straindesign.scip_interface
SCIP and SoPlex solver interface for LP and MILP
Module Contents
- class straindesign.scip_interface.SCIP_LP(c, A_ineq, b_ineq, A_eq, b_eq, lb, ub)[source]
Bases:
pyscipopt.LP
SoPlex interface for LP
This class is a wrapper for the SoPlex-Python API to offer bindings and namings for functions for the construction and manipulation of LPs in an vector-matrix-based manner that are consistent with those of the other solver interfaces in the StrainDesign package. The purpose is to unify the instructions for operating with MILPs and LPs throughout StrainDesign.
Constructor of the SCIP (SoPlex) LP interface class
- Accepts a (mixed integer) linear problem in the form:
minimize(c) subject to: A_ineq * x <= b_ineq
A_eq * x = b_eq lb <= x <= ub forall(i) type(x_i) = vtype(i) (continous, binary, integer) indicator constraints: x(j) = [0|1] -> a_indic * x [<=|=|>=] b_indic
Please ensure that the number of variables and (in)equalities is consistent
Example
scip = SCIP_LP(c, A_ineq, b_ineq, A_eq, b_eq, lb, ub)
- Parameters:
c (list of float) – (Default: None) The objective vector (Objective sense: minimization).
A_ineq (sparse.csr_matrix) – (Default: None) A coefficient matrix of the static inequalities.
b_ineq (list of float) – (Default: None) The right hand side of the static inequalities.
A_eq (sparse.csr_matrix) – (Default: None) A coefficient matrix of the static equalities.
b_eq (list of float) – (Default: None) The right hand side of the static equalities.
lb (list of float) – (Default: None) The lower variable bounds.
ub (list of float) – (Default: None) The upper variable bounds.
Returns –
(SCIP_LP):
A SCIP LP interface class.
- add_eq_constraints(A_eq, b_eq)[source]
Add equality constraints to the model
Additional equality constraints have the form A_eq * x = b_eq. The number of columns in A_eq must match with the number of variables x in the problem.
- add_ineq_constraints(A_ineq, b_ineq)[source]
Add inequality constraints to the model
Additional inequality constraints have the form A_ineq * x <= b_ineq. The number of columns in A_ineq must match with the number of variables x in the problem.
- set_objective_idx(C)[source]
Set the objective function with index-value pairs
e.g.: C=[[1, 1.0], [4,-0.2]]
- class straindesign.scip_interface.SCIP_MILP(c=None, A_ineq=None, b_ineq=None, A_eq=None, b_eq=None, lb=None, ub=None, vtype=None, indic_constr=None, seed=None)[source]
Bases:
pyscipopt.Model
SCIP interface for MILP
This class is a wrapper for the SCIP-Python API to offer bindings and namings for functions for the construction and manipulation of MILPs in an vector-matrix-based manner that are consistent with those of the other solver interfaces in the StrainDesign package. The purpose is to unify the instructions for operating with MILPs and LPs throughout StrainDesign.
The SCIP interface provides support for indicator constraints as well as for the populate function. The SCIP interface does not natively support the populate function. A high level implementation emulates the behavior of populate.
- Accepts a (mixed integer) linear problem in the form:
minimize(c), subject to: A_ineq * x <= b_ineq, A_eq * x = b_eq, lb <= x <= ub, forall(i) type(x_i) = vtype(i) (continous, binary, integer), indicator constraints: x(j) = [0|1] -> a_indic * x [<=|=|>=] b_indic
Please ensure that the number of variables and (in)equalities is consistent
Example
scip = SCIP_MILP(c, A_ineq, b_ineq, A_eq, b_eq, lb, ub, vtype, indic_constr)
- Parameters:
c (list of float) – (Default: None) The objective vector (Objective sense: minimization).
A_ineq (sparse.csr_matrix) – (Default: None) A coefficient matrix of the static inequalities.
b_ineq (list of float) – (Default: None) The right hand side of the static inequalities.
A_eq (sparse.csr_matrix) – (Default: None) A coefficient matrix of the static equalities.
b_eq (list of float) – (Default: None) The right hand side of the static equalities.
lb (list of float) – (Default: None) The lower variable bounds.
ub (list of float) – (Default: None) The upper variable bounds.
vtype (str) – (Default: None) A character string that specifies the type of each variable: ‘c’ontinous, ‘b’inary or ‘i’nteger
indic_constr (IndicatorConstraints) – (Default: None) A set of indicator constraints stored in an object of IndicatorConstraints (see reference manual or docstring).
seed (int16) – (Default: None) An integer value serving as a seed to make MILP solving reproducible.
Returns –
(SCIP_MILP):
A SCIP MILP interface class.
- addExclusionConstraintIneq(x)[source]
Function to add exclusion constraint (SCIP compatibility function)
- add_eq_constraints(A_eq, b_eq)[source]
Add equality constraints to the model
Additional equality constraints have the form A_eq * x = b_eq. The number of columns in A_eq must match with the number of variables x in the problem.
- add_ineq_constraints(A_ineq, b_ineq)[source]
Add inequality constraints to the model
Additional inequality constraints have the form A_ineq * x <= b_ineq. The number of columns in A_ineq must match with the number of variables x in the problem.
- set_ineq_constraint(idx, a_ineq, b_ineq)[source]
Replace a specific inequality constraint
Replace the constraint with the index idx with the constraint a_ineq*x ~ b_ineq
- set_objective_idx(C)[source]
Set the objective function with index-value pairs
e.g.: C=[[1, 1.0], [4,-0.2]]