diff --git a/CHANGELOG.md b/CHANGELOG.md
index 83eb83c533fb1962623280fc730dbf303eb6796a..d78f731a36797f3806a8a8e73ca3123d350e02a3 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -24,6 +24,22 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- added soil map section to GIS docs
+- the `Weather` type now stores all weather information for the whole
+ simulation as a "struct-of-arrays" and with a function interface,
+ e.g. `sunshine(weather, date)` (previously, `Weather` was a struct
+ that stored the weather data for one day only, and
+ `AgricultureModel` had a field `weather::Dict{Date,Weather}`, making
+ it a "dict-of-struct" data layout)
+
+- `AgricultureModel` and `Weather` are now defined with `@kwdef`,
+ allowing for keyword arguments in their constructors
+
+- when reading weather data, we now throw an error when there are
+ missing values for the fields `min_temperature`, `max_temperature`,
+ `mean_temperature`, `precipitation`, and
+ `potential_evapotranspiration` (in the future missing values could
+ also be imputed)
+
### Deprecated
### Removed
diff --git a/src/core/simulation.jl b/src/core/simulation.jl
index b19f4024a459ef835feb6e2eed0f636528a1a97e..e57f075b9b722ae78c920bd058b4a40d50413523 100644
--- a/src/core/simulation.jl
+++ b/src/core/simulation.jl
@@ -12,20 +12,20 @@ This is the heart of the model - a struct that holds all data and state
for one simulation run. It is created by [`initialise`](@ref) and passed
as input to most model functions.
"""
-mutable struct AgricultureModel{Tcroptype,Tcropstate} <: SimulationModel
- settings::Dict{String,Any}
+@kwdef mutable struct AgricultureModel{Tcroptype, Tcropstate} <: SimulationModel
+ settings = Dict{String, Any}()
rng::AbstractRNG
logger::AbstractLogger
- dataoutputs::Dict{String,DataOutput}
+ dataoutputs = Dict{String, DataOutput}()
date::Date
- landscape::Matrix{Pixel}
- weather::Dict{Date,Weather}
- crops::Dict{String,Tcroptype}
- farmers::Vector{Farmer}
- farmplots::Vector{FarmPlot{Tcropstate}}
- animals::Vector{Union{Animal,Nothing}}
- migrants::Vector{Pair{Animal,AnnualDate}}
- events::Vector{FarmEvent}
+ landscape = Matrix{Pixel}()
+ weather::Weather
+ crops = Dict{String, Tcroptype}()
+ farmers = Vector{Farmer}()
+ farmplots = Vector{FarmPlot{Tcropstate}}()
+ animals = Vector{Union{Animal, Nothing}}()
+ migrants = Vector{Pair{Animal, AnnualDate}}()
+ events = Vector{FarmEvent}()
end
"""
@@ -36,7 +36,31 @@ Return the total number of agents in a model object.
function nagents(model::AgricultureModel)
length(model.animals)+length(model.farmers)+length(model.farmplots)
end
-
+
+windspeed(model::AgricultureModel, date::Date) = windspeed(model.weather, date)
+windspeed(model::AgricultureModel) = windspeed(model, model.date)
+
+precipitation(model::AgricultureModel, date::Date) = precipitation(model.weather, date)
+precipitation(model::AgricultureModel) = precipitation(model, model.date)
+
+sunshine(model::AgricultureModel, date::Date) = sunshine(model.weather, date)
+sunshine(model::AgricultureModel) = sunshine(model, model.date)
+
+humidity(model::AgricultureModel, date::Date) = humidity(model.weather, date)
+humidity(model::AgricultureModel) = humidity(model, model.date)
+
+meantemp(model::AgricultureModel, date::Date) = meantemp(model.weather, date)
+meantemp(model::AgricultureModel) = meantemp(model, model.date)
+
+maxtemp(model::AgricultureModel, date::Date) = maxtemp(model.weather, date)
+maxtemp(model::AgricultureModel) = maxtemp(model, model.date)
+
