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Author: reykboerner

src/largedeviations/min_action_method.jl

@@ -35,8 +35,7 @@ value.
   - `show_progress = false`: whether to print a progress bar
 """
 function min_action_method(
-    sys::ContinuousTimeDynamicalSystem, x_i, x_f, T::Real;
-    N=100, kwargs...
+    sys::ContinuousTimeDynamicalSystem, x_i, x_f, T::Real; N=100, kwargs...
 )
     init = reduce(hcat, range(x_i, x_f; length=N))
     return min_action_method(sys, init, T; kwargs...)
@@ -71,8 +70,9 @@ function min_action_method(
         proper_MAM_system(sys)
     end
     times = range(0.0, T; length=size(init, 2))
-    S(x) = action(sys, fix_ends(x, init[:, 1], init[:, end]), times, functional;
-        noise_strength)
+    S(x) = action(
+        sys, fix_ends(x, init[:, 1], init[:, end]), times, functional; noise_strength
+    )
 
     optf = OptimizationFunction((x, _) -> S(x), ad_type)
     prob = OptimizationProblem(optf, init, ())
@@ -85,12 +85,7 @@ function min_action_method(
     end
 
     sol = solve(
-        prob,
-        method;
-        maxiters=maxiter,
-        callback=callback,
-        abstol=abstol,
-        reltol=reltol,
+        prob, method; maxiters=maxiter, callback=callback, abstol=abstol, reltol=reltol
     )
     return MinimumActionPath(StateSpaceSet(sol.u'), sol.objective)
 end;
@@ -113,4 +108,4 @@ end;
 
 Alias for [`min_action_method`](@ref).]
 """
-const action_minimizer = min_action_method
+const action_minimizer = min_action_method

test/CoupledSDEs.jl

@@ -116,7 +116,7 @@ using CriticalTransitions, Test
 
             g!(du, u, p, t) = du .= u
             @test_throws ArgumentError CoupledSDEs(
-                f!, zeros(2); g=g!, covariance=[1 0.3; 0.3 1]
+                f!, zeros(2); g=(g!), covariance=[1 0.3; 0.3 1]
             )
 
             g(u, p, t) = u

test/largedeviations/API.jl

@@ -1,13 +1,13 @@
 @testset "autonomous invertible additive noise" begin
     f!(du, u, p, t) = du .= 1.01u
-    g_corr_alt!(du, u, p, t) = (du .= [1 0.3 1; 0.3 1 1]; return nothing)
-    corr_alt = CoupledSDEs(f!, zeros(2); g=g_corr_alt!, noise_prototype=zeros(2, 3))
+    g_corr_alt!(du, u, p, t) = (du.=[1 0.3 1; 0.3 1 1]; return nothing)
+    corr_alt = CoupledSDEs(f!, zeros(2); g=(g_corr_alt!), noise_prototype=zeros(2, 3))
 
-    g_addit_non_autom!(du, u, p, t) = (du .= 1 / (1 + t); return nothing)
-    addit_non_autom = CoupledSDEs(f!, zeros(2); g=g_addit_non_autom!)
+    g_addit_non_autom!(du, u, p, t) = (du.=1 / (1 + t); return nothing)
+    addit_non_autom = CoupledSDEs(f!, zeros(2); g=(g_addit_non_autom!))
 
-    g_linear_multipli!(du, u, p, t) = (du .= u; return nothing)
-    linear_multipli = CoupledSDEs(f!, rand(2) ./ 10; g=g_linear_multipli!)
+    g_linear_multipli!(du, u, p, t) = (du.=u; return nothing)
+    linear_multipli = CoupledSDEs(f!, rand(2) ./ 10; g=(g_linear_multipli!))
 
     x_i = SA[sqrt(2 / 3), sqrt(2 / 27)]
     x_f = SA[0.001, 0.0]