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Merged
ocots merged 1 commit into from
Jul 30, 2026
Merged

[AUTO] JuliaFormatter.jl run #18

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2 changes: 1 addition & 1 deletion src/ad_types.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -109,7 +109,7 @@ function ad(
MDX<:Traits.AbstractMutabilityTrait,
MDY<:Traits.AbstractMutabilityTrait,
}
_check_not_hvf(X);
_check_not_hvf(X)
_check_not_hvf(Y)
_check_outofplace(MDX) # static dispatch on type parameter — no runtime call
_check_outofplace(MDY)
Expand Down
16 changes: 8 additions & 8 deletions src/lie_macro.jl
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Expand Up @@ -163,9 +163,9 @@ function _lie_mac(
has_var::Val,
backend,
) where {TD,VD}
_check_td(a, TD, has_aut);
_check_td(a, TD, has_aut)
_check_td(b, TD, has_aut)
_check_vd(a, VD, has_var);
_check_vd(a, VD, has_var)
_check_vd(b, VD, has_var)
return ad(_as_vf(a, TD, VD), _as_vf(b, TD, VD); ad_backend=backend)
end
Expand Down Expand Up @@ -285,9 +285,9 @@ function _poisson_mac(
has_var::Val,
backend,
) where {TD,VD}
_check_td(h, TD, has_aut);
_check_td(h, TD, has_aut)
_check_td(g, TD, has_aut)
_check_vd(h, VD, has_var);
_check_vd(h, VD, has_var)
_check_vd(g, VD, has_var)
return Poisson(_as_ham(h, TD, VD), _as_ham(g, TD, VD); ad_backend=backend)
end
Expand Down Expand Up @@ -360,20 +360,20 @@ Parse keyword arguments for the @Lie macro.
- `Expr`: Error expression if parsing failed, otherwise `nothing`.
"""
function __parse_lie_opts(args...)
is_autonomous = Data.__is_autonomous();
is_autonomous = Data.__is_autonomous()
has_aut = false
is_variable = Data.__is_variable();
is_variable = Data.__is_variable()
has_var = false
backend_expr = :(CTLie.__dg_ad_backend())

for arg in args
if arg isa Expr && (arg.head === :(=) || arg.head === :kw)
key, val = arg.args[1], arg.args[2]
if key === :is_autonomous
is_autonomous = val;
is_autonomous = val
has_aut = true
elseif key === :is_variable
is_variable = val;
is_variable = val
has_var = true
elseif key === :ad_backend
backend_expr = val
Expand Down
6 changes: 2 additions & 4 deletions src/time_derivative.jl
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Expand Up @@ -108,8 +108,7 @@ Used to differentiate tuple-valued outputs slot-by-slot, since
See also: [`CTLie.TimeDeriv_HVF`](@ref), [`CTLie._HVFComp2`](@ref)
"""
struct _HVFComp1{F} <: Function
;
X::F;
X::F
end

"""
Expand All @@ -123,8 +122,7 @@ Used to differentiate tuple-valued outputs slot-by-slot, since
See also: [`CTLie.TimeDeriv_HVF`](@ref), [`CTLie._HVFComp1`](@ref)
"""
struct _HVFComp2{F} <: Function
;
X::F;
X::F
end

(_c::_HVFComp1)(args...) = _c.X(args...)[1]
Expand Down
22 changes: 11 additions & 11 deletions test/suite/differential_geometry/test_lift_dg.jl
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Expand Up @@ -13,7 +13,7 @@ function test_lift_dg()
Test.@testset "Lift() - Function → Function" verbose=VERBOSE showtiming=SHOWTIMING begin
F(x) = [x[2], -x[1]]
H2 = CTLie.Lift(F)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
# H2(x,p) = p' * F(x) = [3,4]·[2,-1] = 6-4 = 2
Test.@test H2(x0, p0) ≈ 2.0 atol=1e-10
Expand All @@ -37,7 +37,7 @@ function test_lift_dg()
Test.@testset "Lift() - @inferred type-stability" verbose=VERBOSE showtiming=SHOWTIMING begin
F(x) = [x[2], -x[1]]
H = CTLie.Lift(F)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
Test.@test_nowarn Test.@inferred H(x0, p0)
end
Expand All @@ -46,7 +46,7 @@ function test_lift_dg()
F_na(t, x) = [t * x[2], -x[1]]
H_na = CTLie.Lift(F_na; is_autonomous=false)
t0 = 2.0
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
Test.@test_nowarn Test.@inferred H_na(t0, x0, p0)
end
Expand All @@ -61,7 +61,7 @@ function test_lift_dg()
F(x) = [x[2], -x[1]]
H_kw = CTLie.Lift(F; is_autonomous=true, is_variable=false)
H_typed = CTLie.Lift(F, Traits.Autonomous, Traits.Fixed)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
Test.@test H_kw(x0, p0) ≈ H_typed(x0, p0) atol=1e-10
end
Expand All @@ -78,7 +78,7 @@ function test_lift_dg()
Test.@test H.f isa CTLie.LiftedHamiltonianFunction

