changed: replace an Union with AbstractVector{Int}

Author: franckgaga

docs/src/public/predictive_control.md

@@ -49,7 +49,7 @@ in which ``\mathbf{U}`` and ``\mathbf{R̂_u}`` are both vectors of `nu*Hp` eleme
 the manipulated input increment as ``\mathbf{Δu}(k+j) = \mathbf{u}(k+j) - \mathbf{u}(k+j-1)``,
 the control horizon ``H_c`` enforces that ``\mathbf{Δu}(k+j) = \mathbf{0}`` for ``j ≥ H_c``.
 For this reason, the vector that collects them is truncated up to ``k+H_c-1`` (without
-custom move blocking):
+any custom move blocking):
 
 ```math
     \mathbf{ΔU} =

src/estimator/construct.jl

@@ -116,7 +116,7 @@ function init_integrators(nint::IntVectorOrInt, ny, varname::String)
         nint = fill(0, ny)
     end
     if length(nint) ≠ ny
-        error("nint_$(varname) size ($(length(nint))) ≠ n$(varname) ($ny)")
+        error("nint_$(varname) length ($(length(nint))) ≠ n$(varname) ($ny)")
     end
     any(nint .< 0) && error("nint_$(varname) values should be ≥ 0")
     nx = sum(nint)

src/estimator/internal_model.jl

@@ -104,7 +104,7 @@ InternalModel estimator with a sample time Ts = 0.5 s, LinModel and:
 """
 function InternalModel(
     model::SM;
-    i_ym::IntRangeOrVector = 1:model.ny,
+    i_ym::AbstractVector{Int} = 1:model.ny,
     stoch_ym::LTISystem = (In = I(length(i_ym)); ss(In, In, In, In, model.Ts))
 ) where {NT<:Real, SM<:SimModel{NT}}
     stoch_ym = minreal(ss(stoch_ym))

src/estimator/kalman.jl

@@ -166,7 +166,7 @@ SteadyKalmanFilter estimator with a sample time Ts = 0.5 s, LinModel and:
 """
 function SteadyKalmanFilter(
     model::SM;
-    i_ym::IntRangeOrVector = 1:model.ny,
+    i_ym::AbstractVector{Int} = 1:model.ny,
     sigmaQ = fill(1/model.nx, model.nx),
     sigmaR = fill(1, length(i_ym)),
     nint_u ::IntVectorOrInt = 0,
@@ -397,7 +397,7 @@ KalmanFilter estimator with a sample time Ts = 0.5 s, LinModel and:
 """
 function KalmanFilter(
     model::SM;
-    i_ym::IntRangeOrVector = 1:model.ny,
+    i_ym::AbstractVector{Int} = 1:model.ny,
     sigmaP_0 = fill(1/model.nx, model.nx),
     sigmaQ   = fill(1/model.nx, model.nx),
     sigmaR   = fill(1, length(i_ym)),
@@ -654,7 +654,7 @@ UnscentedKalmanFilter estimator with a sample time Ts = 10.0 s, NonLinModel and:
 """
 function UnscentedKalmanFilter(
     model::SM;
-    i_ym::IntRangeOrVector = 1:model.ny,
+    i_ym::AbstractVector{Int} = 1:model.ny,
     sigmaP_0 = fill(1/model.nx, model.nx),
     sigmaQ   = fill(1/model.nx, model.nx),
     sigmaR   = fill(1, length(i_ym)),
@@ -1009,7 +1009,7 @@ ExtendedKalmanFilter estimator with a sample time Ts = 5.0 s, NonLinModel and:
 """
 function ExtendedKalmanFilter(
     model::SM;
-    i_ym::IntRangeOrVector = 1:model.ny,
+    i_ym::AbstractVector{Int} = 1:model.ny,
     sigmaP_0 = fill(1/model.nx, model.nx),
     sigmaQ   = fill(1/model.nx, model.nx),
     sigmaR   = fill(1, length(i_ym)),

src/estimator/luenberger.jl

@@ -95,7 +95,7 @@ Luenberger estimator with a sample time Ts = 0.5 s, LinModel and:
 """
 function Luenberger(
     model::SM;
-    i_ym::IntRangeOrVector  = 1:model.ny,
+    i_ym::AbstractVector{Int}  = 1:model.ny,
     nint_u ::IntVectorOrInt = 0,
     nint_ym::IntVectorOrInt = default_nint(model, i_ym, nint_u),
     poles = 1e-3*(1:(model.nx + sum(nint_u) + sum(nint_ym))) .+ 0.5,

src/estimator/mhe/construct.jl

@@ -376,7 +376,7 @@ MovingHorizonEstimator estimator with a sample time Ts = 10.0 s, Ipopt optimizer
 function MovingHorizonEstimator(
     model::SM;
     He::Union{Int, Nothing} = nothing,
-    i_ym::IntRangeOrVector = 1:model.ny,
+    i_ym::AbstractVector{Int} = 1:model.ny,
     sigmaP_0 = fill(1/model.nx, model.nx),
     sigmaQ   = fill(1/model.nx, model.nx),
     sigmaR   = fill(1, length(i_ym)),

src/model/linmodel.jl

@@ -136,8 +136,8 @@ LinModel with a sample time Ts = 0.1 s and:
 function LinModel(
     sys::StateSpace{E, NT},
     Ts::Union{Real,Nothing} = nothing;
-    i_u::IntRangeOrVector = 1:size(sys,2),
-    i_d::IntRangeOrVector = Int[]
+    i_u::AbstractVector{Int} = 1:size(sys,2),
+    i_d::AbstractVector{Int} = Int[]
 ) where {E, NT<:Real}
     if !isempty(i_d)
         # common indexes in i_u and i_d are interpreted as measured disturbances d :

src/plot_sim.jl

@@ -319,7 +319,7 @@ end
 "Keep manipulated input `u` unchanged for state estimator simulation."
 sim_getu!(::StateEstimator, u, _ , _ ) = u
 
-function get_indices(arg::IntRangeOrVector, n)
+function get_indices(arg::AbstractVector{Int}, n)
     if length(unique(arg)) ≠ length(arg) || maximum(arg) > n
         error("Plot keyword argument arguments should contains valid and unique indices")
     end

src/sim_model.jl

@@ -1,5 +1,3 @@
-const IntRangeOrVector = Union{UnitRange{Int}, Vector{Int}}
-
 @doc raw"""
 Abstract supertype of [`LinModel`](@ref) and [`NonLinModel`](@ref) types.