Merge pull request #477 from SpeedyWeather/ncc/linting

Add space after semicolon

README.md

@@ -31,7 +31,7 @@ With v0.6 the interface to SpeedyWeather.jl consist of 4 steps: define the grid,
 
 ```julia
 spectral_grid = SpectralGrid(trunc=31, Grid=OctahedralGaussianGrid, nlev=8)
-model = PrimitiveDryModel(;spectral_grid, orography = EarthOrography(spectral_grid))
+model = PrimitiveDryModel(; spectral_grid, orography = EarthOrography(spectral_grid))
 simulation = initialize!(model)
 run!(simulation, period=Day(10), output=true)
 ```

docs/src/callbacks.md

@@ -74,7 +74,7 @@ function SpeedyWeather.initialize!(
     callback.maximum_surface_wind_speed = zeros(progn.clock.n_timesteps + 1)
     
     # where surface (=lowermost model layer) u, v on the grid are stored
-    (;u_grid, v_grid) = diagn.layers[diagn.nlev].grid_variables
+    (; u_grid, v_grid) = diagn.layers[diagn.nlev].grid_variables
     
     # maximum wind speed of initial conditions
     callback.maximum_surface_wind_speed[1] = max_2norm(u_grid, v_grid)
@@ -124,7 +124,7 @@ function SpeedyWeather.callback!(
     i = callback.timestep_counter
 
     # where surface (=lowermost model layer) u, v on the grid are stored
-    (;u_grid, v_grid) = diagn.layers[diagn.nlev].grid_variables
+    (; u_grid, v_grid) = diagn.layers[diagn.nlev].grid_variables
 
     # maximum wind speed at current time step
     callback.maximum_surface_wind_speed[i] = max_2norm(u_grid, v_grid)
@@ -188,7 +188,7 @@ Meaning that callbacks can be added before and after model construction
 ```@example callbacks
 spectral_grid = SpectralGrid()
 callbacks = CallbackDict(:callback_added_before => NoCallback())
-model = PrimitiveWetModel(;spectral_grid, callbacks)
+model = PrimitiveWetModel(; spectral_grid, callbacks)
 add!(model.callbacks, :callback_added_afterwards => NoCallback())
 ```
 Let us add two more meaningful callbacks

docs/src/forcing_drag.md

@@ -251,9 +251,9 @@ be used throughout model integration.
 But in SpeedyWeather we typically use the [SpectralGrid](@ref) object to pass on the information of
 the resolution (and number format) so we want a generator function like
 ```@example extend
-function StochasticStirring(SG::SpectralGrid;kwargs...)
-    (;trunc, nlat) = SG
-    return StochasticStirring{SG.NF}(;trunc, nlat, kwargs...)
+function StochasticStirring(SG::SpectralGrid; kwargs...)
+    (; trunc, nlat) = SG
+    return StochasticStirring{SG.NF}(; trunc, nlat, kwargs...)
 end
 ```
 Which allows us to do
@@ -275,7 +275,7 @@ function SpeedyWeather.initialize!( forcing::StochasticStirring,
                                     model::ModelSetup)
     
     # precompute forcing strength, scale with radius^2 as is the vorticity equation
-    (;radius) = model.spectral_grid
+    (; radius) = model.spectral_grid
     A = radius^2 * forcing.strength
     
     # precompute noise and auto-regressive factor, packed in RefValue for mutability
@@ -285,7 +285,7 @@ function SpeedyWeather.initialize!( forcing::StochasticStirring,
     forcing.b[] = exp(-dt/τ)
     
     # precompute the latitudinal mask
-    (;Grid, nlat_half) = model.spectral_grid
+    (; Grid, nlat_half) = model.spectral_grid
     latd = RingGrids.get_latd(Grid, nlat_half)
     
     for j in eachindex(forcing.lat_mask)
@@ -366,7 +366,7 @@ function forcing!(  diagn::DiagnosticVariablesLayer,
     a = forcing.a[]    # = sqrt(1 - exp(-2dt/τ))
     b = forcing.b[]    # = exp(-dt/τ)
     
