Remove Adapt dependency

Replace interpolation op with generalised spacevaryingutility tools.
CliMA · Oct 23, 2024 · 266d885 · 266d885
1 parent 09ca71a
commit 266d885
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diff --git a/.buildkite/pipeline.yml b/.buildkite/pipeline.yml
@@ -566,6 +566,7 @@ steps:
       - label: "end to end test"
         command: julia --project=calibration/test calibration/test/e2e_test.jl
         artifact_paths: "calibration_end_to_end_test/*"
+        soft_fail: true
 
   - group: "Diagnostic EDMFX"
     steps:
@@ -1184,11 +1185,11 @@ steps:
   - label: ":bar_chart: Tabulate performance summary"
     command: "julia --color=yes --project=perf perf/tabulate_perf_summary.jl"
 
-  - label: ":chart_with_downwards_trend: build history"
-    command:
-      - build_history main
-    artifact_paths:
-      - "build_history.html"
+  # - label: ":chart_with_downwards_trend: build history"
+  #   command:
+  #     - build_history main
+  #   artifact_paths:
+  #     - "build_history.html"
 
   - wait
 

diff --git a/Artifacts.toml b/Artifacts.toml
@@ -25,3 +25,14 @@ git-tree-sha1 = "6693f8451b447543952b3d557d733c7e5c670ed3"
     [[ozone_concentrations_lowres.download]]
     sha256 = "908384b32e90c733c2173654afbb974d238a9a516ad8965039077c6ddb29b5f0"
     url = "https://caltech.box.com/shared/static/6c16wt7i1htxq6tadpt1ng2uftjgdtpr.gz"
+
+[earth_orography_30arcseconds]
+git-tree-sha1 = "03dd08fcbf363ed055a176dd7adefb60ff1c3493"
+
+[earth_orography_60arcseconds]
+git-tree-sha1 = "fe19d8dbe7a18ff39588e1f718014b0479d9c0f7"
+lazy = true
+
+    [[earth_orography_60arcseconds.download]]
+    sha256 = "eca66c0701d1c2b9e271742314915ffbf4a0fae92709df611c323f38e019966e"
+    url = "https://caltech.box.com/shared/static/4asrxcgl6xsgenfcug9p0wkkyhtqilgk.gz"
diff --git a/NEWS.md b/NEWS.md
@@ -4,10 +4,24 @@ ClimaAtmos.jl Release Notes
 Main
 -------
 
+v0.27.7
+-------
+
+### Reproducible restarts for simulations with clouds with RRTMGP
+
+- Reset the RNG seed before calling RRTGMP to a known value (the iteration number).
+  When modeling cloud optics, RRTGMP uses a random number generator. Resetting
+  the seed every time RRTGMP is called to a deterministic value ensures that the
+  simulation is fully reproducible and can be restarted in a reproducible way.
+  Disable this option when running production runs.
+
+  Note: Setting this option to `true` is behavior-changing.
+  PR [3382](https://github.com/CliMA/ClimaAtmos.jl/pull/3382)
+
 ### ![][badge-🐛bugfix] Bug fixes
 
 - Update RRTMGP to v0.19.1, which fixes the sea salt aerosol lookup table.
-  Sea salt aerosol is added to the target amip config. 
+  Sea salt aerosol is added to the target amip config.
   PR [3374](https://github.com/CliMA/ClimaAtmos.jl/pull/3374)
 
 - Fixed radiation diagnostics conflicting with each other. Prior to this change,

diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "ClimaAtmos"
 uuid = "b2c96348-7fb7-4fe0-8da9-78d88439e717"
 authors = ["Climate Modeling Alliance"]
-version = "0.27.6"
+version = "0.27.7"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -27,6 +27,7 @@ Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 NCDatasets = "85f8d34a-cbdd-5861-8df4-14fed0d494ab"
 NVTX = "5da4648a-3479-48b8-97b9-01cb529c0a1f"
 RRTMGP = "a01a1ee8-cea4-48fc-987c-fc7878d79da1"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
@@ -59,6 +60,7 @@ Logging = "1"
 NCDatasets = "0.14.2"
 NVTX = "0.3"
 RRTMGP = "0.19"
+Random = "1"
 SciMLBase = "2.12"
 StaticArrays = "1.7"
 Statistics = "1"

diff --git a/calibration/test/Project.toml b/calibration/test/Project.toml
@@ -12,4 +12,4 @@ MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195"
 YAML = "ddb6d928-2868-570f-bddf-ab3f9cf99eb6"
 
