scipy.optimize.linprog_verbose_callback

scipy.optimize.linprog_verbose_callback(res)

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

resA scipy.optimize.OptimizeResult consisting of the following fields:

x1-D array

The independent variable vector which optimizes the linear programming problem.

funfloat

Value of the objective function.

successbool

True if the algorithm succeeded in finding an optimal solution.

slack1-D 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.

con1-D array

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

phaseint

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.

statusint

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

nitint

The number of iterations performed.

messagestr

A string descriptor of the exit status of the optimization.

linprog(method=’highs’) scipy.optimize.linear_sum_assignment