from copy import deepcopy
import openmdao.api as om
from .phase import Phase
from ..transcriptions import Analytic
from .options import StateOptionsDictionary
from ..utils.misc import _unspecified
class AnalyticPhase(Phase):
"""
The AnalyticPhase object in Dymos.
The AnalyticPhase object in dymos inherits from PhaseBase but is used to override some base methods with ones
that will warn about certain options or methods being invalid for the AnalyticPhase.
Parameters
----------
from_phase : <Phase> or None
A phase instance from which the initialized phase should copy its data.
**kwargs : dict
Dictionary of optional phase arguments.
"""
def __init__(self, from_phase=None, **kwargs):
super().__init__(from_phase=from_phase, **kwargs)
self.simulate_options = None
def initialize(self):
"""
Declare instantiation options for the phase.
"""
super().initialize()
self.options.declare('num_nodes', types=int, default=2,
desc='Number of points in time at which to evaluate the solution to the ODE.')
[docs] def add_state(self, name, state_name=None, units=_unspecified, shape=_unspecified):
"""
Add a state variable to be integrated by the phase.
Parameters
----------
name : str
Path to use as the source of the state variable.
state_name : str
Name of the state variable, if the last element of the source path is ambiguous.
units : str or None
Units in which the state variable is defined. If units is not
specified here then the unit will be determined from the source.
shape : tuple of int
The shape of the state variable. For instance, a 3D cartesian position vector would have
a shape of (3,).
"""
_state_name = name.split('.')[-1] if state_name is None else state_name
if name not in self.state_options:
self.state_options[_state_name] = StateOptionsDictionary()
self.state_options[_state_name]['name'] = _state_name
self.set_state_options(name=name, state_name=state_name, units=units, shape=shape)
def set_state_options(self, name, state_name=None, units=_unspecified, shape=_unspecified):
"""
Set options that apply the EOM state variable of the given name.
Parameters
----------
name : str
Path to use as the source of the state variable.
state_name : str
Name of the state variable, if the last element of the source path is ambiguous.
units : str or None
Units in which the state variable is defined. If units is not
specified here then the unit will be determined from the source.
shape : tuple of int
The shape of the state variable. For instance, a 3D cartesian position vector would have
a shape of (3,).
"""
source = name
_state_name = name.split('.')[-1] if state_name is None else state_name
if name not in self.state_options:
self.state_options[_state_name] = StateOptionsDictionary()
self.state_options[_state_name]['name'] = _state_name
if units is not _unspecified:
self.state_options[_state_name]['units'] = units
if shape is not _unspecified:
self.state_options[_state_name]['shape'] = shape
if source is not _unspecified:
self.state_options[_state_name]['source'] = source
def add_control(self, name, units=_unspecified, desc=_unspecified, opt=_unspecified,
fix_initial=_unspecified, fix_final=_unspecified, targets=_unspecified,
rate_targets=_unspecified, rate2_targets=_unspecified, val=_unspecified,
shape=_unspecified, lower=_unspecified, upper=_unspecified, scaler=_unspecified,
adder=_unspecified, ref0=_unspecified, ref=_unspecified, continuity=_unspecified,
continuity_scaler=_unspecified, rate_continuity=_unspecified,
rate_continuity_scaler=_unspecified, rate2_continuity=_unspecified,
rate2_continuity_scaler=_unspecified):
"""
Adds a dynamic control variable to be tied to a parameter in the ODE.
Parameters
----------
name : str
The name assigned to the control variable. If the ODE has been decorated with
parameters, this should be the name of a control in the system.
units : str or None
The units with which the control parameter in this phase will be defined. It must be
compatible with the units of the targets to which the control is connected.
desc : str
A description of the control variable.
opt : bool
If True, the control value will be a design variable for the optimization problem.
If False, allow the control to be connected externally.
fix_initial : bool
If True, the initial value of this control is fixed and not a design variable.
This option is invalid if opt=False.
fix_final : bool
If True, the final value of this control is fixed and not a design variable.
This option is invalid if opt=False.
targets : Sequence of str or None
Targets in the ODE to which this control is connected.
