piqp_model: The PIQP Solver Model Class

In piqp: R Interface to Proximal Interior Point Quadratic Programming Solver

The PIQP Solver Model Class

Description

This class wraps around the PIQP C++ Solver and exposes methods and fields of the C++ object. Users will never need to directly create instances this class and should use the more user-friendly functions piqp() and solve_piqp().

Methods

Public methods

• piqp_model$new()

• piqp_model$solve()

• piqp_model$update()

• piqp_model$get_settings()

• piqp_model$get_dims()

• piqp_model$update_settings()

• piqp_model$clone()

---

Method new()

Create a new piqp_model object

Usage

piqp_model$new(
  P,
  c,
  A,
  b,
  G,
  h,
  x_lb,
  x_ub,
  settings = list(),
  dense_backend,
  dims
)

Arguments

P

dense or sparse matrix of class dgCMatrix or coercible into such, must be positive semidefinite

c

numeric vector

A

dense or sparse matrix of class dgCMatrix or coercible into such

b

numeric vector

G

dense or sparse matrix of class dgCMatrix or coercible into such

h

numeric vector

x_lb

a numeric vector of lower bounds

x_ub

a numeric vector of upper bounds

settings

list with optimization parameters

dense_backend

a flag indicating if the dense solver is to be used

dims

the dimensions of the problem, a named list containing n, p and m.

Returns

a piqp_model object that can be used to solve the QP

---

Method solve()

Solve the QP model

Usage

piqp_model$solve()

Returns

a list containing the solution

---

Method update()

Update the current piqp_model with new data

Usage

piqp_model$update(
  P = NULL,
  c = NULL,
  A = NULL,
  b = NULL,
  G = NULL,
  h = NULL,
  x_lb = NULL,
  x_ub = NULL
)

Arguments

P

dense or sparse matrix of class dgCMatrix or coercible into such, must be positive semidefinite

c

numeric vector

A

dense or sparse matrix of class dgCMatrix or coercible into such

b

numeric vector

G

dense or sparse matrix of class dgCMatrix or coercible into such

h

numeric vector

x_lb

a numeric vector of lower bounds

x_ub

a numeric vector of upper bounds

settings

list with optimization parameters

dense_backend

a flag indicating if the dense solver is to be used

dims

the dimensions of the problem, a named list containing n, p and m.

---

Method get_settings()

Obtain the current settings for this model

Usage

piqp_model$get_settings()

---

Method get_dims()

Obtain the dimensions of this model

Usage

piqp_model$get_dims()

---

Method update_settings()

Update the current settings with new values for this model

Usage

piqp_model$update_settings(new_settings = list())

Arguments

new_settings

a list of named values for settings, default empty list; see piqp_settings() for a comprehensive list of defaults

---

Method clone()

The objects of this class are cloneable with this method.

Usage

piqp_model$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

piqp documentation built on Aug. 14, 2023, 5:09 p.m.