-ILRIKE-21154.Rhistory

manure_methane_per_ha_kg_co2_e,
manure_direct_N2O_tot_kg_co2_e,
manure_Indirect_N2O_tot_kg_co2_e,
soil_direct_N2O_tot_kg_co2_e,
soil_indirect_N2O_tot_kg_co2_e,
burning,
rice_production_methane_tot_kg_co2_e,
on_farm_fertilizer_emission,
"", rough_of_Soil_direct_N2O_tot_kg_co2_e,
rough_of_soil_indirect_N2O_tot_kg_co2_e,
rough_of_fertilizer_emission,
"", conc_of_Soil_direct_N2O_tot_kg_co2_e,
conc_of_soil_indirect_N2O_tot_kg_co2_e,
conc_of_fertilizer_emission,
"", conc_ip_Soil_direct_N2O_tot_kg_co2_e,
conc_ip_soil_indirect_N2O_tot_kg_co2_e,
conc_ip_fertilizer_emission),
kg_co2_e_per_kg_fpcm = c("", enteric_fermentation_methane_kg_co2_e_per_kg_fpcm,
manure_methane_kg_co2_e_per_kg_fpcm,
manure_direct_N2O_kg_co2_e_per_kg_fpcm,
manure_Indirect_N2O_kg_co2_e_per_kg_fpcm,
soil_direct_N2O_kg_co2_e_per_kg_fpcm,
soil_indirect_N2O_kg_co2_e_per_kg_fpcm,
burning_kg_co2_e_per_kg_fpcm,
rice_production_methane_kg_co2_e_per_kg_fpcm,
on_farm_fertilizer_emission_kg_co2_e_per_kg_fpcm,
"", rough_of_Soil_direct_N2O_kg_co2_e_per_kg_fpcm,
rough_of_soil_indirect_N2O_kg_co2_e_per_kg_fpcm,
rough_of_fertilizer_emission_kg_co2_e_per_kg_fpcm,
"", conc_of_Soil_direct_N2O_kg_co2_e_per_kg_fpcm,
conc_of_soil_indirect_N2O_kg_co2_e_per_kg_fpcm,
conc_of_fertilizer_emission_kg_co2_e_per_kg_fpcm,
"", conc_ip_Soil_direct_N2O_kg_co2_e_per_kg_fpcm,
conc_ip_soil_indirect_N2O_kg_co2_e_per_kg_fpcm,
conc_ip_fertilizer_emission_kg_co2_e_per_kg_fpcm)
)
View(ghg_balance)
View(nitrogen_balance)
feed_types <- unique(land_required[["land_requirements_all"]]$feed)
n_balance <- list()
for (feed in feed_types){
feed_production <- unnest(para[["feed_items"]], cols = c(feed_type_name))
feed_selected_frac <- land_required[["feed_items_frac"]] %>%
as.data.frame() %>%
dplyr::filter(feed_item_name == feed)
feed_selected <- feed_production[feed_production$feed_item_name == feed,]
# feed_production <- unnest(para[["feed_production"]], cols = c(feed_type_name))
#
# feed_production <- na_if(feed_production, "NA") %>%
#   as.data.frame()
#
# feed_production[is.na(feed_production)] <- 0
#
# feed_selected <- feed_production[feed_production$feed_type_name == feed,]
dry_yield <- feed_selected_frac$dry_yield
residue_dry_yield <- feed_selected_frac$residue_dry_yield
main_n <- feed_selected_frac$main_n
residue_n <- as.numeric(feed_selected$residue_n)
n_fixing <- ifelse(feed_selected$category == "Legume", 0.5*(residue_n*residue_dry_yield+main_n*dry_yield)*1000, 0)
feed_selected_land_required <- land_required[["land_requirements_all"]][land_required[["land_requirements_all"]]$feed == feed,]
area_total <- sum(feed_selected_land_required$area_feed)
# feed_item_selected <- as.data.frame(feed_selected[["feed_items"]])
#
# feed_item_selected <- na_if(feed_item_selected, "NA") %>%
#   as.data.frame()
#
# feed_item_selected[is.na(feed_item_selected)] <- 0
manure_fraction <- as.numeric(feed_selected$fraction_as_fertilizer)
# Computing fertilizer rate
ammonia_n_frac <- ifelse(feed_selected$ammonia==0,0,
as.numeric(para[["fertilizer"]][which(para[["fertilizer"]]$fertilizer_desc == "Ammonia"),]$fraction))
ammonium_nitrate_n_frac <- ifelse(feed_selected$ammonium_nitrate==0,0,
as.numeric(para[["fertilizer"]][which(para[["fertilizer"]]$fertilizer_desc == "Ammonium nitrate"),]$fraction))
ammonium_sulfate_n_frac <- ifelse(feed_selected$ammonium_sulfate==0,0,
as.numeric(para[["fertilizer"]][which(para[["fertilizer"]]$fertilizer_desc == "Ammonium sulfate"),]$fraction))
dap_n_frac <- ifelse(feed_selected$dap==0,0,
as.numeric(para[["fertilizer"]][which(para[["fertilizer"]]$fertilizer_desc == "DAP"),]$fraction))
n_solutions_n_frac <- ifelse(feed_selected$n_solutions==0,0,