In the future, if left _unspecified (the default), the phase control will try to connect to an ODE input
of the same name. Set targets to None to prevent this.
rate_targets : Sequence of str or None
The targets in the ODE to which the control rate is connected.
rate2_targets : Sequence of str or None
The parameter in the ODE to which the control 2nd derivative is connected.
val : float
The default value of the control variable at the control input nodes.
shape : Sequence of int
The shape of the control variable at each point in time. Only needed for controls that don't
have a target in the ode.
lower : Sequence of Number or None
The lower bound of the control variable at the nodes.
This option is invalid if opt=False.
upper : Sequence or Number or None
The upper bound of the control variable at the nodes.
This option is invalid if opt=False.
scaler : float or None
The scaler of the control variable at the nodes.
This option is invalid if opt=False.
adder : float or None
The adder of the control variable at the nodes.
This option is invalid if opt=False.
ref0 : float or None
The zero-reference value of the control variable at the nodes.
This option is invalid if opt=False.
ref : float or None
The unit-reference value of the control variable at the nodes.
This option is invalid if opt=False.
continuity : bool
Enforce continuity of control values at segment boundaries.
This option is invalid if opt=False.
continuity_scaler : bool
Scaler of the continuity constraint. This option is invalid if opt=False. This
option is only relevant in the Radau pseudospectral transcription where the continuity
constraint is nonlinear. For Gauss-Lobatto the continuity constraint is linear.
rate_continuity : bool
Enforce continuity of control first derivatives (in dimensionless time) at
segment boundaries.
This option is invalid if opt=False.
rate_continuity_scaler : float
Scaler of the rate continuity constraint at segment boundaries.
This option is invalid if opt=False.
rate2_continuity : bool
Enforce continuity of control second derivatives at segment boundaries.
This option is invalid if opt=False.
rate2_continuity_scaler : float
Scaler of the dimensionless rate continuity constraint at segment boundaries.
This option is invalid if opt=False.
Notes
-----
rate and rate2 continuity are not enforced for input controls.
"""
raise NotImplementedError('AnalyticPhase does not support controls.')
def set_control_options(self, name, units=_unspecified, desc=_unspecified, opt=_unspecified,
fix_initial=_unspecified, fix_final=_unspecified, targets=_unspecified,
rate_targets=_unspecified, rate2_targets=_unspecified, val=_unspecified,
shape=_unspecified, lower=_unspecified, upper=_unspecified, scaler=_unspecified,
adder=_unspecified, ref0=_unspecified, ref=_unspecified, continuity=_unspecified,
continuity_scaler=_unspecified, rate_continuity=_unspecified,
rate_continuity_scaler=_unspecified, rate2_continuity=_unspecified,
rate2_continuity_scaler=_unspecified):
"""
Set options on an existing dynamic control variable in the phase.
Parameters
----------
name : str
The name assigned to the control variable. If the ODE has been decorated with
parameters, this should be the name of a control in the system.
units : str or None
The units with which the control parameter in this phase will be defined. It must be
compatible with the units of the targets to which the control is connected.
desc : str
A description of the control variable.
opt : bool
If True, the control value will be a design variable for the optimization problem.
If False, allow the control to be connected externally.
fix_initial : bool
If True, the initial value of this control is fixed and not a design variable.
This option is invalid if opt=False.
fix_final : bool
If True, the final value of this control is fixed and not a design variable.
This option is invalid if opt=False.
targets : Sequence of str or None
Targets in the ODE to which this control is connected.
In the future, if left _unspecified (the default), the phase control will try to connect to an ODE input
of the same name. Set targets to None to prevent this.
rate_targets : Sequence of str or None
The targets in the ODE to which the control rate is connected.
rate2_targets : Sequence of str or None
The parameter in the ODE to which the control 2nd derivative is connected.
val : float
The default value of the control variable at the control input nodes.
shape : Sequence of int
The shape of the control variable at each point in time. Only needed for controls that don't
have a target in the ode.
lower : Sequence of Number or None
The lower bound of the control variable at the nodes.
This option is invalid if opt=False.
upper : Sequence or Number or None
The upper bound of the control variable at the nodes.
This option is invalid if opt=False.
scaler : float or None
The scaler of the control variable at the nodes.
