`scipy.optimize._linprog_util:_postsolve`

source: /scipy/optimize/_linprog_util.py :1314

Signature

def _postsolve ( x , postsolve_args , complete = False )

Summary

Given solution x to presolved, standard form linear program x, add fixed variables back into the problem and undo the variable substitutions to get solution to original linear program. Also, calculate the objective function value, slack in original upper bound constraints, and residuals in original equality constraints.

Parameters

x : 1-D array

Solution vector to the standard-form problem.

postsolve_args : tuple

Data needed by _postsolve to convert the solution to the standard-form problem into the solution to the original problem, including:

lp : A `scipy.optimize._linprog_util._LPProblem` consisting of the following fields:

c: c
A_ub: A_ub
b_ub: b_ub
A_eq: A_eq
b_eq: b_eq
bounds: bounds
x0: x0

revstack: list of functions

the functions in the list reverse the operations of _presolve() the function signature is x_org = f(x_mod), where x_mod is the result of a presolve step and x_org the value at the start of the step

complete : bool

Whether the solution is was determined in presolve (True if so)

Returns

x : 1-D array: Solution vector to original linear programming problem
: fun: float: optimal objective value for original problem
slack : 1-D array: The (non-negative) slack in the upper bound constraints, that is, b_ub - A_ub @ x
con : 1-D array: The (nominally zero) residuals of the equality constraints, that is, b - A_eq @ x

Aliases

scipy.optimize._linprog._postsolve