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Test: added allocations tests for types that are known to be allocation-free (SKIP THEM FOR NOW) #187

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2 changes: 1 addition & 1 deletion .github/workflows/CI.yml
Original file line number Diff line number Diff line change
@@ -17,7 +17,7 @@ jobs:
permissions: # needed for julia-actions/cache delete old caches that it has created
actions: write
contents: read
continue-on-error: ${{ matrix.version == 'nightly' }}
continue-on-error: ${{ matrix.version == 'nightly' || matrix.version == 'pre' }}
strategy:
fail-fast: false
matrix:
3 changes: 2 additions & 1 deletion src/model/linearization.jl
Original file line number Diff line number Diff line change
@@ -155,7 +155,8 @@ julia> linearize!(linmodel, model, x=[20.0], u=[0.0]); linmodel.A
```
"""
function linearize!(
linmodel::LinModel{NT}, model::SimModel; x=model.x0+model.xop, u=model.uop, d=model.dop
linmodel::LinModel{NT}, model::SimModel;
x=(model.buffer.x.=model.x0.+model.xop), u=model.uop, d=model.dop
) where NT<:Real
nonlinmodel = model
buffer = nonlinmodel.buffer
59 changes: 41 additions & 18 deletions test/1_test_sim_model.jl
Original file line number Diff line number Diff line change
@@ -100,11 +100,14 @@ end
@testitem "LinModel sim methods" setup=[SetupMPCtests] begin
using .SetupMPCtests, ControlSystemsBase
linmodel1 = setop!(LinModel(Gss), uop=[10,50], yop=[50,30])
@test updatestate!(linmodel1, [10, 50]) ≈ zeros(2)
@test updatestate!(linmodel1, [10, 50], Float64[]) ≈ zeros(2)
u, d = [10, 50], Float64[]
@test updatestate!(linmodel1, u) ≈ zeros(2)
@test updatestate!(linmodel1, u, d) ≈ zeros(2)
@test_skip @allocations(updatestate!(linmodel1, u)) == 0
@test linmodel1.x0 ≈ zeros(2)
@test evaloutput(linmodel1) ≈ linmodel1() ≈ [50,30]
@test evaloutput(linmodel1, Float64[]) ≈ linmodel1(Float64[]) ≈ [50,30]
@test_skip @allocations(evaloutput(linmodel1)) == 0
x = initstate!(linmodel1, [10, 60])
@test evaloutput(linmodel1) ≈ [50 + 19.0, 30 + 7.4]
@test preparestate!(linmodel1) ≈ x # new method
@@ -155,9 +158,9 @@ end
using DifferentiationInterface
import FiniteDiff
linmodel1 = LinModel(sys,Ts,i_u=[1,2])
f1(x,u,_,model) = model.A*x + model.Bu*u
h1(x,_,model) = model.C*x
nonlinmodel1 = NonLinModel(f1,h1,Ts,2,2,2,solver=nothing,p=linmodel1)
f1!(x,u,_,model) = model.A*x + model.Bu*u
h1!(x,_,model) = model.C*x
nonlinmodel1 = NonLinModel(f1!,h1!,Ts,2,2,2,solver=nothing,p=linmodel1)
@test nonlinmodel1.nx == 2
@test nonlinmodel1.nu == 2
@test nonlinmodel1.nd == 0
@@ -265,15 +268,21 @@ end
@testitem "NonLinModel sim methods" setup=[SetupMPCtests] begin
using .SetupMPCtests, ControlSystemsBase, LinearAlgebra
linmodel1 = LinModel(sys,Ts,i_u=[1,2])
f1(x,u,_,model) = model.A*x + model.Bu*u
h1(x,_,model) = model.C*x
nonlinmodel = NonLinModel(f1,h1,Ts,2,2,2,p=linmodel1,solver=nothing)
function f1!(xnext, x, u, _ , model)
mul!(xnext, model.A, x)
mul!(xnext, model.Bu, u, 1, 1)