as.numeric(para[["fertilizer"]][which(para[["fertilizer"]]$fertilizer_desc == "N solutions"),]$fraction))
npk_n_frac <- ifelse(feed_selected$npk==0,0,
as.numeric(para[["fertilizer"]][which(para[["fertilizer"]]$fertilizer_desc == "NPK"),]$fraction))
urea_n_frac <- ifelse(feed_selected$urea==0,0,
as.numeric(para[["fertilizer"]][which(para[["fertilizer"]]$fertilizer_desc == "Urea"),]$fraction))
fertilizer_rate <- (feed_selected$ammonia*ammonia_n_frac)+(feed_selected$ammonium_nitrate*ammonium_nitrate_n_frac)+(feed_selected$ammonium_sulfate*ammonium_sulfate_n_frac)+
(feed_selected$dap*dap_n_frac)+(feed_selected$n_solutions*n_solutions_n_frac)+(feed_selected$npk*npk_n_frac)+(feed_selected$urea*urea_n_frac)
main_product_removal <- as.numeric(feed_selected$main_product_removal)
residue_removal <- as.numeric(feed_selected$residue_removal)
sum_n_content_manure_grazing <- energy_required[["annual_results"]] %>%
as.data.frame() %>%
summarise(sum(n_content_manure_grazing)) %>%
as.numeric()
yield_dm_ha <- as.numeric(dry_yield)*1000
main_product_removed_kg_ha <- yield_dm_ha*main_product_removal
n_content_manure_collected <- energy_required[["annual_results"]] %>%
as.data.frame() %>%
summarise(sum(n_content_manure_collected)) %>%
as.numeric()
animal_manure_collected <- n_content_manure_collected*manure_fraction
organic_n_imported <- manure_fraction*(as.numeric(para$purchased_manure)+as.numeric(para$purchased_compost)+as.numeric(para$purchased_organic_n)+as.numeric(para$purchased_bedding))
crop_residue_dm_ha <- as.numeric(feed_selected_frac$residue_dry_yield)*1000
residue_removal <- as.numeric(feed_selected$residue_removal)
main_product_removed_kg <- area_total*main_product_removed_kg_ha
residue_removed_dm_ha <- crop_residue_dm_ha*residue_removal
residue_removed_kg <- area_total*residue_removed_dm_ha
annual_precipitation <- as.numeric(para[["annual_prec"]])
soil_n <- as.numeric(para[["soil_n"]])
ntot_kg_ha_20cm <- soil_n*20*as.numeric(para[["soil_bulk"]])*10
n_mineralized_kg_ha_year <- ntot_kg_ha_20cm*0.03
# Soil type
soil_type <- para[["soil_description"]]
# Soil carbon
soil_c <- as.numeric(para[["soil_c"]])
# Soil clay
soil_clay <- as.numeric(para[["soil_clay"]])
# N content (kg N/kg DM)
ncrop <- as.numeric(feed_selected$main_n)
# N content (kg N /kg DM)
nres <- as.numeric(feed_selected$residue_n)
# Mineral fertilizer
in1 <- area_total*fertilizer_rate
# calculate in2
# Atmospheric deposition
in3 <- 0.14*sqrt(annual_precipitation)*area_total
# Non-symbiotic N fixation
in4a <- ifelse(area_total > 0, (2 + (annual_precipitation - 1350) * 0.005) * area_total, 0)
# Symbiotic N-fixation
in4b <- n_fixing * area_total
# Crop yield  (kgN)
out1 <- area_total*main_product_removed_kg_ha*ncrop
# Crop residue (KgN)
out2 <- ifelse(feed_selected$source_type == "Main", 0, residue_removed_dm_ha * nres * area_total)
# soil loss per plot per feed type
soil_loss_plot <- as.numeric(soil_erosion[soil_erosion$feed_type == feed,]$soil_loss_plot)
# Soil erosion
out5 <- soil_loss_plot*soil_n*1.5
# N content (kgN/kg DM ) from GHG parameters
nfertilizer <- 0 # to fox from GHG
# write data into a dataframe
n_balance[[feed]] <- as.data.frame(cbind(feed,
n_fixing,
area_total,
fertilizer_rate,
animal_manure_collected,
organic_n_imported,
yield_dm_ha,
crop_residue_dm_ha,
residue_removal,
main_product_removal,
main_product_removed_kg_ha,
main_product_removed_kg,
residue_removed_dm_ha,
residue_removed_kg,
annual_precipitation,
soil_n,
ntot_kg_ha_20cm,
n_mineralized_kg_ha_year,
soil_type,
soil_c,
soil_clay,
ncrop,
nres,
in1,
in3,
in4a,
in4b,
out1,
out2,
out5, nfertilizer))
}
n_balance_all <- n_balance %>%
bind_rows() %>%
mutate_at(c(-1, -19), as.numeric)
