Formatting

Author: lamorton

src/systems/optimization/optimizationsystem.jl

@@ -392,7 +392,6 @@ function OptimizationProblemExpr{iip}(sys::OptimizationSystem, u0,
     rep_pars_vals!(obj_expr, pairs_arr)
     @show sys.constraints
     if length(sys.constraints) > 0
-        
         @named cons_sys = NonlinearSystem(sys.constraints, dvs, ps)
         cons = generate_function(cons_sys, checkbounds = checkbounds,
                                  linenumbers = linenumbers,

src/utils.jl

@@ -531,11 +531,10 @@ function collect_constants(eqs::Vector{Matrix{Num}}) # For nonlinear hessian
     return constants
 end
 
-
 collect_constants(x::Num) = collect_constants(unwrap(x))
 function collect_constants(expr::Symbolic{T}) where {T} # For jump system affect / rate 
     constants = Symbolic[]
-    collect_constants!(constants,expr)
+    collect_constants!(constants, expr)
     return constants
 end
 

test/jumpsystem.jl

@@ -3,7 +3,7 @@ MT = ModelingToolkit
 
 # basic MT SIR model with tweaks
 @parameters β γ t
-@constants h=1
+@constants h = 1
 @variables S(t) I(t) R(t)
 rate₁ = β * S * I * h
 affect₁ = [S ~ S - 1 * h, I ~ I + 1]

test/nonlinearsystem.jl

@@ -8,7 +8,7 @@ canonequal(a, b) = isequal(simplify(a), simplify(b))
 
 # Define some variables
 @parameters t σ ρ β
-@constants h=1
+@constants h = 1
 @variables x y z
 
 function test_nlsys_inference(name, sys, vs, ps)
@@ -88,7 +88,7 @@ sol = solve(prob, NewtonRaphson())
 
 @variables u F s a
 eqs1 = [
-    0 ~ σ * (y - x) * h +  F,
+    0 ~ σ * (y - x) * h + F,
     0 ~ x * (ρ - z) - u,
     0 ~ x * y - β * z,
     0 ~ x + y - z - u,
@@ -171,7 +171,8 @@ end
 # observed variable handling
 @variables t x(t) RHS(t)
 @parameters τ
-@named fol = NonlinearSystem([0 ~ (1 - x * h) / τ], [x], [τ]; observed = [RHS ~ (1 - x) / τ])
+@named fol = NonlinearSystem([0 ~ (1 - x * h) / τ], [x], [τ];
+                             observed = [RHS ~ (1 - x) / τ])
 @test isequal(RHS, @nonamespace fol.RHS)
 RHS2 = RHS
 @unpack RHS = fol

test/optimizationsystem.jl

@@ -2,7 +2,7 @@ using ModelingToolkit, SparseArrays, Test, Optimization, OptimizationOptimJL,
       OptimizationMOI, Ipopt, AmplNLWriter, Ipopt_jll
 
 @variables x y
-@constants h=1 
+@constants h = 1 
 @parameters a b
 loss = (a - x)^2 + b * (y * h - x^2)^2
 sys1 = OptimizationSystem(loss, [x, y], [a, b], name = :sys1)

test/pde.jl

@@ -2,7 +2,7 @@ using ModelingToolkit, DiffEqBase, LinearAlgebra
 
 # Define some variables
 @parameters t x
-@constants h=1
+@constants h = 1
 @variables u(..)
 Dt = Differential(t)
 Dxx = Differential(x)^2