Merge pull request #355 from abhro/kwargs-naming

Remove repeated naming for keyword arguments

Author: ChrisRackauckas

docs/src/examples/DiffEqFlux.md

@@ -83,10 +83,10 @@ cb(θ, loss_n_ode(θ)...)
 
 data = Iterators.repeated((), 1000)
 
-res1 = sciml_train(loss_n_ode, θ, ADAM(0.05); cb = cb, maxiters = 100)
+res1 = sciml_train(loss_n_ode, θ, ADAM(0.05); cb, maxiters = 100)
 cb(res1.minimizer, loss_n_ode(res1.minimizer)...; doplot = true)
 
-res2 = sciml_train(loss_n_ode, res1.minimizer, LBFGS(); cb = cb)
+res2 = sciml_train(loss_n_ode, res1.minimizer, LBFGS(); cb)
 cb(res2.minimizer, loss_n_ode(res2.minimizer)...; doplot = true)
 ```
 

docs/src/examples/adaptive_control.md

@@ -107,9 +107,9 @@ plot!(step_p, solve(ODEProblem(apply_inputs(nominal_sim!; u = 1), nominal_ic, (0
     vars = 1, label = "nominal model")
 
 u = (x, p, t) -> sin(3t)
-sin_p = plot(solve(ODEProblem(apply_inputs(truth_sim!; u = u), truth_ic, (0.0, 10.0)));
+sin_p = plot(solve(ODEProblem(apply_inputs(truth_sim!; u), truth_ic, (0.0, 10.0)));
     vars = 1, label = "truth model")
-plot!(sin_p, solve(ODEProblem(apply_inputs(nominal_sim!; u = u), nominal_ic, (0.0, 10.0)));
+plot!(sin_p, solve(ODEProblem(apply_inputs(nominal_sim!; u), nominal_ic, (0.0, 10.0)));
     vars = 1, label = "nominal model")
 
 plot(step_p, sin_p; layout = (2, 1), size = (800, 800))
@@ -155,11 +155,11 @@ function feedback_sys!(D, vars, p, t; ym, r, n)
     regressor = [r, plant_model[1]]
 
     u = control(parameter_estimates, regressor)
-    yp = p.plant_fun(D.plant_model, plant_model, (), t; u = u)
+    yp = p.plant_fun(D.plant_model, plant_model, (), t; u)
     ŷ = sensor_sim!(D.sensor, sensor, (), t; u = yp[1]) + n
     e = ŷ .- ym
     regressor[2] = ŷ
-    adapt!(D.parameter_estimates, parameter_estimates, γ, t; e = e, w = regressor)
+    adapt!(D.parameter_estimates, parameter_estimates, γ, t; e, w = regressor)
     return yp
 end
 ```
@@ -172,7 +172,7 @@ function system!(D, vars, p, t; r = 0.0, n = 0.0)
     @unpack reference_model, feedback_loop = vars
 
