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FFI and LUC emissions now incorporate their XXX_uptake counterparts when graphing #84

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Oct 1, 2024
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Merged

FFI and LUC emissions now incorporate their XXX_uptake counterparts when graphing #84

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108 changes: 104 additions & 4 deletions inst/shinyApp/components/modules/mod_run.R
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Original file line number Diff line number Diff line change
Expand Up @@ -92,8 +92,8 @@ run_server <- function(id, r6) {
observe({

r6$run_mode <- "regular"
runs <- list()
cores <- list()
runs <- list()

for(i in 1:length(input$ssp_path)) {

Expand Down Expand Up @@ -132,15 +132,64 @@ run_server <- function(id, r6) {
}

r6$core <- cores
runs2_list <- list()

for(i in 1:length(input$ssp_path)) {

runs[[i]] <- fetchvars(r6$core[[i]], r6$time()[1]:r6$time()[2], vars = list(r6$selected_var())) %>%
mutate(Scenario = names(which(scenarios == input$ssp_path[i], arr.ind = FALSE)))

if(r6$selected_var() == "ffi_emissions" | r6$selected_var() == "luc_emissions") {

if(r6$selected_var() == "ffi_emissions") {

runs2_list[[i]] <- fetchvars(r6$core[[i]], r6$time()[1]:r6$time()[2], vars = "daccs_uptake") %>%
mutate(Scenario = names(which(scenarios == input$ssp_path[i], arr.ind = FALSE)))

} else if(r6$selected_var() == "luc_emissions") {

runs2_list[[i]] <- fetchvars(r6$core[[i]], r6$time()[1]:r6$time()[2], vars = "luc_uptake") %>%
mutate(Scenario = names(which(scenarios == input$ssp_path[i], arr.ind = FALSE)))

}

}

}

if(r6$selected_var() == "ffi_emissions" | r6$selected_var() == "luc_emissions") {
if(r6$selected_var() == "ffi_emissions") {

runs2 <- bind_rows(runs2_list) %>% pivot_wider(names_from = variable, values_from = value)

bind_rows(runs) %>%
pivot_wider(names_from = variable, values_from = value) %>%
left_join(runs2) %>%
mutate(ffi_emissions = ffi_emissions - daccs_uptake) %>%
select(-daccs_uptake) %>% pivot_longer(cols = ffi_emissions, names_to = "variable", values_to = "value") %>%
select(scenario, year, variable, value, units, Scenario) -> runs_w_uptake

} else if(r6$selected_var() == "luc_emissions") {

runs2 <- bind_rows(runs2_list) %>% pivot_wider(names_from = variable, values_from = value)

bind_rows(runs) %>%
pivot_wider(names_from = variable, values_from = value) %>%
left_join(runs2) %>%
mutate(luc_emissions = luc_emissions - luc_uptake) %>%
select(-luc_uptake) %>% pivot_longer(cols = luc_emissions, names_to = "variable", values_to = "value") %>%
select(scenario, year, variable, value, units, Scenario) -> runs_w_uptake

}
runs_df <- as.data.frame(runs_w_uptake)

} else{
runs_df <- bind_rows(runs)
}

r6$output <- bind_rows(runs)
r6$output <- runs_df
print("Done")

# Save scenarios used in run
r6$ini_list <- unique(r6$output$Scenario)

Expand All @@ -154,13 +203,64 @@ run_server <- function(id, r6) {
observe({
r6$selected_var <- reactive({input$variable})
runs <- list()
runs2_list <- list()

for(i in 1:length(r6$ini_list)) {

runs[[i]] <- fetchvars(r6$core[[i]], r6$time()[1]:r6$time()[2], vars = list(r6$selected_var())) %>%
mutate(Scenario = r6$ini_list[i])

if(r6$selected_var() == "ffi_emissions" | r6$selected_var() == "luc_emissions") {

if(r6$selected_var() == "ffi_emissions") {

runs2_list[[i]] <- fetchvars(r6$core[[i]], r6$time()[1]:r6$time()[2], vars = "daccs_uptake") %>%
mutate(Scenario = r6$ini_list[i])

} else if(r6$selected_var() == "luc_emissions") {

runs2_list[[i]] <- fetchvars(r6$core[[i]], r6$time()[1]:r6$time()[2], vars = "luc_uptake") %>%
mutate(Scenario = r6$ini_list[i])

}

}

}

if(r6$selected_var() == "ffi_emissions" | r6$selected_var() == "luc_emissions") {

if(r6$selected_var() == "ffi_emissions") {
runs2 <- bind_rows(runs2_list) %>% pivot_wider(names_from = variable, values_from = value)

bind_rows(runs) %>%
pivot_wider(names_from = variable, values_from = value) %>%
left_join(runs2) %>%
mutate(ffi_emissions = ffi_emissions - daccs_uptake) %>%
select(-daccs_uptake) %>% pivot_longer(cols = ffi_emissions, names_to = "variable", values_to = "value") %>%
select(scenario, year, variable, value, units, Scenario) -> runs_w_uptake

} else if(r6$selected_var() == "luc_emissions") {
runs2 <- bind_rows(runs2_list) %>% pivot_wider(names_from = variable, values_from = value)

bind_rows(runs) %>%
pivot_wider(names_from = variable, values_from = value) %>%
left_join(runs2) %>%
mutate(luc_emissions = luc_emissions - luc_uptake) %>%
select(-luc_uptake) %>% pivot_longer(cols = luc_emissions, names_to = "variable", values_to = "value") %>%
select(scenario, year, variable, value, units, Scenario) -> runs_w_uptake

}

runs_df <- as.data.frame(runs_w_uptake)

} else{

runs_df <- bind_rows(runs)

}

r6$output <- bind_rows(runs)
r6$output <- runs_df

output$graph <- renderPlotly({
graph_plots(r6 = r6)
Expand Down
2 changes: 2 additions & 0 deletions inst/shinyApp/global.r
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,9 @@ get_titles <- function() {
title <- list("CO2_concentration" = "Atmospheric CO2",
"atmos_co2" = "Atmospheric Carbon Pool",
"ffi_emissions" = "FFI Emissions",
"daccs_uptake" = "FFI Emission Uptake",
"luc_emissions" = "LUC Emissions",
"luc_uptake" = "LuC Emission Uptake",
"N2O_concentration" = "N2O Concentration",
"BC_emissions" = "Black Carbon Emissions",
"OC_emissions" = "Organic Carbon Emissions",
Expand Down
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