# Animal manure (N kg) grazing, Organic N (kg N) total, Organic N (kg N/ha) total
n_balance_all <- n_balance_all %>%
mutate(animal_manure_grazing = sum_n_content_manure_grazing * (main_product_removed_kg+residue_removed_kg)/(sum(n_balance_all$main_product_removed_kg)+sum(n_balance_all$residue_removed_kg)),
organic_n_kg_total = animal_manure_grazing+animal_manure_collected+organic_n_imported,
organic_n_kg_per_ha = ifelse(is.na(organic_n_kg_total/area_total), 0, organic_n_kg_total/area_total)) %>%
dplyr::mutate_if(is.numeric, list(~na_if(.,Inf))) %>%
replace(is.na(.), 0)
View(energy_required)
sum_n_content_manure_grazing <- energy_required[["annual_results"]] %>%
as.data.frame() %>%
summarise(sum(n_content_manure_grazing)) %>%
as.numeric()
sum_n_content_manure_grazing
view(energy_required[["annual_results"]])
energy_required[["annual_results"]]$n_content_manure_grazing
ghg_balance
# Global warming potential (CO2eq)
soil_on_farm <- ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"]
soil_on_farm
# Global warming potential (CO2eq)
soil_on_farm <- ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][1]
# Global warming potential (CO2eq)
soil_on_farm <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][1]) +
as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Indirect N2O", "kg_co2_e_per_ha"][1])
as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][-1])
as.numeric(ghg_balance[ghg_balance$GHG_balance == "Manure-Methane", "kg_co2_e_per_ha"])
rice <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Rice production-Methane", "kg_co2_e_per_ha"])/1000
# Global warming potential (CO2eq)
soil_on_farm <- (as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][1]) +
as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Indirect N2O", "kg_co2_e_per_ha"][1]))/1000
on_farm_table <- data.frame(
sources_and_sinks <- c("Soil","Off-farm Soil", "Liv. Manure", "Liv.enteric fermentation", "Burning", "Rice", "Fertilizer"),
t_CO2e_per_ha <- c(soil_on_farm, soil_off_farm, livestock_manure, livestock_enteric_fermentation, burning_emission, rice, fertilizer_on_farm)
)
# Global warming potential (CO2eq)
soil_on_farm <- (as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][1]) +
as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Indirect N2O", "kg_co2_e_per_ha"][1]))/1000
soil_off_farm <- (sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][-1])) +
sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Indirect N2O", "kg_co2_e_per_ha"][-1])))/1000
livestock_manure <- (as.numeric(ghg_balance[ghg_balance$GHG_balance == "Manure-Methane", "kg_co2_e_per_ha"]) +
as.numeric(ghg_balance[ghg_balance$GHG_balance == "Manure-Direct N2O", "kg_co2_e_per_ha"]) +
as.numeric(ghg_balance[ghg_balance$GHG_balance == "Manure-Indirect N2O", "kg_co2_e_per_ha"]))/1000
livestock_enteric_fermentation <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Enteric fermentation-Methane", "kg_co2_e_per_ha"])/1000
burning_emission <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Burning", "kg_co2_e_per_ha"])/1000
rice <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Rice production-Methane", "kg_co2_e_per_ha"])/1000
fertilizer_on_farm <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Production fertilizer", "kg_co2_e_per_ha"][1])/1000
soil_off_farm_rough <- (sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][2])) +
sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Indirect N2O", "kg_co2_e_per_ha"][2])))/1000
fertilizer_off_farm_rough <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Production fertilizer", "kg_co2_e_per_ha"][2])/1000
soil_off_farm_conc <- (sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][3])) +
sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Indirect N2O", "kg_co2_e_per_ha"][3])))/1000
fertilizer_off_farm_conc <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Production fertilizer", "kg_co2_e_per_ha"][3])/1000
soil_ip_farm_conc <- (sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Direct N2O", "kg_co2_e_per_ha"][4])) +
sum(as.numeric(ghg_balance[ghg_balance$GHG_balance == "Soil-Indirect N2O", "kg_co2_e_per_ha"][4])))/1000
fertilizer_ip_farm_conc <- as.numeric(ghg_balance[ghg_balance$GHG_balance == "Production fertilizer", "kg_co2_e_per_ha"][4])/1000
on_farm_table <- data.frame(
sources_and_sinks <- c("Soil","Off-farm Soil", "Liv. Manure", "Liv.enteric fermentation", "Burning", "Rice", "Fertilizer"),
t_CO2e_per_ha <- c(soil_on_farm, soil_off_farm, livestock_manure, livestock_enteric_fermentation, burning_emission, rice, fertilizer_on_farm)
)
View(on_farm_table)
off_farm_table <- data.frame(
sources_and_sinks = c("Roughages off-farm", "Soil off-farm", "Fertilizer off-farm", "Concentrates off-farm", "Soil off-farm", "Fertilizer off-farm", "Imported concentrates", "Soil off-farm", "Fertilizer off-farm"),
t_CO2e_per_ha = c("", soil_off_farm_rough, fertilizer_off_farm_rough, "", soil_off_farm_conc, fertilizer_off_farm_conc, "", soil_ip_farm_conc, fertilizer_ip_farm_conc)
)
View(off_farm_table)
global_warming_potential <- rbind(data.frame(sources_and_sinks = c("On-farm"),t_CO2e_per_ha = c("")),
on_farm_table,
off_farm_table)
global_warming_potential <- rbind(data.frame(sources_and_sinks = c("On-farm"),t_CO2e_per_ha = c("")),
off_farm_table)
global_warming_potential <- rbind(data.frame(sources_and_sinks = c("On-farm"),t_CO2e_per_ha = c("")),
on_farm_table%>%mutate(t_CO2e_per_ha = as.character(t_CO2e_per_ha)),
off_farm_table)
View(global_warming_potential)
View(on_farm_table)
on_farm_table <- data.frame(
sources_and_sinks = c("Soil","Off-farm Soil", "Liv. Manure", "Liv.enteric fermentation", "Burning", "Rice", "Fertilizer"),
t_CO2e_per_ha = c(soil_on_farm, soil_off_farm, livestock_manure, livestock_enteric_fermentation, burning_emission, rice, fertilizer_on_farm)
)
View(on_farm_table)
global_warming_potential <- rbind(data.frame(sources_and_sinks = c("On-farm"),t_CO2e_per_ha = c("")),
on_farm_table%>%mutate(t_CO2e_per_ha = as.character(t_CO2e_per_ha)),
off_farm_table)
View(global_warming_potential)
on_farm_table <- data.frame(
sources_and_sinks = c("Soil","Off-farm Soil", "Liv. Manure", "Liv.enteric fermentation", "Burning", "Rice", "Fertilizer"),
t_CO2e_per_ha = c(soil_on_farm, soil_off_farm, livestock_manure, livestock_enteric_fermentation, burning_emission, rice, fertilizer_on_farm)
)
off_farm_table <- data.frame(
sources_and_sinks = c("Roughages off-farm", "Soil off-farm", "Fertilizer off-farm", "Concentrates off-farm", "Soil off-farm", "Fertilizer off-farm", "Imported concentrates", "Soil off-farm", "Fertilizer off-farm"),
t_CO2e_per_ha = c("", soil_off_farm_rough, fertilizer_off_farm_rough, "", soil_off_farm_conc, fertilizer_off_farm_conc, "", soil_ip_farm_conc, fertilizer_ip_farm_conc)
)
global_warming_potential <- rbind(data.frame(sources_and_sinks = c("On-farm"),t_CO2e_per_ha = c("")),
on_farm_table,
off_farm_table)
# Plotting GHG emission
on_farm_table %>%
ggplot2::ggplot(aes(x=sources_and_sinks, y=t_CO2e_per_ha))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "", y = "t CO2e/ha", title = "GHG emissions") +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
on_farm_table %>%
ggplot2::ggplot(aes(x=sources_and_sinks, y=t_CO2e_per_ha))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "", y = "t CO2e/ha", title = "GHG emissions") +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggsave(paste0(directoryPath, "/ghg_emission.png"), width = 150, height = 100, units = "mm")
