projects/brazil_td_chem/scripts/plots.R

In ibarraespinosa/vein: Vehicular Emissions Inventories

# streets ####
switch(language,
  "portuguese" = cat("\nPlotando ruas\n"),
  "english" = cat("\nPlotting streets\n"),
  "spanish" = cat("\nPlotando calles\n")
)

x <- readRDS("post/emi_street.rds")
ns <- names(x)[!grepl("geom", names(x))]
for (i in seq_along(ns)) {
  png(
    filename = paste0("images/STREETS_", ns[i], ".png"),
    width = 2100,
    height = 1500,
    units = "px",
    pointsize = 12,
    bg = "white",
    res = 300
  )
  par(bg = "white")
  plot(x[ns[i]],
    axes = TRUE,
    bg = bg,
    pal = cptcity::cpt(
      colorRampPalette = TRUE,
      rev = TRUE,
      pal = pal
    ),
    lwd = 1,
    key.pos = 1
  )
  dev.off()
}

# grids ####
x <- readRDS("post/emi_grid.rds")
ns <- names(x)[!grepl("geom", names(x))]
switch(language,
  "portuguese" = cat("\nPlotando grades\n"),
  "english" = cat("\nPlotting grids\n"),
  "spanish" = cat("\nPlotando grillas\n")
)
for (i in seq_along(ns)) {
  png(
    filename = paste0("images/GRIDS_", ns[i], ".png"),
    width = 2100,
    height = 1500,
    units = "px",
    pointsize = 12,
    bg = "white",
    res = 300
  )
  par(bg = "white")
  plot(x[ns[i]],
    axes = TRUE,
    bg = bg,
    pal = cptcity::cpt(
      colorRampPalette = TRUE,
      rev = FALSE,
      pal = pal
    ),
    lty = 0,
    key.pos = 1
  )
  dev.off()
}


# category ####
dt <- readRDS("post/emi_table.rds")
dt0 <- dt[, round(sum(t), 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 <- fifelse(
  dt$veh %in% n_PC, "PC",
  fifelse(
    dt$veh %in% n_LCV, "LCV",
    fifelse(
      dt$veh %in% n_TRUCKS, "TRUCKS",
      fifelse(
        dt$veh %in% n_BUS, "BUS",
        fifelse(
          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)),
  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)),
  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)),
  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 mes
switch(language,
  "portuguese" = cat("\nPlotando categorias por mes\n"),
  "english" = cat("\nPlotting categories by month\n"),
  "spanish" = cat("\nPlotando categorias por mes\n")
)

dt1 <- dt[pollutant %in% pol,
  as.numeric(sum(t)),
  by = .(pollutant, vehicles, month)
]

for (i in seq_along(pol)) {
  p <- ggplot(
    dt1[pollutant == pol[i]],
    aes(x = month, 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/MONTH_", pol[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)),
  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())