Update nonlinear_solve.jl

more trying to fix with 1.6

Author: TorkelE

test/miscellaneous_tests/nonlinear_solve.jl

@@ -25,7 +25,7 @@ let
     nl_prob = NonlinearProblem(steady_state_network_1, u0, p)
 
     # Solves it using standard algorithm and simulation based algorithm.
-    sol1 = solve(nl_prob, LevenbergMarquardt(); abstol=1e-12, reltol=1e-12).u
+    sol1 = solve(nl_prob; abstol=1e-12, reltol=1e-12).u
     sol2 = solve(nl_prob, DynamicSS(Rosenbrock23(); abstol=1e-12, reltol=1e-12); abstol=1e-12, reltol=1e-12).u
 
     # Tests solutions are correct.
@@ -54,7 +54,7 @@ let
     nl_prob = NonlinearProblem(steady_state_network_2, u0, p)
 
     # Solves it using standard algorithm and simulation based algorithm.
-    sol1 = solve(nl_prob, LevenbergMarquardt(); abstol=1e-12, reltol=1e-12).u
+    sol1 = solve(nl_prob; abstol=1e-12, reltol=1e-12).u
     sol2 = solve(nl_prob, DynamicSS(Rosenbrock23(); abstol=1e-12, reltol=1e-12); abstol=1e-12, reltol=1e-12).u
 
     # Computes NonlinearFunction (manually and automatically).
@@ -90,11 +90,11 @@ let
     nl_prob_2 = NonlinearProblem(steady_state_network_3, u0, p)
 
     # Solves it using standard algorithm and simulation based algorithm.
-    sol1 = solve(nl_prob_1, LevenbergMarquardt(); abstol=1e-12, reltol=1e-12)
+    sol1 = solve(nl_prob_1; abstol=1e-12, reltol=1e-12)
     sol2 = solve(nl_prob_2, DynamicSS(Rosenbrock23(); abstol=1e-12, reltol=1e-12); abstol=1e-12, reltol=1e-12)
 
     # Checks output using NonlinearFunction.
     nfunc = NonlinearFunction(convert(NonlinearSystem, steady_state_network_3))   
     @test isapprox(nfunc([sol1[X], sol1[Y], sol1[Y2], sol1[XY2]], last.(p)), [0.0, 0.0, 0.0, 0.0]; atol=1e-10)
     @test isapprox(nfunc([sol2[X], sol2[Y], sol2[Y2], sol2[XY2]], last.(p)), [0.0, 0.0, 0.0, 0.0]; atol=1e-10)
-end
+end