This option is invalid if opt=False.
adder : float or None
The adder of the control variable at the nodes.
This option is invalid if opt=False.
ref0 : float or None
The zero-reference value of the control variable at the nodes.
This option is invalid if opt=False.
ref : float or None
The unit-reference value of the control variable at the nodes.
This option is invalid if opt=False.
continuity : bool
Enforce continuity of control values at segment boundaries.
This option is invalid if opt=False.
continuity_scaler : bool
Scaler of the continuity constraint. This option is invalid if opt=False. This
option is only relevant in the Radau pseudospectral transcription where the continuity
constraint is nonlinear. For Gauss-Lobatto the continuity constraint is linear.
rate_continuity : bool
Enforce continuity of control first derivatives (in dimensionless time) at
segment boundaries.
This option is invalid if opt=False.
rate_continuity_scaler : float
Scaler of the rate continuity constraint at segment boundaries.
This option is invalid if opt=False.
rate2_continuity : bool
Enforce continuity of control second derivatives at segment boundaries.
This option is invalid if opt=False.
rate2_continuity_scaler : float
Scaler of the dimensionless rate continuity constraint at segment boundaries.
This option is invalid if opt=False.
Notes
-----
rate and rate2 continuity are not enforced for input controls.
"""
raise NotImplementedError('AnalyticPhase does not support controls.')
def add_polynomial_control(self, name, order, desc=_unspecified, val=_unspecified, units=_unspecified,
opt=_unspecified, fix_initial=_unspecified, fix_final=_unspecified,
lower=_unspecified, upper=_unspecified,
scaler=_unspecified, adder=_unspecified, ref0=_unspecified,
ref=_unspecified, targets=_unspecified, rate_targets=_unspecified,
rate2_targets=_unspecified, shape=_unspecified):
"""
Adds an polynomial control variable to be tied to a parameter in the ODE.
Polynomial controls are defined by values at the Legendre-Gauss-Lobatto nodes of a
single polynomial, defined on [-1, 1] in phase tau space.
For a polynomial control of a given order, the number of nodes used to define the
polynomial is (order + 1).
Parameters
----------
name : str
Name of the controllable parameter in the ODE.
order : int
The order of the interpolating polynomial used to represent the control value in
phase tau space.
desc : str
A description of the polynomial control.
val : float or ndarray
Default value of the control at all nodes. If val scalar and the control
is dynamic it will be broadcast.
units : str or None or 0
Units in which the control variable is defined. If 0, use the units declared
for the parameter in the ODE.
opt : bool
If True (default) the value(s) of this control will be design variables in
the optimization problem, in the path 'phase_name.indep_controls.controls:control_name'.
If False, the values of this control will exist as input controls:{name}.
fix_initial : bool
If True, the given initial value of the polynomial control is not a design variable and
will not be changed during the optimization.
fix_final : bool
If True, the given final value of the polynomial control is not a design variable and
will not be changed during the optimization.
lower : float or ndarray
The lower bound of the control at the nodes of the phase.
upper : float or ndarray
The upper bound of the control at the nodes of the phase.
scaler : float or ndarray
The scaler of the control value at the nodes of the phase.
adder : float or ndarray
The adder of the control value at the nodes of the phase.
ref0 : float or ndarray
The zero-reference value of the control at the nodes of the phase.
ref : float or ndarray
The unit-reference value of the control at the nodes of the phase.
targets : Sequence of str or None
Targets in the ODE to which this polynomial control is connected.
rate_targets : None or str
The name of the parameter in the ODE to which the first time-derivative
of the control value is connected.
rate2_targets : None or str
The name of the parameter in the ODE to which the second time-derivative
of the control value is connected.
shape : Sequence of int
The shape of the control variable at each point in time.
"""
raise NotImplementedError('AnalyticPhase does not support polynomial controls.')
def setup(self):
"""
Build the model hierarchy for a Dymos AnalyticPhase.
