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:
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.