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Uses MarginalInstance and allows an incoming model #16

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Uses MarginalInstance and allows an incoming model #16

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94 changes: 58 additions & 36 deletions src/monte_carlo.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -7,57 +7,73 @@
# then creates a second function, "fair_monte_carlo" that performs the actual analysis. This function returns
# a dictionary with temperature, atmospheric co2, ch4, and n2o, and radiative forcing. Adding other outputs
# is doable please add an Issue on Github if you would like this to be done. This returned function can optionally take
# a vector of vectors to force co2, ch4, and n2o emissions trajectories for the `n_samples` runs, providing
# these in the native MimiFAIRv2 emissions units, using optional arguments `co2_em_vals`, `ch4_em_vals`, and `n2o_em_vals`
# respectively.
# a vector of vectors to force co2, ch4, and n2o emissions trajectories for the `n_samples` runs, providing
# these in the native MimiFAIRv2 emissions units, using optional arguments `co2_em_vals`, `ch4_em_vals`, and `n2o_em_vals`
# respectively.
#
# The required constrained parameter files are uploaded to Zenodo with the citation Frank Errickson,
# & Lisa Rennels. (2021). MimiFAIRV2 Large Data File Storage (0.1.0-DEV) [Data set]. Zenodo.
# The required constrained parameter files are uploaded to Zenodo with the citation Frank Errickson,
# & Lisa Rennels. (2021). MimiFAIRV2 Large Data File Storage (0.1.0-DEV) [Data set]. Zenodo.
# https://doi.org/10.5281/zenodo.5513221
#
# Function Arguments:
#
# n_samples: Number of samples to randomly draw from original constrained parameter values (max = 93,995).
# emissions_scenario: Current options are: "ssp119", "ssp126", "ssp245", "ssp370", "ssp585"
# start_year: First year to run the model (note, Mimi-FAIR requires user-supplied initial conditions if not starting in 1750 so this is not yet supported for a year other than 1750).
# end_year: Final year to run the model.
# data_dir: Location of the data files
# sample_id_subset: IDs of the subset of samples to use from original constrained parameter values (each ID between 1 and 93,995
# inclusive). If this argument is set, it will be used instead of the step to create n random indices. The length
# sample_id_subset: IDs of the subset of samples to use from original constrained parameter values (each ID between 1 and 93,995
# inclusive). If this argument is set, it will be used instead of the step to create n random indices. The length
# should match n_samples, and if it is longer we will choose the first 1:n.
# delete_downloaded_data: Boolean (defaulting to false) to recursively delete all downloaded large data files of constrained parameters
# at the end of the script. Should be set to `false` if one will be running this several times and want to avoid
# at the end of the script. Should be set to `false` if one will be running this several times and want to avoid
# re-downloading each time.
#
#----------------------------------------------------------------------------------------------------------------------

# Load packages.
using CSVFiles, DataFrames, Mimi, MimiFAIRv2, StatsBase, Downloads

using CSVFiles, DataFrames, Mimi, MimiFAIRv2, StatsBase, Downloads, ProgressMeter
import Mimi.MarginalInstance

function create_fair_monte_carlo(n_samples::Int;
emissions_scenario::String="ssp585",
start_year::Int=1750,
end_year::Int=2300,
data_dir::String = joinpath(@__DIR__, "..", "data", "large_constrained_parameter_files"),
sample_id_subset::Union{Vector, Nothing} = nothing,
delete_downloaded_data::Bool = true
)

# Load an instance of FAIR with user-specificed settings.
fair_model = MimiFAIRv2.get_model(emissions_forcing_scenario=emissions_scenario, start_year=start_year, end_year=end_year)

create_fair_monte_carlo(fair_model, n_samples; start_year=start_year, end_year=end_year, data_dir=data_dir,
sample_id_subset=sample_id_subset, delete_downloaded_data=delete_downloaded_data)
end

function create_fair_monte_carlo(n_samples::Int;
emissions_scenario::String="ssp585",
start_year::Int=1750,
end_year::Int=2300,
data_dir::String = joinpath(@__DIR__, "..", "data", "large_constrained_parameter_files"),
sample_id_subset::Union{Vector, Nothing} = nothing,
delete_downloaded_data::Bool = true
)
function create_fair_monte_carlo(fair_model::Union{Model, MarginalModel}, n_samples::Int;
start_year::Int=1750,
end_year::Int=2300,
data_dir::String = joinpath(@__DIR__, "..", "data", "large_constrained_parameter_files"),
sample_id_subset::Union{Vector, Nothing} = nothing,
delete_downloaded_data::Bool = true,
other_mc_set::Function = ((model, ii) -> nothing),
other_mc_get::Function = (model -> nothing)
)

if start_year !== 1750
error("FAIRv2 model monte carlo simulation should not be set to start with a year differing from 1750 as initial conditions are not calibrated for a different start year!")
end
# Load constrained FAIR parameters from Leach et al. (2021)
end