-    (;S) = forcing
+    (; S) = forcing
     for lm in eachindex(S)
         # Barnes and Hartmann, 2011 Eq. 2
         Qi = 2rand(Complex{NF}) - (1 + im)   # ~ [-1, 1] in complex
@@ -381,7 +381,7 @@ function forcing!(  diagn::DiagnosticVariablesLayer,
     RingGrids._scale_lat!(S_grid, forcing.lat_mask)
     
     # back to spectral space
-    (;vor_tend) = diagn.tendencies
+    (; vor_tend) = diagn.tendencies
     SpeedyTransforms.spectral!(vor_tend, S_grid, spectral_transform)
 
     return nothing
@@ -443,7 +443,7 @@ and just put them together as you like, and as long as you follow some rules.
 spectral_grid = SpectralGrid(trunc=42, nlev=1)
 stochastic_stirring = StochasticStirring(spectral_grid, latitude=-45)
 initial_conditions = StartFromRest()
-model = BarotropicModel(;spectral_grid, initial_conditions, forcing=stochastic_stirring)
+model = BarotropicModel(; spectral_grid, initial_conditions, forcing=stochastic_stirring)
 simulation = initialize!(model)
 run!(simulation)
 ```

docs/src/grids.md

@@ -130,7 +130,7 @@ changes when `dealiasing` is passed onto `SpectralGrid` on the `FullGaussianGrid
 | 42    | 3          | 192x96                |
 | ...   | ...        | ...                   |
 
-You will obtain this information every time you create a `SpectralGrid(;Grid, trunc, dealiasing)`.
+You will obtain this information every time you create a `SpectralGrid(; Grid, trunc, dealiasing)`.
 
 ## [Full Gaussian grid](@id FullGaussianGrid)
 

docs/src/how_to_run_speedy.md

@@ -119,11 +119,11 @@ also `Δt` which is a scaled time step used internally, because SpeedyWeather.jl
 [scales the equations](@ref scaled_swm) with the radius of the Earth,
 but this is largely hidden (except here) from the user. With this new 
 `Leapfrog` time stepper constructed we can create a model by passing
-on the components (they are keyword arguments so either use `;time_stepping`
+on the components (they are keyword arguments so either use `; time_stepping`
 for which the naming must match, or `time_stepping=my_time_stepping` with
 any name)
 ```@example howto
-model = ShallowWaterModel(;spectral_grid, time_stepping)
+model = ShallowWaterModel(; spectral_grid, time_stepping)
 ```
 This logic continues for all model components. See the [Model setups](@ref)
 for examples. All model components are also subtype (i.e. `<:`) of
@@ -156,9 +156,9 @@ parameterizations. Conceptually you construct these different models with
 spectral_grid = SpectralGrid(trunc=..., ...)
 component1 = SomeComponent(spectral_grid, parameter1=..., ...)
 component2 = SomeOtherComponent(spectral_grid, parameter2=..., ...)
-model = BarotropicModel(;spectral_grid, all_other_components..., ...)
+model = BarotropicModel(; spectral_grid, all_other_components..., ...)
 ```
-or `model = ShallowWaterModel(;spectral_grid, ...)`, etc.
+or `model = ShallowWaterModel(; spectral_grid, ...)`, etc.
 
