How to fix "submatrix incorrectly defined" in Scilab? - optimization

Question

I am trying to find three parameters (a, b, c) to fit my experimental data using ODE solver and optimization by least squares using Scilab in-built functions.
However, I keep having the message "submatrix incorrectly defined" at line "y_exp(:,1) = [0.135 ..."
When I try another series of data (t, yexp) such as the one used in the original template I get no error messages. The template I use was found here: https://wiki.scilab.org/Non%20linear%20optimization%20for%20parameter%20fitting%20example
function dy = myModel ( t , y , a , b, c )
// The right-hand side of the Ordinary Differential Equation.
dy(1) = -a*y(1) - b*y(1)*y(2)
dy(2) = a*y(1) - b*y(1)*y(2) - c*y(2)
endfunction
function f = myDifferences ( k )
// Returns the difference between the simulated differential
// equation and the experimental data.
global MYDATA
t = MYDATA.t
y_exp = MYDATA.y_exp
a = k(1)
b = k(2)
c = k(3)
y0 = y_exp(1,:)
t0 = 0
y_calc=ode(y0',t0,t,list(myModel,a,b,c))
diffmat = y_calc' - y_exp
// Make a column vector
f = diffmat(:)
MYDATA.funeval = MYDATA.funeval+ 1
endfunction
// Experimental data
t = [0,20,30,45,75,105,135,180,240]';
y_exp(:,1) =
[0.135,0.0924,0.067,0.0527,0.0363,0.02445,0.01668,0.012,0.009]';
y_exp(:,2) =
[0,0.00918,0.0132,0.01835,0.0261,0.03215,0.0366,0.0393,0.0401]';
// Store data for future use
global MYDATA;
MYDATA.t = t;
MYDATA.y_exp = y_exp;
MYDATA.funeval = 0;
function val = L_Squares ( k )
// Computes the sum of squares of the differences.
f = myDifferences ( k )
val = sum(f.^2)
endfunction
// Initial guess
a = 0;
b = 0;
c = 0;
x0 = [a;b;c];
[fopt ,xopt]=leastsq(myDifferences, x0)
Does anyone know how to approach this problem?

Answer 1

Just rewrite lines 28,29 as
y_exp = [0.135,0.0924,0.067,0.0527,0.0363,0.02445,0.01668,0.012,0.009
0,0.00918,0.0132,0.01835,0.0261,0.03215,0.0366,0.0393,0.0401]';
or insert a clear at line 1 (you may have defined y_exp before with a different size).