+mintemp(model::AgricultureModel, date::Date) = mintemp(model.weather, date)
+mintemp(model::AgricultureModel) = mintemp(model, model.date)
+
+evapotranspiration(model::AgricultureModel, date::Date) = evapotranspiration(model.weather, date)
+evapotranspiration(model::AgricultureModel) = evapotranspiration(model, model.date)
+
"""
stepagent!(agent, model)
@@ -117,22 +141,14 @@ function initmodel(settings::Dict{String, Any})
settings["core.enddate"])
crops, Tcroptype, Tcropstate = initcropmodel(settings["crop.cropmodel"],
settings["crop.cropdirectory"])
- farmers = Vector{Farmer}()
- farmplots = Vector{FarmPlot{Tcropstate}}()
- model = AgricultureModel{Tcroptype,Tcropstate}(
+ model = AgricultureModel{Tcroptype, Tcropstate}(;
settings,
- StableRNG(settings["core.seed"]),
+ rng = StableRNG(settings["core.seed"]),
logger,
- Dict{String,DataOutput}(),
- settings["core.startdate"],
+ date = settings["core.startdate"],
landscape,
weather,
- crops,
- farmers,
- farmplots,
- Vector{Union{Animal,Nothing}}(),
- Vector{Pair{Animal, Date}}(),
- Vector{FarmEvent}()
+ crops
)
saveinputfiles(model)
diff --git a/src/world/weather.jl b/src/world/weather.jl
index 055d2e0115629438ee8477c5d03fa0a2448bcc42..8883a8d978034c9213f4d1e799206c1b3d443c47 100644
--- a/src/world/weather.jl
+++ b/src/world/weather.jl
@@ -7,18 +7,63 @@
"""
Weather
-A single weather datum, combining the observations from one day.
-"""
-struct Weather
- windspeed::Union{Missing,Float64}
- precipitation::Union{Missing,Float64}
- sunshine::Union{Missing,Float64}
- cloudcover::Union{Missing,Float64}
- humidity::Union{Missing,Float64}
- meantemp::Union{Missing,Float64}
- maxtemp::Union{Missing,Float64}
- mintemp::Union{Missing,Float64}
- evapotranspiration::Union{Missing,Float64}
+Holds the weather information for the whole simulation period.
+"""
+@kwdef struct Weather
+ firstdate::Date
+ lastdate::Date
+ # TODO: types for some of these fields can be just `Vector{Float64}` after
+ # fixing missing measurement values (replacing with values
+ # approximated from previous/later measurements)
+ windspeed::Vector{Union{Missing,Float64}}
+ precipitation::Vector{Float64}
+ sunshine::Vector{Union{Missing,Float64}}
+ cloudcover::Vector{Union{Missing,Float64}}
+ humidity::Vector{Union{Missing,Float64}}
+ meantemp::Vector{Float64}
+ maxtemp::Vector{Float64}
+ mintemp::Vector{Float64}
+ evapotranspiration::Vector{Float64}
+end
+
+function Base.length(weather::Weather)
+ return Dates.value(weather.lastdate - weather.firstdate) + 1
+end
+
+function daynumber(weather::Weather, date::Date)
+ @assert weather.firstdate <= date <= weather.lastdate
+ return Dates.value(date - weather.firstdate) + 1
+end
+
+function findspans(predicate_fn, arr::AbstractVector)
+ spans = Tuple{Int, Int}[]
+ startidx = nothing
+ for i = firstindex(arr):lastindex(arr)
+ if predicate_fn(arr[i])
+ if startidx === nothing
+ startidx = i
+ end
+ elseif startidx !== nothing
+ push!(spans, (startidx, i - 1))
+ startidx = nothing
+ end
+ end
+ if startidx !== nothing
+ push!(spans, (startidx, lastindex(arr)))
+ end
+ return spans
+end
+
+function fix_missing_weatherdata!(df::DataFrame)
+ colnames_to_fix = ["min_temperature", "max_temperature", "mean_temperature",
+ "precipitation", "potential_evapotranspiration"]
+ for colname in colnames_to_fix
+ spans = findspans(ismissing, getproperty(df, colname))
+ # TODO: fix missing values and warn here instead of error
+ if ! isempty(spans)
+ error("Column $colname has missing values: $spans")
+ end
+ end
end
"""
@@ -33,97 +78,103 @@ mapped to dates.
