+++ title = "Contributing" subtitle = "" hascode = true date = Date(2023, 5, 5) rss = "How to contribute"
tags = ["syntax", "code"] +++
Contributing to EarthSciML
See the SciML contributor's guide here.
diff --git a/404.html b/404.html deleted file mode 100644 index 564acfc..0000000 --- a/404.html +++ /dev/null @@ -1 +0,0 @@ -
See the SciML contributor's guide here.
- ${display_result} -
-+++ title = "Contributing" subtitle = "" hascode = true date = Date(2023, 5, 5) rss = "How to contribute"
tags = ["syntax", "code"] +++
See the SciML contributor's guide here.
Settings
This document was generated with Documenter.jl version 1.5.0 on Wednesday 14 August 2024. Using Julia version 1.10.4.
A next-generation software framework for geoscientific modeling and analysis
Status `~/work/earthsci.dev/earthsci.dev/Project.toml`
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- [ade2ca70] Dates
-Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated`
Julia Version 1.10.4
-Commit 48d4fd48430 (2024-06-04 10:41 UTC)
-Build Info:
- Official https://julialang.org/ release
-Platform Info:
- OS: Linux (x86_64-linux-gnu)
- CPU: 4 × AMD EPYC 7763 64-Core Processor
- WORD_SIZE: 64
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- [1a1011a3] SharedArrays
- [6462fe0b] Sockets
- [2f01184e] SparseArrays v1.10.0
- [10745b16] Statistics v1.10.0
- [4607b0f0] SuiteSparse
- [fa267f1f] TOML v1.0.3
- [a4e569a6] Tar v1.10.0
- [8dfed614] Test
- [cf7118a7] UUIDs
- [4ec0a83e] Unicode
- [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
- [deac9b47] LibCURL_jll v8.4.0+0
- [e37daf67] LibGit2_jll v1.6.4+0
- [29816b5a] LibSSH2_jll v1.11.0+1
- [c8ffd9c3] MbedTLS_jll v2.28.2+1
- [14a3606d] MozillaCACerts_jll v2023.1.10
- [4536629a] OpenBLAS_jll v0.3.23+4
- [05823500] OpenLibm_jll v0.8.1+2
- [efcefdf7] PCRE2_jll v10.42.0+1
- [bea87d4a] SuiteSparse_jll v7.2.1+1
- [83775a58] Zlib_jll v1.2.13+1
- [8e850b90] libblastrampoline_jll v5.8.0+1
- [8e850ede] nghttp2_jll v1.52.0+1
- [3f19e933] p7zip_jll v17.4.0+2
-Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`
Settings
This document was generated with Documenter.jl version 1.5.0 on Wednesday 14 August 2024. Using Julia version 1.10.4.
using EarthSciMLBase, EarthSciData, GasChem, EnvironmentalTransport
-using ModelingToolkit, DifferentialEquations
-using DomainSets, Unitful, Dates
-using NCDatasets, Plots
-using SciMLBase: DiscreteCallback
-using ProgressMeter
-
-@parameters t [unit = u"s", description = "Time"]
-@parameters lat = 40
-@parameters lon = -97
-@parameters lev = 1
-emis = NEI2016MonthlyEmis("mrggrid_withbeis_withrwc", t, lon, lat, lev; dtype=Float64)
-
-geosfp = GEOSFP("4x5", t; dtype = Float64,
- coord_defaults = Dict(:lon => 0.0, :lat => 0.0, :lev => 1.0))
-
-starttime = datetime2unix(DateTime(2016, 5, 1, 0, 0))
-endtime = datetime2unix(DateTime(2016, 5, 1, 5, 0))
-
-domain = DomainInfo(
- [partialderivatives_δxyδlonlat,
- partialderivatives_δPδlev_geosfp(geosfp)],
- constIC(16.0, t ∈ Interval(starttime, endtime)),
- constBC(16.0,
- lon ∈ Interval(deg2rad(-130.0), deg2rad(-60.0)),
- lat ∈ Interval(deg2rad(9.75), deg2rad(60.0)),
- lev ∈ Interval(1, 15)),
- dtype = Float64)
-
-chem = SuperFast(t)
-photolysis = FastJX(t)
-
-outfile = ("RUNNER_TEMP" ∈ keys(ENV) ? ENV["RUNNER_TEMP"] : tempname()) * "out.nc" # This is just a location to save the output.
