projects/brazil_bu_chem/scripts/plots.R

In ibarraespinosa/vein: Vehicular Emissions Inventories

# check hours
if (length(hours) > nrow(tfs)) {
  switch(language,
    "portuguese" = stop("\nEscolhe um número de horas menor ou igual que numero de horas de tfs\n"),
    "english" = stop("\nChoose a number of hours less than or equal to the number of hours of tfs\n"),
    "spanish" = stop("\nEscoje un numero de horas menor o igual que el numero de horas de tfs\n")
  )
}

hh <- paste0(ifelse(nchar(hours) < 2, paste0("0", hours), hours), "-00")

# streets
switch(language,
  "portuguese" = cat("\nPlotando ruas\n"),
  "english" = cat("\nPlotting streets\n"),
  "spanish" = cat("\nPlotando calles\n")
)
for (i in seq_along(pol)) {
  for (j in seq_along(hours)) {
    x <- readRDS(paste0("post/streets/", pol[i], ".rds"))
    cn <- names(x)[hours + 1]

    png(
      filename = paste0("images/STREETS_", pol[i], "_", hh[j], ".png"),
      width = 2100, height = 1500, units = "px", pointsize = 12,
      bg = "white", res = 300
    )
    par(bg = "white")
    plot(x[as.numeric(x[[cn[j]]]) > 0, ][cn[j]],
      axes = TRUE,
      bg = bg,
      main = paste0(pol[i], ": ", tit, " [g/h] ", hh[j], " LT"),
      pal = cptcity::cpt(colorRampPalette = TRUE, rev = TRUE, pal = pal), lwd = 2
    )
    dev.off()
  }
}

# grade
switch(language,
  "portuguese" = cat("\nPlotando grades\n"),
  "english" = cat("\nPlotting grids\n"),
  "spanish" = cat("\nPlotando grillas\n")
)
for (i in seq_along(pol)) {
  for (j in seq_along(hours)) {
    x <- readRDS(paste0("post/grids/", pol[i], ".rds"))
    cn <- names(x)[hours + 1]

    png(
      filename = paste0("images/GRIDS_", pol[i], "_", hh[j], ".png"),
      width = 2100, height = 1500, units = "px", pointsize = 12,
      bg = "white", res = 300
    )
    par(bg = "white")
    plot(x[as.numeric(x[[cn[j]]]) > 0, ][cn[j]],
      axes = TRUE,
      bg = bg,
      lty = 0.3,
      main = paste0(pol[i], ": ", tit, " [g/km^2/h] ", hh[j], " LT"),
      pal = cptcity::cpt(colorRampPalette = TRUE, rev = TRUE, pal = pal)
    )
    dev.off()
  }
}


# categoria
dt <- readRDS("post/datatable/emissions.rds")
dt0 <- dt[, round(sum(t) * factor_emi, 2), by = .(pollutant, type_emi)]


dt$veh <- as.character(dt$veh)
uv <- unique(dt$veh)
n_PC <- uv[grep(pattern = "PC", x = uv)]
n_LCV <- uv[grep(pattern = "LCV", x = uv)]
n_TRUCKS <- uv[grep(pattern = "TRUCKS", x = uv)]
n_BUS <- uv[grep(pattern = "BUS", x = uv)]
n_MC <- uv[grep(pattern = "MC", x = uv)]
dt$vehicles <- ifelse(
  dt$veh %in% n_PC, "PC",
  ifelse(
    dt$veh %in% n_LCV, "LCV",
    ifelse(
      dt$veh %in% n_TRUCKS, "TRUCKS",
      ifelse(
        dt$veh %in% n_BUS, "BUS",
        ifelse(
          dt$veh %in% n_MC, "MC", "Fleet"
        )
      )
    )
  )
)

# totais x veicles
switch(language,
  "portuguese" = cat("\nPlotando categorias por total\n"),
  "english" = cat("\nPlotting categories by total\n"),
  "spanish" = cat("\nPlotando categorias por total\n")
)
dt1 <- dt[pollutant %in% pol,
  as.numeric(sum(t)) * factor_emi,
  by = .(pollutant, veh)
]
dt1$veh <- factor(
  x = dt1$veh,
  levels = metadata$vehicles
)
for (i in seq_along(pol)) {
  p <- ggplot(
    dt1[pollutant == pol[i]],
    aes(x = veh, y = V1, fill = V1)
  ) +
    geom_bar(stat = "identity", col = "black") +
    labs(
      y = "t/ano",
      title = paste0(pol[i], ": ", tit)
    ) +
    scale_fill_gradientn(pol[i], colours = cpt()) +
    scale_x_discrete(limits = rev(metadata$vehicles)) +
    theme_bw() +
    coord_flip()

  png(
    filename = paste0("images/TOTAL_", pol[i], ".png"),
    width = 2100, height = 1500, units = "px", pointsize = 12,
    bg = "white", res = 300
  )
  print(p)
  dev.off()
}

