How can I use a vector as a problem-dependent variable for fittype

General task description: Programatically fit a series of experimental data sets using a custom equation describing the data as a superposition of two curves.

What's the issue: Vectors are not being recognized in the problem argument of fittype. I have seen on the help file that the program argument is a cell array with one element per problem constant. Is there a way to input a vector to be used in the fit equation? I also seem to be having the same issue passing the X vector into the fit equation. As you will see, I rely on knowing the length of X to construct the fit vector.

Notes: The two curves used to fit the data are named I_1 and I_2 below. The scaling constants are named sc_1 and sc_2. A third scaling constant is used to scale the entire superposition and is named sc_tot. As you will see, "abc_Superpos.m" is run first which then calls the other m files, also shown below.

The Code:

abc_Superpos.m %below are the contents of this m file

% The first part of this code is included to have sample data to run the rest of the code. My real curves are from experimental data, not calculated from a function.

clear all X = (1:31); num_X_points = 31; num_curves = 5;

for dat_r = 1:num_curves for dat_c = 1:length(X) I_1_all_data(dat_r,dat_c) = X(dat_c)^2; I_2_all_data(dat_r,dat_c) = exp(-X(dat_c)); end end I_mix_all_data = 3*I_1 + I_2;

for incr = 1:num_curves
       I_1(incr,:) = I_1_all_data(incr,:); %component 1
       I_2(incr,:) = I_2_all_times(incr,:); %component 2
      I_mix(incr,:) = I_mix_all_data(incr,:); %mix

        abc_Superpos_cf_ = abc_Superpos_fcn(X,I_mix,I_1,I_2);
end

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abc_Superpos_fcn(X,Y,I_1,I_2).m %below are the contents of this m file

function [abc_Superpos_cf_] = abc_Superpos_fcn(X,Y,I_1,I_2)

    X = X(:);
    Y = Y(:);

ex_ = false(length(X),1); ex_([]) = 1; ex_ = ex_ | (Y <= 0);

fo_ = fitoptions('Weight',Y,'Algorithm', 'Trust-Region', 'method','NonlinearLeastSquares',... 'Lower',[0 0 0],'Upper', [1000 1000 1000], 'MaxFunEvals', 10000,'MaxIter',10000,... 'TolFun', 1e-10, 'TolX', 1e-10, 'DiffMinChange', 1e-10, 'DiffMaxChange', 1e-7); ok_ = isfinite(X) & isfinite(Y) & isfinite(Y); st_ = [1 1 1]; set(fo_,'Startpoint',st_);

ft_ = fittype('abc_EQN_Superpos_fcn(I_1,I_2,sc_1,sc_2,sc_tot,X)',... 'dependent',{'Y'},'independent',{'X'},... 'coefficients',{'sc_1','sc_2','sc_tot'}, 'problem',{'I_1', 'I_2'});

if sum(~ex_(ok_))<2

   error('Not enough data left to fit ''%s'' after applying exclusion rule ''%s''.','fit 1','nozeros')
else
   abc_Superpos_cf_ = fit(X(ok_),Y(ok_),ft_,fo_);

end

if 0 cv_ = { 0.1011653947332, 7.519747020586, 0.0006793571606672}; abc_Superpos_cf_ = cfit(ft_,cv_{:}); end

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abc_EQN_Superpos_fcn.m %below are the contents of this m file

function [abc_EQN_Superpos_cf_] = abc_EQN_Superpos_fcn(I_1,I_2,sc_1,sc_2,sc_tot,X)

I_em_specfit_superpos = zeros(x_range); for X_index = 1:x_range I_em_specfit_superpos(X_index) = (sc_1*I_1(X_index) + sc_2*I_2(X_index)); end

 abc_EQN_Superpos_cf_ = sc_tot * I_em_specfit_superpos;