# Plotting GHG emission
on_farm_table %>%
ggplot2::ggplot(aes(x=sources_and_sinks, y=t_CO2e_per_ha))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "", y = "t CO2e/ha", title = "GHG emissions") +
geom_text(aes(label = t_CO2e_per_ha), vjust = -0.5, size = 3) +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
# Plotting GHG emission
on_farm_table %>%
ggplot2::ggplot(aes(x=sources_and_sinks, y=t_CO2e_per_ha))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "", y = "t CO2e/ha", title = "GHG emissions") +
geom_text(aes(label = t_CO2e_per_ha), vjust = -0.5, size = 3, angle = 45) +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
on_farm_table %>%
ggplot2::ggplot(aes(x=sources_and_sinks, y=t_CO2e_per_ha))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "", y = "t CO2e/ha", title = "GHG emissions") +
geom_text(aes(label = t_CO2e_per_ha), vjust = -0.5, size = 3, angle = 45) +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggsave(paste0(directoryPath, "/ghg_emission.png"), width = 150, height = 100, units = "mm")
# Plotting GHG emission
on_farm_table %>%
ggplot2::ggplot(aes(x=sources_and_sinks, y=t_CO2e_per_ha))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "", y = "t CO2e/ha", title = "GHG emissions") +
geom_text(aes(label = round(t_CO2e_per_ha, 2)), vjust = -0.5, size = 3, angle = 45) +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
on_farm_table %>%
ggplot2::ggplot(aes(x=sources_and_sinks, y=t_CO2e_per_ha))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "", y = "t CO2e/ha", title = "GHG emissions") +
geom_text(aes(label = round(t_CO2e_per_ha, 2)), vjust = -0.5, size = 3, angle = 45) +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggsave(paste0(directoryPath, "/ghg_emission.png"), width = 150, height = 100, units = "mm")
# Plotting land requirement
land_required %>%
group_by(feed, season_name) %>%
summarise(area_feed_total = sum(area_feed, na.rm = T)) %>%
ggplot2::ggplot(aes(x=feed, y=area_feed_total, fill=season_name))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "Feed Item", y = "Area (Ha)", fill = "Seasons", title = "Land Requirement and Feed Basket") +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
###############################################################################################
## Soil impact
###############################################################################################
# Plotting N balance
nitrogen_balance %>%
group_by(feed) %>%
summarise(nbalance_kg_n_total = sum(nbalance_kg_n_total, na.rm = T)) %>%
ggplot2::ggplot(aes(x=feed, y=nbalance_kg_n_total))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "Feed Item", y = "Kg N", title = "Total Nitrogen Balance by Feed Item") +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
###############################################################################################
## Soil impact
###############################################################################################
# Plotting N balance
nitrogen_balance %>%
group_by(feed) %>%
summarise(nbalance_kg_n_total = sum(nbalance_kg_n_total, na.rm = T)) %>%
ggplot2::ggplot(aes(x=feed, y=nbalance_kg_n_total))+
geom_bar(stat = "identity", width = 0.6)+
labs(x = "Feed Item", y = "Kg N", title = "Total Nitrogen Balance by Feed Item") +
geom_text(aes(label = round(nbalance_kg_n_total, 2)), vjust = -0.5, size = 3, angle = 45) +
theme_bw()+
theme(axis.text.x = element_text(angle = 45, hjust = 1))
library(cleaned)
rm(list = ls())