end
h1!(y, x , _ , model) = mul!(y, model.C, x)
nonlinmodel = NonLinModel(f1!,h1!,Ts,2,2,2,p=linmodel1,solver=nothing)

@test updatestate!(nonlinmodel, zeros(2,)) ≈ zeros(2)
@test updatestate!(nonlinmodel, zeros(2,), Float64[]) ≈ zeros(2)
u, d = zeros(2), Float64[]
@test updatestate!(nonlinmodel, u) ≈ zeros(2)
@test updatestate!(nonlinmodel, u, d) ≈ zeros(2)
@test_skip @allocations(updatestate!(nonlinmodel, u)) == 0
@test nonlinmodel.x0 ≈ zeros(2)
@test evaloutput(nonlinmodel) ≈ nonlinmodel() ≈ zeros(2)
@test evaloutput(nonlinmodel, Float64[]) ≈ nonlinmodel(Float64[]) ≈ zeros(2)
@test evaloutput(nonlinmodel, d) ≈ nonlinmodel(Float64[]) ≈ zeros(2)
@test_skip @allocations(evaloutput(nonlinmodel)) == 0

x = initstate!(nonlinmodel, [0, 10]) # do nothing for NonLinModel
@test evaloutput(nonlinmodel) ≈ [0, 0]
@@ -287,9 +296,9 @@ end
using DifferentiationInterface
import ForwardDiff, FiniteDiff
Ts = 1.0
f1(x,u,d,_) = x.^5 .+ u.^4 .+ d.^3
h1(x,d,_) = x.^2 .+ d
nonlinmodel1 = NonLinModel(f1,h1,Ts,1,1,1,1,solver=nothing)
f1!(x,u,d,_) = x.^5 .+ u.^4 .+ d.^3
h1!(x,d,_) = x.^2 .+ d
nonlinmodel1 = NonLinModel(f1!,h1!,Ts,1,1,1,1,solver=nothing)
x, u, d = [2.0], [3.0], [4.0]
linmodel1 = linearize(nonlinmodel1; x, u, d)
@test linmodel1.A ≈ 5*x.^4
@@ -302,9 +311,9 @@ end
@test linmodel1.Bu ≈ linmodel1b.Bu
@test linmodel1.Bd ≈ linmodel1b.Bd
@test linmodel1.C ≈ linmodel1b.C
@test linmodel1.Dd ≈ linmodel1b.Dd
@test linmodel1.Dd ≈ linmodel1b.Dd

nonlinmodel2 = NonLinModel(f1,h1,Ts,1,1,1,1,solver=nothing, jacobian=AutoFiniteDiff())
nonlinmodel2 = NonLinModel(f1!,h1!,Ts,1,1,1,1,solver=nothing, jacobian=AutoFiniteDiff())
linmodel2 = linearize(nonlinmodel2; x, u, d)
@test linmodel2.A ≈ 5*x.^4 atol=1e-3
@test linmodel2.Bu ≈ 4*u.^3 atol=1e-3
@@ -334,7 +343,7 @@ end
@test linmodel3.Bd ≈ Bd
@test linmodel3.C ≈ C
@test linmodel3.Dd ≈ Dd

# test `linearize` at a non-equilibrium point:
Ynl, Yl = let nonlinmodel3=nonlinmodel3
N = 5
@@ -348,18 +357,32 @@ end
yl = linmodel3(d)
Ynl[i] = ynl[1]
Yl[i] = yl[1]
linmodel3 = linearize(nonlinmodel3; u, d)
linearize!(linmodel3, nonlinmodel3; u, d)
updatestate!(nonlinmodel3, u, d)
updatestate!(linmodel3, u, d)
end
Ynl, Yl
end
@test all(isapprox.(Ynl, Yl, atol=1e-6))

# test nd==0 also works with AutoFiniteDiff (does not support empty matrices):
f2!(xnext, x, u, _, _) = (xnext .= x .+ u)
h2!(y, x, _, _) = (y .= x)
nonlinmodel4 = NonLinModel(f2!,h2!,Ts,1,1,1,0,solver=nothing,jacobian=AutoFiniteDiff())
@test_nowarn linearize(nonlinmodel4, x=[1], u=[2])

function f3!(xnext, x, u, d, _)
xnext .= x.*u .+ x.*d
end
function h3!(y, x, d, _)
y .= x.*d
end
nonlinmodel4 = NonLinModel(f3!, h3!, Ts, 1, 1, 1, 1, solver=nothing)
linmodel4 = linearize(nonlinmodel4; x, u, d)
# return nothing (see this issue : https://github.com/JuliaLang/julia/issues/51112):
linearize2!(linmodel, model) = (linearize!(linmodel, model); nothing)
linearize2!(linmodel4, nonlinmodel4)
@test_skip @allocations(linearize2!(linmodel4, nonlinmodel4)) == 0
