An interface for the SCS solver
SCS()
# S4 method for class 'SCS'
mip_capable(solver)
# S4 method for class 'SCS'
status_map(solver, status)
# S4 method for class 'SCS'
name(x)
# S4 method for class 'SCS'
import_solver(solver)
# S4 method for class 'SCS'
reduction_format_constr(object, problem, constr, exp_cone_order)
# S4 method for class 'SCS,Problem'
perform(object, problem)
# S4 method for class 'SCS,list,list'
invert(object, solution, inverse_data)
# S4 method for class 'SCS'
solve_via_data(
object,
data,
warm_start,
verbose,
feastol,
reltol,
abstol,
num_iter,
solver_opts,
solver_cache
)
A SCS object.
A status code returned by the solver.
A Problem object.
A Constraint to format.
A list indicating how the exponential cone arguments are ordered.
The raw solution returned by the solver.
A list containing data necessary for the inversion.
Data generated via an apply call.
A boolean of whether to warm start the solver.
A boolean of whether to enable solver verbosity.
The feasible tolerance on the primal and dual residual.
The relative tolerance on the duality gap.
The absolute tolerance on the duality gap.
The maximum number of iterations.
A list of Solver specific options
Cache for the solver.
mip_capable(SCS)
: Can the solver handle mixed-integer programs?
status_map(SCS)
: Converts status returned by SCS solver to its respective CVXPY status.
name(SCS)
: Returns the name of the solver
import_solver(SCS)
: Imports the solver
reduction_format_constr(SCS)
: Return a linear operator to multiply by PSD constraint coefficients.
perform(object = SCS, problem = Problem)
: Returns a new problem and data for inverting the new solution
invert(object = SCS, solution = list, inverse_data = list)
: Returns the solution to the original problem given the inverse_data.
solve_via_data(SCS)
: Solve a problem represented by data returned from apply.