---
title: "Compare scenarios Transport"
output:
  pdf_document: default
  html_document:
    df_print: paged
classoption: landscape
---

```{r, echo=FALSE, message=FALSE, warning=FALSE}
require(ggplot2)
require(moinput)
require(rmndt)
require(quitte)
library(lucode)
library(magpie)
library(quitte)
```

```{r, echo=FALSE, message=FALSE, warning=FALSE}
# Set RDS files path
EJmode_all = readRDS("EJmode_all.RDS")
EJLDV_all = readRDS("EJLDV_all.RDS")
fleet_all = readRDS("fleet_all.RDS")
salescomp_all = readRDS("salescomp_all.RDS")
ESmodecap_all = readRDS("ESmodecap_all.RDS")
CO2km_int_newsales_all = readRDS("CO2km_int_newsales_all.RDS")
EJfuels_all = readRDS("EJfuels_all.RDS")
emidem_all = readRDS("emidem_all.RDS")

setConfig(forcecache=T)

cols <- c("NG" = "#d11141",
          "Liquids" = "#8c8c8c",
          "Hybrid Liquids" = "#ffc425",
          "Hybrid Electric" = "#f37735",
          "BEV" = "#00b159",
          "Electricity" = "#00b159",
          "FCEV" = "#00aedb",
          "Hydrogen" = "#00aedb",
          "Biodiesel" = "#66a182",
          "Synfuel" = "orchid",
          "Oil" = "#2e4057",
          "fuel price pkm" = "#edae49",
          "Operating costs registration and insurance" = "#8d96a3",
          "Operating costs maintenance" = "#00798c",
          "Capital cost" = "#d1495b",
          "International Aviation" = "#9acd32",
          "Domestic Aviation" = "#7cfc00",
          "Bus" = "#32cd32",
          "Passenger Rail" = "#2e8b57",
          "Freight Rail" = "#ee4000",
          "Trucks" = "#ff6a6a",
          "International Shipping" = "#cd2626",
          "Domestic Shipping" = "#ff4040",
          "Shipping" = "#ff4040",
          "Truck" = "#ff7f50",
          "Trucks (<3.5t)" = "#ff7f50",
          "Trucks (3.5t-16)" = "#8b0000",
          "Trucks (>16)" = "#fa8072",
          "Motorbikes" = "#1874cd", #"dodgerblue3",
          "Small Cars" = "#87cefa",
          "Large Cars" = "#6495ed",
          "Van" = " 	#40e0d0",
          "LDV" = "#00bfff",
          "Non motorized" = "#da70d6",
          "Freight"="#ff0000",
          "Freight (Inland)" = "#cd5555",
          "Pass non LDV" = "#6b8e23", 
          "Pass" = "#66cdaa",
          "Pass non LDV (Domestic)" = "#54ff9f",
          "refined liquids enduse" = "#8c8c8c",
          "FE|Transport|Hydrogen" = "#00aedb", 
          "FE|Transport|NG" = "#d11141",
          "FE|Transport|Liquids" = "#8c8c8c", 
          "FE|Transport|Electricity" = "#00b159",
          "FE|Transport" = "#1e90ff", 
          "FE|Buildings" = "#d2b48c",
          "FE|Industry" = "#919191",
          "Electricity_push" = "#00b159",
          "ElecEra" = "#00b159",
          "ElecEraWise" = "#68c6a4",
          "HydrHype" = "#00aedb",
          "HydrHypeWise" = "#o3878f",
          "Hydrogen_push" = "#00aedb",
          "Smart_lifestyles_Electricity_push" = "#68c6a4",
          # "Smart_lyfestiles_Electricity_push" = "#03878f", ##maybe "#o3878f"
          "Conservative_liquids" = "#113245",
          "ConvCase" = "#113245",
          "ConvCaseWise" = "#d11141",
          "Emi|CO2|Transport|Demand" = "#113245",
          "Emi|CO2|Industry|Gross" = "#919191",
          "Emi|CO2|Buildings|Direct" = "#d2b48c",
          "Emi|CO2|Energy|Supply|Gross" = "#f2b531",
          "Emi|CO2|CDR|BECCS" = "#ed5958",
          "Emi|CO2|Land-Use Change" = "#66a182",
          "Cons. + Synfuels" = "orchid",
          "Ctax_Conservative" = "#d11141")

legend_ord_modes <- c("Freight Rail", "Truck", "Shipping", "International Shipping", "Domestic Shipping",  "Trucks",
                "Motorbikes", "Small Cars", "Large Cars", "Van",
                "International Aviation", "Domestic Aviation","Bus", "Passenger Rail",
                "Freight", "LDV", "Pass non LDV", "Freight (Inland)", "Pass non LDV (Domestic)", "Non motorized")

legend_ord_fuels <- c("BEV", "Electricity", "Hybrid Electric", "FCEV", "Hydrogen", "Hybrid Liquids", "Liquids", "Oil", "Biodiesel", "Synfuel", "NG")

legend_ord_costs <- c("fuel price pkm", "Operating costs registration and insurance", "Operating costs maintenance", "Capital cost")

legend_ord_emissions <- c("Emi|CO2|Industry|Gross", "Emi|CO2|Buildings|Direct", "Emi|CO2|Transport|Demand", "Emi|CO2|Energy|Supply|Gross", "Emi|CO2|Land-Use Change","Emi|CO2|CDR|BECCS")

legend_ord = c(legend_ord_modes, legend_ord_fuels, legend_ord_costs)




