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changed the tutorial method to itp
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docs/src/tutorials/nonlinear.md

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@@ -21,15 +21,25 @@ AbstractArray for automatic differentiation.
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## Using Bracketing Methods
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For scalar rootfinding problems, bracketing methods exist. In this case, one passes
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For scalar rootfinding problems, bracketing methods exist in `SimpleNonlinearSolve`. In this case, one passes
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a bracket instead of an initial condition, for example:
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```@example
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using NonlinearSolve
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using SimpleNonlinearSolve
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f(u, p) = u * u - 2.0
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uspan = (1.0, 2.0) # brackets
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probB = IntervalNonlinearProblem(f, uspan)
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sol = solve(probB, Falsi())
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sol = solve(probB, ITP())
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```
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The user can also set a tolerance that suits the application.
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```@example
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using SimpleNonlinearSolve
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f(u, p) = u * u - 2.0
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uspan = (1.0, 2.0) # brackets
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probB = IntervalNonlinearProblem(f, uspan)
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sol = solve(probB, ITP(), abstol = 0.01)
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```
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## Using Jacobian Free Newton Krylov (JNFK) Methods

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