 [compat]
-ClimaCalibrate = "0.0.2, 0.0.3"
+ClimaCalibrate = "0.0.2 - 0.0.4"
diff --git a/calibration/test/e2e_test.jl b/calibration/test/e2e_test.jl
@@ -18,6 +18,87 @@ using Test
 
 using Dates
 
+# Debug plots
+function scatter_plot(eki::EKP.EnsembleKalmanProcess)
+    f = CairoMakie.Figure(resolution = (800, 600))
+    ax = CairoMakie.Axis(
+        f[1, 1],
+        ylabel = "Parameter Value",
+        xlabel = "Top of atmosphere radiative SW flux",
+    )
+
+    g = vec.(EKP.get_g(eki; return_array = true))
+    params = vec.((EKP.get_ϕ(prior, eki)))
+
+    for (gg, uu) in zip(g, params)
+        CairoMakie.scatter!(ax, gg, uu)
+    end
+
+    CairoMakie.hlines!(ax, [astronomical_unit], linestyle = :dash)
+    CairoMakie.vlines!(ax, observations, linestyle = :dash)
+
+    output = joinpath(output_dir, "scatter.png")
+    CairoMakie.save(output, f)
+    return output
+end
+
+function param_versus_iter_plot(eki::EKP.EnsembleKalmanProcess)
+    f = CairoMakie.Figure(resolution = (800, 600))
+    ax = CairoMakie.Axis(
+        f[1, 1],
+        ylabel = "Parameter Value",
+        xlabel = "Iteration",
+    )
+    params = EKP.get_ϕ(prior, eki)
+    for (i, param) in enumerate(params)
+        CairoMakie.scatter!(ax, fill(i, length(param)), vec(param))
+    end
+
+    CairoMakie.hlines!(ax, [astronomical_unit]; color = :red, linestyle = :dash)
+
+    output = joinpath(output_dir, "param_vs_iter.png")
+    CairoMakie.save(output, f)
+    return output
+end
+
+# Observation map
+function CAL.observation_map(iteration)
+    single_member_dims = (1,)
+    G_ensemble = Array{Float64}(undef, single_member_dims..., ensemble_size)
+
+    for m in 1:ensemble_size
+        member_path = CAL.path_to_ensemble_member(output_dir, iteration, m)
+        simdir_path = joinpath(member_path, "output_active")
+        if isdir(simdir_path)
+            simdir = SimDir(simdir_path)
+            G_ensemble[:, m] .= process_member_data(simdir)
+        else
+            G_ensemble[:, m] .= NaN
+        end
+    end
+    return G_ensemble
+end
+
+function process_member_data(simdir::SimDir)
+    isempty(simdir.vars) && return NaN
+    rsut =
+        get(simdir; short_name = "rsut", reduction = "average", period = "30d")
+    return slice(average_xy(rsut); time = 30).data
+end
+
+# EKI test
+function minimal_eki_test(eki)
+    params = EKP.get_ϕ(prior, eki)
+    spread = map(var, params)
+
+    # Spread should be heavily decreased as particles have converged
+    @test last(spread) / first(spread) < 0.1
+    # Parameter should be close to true value
+    @test mean(last(params)) ≈ astronomical_unit rtol = 0.02
+end
+
+# Script:
+
 if !(@isdefined backend)
     backend = CAL.get_backend()
 end
@@ -39,7 +120,9 @@ if backend <: CAL.HPCBackend
             Dates.value(t2 - t1) / 1000 / 60
         end / length(wait_times)
 
-    if mean_wait_time_in_mins > 20
+    @show mean_wait_time_in_mins
+
+    if mean_wait_time_in_mins > 10
         @warn """Average wait time for esmbuild is $(round(mean_wait_time_in_mins, digits=2)) minutes. \
                 Cluster is too busy to run this test, exiting"""
         exit()
@@ -52,32 +135,7 @@ const model_interface =
     joinpath(pkgdir(CA), "calibration", "model_interface.jl")
 const output_dir = "calibration_end_to_end_test"
 include(model_interface)
-ensemble_size = 10
-
-# Observation map
-function CAL.observation_map(iteration)
-    single_member_dims = (1,)
-    G_ensemble = Array{Float64}(undef, single_member_dims..., ensemble_size)
-
-    for m in 1:ensemble_size
-        member_path = CAL.path_to_ensemble_member(output_dir, iteration, m)
-        simdir_path = joinpath(member_path, "output_active")
-        if isdir(simdir_path)
-            simdir = SimDir(simdir_path)
-            G_ensemble[:, m] .= process_member_data(simdir)
-        else
-            G_ensemble[:, m] .= NaN
-        end
-    end
-    return G_ensemble
-end
-
-function process_member_data(simdir::SimDir)
-    isempty(simdir.vars) && return NaN
-    rsut =
-        get(simdir; short_name = "rsut", reduction = "average", period = "30d")
-    return slice(average_xy(rsut); time = 30).data
-end
+ensemble_size = 15
 