```

```{r, echo=FALSE, message=FALSE, warning=FALSE}

```

```{r, echo=FALSE, message=FALSE, warning=FALSE}
## Vintages
vintcomparisonpf = function(dt){
  dt = dt[year %in% c(2015, 2050, 2100)]
  plot = ggplot()+
    geom_bar(data = dt,
             aes(x=scenario, y=value, group=interaction(variable, technology),
                 fill = technology, width=.75), alpha = 0.5, position="stack", stat = "identity", width = 0.5)+
    geom_bar(data = dt,
             aes(x=scenario, y=value, group=interaction(variable, technology),
                 fill = technology, alpha = factor(alphaval),  width=.75), position="stack", stat = "identity", width = 0.5, color = "black", size=0.05)+
    guides(fill = guide_legend(reverse=TRUE))+
    theme_minimal()+
    facet_grid(year~region)+
    theme(axis.text.x = element_text(angle = 90, size=8, vjust=0.5, hjust=1),
          title = element_text(size=8),
          axis.line = element_line(size = 0.5, colour = "grey"),
          # legend.text = element_text(size=8),
          strip.text = element_text(size=8),
          strip.background = element_rect(color = "grey"))+
    scale_alpha_discrete(breaks = c(1,0), name = "Status", labels = c("Vintages","New additions")) +
    guides(linetype=FALSE,
           fill=guide_legend(reverse=FALSE, title="Transport mode"))+
    scale_fill_manual(values = cols)+
    labs(y = "[million Veh]", x="", title = "LDV fleet")
    return(plot)
}

vintcomparisonpf(fleet_all)
## Sales composition


```


```{r, echo=FALSE, message=FALSE, warning=FALSE}
salescompf = function(dt){

  plot = ggplot()+
    geom_bar(data = dt, aes(x=as.numeric(as.character(year)),y=shareFS1, group = technology, fill = technology), position = position_stack(), stat = "identity")+
    theme_minimal()+
    facet_grid(region ~ scenario)+
    scale_fill_manual("Technology", values = cols)+
    expand_limits(y = c(0,1))+
    scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
    theme(axis.text.x = element_text(angle = 90, vjust=0.5, hjust=1, size = 8),
          axis.text.y = element_text(size=8),
          axis.line = element_line(size = 0.5, colour = "grey"),
          axis.title = element_text(size = 8),
          title = element_text(size = 8),
          # legend.text = element_text(8),
          # legend.title = element_text(size = 8),
          strip.text = element_text(size=8),
          strip.background = element_rect(color = "grey"))+
    labs(x = "", y = "[%]", title = "Market share of new LDV sales")
  return(plot)
}

salescompf(salescomp_all)

