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tweak
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baggepinnen committed Nov 21, 2024
1 parent f87943e commit eae2b46
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Showing 2 changed files with 9 additions and 9 deletions.
2 changes: 1 addition & 1 deletion docs/Project.toml
Original file line number Diff line number Diff line change
Expand Up @@ -22,5 +22,5 @@ julia = "1.6"
Lux = "1.3"
SparseConnectivityTracer = "0.6.8"
SparseMatrixColorings = "0.4.10"
DifferentiationInterface = "0.6.23"
DifferentiationInterface = "0.6.22"
ComponentArrays = "0.15.19"
16 changes: 8 additions & 8 deletions test/test_jet.jl
Original file line number Diff line number Diff line change
Expand Up @@ -20,8 +20,8 @@ const _B = @SMatrix [-0.7400216956683083 1.6097265310456392; -1.4384539113366408
const _C = SMatrix{ny,ny}(eye(ny))
# C = SMatrix{p,n}([1 1])

dynamics(x,u,p,t) = _A*x .+ _B*u
measurement(x,u,p,t) = _C*x
dynamics_jet(x,u,p,t) = _A*x .+ _B*u
measurement_jet(x,u,p,t) = _C*x

T = 200 # Number of time steps
kf = KalmanFilter(_A, _B, _C, 0, eye(nx), eye(ny), d0)
Expand All @@ -35,7 +35,7 @@ x,u,y = tosvec.((x,u,y))
@test_opt correct!(kf, u[1], y[1])
@report_call correct!(kf, u[1], y[1])

ukf = UnscentedKalmanFilter(dynamics, measurement, eye(nx), eye(ny), d0; ny, nu)
ukf = UnscentedKalmanFilter(dynamics_jet, measurement_jet, eye(nx), eye(ny), d0; ny, nu)
@test ukf.R1 isa SMatrix{2, 2, Float64, 4}
@test_opt predict!(ukf, u[1])
@report_call predict!(ukf, u[1])
Expand All @@ -53,7 +53,7 @@ skf = SqKalmanFilter(_A, _B, _C, 0, eye(nx), eye(ny), d0)
@report_call correct!(skf, u[1], y[1])


ekf = ExtendedKalmanFilter(dynamics, measurement, eye(nx), eye(ny), d0; nu)
ekf = ExtendedKalmanFilter(dynamics_jet, measurement_jet, eye(nx), eye(ny), d0; nu)
@test ekf.kf.R1 isa SMatrix{2, 2, Float64, 4}
@test_opt predict!(ekf, u[1])
@report_call predict!(ekf, u[1])
Expand All @@ -66,21 +66,21 @@ ekf = ExtendedKalmanFilter(dynamics, measurement, eye(nx), eye(ny), d0; nu)
## Test allocations ============================================================
forward_trajectory(kf, u, y)
a = @allocations forward_trajectory(kf, u, y)
@test a <= 15 # Allocations occur when the arrays are allocated for saving the data, the important thing is that the number of allocations do not grow with the length of the trajectory (T = 200)
@test a <= 16*1.1 # Allocations occur when the arrays are allocated for saving the data, the important thing is that the number of allocations do not grow with the length of the trajectory (T = 200)

forward_trajectory(ukf, u, y)
a = @allocations forward_trajectory(ukf, u, y)
@test a <= 15
@test a <= 16*1.1

forward_trajectory(skf, u, y)
a = @allocations forward_trajectory(skf, u, y)

if get(ENV, "CI", nothing) == "true"
@test a <= 217 # Mysteriously higher on CI despite identical package environments
@test a <= 300 # Mysteriously higher on CI despite identical package environments
else
@test a <= 50 # was 7 on julia v1.10.6
end

forward_trajectory(ekf, u, y)
a = @allocations forward_trajectory(ekf, u, y)
@test a <= 15
@test a <= 16*1.1

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