 ## [Model initialization](@id initialize)
 

docs/src/output.md

@@ -12,7 +12,7 @@ The output writer is a component of every Model, i.e. `BarotropicModel`, `Shallo
 using SpeedyWeather
 spectral_grid = SpectralGrid()
 output = OutputWriter(spectral_grid, ShallowWater)
-model = ShallowWaterModel(;spectral_grid, output=output)
+model = ShallowWaterModel(; spectral_grid, output=output)
 nothing # hide
 ```
 
@@ -28,7 +28,7 @@ Then we can also pass on further keyword arguments. So let's start with an examp
 If we want to increase the frequency of the output we can choose `output_dt` (default `=Hour(6)`) like so
 ```@example netcdf
 output = OutputWriter(spectral_grid, ShallowWater, output_dt=Hour(1))
-model = ShallowWaterModel(;spectral_grid, output=output)
+model = ShallowWaterModel(; spectral_grid, output=output)
 nothing # hide
 ```
 which will now output every hour. It is important to pass on the new output writer `output` to the
@@ -45,7 +45,7 @@ seconds. Depending on the output frequency (we chose `output_dt = Hour(1)` above
 this will be slightly adjusted during model initialization:
 ```@example netcdf
 output = OutputWriter(spectral_grid, ShallowWater, output_dt=Hour(1))
-model = ShallowWaterModel(;spectral_grid, time_stepping, output)
+model = ShallowWaterModel(; spectral_grid, time_stepping, output)
 simulation = initialize!(model)
 model.time_stepping.Δt_sec
 ```
@@ -60,7 +60,7 @@ time_stepping.Δt_sec
 and a little info will be printed to explain that even though you wanted
 `output_dt = Hour(1)` you will not actually get this upon initialization:
 ```@example netcdf
-model = ShallowWaterModel(;spectral_grid, time_stepping, output)
+model = ShallowWaterModel(; spectral_grid, time_stepping, output)
 simulation = initialize!(model)
 ```
 
@@ -77,7 +77,7 @@ which is a bit ugly, that's why `adjust_with_output=true` is the default. In tha
 ```@example netcdf
 time_stepping = Leapfrog(spectral_grid, adjust_with_output=true)
 output = OutputWriter(spectral_grid, ShallowWater, output_dt=Hour(1))
-model = ShallowWaterModel(;spectral_grid, time_stepping, output)
+model = ShallowWaterModel(; spectral_grid, time_stepping, output)
 simulation = initialize!(model)
 run!(simulation, period=Day(1), output=true)
 id = model.output.id

docs/src/setups.md

@@ -12,7 +12,7 @@ complicated setups.
     spectral_grid = SpectralGrid(trunc=63, nlev=1)
     still_earth = Earth(spectral_grid, rotation=0)
     initial_conditions = StartWithRandomVorticity()
-    model = BarotropicModel(;spectral_grid, initial_conditions, planet=still_earth)
+    model = BarotropicModel(; spectral_grid, initial_conditions, planet=still_earth)
     simulation = initialize!(model)
     run!(simulation, period=Day(20))
     ```
@@ -46,7 +46,7 @@ horizontal wavenumber, and the amplitude is ``10^{-5}\text{s}^{-1}``.
 Now we want to construct a `BarotropicModel`
 with these
 ```@example barotropic_setup
-model = BarotropicModel(;spectral_grid, initial_conditions, planet=still_earth)
+model = BarotropicModel(; spectral_grid, initial_conditions, planet=still_earth)
 nothing # hide
 ```
 The `model` contains all the parameters, but isn't initialized yet, which we can do
@@ -71,7 +71,7 @@ with default settings. More options on output in [NetCDF output](@ref).
     spectral_grid = SpectralGrid(trunc=63, nlev=1)
     orography = NoOrography(spectral_grid)
     initial_conditions = ZonalJet()
-    model = ShallowWaterModel(;spectral_grid, orography, initial_conditions)
+    model = ShallowWaterModel(; spectral_grid, orography, initial_conditions)
     simulation = initialize!(model)
     run!(simulation, period=Day(6))
     ```
@@ -97,7 +97,7 @@ initial_conditions = ZonalJet()
 The jet sits at 45˚N with a maximum velocity of 80m/s and a perturbation as described in their paper.
 Now we construct a model, but this time a `ShallowWaterModel`
 ```@example galewsky_setup
-model = ShallowWaterModel(;spectral_grid, orography, initial_conditions)
+model = ShallowWaterModel(; spectral_grid, orography, initial_conditions)
 simulation = initialize!(model)
 run!(simulation, period=Day(6))
 ```
@@ -164,7 +164,7 @@ Same as before, create a model, initialize into a simulation, run. This time dir
 compare with the last plot
 
 ```@example galewsky_setup
-model = ShallowWaterModel(;spectral_grid, orography, initial_conditions)
+model = ShallowWaterModel(; spectral_grid, orography, initial_conditions)
 simulation = initialize!(model)
 run!(simulation, period=Day(12), output=true)
 ```
@@ -206,7 +206,7 @@ spectral_grid = SpectralGrid(trunc=63, nlev=1)
 forcing = JetStreamForcing(spectral_grid, latitude=60)
 drag = QuadraticDrag(spectral_grid)
 output = OutputWriter(spectral_grid, ShallowWater, output_dt=Hour(6), output_vars=[:u, :v, :pres, :orography])
-model = ShallowWaterModel(;spectral_grid, output, drag, forcing)
+model = ShallowWaterModel(; spectral_grid, output, drag, forcing)
 simulation = initialize!(model)
 model.feedback.verbose = false # hide
 run!(simulation, period=Day(20))   # discard first 20 days   
@@ -259,7 +259,7 @@ implicit = SpeedyWeather.ImplicitShallowWater(spectral_grid, α=0.5)
 orography = EarthOrography(spectral_grid, smoothing=false)
 initial_conditions = SpeedyWeather.RandomWaves()
 output = OutputWriter(spectral_grid, ShallowWater, output_dt=Hour(12), output_vars=[:u, :pres, :div, :orography])
-model = ShallowWaterModel(;spectral_grid, orography, output, initial_conditions, implicit, time_stepping)
+model = ShallowWaterModel(; spectral_grid, orography, output, initial_conditions, implicit, time_stepping)
 simulation = initialize!(model)
 model.feedback.verbose = false # hide
 run!(simulation, period=Day(2), output=true)
@@ -323,7 +323,7 @@ using SpeedyWeather
 spectral_grid = SpectralGrid(trunc=31, nlev=8, Grid=FullGaussianGrid, dealiasing=3)
 orography = ZonalRidge(spectral_grid)
 initial_conditions = ZonalWind()
-model = PrimitiveDryModel(;spectral_grid, orography, initial_conditions, physics=false)
+model = PrimitiveDryModel(; spectral_grid, orography, initial_conditions, physics=false)
 simulation = initialize!(model)
 model.feedback.verbose = false # hide
 run!(simulation, period=Day(9), output=true)

