OptimalEstimationData
#####################

.. currentmodule:: pyarts3.arts

.. autoclass:: OptimalEstimationData

  .. rubric:: Overview

  .. list-table::

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

  .. rubric:: Constructors

  .. automethod:: __init__
     :noindex:

  .. rubric:: Methods

  .. automethod:: OptimalEstimationData.check
  .. automethod:: OptimalEstimationData.clear
  .. automethod:: OptimalEstimationData.clear_auxiliary
  .. automethod:: OptimalEstimationData.readxml
  .. automethod:: OptimalEstimationData.savexml
  .. automethod:: OptimalEstimationData.uncheck

  .. rubric:: Static Methods

  .. automethod:: OptimalEstimationData.fromxml

  .. rubric:: Attributes

  .. attribute:: OptimalEstimationData.basis_lost_dofs
     :type: float

     Degrees of freedom lost in the basis matrix.

     .. :class:`float`


  .. attribute:: OptimalEstimationData.basis_lost_information_bits
     :type: float

     Information bits lost in the basis matrix.

     .. :class:`float`


  .. attribute:: OptimalEstimationData.basis_singular_values
     :type: ~pyarts3.arts.Vector

     Singular values of the basis matrix.

     .. :class:`~pyarts3.arts.Vector`


  .. attribute:: OptimalEstimationData.checked
     :type: bool

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

     .. :class:`bool`


  .. attribute:: OptimalEstimationData.covmat_diagonal_blocks
     :type: ~pyarts3.arts.JacobianTargetsDiagonalCovarianceMatrixMap

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

     .. :class:`~pyarts3.arts.JacobianTargetsDiagonalCovarianceMatrixMap`


  .. attribute:: OptimalEstimationData.diagnostics
     :type: ~pyarts3.arts.OptimalEstimationDiagnostics

     Diagnostics information.

     .. :class:`~pyarts3.arts.OptimalEstimationDiagnostics`


  .. attribute:: OptimalEstimationData.measurement_averaging_kernel
     :type: ~pyarts3.arts.Matrix

     Averaging kernel of the measurement.

     .. :class:`~pyarts3.arts.Matrix`


  .. attribute:: OptimalEstimationData.measurement_basis_mat
     :type: ~pyarts3.arts.BlockMatrix

     Basis matrix of the measurement.

     .. :class:`~pyarts3.arts.BlockMatrix`


  .. attribute:: OptimalEstimationData.measurement_gain_mat
     :type: ~pyarts3.arts.Matrix

     Gain matrix of the measurement.

     .. :class:`~pyarts3.arts.Matrix`


  .. attribute:: OptimalEstimationData.measurement_jac
     :type: ~pyarts3.arts.Matrix

     Jacobian of the measurement operator.

     .. :class:`~pyarts3.arts.Matrix`


  .. attribute:: OptimalEstimationData.measurement_vec
     :type: ~pyarts3.arts.Vector

     Measurement vector.

     .. :class:`~pyarts3.arts.Vector`


  .. attribute:: OptimalEstimationData.measurement_vec_error_covmat
     :type: ~pyarts3.arts.CovarianceMatrix

     Covariance matrix of the measurement vector error.

     .. :class:`~pyarts3.arts.CovarianceMatrix`


  .. attribute:: OptimalEstimationData.measurement_vec_fit
     :type: ~pyarts3.arts.Vector

     Fitted measurement vector.

     .. :class:`~pyarts3.arts.Vector`


  .. attribute:: OptimalEstimationData.measurement_vec_normalization
     :type: ~pyarts3.arts.Vector

     Normalization vector for the measurement vector.

     .. :class:`~pyarts3.arts.Vector`


  .. attribute:: OptimalEstimationData.model_state_basis_mat
     :type: ~pyarts3.arts.BlockMatrix

     Basis matrix of the model state.

     .. :class:`~pyarts3.arts.BlockMatrix`


  .. attribute:: OptimalEstimationData.model_state_covmat
     :type: ~pyarts3.arts.CovarianceMatrix

     Covariance matrix of the model state.

     .. :class:`~pyarts3.arts.CovarianceMatrix`


  .. attribute:: OptimalEstimationData.model_state_covmat_normalization
     :type: ~pyarts3.arts.Vector

     Normalization vector for the model state covariance matrix.

     .. :class:`~pyarts3.arts.Vector`


  .. attribute:: OptimalEstimationData.model_state_vec
     :type: ~pyarts3.arts.Vector

     Current model state vector.

     .. :class:`~pyarts3.arts.Vector`


  .. attribute:: OptimalEstimationData.model_state_vec_apriori
     :type: ~pyarts3.arts.Vector

     A priori model state vector.

     .. :class:`~pyarts3.arts.Vector`


  .. attribute:: OptimalEstimationData.observation_error_covmat
     :type: ~pyarts3.arts.Matrix

     Covariance matrix of the observation error.

     .. :class:`~pyarts3.arts.Matrix`


  .. attribute:: OptimalEstimationData.smoothing_error_covmat
     :type: ~pyarts3.arts.Matrix

     Covariance matrix of the smoothing error.

     .. :class:`~pyarts3.arts.Matrix`



  .. rubric:: Operators

  .. automethod:: OptimalEstimationData.__eq__
  .. automethod:: OptimalEstimationData.__format__
  .. automethod:: OptimalEstimationData.__ge__
  .. automethod:: OptimalEstimationData.__gt__
  .. automethod:: OptimalEstimationData.__hash__
  .. automethod:: OptimalEstimationData.__init__
  .. automethod:: OptimalEstimationData.__le__
  .. automethod:: OptimalEstimationData.__lt__
  .. automethod:: OptimalEstimationData.__ne__
  .. automethod:: OptimalEstimationData.__repr__
  .. automethod:: OptimalEstimationData.__str__