# totais x veicles
switch(language,
  "portuguese" = cat("\nPlotando categorias por type_emi\n"),
  "english" = cat("\nPlotting categories by type_emi\n"),
  "spanish" = cat("\nPlotando categorias por type_emi\n")
)
dt1 <- dt[pollutant %in% pol,
  as.numeric(sum(t)) * factor_emi,
  by = .(pollutant, veh, type_emi)
]
dt1$veh <- factor(
  x = dt1$veh,
  levels = metadata$vehicles
)
dt1$pol_te <- as.character(paste0(dt1$pollutant, "_", dt1$type_emi))
pole <- as.character(unique(dt1$pol_te))

for (i in seq_along(pole)) {
  p <- ggplot(
    dt1[pol_te == pole[i]],
    aes(x = veh, y = V1, fill = V1)
  ) +
    geom_bar(stat = "identity", col = "black") +
    labs(
      y = "t/ano",
      title = paste0(pole[i], ": ", tit)
    ) +
    scale_fill_gradientn(pole[i], colours = cpt()) +
    scale_x_discrete(limits = rev(metadata$vehicles)) +
    theme_bw() +
    coord_flip()

  png(
    filename = paste0("images/TOTAL_", pole[i], ".png"),
    width = 2100, height = 1500, units = "px", pointsize = 12,
    bg = "white", res = 300
  )
  print(p)
  dev.off()
}

# totais x veh
switch(language,
  "portuguese" = cat("\nPlotando categorias por total e tipo\n"),
  "english" = cat("\nPlotting categories by total and type\n"),
  "spanish" = cat("\nPlotando categorias por total y tipo\n")
)

dt1 <- dt[pollutant %in% pol,
  as.numeric(sum(t)) * factor_emi,
  by = .(pollutant, veh, type_emi)
]

for (i in seq_along(pol)) {
  p <- ggplot(
    dt1[pollutant == pol[i]],
    aes(x = veh, y = V1, fill = type_emi)
  ) +
    geom_bar(stat = "identity", col = "black") +
    labs(
      y = "t/ano",
      title = paste0(pol[i], ": ", tit)
    ) +
    scale_x_discrete(limits = rev(metadata$vehicles)) +
    coord_flip() +
    theme_bw()

  png(
    filename = paste0("images/TOTAL_TYPE_", pol[i], ".png"),
    width = 2100, height = 1500, units = "px", pointsize = 12,
    bg = "white", res = 300
  )
  print(p)
  dev.off()
}


# totais x hora
switch(language,
  "portuguese" = cat("\nPlotando categorias por hora\n"),
  "english" = cat("\nPlotting categories by hour\n"),
  "spanish" = cat("\nPlotando categorias por hora\n")
)
dt1 <- dt[pollutant %in% pol,
  as.numeric(sum(t)) * factor_emi,
  by = .(pollutant, vehicles, hour)
]

for (i in seq_along(pol)) {
  p <- ggplot(
    dt1[pollutant == pol[i]],
    aes(x = hour, y = V1, fill = vehicles)
  ) +
    geom_bar(stat = "identity", col = "black") +
    labs(
      y = "t/ano",
      title = paste0(pol[i], ": ", tit)
    ) +
    theme_bw()

  png(
    filename = paste0("images/HOUR_", pol[i], ".png"),
    width = 2100, height = 1500, units = "px", pointsize = 12,
    bg = "white", res = 300
  )
  print(p)
  dev.off()
}

switch(language,
  "portuguese" = cat("\nPlotando categorias por hora e type_emi\n"),
  "english" = cat("\nPlotting categories by hour and type_emi\n"),
  "spanish" = cat("\nPlotando categorias por hora y type_emi\n")
)
dt1 <- dt[pollutant %in% pol,
  as.numeric(sum(t)) * factor_emi,
  by = .(pollutant, vehicles, hour, type_emi)
]
dt1$pol_te <- as.character(paste0(dt1$pollutant, "_", dt1$type_emi))
pole <- as.character(unique(dt1$pol_te))

for (i in seq_along(pole)) {
  p <- ggplot(
    dt1[pol_te == pole[i]],
    aes(x = hour, y = V1, fill = vehicles)
  ) +
    geom_bar(stat = "identity", col = "black") +
    labs(
      y = "t/ano",
      title = paste0(pol[i], ": ", tit)
    ) +
    theme_bw()

  png(
    filename = paste0("images/HOUR_", pole[i], ".png"),
    width = 2100, height = 1500, units = "px", pointsize = 12,
    bg = "white", res = 300
  )
  print(p)
  dev.off()
}

# totais x age
dt1 <- dt[pollutant %in% pol,
  as.numeric(sum(t)) * factor_emi,
  by = .(pollutant, vehicles, age)
]

for (i in seq_along(pol)) {
  p <- ggplot(
    dt1[pollutant == pol[i]],
    aes(x = age, y = V1, fill = vehicles)
  ) +
    geom_bar(stat = "identity", col = "black") +
    labs(
      y = "t/ano",
      title = ifelse(pol[i] == "PM",
        paste0(pol[i], ": ", tit, " sem ressuspenssao "),
        paste0(pol[i], ": ", tit)
      )
    ) +
    theme_bw()

  png(
    filename = paste0("images/AGE_", pol[i], ".png"),
    width = 2100, height = 1500, units = "px", pointsize = 12,
    bg = "white", res = 300
  )
  print(p)
  dev.off()
}

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


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


suppressWarnings(
  rm(
    "bg", "breaks", "cn", "dt", "dt0", "dt1", "ef_cetesb2", "factor_emi",
    "hh", "hours", "i", "j", "metadata", "n_BUS", "n_LCV", "n_MC", "n_PC",
    "n_TRUCKS", "num_vein", "p", "pal", "pol", "pole", "tfs", "tit", "uv",
    "veh", "vein_version", "x", "year"
  )
)


ls()
invisible(gc())