-output = NetCDFOutputter(outfile, 3600.0)
-
-csys = couple(chem, photolysis, geosfp, emis, domain, output)
-
-adv = AdvectionOperator(600.0, l94_stencil)
-
-csys = couple(csys, adv)
-
-function pbar(start, finish)
- p = Progress(Int(round(finish-start)))
- DiscreteCallback(
- (_, _, _) -> true,
- (integrator) -> update!(p, Int(round(integrator.t-start)));
- save_positions = (false, false),
- )
-end
-#csys = couple(csys, pbar(starttime, endtime))
-
-
-sim = Simulator(csys, [deg2rad(15), deg2rad(10), 1])
-st = SimulatorStrangThreads(Tsit5(), SSPRK22(), 600.0)
-
-@time run!(sim, st, save_on=false, save_start=false, save_end=false,
- initialize_save=false)
-
-ds = NCDataset(outfile, "r")
-
-anim = @animate for i ∈ 1:size(ds["SuperFast₊O3"])[4]
- plot(
- heatmap(ds["SuperFast₊O3"][:, :, 1, i]', title="Ground-Level"),
- heatmap(ds["SuperFast₊O3"][:, 2, :, i]', title="Vertical Cross-Section"),
- )
-end
-gif(anim, fps = 15)
Settings
This document was generated with Documenter.jl version 1.5.0 on Wednesday 14 August 2024. Using Julia version 1.10.4.
+++ title = "EarthSciML Example" subtitle = "" hascode = true date = Date(2023, 7, 1) rss = "EarthSciML Example"
tags = ["syntax", "code"] +++
\toc
-using EarthSciData, EarthSciMLBase, GasChem,
- DomainSets, ModelingToolkit, MethodOfLines,
- DifferentialEquations, Dates, Distributions,
- Latexify, Plots, SciMLBase,
- CairoMakie, GraphMakie, MetaGraphsNext
-
-@parameters t lev lon lat
-model = SuperFast(t)
-ls = latexify(model.rxn_sys) # TODO: Change to model.rxn_sys
-print(replace(ls.s, raw"\require{mhchem}" => "")) # hide
This is what ls
looks like:
\textoutput{./code/ex1}
# Set start and end times.
-start, finish = Dates.datetime2unix.([
- Dates.DateTime(2022, 5, 1),
- Dates.DateTime(2022, 5, 3),
-])
-
-# Create a model by combining SuperFast chemistry and FastJX photolysis.
-model_ode = SuperFast(t) + FastJX(t)
-
-# Run the simulation.
-prob = ODEProblem(structural_simplify(get_mtk(model_ode)), [], (start, finish), [])
-sol = solve(prob, TRBDF2(), saveat=1800.0)
-
-# Plot result.
-ticks = Dates.datetime2unix.([Dates.DateTime(2022, 5, 1), Dates.DateTime(2022, 5, 2),
- Dates.DateTime(2022, 5, 3)])
-tickstrings = Dates.format.(Dates.unix2datetime.(ticks), "m-d-yy")
-Plots.plot(sol,ylims=(0,30),xlabel="Date", ylabel="Concentration (ppb)",
- ylabelfontsize=9, xlabelfontsize=9,
- xticks=(ticks, tickstrings), legend=:outertopright, size=(500, 310))
-Plots.savefig(joinpath(@OUTPUT, "ode.svg")) # hide
\textoutput{./code/ex2}
\fig{ode}
struct Emissions <: EarthSciMLODESystem
- sys
- function Emissions(t, μ_lon, σ)
- @variables NO(t) ISOP(t)
- dist = MvNormal([start,μ_lon],[3600.0,σ])
- @parameters lon
- D = Differential(t)
- new(ODESystem([
- D(NO) ~ pdf(dist, [t, lon]) * 50,
- D(ISOP) ~ pdf(dist, [t, lon]) * 50,
- ], t, name=:emissions))
- end
-end
-Base.:(+)(e::Emissions, b::SuperFast) = operator_compose(b, e)
-Base.:(+)(b::SuperFast, e::Emissions) = e + b
\textoutput{./code/ex3}
function ModelingToolkit.check_units(eqs...) # Skip unit enforcement for now
- nothing
- #ModelingToolkit.validate(eqs...) || @info "Some equations had invalid units. See warnings for details."
-end
-
-# Skip returning the observed variables (i.e. variables that are not state variables)
-# because it is currently extremely slow to do so for this demo.
