OptimalEstimationData

class pyarts3.arts.OptimalEstimationData(*args, **kwargs)

Owning OEM problem, basis information and retrieval results. Used by oemCalc and oemCalcReduced.

Sizes

A variable x of this group may name 4 dimensions, read as x.model_state_vec_apriori.size(), x.measurement_vec.size(), x.model_state_basis_mat.ncols() and x.measurement_basis_mat.nrows().

Overview

Method	check()	Validate numerical inputs and optional finalized targets; report all problems or mark checked. In-place edits remain possible and require calling check() again when necessary.
Method	clear()	Reset all inputs and results.
Method	clear_auxiliary()	Release recomputable products and caches, preserving inputs, current state, bases and diagnostics.
Method	readxml()	Read variable from file.
Method	savexml()	Saves variable to file.
Method	uncheck()	Allow manual attribute replacement without changing values.
Static Method	fromxml()	Create variable from file.
float	basis_lost_dofs	Degrees of freedom lost in the basis matrix.
float	basis_lost_information_bits	Information bits lost in the basis matrix.
Vector	basis_singular_values	Singular values of the basis matrix.
bool	checked	Whether input validation succeeded. Attribute replacement requires uncheck().
JacobianTargetsDiagonalCovarianceMatrixMap	covmat_diagonal_blocks	Pending per-target covariance blocks used during target-based setup.
OptimalEstimationDiagnostics	diagnostics	Diagnostics information.
Matrix	measurement_averaging_kernel	Averaging kernel of the measurement.
BlockMatrix	measurement_basis_mat	Basis matrix of the measurement.
Matrix	measurement_gain_mat	Gain matrix of the measurement.
Matrix	measurement_jac	Jacobian of the measurement operator.
Vector	measurement_vec	Measurement vector.
CovarianceMatrix	measurement_vec_error_covmat	Covariance matrix of the measurement vector error.
Vector	measurement_vec_fit	Fitted measurement vector.
Vector	measurement_vec_normalization	Normalization vector for the measurement vector.
BlockMatrix	model_state_basis_mat	Basis matrix of the model state.
CovarianceMatrix	model_state_covmat	Covariance matrix of the model state.
Vector	model_state_covmat_normalization	Normalization vector for the model state covariance matrix.
Vector	model_state_vec	Current model state vector.
Vector	model_state_vec_apriori	A priori model state vector.
Matrix	observation_error_covmat	Covariance matrix of the observation error.
Matrix	smoothing_error_covmat	Covariance matrix of the smoothing error.
Operator	__eq__()	Return self==value.
Operator	__format__()	Default object formatter.
Operator	__ge__()	Return self>=value.
Operator	__gt__()	Return self>value.
Operator	__hash__()	Return hash(self).
Operator	__init__()	__init__(self, arg: pyarts3.arts.OptimalEstimationData) -> None
Operator	__le__()	Return self<=value.
Operator	__lt__()	Return self<value.
Operator	__ne__()	Return self!=value.
Operator	__repr__()	Return repr(self).
Operator	__str__()	Return str(self).

Constructors

__init__(self) → None

__init__(self, arg: OptimalEstimationData) → None

Methods

check(self, jac_targets: JacobianTargets | None = None) → None

Validate numerical inputs and optional finalized targets; report all problems or mark checked. In-place edits remain possible and require calling check() again when necessary.

clear(self) → None

Reset all inputs and results.

clear_auxiliary(self) → None

Release recomputable products and caches, preserving inputs, current state, bases and diagnostics.

readxml(self, file: str) → str

Read variable from file.

Parameters:

file (str) – A file that can be read.

Raises:

RuntimeError – For any failure to read.

Returns:

file – The file path found (may differ from input due to environment variables).

Return type:

str

savexml(self, file: str, type: str = 'ascii', clobber: bool = True) → str

Saves variable to file.

Parameters:

• file (str) – The path to which the file is written. Note that several of the options might modify the name or write more files.

• type (str, optional) – Type of file to save. See FileType for options. Defaults is “ascii”.

• clobber (bool, optional) – Overwrite existing files or add new file with modified name? Defaults is True.

Raises:

RuntimeError – For any failure to write.

Returns:

file – The file saved. May differ from input.

Return type:

str

uncheck(self) → None

Allow manual attribute replacement without changing values.

Static Methods

fromxml(file: str) → OptimalEstimationData

Create variable from file.

Parameters:

file (str) – A file that can be read

Raises:

RuntimeError – For any failure to read.

Returns:

artstype – The variable created from the file.

Return type:

OptimalEstimationData

Attributes

basis_lost_dofs: float

Degrees of freedom lost in the basis matrix.

basis_lost_information_bits: float

Information bits lost in the basis matrix.

basis_singular_values: Vector

Singular values of the basis matrix.

checked: bool

Whether input validation succeeded. Attribute replacement requires uncheck().

covmat_diagonal_blocks: JacobianTargetsDiagonalCovarianceMatrixMap

Pending per-target covariance blocks used during target-based setup.

diagnostics: OptimalEstimationDiagnostics

Diagnostics information.

measurement_averaging_kernel: Matrix

Averaging kernel of the measurement.

measurement_basis_mat: BlockMatrix

Basis matrix of the measurement.

measurement_gain_mat: Matrix

Gain matrix of the measurement.

measurement_jac: Matrix

Jacobian of the measurement operator.

measurement_vec: Vector

Measurement vector.

measurement_vec_error_covmat: CovarianceMatrix

Covariance matrix of the measurement vector error.

measurement_vec_fit: Vector

Fitted measurement vector.

measurement_vec_normalization: Vector

Normalization vector for the measurement vector.

model_state_basis_mat: BlockMatrix

Basis matrix of the model state.

model_state_covmat: CovarianceMatrix

Covariance matrix of the model state.

model_state_covmat_normalization: Vector

Normalization vector for the model state covariance matrix.

model_state_vec: Vector

Current model state vector.

model_state_vec_apriori: Vector

A priori model state vector.

observation_error_covmat: Matrix

Covariance matrix of the observation error.

smoothing_error_covmat: Matrix

Covariance matrix of the smoothing error.

Operators

__eq__(value, /)

Return self==value.

__format__(format_spec, /)

Default object formatter.

Return str(self) if format_spec is empty. Raise TypeError otherwise.

__ge__(value, /)

Return self>=value.

__gt__(value, /)

Return self>value.

__hash__()

Return hash(self).

__init__(self) → None

__init__(self, arg: OptimalEstimationData) → None

__le__(value, /)

Return self<=value.

__lt__(value, /)

Return self<value.

__ne__(value, /)

Return self!=value.

__repr__()

Return repr(self).

__str__()

Return str(self).