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Generate and propagate Monte Carlo Simulations based on a template input file.

Source: R/fct_combine_mcs_cstock.R
fct_combine_mcs_cstock.Rd

TBD

Usage

fct_combine_mcs_cstock(.ad, .cs, .usr)

Arguments

.ad

Activity Data input table for the shiny app (AD_lu_transitions)

.cs

Carbon Stock input table for the shiny app (c_stocks)

.usr

User inputs' table for the shiny app (user_inputs). Contains the number of iterations of the MCS, carbon fraction if needed and if truncated PDFs should be used when necessary.

Value

A data frame with Monte Carlo simulations of CO2 emissions for each land use transition, REDD+ activity or emission reductions level.

Examples

library(mocaredd)
library(readxl)
library(dplyr)

path <- system.file("extdata/example2-with-sims.xlsx", package = "mocaredd")

cs <- read_xlsx(path = path, sheet = "c_stocks", na = "NA")
ad <- read_xlsx(path = path, sheet = "AD_lu_transitions", na = "NA")
usr <- read_xlsx(path = path, sheet = "user_inputs", na = "NA")

res <- fct_combine_mcs_cstock(.ad = ad, .cs = cs, .usr = usr)
#> Error in pmap(combi, function(period, lu) {    c_sub <- filter(.cs, .data$c_period == period, .data$c_lu_id ==         lu)    c_check <- fct_check_pool(.c_sub = c_sub, .c_unit = .usr$c_unit,         .c_fraction = .usr$c_fraction)}): could not find function "pmap"
res |> filter(sim_no == 1)
#> Error: object 'res' not found