"""
function initweather(weatherfile::String, startdate::Date, enddate::Date)
@debug "Initialising weather"
- data = CSV.File(weatherfile, missingstring="NA", dateformat="yyyy-mm-dd",
- types=[Date, Float64, Float64, Float64, Float64, Float64,
- Float64, Float64, Float64, Float64])
- weather = Dict{Date,Weather}()
- for row in data
- if row.date >= startdate && row.date <= enddate
- weather[row.date] = Weather(row.mean_windspeed, row.precipitation,
- row.sunshine_hours, row.mean_cloud_cover,
- row.mean_humidity, row.mean_temperature,
- row.max_temperature, row.min_temperature,
- row.potential_evapotranspiration)
- end
+ if startdate > enddate
+ error("Startdate is after enddate: $startdate > $enddate.")
+ end
+ Tfloat = Union{Missing, Float64}
+ df = CSV.read(weatherfile, DataFrame;
+ missingstring="NA", dateformat="yyyy-mm-dd",
+ types=[Date, Tfloat, Tfloat, Tfloat, Tfloat, Tfloat,
+ Tfloat, Tfloat, Tfloat, Tfloat])
+ needed_cols = [
+ "date", "mean_windspeed", "precipitation", "sunshine_hours",
+ "mean_cloud_cover", "mean_humidity", "mean_temperature",
+ "max_temperature", "min_temperature", "potential_evapotranspiration"
+ ]
+ if ! issubset(needed_cols, names(df))
+ error("Missing columns in weather data file: $(setdiff(needed_cols, names(df)))")
end
- if length(weather) <= Dates.value(enddate-startdate)
- @warn ("There are missing days in the weather input file:"
- * " expected $(Dates.value(enddate-startdate) + 1), got $(length(weather)).")
+ filter!(r -> r.date >= startdate && r.date <= enddate, df)
+ sort!(df, :date)
+ if startdate:enddate != df.date
+ error("There are missing days (rows) in the weather data file."
+ * " expected $(Dates.value(enddate - startdate) + 1), got $(nrow(df)))."
+ * " Missing dates are $(setdiff(startdate:enddate, df.date)).")
end
- weather
+ fix_missing_weatherdata!(df)
+ return Weather(; firstdate = minimum(df.date),
+ lastdate = maximum(df.date),
+ windspeed = df.mean_windspeed,
+ precipitation = df.precipitation,
+ sunshine = df.sunshine_hours,
+ cloudcover = df.mean_cloud_cover,
+ humidity = df.mean_humidity,
+ meantemp = df.mean_temperature,
+ maxtemp = df.max_temperature,
+ mintemp = df.min_temperature,
+ evapotranspiration = df.potential_evapotranspiration)
end
"""
- windspeed(model)
+ windspeed(weather, date)
-Return today's average windspeed in m/s.
+Return the average windspeed in m/s on `date`.
"""
-function windspeed(model::SimulationModel)
- model.weather[model.date].windspeed
-end
+windspeed(weather::Weather, date::Date) =
+ weather.windspeed[daynumber(weather, date)]
"""
- precipitation(model)
+ precipitation(weather, date)
-Return today's total precipitation in mm.
+Return the total precipitation in mm on `date`.
"""
-function precipitation(model::SimulationModel)
- model.weather[model.date].precipitation
-end
+precipitation(weather::Weather, date::Date) =
+ weather.precipitation[daynumber(weather, date)]
"""
- sunshine(model)
+ sunshine(weather, date)
-Return today's sunshine duration in hours.
+Return the sunshine duration in hours on `date`.
"""
-function sunshine(model::SimulationModel)
- model.weather[model.date].sunshine
-end
+sunshine(weather::Weather, date::Date) =
+ weather.sunshine[daynumber(weather, date)]
"""
- humidity(model)
+ humidity(weather, date)
Return today's average vapour pressure in %.
"""
-function humidity(model::SimulationModel)
- model.weather[model.date].humidity
-end
+humidity(weather::Weather, date::Date) =
+ weather.humidity[daynumber(weather, date)]
"""
- meantemp(model)
+ meantemp(weather, date)
-Return today's mean temperature in °C.
+Return the mean temperature in °C on `date`.
