Convert outer constructors to inner constructors

CliMA · Jul 20, 2021 · ada7396 · ada7396
1 parent b8b7595
commit ada7396
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Showing 4 changed files with 206 additions and 210 deletions.
diff --git a/src/EDMF_Environment.jl b/src/EDMF_Environment.jl
@@ -27,80 +27,6 @@ function set_bcs(self::EnvironmentVariable_2m, Gr::Grid)
     end
 end
 
-function EnvironmentVariables(namelist, Gr::Grid)
-    nz = Gr.nzg
-
-    W = EnvironmentVariable(nz, "full", "velocity", "w", "m/s")
-    QT = EnvironmentVariable(nz, "half", "scalar", "qt", "kg/kg")
-    QL = EnvironmentVariable(nz, "half", "scalar", "ql", "kg/kg")
-    RH = EnvironmentVariable(nz, "half", "scalar", "RH", "%")
-    H = EnvironmentVariable(nz, "half", "scalar", "thetal", "K")
-    THL = EnvironmentVariable(nz, "half", "scalar", "thetal", "K")
-    T = EnvironmentVariable(nz, "half", "scalar", "temperature", "K")
-    B = EnvironmentVariable(nz, "half", "scalar", "buoyancy", "m^2/s^3")
-    Area = EnvironmentVariable(nz, "half", "scalar", "env_area", "-")
-    cloud_fraction = EnvironmentVariable(nz, "half", "scalar", "env_cloud_fraction", "-")
-
-    # TODO - the flag setting is repeated from Variables.pyx logic
-    calc_tke = true
-    calc_tke = try
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["calculate_tke"]
-    catch
-        nothing
-    end
-
-    calc_scalar_var = try
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["calc_scalar_var"]
-    catch
-        println("Defaulting to non-calculation of scalar variances")
-        false
-    end
-
-    EnvThermo_scheme = try
-        string(namelist["thermodynamics"]["sgs"])
-    catch
-        println("Defaulting to saturation adjustment and microphysics with respect to environmental means")
-        "mean"
-    end
-
-    if calc_tke
-        TKE = EnvironmentVariable_2m(nz, "half", "scalar", "tke", "m^2/s^2")
-    end
-
-    if calc_scalar_var
-        QTvar = EnvironmentVariable_2m(nz, "half", "scalar", "qt_var", "kg^2/kg^2")
-        Hvar = EnvironmentVariable_2m(nz, "half", "scalar", "thetal_var", "K^2")
-        HQTcov = EnvironmentVariable_2m(nz, "half", "scalar", "thetal_qt_covar", "K(kg/kg)")
-    end
-
-    if EnvThermo_scheme == "quadrature"
-        if (calc_scalar_var == false)
-            error("EDMF_Environment.pyx: scalar variance has to be calculated for quadrature saturation and microphysics")
-        end
-    end
-
-    return EnvironmentVariables(;
-        Gr,
-        W,
-        Area,
-        QT,
-        QL,
-        H,
-        THL,
-        RH,
-        T,
-        B,
-        cloud_fraction,
-        TKE,
-        Hvar,
-        QTvar,
-        HQTcov,
-        calc_tke,
-        calc_scalar_var,
-        EnvThermo_scheme,
-    )
-end
-
 function initialize_io(self::EnvironmentVariables, Stats::NetCDFIO_Stats)
     add_profile(Stats, "env_w")
     add_profile(Stats, "env_qt")

diff --git a/src/EDMF_Rain.jl b/src/EDMF_Rain.jl
@@ -7,48 +7,6 @@ function set_bcs(self::RainVariable, Gr::Grid)
     return
 end
 
