Time averaging and FieldSlicer for NetCDFOutputWriter

.buildkite/pipeline.yml

@@ -196,7 +196,7 @@ steps:
       - "$SVERDRUP_HOME/julia-$JULIA_VERSION/bin/julia --color=yes --project -e 'using Pkg; Pkg.test()'"
     agents:
       queue: Oceananigans
-      architecture: GPU'
+      architecture: GPU
     depends_on: "init_gpu"
 
   - label: "🦍 cpu scripts"

docs/src/model_setup/background_fields.md

@@ -53,7 +53,7 @@ model.background_fields.velocities.u
 FunctionField located at (Face, Cell, Cell)
 ├── func: U
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=1, Ny=1, Nz=1)
-├── clock: Clock(time=0.000 s, iteration=0)
+├── clock: Clock(time=0 seconds, iteration=0)
 └── parameters: nothing
 ```
 
@@ -96,6 +96,6 @@ model.background_fields.tracers.b
 FunctionField located at (Cell, Cell, Cell)
 ├── func: B
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=1, Ny=1, Nz=1)
-├── clock: Clock(time=0.000 s, iteration=0)
+├── clock: Clock(time=0 seconds, iteration=0)
 └── parameters: (α = 3.14, N = 1.0, f = 0.1)
 ```

docs/src/model_setup/boundary_conditions.md

@@ -241,7 +241,7 @@ julia> T_bcs = TracerBoundaryConditions(grid, top = ValueBoundaryCondition(20),
                                            bottom = GradientBoundaryCondition(0.01));
 
 julia> model = IncompressibleModel(grid=grid, boundary_conditions=(u=u_bcs, T=T_bcs))
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=16, Ny=16, Nz=16)
 ├── tracers: (:T, :S)
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(:T, :S),Tuple{Float64,Float64}}}

docs/src/model_setup/buoyancy_and_equation_of_state.md

@@ -21,7 +21,7 @@ end
 julia> grid = RegularCartesianGrid(size=(64, 64, 64), extent=(1, 1, 1));
 
 julia> model = IncompressibleModel(grid=grid, buoyancy=nothing)
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=64, Ny=64, Nz=64)
 ├── tracers: (:T, :S)
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(:T, :S),Tuple{Float64,Float64}}}
@@ -35,7 +35,7 @@ also pass`tracers = ()` to the model constructor.
 
 ```jldoctest buoyancy
 julia> model = IncompressibleModel(grid=grid, buoyancy=nothing, tracers=())
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=64, Ny=64, Nz=64)
 ├── tracers: ()
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(),Tuple{}}}
@@ -50,7 +50,7 @@ constructor. Buoyancy `:b` must be included as a tracer, for example,
 
 ```jldoctest buoyancy
 julia> model = IncompressibleModel(grid=grid, buoyancy=BuoyancyTracer(), tracers=(:b))
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=64, Ny=64, Nz=64)
 ├── tracers: (:b,)
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(:b,),Tuple{Float64}}}
@@ -65,7 +65,7 @@ To evolve temperature $T$ and salinity $S$ and diagnose the buoyancy, you can pa
 
 ```jldoctest buoyancy
 julia> model = IncompressibleModel(grid=grid, buoyancy=SeawaterBuoyancy())
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=64, Ny=64, Nz=64)
 ├── tracers: (:T, :S)
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(:T, :S),Tuple{Float64,Float64}}}
@@ -86,7 +86,7 @@ SeawaterBuoyancy{Float64}: g = 1.3
 └── equation of state: LinearEquationOfState{Float64}: α = 1.67e-04, β = 7.80e-04
 
 julia> model = IncompressibleModel(grid=grid, buoyancy=buoyancy)
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=64, Ny=64, Nz=64)
 ├── tracers: (:T, :S)
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(:T, :S),Tuple{Float64,Float64}}}

docs/src/model_setup/clock.md

@@ -13,15 +13,15 @@ end
 
 ```jldoctest
 julia> clock = Clock(time=0.0)
-Clock{Float64}: time = 0.000 s, iteration = 0, stage = 1
+Clock{Float64}: time = 0 seconds, iteration = 0, stage = 1
 ```
 
 but can be modified to start the model clock at some other time.
 For example, passing
 