```

```{r, echo=FALSE, message=FALSE, warning=FALSE}
EJLDVpf = function(dt){
  dt[, technology := factor(technology, levels = legend_ord)]
  plot = ggplot()+
    geom_area(data = dt, aes(x=year, y=demand_EJ, group = technology, fill = technology), color="black",position= position_stack())+
    labs(x = "", y = "[EJ]", title = "LDV Final Energy demand")+
    theme_minimal()+
    facet_grid(scenario~region)+
    scale_fill_manual("Technology", values = cols, breaks=legend_ord)+
    expand_limits(y = c(0,1))+
    scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
    theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
          axis.text.y = element_text(size = 8),
          axis.title = element_text(size = 8),
          axis.line = element_line(size = 0.5, colour = "grey"),
          title = element_text(size = 8),
          # legend.text = element_text(size =8),
          # legend.title = element_text(size = 8),
          strip.text = element_text(size=8),
          strip.background = element_rect(color = "grey"))
  return(plot)
}

EJLDVpf(EJLDV_all)

```

```{r, echo=FALSE, message=FALSE, warning=FALSE}
EJmodepf = function(dt){
  plot = ggplot()+
    geom_area(data = dt, aes(x=year, y=demand_EJ, group = interaction(vehicle_type_plot,aggr_mode), fill = vehicle_type_plot), color = "black", position= position_stack())+
    labs(x = "", y = "[EJ]", title = "Total transport final energy demand")+
    theme_minimal()+
    facet_grid(scenario~region)+
    scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
    expand_limits(y = c(0,1))+
    scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
    theme(axis.text.x = element_text(angle = 90, size = 8, vjust=0.5, hjust=1),
          axis.text.y = element_text(size=8),
          axis.title = element_text(size = 8),
          title = element_text(size = 8),
          # legend.text = element_text(size = 8),
          # legend.title = element_text(size =8),
          strip.text = element_text(size=8),
          axis.line = element_line(size = 0.5, colour = "grey"),
          strip.background = element_rect(color = "grey"))
  return(plot)
}

EJmodepf(EJmode_all)

```


```{r, echo=FALSE, message=FALSE, warning=FALSE}
ESmodecappf = function(dt){
  dt[, vehicle_type_plot := factor(vehicle_type_plot, levels = legend_ord)]
  plot_frgt = ggplot()+
    geom_area(data = dt[mode == "freight"], aes(x=year, y=cap_dem, group = vehicle_type_plot, fill = vehicle_type_plot), color="black",position= position_stack())+
    labs(x = "", y = "Energy Services demand [tkm/cap]")+
    theme_minimal()+
    facet_grid(scenario~region)+
    scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
    expand_limits(y = c(0,1))+
    scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
    theme(axis.text.x = element_text(angle = 90,  size = 8, vjust=0.5, hjust=1),
          axis.text.y = element_text(size = 8),
          axis.title = element_text(size = 8),
          title = element_text(size = 8),
          legend.text = element_text(size = 8),
          legend.title = element_text(size = 8),
          strip.text = element_text(size = 8),
          strip.background = element_rect(color = "grey"),
          axis.line = element_line(size = 0.5, colour = "grey"))

  
  plot_pass = ggplot()+
    geom_area(data = dt[mode == "pass"], aes(x=year, y=cap_dem, group = vehicle_type_plot, fill = vehicle_type_plot), color="black",position= position_stack())+
    labs(x = "", y = "Energy Services demand [pkm/cap]")+
    theme_minimal()+
    facet_grid(scenario~region)+
    scale_fill_manual("Vehicle Type",values = cols, breaks=legend_ord)+
    expand_limits(y = c(0,1))+
    scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
    theme(axis.text.x = element_text(angle = 90,  size = 8, vjust=0.5, hjust=1),
          axis.text.y = element_text(size = 8),
          axis.title = element_text(size = 8),
          title = element_text(size = 8),
          legend.text = element_text(size = 8),
          legend.title = element_text(size = 8),
          strip.text = element_text(size = 8),
          strip.background = element_rect(color = "grey"),
          axis.line = element_line(size = 0.5, colour = "grey"))


    return(list(plot_pass = plot_pass, plot_frgt = plot_frgt))
}


ESmodecappf(ESmodecap_all)

