added: pretty-print diff. backends in NonLinModel, NonLinMPC and MovingHorizonEstimator

Author: franckgaga

src/controller/nonlinmpc.jl

@@ -748,8 +748,14 @@ end
 
 "Evaluate the economic term `E*JE` of the objective function for [`NonLinMPC`](@ref)."
 function obj_econ(
-    mpc::NonLinMPC, model::SimModel, Ue, Ŷe::AbstractVector{NT}
+    mpc::NonLinMPC, ::SimModel, Ue, Ŷe::AbstractVector{NT}
 ) where NT<:Real
     E_JE = mpc.weights.iszero_E ? zero(NT) : mpc.weights.E*mpc.JE(Ue, Ŷe, mpc.D̂e, mpc.p)
     return E_JE
-end
+end
+
+"Print the differentiation backends of a [`NonLinMPC`](@ref) controller."
+function print_backends(io::IO, mpc::NonLinMPC)
+    println(io, "├ gradient: $(backend_str(mpc.gradient))")
+    println(io, "├ jacobian: $(backend_str(mpc.jacobian))")
+end

src/estimator/mhe.jl

@@ -9,10 +9,18 @@ function Base.show(io::IO, estim::MovingHorizonEstimator)
     println(io, "$(nameof(typeof(estim))) estimator with a sample time Ts = $(model.Ts) s:")
     println(io, "├ model: $(nameof(typeof(model)))")
     println(io, "├ optimizer: $(JuMP.solver_name(estim.optim)) ")
+    print_backends(io, estim, model)
     println(io, "└ dimensions:")
     print_estim_dim(io, estim, n)
 end
 
+function print_backends(io::IO, estim::MovingHorizonEstimator, ::SimModel)
+    println(io, "├ gradient: $(backend_str(estim.gradient))")
+    println(io, "├ jacobian: $(backend_str(estim.jacobian))")
+end
+print_backends(::IO, ::MovingHorizonEstimator, ::LinModel) = nothing
+
+
 "Print the overall dimensions of the MHE `estim` with left padding `n`."
 function print_estim_dim(io::IO, estim::MovingHorizonEstimator, n)
     nu, nd = estim.model.nu, estim.model.nd

src/general.jl

@@ -61,6 +61,14 @@ end
 init_diffmat(T, backend::AbstractADType, _  , nx , ny) = Matrix{T}(undef, ny, nx)
 init_diffmat(T, backend::AutoSparse    ,prep , _ , _ ) = similar(sparsity_pattern(prep), T)
 
+backend_str(backend::AbstractADType) = string(nameof(typeof(backend)))
+function backend_str(backend::AutoSparse)
+    str =   "AutoSparse ($(nameof(typeof(backend.dense_ad))),"*
+            " $(nameof(typeof(backend.sparsity_detector))),"*
+            " $(nameof(typeof(backend.coloring_algorithm))))"
+    return str
+end
+
 "Verify that x and y elements are different using `!==`."
 isdifferent(x, y) = any(xi !== yi for (xi, yi) in zip(x, y))
 

src/model/nonlinmodel.jl

@@ -311,8 +311,11 @@ h!(y0, model::NonLinModel, x0, d0, p) = model.h!(y0, x0, d0, p)
 
 include("solver.jl")
 
-function detailstr(model::NonLinModel{<:Real, <:RungeKutta{N}}) where N
-    return "solver: $(nameof(typeof(model.solver)))($N)"
+function print_details(io::IO, model::NonLinModel{<:Real, <:RungeKutta{N}}) where N
+    println(io, "├ solver: $(nameof(typeof(model.solver)))($N)")
+    println(io, "├ linearization: $(backend_str(model.jacobian))")
+end
+function print_details(io::IO, model::NonLinModel) 
+    println(io, "├ solver: $(nameof(typeof(model.solver)))")
+    println(io, "├ linearization: $(backend_str(model.jacobian))")
 end
-detailstr(::NonLinModel{<:Real, <:EmptySolver}) = "solver: empty"
-detailstr(::NonLinModel) = ""

src/predictive_control.jl

@@ -37,13 +37,17 @@ function Base.show(io::IO, mpc::PredictiveController)
     println(io, "├ model: $(nameof(typeof(model)))")
     println(io, "├ optimizer: $(JuMP.solver_name(mpc.optim)) ")
     println(io, "├ transcription: $(nameof(typeof(mpc.transcription)))")
+    print_backends(io, mpc)
     println(io, "└ dimensions:")
     println(io, "  ├$(lpad(Hp, n)) prediction steps Hp")
     println(io, "  ├$(lpad(Hc, n)) control steps Hc")
     println(io, "  ├$(lpad(nϵ, n)) slack variable ϵ (control constraints)")
     print_estim_dim(io, mpc.estim, n)
 end
 
+"No differentiation backends to print for a `PredictiveController` by default."
+print_backends(::IO, ::PredictiveController) = nothing
+
 "Functor allowing callable `PredictiveController` object as an alias for `moveinput!`."
 function (mpc::PredictiveController)(
     ry::Vector = mpc.estim.model.yop, 

src/sim_model.jl

@@ -174,8 +174,6 @@ function setstate!(model::SimModel, x)
     return model
 end
 
-detailstr(model::SimModel) = ""
-
 @doc raw"""
     initstate!(model::SimModel, u, d=[]) -> x
 
@@ -374,15 +372,17 @@ function Base.show(io::IO, model::SimModel)
     nu, nd = model.nu, model.nd
     nx, ny = model.nx, model.ny
     n = maximum(ndigits.((nu, nx, ny, nd))) + 1
-    details = detailstr(model) 
     println(io, "$(nameof(typeof(model))) with a sample time Ts = $(model.Ts) s:")
-    !isempty(details) && println(io, "├ $details")
+    print_details(io, model)
     println(io, "└ dimensions:")
     println(io, "  ├$(lpad(nu, n)) manipulated inputs u")
     println(io, "  ├$(lpad(nx, n)) states x")
     println(io, "  ├$(lpad(ny, n)) outputs y")
     print(io,   "  └$(lpad(nd, n)) measured disturbances d")
 end
 
+"Print additional details of `model` if any (no details by default)."
+print_details(::IO, ::SimModel) = nothing
+
 "Functor allowing callable `SimModel` object as an alias for `evaloutput`."
 (model::SimModel)(d=model.buffer.empty) = evaloutput(model::SimModel, d)