-SciMLBase.observed(sol::SciMLBase.AbstractTimeseriesSolution, sym, i::Colon) = zeros(Float64, length(sol.t))
\textoutput{./code/ex4}
domain = DomainInfo(
- partialderivatives_lonlat2xymeters,
- constIC(1.0f0, t ∈ Interval(start, finish)),
- zerogradBC(lon ∈ Interval(-130f0, -100f0)))
-
-geos = GEOSFP("0.25x0.3125_NA", t; coord_defaults = Dict(:lat => 34.0, :lev => 1))
-
-model = SuperFast(t) + FastJX(t) + domain +
- Emissions(t, -118.2, 0.2)+ Advection() + geos
-
-g = graph(model)
-
-f, ax, p = graphplot(g; ilabels=labels(g))
-hidedecorations!(ax); hidespines!(ax); ax.aspect = DataAspect()
-
-save(joinpath(@OUTPUT, "graph.svg"), f) # hide
\output{./code/ex5a} \fig{graph}
discretization = MOLFiniteDifference([lon => 50], t, approx_order=2)
-prob = discretize(get_mtk(model), discretization)
-sol = solve(prob, TRBDF2(), saveat=3600.0)
\output{./code/ex5b}
discrete_lon = sol[lon]
-discrete_t = sol[t]
-
-@variables superfast₊O3(..) superfast₊NO(..) superfast₊ISOP(..) superfast₊NO2(..)
-sol_isop = sol[superfast₊ISOP(t, lon)]
-sol_o3 = sol[superfast₊O3(t, lon)]
-sol_no = sol[superfast₊NO(t, lon)]
-sol_no2 = sol[superfast₊NO2(t, lon)]
-
-using LaTeXStrings
-Plots.plot(
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_isop[:, 1:end]',
- xticks=(ticks, tickstrings),
- ylabel="Longitude (°)", title="Isoprene", titlefontsize=12,
- margin=0Plots.mm,
- size=(600, 400), dpi=300),
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_no[:, 1:end]',
- xticks=(ticks, tickstrings), title="NO", titlefontsize=12),
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_no2[:, 1:end]',
- xticks=(ticks, tickstrings), xlabel="Date", title=L"\textrm{NO_2}"),
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_o3[:, 1:end]',colorbar_title="Concentration (ppb)",
- xticks=(ticks, tickstrings), title=L"\textrm{O_3}", titlefontsize=12),
-)
-Plots.savefig(joinpath(@OUTPUT, "pde.svg"))
\textoutput{./code/ex6}
\fig{pde}
Settings
This document was generated with Documenter.jl version 1.5.0 on Wednesday 14 August 2024. Using Julia version 1.10.4.
First, install the package:
] add EarthSciMLBase
Then, load it:
> using EarthSciMLBase
Settings
This document was generated with Documenter.jl version 1.5.0 on Wednesday 14 August 2024. Using Julia version 1.10.4.
A next-generation software framework for geoscientific modeling and analysis
Earth Science models are important tools for understanding and making predictions about our environment. The next generation of geoscientific models needs to be integrated across disciplines and to better facilitate convergent research. However, current model development focuses on tightly-coupled model components for numerical efficiency, requiring development or gatekeeping by a close-knit team. These two requirements are mutually exclusive and incompatible: development processes that require contributions from diverse individuals require components that are modular and granular, whereas the development of tightly coupled components requires a centrally-managed organization. We term this challenge the community fragmentation problem.
An additional current barrier to the openness of geoscientific resources is that geoscientists developing algorithms performant enough for inclusion in large-scale models are also required to have extensive knowledge of numerical methods for integrating differential equations, and these skills are not taught in many geoscientific curricula. We term this the two-domain problem.
This project aims to solve these two problems by seeding a transition to symbolic equation-based model development, where model components and their interrelationships are specified symbolically as systems of differential-algebraic equations, visually similar to how they would appear in a scientific journal article.
using EarthSciData, EarthSciMLBase, GasChem,
- DomainSets, ModelingToolkit, MethodOfLines,
- DifferentialEquations, Dates, Distributions,
- Latexify, Plots, SciMLBase,
- CairoMakie, GraphMakie, MetaGraphsNext
-
-@parameters t lev lon lat
-model = SuperFast(t)
-ls = latexify(model.rxn_sys) # TODO: Change to model.rxn_sys
This is what ls
looks like:
# Set start and end times.
-start, finish = Dates.datetime2unix.([
- Dates.DateTime(2022, 5, 1),
- Dates.DateTime(2022, 5, 3),
-])
-
-# Create a model by combining SuperFast chemistry and FastJX photolysis.
-model_ode = SuperFast(t) + FastJX(t)
-
-# Run the simulation.
-prob = ODEProblem(structural_simplify(get_mtk(model_ode)), [], (start, finish), [])
-sol = solve(prob, TRBDF2(), saveat=1800.0)
-
-# Plot result.