# Desktop
# args = c("C:/Users/soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/gui_test/Ramin/output.json",
#          "C:/Users/Soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/cleaned_tool/cleaned/inst/extdata/ghg_parameters.json",
#          "C:/Users/Soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/cleaned_tool/cleaned/inst/extdata/stock_change_parameters.json",
#          "C:/Users/Soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/cleaned_tool/cleaned/inst/extdata/energy_parameters.json",
#          "C:/Users/soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/output250723.json")
# Laptop
args = c("C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/gui_test/Ramin/output.json",
"C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/cleaned_tool/cleaned/inst/extdata/ghg_parameters.json",
"C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/cleaned_tool/cleaned/inst/extdata/stock_change_parameters.json",
"C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/cleaned_tool/cleaned/inst/extdata/energy_parameters.json",
"C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/output250723.json")
para <- fromJSON(args[1], flatten = TRUE)
ghg_ipcc_data <- fromJSON(args[2], flatten = TRUE)
stock_change_para <- fromJSON(args[3], flatten = TRUE)
energy_parameters <- fromJSON(args[4], flatten = TRUE)
filePath <- args[5]
feed_basket_quality <- feed_quality(para)
energy_required <- energy_requirement(para, feed_basket_quality,energy_parameters)
land_required <- land_requirement(feed_basket_quality, energy_required, para)
soil_erosion <- soil_health(para, land_required)
water_required <- water_requirement(para,land_required)
nitrogen_balance <- n_balance(para, land_required, soil_erosion)
livestock_productivity <- land_productivity(para)
View(livestock_productivity)
library(cleaned)
args <- list("C:/Users/soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/outFile.json",
"C:/Users/soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/test1.json",
"C:/Users/soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/test2.json")
outFile <- args[[1]]
oDir <- "C:/Users/soloo/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/plots/"
clean_plotting(args[1], args[2])
outFile <- jsonlite::fromJSON(outFile, flatten = TRUE)
library(tidyverse)
library(jsonlite)
outFile <- jsonlite::fromJSON(outFile, flatten = TRUE)
rm(list = ls())
args <- list("C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/outFile.json",
"C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/test1.json",
"C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/test2.json")
outFile <- args[[1]]
oDir <- "C:/Users/SOloo.CGIARAD/OneDrive - CGIAR/Documents/ILRI work/Projects/CLEANED-XtRa/outputs/test060923/plots/"
outFile <- jsonlite::fromJSON(outFile, flatten = TRUE)
outFile$scenario <- as.factor(outFile$scenario)
oDir <- oDir
if (!file.exists(oDir)) {dir.create(oDir, recursive=T)}
for(i in 2:ncol(outFile)){
datos <- outFile %>% select(1, all_of(i))
# titles
tt <- colnames(datos[2])
if(tt == "total_milk_produced_kg_fpcm_per_year"){
title = "Total milk FPCM (kg/yr)"
}else if(tt == "total_meat_produced_kg_per_year"){
title = "Total meat (kg/yr)"
}else if(tt == "total_protein_produced_kg_per_year"){
title = "Total protein (kg/yr)"
}else if (tt == "total_tlu"){
title = "Tropical Livestock Unit"
}else if (tt == "total_land_requirement_ha"){
title = "Land required (ha/yr)"
}else if (tt == "total_land_requirement_ha_per_kg_fpcm"){
title = "Land required (ha/kg FPCM)"
}else if (tt == "total_land_requirement_ha_per_kg_meat"){
title = "Land required (ha/kg meat)"
}else if (tt == "total_land_requirement_ha_per_kg_protein"){
title = "Land required (ha/kg protein)"