     ym = ref_sim!(D.reference_model, reference_model, (), t; u = r)
-    yp = feedback_sys!(D.feedback_loop, feedback_loop, p, t; ym = ym, r = r, n = n)
+    yp = feedback_sys!(D.feedback_loop, feedback_loop, p, t; ym, r, n)
     return yp
 end
 ```
@@ -219,10 +219,7 @@ function simulate(plant_fun, plant_ic;
     )
 
     # Model parameters
-    p = (
-        gamma = adapt_gain,
-        plant_fun = plant_fun
-    )
+    p = (; gamma = adapt_gain, plant_fun)
 
     sim_fun = apply_inputs(system!; r = input_signal, n = deterministic_noise)
 

docs/src/examples/coulomb_control.md

@@ -69,7 +69,7 @@ function feedback_sys!(D, components, p, t; ref = 0.0)
     @unpack ctrl, plant = components
 
     u = p.ctrl.fun(D.ctrl, ctrl, p.ctrl.params, t; err = ref-plant.x, v = -plant.v)
-    return p.plant.fun(D.plant, plant, p.plant.params, t; u = u)
+    return p.plant.fun(D.plant, plant, p.plant.params, t; u)
 end
 
 step_input(; time = 1.0, mag = 1.0) = (x, p, t) -> t>time ? mag : 0
@@ -91,7 +91,7 @@ const m = 50.0
 const μ = 0.1
 const k = 50.0
 
-p = (m = m, μ = μ, k = k)
+p = (; m, μ, k)
 ic = ComponentArray(v = 0, x = 0)
 
 ODEProblem(simulator(coulomb_block!, u = 5), ic, tspan, p) |> solve |> plot
@@ -147,7 +147,7 @@ plot(sol, vars = 3)
     # plant_fun = coulomb_block!
 
     ref = if reference==sine_input
-        reference(period = period, mag = magnitude)
+        reference(; period, mag = magnitude)
     else
         reference(mag = magnitude)
     end
@@ -158,25 +158,19 @@ plot(sol, vars = 3)
     c = 4*μ*m*g/(π*ω*magnitude) # Viscous equivalent damping
     k = 50.0
 
-    plant_p = (m = m, μ = μ, c = c, k = k) # We'll just put everything for both models in here
-    ctrl_p = (kp = kp, ki = ki, kd = kd)
+    plant_p = (; m, μ, c, k) # We'll just put everything for both models in here
+    ctrl_p = (; kp, ki, kd)
 
     plant_ic = (v = 0, x = 0)
     ctrl_ic = (; x = 0)
 
     # Set up and solve
     sys_p = (
-        ctrl = (
-            params = ctrl_p,
-            fun = ctrl_fun
-        ),
-        plant = (
-            params = plant_p,
-            fun = damping
-        )
+        ctrl = (params = ctrl_p, fun = ctrl_fun),
+        plant = (params = plant_p, fun = damping)
     )
     sys_ic = ComponentArray(ctrl = ctrl_ic, plant = plant_ic)
-    sys_fun = ODEFunction(simulator(feedback_sys!, ref = ref), syms = [:u, :v, :x])
+    sys_fun = ODEFunction(simulator(feedback_sys!; ref), syms = [:u, :v, :x])
     sys_prob = ODEProblem(sys_fun, sys_ic, tspan, sys_p)
 
     sol = solve(sys_prob, Tsit5())

examples/DiffEqFlux_example.jl

@@ -104,10 +104,10 @@ cb(θ, loss_n_ode(θ)...)
 
 data = Iterators.repeated((), 1000)
 
-res1 = sciml_train(loss_n_ode, θ, ADAM(0.05); maxiters = 100, save_best = true, cb = cb)
+res1 = sciml_train(loss_n_ode, θ, ADAM(0.05); maxiters = 100, save_best = true, cb)
 cb(res1.minimizer, loss_n_ode(res1.minimizer)...; doplot = true)
 
-res2 = sciml_train(loss_n_ode, res1.minimizer, LBFGS(), cb = cb)
+res2 = sciml_train(loss_n_ode, res1.minimizer, LBFGS(), cb)
 cb(res2.minimizer, loss_n_ode(res2.minimizer)...; doplot = true)
 
 # gif(anim, "DiffEqFlux.gif", fps=15)

examples/adaptive_control_example.jl

@@ -91,11 +91,11 @@ function feedback_sys!(D, vars, p, t; ym, r, n)
     regressor = [r, plant_model[1]]
 
     u = control(parameter_estimates, regressor)
-    yp = p.plant_fun(D.plant_model, plant_model, (), t; u = u)
+    yp = p.plant_fun(D.plant_model, plant_model, (), t; u)
     ŷ = sensor_sim!(D.sensor, sensor, (), t; u = yp[1]) + n
     e = ŷ .- ym
     regressor[2] = ŷ
-    adapt!(D.parameter_estimates, parameter_estimates, γ, t; e = e, w = regressor)