 ```jldoctest
 julia> clock = Clock(time=3600.0)
-Clock{Float64}: time = 1.000 hr, iteration = 0, stage = 1
+Clock{Float64}: time = 1 hour, iteration = 0, stage = 1
 ```
 
 to the constructor for `IncompressibleModel` causes the simulation

docs/src/model_setup/diagnostics.md

@@ -11,89 +11,3 @@ time or be specified at any later time and appended (or assigned with a key valu
 Most diagnostics can be run at specified frequencies (e.g. every 25 time steps) or specified intervals (e.g. every
 15 minutes of simulation time). If you'd like to run a diagnostic on demand then do not specify any intervals
 (and do not add it to `simulation.diagnostics`).
-
-We describe the [`Average`](@ref) diagnostic in detail below but see the API documentation for other diagnostics such
-as [`TimeSeries`](@ref), [`FieldMaximum`](@ref), [`CFL`](@ref), and [`NaNChecker`](@ref).
-
-## Horizontal averages
-
-You can create a horizontal `Average` diagnostic by passing a field to the constructor, e.g.
-
-```@meta
-DocTestSetup = quote
-    using Oceananigans
-    using Oceananigans.Diagnostics
-end
-```
-
-```jldoctest
-julia> model = IncompressibleModel(grid=RegularCartesianGrid(size=(4, 4, 4), extent=(1, 1, 1)));
-
-julia> T_avg = Average(model.tracers.T, dims=(1, 2));
-
-julia> T_avg(model)  # Compute horizontal average of T on demand
-1×1×6 Array{Float64,3}:
-[:, :, 1] =
- 0.0
-
-[:, :, 2] =
- 0.0
-
-[:, :, 3] =
- 0.0
-
-[:, :, 4] =
- 0.0
-
-[:, :, 5] =
- 0.0
-
-[:, :, 6] =
- 0.0
-```
-
-which can then be called on-demand via `T_avg(model)` to return the horizontally averaged temperature. Notice that
-halo regions are included in the output of the horizontal average. When running on the GPU you may want it to return
-an `Array` instead of a `CuArray` in case you want to save the horizontal average to disk in which case you'd want to
-construct it like
-
-```jldoctest
-julia> model = IncompressibleModel(grid=RegularCartesianGrid(size=(4, 4, 4), extent=(1, 1, 1)));
-
-julia> T_avg = Average(model.tracers.T, dims=(1, 2), return_type=Array);
-
-julia> T_avg(model)  # Will always return an Array
-1×1×6 Array{Float64,3}:
-[:, :, 1] =
- 0.0
-
-[:, :, 2] =
- 0.0
-
-[:, :, 3] =
- 0.0
-
-[:, :, 4] =
- 0.0
-
-[:, :, 5] =
- 0.0
-
-[:, :, 6] =
- 0.0
-```
-
-You can also use pass an abstract operator to take the horizontal average of any diagnosed quantity. For example, to
-compute the horizontal average of the vertical component of vorticity:
-
-```julia
-model = IncompressibleModel(grid=RegularCartesianGrid(size=(16, 16, 16), extent=(1, 1, 1)))
-simulation = Simulation(model, Δt=6, stop_iteration=10)
-
-u, v, w = model.velocities
-ζ = ∂x(v) - ∂y(u)
-ζ_avg = Average(ζ, dims=(1, 2))
-simulation.diagnostics[:vorticity_profile] = ζ_avg
-```
-
-See [`Average`](@ref) for more details and options.

docs/src/model_setup/output_writers.md

@@ -28,7 +28,7 @@ simulation = Simulation(model, Δt=12, stop_time=3600);
 fields = Dict("u" => model.velocities.u, "T" => model.tracers.T);
 
 simulation.output_writers[:field_writer] =
-    NetCDFOutputWriter(model, fields, filename="output_fields.nc", time_interval=60)
+    NetCDFOutputWriter(model, fields, filepath="output_fields.nc", time_interval=60)
 
 # output
 NetCDFOutputWriter (time_interval=60): output_fields.nc
@@ -38,8 +38,8 @@ NetCDFOutputWriter (time_interval=60): output_fields.nc
 
 ```jldoctest netcdf1
 simulation.output_writers[:surface_slice_writer] =
-    NetCDFOutputWriter(model, fields, filename="output_surface_xy_slice.nc",
-                       time_interval=60, zC=grid.Nz, zF=grid.Nz+1)
+    NetCDFOutputWriter(model, fields, filepath="output_surface_xy_slice.nc",
+                       time_interval=60, field_slicer=FieldSlicer(k=grid.Nz))
 
