ParabolicFit1D

class ParabolicFit1D(rawData)

Bases: FitData1D

Parabolic function fit for one-dimensional data.

Fits a parabolic function of the form \(y = a\,x^2 + b\,x + c\) to experimental data. Uses MATLAB’s built-in poly2 fit type for efficient quadratic regression.

• Formula: \(y = a\,x^2 + b\,x + c\)

• Coefficients: \(a\) (quadratic), \(b\) (linear), \(c\) (constant)

Example1:

% Fit parabolic function to experimental data
x = linspace(-5, 5, 100);
y = 0.5*x.^2 + 2*x + 1 + 0.1*randn(size(x));
data = [x', y'];
parabolicFit = ParabolicFit1D(data);
parabolicFit.do();
parabolicFit.plot();

Example2:

% Access fit parameters
parabolicFit = ParabolicFit1D(data);
parabolicFit.do();
a = parabolicFit.Coefficient(1); % quadratic coefficient
b = parabolicFit.Coefficient(2); % linear coefficient
c = parabolicFit.Coefficient(3); % constant term

Constructor Summary

ParabolicFit1D(rawData)

Constructor for ParabolicFit1D class.

Parameters:

rawData (double array) – Input data as n x 2 matrix [x, y]

Method Summary

guessCoefficient()

Parabolic fit uses MATLAB’s automatic parameter estimation.

For parabolic fits, MATLAB automatically estimates the quadratic, linear, and constant coefficients, so no manual guessing is required.

setFormula()

Set the parabolic fit formula.