-ticks = Dates.datetime2unix.([Dates.DateTime(2022, 5, 1), Dates.DateTime(2022, 5, 2),
- Dates.DateTime(2022, 5, 3)])
-tickstrings = Dates.format.(Dates.unix2datetime.(ticks), "m-d-yy")
-Plots.plot(sol,ylims=(0,30),xlabel="Date", ylabel="Concentration (ppb)",
- ylabelfontsize=9, xlabelfontsize=9,
- xticks=(ticks, tickstrings), legend=:outertopright, size=(500, 310))
struct Emissions <: EarthSciMLODESystem
- sys
- function Emissions(t, μ_lon, σ)
- @variables NO(t) ISOP(t)
- dist = MvNormal([start,μ_lon],[3600.0,σ])
- @parameters lon
- D = Differential(t)
- new(ODESystem([
- D(NO) ~ pdf(dist, [t, lon]) * 50,
- D(ISOP) ~ pdf(dist, [t, lon]) * 50,
- ], t, name=:emissions))
- end
-end
-Base.:(+)(e::Emissions, b::SuperFast) = operator_compose(b, e)
-Base.:(+)(b::SuperFast, e::Emissions) = e + b
function ModelingToolkit.check_units(eqs...) # Skip unit enforcement for now
- nothing
- #ModelingToolkit.validate(eqs...) || @info "Some equations had invalid units. See warnings for details."
-end
-
-# Skip returning the observed variables (i.e. variables that are not state variables)
-# because it is currently extremely slow to do so for this demo.
-SciMLBase.observed(sol::SciMLBase.AbstractTimeseriesSolution, sym, i::Colon) = zeros(Float64, length(sol.t))
domain = DomainInfo(
- partialderivatives_lonlat2xymeters,
- constIC(1.0f0, t ∈ Interval(start, finish)),
- zerogradBC(lon ∈ Interval(-130f0, -100f0)))
-
-geos = GEOSFP("0.25x0.3125_NA", t; coord_defaults = Dict(:lat => 34.0, :lev => 1))
-
-model = SuperFast(t) + FastJX(t) + domain +
- Emissions(t, -118.2, 0.2)+ Advection() + geos
-
-g = graph(model)
-
-f, ax, p = graphplot(g; ilabels=labels(g))
-hidedecorations!(ax); hidespines!(ax); ax.aspect = DataAspect()
MethodError: no method matching EarthSciData.GEOSFP(::String, ::Symbolics.Num; coord_defaults::Dict{Symbol, Real})
-
// Image matching '/assets/tutorials/example/code/graph' not found. //
discretization = MOLFiniteDifference([lon => 50], t, approx_order=2)
-prob = discretize(get_mtk(model), discretization)
-sol = solve(prob, TRBDF2(), saveat=3600.0)
MethodError: no method matching discretize(::ModelingToolkit.ODESystem, ::MethodOfLines.MOLFiniteDifference{MethodOfLines.CenterAlignedGrid, MethodOfLines.ScalarizedDiscretization})
-
-Closest candidates are:
- discretize(!Matched::ModelingToolkit.PDESystem, ::PDEBase.AbstractEquationSystemDiscretization; analytic, kwargs...)
- @ PDEBase ~/.julia/packages/PDEBase/Aqj4G/src/discretization_state.jl:55
-
-
discrete_lon = sol[lon]
-discrete_t = sol[t]
-
-@variables superfast₊O3(..) superfast₊NO(..) superfast₊ISOP(..) superfast₊NO2(..)
-sol_isop = sol[superfast₊ISOP(t, lon)]
-sol_o3 = sol[superfast₊O3(t, lon)]
-sol_no = sol[superfast₊NO(t, lon)]
-sol_no2 = sol[superfast₊NO2(t, lon)]
-
-using LaTeXStrings
-Plots.plot(
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_isop[:, 1:end]',
- xticks=(ticks, tickstrings),
- ylabel="Longitude (°)", title="Isoprene", titlefontsize=12,
- margin=0Plots.mm,
- size=(600, 400), dpi=300),
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_no[:, 1:end]',
- xticks=(ticks, tickstrings), title="NO", titlefontsize=12),
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_no2[:, 1:end]',
- xticks=(ticks, tickstrings), xlabel="Date", title=L"\textrm{NO_2}"),
- Plots.heatmap(discrete_t, discrete_lon[1:end], sol_o3[:, 1:end]',colorbar_title="Concentration (ppb)",
- xticks=(ticks, tickstrings), title=L"\textrm{O_3}", titlefontsize=12),
-)
-Plots.savefig(joinpath(@OUTPUT, "pde.svg"))
ArgumentError: lon is neither an observed nor a state variable. // Image matching '/assets/tutorials/example/code/pde' not found. //
First, install the package:
] add EarthSciMLBase
-Then, load it:
-> using EarthSciMLBase
-