end

@testitem "NonLinModel real time simulations" setup=[SetupMPCtests] begin
122 changes: 80 additions & 42 deletions test/2_test_state_estim.jl
Original file line number Diff line number Diff line change
@@ -65,14 +65,18 @@ end
using .SetupMPCtests, ControlSystemsBase, LinearAlgebra
linmodel1 = setop!(LinModel(sys,Ts,i_u=[1,2]), uop=[10,50], yop=[50,30])
skalmanfilter1 = SteadyKalmanFilter(linmodel1, nint_ym=[1, 1])
preparestate!(skalmanfilter1, [50, 30])
@test updatestate!(skalmanfilter1, [10, 50], [50, 30]) ≈ zeros(4)
preparestate!(skalmanfilter1, [50, 30])
@test updatestate!(skalmanfilter1, [10, 50], [50, 30], Float64[]) ≈ zeros(4)
u, y, d = [10, 50], [50, 30], Float64[]
preparestate!(skalmanfilter1, y)
@test updatestate!(skalmanfilter1, u, y) ≈ zeros(4)
preparestate!(skalmanfilter1, y)
@test updatestate!(skalmanfilter1, u, y, d) ≈ zeros(4)
@test skalmanfilter1.x̂0 ≈ zeros(4)
preparestate!(skalmanfilter1, [50, 30])
@test_skip @allocations(preparestate!(skalmanfilter1, y)) == 0
@test_skip @allocations(updatestate!(skalmanfilter1, u, y)) == 0
preparestate!(skalmanfilter1, y)
@test evaloutput(skalmanfilter1) ≈ skalmanfilter1() ≈ [50, 30]
@test evaloutput(skalmanfilter1, Float64[]) ≈ skalmanfilter1(Float64[]) ≈ [50, 30]
@test evaloutput(skalmanfilter1, d) ≈ skalmanfilter1(d) ≈ [50, 30]
@test_skip @allocations(evaloutput(skalmanfilter1, d)) == 0
@test initstate!(skalmanfilter1, [10, 50], [50, 30+1]) ≈ [zeros(3); [1]]
linmodel2 = LinModel(append(tf(1, [1, 0]), tf(2, [10, 1])), 1.0)
skalmanfilter2 = SteadyKalmanFilter(linmodel2, nint_u=[1, 1], direct=false)
@@ -194,14 +198,18 @@ end
using .SetupMPCtests, ControlSystemsBase, LinearAlgebra
linmodel1 = setop!(LinModel(sys,Ts,i_u=[1,2]), uop=[10,50], yop=[50,30])
kalmanfilter1 = KalmanFilter(linmodel1)
preparestate!(kalmanfilter1, [50, 30])
@test updatestate!(kalmanfilter1, [10, 50], [50, 30]) ≈ zeros(4)
preparestate!(kalmanfilter1, [50, 30])
@test updatestate!(kalmanfilter1, [10, 50], [50, 30], Float64[]) ≈ zeros(4)
u, y, d = [10, 50], [50, 30], Float64[]
preparestate!(kalmanfilter1, y)
@test updatestate!(kalmanfilter1, u, y) ≈ zeros(4)
preparestate!(kalmanfilter1, y)
@test updatestate!(kalmanfilter1, u, y, d) ≈ zeros(4)
@test kalmanfilter1.x̂0 ≈ zeros(4)
preparestate!(kalmanfilter1, [50, 30])
@test_skip @allocations(preparestate!(kalmanfilter1, y)) == 0
@test_skip @allocations(updatestate!(kalmanfilter1, u, y)) == 0
preparestate!(kalmanfilter1, y)
@test evaloutput(kalmanfilter1) ≈ kalmanfilter1() ≈ [50, 30]
@test evaloutput(kalmanfilter1, Float64[]) ≈ kalmanfilter1(Float64[]) ≈ [50, 30]
@test evaloutput(kalmanfilter1, d) ≈ kalmanfilter1(d) ≈ [50, 30]
@test_skip @allocations(evaloutput(kalmanfilter1, d)) == 0
@test initstate!(kalmanfilter1, [10, 50], [50, 30+1]) ≈ [zeros(3); [1]]
setstate!(kalmanfilter1, [1,2,3,4])
@test kalmanfilter1.x̂0 ≈ [1,2,3,4]
@@ -311,14 +319,18 @@ end
using .SetupMPCtests, ControlSystemsBase, LinearAlgebra