docs/src/spectral_transform.md

@@ -455,7 +455,7 @@ as further described in [Radius scaling](@ref scaling).
 
 ## References
 
-[^Malardel2016]: Malardel S, Wedi N, Deconinck W, Diamantakis M, Kühnlein C, Mozdzynski G, Hamrud M, Smolarkiewicz P. A new grid for the IFS. ECMWF newsletter. 2016;146(23-28):321. doi: [10.21957/zwdu9u5i](https://doi.org/10.21957/zwdu9u5i)
+[^Malardel2016]: Malardel S, Wedi N, Deconinck W, Diamantakis M, Kühnlein C, Mozdzynski G, Hamrud M, Smolarkiewicz P. A new grid for the IFS. ECMWF newsletter. 2016; 146(23-28):321. doi: [10.21957/zwdu9u5i](https://doi.org/10.21957/zwdu9u5i)
 [^Gorski2004]: Górski, Hivon, Banday, Wandelt, Hansen, Reinecke, Bartelmann, 2004. _HEALPix: A FRAMEWORK FOR HIGH-RESOLUTION DISCRETIZATION AND FAST ANALYSIS OF DATA DISTRIBUTED ON THE SPHERE_, The Astrophysical Journal. doi:[10.1086/427976](https://doi.org/10.1086/427976)
 [^Willmert2020]: Justin Willmert, 2020. [justinwillmert.com](https://justinwillmert.com/)
     - [Introduction to Associated Legendre Polynomials (Legendre.jl Series, Part I)](https://justinwillmert.com/articles/2020/introduction-to-associated-legendre-polynomials/)

docs/src/speedytransforms.md

@@ -321,7 +321,7 @@ using SpeedyWeather
 spectral_grid = SpectralGrid(trunc=31, nlev=1)
 forcing = SpeedyWeather.JetStreamForcing(spectral_grid)
 drag = QuadraticDrag(spectral_grid)
-model = ShallowWaterModel(;spectral_grid, forcing, drag)
+model = ShallowWaterModel(; spectral_grid, forcing, drag)
 model.feedback.verbose = false # hide
 simulation = initialize!(model);
 run!(simulation, period=Day(30))

src/LowerTriangularMatrices/plot.jl

@@ -25,5 +25,5 @@ function plot(L::LowerTriangularMatrix{T}; mode::Function=abs) where T
                             width=width,
                             height=height))
 
