assimulo.examples.cvode_with_initial_sensitivity.
run_example
(with_plots=True)[source]¶This example shows how to use Assimulo and CVode for simulating sensitivities for initial conditions.
with the parameter dependent inital conditions \(y_1(0) = 0, y_2(0) = 0, y_3(0) = 0\) . The initial values are taken as parameters \(p_1,p_2,p_3\) for the computation of the sensitivity matrix, see http://sundials.2283335.n4.nabble.com/Forward-sensitivities-for-initial-conditions-td3239724.html
on return:
- exp_mod problem instance
- exp_sim solver instance
Final Run Statistics: Example: Computing Sensitivities
Number of steps : 139
Number of function evaluations : 164
Number of Jacobian evaluations : 3
Number of function eval. due to Jacobian eval. : 9
Number of error test failures : 2
Number of nonlinear iterations : 160
Number of nonlinear convergence failures : 0
Number of sensitivity evaluations : 164
Number of function eval. due to sensitivity eval. : 984
Number of sensitivity nonlinear iterations : 0
Number of sensitivity nonlinear convergence failures : 0
Number of sensitivity error test failures : 0
Sensitivity options:
Method : SIMULTANEOUS
Difference quotient type : CENTERED
Suppress Sens : False
Solver options:
Solver : CVode
Linear multistep method : BDF
Nonlinear solver : Newton
Linear solver type : DENSE
Maximal order : 5
Tolerances (absolute) : 1e-06
Tolerances (relative) : 1e-07
Simulation interval : 0.0 - 400.0 seconds.
Elapsed simulation time: 0.0260779857635 seconds.
Note
Press [source] (to the top right) to view the example.