An interface for the SCS solver

SCS()

# S4 method for SCS
mip_capable(solver)

# S4 method for SCS
status_map(solver, status)

# S4 method for SCS
name(x)

# S4 method for SCS
import_solver(solver)

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

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

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

# S4 method for 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.