def __init__(self, problem, solver='ode15s', **solver_options):
        """

        :param problem: Problem to simulate
        :type problem: ODEProblem
        :param compute_sensitivities: Whether the model should test parameter sensitivity or not
        :param solver: the solver to use. Currently, the solvers that available are:

                       `'cvode'`
                            sundials CVode solver, as implemented in :class:`assimulo.solvers.sundials.CVode`
                       `'dopri5'`
                            Dopri5 solver, see :class:`assimulo.solvers.runge_kutta.Dopri5`
                       `'euler'`
                            Euler solver, see :class:`assimulo.solvers.euler.ExplicitEuler`
                       `'ode15s`:
                            sundials CVODE solver, with default parameters set to mimick the MATLAB's
                            See :class:`~means.simulation.solvers.ODE15sMixin` for the list of these parameters.
                       `'lsodar'`
                            LSODAR solver, see :class:`assimulo.solvers.odepack.LSODAR`
                       `'radau5'`
                            Radau5 solver, see :class:`assimulo.solvers.radau5.Radau5ODE`
                       `'rodas'`
                            Rosenbrock method of order (3)4 with step-size control,
                            see :class:`assimulo.solvers.rosenbrock.RodasODE`
                       `'rungekutta34'`
                            Adaptive Runda-Kutta of order four,
                            see :class:`assimulo.solvers.runge_kutta.RungeKutta34`
                       `'rungekutta4'`
                            Runge-Kutta method of order 4,
                            see :class:`assimulo.solvers.runge_kutta.RungeKutta4`

                       The list of these solvers is always accessible at runtime
                       from :meth:`Simulation.supported_solvers()` method.

                       .. _`ode15s`: http://www.mathworks.ch/ch/help/matlab/ref/ode15s.html

        :type solver: basestring
        :param solver_options: options to set in the solver. Consult `Assimulo documentation`_ for available options
                               for information on specific options available.

        .. _`Assimulo documentation`: http://www.jmodelica.org/assimulo_home/
        """
        self.__problem = problem
        _validate_problem(problem)


        self._solver = solver.lower()
        self._solver_options = solver_options
def __init__ ( self , problem , solver = 'ode15s' , ** solver_options ) : self . __problem = problem _validate_problem ( problem ) self . _solver = solver . lower ( ) self . _solver_options = solver_options
:param problem: Problem to simulate
        :type problem: ODEProblem
        :param compute_sensitivities: Whether the model should test parameter sensitivity or not
        :param solver: the solver to use. Currently, the solvers that available are:

                       `'cvode'`
                            sundials CVode solver, as implemented in :class:`assimulo.solvers.sundials.CVode`
                       `'dopri5'`
                            Dopri5 solver, see :class:`assimulo.solvers.runge_kutta.Dopri5`
                       `'euler'`
                            Euler solver, see :class:`assimulo.solvers.euler.ExplicitEuler`
                       `'ode15s`:
                            sundials CVODE solver, with default parameters set to mimick the MATLAB's
                            See :class:`~means.simulation.solvers.ODE15sMixin` for the list of these parameters.
                       `'lsodar'`
                            LSODAR solver, see :class:`assimulo.solvers.odepack.LSODAR`
                       `'radau5'`
                            Radau5 solver, see :class:`assimulo.solvers.radau5.Radau5ODE`
                       `'rodas'`
                            Rosenbrock method of order (3)4 with step-size control,
                            see :class:`assimulo.solvers.rosenbrock.RodasODE`
                       `'rungekutta34'`
                            Adaptive Runda-Kutta of order four,
                            see :class:`assimulo.solvers.runge_kutta.RungeKutta34`
                       `'rungekutta4'`
                            Runge-Kutta method of order 4,
                            see :class:`assimulo.solvers.runge_kutta.RungeKutta4`

                       The list of these solvers is always accessible at runtime
                       from :meth:`Simulation.supported_solvers()` method.

                       .. _`ode15s`: http://www.mathworks.ch/ch/help/matlab/ref/ode15s.html

        :type solver: basestring
        :param solver_options: options to set in the solver. Consult `Assimulo documentation`_ for available options
                               for information on specific options available.

        .. _`Assimulo documentation`: http://www.jmodelica.org/assimulo_home/