_H_D, "\n"))

# fuel
kf <- rep(k_D, 5)

for(i in seq_along(n_TRUCKS)) {
  x <- veh[[n_TRUCKS[i]]]*kf[i]
  x <- Vehicles(matrix(x, ncol = length(x)))
  saveRDS(x, paste0("veh/", n_TRUCKS[i], ".rds"))
  l_TRUCKS[[i]] <- unlist(x)
}
dft <- as.data.frame(do.call("cbind", l_TRUCKS))
names(dft) <- n_TRUCKS

# BUS ####
#
# calculate proportion in BUS
#

kBUS_URBAN_D <- sum(veh$BUS_URBAN_D)/sum(veh[, n_BUS])
kBUS_MICRO_D <- sum(veh$BUS_MICRO_D)/sum(veh[, n_BUS])
kBUS_COACH_D <- sum(veh$BUS_COACH_D)/sum(veh[, n_BUS])
kBUS <- c(kBUS_URBAN_D, kBUS_MICRO_D, kBUS_COACH_D)
l_BUS <- list()

cat(paste0(
  "BUS_URBAN_D  é ", round(kBUS_URBAN_D, 3), " de BUS\n",
  "BUS_MICRO_D  é ", round(kBUS_MICRO_D, 3), " de BUS\n",
  "BUS_URBAN_D  é ", round(kBUS_COACH_D, 3), " de BUS\n",
  "sum: ", kBUS_URBAN_D + kBUS_MICRO_D +  kBUS_COACH_D, "\n\n"))

# fuel
kf <- rep(k_D, 3)

for(i in seq_along(n_BUS)) {
  x <- veh[[n_BUS[i]]]*kf[i]
  x <- Vehicles(matrix(x, ncol = length(x)))
  saveRDS(x, paste0("veh/", n_BUS[i], ".rds"))
  l_BUS[[i]] <- unlist(x)
}
dfb <- as.data.frame(do.call("cbind", l_BUS))
names(dfb) <- n_BUS

# MC ####
#
# calculate proportion in MC
#

kMC_150_G <- sum(veh$MC_150_G)/sum(veh[, n_MC])
kMC_150_500_G <- sum(veh$MC_150_500_G)/sum(veh[, n_MC])
kMC_500_G <- sum(veh$MC_500_G)/sum(veh[, n_MC])
kMC_150_FG <- sum(veh$MC_150_FG)/sum(veh[, n_MC])
kMC_150_500_FG <- sum(veh$MC_150_500_FG)/sum(veh[, n_MC])
kMC_500_FG <- sum(veh$MC_500_FG)/sum(veh[, n_MC])
kMC_150_FE <- sum(veh$MC_150_FE)/sum(veh[, n_MC])
kMC_150_500_FE <- sum(veh$MC_150_500_FE)/sum(veh[, n_MC])
kMC_500_FE <- sum(veh$MC_500_FE)/sum(veh[, n_MC])
kMC <- c(kMC_150_G, kMC_150_500_G, kMC_500_G,
         kMC_150_FG, kMC_150_500_FG, kMC_500_FG,
         kMC_150_FE, kMC_150_500_FE, kMC_500_FE)
l_MC <- list()

cat(paste0(
  "MC_150_G  é ", round(kMC_150_G, 3), " de MC\n",
  "MC_150_500_G  é ", round(kMC_150_500_G, 3), " de MC\n",
  "MC_500_G  é ", round(kMC_500_G, 3), " de MC\n",
  "MC_150_FG  é ", round(kMC_150_FG, 3), " de MC\n",
  "MC_150_500_FG  é ", round(kMC_150_500_FG, 3), " de MC\n",
  "MC_500_FG  é ", round(kMC_500_FG, 3), " de MC\n",
  "MC_150_FE  é ", round(kMC_150_FE, 3), " de MC\n",
  "MC_150_500_FE  é ", round(kMC_150_500_FE, 3), " de MC\n",
  "MC_500_FE  é ", round(kMC_500_FE, 3), " de MC\n",
  "sum: ", 
  kMC_150_G + kMC_150_500_G +  kMC_500_G +
    kMC_150_FG + kMC_150_500_FG + kMC_500_FG +
    kMC_150_FE + kMC_150_500_FE + kMC_500_FE, "\n\n"))

