Merge pull request #130 from milankl/whatsnext

get it mode specific and tendency by u_n+1-u_n etc

Author: Milan K

src/DefaultParameters.jl

@@ -101,6 +101,7 @@
     init_run_id::Int=0                  # run id for restart from run number
     init_starti::Int=-1                 # timestep to start from (-1 meaning last)
     get_id_mode::String="continue"      # How to determine the run id: "continue" or "fill"
+    run_id::Int=-1                      # Output with a specific run id
 
     # ASSERT - CHECK THAT THE INPUT PARAMETERS MAKE SENSE
     @assert all((nx,Lx,L_ratio) .> 0.)  "nx, Lx, L_ratio have to be >0"
@@ -133,7 +134,7 @@
     @assert initial_cond in ["rest", "ncfile"] "Initial conditions '$initial_cond' unsupported."
     @assert init_run_id >= 0 "Initial condition run id, init_run_id, has to be >= 0, $init_run_id given."
     @assert init_starti > 0 || init_starti == -1 "Start index, init_starti, has to be >0 || -1, $init_starti given."
-    @assert get_id_mode in ["continue","fill"] "get_id_mode $get_id_mode unsupported."
+    @assert get_id_mode in ["continue","fill","specific"] "get_id_mode $get_id_mode unsupported."
 end
 
 """

src/Output.jl

@@ -88,42 +88,55 @@ function output_nc!(i::Int,
         @unpack f_q,ep,dtint = S.grid
 
         # CUT OFF HALOS
-        @views u = Prog.u[halo+1:end-halo,halo+1:end-halo]
-        @views v = Prog.v[halo+1:end-halo,halo+1:end-halo]
-        @views η = Prog.η[haloη+1:end-haloη,haloη+1:end-haloη]
-        @views sst = Prog.sst[halosstx+1:end-halosstx,halossty+1:end-halossty]
-        @views ζ = (dvdx[2:end-1,2:end-1]-dudy[2+ep:end-1,2:end-1])./abs.(f_q)
-        @views du = Diag.Tendencies.du[halo+1:end-halo,halo+1:end-halo]
-        @views dv = Diag.Tendencies.dv[halo+1:end-halo,halo+1:end-halo]
-        @views dη = Diag.Tendencies.dη[haloη+1:end-haloη,haloη+1:end-haloη]
+        # @views u = Prog.u[halo+1:end-halo,halo+1:end-halo]
+        # @views v = Prog.v[halo+1:end-halo,halo+1:end-halo]
+        # @views η = Prog.η[haloη+1:end-haloη,haloη+1:end-haloη]
+        # @views sst = Prog.sst[halosstx+1:end-halosstx,halossty+1:end-halossty]
+        # @views ζ = (dvdx[2:end-1,2:end-1]-dudy[2+ep:end-1,2:end-1])./abs.(f_q)
+        # @views du = Diag.Tendencies.du[halo+1:end-halo,halo+1:end-halo]
+        # @views dv = Diag.Tendencies.dv[halo+1:end-halo,halo+1:end-halo]
+        # @views dη = Diag.Tendencies.dη[haloη+1:end-haloη,haloη+1:end-haloη]
+
+        # As output is before copyto!(u,u0), take u0,v0,η0
+        @views u = Float32.(Diag.RungeKutta.u0[halo+1:end-halo,halo+1:end-halo])
+        @views v = Float32.(Diag.RungeKutta.v0[halo+1:end-halo,halo+1:end-halo])
+        @views η = Float32.(Diag.RungeKutta.η0[haloη+1:end-haloη,haloη+1:end-haloη])
+        
+        @views sst = Float32.(Prog.sst[halosstx+1:end-halosstx,halossty+1:end-halossty])
+        @views ζ = Float32.((dvdx[2:end-1,2:end-1]-dudy[2+ep:end-1,2:end-1])./abs.(f_q))
+
+        # Tendencies calculate from the last time step, du = u_n+1-u_n etc
+        @views du = u-Float32.(Prog.u[halo+1:end-halo,halo+1:end-halo])
+        @views dv = v-Float32.(Prog.v[halo+1:end-halo,halo+1:end-halo])
+        @views dη = η-Float32.(Prog.η[haloη+1:end-haloη,haloη+1:end-haloη])
 
         # WRITING THE VARIABLES
         if ncs.u != nothing
-            NetCDF.putvar(ncs.u,"u",Float32.(u),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.u,"u",u,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.v != nothing
-            NetCDF.putvar(ncs.v,"v",Float32.(v),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.v,"v",v,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.η != nothing
-            NetCDF.putvar(ncs.η,"eta",Float32.(η),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.η,"eta",η,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.sst != nothing
-            NetCDF.putvar(ncs.sst,"sst",Float32.(sst),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.sst,"sst",sst,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.q != nothing
-            NetCDF.putvar(ncs.q,"q",Float32.(q),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.q,"q",q,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.ζ != nothing
-            NetCDF.putvar(ncs.ζ,"relvort",Float32.(ζ),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.ζ,"relvort",ζ,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.du != nothing
-            NetCDF.putvar(ncs.du,"du",Float32.(du),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.du,"du",du,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.dv != nothing
-            NetCDF.putvar(ncs.dv,"dv",Float32.(dv),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.dv,"dv",dv,start=[1,1,iout],count=[-1,-1,1])
         end
         if ncs.dη != nothing
-            NetCDF.putvar(ncs.dη,"deta",Float32.(dη),start=[1,1,iout],count=[-1,-1,1])
+            NetCDF.putvar(ncs.dη,"deta",dη,start=[1,1,iout],count=[-1,-1,1])
         end
 
 
@@ -181,14 +194,15 @@ function get_run_id_path(S::ModelSetup)
                 runpath = joinpath(outpath,"run"*@sprintf("%04d",run_id))
                 mkdir(runpath)
 
-            # elseif order == "specific" # specify the run_id as input argument
-            #     runpath = joinpath(outpath,"run"*@sprintf("%04d",run_id))
-            #     try # create folder if not existent
-            #         mkdir(runpath)
-            #     catch # else rm folder and create new one
-            #         rm(runpath,recursive=true)
-            #         mkdir(runpath)
-            #     end
+            elseif get_id_mode == "specific" # specify the run_id as input argument
+                @unpack run_id = S.parameters
+                runpath = joinpath(outpath,"run"*@sprintf("%04d",run_id))
+                try # create folder if not existent
+                    mkdir(runpath)
+                catch # else rm folder and create new one
+                    rm(runpath,recursive=true)
+                    mkdir(runpath)
+                end
 
             elseif get_id_mode == "continue" # find largest folder and count one up
                 run_id = maximum(existing_runs)+1

src/TimeIntegration.jl

@@ -88,10 +88,6 @@ function time_integration(  Prog::PrognosticVars{Tprog},
             add_drag_diff_tendencies!(u0,v0,Diag,S)
         end
 
-        # RK3/4 copy back from substeps
-        copyto!(u,u0)
-        copyto!(v,v0)
-        copyto!(η,η0)
         t += dtint
 
         # TRACER ADVECTION
@@ -105,6 +101,11 @@ function time_integration(  Prog::PrognosticVars{Tprog},
         if feedback.nans_detected
             break
         end
+
+        # RK3/4 copy back from substeps
+        copyto!(u,u0)
+        copyto!(v,v0)
+        copyto!(η,η0)
     end
 
     # finalise feedback and output