-function RainVariables(namelist, Gr::Grid)
-    nzg = Gr.nzg
-
-    QR = RainVariable(nzg, "qr_mean", "kg/kg")
-    # temporary variables for diagnostics to know where the rain is coming from
-    Upd_QR = RainVariable(nzg, "upd_qr", "kg/kg")
-    Env_QR = RainVariable(nzg, "env_qr", "kg/kg")
-    # in the future we could test prognostic equations for stratiform and updraft rain
-    RainArea = RainVariable(nzg, "rain_area", "rain_area_fraction [-]")
-    Upd_RainArea = RainVariable(nzg, "upd_rain_area", "updraft_rain_area_fraction [-]")
-    Env_RainArea = RainVariable(nzg, "env_rain_area", "environment_rain_area_fraction [-]")
-
-    mean_rwp = 0.0
-    upd_rwp = 0.0
-    env_rwp = 0.0
-
-    rain_model = try
-        string(namelist["microphysics"]["rain_model"])
-    catch
-        println("EDMF_Rain: defaulting to no rain")
-        "None"
-    end
-
-    if !(rain_model in ["None", "cutoff", "clima_1m"])
-        error("rain model not recognized")
-    end
-
-    return RainVariables(;
-        rain_model,
-        mean_rwp,
-        env_rwp,
-        upd_rwp,
-        Gr,
-        QR,
-        RainArea,
-        Upd_QR,
-        Upd_RainArea,
-        Env_QR,
-        Env_RainArea,
-    )
-end
-
 function initialize_io(self::RainVariables, Stats::NetCDFIO_Stats)
     add_profile(Stats, "qr_mean")
     add_profile(Stats, "updraft_qr")

diff --git a/src/Variables.jl b/src/Variables.jl
@@ -67,100 +67,6 @@ function set_bcs(self::VariableDiagnostic, Gr::Grid)
     return
 end
 
-function GridMeanVariables(namelist, Gr::Grid, Ref::ReferenceState)
-    lwp = 0.0
-    cloud_base = 0.0
-    cloud_top = 0.0
-    cloud_cover = 0.0
-
-    U = VariablePrognostic(Gr.nzg, "half", "velocity", "sym", "u", "m/s")
-    V = VariablePrognostic(Gr.nzg, "half", "velocity", "sym", "v", "m/s")
-    # Just leave this zero for now!
-    W = VariablePrognostic(Gr.nzg, "full", "velocity", "asym", "v", "m/s")
-
-    # Create thermodynamic variables
-    QT = VariablePrognostic(Gr.nzg, "half", "scalar", "sym", "qt", "kg/kg")
-    RH = VariablePrognostic(Gr.nzg, "half", "scalar", "sym", "RH", "%")
-
-    H = VariablePrognostic(Gr.nzg, "half", "scalar", "sym", "thetal", "K")
-    t_to_prog_fp = t_to_thetali_c
-    prog_to_t_fp = eos_first_guess_thetal
-
-    # Diagnostic Variables--same class as the prognostic variables, but we append to diagnostics list
-    QL = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "ql", "kg/kg")
-    T = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "temperature", "K")
-    B = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "buoyancy", "m^2/s^3")
-    THL = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "thetal", "K")
-
-    cloud_fraction = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "cloud fraction", "-")
-
-    # TKE   TODO   repeated from EDMF_Environment.pyx logic
-    calc_tke = true
-    try
-        calc_tke = namelist["turbulence"]["EDMF_PrognosticTKE"]["calculate_tke"]
-    catch
-    end
-
-    calc_scalar_var = try
-        namelist["turbulence"]["EDMF_PrognosticTKE"]["calc_scalar_var"]
-    catch
-        false
-    end
-
-    EnvThermo_scheme = try
-        string(namelist["thermodynamics"]["sgs"])
-    catch
-        "mean"
-    end
-
-    #Now add the 2nd moment variables
-    if calc_tke
-        TKE = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "tke", "m^2/s^2")
-        W_third_m = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "W_third_m", "m^3/s^3")
-    end
-
-    if calc_scalar_var
-        QTvar = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "qt_var", "kg^2/kg^2")
-        QT_third_m = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "qt_third_m", "kg^3/kg^3")
-        Hvar = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "thetal_var", "K^2")
-        H_third_m = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "thetal_third_m", "-")
-        HQTcov = VariableDiagnostic(Gr.nzg, "half", "scalar", "sym", "thetal_qt_covar", "K(kg/kg)")
-    end
-
-    return GridMeanVariables(;
-        Gr,
-        Ref,
-        lwp,
-        cloud_base,
-        cloud_top,
-        cloud_cover,
-        U,
-        V,
-        W,
-        QT,
-        RH,
-        H,
-        t_to_prog_fp,
-        prog_to_t_fp,
-        QL,
-        T,
-        B,
-        THL,
-        cloud_fraction,
-        calc_tke,
-        calc_scalar_var,
-        EnvThermo_scheme,
-        TKE,
-        W_third_m,
-        QTvar,
-        QT_third_m,
-        Hvar,
-        H_third_m,
-        HQTcov,
-    )
-
-end
-
 function zero_tendencies(self::GridMeanVariables)
     zero_tendencies(self.U, self.Gr)
     zero_tendencies(self.V, self.Gr)