"""
-function meantemp(model::SimulationModel)
- model.weather[model.date].meantemp
-end
+meantemp(weather::Weather, date::Date) =
+ weather.meantemp[daynumber(weather, date)]
"""
- maxtemp(model)
+ maxtemp(weather, date)
-Return today's maximum temperature in °C.
+Return the maximum temperature in °C on `date`.
"""
-function maxtemp(model::SimulationModel)
- model.weather[model.date].maxtemp
-end
+maxtemp(weather::Weather, date::Date) =
+ weather.maxtemp[daynumber(weather, date)]
"""
- mintemp(model)
+ mintemp(weather, date)
-Return today's minimum temperature in °C.
+Return the minimum temperature in °C on `date`.
"""
-function mintemp(model::SimulationModel)
- model.weather[model.date].mintemp
-end
+mintemp(weather::Weather, date::Date) =
+ weather.mintemp[daynumber(weather, date)]
"""
- evapotranspiration(model)
+ evapotranspiration(weather, date)
-Return today's potential evapotranspiration (ETo), based on
-the
+Return today's potential evapotranspiration (ETo) on `date`.
"""
-function evapotranspiration(model::SimulationModel)
- model.weather[model.date].evapotranspiration
-end
-
-#TODO add functions for evapotranspiration
+evapotranspiration(weather::Weather, date::Date) =
+ weather.evapotranspiration[daynumber(weather, date)]
diff --git a/test/io_tests.jl b/test/io_tests.jl
index 79d9fa103bb28e9dfb896220ef27680e325a8303..8aa70f38b4b61d5e7cd0e4a9df739541dced9e70 100644
--- a/test/io_tests.jl
+++ b/test/io_tests.jl
@@ -9,8 +9,8 @@
@test @param(core.startdate) == Date(2022, 2, 1)
@test @param(core.loglevel) == "warn"
@test @param(nature.targetspecies) == ["Wolpertinger", "Wyvern"]
- @param(core.enddate) = Date(2022,1,3)
- @test @param(core.enddate) == Date(2022,1,3)
+ @param(core.enddate) = Date(2022,2,3)
+ @test @param(core.enddate) == Date(2022,2,3)
end
@testset "Output functions" begin
diff --git a/test/landscape_tests.jl b/test/landscape_tests.jl
index beba14f22ef5bcb8a29e754aae8f058fa66c8ccd..a500e526b5b3758a05639ecb0daba703d8e6d8e7 100644
--- a/test/landscape_tests.jl
+++ b/test/landscape_tests.jl
@@ -67,7 +67,7 @@ end
@testset "Weather initialisation" begin
# these tests are specific to the Jena weather file
model = inittestmodel()
- @test length(keys(model.weather)) == 59
+ @test length(model.weather) == 59
@test ismissing(Ps.windspeed(model))
@test Ps.precipitation(model) == 1.3
@test ismissing(Ps.sunshine(model))
diff --git a/test/runtests.jl b/test/runtests.jl
index f4401eb979260e76796ca17e722146e7c8ceea80..f30aca6495bf1d9c79367aa4b7b68143a6f80a59 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -45,22 +45,14 @@ function inittestmodel(smallmap=true)
TESTSETTINGS["core.enddate"])
# TODO: support other crop models besides ALMaSS
crops = Ps.ALMaSS.readcropparameters(TESTSETTINGS["crop.cropdirectory"])
- farmers = Vector{Farmer}()
- farmplots = Vector{Ps.FarmPlot{Ps.ALMaSS.CropState}}()
- model = AgricultureModel{Ps.ALMaSS.CropType,Ps.ALMaSS.CropState}(
- TESTSETTINGS,
- StableRNG(TESTSETTINGS["core.seed"]),
- global_logger(),
- Dict{String,DataOutput}(),
- TESTSETTINGS["core.startdate"],
+ model = AgricultureModel{Ps.ALMaSS.CropType,Ps.ALMaSS.CropState}(;
+ settings = copy(TESTSETTINGS),
+ rng = StableRNG(TESTSETTINGS["core.seed"]),
+ logger = global_logger(),
+ date = TESTSETTINGS["core.startdate"],
landscape,
weather,
- crops,
- farmers,
- farmplots,
- Vector{Union{Animal,Nothing}}(),
- Vector{Pair{Animal, Date}}(),
- Vector{FarmEvent}()
+ crops
)
model
end