pymloc.model.dynamical_system.parameter_dae

Functions

jac_jax_reshaped(fun, shape, *args, **kwargs)

Classes

AutomaticLinearDAE(parameter_dae)

LinearParameterDAE(ll_vars, hl_vars, …[, …])

Class for parameter dependent linear differential algebraic equations of the form

ParameterDAE(lower_level_variables, …[, …])

class pymloc.model.dynamical_system.parameter_dae.AutomaticLinearDAE(parameter_dae)

Bases: pymloc.model.dynamical_system.representations.LinearFlowRepresentation

Parameters

parameter_dae (pymloc.model.dynamical_system.parameter_dae.LinearParameterDAE) –

class pymloc.model.dynamical_system.parameter_dae.LinearParameterDAE(ll_vars, hl_vars, loc_vars, e, a, f, n, der_e=None)

Bases: pymloc.model.dynamical_system.parameter_dae.ParameterDAE

Class for parameter dependent linear differential algebraic equations of the form

\[ \begin{align}\begin{aligned}E(t, \theta)\dot{x} = A(t, \theta)x + f(t, \theta)\\or (ommiting time and parameter arguments)\end{aligned}\end{align} \]
\[ \begin{align}\begin{aligned}E(\frac{\mathrm d}{\mathrm dt}E^+E{x}) = Ax + f.\\All coefficients are assumed sufficiently smooth. The system is assumed to be strangeness-free. All quantities according to the definitions in Kunkel, Mehrmann (2006) for every fixed parameter value.\end{aligned}\end{align} \]
Parameters

  • e (Callable[[numpy.ndarray, float], numpy.ndarray]) –

  • a (Callable[[numpy.ndarray, float], numpy.ndarray]) –

  • f (Callable[[numpy.ndarray, float], numpy.ndarray]) –

  • n (int) –

  • der_e (Optional[Callable[[numpy.ndarray, float], numpy.ndarray]]) –

property a
property a_theta
d_a(t, param)
Parameters

  • t (float) –

  • param (jax.numpy.lax_numpy.ndarray) –

Return type

jax.numpy.lax_numpy.ndarray

property der_e
property e
e_plus(t, param)
Parameters

  • t (float) –

  • param (jax.numpy.lax_numpy.ndarray) –

Return type

jax.numpy.lax_numpy.ndarray

property e_theta
property f
f_a(t, param)
Parameters

  • t (float) –

  • param (jax.numpy.lax_numpy.ndarray) –

Return type

jax.numpy.lax_numpy.ndarray

property f_theta
p_z(t, param)
Parameters

  • t (float) –

  • param (jax.numpy.lax_numpy.ndarray) –

Return type

jax.numpy.lax_numpy.ndarray

projector_cal(t, param)
Parameters

  • t (float) –

  • param (jax.numpy.lax_numpy.ndarray) –

Return type

jax.numpy.lax_numpy.ndarray

projectors(t, param)
Parameters

  • t (float) –

  • param (jax.numpy.lax_numpy.ndarray) –

Return type

Tuple[jax.numpy.lax_numpy.ndarray, jax.numpy.lax_numpy.ndarray]

residual(hl_vars, loc_vars, ll_vars)
Parameters
class pymloc.model.dynamical_system.parameter_dae.ParameterDAE(lower_level_variables, higher_level_variables, local_level_variables, n, residual=None)

Bases: pymloc.model.multilevel_object.MultiLevelObject

Parameters

  • n (int) –

  • residual (Optional[Callable]) –

pymloc.model.dynamical_system.parameter_dae.jac_jax_reshaped(fun, shape, *args, **kwargs)