 # output
 NetCDFOutputWriter (time_interval=60): output_surface_xy_slice.nc
@@ -79,7 +79,7 @@ global_attributes = Dict("location" => "Bay of Fundy", "onions" => 7);
 
 simulation.output_writers[:stuff] =
     NetCDFOutputWriter(model, outputs,
-                       iteration_interval=1, filename="stuff.nc", dimensions=dims, verbose=true,
+                       iteration_interval=1, filepath="stuff.nc", dimensions=dims, verbose=true,
                        global_attributes=global_attributes, output_attributes=output_attributes)
 
 # output
@@ -114,7 +114,7 @@ function init_save_some_metadata(file, model)
     file["parameters/density"] = 1027
 end
 
-T_avg =  Average(model.tracers.T, dims=(1, 2))
+T_avg =  AveragedField(model.tracers.T, dims=(1, 2))
 
 outputs = Dict(
     :w => model -> model.velocities.u,

docs/src/model_setup/tracers.md

@@ -13,7 +13,7 @@ end
 julia> grid = RegularCartesianGrid(size=(64, 64, 64), extent=(1, 1, 1));
 
 julia> model = IncompressibleModel(grid=grid)
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=64, Ny=64, Nz=64)
 ├── tracers: (:T, :S)
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(:T, :S),Tuple{Float64,Float64}}}
@@ -43,7 +43,7 @@ quantities $C_1$, CO₂, and nitrogen as additional passive tracers you could se
 
 ```jldoctest tracers
 julia> model = IncompressibleModel(grid=grid, tracers=(:T, :S, :C₁, :CO₂, :nitrogen))
-IncompressibleModel{CPU, Float64}(time = 0.000 s, iteration = 0)
+IncompressibleModel{CPU, Float64}(time = 0 seconds, iteration = 0)
 ├── grid: RegularCartesianGrid{Float64, Periodic, Periodic, Bounded}(Nx=64, Ny=64, Nz=64)
 ├── tracers: (:T, :S, :C₁, :CO₂, :nitrogen)
 ├── closure: IsotropicDiffusivity{Float64,NamedTuple{(:T, :S, :C₁, :CO₂, :nitrogen),NTuple{5,Float64}}}

examples/eady_turbulence.jl

@@ -95,10 +95,11 @@
 # | $ κ_z $    | Laplacian vertical diffusivity | $ 10^{-2} $ | $ \mathrm{m^2 s^{-1}} $ |
 # | $ \varkappa_h $    | Biharmonic horizontal diffusivity | $ 10^{-2} \times \Delta x^4 / \mathrm{day} $ | $ \mathrm{m^4 s^{-1}} $ |
 #
-# We start off by importing `Oceananigans` and some convenient aliases for dimensions:
+# We start off by importing `Oceananigans`, some convenient aliases for dimensions, and a function
+# that generates a pretty string from a number that represents 'time' in seconds:
 
 using Oceananigans, Printf
-using Oceananigans.Utils: hour, day
+using Oceananigans.Utils: hour, day, prettytime
 
 # ## The grid
 #

examples/langmuir_turbulence.jl

@@ -170,6 +170,7 @@ nothing # hide
 # maximum absolute value of $u, v, w$ and the current wall clock time.
 
 using Oceananigans.Diagnostics, Printf
+using Oceananigans.Utils: prettytime
 
 umax = FieldMaximum(abs, model.velocities.u)
 vmax = FieldMaximum(abs, model.velocities.v)

src/AbstractOperations/AbstractOperations.jl

@@ -1,6 +1,6 @@
 module AbstractOperations
 
-export ∂x, ∂y, ∂z, @at, Computation, compute!, @unary, @binary, @multiary
+export ∂x, ∂y, ∂z, @at, @unary, @binary, @multiary
 
 using Base: @propagate_inbounds
 
@@ -20,7 +20,6 @@ using Oceananigans.Fields: gpufriendly
 using Oceananigans.Operators: interpolation_operator
 using Oceananigans.Architectures: device
 using Oceananigans.Models: AbstractModel
-using Oceananigans.Diagnostics: Average, normalize_sum!
 
 import Oceananigans.Architectures: architecture
 import Oceananigans.Fields: data, compute!
@@ -52,7 +51,6 @@ include("binary_operations.jl")
 include("multiary_operations.jl")
 include("derivatives.jl")
 
-include("computations.jl")
 include("show_abstract_operations.jl")
 include("averages_of_operations.jl")