+    adapt!(D.parameter_estimates, parameter_estimates, γ, t; e, w = regressor)
     return yp
 end
 # Now the full system takes in an input signal `r`, feeds it through the reference model,
@@ -104,7 +104,7 @@ function system!(D, vars, p, t; r = 0.0, n = 0.0)
     @unpack reference_model, feedback_loop = vars
 
     ym = ref_sim!(D.reference_model, reference_model, (), t; u = r)
-    yp = feedback_sys!(D.feedback_loop, feedback_loop, p, t; ym = ym, r = r, n = n)
+    yp = feedback_sys!(D.feedback_loop, feedback_loop, p, t; ym, r, n)
     return yp
 end
 
@@ -147,10 +147,7 @@ function simulate(
     )
 
     # Model parameters
-    p = (
-        gamma = adapt_gain,
-        plant_fun = plant_fun,
-    )
+    p = (; gamma = adapt_gain, plant_fun)
 
     sim_fun = apply_inputs(system!; r = input_signal, n = deterministic_noise)
 

examples/coulomb_control.ipynb

@@ -92,7 +92,7 @@
     "    @unpack ctrl, plant = components\n",
     "\n",
     "    u = p.ctrl.fun(D.ctrl, ctrl, p.ctrl.params, t; err=ref-plant.x, v=-plant.v)\n",
-    "    return p.plant.fun(D.plant, plant, p.plant.params, t; u=u)\n",
+    "    return p.plant.fun(D.plant, plant, p.plant.params, t; u)\n",
     "end\n",
     "\n",
     "step_input(;time=1.0, mag=1.0) = (x,p,t) -> t>time ? mag : 0\n",
@@ -1727,7 +1727,7 @@
     "    # plant_fun = coulomb_block!\n",
     "    \n",
     "    ref = if reference==sine_input\n",
-    "        reference(period=period, mag=magnitude)\n",
+    "        reference(; period, mag=magnitude)\n",
     "        else\n",
     "        reference(mag=magnitude)\n",
     "    end\n",
@@ -1738,8 +1738,8 @@
     "    c = 4*μ*m*g/(π*ω*magnitude) # Viscous equivalent damping\n",
     "    k = 50.0\n",
     "\n",
-    "    plant_p = (m=m, μ=μ, c=c, k=k)\n",
-    "    ctrl_p = (kp=kp, ki=ki, kd=kd)\n",
+    "    plant_p = (; m, μ, c, k)\n",
+    "    ctrl_p = (; kp, ki, kd)\n",
     "\n",
     "    plant_ic = (v=0, x=0)\n",
     "    ctrl_ic = (;x=0)\n",
@@ -1748,17 +1748,11 @@
     "\n",
     "    # Set up and solve\n",
     "    sys_p = (\n",
-    "        ctrl = (\n",
-    "            params = ctrl_p,\n",
-    "            fun = ctrl_fun,\n",
-    "        ),\n",
-    "        plant = (\n",
-    "            params = plant_p,\n",
-    "            fun = damping,\n",
-    "        ),\n",
+    "        ctrl = (params = ctrl_p, fun = ctrl_fun),\n",
+    "        plant = (params = plant_p, fun = damping),\n",
     "    )\n",
     "    sys_ic = ComponentArray(ctrl=ctrl_ic, plant=plant_ic)\n",
-    "    sys_fun = ODEFunction(simulator(feedback_sys!, ref=ref), syms=[:u, :v, :x])\n",
+    "    sys_fun = ODEFunction(simulator(feedback_sys!; ref), syms=[:u, :v, :x])\n",
     "    sys_prob = ODEProblem(sys_fun, sys_ic, tspan, sys_p)\n",
     "\n",
     "    sol = solve(sys_prob, Tsit5())\n",

ext/ComponentArraysGPUArraysExt.jl

@@ -68,15 +68,15 @@ function Base.mapreduce(
     return mapreduce(f, op, getdata(x), map(getdata, args)...; kwargs...)
 end
 
-# These are all stolen from GPUArrays.j;
+# These are all stolen from GPUArrays.jl
 Base.any(A::GPUComponentArray{Bool}) = mapreduce(identity, |, getdata(A))
 Base.all(A::GPUComponentArray{Bool}) = mapreduce(identity, &, getdata(A))
 
 Base.any(f::Function, A::GPUComponentArray) = mapreduce(f, |, getdata(A))
 Base.all(f::Function, A::GPUComponentArray) = mapreduce(f, &, getdata(A))
 
 function Base.count(pred::Function, A::GPUComponentArray; dims = :, init = 0)
-    return mapreduce(pred, Base.add_sum, getdata(A); init = init, dims = dims)
+    return mapreduce(pred, Base.add_sum, getdata(A); init, dims)
 end
 