# Check correctness
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
# H(x,p) = p'*X(x) = [3,4]·[2,-1] = 6-4 = 2
Test.@test H(x0, p0) ≈ 2.0 atol=1e-10
Expand All @@ -95,8 +95,8 @@ function test_lift_dg()
F(x, v) = [v[1] * x[2], -x[1]]
H = CTLie.Lift(F; is_autonomous=true, is_variable=true)
Test.@test H isa Function
x0 = [1.0, 2.0];
p0 = [3.0, 4.0];
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
v0 = [2.0]
# H(x,p,v) = p' * F(x,v) = [3,4]·[2*2,-1] = 12-4 = 8
Test.@test H(x0, p0, v0) ≈ 8.0 atol=1e-10
Expand All @@ -106,9 +106,9 @@ function test_lift_dg()
F(t, x, v) = [t * v[1] * x[2], -x[1]]
H = CTLie.Lift(F; is_autonomous=false, is_variable=true)
Test.@test H isa Function
t0 = 2.0;
x0 = [1.0, 2.0];
p0 = [3.0, 4.0];
t0 = 2.0
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
v0 = [2.0]
# H(t,x,p,v) = p' * F(t,x,v) = [3,4]·[2*2*2,-1] = 24-4 = 20
Test.@test H(t0, x0, p0, v0) ≈ 20.0 atol=1e-10
Expand All @@ -117,7 +117,7 @@ function test_lift_dg()
Test.@testset "Lift() - scalar case" verbose=VERBOSE showtiming=SHOWTIMING begin
F(x) = -2 * x # returns scalar (treated as 1D vector)
H = CTLie.Lift(F)
x0 = 2.0;
x0 = 2.0
p0 = 3.0
# H(x,p) = p * F(x) = 3 * (-4) = -12
Test.@test H(x0, p0) ≈ -12.0 atol=1e-10
Expand Down
10 changes: 5 additions & 5 deletions test/suite/differential_geometry/test_macro_dg.jl
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Expand Up @@ -13,8 +13,8 @@ const VERBOSE = isdefined(Main, :TestData) ? Main.TestData.VERBOSE : true
const SHOWTIMING = isdefined(Main, :TestData) ? Main.TestData.SHOWTIMING : true

# ─── Shared constants used across many testsets ────────────────────────────
const _Γ = 2;
const _γ = 1;
const _Γ = 2
const _γ = 1
const _δ = _γ - _Γ # δ = -1
const _t = 1.0
const _x3 = [1.0, 2.0, 3.0]
Expand Down Expand Up @@ -362,7 +362,7 @@ function test_macro_dg()

# =========================================================================
Test.@testset "poisson macro — Hamiltonians, nonautonomous nonfixed" verbose=VERBOSE showtiming=SHOWTIMING begin
t2 = 2.0;
t2 = 2.0
vv = [4.0, 4.0]
f = (t, x, p, v) -> t*v[1]*x[2]^2 + 2x[1]^2 + p[1]^2 + v[2]
g = (t, x, p, v) -> 3x[2]^2 - x[1]^2 + p[2]^2 + p[1] + t - v[2]
Expand Down Expand Up @@ -444,7 +444,7 @@ function test_macro_dg()

# =========================================================================
Test.@testset "poisson macro — plain functions, nonautonomous nonfixed" verbose=VERBOSE showtiming=SHOWTIMING begin
t2 = 2.0;
t2 = 2.0
vv = 2.0
f = (t, x, p, v) -> 0.5*(x[1]^2 + x[2]^2 + p[1]^2 + v)
g = (t, x, p, v) -> 0.5*(x[1]^2 + x[2]^2 + p[2]^2 + v)
Expand Down Expand Up @@ -501,7 +501,7 @@ function test_macro_dg()
Test.@test mac_Hf_v(_x2, _p2, vv) ≈ ref_v(_x2, _p2, vv) atol=1e-6

