format

docs/src/tutorials/advanced.md

@@ -278,12 +278,12 @@ For more information on the preconditioner interface, see the
 
 ## Speed up Jacobian computation with sparsity exploitation and matrix coloring
 
-To cut down the of Jacobian building overhead, we can choose to exploit the sparsity pattern and deploy matrix coloring during Jacobian construction. With NonlinearSolve.jl, we can simply use ```autodiff=AutoSparseForwardDiff()``` to automatically exploit the sparsity pattern of Jacobian matrices:
+To cut down the of Jacobian building overhead, we can choose to exploit the sparsity pattern and deploy matrix coloring during Jacobian construction. With NonlinearSolve.jl, we can simply use `autodiff=AutoSparseForwardDiff()` to automatically exploit the sparsity pattern of Jacobian matrices:
 
 ```@example ill_conditioned_nlprob
 @benchmark solve(prob_brusselator_2d,
-    NewtonRaphson(linsolve=KrylovJL_GMRES(), precs=incompletelu, concrete_jac=true,
-        autodiff=AutoSparseForwardDiff()));
+    NewtonRaphson(linsolve = KrylovJL_GMRES(), precs = incompletelu, concrete_jac = true,
+        autodiff = AutoSparseForwardDiff()));
 nothing # hide
 ```
 
@@ -292,11 +292,11 @@ To setup matrix coloring for the jacobian sparsity pattern, we can simply get th
 ```@example ill_conditioned_nlprob
 using ArrayInterface
 colorvec = ArrayInterface.matrix_colors(jac_sparsity)
-ff = NonlinearFunction(brusselator_2d_loop; jac_prototype=float.(jac_sparsity), colorvec)
+ff = NonlinearFunction(brusselator_2d_loop; jac_prototype = float.(jac_sparsity), colorvec)
 prob_brusselator_2d_sparse = NonlinearProblem(ff, u0, p)
 
 @benchmark solve(prob_brusselator_2d_sparse,
-    NewtonRaphson(linsolve=KrylovJL_GMRES(), precs=incompletelu, concrete_jac=true,
-        autodiff=AutoSparseForwardDiff()));
+    NewtonRaphson(linsolve = KrylovJL_GMRES(), precs = incompletelu, concrete_jac = true,
+        autodiff = AutoSparseForwardDiff()));
 nothing # hide
-```
+```

test/basictests.jl

@@ -49,7 +49,6 @@ end
             @test (@ballocated solve!($cache)) < 200
         end
 
-
         precs = [
             NonlinearSolve.DEFAULT_PRECS,
             (args...) -> (Diagonal(rand!(similar(u0))), nothing),