```


```{r, echo=FALSE, message=FALSE, warning=FALSE}
CO2km_int_newsalespf = function(dt){
  dt = dt[!is.na(gCO2_km_ave)]
  plot = ggplot()+
    geom_line(data = dt[year >=2020], aes(x = year, y = gCO2_km_ave, group = scenario, color = scenario))+
    labs(title = expression(paste(CO["2"], " intensity of LDVs new additions")), y = expression(paste("[", gCO["2"], "/km]")), x = "")+
    expand_limits(y = c(0,1))+
    scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
    theme_minimal()+
    facet_grid(~region)+
    theme(axis.text.x = element_text(angle = 90,  size = 8, vjust=0.5, hjust=1),
          axis.text.y = element_text(size = 8),
          axis.title = element_text(size = 8),
          title = element_text(size = 8),
          legend.text = element_text(size = 8),
          legend.title = element_text(size = 8),
          strip.text = element_text(size = 8),
          strip.background = element_rect(color = "grey"),
          axis.line = element_line(size = 0.5, colour = "grey"))+
    guides(linetype = FALSE)
  return(plot)
}

CO2km_int_newsalespf(CO2km_int_newsales_all)
```


```{r, echo=FALSE, message=FALSE, warning=FALSE}
## LDV by fuel
EJfuels_pf = function(dt){
  plot = ggplot()+
    geom_area(data = dt, aes(x=year, y=demand_EJ, group = subtech, fill = subtech), color="black", position= position_stack())+
    labs(x = "", y = "[EJ]", title = "Transport FE demand by fuel")+
    theme_minimal()+
    facet_grid(scenario~region)+
    scale_fill_manual("Technology",values = cols, breaks=legend_ord)+
    expand_limits(y = c(0,1))+
    scale_x_continuous(breaks = c(2015,2030,2050, 2100))+
    theme(axis.text.x = element_text(angle = 90,  size = 8, vjust=0.5, hjust=1),
          axis.text.y = element_text(size = 8),
          axis.title = element_text(size = 8),
          title = element_text(size = 8),
          legend.text = element_text(size = 8),
          legend.title = element_text(size = 8),
          strip.text = element_text(size = 8),
          strip.background = element_rect(color = "grey"),
          axis.line = element_line(size = 0.5, colour = "grey"))
  return(plot)
}

EJfuels_pf(EJfuels_all)
```


```{r, echo=FALSE, message=FALSE, warning=FALSE}
emidem_pf = function(dt){
 
  plot = ggplot()+
    geom_line(data = dt, aes(x = year, y = value, group = variable, color = variable))+
    labs(x = "", y = "CO2 emissions [Mt/CO2]")+
    theme_minimal()+
    facet_grid(~region)+
    theme(axis.text.x = element_text(size = 8),
          axis.text.y = element_text(size=8),
          axis.title = element_text(size = 9),
          title = element_text(size = 9),
          legend.position = "none",
          strip.text = element_text(size=9))+
    scale_color_manual("Scenario", values = cols)
   
  return(plot)
}

emidem_pf(emidem_all)
```