### Persefone.jl - a model of agricultural landscapes and ecosystems in Europe. ### ### This file includes functions for saving the model output. ### const LOGFILE = "simulation.log" ## Much of this code was adapted from the GeMM model by Leidinger et al. ## (https://github.com/CCTB-Ecomods/gemm/blob/master/src/output.jl) """ createdatadir(outdir, overwrite) Creates the output directory, dealing with possible conflicts. """ function createdatadir(outdir::String, overwrite::Union{Bool,String}) if isdir(outdir) if overwrite == "ask" println("The chosen output directory $(outdir) already exists.") println("Type 'yes' to overwrite this directory. Otherwise, the simulation will abort.") print("Overwrite? ") answer = readline() overwrite = (answer == "yes" || answer == "y") end !overwrite ? Base.error("Output directory exists, will not overwrite. Aborting.") : @warn "Overwriting existing output directory $(outdir)." #TODO replace with exception end mkpath(outdir) end """ modellogger(loglevel, outdir, output="both") Create a logger object that writes output both to screen and to a logfile. This object is stored as `model.logger` and can then be used with `with_logger()`. Note: requires [`createdatadir`](@ref) to be run first. """ function modellogger(loglevel::String, outdir::String, output::String="both") !isdir(outdir) && #TODO replace with exception Base.error("$(outdir) does not exist. Call `createdatadir()` before `modellogger()`.") loglevel == "debug" ? loglevel = Logging.Debug : loglevel == "warn" ? loglevel = Logging.Warn : loglevel == "info" ? loglevel = Logging.Info : Base.error("Invalid loglevel $loglevel, should be debug/info/warn.") #TODO make exception (output in ["file", "both"]) && (logfile = open(joinpath(outdir, LOGFILE), "w+")) if output == "both" return TeeLogger(ConsoleLogger(logfile, loglevel), ConsoleLogger(stdout, loglevel)) elseif output == "file" return ConsoleLogger(logfile, loglevel) elseif output == "screen" return ConsoleLogger(stdout, loglevel) else Base.error("Invalid log output target $output, should be file/screen/both.") end end """ withtestlogger(model) Replace the model logger with the currently active logger. This is intended to be used in the testsuite to circumvent a [Julia issue](https://github.com/JuliaLang/julia/issues/48456), where `@test_logs` doesn't work with local loggers. """ function withtestlogger(model::SimulationModel) # copied together from https://github.com/JuliaLang/julia/blob/master/base/logging.jl logstate = current_task().logstate logstate == nothing ? model.logger = global_logger() : model.logger = logstate.logger model end """ saveinputfiles(model) Copy all input files into the output directory, including the actual parameter settings used. This allows replicating a run in future. """ function saveinputfiles(model::SimulationModel) #XXX If this is a parallel run, we should save the global config to the top-level # output directory @debug "Setting up output directory $(@param(core.outdir))." currentcommit = read(`git rev-parse HEAD`, String)[1:8] open(joinpath(@param(core.outdir), basename(@param(core.configfile))), "w") do f println(f, "#\n# --- Persefone configuration parameters ---") println(f, "# This file was generated automatically.") println(f, "# Simulation run on $(string(Dates.format(Dates.now(), "d u Y HH:MM:SS"))),") # Record the current git commit and versions of dependencies for reproducibility println(f, "# with Persefone $(pkgversion(Persefone)), git commit $(currentcommit),") println(f, "# running on Julia $(VERSION).\n#\n") if !isempty(strip(read(`git status -s`, String))) println(f, "# WARNING: Your repository contains uncommitted changes. This may") println(f, "# compromise the reproducibility of this simulation run.\n") end TOML.print(f, prepareTOML(model.settings)) end # Copy the map files to the output folder lcmap = @param(world.landcovermap) ffmap = @param(world.farmfieldsmap) #TODO replace errors with exceptions !(isfile(lcmap)) && Base.error("The map file $(lcmap) doesn't exist.") !(isfile(ffmap)) && Base.error("The map file $(ffmap) doesn't exist.") cp(lcmap, joinpath(@param(core.outdir), basename(lcmap)), force = true) cp(ffmap, joinpath(@param(core.outdir), basename(ffmap)), force = true) end """ prepareTOML(dict) An internal utility function to re-convert the one-dimensional dict created by [`flattenTOML`](@ref) into the two-dimensional dict needed by `TOML.print`, and convert any data types into TOML-compatible types where necessary. """ function prepareTOML(settings) # convert data types settings["core.loglevel"] == Logging.Debug ? settings["core.loglevel"] = "debug" : settings["core.loglevel"] == Logging.Warn ? settings["core.loglevel"] = "warn" : settings["core.loglevel"] = "info" # convert dict structure fulldict = Dict{String, Dict{String, Any}}() for parameter in keys(settings) domain, param = split(parameter, ".") !