Apply JuliaFormatter to fix code formatting

docs/src/basics/Composition.md

@@ -126,8 +126,8 @@ sys = System(
 # ...
 # directly in the defaults argument
     defaults = Pair{Num, Any}[x => u,
-    y => σ,
-    z => u - 0.1])
+y => σ,
+z => u - 0.1])
 # by assigning to the parameter
 sys.y = u * 1.1
 ```

docs/src/basics/MTKLanguage.md

@@ -382,7 +382,7 @@ Refer the following example for different ways to define symbolic arrays.
         p1[1:4]
         p2[1:N]
         p3[1:N,
-            1:M] = 10,
+        1:M] = 10,
         [description = "A multi-dimensional array of arbitrary length with description"]
         (p4[1:N, 1:M] = 10),
         [description = "An alternate syntax for p3 to match the syntax of vanilla parameters macro"]

docs/src/examples/sparse_jacobians.md

@@ -27,16 +27,16 @@ function brusselator_2d_loop(du, u, p, t)
         jm1 = limit(i + 1, N), limit(i - 1, N), limit(j + 1, N),
         limit(j - 1, N)
         du[i,
-            j,
-            1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
-                  4u[i, j, 1]) +
-                 B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
-                 brusselator_f(x, y, t)
+        j,
+        1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
+                       4u[i, j, 1]) +
+                      B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
+                      brusselator_f(x, y, t)
         du[i,
-            j,
-            2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
-                  4u[i, j, 2]) +
-                 A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
+        j,
+        2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
+                       4u[i, j, 2]) +
+                      A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
     end
 end
 p = (3.4, 1.0, 10.0, step(xyd_brusselator))

src/problems/docs.jl

@@ -219,7 +219,7 @@ function function_docstring(func, istd, optionals)
     Beyond the arguments listed below, this constructor accepts all keyword arguments
     supported by the DifferentialEquations.jl `solve` function. For a complete list
     and detailed descriptions, see the [DifferentialEquations.jl solve documentation](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/).
-  
+
     # Keyword arguments
 
     - `u0`: The `u0` vector for the corresponding problem, if available. Can be obtained

test/analysis_points.jl

@@ -680,7 +680,7 @@ end
     fr = CS.freqrespv(S, [0.01, 1, 100])
     # https://github.com/SciML/ModelingToolkit.jl/pull/3469
     reference_fr = ComplexF64[-1.2505330104772838e-11 - 2.500062613816021e-9im,
-        -0.0024688370221621625 - 0.002279011866413123im,
-        1.8100018764334602 + 0.3623845793211718im]
+    -0.0024688370221621625 - 0.002279011866413123im,
+    1.8100018764334602 + 0.3623845793211718im]
     @test isapprox(fr, reference_fr)
 end

test/clock.jl

@@ -333,7 +333,7 @@ eqs = [yd ~ Sample(dt)(y)
 
     @test sol.u≈sol2.u atol=1e-6
     @test sol_nosplit.u≈sol2.u atol=1e-6
-    
+
     ##
     @info "Testing hybrid system with components"
     using ModelingToolkitStandardLibrary.Blocks

test/initial_values.jl

@@ -306,13 +306,13 @@ end
     @mtkcompile sys = System(eqs, t)
 
     u0 = SA[D(x) => 2.0f0,
-        x => 1.0f0,
-        y => 0.0f0,
-        z => 0.0f0]
+    x => 1.0f0,
+    y => 0.0f0,
+    z => 0.0f0]
 
     p = SA[σ => 28.0f0,
-        ρ => 10.0f0,
-        β => 8.0f0 / 3]
+    ρ => 10.0f0,
+    β => 8.0f0 / 3]
 
     tspan = (0.0f0, 100.0f0)
     prob = ODEProblem(sys, [u0; p], tspan)

test/jacobiansparsity.jl

@@ -13,16 +13,16 @@ function brusselator_2d_loop(du, u, p, t)
         ip1, im1, jp1, jm1 = lim(i + 1, N), lim(i - 1, N), lim(j + 1, N),
         lim(j - 1, N)
         du[i,
-            j,
-            1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
-                  4u[i, j, 1]) +
-                 B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
-                 brusselator_f(x, y, t)
+        j,
+        1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
+                       4u[i, j, 1]) +
+                      B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
+                      brusselator_f(x, y, t)
         du[i,
-            j,
-            2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
-                  4u[i, j, 2]) +
-                 A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
+        j,
+        2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
+                       4u[i, j, 2]) +
+                      A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
     end
 end
 

test/modelingtoolkitize.jl

@@ -18,16 +18,16 @@ function brusselator_2d_loop(du, u, p, t)
         jm1 = limit(i + 1, N), limit(i - 1, N), limit(j + 1, N),
         limit(j - 1, N)
         du[i,
-            j,
-            1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
-                  4u[i, j, 1]) +
-                 B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
-                 brusselator_f(x, y, t)
+        j,
+        1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
+                       4u[i, j, 1]) +
+                      B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
+                      brusselator_f(x, y, t)
         du[i,
-            j,
-            2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
-                  4u[i, j, 2]) +
-                 A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
+        j,
+        2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
+                       4u[i, j, 2]) +
+                      A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
     end
 end
 

test/odesystem.jl

@@ -652,7 +652,8 @@ let
     vars = @variables x y
     arr = ModelingToolkit.varmap_to_vars(
         Dict([x => 0.0, y => [0.0, 1.0]]), vars; use_union = true) #error
-    sol = Union{Float64, Vector{Float64}}[0.0, [0.0, 1.0]]
+    sol = Union{Float64, Vector{Float64}}[0.0, [
+        0.0, 1.0]]
     @test arr == sol
     @test typeof(arr) == typeof(sol)
 end
@@ -1502,13 +1503,13 @@ end
     @mtkcompile sys=System(eqs, t) split=false
 
     u0 = SA[D(x) => 2.0f0,
-        x => 1.0f0,
-        y => 0.0f0,
-        z => 0.0f0]
+    x => 1.0f0,
+    y => 0.0f0,
+    z => 0.0f0]
 
     p = SA[σ => 28.0f0,
-        ρ => 10.0f0,
-        β => 8.0f0 / 3.0f0]
+    ρ => 10.0f0,
+    β => 8.0f0 / 3.0f0]
 
     tspan = (0.0f0, 100.0f0)
     prob = ODEProblem{false}(sys, [u0; p], tspan)