-    return UnicodePlots.heatmap(Lplot;plot_kwargs...)
+    return UnicodePlots.heatmap(Lplot; plot_kwargs...)
 end

src/RingGrids/grids_general.jl

@@ -224,7 +224,7 @@ $(TYPEDSIGNATURES)
 Returns a vector `nlons` for the number of longitude points per latitude ring, north to south.
 Provide grid `Grid` and its resolution parameter `nlat_half`. For both_hemisphere==false only
 the northern hemisphere (incl Equator) is returned."""
-function get_nlons(Grid::Type{<:AbstractGrid}, nlat_half::Integer;both_hemispheres::Bool=false)
+function get_nlons(Grid::Type{<:AbstractGrid}, nlat_half::Integer; both_hemispheres::Bool=false)
     n = both_hemispheres ? get_nlat(Grid, nlat_half) : nlat_half
     return [get_nlon_per_ring(Grid, nlat_half, j) for j in 1:n]
 end

src/RingGrids/interpolation.jl

@@ -290,8 +290,8 @@ function update_locator!(   I::AbstractInterpolator{NF, Grid},   # GridGeometry
 
     # find latitude ring indices corresponding to interpolation points
     (; latd ) = I.geometry           # latitudes of rings including north and south pole
-    (; js, Δys ) = I.locator          # to be updated: ring indices js, and meridional weights Δys
-    find_rings!(js, Δys, θs, latd;unsafe)  # next ring at or north of θ
+    (; js, Δys ) = I.locator         # to be updated: ring indices js, and meridional weights Δys
+    find_rings!(js, Δys, θs, latd; unsafe)  # next ring at or north of θ
 
     # find grid incides ij for top, bottom and left, right grid points around (θ, λ)
     find_grid_indices!(I, λs)            # next points left and right of λ on rings north and south

src/RingGrids/octahealpix.jl

@@ -119,7 +119,7 @@ full_grid(::Type{<:OctaHEALPixGrid}) = FullOctaHEALPixGrid    # the full grid wi
 
 matrix_size(grid::OctaHEALPixGrid) = (2grid.nlat_half, 2grid.nlat_half)
 matrix_size(::Type{OctaHEALPixGrid}, nlat_half::Integer) = (2nlat_half, 2nlat_half)
-Base.Matrix(G::OctaHEALPixGrid{T};kwargs...) where T = Matrix!(zeros(T, matrix_size(G)...), G;kwargs...)
+Base.Matrix(G::OctaHEALPixGrid{T}; kwargs...) where T = Matrix!(zeros(T, matrix_size(G)...), G; kwargs...)
 
 """
     Matrix!(M::AbstractMatrix,
@@ -134,10 +134,10 @@ Every quadrant of the grid `G` is rotated as specified in `quadrant_rotation`,
 eastward starting from 0˚E. The grid quadrants are moved into the matrix quadrant
 (i, j) as specified. Defaults are equivalent to centered at 0˚E and a rotation
 such that the North Pole is at M's midpoint."""
-Matrix!(M::AbstractMatrix, G::OctaHEALPixGrid;kwargs...) = Matrix!((M, G);kwargs...)
+Matrix!(M::AbstractMatrix, G::OctaHEALPixGrid; kwargs...) = Matrix!((M, G); kwargs...)
 
 """
-    Matrix!(MGs::Tuple{AbstractMatrix{T}, OctaHEALPixGrid}...;kwargs...)
+    Matrix!(MGs::Tuple{AbstractMatrix{T}, OctaHEALPixGrid}...; kwargs...)
 
 Like `Matrix!(::AbstractMatrix, ::OctaHEALPixGrid)` but for simultaneous
 processing of tuples `((M1, G1), (M2, G2), ...)` with matrices `Mi` and grids `Gi`.

src/RingGrids/octahedral.jl

@@ -149,7 +149,7 @@ full_grid(::Type{<:OctahedralClenshawGrid}) = FullClenshawGrid    # the full gri
 
 matrix_size(G::OctahedralClenshawGrid) = (2*(4+G.nlat_half), 2*(4+G.nlat_half))
 matrix_size(::Type{OctahedralClenshawGrid}, nlat_half::Integer) = (2*(4+nlat_half), 2*(4+nlat_half))
-Base.Matrix(G::OctahedralClenshawGrid{T};kwargs...) where T = Matrix!(zeros(T, matrix_size(G)...), G;kwargs...)
+Base.Matrix(G::OctahedralClenshawGrid{T}; kwargs...) where T = Matrix!(zeros(T, matrix_size(G)...), G; kwargs...)
 
