giant.calibration.estimatorsΒΆ

Modules

alignment

geometric

Functions

static_alignment_estimator

This function estimates a static attitude alignment between one frame and another.

temperature_dependent_alignment_estimator

This function estimates a temperature dependent attitude alignment between one frame and another.

evaluate_temperature_dependent_alignment

This function takes a fit temperature dependent alignment solution and evaluates what the alignment rotation is at a specified temperature.

Classes

GeometricEstimatorOptions

GeometricEstimatorOptions(weighted_estimation: bool = False, a_priori_model_covariance: Optional[numpy.ndarray[tuple[Any, ...], numpy.dtype[numpy.float64]]] = None)

GeometricEstimator

This protocol class serves as the template for implementing a class for doing geometric camera model estimation in GIANT.

IterativeNonlinearLstSqOptions

IterativeNonlinearLstSqOptions(weighted_estimation: bool = False, a_priori_model_covariance: Optional[numpy.ndarray[tuple[Any, ...], numpy.dtype[numpy.float64]]] = None, max_iter: int = 20, residual_atol: float = 1e-10, residual_rtol: float = 1e-10, state_atol: float = 1e-10, state_rtol: float = 1e-10)

IterativeNonlinearLSTSQ

This concrete estimator implements iterative non-linear least squares for estimating an updated camera model.

LMAEstimatorOptions

LMAEstimatorOptions(weighted_estimation: bool = False, a_priori_model_covariance: Optional[numpy.ndarray[tuple[Any, ...], numpy.dtype[numpy.float64]]] = None, max_iter: int = 20, residual_atol: float = 1e-10, residual_rtol: float = 1e-10, state_atol: float = 1e-10, state_rtol: float = 1e-10, max_divergence_steps: int = 5)

LMAEstimator

This implements a Levenberg-Marquardt Algorithm estimator, which is analogous to a damped iterative non-linear least squares.

TemperatureDependentResults

Named tuple to make the results clear