Output of MATLAB Curve Fitting Toolbox does not match generated function -

a similar question has been answered in past, part of question not answered (matlab curve fitting tool, cftool, generate code function not give same fit).

i have set of data points meant show "ideal" curve mechanism studying.

when ask curve fitting toolbox in matlab find 2-term exponential, great fit (r-square: 0.9998, adjusted r-square: 0.9997). however, when generate code fit, changes coefficients a, b, c , d.

in toolbox, displays:

general model exp2:

 f(x) = a*exp(b*x) + c*exp(d*x) 

coefficients (with 95% confidence bounds):

   =   4.698e+04  (-1.477e+13, 1.477e+13)     b =      0.4381  (-1200, 1201)     c =  -4.698e+04  (-1.477e+13, 1.477e+13)     d =      0.4381  (-1200, 1201) 

goodness of fit:

sse: 0.002979

r-square: 0.9998

adjusted r-square: 0.9997

rmse: 0.006823

function generated curve-fitting toolbox:

function [fitresult, gof] = createfit1(bgst, testst) %createfit1(bgst,testst) %  create fit. % %  data 'standard mechanism' fit: %      x input : bgst %      y output: testst %  output: %      fitresult : fit object representing fit. %      gof : structure goodness-of fit info. % %  see fit, cfit, sfit.  %  auto-generated matlab on 29-apr-2015 15:54:07   %% fit: 'standard mechanism'. [xdata, ydata] = preparecurvedata( bgst, testst );  % set fittype , options. ft = fittype( 'exp2' ); opts = fitoptions( 'method', 'nonlinearleastsquares' ); opts.display = 'off'; opts.startpoint = [0.935605768794225 0.667093185616236 0 0.667093185616236];  % fit model data. [fitresult, gof] = fit( xdata, ydata, ft, opts );  % plot fit data. figure( 'name', 'standard mechanism' ); h = plot( fitresult, xdata, ydata ); legend( h, 'testst vs. bgst', 'standard mechanism', 'location', 'northeast' ); % label axes xlabel bgst ylabel testst grid on 

notice coefficients different, curves generated.

notice coefficients displayed in curve-fitting toolbox, c = -a , d = b, y should equal 0 value of x, ludicrous.

but when edit generated function replace function's coefficients coefficients toolbox, curve.

edited code:

function [fitresult, gof] = standardfit(bgst, testst) %standardfit(bgst,testst) %  create fit. % %  data 'standard mechanism' fit: %      x input : bgst %      y output: testst %  output: %      fitresult : fit object representing fit. %      gof : structure goodness-of fit info. % %  see fit, cfit, sfit.  %  auto-generated matlab on 29-apr-2015 15:54:07  %from curve fitting toolbox: %general model exp2: %     f(x) = a*exp(b*x) + c*exp(d*x) %coefficients (with 95% confidence bounds): %       =   4.698e+04  (-1.477e+13, 1.477e+13) %       b =      0.4381  (-1200, 1201) %       c =  -4.698e+04  (-1.477e+13, 1.477e+13) %       d =      0.4381  (-1200, 1201)  %goodness of fit: %  sse: 0.002979 %  r-square: 0.9998 %  adjusted r-square: 0.9997 %  rmse: 0.006823   %% fit: 'standard mechanism'. [xdata, ydata] = preparecurvedata( bgst, testst );  % set fittype , options. ft = fittype( 'exp2' ); opts = fitoptions( 'method', 'nonlinearleastsquares' ); opts.display = 'off'; opts.startpoint = [4.698e+04 0.4381 -4.698e+04 0.4381];  % fit model data. [fitresult, gof] = fit( xdata, ydata, ft, opts );  % plot fit data. figure( 'name', 'standard mechanism' ); h = plot( fitresult, xdata, ydata ); legend( h, 'testst vs. bgst', 'standard mechanism', 'location', 'northeast' ); % label axes xlabel bgst ylabel testst grid on 

i don't have enough reputation post images of curves, in toolbox looks perfect , 1 function looks awful - translated in same way linked poster.

here's variable bgst:

-2.85 -2.8 -2.75 -2.7 -2.65 -2.6 -2.55 -2.5 -2.45 -2.4 -2.35 -2.3 -2.25 -2.2 -2.15 -2.1 -2.05 -2 -1.95 -1.9 -1.85 -1.8 -1.75 -1.7 -1.65 -1.6 -1.55 -1.5 -1.45 -1.4 -1.35 -1.3 -1.25 -1.2 -1.15 -1.1 -1.05 -1 -0.95 -0.9 -0.85 -0.8 -0.75 -0.7 -0.65 -0.6 -0.55 -0.5 -0.45 -0.4 -0.35 -0.3 -0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 

here's variable testst:

0 0.01 0.01 0.02 0.02 0.02 0.03 0.04 0.04 0.05 0.06 0.06 0.07 0.08 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.2 0.21 0.23 0.24 0.26 0.28 0.3 0.31 0.33 0.35 0.37 0.39 0.41 0.43 0.45 0.48 0.5 0.52 0.55 0.57 0.6 0.63 0.66 0.68 0.72 0.74 0.78 0.81 0.85 0.88 0.92 0.96 1 1.04 1.08 1.12 1.17 1.21 1.26 1.3 1.35 1.39 1.44 

edit: have enough reputation add images.

figure generated curve fitting toolbox:

figure generated automatically-generated function:

i ran similar problem using exponential fit due how coefficients bounded. it's possible they're bounded in dialogue, don't see they'd bounded in generated code.