# Function + Hamiltonian, nonautonomous nonfixed
t2 = 2.0;
t2 = 2.0
vv = 2.0
h_tv = (t, x, p, v) -> t*x[2]^2 + 2x[1]^2 + p[1]^2 + v
g_tv = (t, x, p, v) -> 3x[2]^2 - x[1]^2 + p[2]^2 + v
Expand Down
40 changes: 20 additions & 20 deletions test/suite/differential_geometry/test_poisson_dg.jl
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Expand Up @@ -20,7 +20,7 @@ function test_poisson_dg()
G(x, p) = p[2]^2 / 2 + x[2]
PH = CTLie.Poisson(H, G)
PG = CTLie.Poisson(G, H)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
Test.@test PH(x0, p0) ≈ -PG(x0, p0) atol=1e-6
end
Expand All @@ -31,7 +31,7 @@ function test_poisson_dg()
G(x, p) = p[1] # ∇pG = [1,0], ∇xG = 0
# {H,G} = ∇pH · ∇xG - ∇xH · ∇pG = 0·0 - [1,0]·[1,0] = -1
PB = CTLie.Poisson(H, G)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
Test.@test PB(x0, p0) ≈ -1.0 atol=1e-6
end
Expand All @@ -57,8 +57,8 @@ function test_poisson_dg()
H(t, x, p) = t * p[1]
G(t, x, p) = x[1]
PB = CTLie.Poisson(H, G; is_autonomous=false, is_variable=false)
t0 = 3.0;
x0 = [1.0, 2.0];
t0 = 3.0
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
Test.@test PB(t0, x0, p0) ≈ t0 atol=1e-6
end
Expand All @@ -69,8 +69,8 @@ function test_poisson_dg()
H(x, p, v) = v[1] * p[1]
G(x, p, v) = x[1]
PB = CTLie.Poisson(H, G; is_autonomous=true, is_variable=true)
x0 = [1.0, 2.0];
p0 = [0.5, 1.0];
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
v0 = [2.0]
Test.@test PB(x0, p0, v0) ≈ v0[1] atol=1e-6
end
Expand All @@ -81,9 +81,9 @@ function test_poisson_dg()
H(t, x, p, v) = t * v[1] * p[1]
G(t, x, p, v) = x[1]
PB = CTLie.Poisson(H, G; is_autonomous=false, is_variable=true)
t0 = 3.0;
x0 = [1.0, 2.0];
p0 = [0.5, 1.0];
t0 = 3.0
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
v0 = [2.0]
Test.@test PB(t0, x0, p0, v0) ≈ t0 * v0[1] atol=1e-6
end
Expand All @@ -107,7 +107,7 @@ function test_poisson_dg()
H(x, p) = p[1]^2 / 2 + x[1]^2
G(x, p) = x[1] * p[1]
PB = CTLie.Poisson(H, G)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
Test.@test (Test.@inferred PB(x0, p0)) isa Float64
end
Expand All @@ -116,8 +116,8 @@ function test_poisson_dg()
H(x, p, v) = v[1] * p[1]^2 / 2 + x[1]^2
G(x, p, v) = x[1] * p[1]
PB = CTLie.Poisson(H, G; is_autonomous=true, is_variable=true)
x0 = [1.0, 2.0];
p0 = [0.5, 1.0];
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
v0 = [2.0]
Test.@test (Test.@inferred PB(x0, p0, v0)) isa Float64
end
Expand All @@ -126,8 +126,8 @@ function test_poisson_dg()
H(t, x, p) = t * p[1]
G(t, x, p) = x[1]
PB = CTLie.Poisson(H, G; is_autonomous=false, is_variable=false)
t0 = 3.0;
x0 = [1.0, 2.0];
t0 = 3.0
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
Test.@test (Test.@inferred PB(t0, x0, p0)) isa Float64
end
Expand All @@ -136,9 +136,9 @@ function test_poisson_dg()
H(t, x, p, v) = t * v[1] * p[1]^2 / 2 + x[1]
G(t, x, p, v) = x[1] * p[1]
PB = CTLie.Poisson(H, G; is_autonomous=false, is_variable=true)
t0 = 3.0;
x0 = [1.0, 2.0];
p0 = [0.5, 1.0];
t0 = 3.0
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
v0 = [2.0]
Test.@test (Test.@inferred PB(t0, x0, p0, v0)) isa Float64
end
Expand All @@ -150,7 +150,7 @@ function test_poisson_dg()
ad_backend=ADTypes.AutoForwardDiff()
)
PB = CTLie.Poisson(H, G; ad_backend=backend)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
val = PB(x0, p0)
Test.@test val isa Number
Expand All @@ -163,7 +163,7 @@ function test_poisson_dg()
# Autonomous, Fixed
PB_af_typed = CTLie.Poisson(H, G, Traits.Autonomous, Traits.Fixed)
PB_af_kwargs = CTLie.Poisson(H, G; is_autonomous=true, is_variable=false)
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [0.5, 1.0]
Test.@test PB_af_typed(x0, p0) ≈ PB_af_kwargs(x0, p0) atol=1e-6