}else if (tt == "total_land_requirement_ha_per_tlu"){
title = "Land required (ha/TLU)"
}else if (tt == "total_n_balance_kg_n_per_year"){
title = "N balance (kg N/yr)"
}else if (tt == "percent_area_mining"){
title = "Soil mining (%)"
}else if (tt == "percent_area_leaching"){
title = "Soil leaching (%)"
}else if (tt == "n_balance_kg_n_per_ha_per_year"){
title = "N balance (kg N/ha/yr)"
}else if (tt == "n_balance_kg_n_per_kg_fpcm"){
title = "N balance (kg N/kg FPCM)"
}else if (tt == "n_balance_kg_n_per_kg_meat"){
title = "N balance (kg N/kg meat)"
}else if (tt == "n_balance_kg_n_per_kg_protein"){
title = "N balance (kg N/kg protein)"
}else if (tt == "erosion_t_soil_year"){
title = "Erosion (t soil/yr)"
}else if (tt == "erosion_t_soil_per_ha_per_year"){
title = "Erosion (t soil/ha/yr)"
}else if (tt == "erosion_t_soil_per_kg_fpcm"){
title = "Erosion (t soil/kg FPCM)"
}else if (tt == "erosion_t_soil_per_kg_meat"){
title = "Erosion (t soil/kg meat)"
}else if (tt == "erosion_t_soil_per_kg_protein"){
title = "Erosion (t soil/kg protein)"
}else if (tt == "ghg_emission_t_co2_eq_per_year"){
title = "GHG (t CO2eq/yr)"
}else if (tt == "ghg_emission_t_co2_eq_per_ha_per_year"){
title = "GHG (t CO2eq/ha/yr)"
}else if (tt == "ghg_emission_t_co2_eq_per_kg_fpcm"){
title = "GHG (CO2eq/kg FPCM)"
}else if (tt == "ghg_emission_t_co2_eq_per_kg_meat"){
title = "GHG (CO2eq/kg meat)"
}else if (tt == "ghg_emission_t_co2_eq_per_kg_protein"){
title = "GHG (CO2eq/kg protein)"
}else if (tt == "percent_precipitation_used_for_feed_production"){
title = "% Precipitation use for feed production"
}else if (tt == "total_water_use_m3"){
title = "Water use (m3/yr)"
}else if (tt == "total_water_use_m3_per_ha"){
title = "Water use (m3/ha)"
}else if (tt == "total_water_use_m3_per_kg_fpcm"){
title = "Water use (m3/kg FPCM)"
}else if (tt == "total_water_use_m3_per_kg_meat"){
title = "Water use (m3/kg meat)"
}else if (tt == "total_water_use_m3_per_kg_protein"){
title = "Water (m3/kg protein)"
}else if (tt == "carbon_stock_change_t_co2eq_per_year"){
title = "Carbon stock changes (t CO2eq/yr)"
}else if (tt == "carbon_stock_change_t_co2eq_per_ha_per_year"){
title = "Carbon stock changes (t CO2eq/ha/yr)"
}else if (tt == "carbon_stock_change_t_co2eq_per_fpcm"){
title = "Carbon stock changes (t CO2eq/kg FPCM)"
}else if (tt == "carbon_stock_change_t_co2eq_per_meat"){
title = "Carbon stock changes (t CO2eq/kg meat)"
}else if (tt == "carbon_stock_change_t_co2eq_per_protein"){
title = "Carbon stock changes (t CO2eq/kg protein)"
}else if (tt == "total_milk_produced_energy_kcal_per_year"){
title = "Energy (kcal/kg FPCM)"
}else if (tt == "total_meat_produced_energy_kcal_per_year"){
title = "Energy (kcal/kg meat)"
}else if (tt == "total_milk_produced_ame_days_per_year"){
title = "AME (days/kg FPCM)"
}else if (tt == "total_meat_produced_ame_days_per_year"){
title = "AME (days/kg meat)"
}else if (tt == "total_carbon_balance_per_fpcm"){
title = "Carbon balance (t CO2eq/kg FPCM)"
}else if (tt == "total_carbon_balance_per_meat"){
title = "Carbon balance (t CO2eq/kg meat)"
}else if (tt == "total_carbon_balance_per_protein"){
title = "Carbon balance (t CO2eq/kg protein)"
}else{
NA
}
ggplot(datos, aes_string("scenario", y = tt, fill = "scenario")) +
geom_bar(stat = "identity",
position = "dodge",
width = 0.2) +
geom_text(aes(label = round(datos[,2],2)), position = position_dodge(width = 0.2), vjust = -0.5, size = 2) +
labs(x = "", y = tt, title = title, fill = "Scenario") +
theme_bw()
ggsave(paste0(oDir, tt, ".png"), width = 150, height = 100, units = "mm")
}
library(cleaned)
library(cleaned)
install.packages("roxygen2")
library(roxygen2)
library(cleaned)