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Copy file name to clipboardExpand all lines: src/stats.jl
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@@ -66,13 +66,13 @@ abstract type AbstractExecutionStats end
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"""
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GenericExecutionStats(nlp; ...)
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A GenericExecutionStats is a struct for storing output information of solvers.
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A GenericExecutionStats is a struct for storing the output information of solvers.
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It contains the following fields:
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- `status`: Indicates the output of the solver. Use `show_statuses()` for the full list;
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- `solution`: The final approximation returned by the solver (default: an uninitialized vector like `nlp.meta.x0`);
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- `objective`: The objective value at `solution` (default: `Inf`);
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- `dual_feas`: The dual feasibility norm at `solution` (default: `Inf`);
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- `primal_feas`: The primal feasibility norm at `solution` (default: `0.0` if uncontrained, `Inf` otherwise);
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- `primal_feas`: The primal feasibility norm at `solution` (default: `0.0` if unconstrained, `Inf` otherwise);
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- `multipliers`: The Lagrange multipliers wrt to the constraints (default: an uninitialized vector like `nlp.meta.y0`);
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- `multipliers_L`: The Lagrange multipliers wrt to the lower bounds on the variables (default: an uninitialized vector like `nlp.meta.x0` if there are bounds, or a zero-length vector if not);
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- `multipliers_U`: The Lagrange multipliers wrt to the upper bounds on the variables (default: an uninitialized vector like `nlp.meta.x0` if there are bounds, or a zero-length vector if not);
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