SCS-class function

class

An interface for the SCS solver

SCS()

## S4 method for signature 'SCS'
mip_capable(solver)

## S4 method for signature 'SCS'
status_map(solver, status)

## S4 method for signature 'SCS'
name(x)

## S4 method for signature 'SCS'
import_solver(solver)

## S4 method for signature 'SCS'
reduction_format_constr(object, problem, constr, exp_cone_order)

## S4 method for signature 'SCS,Problem'
perform(object, problem)

## S4 method for signature 'SCS,list,list'
invert(object, solution, inverse_data)

## S4 method for signature 'SCS'
solve_via_data(
  object,
  data,
  warm_start,
  verbose,
  feastol,
  reltol,
  abstol,
  num_iter,
  solver_opts,
  solver_cache
)

Arguments

• solver, object, x: A SCS object.
• status: A status code returned by the solver.
• problem: A Problem object.
• constr: A Constraint to format.
• exp_cone_order: A list indicating how the exponential cone arguments are ordered.
• solution: The raw solution returned by the solver.
• inverse_data: A list containing data necessary for the inversion.
• data: Data generated via an apply call.
• warm_start: A boolean of whether to warm start the solver.
• verbose: A boolean of whether to enable solver verbosity.
• feastol: The feasible tolerance on the primal and dual residual.
• reltol: The relative tolerance on the duality gap.
• abstol: The absolute tolerance on the duality gap.
• num_iter: The maximum number of iterations.
• solver_opts: A list of Solver specific options
• solver_cache: Cache for the solver.

Methods (by generic)

• 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.