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
)
```

- 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.

`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.