# Load constrained FAIR parameters from Leach et al. (2021)

# Full files are pulled down via zenodo links to a local directory if they do
# not already exist in the repository relative path
isdir(data_dir) || mkpath(data_dir)
_download_paths = Dict(
:julia_constrained_thermal_parameters_average_probs => "https://zenodo.org/record/5513221/files/julia_constrained_thermal_parameters_average_probs.csv?download=1",
:julia_constrained_thermal_parameters_average_probs => "https://zenodo.org/record/5513221/files/julia_constrained_thermal_parameters_average_probs.csv?download=1",
:julia_constrained_gas_cycle_parameters_average_probs => "https://zenodo.org/record/5513221/files/julia_constrained_gas_cycle_parameters_average_probs.csv?download=1",
:julia_constrained_indirect_forcing_parameters_average_probs => "https://zenodo.org/record/5513221/files/julia_constrained_indirect_forcing_parameters_average_probs.csv?download=1",
:julia_constrained_exogenous_forcing_parameters_average_probs => "https://zenodo.org/record/5513221/files/julia_constrained_exogenous_forcing_parameters_average_probs.csv?download=1",
:julia_constrained_indirect_forcing_parameters_average_probs => "https://zenodo.org/record/5513221/files/julia_constrained_indirect_forcing_parameters_average_probs.csv?download=1",
:julia_constrained_exogenous_forcing_parameters_average_probs => "https://zenodo.org/record/5513221/files/julia_constrained_exogenous_forcing_parameters_average_probs.csv?download=1",
)

for (k, v) in _download_paths
Expand All @@ -77,7 +93,7 @@ function create_fair_monte_carlo(n_samples::Int;
# Create random indices and create a subset of FAIR sample id values (for indexing data) if they were not provided directly by the user with the
# optional sample_id_subset parameter.
if isnothing(sample_id_subset)
rand_indices = sort(sample(1:93995, n_samples, replace=false))
rand_indices = sort(sample(1:93995, n_samples, replace=false))
sample_id_subset = thermal_params[rand_indices, :sample_id]
# Do some checks on the provided sample id subset
else
Expand Down Expand Up @@ -264,22 +280,22 @@ function create_fair_monte_carlo(n_samples::Int;
error("The provided n2o_em_vals must be a vector with n_samples ($n_samples) elements, each of which is a vector spanning the full time of the model being run ($start_year to $end_year). Provided co2_em_vals has $(length(n2o_em_vals)), with first element of length $(length(n2o_em_vals[1]))")
end
end

# Initialize an array to store FAIR temperature projections.
temperatures = zeros(length(start_year:end_year), n_samples) # Global mean surface temperature anomaly (K)
rf = zeros(length(start_year:end_year), n_samples) # Total radiative forcing, with individual components scaled by their respective efficacy (Wm⁻²)
co2 = zeros(length(start_year:end_year), n_samples) # Total atmospheric carbon dioxide concentrations (ppm).
ch4 = zeros(length(start_year:end_year), n_samples) # Total atmospheric methane concentrations (ppb)
n2o = zeros(length(start_year:end_year), n_samples) # Total atmospheric nitrous oxide concentrations (ppb).

# Load an instance of FAIR with user-specificed settings.
fair_model = MimiFAIRv2.get_model(emissions_forcing_scenario=emissions_scenario, start_year=start_year, end_year=end_year)

# Create a model instance to speed things up.
fair_instance = Mimi.build(fair_model)

progress = Progress(n_samples, 1)

otherresults = []
for i = 1:n_samples

# ---- Emissions Trajectories ---- #
if !(isnothing(co2_em_vals))
update_param!(fair_instance, :co2_cycle, :E_co2, co2_em_vals[i])
Expand All @@ -288,7 +304,7 @@ function create_fair_monte_carlo(n_samples::Int;
if !(isnothing(n2o_em_vals))
update_param!(fair_instance, :n2o_cycle, :E_n2o, n2o_em_vals[i])
end

if !(isnothing(ch4_em_vals))
update_param!(fair_instance, :ch4_cycle, :E_ch4, ch4_em_vals[i])
end
Expand Down Expand Up @@ -415,6 +431,9 @@ function create_fair_monte_carlo(n_samples::Int;
update_param!(fair_instance, :shared_flourinated_pi, flourinated_pi_conc[:,i])
update_param!(fair_instance, :shared_aerosol_plus_pi, aerosol_plus_pi_conc[:,i])

# Any other parameter setting
other_mc_set(fair_instance, i)

# Run model.
run(fair_instance)

Expand All @@ -425,11 +444,14 @@ function create_fair_monte_carlo(n_samples::Int;
ch4[:, i] = fair_instance[:ch4_cycle, :ch4] # Total atmospheric methane concentrations (ppb)
n2o[:, i] = fair_instance[:n2o_cycle, :n2o] # Total atmospheric nitrous oxide concentrations (ppb)

othermc = other_mc_get(fair_instance)
push!(otherresults, othermc)
next!(progress)
end

# Return temperature and radiative forcing
return Dict(:temperatures => temperatures, :rf => rf, :co2 => co2, :ch4 => ch4, :n2o => n2o)
# Return temperature and radiative forcing
return Dict(:temperatures => temperatures, :rf => rf, :co2 => co2, :ch4 => ch4, :n2o => n2o, :other => otherresults)

end

# Recursively delete the constrained files downloaded
Expand Down