 # Generate observations
 obs_path = joinpath(experiment_dir, "observations.jld2")
@@ -95,7 +153,7 @@ end
 astronomical_unit = 149_597_870_000
 observations = JLD2.load_object(obs_path)
 noise = 0.1 * I
-n_iterations = 3
+n_iterations = 4
 prior = CAL.get_prior(joinpath(experiment_dir, "prior.toml"))
 experiment_config = CAL.ExperimentConfig(;
     n_iterations,
@@ -106,17 +164,6 @@ experiment_config = CAL.ExperimentConfig(;
     prior,
 )
 
-# Minimal EKI test
-function minimal_eki_test(eki)
-    params = EKP.get_u(eki)
-    spread = map(x -> var(abs.(x)), params)
-
-    # Spread should be heavily decreased as particles have converged
-    @test last(spread) / first(spread) < 0.1
-    # Parameter should be close to true value
-    @test mean(last(params)) ≈ astronomical_unit rtol = 0.02
-end
-
 @info "Running calibration E2E test" backend
 if backend <: CAL.HPCBackend
     test_eki = CAL.calibrate(
@@ -129,6 +176,10 @@ if backend <: CAL.HPCBackend
 else
     test_eki = CAL.calibrate(backend, experiment_config)
 end
+
+scatter_plot(test_eki)
+param_versus_iter_plot(test_eki)
+
 @testset "Test Calibration on $backend" begin
     minimal_eki_test(test_eki)
 end
@@ -145,50 +196,3 @@ end
         @test uu ≈ slurm_uu rtol = 0.02
     end
 end
-
-# Debug plots
-function scatter_plot(eki::EKP.EnsembleKalmanProcess)
-    f = CairoMakie.Figure(resolution = (800, 600))
-    ax = CairoMakie.Axis(
-        f[1, 1],
-        ylabel = "Absolute Parameter Value",
-        xlabel = "Top of atmosphere radiative SW flux",
-    )
-
-    g = vec.(EKP.get_g(eki; return_array = true))
-    params = map(x -> abs.(x), vec.((EKP.get_u(eki))))
-
-    for (gg, uu) in zip(g, params)
-        CairoMakie.scatter!(ax, gg, uu)
-    end
-
-    CairoMakie.hlines!(ax, [astronomical_unit], linestyle = :dash)
-    CairoMakie.vlines!(ax, observations, linestyle = :dash)
-
-    output = joinpath(output_dir, "scatter.png")
-    CairoMakie.save(output, f)
-    return output
-end
-
-scatter_plot(test_eki)
-
-function param_versus_iter_plot(eki::EKP.EnsembleKalmanProcess)
-    f = CairoMakie.Figure(resolution = (800, 600))
-    ax = CairoMakie.Axis(
-        f[1, 1],
-        ylabel = "Parameter Value",
-        xlabel = "Iteration",
-    )
-    params = EKP.get_u(eki)
-    for (i, param) in enumerate(params)
-        CairoMakie.scatter!(ax, fill(i, length(param)), vec(param))
-    end
-
-    CairoMakie.hlines!(ax, [astronomical_unit]; color = :red, linestyle = :dash)
-
-    output = joinpath(output_dir, "param_vs_iter.png")
-    CairoMakie.save(output, f)
-    return output
-end
-
-param_versus_iter_plot(test_eki)
diff --git a/calibration/test/prior.toml b/calibration/test/prior.toml
@@ -1,3 +1,3 @@
 [astronomical_unit]
-prior = "constrained_gaussian(astronomical_unit, 200_000, 100597870000, -Inf, Inf)"
+prior = "constrained_gaussian(astronomical_unit, 60_000_000_000, 100_000_000_000, 200_000, Inf)"
 type = "float"
diff --git a/config/default_configs/default_config.yml b/config/default_configs/default_config.yml
@@ -49,9 +49,6 @@ sleve_s:
 topo_smoothing:
   help: "Choose whether to order-2 smoothing on the LGL mesh"
   value: false
-smoothing_order:
-  help: "Define the surface smoothing kernel factor (integer) [`3 (default)`]"
-  value: 3
 # ODE
 use_newton_rtol:
   help: "Whether to check if the current iteration of Newton's method has an error within a relative tolerance, instead of always taking the maximum number of iterations (only for ClimaTimeSteppers.jl)"
@@ -336,3 +333,6 @@ edmfx_sgs_diffusive_flux:
 updraft_number:
   help: "Sets the number of updrafts for the EDMF scheme"
   value: 1
+radiation_reset_rng_seed:
+  help: "Reset the RNG seed before calling RRTGMP to a known value (the timestep number). When modeling cloud optics, RRTGMP uses a random number generator. Resetting the seed every time RRTGMP is called to a deterministic value ensures that the simulation is fully reproducible and can be restarted in a reproducible way. Disable this option when running production runs. Please note that this flag is only used for `AllSkyRadiation` and `AllSkyRadiationWithClearSkyDiagnostics` radiation modes."
+  value: false