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also show the minimizer #1054

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also show the minimizer #1054

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c5e06e7
also show the minimizer
MariusDruleaRB Oct 12, 2023
af5e952
objective calls not counting gradient calls
MariusDrulea Oct 16, 2023
8423d95
specify direct calls
MariusDrulea Oct 16, 2023
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2 changes: 1 addition & 1 deletion docs/src/user/config.md
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Expand Up @@ -41,7 +41,7 @@ In addition to the solver, you can alter the behavior of the Optim package by us
* `x_tol`: Absolute tolerance in changes of the input vector `x`, in infinity norm. Defaults to `0.0`.
* `f_tol`: Relative tolerance in changes of the objective value. Defaults to `0.0`.
* `g_tol`: Absolute tolerance in the gradient, in infinity norm. Defaults to `1e-8`. For gradient free methods, this will control the main convergence tolerance, which is solver specific.
* `f_calls_limit`: A soft upper limit on the number of objective calls. Defaults to `0` (unlimited).
* `f_calls_limit`: A soft upper limit on the number of direct objective calls. Defaults to `0` (unlimited). Does not count the objective calls in gradient and hessian estimation.
* `g_calls_limit`: A soft upper limit on the number of gradient calls. Defaults to `0` (unlimited).
* `h_calls_limit`: A soft upper limit on the number of Hessian calls. Defaults to `0` (unlimited).
* `allow_f_increases`: Allow steps that increase the objective value. Defaults to `false`. Note that, when setting this to `true`, the last iterate will be returned as the minimizer even if the objective increased.
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1 change: 1 addition & 0 deletions src/types.jl
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Expand Up @@ -256,6 +256,7 @@ function Base.show(io::IO, r::MultivariateOptimizationResults)
@printf io " * Status: %s\n\n" status_string

@printf io " * Candidate solution\n"
println(io, " Minimizer: ", minimizer(r))
@printf io " Final objective value: %e\n" minimum(r)
@printf io "\n"

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