psamm.lpsolver.gurobi
– Gurobi LP solver¶
Linear programming solver using Gurobi.

class
psamm.lpsolver.gurobi.
Constraint
(prob, name)¶ Represents a constraint in a gurobi.Problem.

class
psamm.lpsolver.gurobi.
Problem
(**kwargs)¶ Represents an LPproblem of a gurobi.Solver.

add_linear_constraints
(*relations)¶ Add constraints to the problem.
Each constraint is represented by a Relation, and the expression in that relation can be a set expression.

define
(*names, **kwargs)¶ Define a variable in the problem.
Variables must be defined before they can be accessed by var() or set(). This function takes keyword arguments lower and upper to define the bounds of the variable (default: inf to inf). The keyword argument types can be used to select the type of the variable (Continuous (default), Binary or Integer). Setting any variables different than Continuous will turn the problem into an MILP problem. Raises ValueError if a name is already defined.

feasibility_tolerance
¶ Feasibility tolerance.

gurobi
¶ The underlying Gurobi Model object.

has_variable
(name)¶ Check whether variable is defined in the model.

integrality_tolerance
¶ Integrality tolerance.

optimality_tolerance
¶ Optimality tolerance.

set_linear_objective
(expression)¶ Set linear objective of problem.

set_objective
(expression)¶ Set linear objective of problem.

set_objective_sense
(sense)¶ Set type of problem (maximize or minimize).

solve_unchecked
(sense=None)¶ Solve problem and return result.
The user must manually check the status of the result to determine whether an optimal solution was found. A
SolverError
may still be raised if the underlying solver raises an exception.


class
psamm.lpsolver.gurobi.
Result
(prob)¶ Represents the solution to a gurobi.Problem.
This object will be returned from the gurobi.Problem.solve() method or by accessing the gurobi.Problem.result property after solving a problem. This class should not be instantiated manually.
Result will evaluate to a boolean according to the success of the solution, so checking the truth value of the result will immediately indicate whether solving was successful.

get_value
(expression)¶ Return value of expression.

status
¶ Return string indicating the error encountered on failure.

success
¶ Return boolean indicating whether a solution was found.

unbounded
¶ Whether solution is unbounded