# fuel
kf <- c(rep(k_G, 6), rep(k_E, 3))

for(i in seq_along(n_MC)) {
  x <- veh[[n_MC[i]]]*kf[i]
  x <- Vehicles(matrix(x, ncol = length(x)))
  saveRDS(x, paste0("veh/", n_MC[i], ".rds"))
  l_MC[[i]] <- unlist(x)
}
dfm <- as.data.frame(do.call("cbind", l_MC))
names(dfm) <- n_MC

df <- cbind(dfpc, dflcv, dft, dfb, dfm)

# plots ####
switch (language,
        "portuguese" = cat("Plotando frota \n"),
        "english" = cat("Plotting fleet \n"),
        "spanish" = cat("Plotando flota \n"))

for(i in seq_along(n_veh)) {
  df_x <- df[, n_veh[[i]]]
  png(
    paste0("images/VEH_", 
           names(n_veh)[i],
           ".png"), 
    2000, 1500, "px",res = 300)
  colplot(df = df_x,
          cols = n_veh[[i]],
          xlab = "Age",
          ylab = "veh",
          main = paste0("Veh", names(n_veh)[i]),
          type = "l",
          pch = NULL,
          lwd =1,
          theme = theme,
          spl = 8)
  dev.off()
}



# ggplot2
f <- list.files(path = "veh", pattern = ".rds", full.names = T)
na <- list.files(path = "veh", pattern = ".rds")
na <- gsub(pattern = ".rds", replacement = "", x = na)
ff <- unlist(lapply(seq_along(f), function(i){
  sum(readRDS(f[i]), na.rm =T)
}))
df <- data.frame(per = ff,
                 Categoria = na)
df <- df[df$Categoria != "fleet_age", ]
df$per <- df$per/sum(df$per)*100
df$Categoria <- factor(df$Categoria, levels = metadata$vehicles)
p <- ggplot(df, aes(x = Categoria, y = per, fill = per)) +
  geom_bar(stat = "identity", col = "black")+
  labs(y = "[%]", 
       title = "Vehicular composition [%]") +
  ggplot2::scale_fill_gradientn("[%]",colours = cptcity::cpt(rev = T)) + 
  theme_bw() +
  coord_flip() +
  scale_x_discrete(limits = rev(metadata$vehicles)) +
  theme(axis.text.x=element_text(angle=90,hjust=1)) 

png(filename =  paste0("images/TRAFFIC.png"),
    width = 2500, height = 2500, units = "px", pointsize = 12,
    bg = "white",  res = 300)
print(p)
dev.off()

switch (language,
        "portuguese" = message("\nArquivos em:"),
        "english" = message("\nFiles in:"),
        "spanish" = message("\nArchivos en:"))

message("veh/*\n")

switch (language,
        "portuguese" = message("\nFiguras em"),
        "english" = message("\nFigures in"),
        "spanish" = message("\nFiguras en"))
message("/images")

switch (language,
        "portuguese" = message("Limpando..."),
        "english" = message("Cleaning..."),
        "spanish" = message("Limpiando..."))

suppressWarnings(rm(kPC, kPC_G, kPC_E, kPC_FG, kPC_FE,
                    kLCV, kLCV_G, kLCV_E, kLCV_FG, kLCV_FE, kLCV_D,
                    kTRUCKS, kTRUCKS_SL_D, kTRUCKS_L_D, kTRUCKS_M_D, kTRUCKS_SH_D, kTRUCKS_H_D,
                    kBUS, kBUS_URBAN_D, kBUS_MICRO_D, kBUS_COACH_D,
                    kMC,kMC_150_G, kMC_150_500_G, kMC_500_G,
                    kMC_150_FG, kMC_150_500_FG, kMC_500_FG,
                    kMC_150_FE, kMC_150_500_FE, kMC_500_FE,
                    l_PC, l_LCV, l_TRUCKS, l_BUS, l_MC,
                    i, arquivos, cores, df, f, ff, 
                    n_PC, n_LCV, n_TRUCKS, n_BUS, n_MC,
                    na, nveh, p, tit, tit2, veiculos, verbose, x, kf,
                    k_G, k_D, k_E,
                    metadata, net, veh, year))
invisible(gc())