How to make odeint successful?

Question

I am a python beginner, currently using scipy's odeint to compute a coupled ODE system, however, when I run, python shell always tell me that

>>> Excess work done on this call (perhaps wrong Dfun type). Run with full_output = 1 to get quantitative information. >>>

So, I have to change my time step and final time, in order to make it integratable. To do this, I need to try a different combinations, which is quite a pain. Could anyone tell me how can I ask odeint to automatically vary the time step and final time to successfully integrate this ode system?

and here is part of the code which has called odeint:

def main(t, init_pop_a, init_pop_b, *args, **kwargs): """ solve the obe for a given set of parameters """ # construct initial condition # initially, rho_ee = 0 rho_init = zeros((16,16))*1j ######## rho_init[1,1] = init_pop_a rho_init[2,2] = init_pop_b rho_init[0,0] = 1 - (init_pop_a + init_pop_b)######## rho_init_ravel, params = to_1d(rho_init) # perform the integration result = odeint(wrapped_bloch3, rho_init_ravel, t, args=args) # BUG: need to pass kwargs # rewrap the result return from_1d(result, params, prepend=(len(t),)) things = [2*pi, 20*pi, 0,0, 0,0, 0.1,100] Omega_a, Omega_b, Delta_a, Delta_b, \ init_pop_a, init_pop_b, tstep, tfinal = things args = ( Delta_a, Delta_b, Omega_a, Omega_b ) t = arange(0, tfinal + tstep, tstep) data = main(t, init_pop_a, init_pop_b, *args) plt.plot(t,abs(data[:,4,4]))

where wrapped_bloch3 is the function compute dy/dt.

Could you provide more of your code, especially the call to odeint? — David Robinson
– David Robinson, Commented Feb 27, 2012 at 14:05
You are going to have to add quite a lot more detail than you have provided to get help: What type of ODEs are you working with? Are they stiff? Are you providing a Jacobian function to odeint? Are you sure it is reasonable? — talonmies
– talonmies, Commented Feb 27, 2012 at 14:07
@user1233157: the most obvious thing to do is define a jacobian term for the solver. That should greatly accelerate convergence. — talonmies
– talonmies, Commented Feb 27, 2012 at 15:30
@talonmies: thank you for the suggestion, however, my coupled ode system have 16*16 number of equations which could take me a very long time to write theirs Jacobian. i have looked the documentation of odeint, they have someting like while successful, looks like may be able to solve my problem, but i just couldnt understand that. — user1233157
– user1233157, Commented Feb 27, 2012 at 15:41

Community · Accepted Answer · 2017-05-23 11:52:02Z

EDIT: I note you already got an answer here: complex ODE systems in scipy

odeint does not work with complex-valued equations. I get

from scipy.integrate import odeint import numpy as np def func(t, y): return 1 + 1j t = np.linspace(0, 1, 200) y = odeint(func, 0, t) # -> This outputs: # # TypeError: can't convert complex to float # odepack.error: Result from function call is not a proper array of floats.

You can solve your equation by the other ode solver:

from scipy.integrate import ode import numpy as np def myodeint(func, y0, t): y0 = np.array(y0, complex) func2 = lambda t, y: func(y, t) # odeint has these the other way :/ sol = ode(func2).set_integrator('zvode').set_initial_value(y0, t=t[0]) y = [sol.integrate(tp) for tp in t[1:]] y.insert(0, y0) return np.array(y) def func(y, t, alpha): return 1j*alpha*y alpha = 3.3 t = np.linspace(0, 1, 200) y = myodeint(lambda y, t: func(y, t, alpha), [1, 0, 0], t)

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