`Uncertainty Quantification`#

class UncertaintyQuantification(epoch: int, frame: str = 'J2000', definition=None)#

Bases: ABC

Abstract base class for uncertainty quantification.

Provides a common interface for different uncertainty representations including covariance matrices, sigma points, and other uncertainty propagation methods.

Parameters:

epoch (int) – The epoch of the uncertainty representation.
frame (str, optional) – The reference frame. Defaults to ‘J2000’.
definition (optional) – Sequence or state definition. Defaults to None.

Attributes:

definition: The sequence or state definition.
epoch: The epoch of the uncertainty representation.
frame: The reference frame of the uncertainty representation.

Methods

`get_standard_deviations`()	Get standard deviations for each parameter.
`to_array`()	Convert uncertainty representation to numpy array.

abstractmethod get_standard_deviations() → ndarray#

Get standard deviations for each parameter.

Returns:: Array of standard deviations.
Return type:: np.ndarray

abstractmethod to_array() → ndarray#

Convert uncertainty representation to numpy array.

Returns:: Numpy array representation without units.
Return type:: np.ndarray

property definition#: The sequence or state definition.

property epoch: int#: The epoch of the uncertainty representation.

property frame: str#: The reference frame of the uncertainty representation.

Uncertainty Quantification#

`Uncertainty Quantification`#