SciPy

scipy.optimize.linprog_verbose_callback

scipy.optimize.linprog_verbose_callback(res)[source]

A sample callback function demonstrating the linprog callback interface. This callback produces detailed output to sys.stdout before each iteration and after the final iteration of the simplex algorithm.

Parameters:
res : A scipy.optimize.OptimizeResult consisting of the following fields:
x : 1D array

The independent variable vector which optimizes the linear programming problem.

fun : float

Value of the objective function.

success : bool

True if the algorithm succeeded in finding an optimal solution.

slack : 1D array

The values of the slack variables. Each slack variable corresponds to an inequality constraint. If the slack is zero, then the corresponding constraint is active.

con : 1D array

The (nominally zero) residuals of the equality constraints, that is, b - A_eq @ x

phase : int

The phase of the optimization being executed. In phase 1 a basic feasible solution is sought and the T has an additional row representing an alternate objective function.

status : int

An integer representing the exit status of the optimization:

0 : Optimization terminated successfully
1 : Iteration limit reached
2 : Problem appears to be infeasible
3 : Problem appears to be unbounded
4 : Serious numerical difficulties encountered
nit : int

The number of iterations performed.

message : str

A string descriptor of the exit status of the optimization.

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