"""
# Finalize the variables if it hasn't happened already.
# If this phase exists within a Trajectory, the trajectory will finalize them during setup.
transcription = self.options['transcription'] = Analytic(order=self.options['num_nodes'])
transcription.setup_time(self)
if self.control_options:
transcription.setup_controls(self)
if self.parameter_options:
transcription.setup_parameters(self)
# Never allow state rate outputs for analytic phases
self.timeseries_options['include_state_rates'] = False
self.timeseries_options._dict['include_state_rates']['values'] = [False]
transcription.setup_states(self)
self._check_ode()
transcription.setup_ode(self)
transcription.setup_timeseries_outputs(self)
transcription.setup_defects(self)
transcription.setup_solvers(self)
def simulate(self, times_per_seg=10, method=_unspecified, atol=_unspecified, rtol=_unspecified,
first_step=_unspecified, max_step=_unspecified, record_file=None):
"""
Stub to make sure users are informed that simulate cannot be done on AnalyticPhase.
Parameters
----------
times_per_seg : int or None
Number of equally spaced times per segment at which output is requested. If None,
output will be provided at all Nodes.
method : str
The scipy.integrate.solve_ivp integration method.
atol : float
Absolute convergence tolerance for scipy.integrate.solve_ivp.
rtol : float
Relative convergence tolerance for scipy.integrate.solve_ivp.
first_step : float
Initial step size for the integration.
max_step : float
Maximum step size for the integration.
record_file : str or None
If a string, the file to which the result of the simulation will be saved.
If None, no record of the simulation will be saved.
Returns
-------
problem
An OpenMDAO Problem in which the simulation is implemented. This Problem interface
can be interrogated to obtain timeseries outputs in the same manner as other Phases
to obtain results at the requested times.
"""
raise NotImplementedError('Method `simulate` is not available for AnalyticPhase.')
def set_simulate_options(self, *args, **kwargs):
"""
Stub to make sure users are informed that simulate cannot be done on AnalyticPhase.
Parameters
----------
*args
Position arguments.
**kwargs : float
Keyword arguments.
Raises
------
NotImplementedError
Simulation cannot be performed on AnalyticPhase.
"""
raise NotImplementedError('Method set_simulate_options is not available for AnalyticPhase.')
def duplicate(self, num_nodes=None, boundary_constraints=False, path_constraints=False, objectives=False,
fix_initial_time=False):
"""
Create a copy of this phase where most options and attributes are deep copies of those in the original.
By default, a deepcopy of the transcription in the original phase is used.
Boundary constraints, path constraints, and objectives are _NOT_ copied by default, but the user may opt to do so.
By default, initial time is not fixed, nor are the initial or final state values.
These also can be overridden with the appropriate arguments.
Parameters
----------
num_nodes : int or None
The number of nodes to use in the new phase, or None if it should use the same
number as the phase being duplicated.
boundary_constraints : bool
If True, retain all boundary constraints from the phase to be copied.
path_constraints : bool
If True, retain all path constraints from the phase to be copied.
objectives : bool
If True, retain all objectives from the phase to be copied.
fix_initial_time : bool
If True, fix the initial time of the returned phase.
Returns
-------
AnalyticPhase
The new phase created by duplicating this one.
"""
nn = num_nodes if num_nodes is not None else self.options['num_nodes']
ode_class = self.options['ode_class']
ode_init_kwargs = self.options['ode_init_kwargs']
auto_solvers = self.options['auto_solvers']
p = AnalyticPhase(num_nodes=nn, ode_class=ode_class, ode_init_kwargs=ode_init_kwargs,
auto_solvers=auto_solvers)
p.time_options.update(deepcopy(self.time_options))
p.time_options['fix_initial'] = fix_initial_time
for state_name, state_options in self.state_options.items():
p.state_options[state_name] = deepcopy(state_options)
for param_name, param_options in self.parameter_options.items():
p.parameter_options[param_name] = deepcopy(param_options)
p._timeseries = deepcopy(self._timeseries)
p.refine_options = deepcopy(self.refine_options)
p.simulate_options = deepcopy(self.simulate_options)
p.timeseries_options = deepcopy(self.timeseries_options)
if boundary_constraints:
p._initial_boundary_constraints = deepcopy(self._initial_boundary_constraints)
p._final_boundary_constraints = deepcopy(self._final_boundary_constraints)
if path_constraints:
p._path_constraints = deepcopy(self._path_constraints)
if objectives:
p._objectives = deepcopy(self._objectives)
return p