 # avoid calling into `initarray!`

src/show.jl

@@ -41,30 +41,30 @@ Base.show(io::IO, ci::ComponentIndex) = print(io, "ComponentIndex($(ci.idx), $(c
 
 # Show ComponentArrays
 function _print_type_short(io, ca; color = :normal)
-    return _print_type_short(io, typeof(ca); color = color)
+    return _print_type_short(io, typeof(ca); color)
 end
-_print_type_short(io, T::Type; color = :normal) = printstyled(io, T; color = color)
+_print_type_short(io, T::Type; color = :normal) = printstyled(io, T; color)
 function _print_type_short(io, ::Type{<:ComponentArray{T, N, <:Array}}; color = :normal) where {
         T, N,
     }
-    return printstyled(io, "ComponentArray{$T,$N}"; color = color)
+    return printstyled(io, "ComponentArray{$T,$N}"; color)
 end # do not pollute the stacktrace with verbose type printing
 function _print_type_short(io, ::Type{<:ComponentArray{T, 1, <:Array}}; color = :normal) where {T}
-    return printstyled(io, "ComponentVector{$T}"; color = color)
+    return printstyled(io, "ComponentVector{$T}"; color)
 end
 function _print_type_short(io, ::Type{<:ComponentArray{T, 2, <:Array}}; color = :normal) where {T}
-    return printstyled(io, "ComponentMatrix{$T}"; color = color)
+    return printstyled(io, "ComponentMatrix{$T}"; color)
 end
 function _print_type_short(io, ::Type{<:ComponentArray{T, N, <:SubArray}}; color = :normal) where {
         T, N,
     }
-    return printstyled(io, "ComponentArray{$T,$N,SubArray...}"; color = color)
+    return printstyled(io, "ComponentArray{$T,$N,SubArray...}"; color)
 end # do not pollute the stacktrace with verbose type printing
 function _print_type_short(io, ::Type{<:ComponentArray{T, 1, <:SubArray}}; color = :normal) where {T}
-    return printstyled(io, "ComponentVector{$T,SubArray...}"; color = color)
+    return printstyled(io, "ComponentVector{$T,SubArray...}"; color)
 end
 function _print_type_short(io, ::Type{<:ComponentArray{T, 2, <:SubArray}}; color = :normal) where {T}
-    return printstyled(io, "ComponentMatrix{$T,SubArray...}"; color = color)
+    return printstyled(io, "ComponentMatrix{$T,SubArray...}"; color)
 end
 
 function Base.show(io::IO, x::ComponentVector)

test/autodiff/autodiff_tests.jl

@@ -109,7 +109,7 @@ end
 
 @testset "Issues" begin
     function mysum(x::AbstractVector)
-        y = ComponentVector(x = x)
+        y = ComponentVector(; x)
         z = ComponentVector(; z = x .^ 2)
         return sum(y) + sum(abs2, z)
     end

test/core_tests.jl

@@ -15,7 +15,7 @@ r2v(r::AbstractUnitRange) = ViewAxis(r, ShapedAxis(size(r)))
 
 ## Test setup
 c = (a = (a = 1, b = [1.0, 4.4]), b = [0.4, 2, 1, 45])
-nt = (a = 100, b = [4, 1.3], c = c)
+nt = (; a = 100, b = [4, 1.3], c)
 nt2 = (
     a = 5, b = [(a = (a = 20, b = 1), b = 0), (a = (a = 33, b = 1), b = 0)],
     c = (a = (a = 2, b = [1, 2]), b = [1.0 2.0; 5 6]),
@@ -605,10 +605,10 @@ end
     @test ldiv!(getdata(tempmat), lu(cmat + I), cmat) isa AbstractMatrix
 
     c = (a = 2, b = [1, 2])
-    x = ComponentArray(
-        a = 5, b = [
-            (a = 20.0, b = 3.0), (a = 33.0, b = 2.0), (a = 44.0, b = 3.0),
-        ], c = c
+    x = ComponentArray(;
+        a = 5,
+        b = [(a = 20.0, b = 3.0), (a = 33.0, b = 2.0), (a = 44.0, b = 3.0)],
+        c,
     )
     @test ldiv!(rand(10), Diagonal(x), x) isa Vector
 
@@ -924,7 +924,7 @@ end
     b = range(0.0, 1.0; length = 2) |> collect
     c = range(0.0, 1.0, length = 3) |> collect
     d = range(0.0, 1.0; length = 0) |> collect
-    u = ComponentVector(a = a, b = b, c = c, d = d)
+    u = ComponentVector(; a, b, c, d)
 
     function get_state_index(
             idx::Int,