linmodel1 = setop!(LinModel(sys,Ts,i_u=[1,2]), uop=[10,50], yop=[50,30])
lo1 = Luenberger(linmodel1, nint_ym=[1, 1])
preparestate!(lo1, [50, 30])
@test updatestate!(lo1, [10, 50], [50, 30]) ≈ zeros(4)
preparestate!(lo1, [50, 30])
@test updatestate!(lo1, [10, 50], [50, 30], Float64[]) ≈ zeros(4)
u, y, d = [10, 50], [50, 30], Float64[]
preparestate!(lo1, y)
@test updatestate!(lo1, u, y) ≈ zeros(4)
preparestate!(lo1, y)
@test updatestate!(lo1, u, y, d) ≈ zeros(4)
@test lo1.x̂0 ≈ zeros(4)
preparestate!(lo1, [50, 30])
@test_skip @allocations(preparestate!(lo1, y)) == 0
@test_skip @allocations(updatestate!(lo1, u, y)) == 0
preparestate!(lo1, y)
@test evaloutput(lo1) ≈ lo1() ≈ [50, 30]
@test evaloutput(lo1, Float64[]) ≈ lo1(Float64[]) ≈ [50, 30]
@test evaloutput(lo1, d) ≈ lo1(d) ≈ [50, 30]
@test_skip @allocations(evaloutput(lo1, d)) == 0
@test initstate!(lo1, [10, 50], [50, 30+1]) ≈ [zeros(3); [1]]
setstate!(lo1, [1,2,3,4])
@test lo1.x̂0 ≈ [1,2,3,4]
@@ -436,14 +448,18 @@ end
using .SetupMPCtests, ControlSystemsBase, LinearAlgebra
linmodel1 = setop!(LinModel(sys,Ts,i_u=[1,2]) , uop=[10,50], yop=[50,30])
internalmodel1 = InternalModel(linmodel1)
preparestate!(internalmodel1, [50, 30] .+ 1)
@test updatestate!(internalmodel1, [10, 50], [50, 30] .+ 1) ≈ zeros(2)
preparestate!(internalmodel1, [50, 30] .+ 1)
@test updatestate!(internalmodel1, [10, 50], [50, 30] .+ 1, Float64[]) ≈ zeros(2)
u, y, d = [10, 50], [50, 30] .+ 1, Float64[]
preparestate!(internalmodel1, y)
@test updatestate!(internalmodel1, u, y) ≈ zeros(2)
preparestate!(internalmodel1, y)
@test updatestate!(internalmodel1, u, y, d) ≈ zeros(2)
@test internalmodel1.x̂d ≈ internalmodel1.x̂0 ≈ zeros(2)
@test internalmodel1.x̂s ≈ ones(2)
preparestate!(internalmodel1, [51, 31])
@test evaloutput(internalmodel1, Float64[]) ≈ [51,31]
@test_skip @allocations(preparestate!(internalmodel1, y)) == 0
@test_skip @allocations(updatestate!(internalmodel1, u, y)) == 0
preparestate!(internalmodel1, y)
@test evaloutput(internalmodel1, d) ≈ [51,31]
@test_skip @allocations(evaloutput(internalmodel1, d)) == 0
@test initstate!(internalmodel1, [10, 50], [50, 30]) ≈ zeros(2)
@test internalmodel1.x̂s ≈ zeros(2)
setstate!(internalmodel1, [1,2])
@@ -557,19 +573,30 @@ end
@testitem "UnscentedKalmanFilter estimator methods" setup=[SetupMPCtests] begin
using .SetupMPCtests, ControlSystemsBase, LinearAlgebra
linmodel1 = LinModel(sys,Ts,i_u=[1,2])
f(x,u,_,model) = model.A*x + model.Bu*u
h(x,_,model) = model.C*x
nonlinmodel = NonLinModel(f, h, Ts, 2, 2, 2, solver=nothing, p=linmodel1)
function f!(xnext, x,u,_,model)
mul!(xnext, model.A, x)
mul!(xnext, model.Bu, u, 1, 1)
return nothing
end
function h!(y, x,_,model)
mul!(y, model.C, x)
return nothing
end
nonlinmodel = NonLinModel(f!, h!, Ts, 2, 2, 2, solver=nothing, p=linmodel1)
nonlinmodel = setop!(nonlinmodel, uop=[10,50], yop=[50,30])
ukf1 = UnscentedKalmanFilter(nonlinmodel)
preparestate!(ukf1, [50, 30])
@test updatestate!(ukf1, [10, 50], [50, 30]) ≈ zeros(4) atol=1e-9
