README
¶
osqp.go
Few lines describing your project.
📝 Table of Contents
- 📝 Table of Contents
- 🧐 Problem Statement
- 💡 Idea / Solution
- ⛓️ Dependencies / Limitations
- 🚀 Future Scope
- 🏁 Getting Started
- 🎈 Usage
- ⛏️ Built With
- ✍️ Authors
- 🎉 Acknowledgments
🧐 Problem Statement
Currently, there is no Go interface for Quadratic Programming implementation on C. Users who want to use Quadratic Programming in Go have to write their own interface or use an existing one that may not be optimized for their specific use case. Without a Go interface for OSQP implementation on C, users who want to use Quadratic Programming in Go will have to spend time and resources writing their own interface or using an existing one that may not be optimized for their specific use case. This can lead to suboptimal performance and increased development time.
- IDEAL: The goal of this project is to create a Go interface for OSQP implementation on C. The interface should be easy to use and should allow users to solve optimization problems using OSQP in Go.
- REALITY: Currently, there is no Go interface for OSQP implementation on C. Users who want to use OSQP in Go have to write their own interface or use an existing one that may not be optimized for their specific use case.
- CONSEQUENCES: Without a Go interface for OSQP implementation on C, users who want to use OSQP in Go will have to spend time and resources writing their own interface or using an existing one that may not be optimized for their specific use case. This can lead to suboptimal performance and increased development time.
💡 Idea / Solution
To achieve this goal, we will create a Go package that provides a simple and intuitive interface for OSQP implementation on C. The package will be designed to be easy to use and will provide users with all the functionality they need to solve optimization problems using OSQP in Go.
⛓️ Dependencies / Limitations
- OSQP implementation on C
🚀 Future Scope
Write about what you could not develop during the course of the project; and about what your project can achieve in the future.
🏁 Getting Started
These instructions will get you a copy of the project up and running on your local machine.
Prerequisites
- OSQP Library
You can find detailed instructions on using build a osqp library and many tips in its documentation own here.
Installing
To get started you need to have binaries build of OSQP in C or you can copy from libs directory in the example.
To install the library you can run the command below.
go get -u github.com/jerensl/osqp.go
🎈 Usage
See example/ for a variety of examples.
Simple:
package main
import (
"fmt"
"github.com/jerensl/osqp.go"
)
func main() {
newOSQP := osqp.NewOSQP()
p_mat, err := osqp.NewCSCMatrix([][]float64{{4, 1}, {0, 2}})
if err != nil {
fmt.Println(err)
return
}
a_mat, err := osqp.NewCSCMatrix([][]float64{{1, 1}, {1, 0}, {0, 1}})
if err != nil {
fmt.Println(err)
return
}
q := []float64{1.0, 1.0}
l := []float64{1.0, 0.0, 0.0}
u := []float64{1.0, 0.7, 0.7}
newOSQP.Setup(p_mat, q, a_mat, l, u)
newOSQP.Solve()
fmt.Println(newOSQP.Solution())
newOSQP.CleanUp()
}
⛏️ Built With
- OSQP - OSQP Library in C
✍️ Authors
- @jerensl - Idea & Initial work
See also the list of contributors who participated in this project.
🎉 Acknowledgments
Documentation
¶
Index ¶
- func BlockDiag(blocks []*mat.Dense) *mat.Dense
- func DenseEye(size int, val float64) *mat.Dense
- func DenseEyeK(size int, val float64, k int) *mat.Dense
- func ToNegative(matDense mat.Matrix) mat.Matrix
- func ToNegativeDense(vecDense mat.Dense) *mat.Dense
- func ToNegativeVecDense(vecDense mat.VecDense) *mat.Dense
- func VStack(matrix []mat.Matrix) *mat.Dense
- func VecZeros(num int) mat.Matrix
- type Data
- type OSQPConfig
- func (o OSQPConfig) CleanUp()
- func (o OSQPConfig) Setup(p SparseMatrix, q []float64, a SparseMatrix, l []float64, u []float64)
- func (o OSQPConfig) Solution() (float32, float32)
- func (o OSQPConfig) Solve()
- func (o OSQPConfig) UpdateAMat(aNew []float64)
- func (o OSQPConfig) UpdateBounds(lNew, uNew []float64)
- func (o OSQPConfig) UpdateLinCost(qNew []float64)
- func (o OSQPConfig) UpdatePMat(pNew []float64)
- type SparseMatrix
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
Types ¶
type Data ¶
type Data struct {
M int64
N int64
P_mat SparseMatrix
Q []float64
A_mat SparseMatrix
L []float64
U []float64
}
type OSQPConfig ¶
type OSQPConfig struct {
// contains filtered or unexported fields
}
func NewOSQP ¶
func NewOSQP() *OSQPConfig
func (OSQPConfig) CleanUp ¶
func (o OSQPConfig) CleanUp()
func (OSQPConfig) Setup ¶
func (o OSQPConfig) Setup(p SparseMatrix, q []float64, a SparseMatrix, l []float64, u []float64)
func (OSQPConfig) Solution ¶
func (o OSQPConfig) Solution() (float32, float32)
func (OSQPConfig) Solve ¶
func (o OSQPConfig) Solve()
func (OSQPConfig) UpdateAMat ¶
func (o OSQPConfig) UpdateAMat(aNew []float64)
func (OSQPConfig) UpdateBounds ¶
func (o OSQPConfig) UpdateBounds(lNew, uNew []float64)
func (OSQPConfig) UpdateLinCost ¶
func (o OSQPConfig) UpdateLinCost(qNew []float64)
func (OSQPConfig) UpdatePMat ¶
func (o OSQPConfig) UpdatePMat(pNew []float64)
type SparseMatrix ¶
type SparseMatrix struct {
// contains filtered or unexported fields
}
func NewCSCDenseMatrix ¶
func NewCSCDenseMatrix(matrix mat.Matrix) (SparseMatrix, error)
func NewCSCMatrix ¶
func NewCSCMatrix(matrix [][]float64) (SparseMatrix, error)
func NewDiagCSCMatrix ¶
func NewDiagCSCMatrix(size int, value float64) (*SparseMatrix, error)
func (SparseMatrix) Data ¶
func (s SparseMatrix) Data() []float64
func (SparseMatrix) Dimension ¶
func (s SparseMatrix) Dimension() (int, int)
func (SparseMatrix) Ind ¶
func (s SparseMatrix) Ind() []int
func (SparseMatrix) IndPtr ¶
func (s SparseMatrix) IndPtr() []int
func (SparseMatrix) NNZ ¶
func (s SparseMatrix) NNZ() int64
func (SparseMatrix) ToDense ¶
func (s SparseMatrix) ToDense() *mat.Dense
func (SparseMatrix) Transpose ¶
func (s SparseMatrix) Transpose(matrix [][]float64) [][]float64
Source Files
Directories