Simplify README examples to just use the default method

Fixes #209

README.md

@@ -24,34 +24,13 @@ using NonlinearSolve, StaticArrays
 
 f(u, p) = u .* u .- 2
 u0 = @SVector[1.0, 1.0]
-probN = NonlinearProblem(f, u0)
-solver = solve(probN, NewtonRaphson(), abstol = 1e-9)
+prob = NonlinearProblem(f, u0)
+solver = solve(prob)
 
 ## Bracketing Methods
 
 f(u, p) = u .* u .- 2.0
 u0 = (1.0, 2.0) # brackets
-probB = IntervalNonlinearProblem(f, u0)
-sol = solve(probB, ITP())
+prob = IntervalNonlinearProblem(f, u0)
+sol = solve(prob)
 ```
-
-## v1.0 Breaking Release Highlights!
-
-v1.0 has been released for NonlinearSolve.jl, making it a decentralized solver library
-akin to DifferentialEquations.jl. For simple implementations of nonlinear solvers,
-you can now use SimpleNonlinearSolve.jl. `Falsi`, `Bisection`, and `NewtonRaphson`
-implementations designed for scalar and static vector inputs have all moved to the
-lower dependency version. NonlinearSolve.jl is thus designed for the larger scale
-more complex implementations, with `NewtonRaphson` now sporting support for
-LinearSolve.jl and soon SparseDiffTools.jl to allow for preconditioned Newton-Krylov and
-exploitation of sparsity. The two pieces will continue to grow in this direction,
-with NonlinearSolve.jl gaining more and more wrapped solver libraries and support
-for more complex methods, while SimpleNonlinearSolve.jl will keep a lower dependency
-version with implementations for small scale problems that do not need all of the
-extra tooling.
-
-Additionally, `NonlinearProblem` was split into `NonlinearProblem` and `IntervalNonlinearProblem`,
-i.e. the bracketing versions now have their own problem definition, rather than using
-a `Tuple` for `u0` in a `NonlinearProblem`. This helps for finding problem-algorithm
-pairing errors at type time and overall improves the documentation / makes the roles
-more clear.