preparestate!(ukf1, [50, 30])
@test updatestate!(ukf1, [10, 50], [50, 30], Float64[]) ≈ zeros(4) atol=1e-9
u, y, d = [10, 50], [50, 30], Float64[]
preparestate!(ukf1, y)
@test updatestate!(ukf1, u, y) ≈ zeros(4) atol=1e-9
preparestate!(ukf1, y)
@test updatestate!(ukf1, u, y, d) ≈ zeros(4) atol=1e-9
@test ukf1.x̂0 ≈ zeros(4) atol=1e-9
preparestate!(ukf1, [50, 30])
@test_skip @allocations(preparestate!(ukf1, y)) == 0
@test_skip @allocations(updatestate!(ukf1, u, y)) == 0
preparestate!(ukf1, y)
@test evaloutput(ukf1) ≈ ukf1() ≈ [50, 30]
@test evaloutput(ukf1, Float64[]) ≈ ukf1(Float64[]) ≈ [50, 30]
@test evaloutput(ukf1, d) ≈ ukf1(d) ≈ [50, 30]
@test_skip @allocations(evaloutput(ukf1, d)) == 0
@test initstate!(ukf1, [10, 50], [50, 30+1]) ≈ zeros(4) atol=1e-9
setstate!(ukf1, [1,2,3,4])
@test ukf1.x̂0 ≈ [1,2,3,4]
@@ -705,19 +732,30 @@ end
using DifferentiationInterface
import FiniteDiff
linmodel1 = LinModel(sys,Ts,i_u=[1,2])
f(x,u,_,model) = model.A*x + model.Bu*u
h(x,_,model) = model.C*x
nonlinmodel = NonLinModel(f, h, Ts, 2, 2, 2, solver=nothing, p=linmodel1)
function f!(xnext, x,u,_,model)
mul!(xnext, model.A, x)
mul!(xnext, model.Bu, u, 1, 1)
return nothing
end
function h!(y, x,_,model)
mul!(y, model.C, x)
return nothing
end
nonlinmodel = NonLinModel(f!, h!, Ts, 2, 2, 2, solver=nothing, p=linmodel1)
nonlinmodel = setop!(nonlinmodel, uop=[10,50], yop=[50,30])
ekf1 = ExtendedKalmanFilter(nonlinmodel)
preparestate!(ekf1, [50, 30])
@test updatestate!(ekf1, [10, 50], [50, 30]) ≈ zeros(4) atol=1e-9
preparestate!(ekf1, [50, 30])
@test updatestate!(ekf1, [10, 50], [50, 30], Float64[]) ≈ zeros(4) atol=1e-9
u, y, d = [10, 50], [50, 30], Float64[]
preparestate!(ekf1, y)
@test updatestate!(ekf1, u, y) ≈ zeros(4) atol=1e-9
preparestate!(ekf1, y)
@test updatestate!(ekf1, u, y, d) ≈ zeros(4) atol=1e-9
@test ekf1.x̂0 ≈ zeros(4) atol=1e-9
preparestate!(ekf1, [50, 30])
@test_skip @allocations(preparestate!(ekf1, y)) == 0
@test_skip @allocations(updatestate!(ekf1, u, y)) == 0
preparestate!(ekf1, y)
@test evaloutput(ekf1) ≈ ekf1() ≈ [50, 30]
@test evaloutput(ekf1, Float64[]) ≈ ekf1(Float64[]) ≈ [50, 30]
@test evaloutput(ekf1, d) ≈ ekf1(d) ≈ [50, 30]
@test_skip @allocations(evaloutput(ekf1, d)) == 0
@test initstate!(ekf1, [10, 50], [50, 30+1]) ≈ zeros(4);
setstate!(ekf1, [1,2,3,4])
@test ekf1.x̂0 ≈ [1,2,3,4]
5 changes: 3 additions & 2 deletions test/3_test_predictive_control.jl
Original file line number Diff line number Diff line change
@@ -425,12 +425,13 @@ end
@testitem "ExplicitMPC moves and getinfo" setup=[SetupMPCtests] begin
using .SetupMPCtests, ControlSystemsBase, LinearAlgebra
mpc1 = ExplicitMPC(LinModel(tf(5, [2, 1]), 3), Nwt=[0], Hp=1000, Hc=1)
r = [5]
preparestate!(mpc1, [0])
r, y = [5], [0]
preparestate!(mpc1, y)
u = moveinput!(mpc1, r)
@test u ≈ [1] atol=1e-2
u = mpc1(r)
@test u ≈ [1] atol=1e-2
@test_skip @allocations(moveinput!(mpc1, r)) == 0
info = getinfo(mpc1)
@test info[:u] ≈ u
@test info[:Ŷ][end] ≈ r[1] atol=1e-2