(domain in keys(fulldict)) && (fulldict[domain] = Dict{String,Any}()) fulldict[domain][param] = settings[parameter] end fulldict end """ DataOutput A struct for organising model output. This is used to collect model data in an in-memory dataframe or for CSV output. Submodels can register their own output functions using [`newdataoutput!`](@ref). Struct fields: - name: a string identifier for the data collection (used as file name) - header: a list of column names - outputfunction: a function that takes a model object and returns data values to record (formatted as a vector of vectors) - frequency: how often to call the output function (daily/monthly/yearly/end/never) - plotfunction: a function that takes a model object and returns a Makie figure object (optional) """ struct DataOutput name::String header::Vector{String} outputfunction::Function frequency::String plotfunction::Union{Function,Nothing} end """ newdataoutput!(model, name, header, outputfunction, frequency) Create and register a new data output. This function must be called by all submodels that want to have their output functions called regularly. """ function newdataoutput!(model::SimulationModel, name::String, header::Vector{String}, outputfunction::Function, frequency::String, plotfunction::Union{Function,Nothing}=nothing) if !(frequency in ("daily", "monthly", "yearly", "end", "never")) Base.error("Invalid frequency '$frequency' for $name.") #TODO replace with exception end ndo = DataOutput(name, header, outputfunction, frequency, plotfunction) append!(model.dataoutputs, [ndo]) if frequency != "never" if @param(core.csvoutput) open(joinpath(@param(core.outdir), name*".csv"), "w") do f println(f, join(header, ",")) end end if @param(core.storedata) df = DataFrame() for h in header df[!,h] = Any[] #XXX allow specifying types? end model.datatables[name] = df end end end """ outputdata(model, force=false) Cycle through all registered data outputs and activate them according to their configured frequency. If `force` is `true`, activate all outputs regardless of their configuration. """ function outputdata(model::SimulationModel, force=false) #XXX enable output every X days, or weekly? #XXX all output functions except for "end" are run on the first update # -> should they all be run on the last update, too? startdate = @param(core.startdate) isnextmonth = d -> (day(d) == day(startdate)) isnextyear = d -> (month(d) == month(startdate) && day(d) == day(startdate)) for output in model.dataoutputs (!force && output.frequency == "never") && continue # check if this output should be activated today if force || (output.frequency == "daily") || (output.frequency == "monthly" && isnextmonth(model.date)) || (output.frequency == "yearly" && isnextyear(model.date)) || (output.frequency == "end" && model.date == @param(core.enddate)) data = output.outputfunction(model) if @param(core.csvoutput) open(joinpath(@param(core.outdir), output.name*".csv"), "a") do f for row in data println(f, join(row, ",")) end end end if @param(core.storedata) for row in data push!(model.datatables[output.name], row) end end end end end """ visualiseoutput(model) Cycle through all data outputs and call their respective plot functions, saving each figure to file. """ function visualiseoutput(model::SimulationModel) @debug "Visualising output." CairoMakie.activate!() # make sure we're using Cairo for output in model.dataoutputs isnothing(output.plotfunction) && continue figure = output.plotfunction(model) save(joinpath(@param(core.outdir), output.name*"."*@param(core.figureformat)), figure) end end """ savemodelobject(model, filename) Serialise a model object and save it to file for later reference. Includes the current model and Julia versions for compatibility checking. WARNING: produces large files (>100 MB) and takes a while to execute. """ function savemodelobject(model::SimulationModel, filename::String) object = Dict("model"=>model, "modelversion"=>pkgversion(Persefone), "juliaversion"=>VERSION) !endswith(filename, ".dat") && (filename *= ".dat") filename = joinpath(@param(core.outdir), filename) serialize(filename, object) @debug "Saved model object to $(filename)." end