Expand Down Expand Up @@ -197,7 +197,7 @@ function test_poisson_dg()
H(x, p) = 0.5 * (p^2 + x^2)
G(x, p) = x
PB = CTLie.Poisson(H, G)
x0 = 1.0;
x0 = 1.0
p0 = 3.0
# {H, G} = ∂H/∂p * ∂G/∂x - ∂H/∂x * ∂G/∂p = p * 1 - x * 0 = p
Test.@test PB(x0, p0) ≈ 3.0 atol=1e-6
Expand Down
28 changes: 14 additions & 14 deletions test/suite/differential_geometry/test_time_derivative_dg.jl
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Expand Up @@ -45,7 +45,7 @@ function test_time_derivative_dg()
# internal functor (callable struct, not closure)
Test.@test dX.f isa CTLie.TimeDeriv_VF
# ∂/∂t [t*x2, -t*x1] = [x2, -x1]
t0 = 2.0;
t0 = 2.0
x0 = [1.0, 2.0]
Test.@test isapprox(dX(t0, x0), [x0[2], -x0[1]]; atol=1e-6)
dX(t0, x0) # warm-up
Expand Down Expand Up @@ -80,8 +80,8 @@ function test_time_derivative_dg()
(t, x, v) -> [t * v[1] * x[2], -x[1]]; is_autonomous=false, is_variable=true
)
dX = CTLie.∂ₜ(X)
t0 = 2.0;
x0 = [1.0, 2.0];
t0 = 2.0
x0 = [1.0, 2.0]
v0 = [3.0]
Test.@test isapprox(dX(t0, x0, v0), [v0[1] * x0[2], 0.0]; atol=1e-6)
end
Expand All @@ -98,7 +98,7 @@ function test_time_derivative_dg()
Test.@test dH isa Data.Hamiltonian
Test.@test dH isa Data.AbstractHamiltonian{Traits.NonAutonomous,Traits.Fixed}
# ∂/∂t [t * p'x] = p'x
x0 = [1.0, 2.0];
x0 = [1.0, 2.0]
p0 = [3.0, 4.0]
Test.@test dH(2.0, x0, p0) ≈ p0' * x0 atol=1e-6
dH(2.0, x0, p0) # warm-up
Expand Down Expand Up @@ -129,9 +129,9 @@ function test_time_derivative_dg()
(t, x, p, v) -> t * v[1] * p[1]; is_autonomous=false, is_variable=true
)
dH = CTLie.∂ₜ(H)
t0 = 2.0;
x0 = [1.0];
p0 = [3.0];
t0 = 2.0
x0 = [1.0]
p0 = [3.0]
v0 = [4.0]
Test.@test dH(t0, x0, p0, v0) ≈ v0[1] * p0[1] atol=1e-6
end
Expand All @@ -150,8 +150,8 @@ function test_time_derivative_dg()
Test.@test dX isa Data.AbstractHamiltonianVectorField{
Traits.NonAutonomous,Traits.Fixed,Traits.OutOfPlace
}
t0 = 2.0;
x0 = [1.0];
t0 = 2.0
x0 = [1.0]
p0 = [3.0]
dx, dp = dX(t0, x0, p0)
Test.@test dx ≈ p0 atol=1e-6
Expand Down Expand Up @@ -192,9 +192,9 @@ function test_time_derivative_dg()
(t, x, p, v) -> (t * v[1] * p, -x); is_autonomous=false, is_variable=true
)
dX = CTLie.∂ₜ(X)
t0 = 2.0;
x0 = [1.0];
p0 = [3.0];
t0 = 2.0
x0 = [1.0]
p0 = [3.0]
v0 = [4.0]
dx, dp = dX(t0, x0, p0, v0)
Test.@test dx ≈ v0[1] .* p0 atol=1e-6
Expand All @@ -206,8 +206,8 @@ function test_time_derivative_dg()
(t, x, p) -> (t * p, -t * x); is_autonomous=false, is_variable=false
)
dX = CTLie.∂ₜ(X)
t0 = 2.0;
x0 = [1.0];
t0 = 2.0
x0 = [1.0]
p0 = [3.0]
dX(t0, x0, p0) # warm-up
Test.@test_nowarn Test.@inferred dX(t0, x0, p0)
Expand Down