For further details please consult the OSQP documentation: https://osqp.org/

1 2 3 4 5 6 7 8 | ```
osqpSettings(rho = 0.1, sigma = 1e-06, max_iter = 4000L,
eps_abs = 0.001, eps_rel = 0.001, eps_prim_inf = 1e-04,
eps_dual_inf = 1e-04, alpha = 1.6, linsys_solver = c(QDLDL_SOLVER =
0L), delta = 1e-06, polish = FALSE, polish_refine_iter = 3L,
verbose = TRUE, scaled_termination = FALSE,
check_termination = 25L, warm_start = TRUE, scaling = 10L,
adaptive_rho = 1L, adaptive_rho_interval = 0L,
adaptive_rho_tolerance = 5, adaptive_rho_fraction = 0.4)
``` |

`rho` |
ADMM step rho |

`sigma` |
ADMM step sigma |

`max_iter` |
maximum iterations |

`eps_abs` |
absolute convergence tolerance |

`eps_rel` |
relative convergence tolerance |

`eps_prim_inf` |
primal infeasibility tolerance |

`eps_dual_inf` |
dual infeasibility tolerance |

`alpha` |
relaxation parameter |

`linsys_solver` |
which linear systems solver to use, 0=QDLDL, 1=MKL Pardiso |

`delta` |
regularization parameter for polish |

`polish` |
boolean, polish ADMM solution |

`polish_refine_iter` |
iterative refinement steps in polish |

`verbose` |
boolean, write out progress |

`scaled_termination` |
boolean, use scaled termination criteria |

`check_termination` |
integer, check termination interval. If 0, termination checking is disabled |

`warm_start` |
boolean, warm start |

`scaling` |
heuristic data scaling iterations. If 0, scaling disabled |

`adaptive_rho` |
cboolean, is rho step size adaptive? |

`adaptive_rho_interval` |
Number of iterations between rho adaptations rho. If 0, it is automatic |

`adaptive_rho_tolerance` |
Tolerance X for adapting rho. The new rho has to be X times larger or 1/X times smaller than the current one to trigger a new factorization |

`adaptive_rho_fraction` |
Interval for adapting rho (fraction of the setup time) |

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