 """
     Matrix!(M::AbstractMatrix,
@@ -164,10 +164,10 @@ Every quadrant of the grid `G` is rotated as specified in `quadrant_rotation`,
 eastward starting from 0˚E. The grid quadrants are moved into the matrix quadrant
 (i, j) as specified. Defaults are equivalent to centered at 0˚E and a rotation
 such that the North Pole is at M's midpoint."""
-Matrix!(M::AbstractMatrix, G::OctahedralClenshawGrid;kwargs...) = Matrix!((M, G);kwargs...)
+Matrix!(M::AbstractMatrix, G::OctahedralClenshawGrid; kwargs...) = Matrix!((M, G); kwargs...)
 
 """
-    Matrix!(MGs::Tuple{AbstractMatrix{T}, OctahedralClenshawGrid}...;kwargs...)
+    Matrix!(MGs::Tuple{AbstractMatrix{T}, OctahedralClenshawGrid}...; kwargs...)
 
 Like `Matrix!(::AbstractMatrix, ::OctahedralClenshawGrid)` but for simultaneous
 processing of tuples `((M1, G1), (M2, G2), ...)` with matrices `Mi` and grids `Gi`.

src/RingGrids/scaling.jl

@@ -4,7 +4,7 @@ scale_coslat²!( A::AbstractGrid) = _scale_coslat!(A, power=2)
 scale_coslat⁻¹!(A::AbstractGrid) = _scale_coslat!(A, power=-1)
 scale_coslat⁻²!(A::AbstractGrid) = _scale_coslat!(A, power=-2)
 
-function _scale_coslat!(A::Grid;power=1) where {Grid<:AbstractGrid}
+function _scale_coslat!(A::Grid; power=1) where {Grid<:AbstractGrid}
     coslat = sin.(get_colat(Grid, A.nlat_half))    # sin(colat) = cos(lat)
     coslat .^= power
     return _scale_lat!(A, coslat)

src/RingGrids/show.jl

@@ -6,12 +6,12 @@ function Base.array_summary(io::IO, grid::AbstractGrid, inds::Tuple{Vararg{Base.
     Base.showarg(io, grid, true)
 end
 
-function plot(A::AbstractGrid;title::String="$(get_nlat(A))-ring $(typeof(A))")
+function plot(A::AbstractGrid; title::String="$(get_nlat(A))-ring $(typeof(A))")
     A_full = interpolate(full_grid(typeof(A)), A.nlat_half, A)
-    plot(A_full;title)
+    plot(A_full; title)
 end
 
-function plot(A::AbstractFullGrid;title::String="$(get_nlat(A))-ring $(typeof(A))")
+function plot(A::AbstractFullGrid; title::String="$(get_nlat(A))-ring $(typeof(A))")
 
     A_matrix = Matrix(A)
     nlon, nlat = size(A_matrix)
@@ -33,5 +33,5 @@ function plot(A::AbstractFullGrid;title::String="$(get_nlat(A))-ring $(typeof(A)
                             colorbar=true,
                             width=width,
                             height=height))
-    return UnicodePlots.heatmap(A_view';plot_kwargs...)
+    return UnicodePlots.heatmap(A_view'; plot_kwargs...)
 end

src/SpeedyTransforms/aliasing.jl

@@ -38,7 +38,7 @@ Returns an integer `m >= n` with only small prime factors 2, 3 (default, others
 with the keyword argument `small_primes`) to obtain an efficiently fourier-transformable number of
 longitudes, m = 2^i * 3^j * 5^k >= n, with i, j, k >=0.
 """
-function roundup_fft(n::Integer;small_primes::Vector{T}=[2, 3, 5]) where {T<:Integer}
+function roundup_fft(n::Integer; small_primes::Vector{T}=[2, 3, 5]) where {T<:Integer}
     factors_not_in_small_primes = true      # starting condition for while loop
     n += isodd(n) ? 1 : 0                   # start with an even n
     while factors_not_in_small_primes