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tutorials/introduction-to-solverbenchmark/index.jmd

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@@ -224,9 +224,9 @@ The tutorial covers how to use the problems from `OptimizationProblems` to run a
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### Handling `solver_specific` in `stats`
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If a solver's `GenericExecutionStats` contains a `solver_specific` dictionary, those values can be tabulated alongside the standard metrics such as `status` and `elapsed_time`.
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If a solver's `GenericExecutionStats` contains a `solver_specific` dictionary, then when `bmark_solvers` processes the results it creates a column in the per-solver `DataFrame` for each key in that dictionary. These columns can then be analyzed and compared alongside the standard metrics such as `status` and `elapsed_time`.
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Here is an example showing how to populate `solver_specific` and place those fields in a stats table:
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Here is an example showing how to set a solver-specific flag so that it appears as a column in the resulting stats table and can be used for tabulation:
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```julia
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import NLPModels: reset!
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using NLPModelsTest, DataFrames, SolverCore, SolverBenchmark

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