Files
sjy01-image-proc/pkg/utils/interp_polynomial.go
2024-07-12 11:34:02 +08:00

59 lines
1.2 KiB
Go

package utils
import (
"math"
"gonum.org/v1/gonum/mat"
)
type PolynomialInterpolator struct {
Degree int
Coeffs []float64
}
func (p *PolynomialInterpolator) Fit(x, y []float64) error {
if p.Degree == 0 {
p.Degree = len(x) - 1
}
degree := p.Degree
n := len(x)
// Create the Vandermonde matrix
vander := mat.NewDense(n, degree+1, nil)
for i := 0; i < n; i++ {
for j := 0; j <= degree; j++ {
vander.Set(i, j, math.Pow(x[i], float64(j)))
}
}
// Create the right-hand side vector
yVec := mat.NewVecDense(n, y)
// Solve the least squares problem
var qr mat.QR
qr.Factorize(vander)
coeffs := mat.NewDense(degree+1, 1, nil)
err := qr.SolveTo(coeffs, false, yVec)
p.Coeffs = coeffs.RawMatrix().Data
return err
}
func (p PolynomialInterpolator) Predict(x float64) float64 {
var y float64
for i, coeff := range p.Coeffs {
y += coeff * math.Pow(x, float64(i))
}
return y
}
func InterpPolynomial(x []float64, y []float64, xq float64, degree int) float64 {
if len(x) != len(y) {
return 0.0
}
start, end := FindClosestSubset(x, xq, degree+1)
interp := &PolynomialInterpolator{Degree: degree}
interp.Fit(x[start:end+1], y[start:end+1])
return interp.Predict(xq)
}