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firstly, thank you for writing ddeint!. I am trying to solve an initial value problem for the case that x''(t) is known and depends on x(t-dt). In scipy without the delay I do this as following:
I implemented dde solver base on ddeint with scipy.integrate.solve_ivp which is newer version. https://github.com/Menginventor/dde_ivp
It support rk23, rk45 adaptive step size. vectorized variable, dense output, and event detection
I would be more efficient and accurate the existing ddeint. Feel free to try it out.
Hi Zulko,
firstly, thank you for writing ddeint!. I am trying to solve an initial value problem for the case that x''(t) is known and depends on x(t-dt). In scipy without the delay I do this as following:
def function(z, t):
return np.array([x''(z[1]), z[0]])
then odeint returns an np.array of [x',x]
However in ddeint this seems difficult as I cannot index z. Any help would be appreciated.
Cheers!
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