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