Recent content by quantumCircuit

Yes, but shouldn't that be a job of the minimize function?

Here is the code I used so far: def objective_function(z): return (np.sum((z[0] - z[1])**2) + np.sum((z[2] - z[3])**2))/2 z = np.array([x_exp, x_calc, y_exp, y_calc]) opt = minimize(objective_function, x0=params) opt.x

I think the problem is that the function minimize from SciPy doesn't take the data I am sending it. It just tries to find the minimum of a 4-value function with six parameters, but it doesn't calculate the residuals of the experimental and calculated data at all.

Thank you for the reply, but I would like to ask you for a little clarification here, as this is something I am completely unfamiliar with. I cannot get the minimize function working. So far I have done this. I have the experimental data for x(t), and y(t), and I have values for the parameters...

About post #2, no, it doesn't give satisfactory result because the system is coupled, and to answer the question in #3, yes, on of the species is going extinct, and the other thrives. I don't know how to solve a coupled differential system, as far as I have searched on the Internet, I couldn't...

Yes, this is exactly what I am trying to do, but the only problem being is that I don't have estimated parameters, so I am trying to do the estimation. I have already tried to estimate them with setting x=0 and y=0, as I said before, and also I have tried to simultaneously use least square...

Namely, in the system, I have obtained the value of parameters L, M, A and D, because I treat the other organism as equal to zero, i.e., it doesn't exist, but I am struggling about the values of B and C, that are coupled with the product of x and y. Can anyone help me how to obtain those values...