State

openscvx.backend.state.State

Bases: Variable

A class representing the state variables in an optimal control problem.

The State class extends Variable to handle state-specific properties like initial and final conditions, as well as true and augmented state dimensions. It supports various boundary condition types: - Fixed values (Fix) - Free variables (Free) - Minimization objectives (Minimize) - Maximization objectives (Maximize)

Attributes:

Name	Type	Description
name	str	Name of the state variable.
shape	tuple	Shape of the state variable array.
min	ndarray	Minimum bounds for the state variables. Shape: (n_states,).
max	ndarray	Maximum bounds for the state variables. Shape: (n_states,).
guess	ndarray	Used to initialize SCP and contains the current SCP solution for the state trajectory. Shape: (n_nodes, n_states).
initial	ndarray	Initial state values or boundary condition objects (Free, Fixed, Minimize, Maximize). Shape: (n_states,).
final	ndarray	Final state values or boundary condition objects (Free, Fixed, Minimize, Maximize). Shape: (n_states,).
_initial	ndarray	Internal storage for initial state values.
_final	ndarray	Internal storage for final state values.
initial_type	str	Type of initial boundary condition ('fix', 'free', 'minimize', 'maximize').
final_type	str	Type of final boundary condition ('fix', 'free', 'minimize', 'maximize').
_true_dim	int	True dimensionality of the state variables.
_true_slice	slice	Slice for accessing true state variables.
_augmented_slice	slice	Slice for accessing augmented state variables.

Notes

Attributes prefixed with underscore (_) are for internal use only and should not be accessed directly.

Example

state = State("position", (3,))
state.min = np.array([0, 0, 10])
state.max = np.array([10, 10, 200])
state.guess = np.linspace([0, 1, 2], [10, 5, 8], 3)
state.initial = np.array([Fix(0), Free(1), 2])
state.final = np.array([Fix(10), Free(5), Maximize(8)])

augmented property

Get the augmented state variables.

Returns:

Name	Type	Description
State		A new State object containing only the augmented state variables

final property writable

Get the final state values.

Returns:

Type	Description
	np.ndarray: Array of final state values

initial property writable

Get the initial state values.

Returns:

Type	Description
	np.ndarray: Array of initial state values

max property writable

Get the maximum bounds for the state variables.

Returns:

Type	Description
	np.ndarray: Array of maximum values for each state variable

min property writable

Get the minimum bounds for the state variables.

Returns:

Type	Description
	np.ndarray: Array of minimum values for each state variable

true property

Get the true state variables (excluding augmented states).

Returns:

Name	Type	Description
State		A new State object containing only the true state variables

_check_bounds_against_initial_final()

Check if initial and final values respect the bounds.

Raises:

Type	Description
ValueError	If any fixed initial or final value violates the bounds

_update_slices()

Update the slice objects for true and augmented states.

append(other=None, *, min=-np.inf, max=np.inf, guess=0.0, initial=0.0, final=0.0, augmented=False)

Append another state or create a new state variable.

Parameters:

Name	Type	Description	Default
other	State	Another State object to append	None
min	float	Minimum bound for new state. Defaults to -np.inf	-inf
max	float	Maximum bound for new state. Defaults to np.inf	inf
guess	float	Initial guess for new state. Defaults to 0.0	0.0
initial	float	Initial value for new state. Defaults to 0.0	0.0
final	float	Final value for new state. Defaults to 0.0	0.0
augmented	bool	Whether the new state is augmented. Defaults to False	False

Boundary Conditions

openscvx.backend.state.Free

Class representing a free state variable in the optimization problem.

A free state variable is one that is not constrained to any specific value but can be optimized within its bounds.

Attributes:

Name	Type	Description
guess		The initial guess value for optimization.

openscvx.backend.state.Fix

Class representing a fixed state variable in the optimization problem.

A fixed state variable is one that is constrained to a specific value and cannot be optimized.

Attributes:

Name	Type	Description
value		The fixed value that the state variable must take.

openscvx.backend.state.Minimize

Class representing a state variable to be minimized in the optimization problem.

A minimized state variable is one that is optimized to achieve the lowest possible value within its bounds.

Attributes:

Name	Type	Description
guess		The initial guess value for optimization.

openscvx.backend.state.Maximize

Class representing a state variable to be maximized in the optimization problem.

A maximized state variable is one that is optimized to achieve the highest possible value within its bounds.

Attributes:

Name	Type	Description
guess		The initial guess value for optimization.