retrievalAddSinefit

Workspace.retrievalAddSinefit(self: pyarts.arts._Workspace, covmat_sx: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.CovarianceMatrix]] = self.covmat_sx, jacobian_quantities: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.ArrayOfRetrievalQuantity]] = self.jacobian_quantities, jacobian_agenda: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Agenda]] = self.jacobian_agenda, covmat_block: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Sparse]] = self.covmat_block, covmat_inv_block: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Sparse]] = self.covmat_inv_block, sensor_response_pol_grid: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.ArrayOfIndex]] = self.sensor_response_pol_grid, sensor_response_dlos_grid: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Matrix]] = self.sensor_response_dlos_grid, sensor_pos: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Matrix]] = self.sensor_pos, period_lengths: Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Vector], no_pol_variation: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Index]] = 0, no_los_variation: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Index]] = 0, no_mblock_variation: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Index]] = 0, verbosity: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Verbosity]] = self.verbosity) → None

Same as jacobianAddSinefit() but also adds a new block to covmat_sx using the matrices in covmat_block and covmat_inv_block.

If covmat_inv_block is non-empty, it is used as inverse for the added block which avoids its numerical computation.

For number and order of elements added to x, see jacobianAddSinefit().

Author(s): Simon Pfreundschuh

Parameters:

  • covmat_sx (CovarianceMatrix, optional) – Covariance matrix of a priori distribution. See covmat_sx, defaults to self.covmat_sx [INOUT]

  • jacobian_quantities (ArrayOfRetrievalQuantity, optional) – The retrieval quantities in the Jacobian matrix. See jacobian_quantities, defaults to self.jacobian_quantities [INOUT]

  • jacobian_agenda (Agenda, optional) – Pure numerical Jacobian calculations. See jacobian_agenda, defaults to self.jacobian_agenda [INOUT]

  • covmat_block (Sparse, optional) – Holds matrices used to set blocks in covmat_sx and covmat_se. See covmat_block, defaults to self.covmat_block [IN]

  • covmat_inv_block (Sparse, optional) – Holds matrices used to set the inverse blocks in covmat_sx and covmat_se. See covmat_inv_block, defaults to self.covmat_inv_block [IN]

  • sensor_response_pol_grid (ArrayOfIndex, optional) – The “polarisation grid” associated with sensor_response. See sensor_response_pol_grid, defaults to self.sensor_response_pol_grid [IN]

  • sensor_response_dlos_grid (Matrix, optional) – The zenith and azimuth angles associated with sensor_response. See sensor_response_dlos_grid, defaults to self.sensor_response_dlos_grid [IN]

  • sensor_pos (Matrix, optional) – The sensor position for each measurement block. See sensor_pos, defaults to self.sensor_pos [IN]

  • period_lengths (Vector) – Period lengths of the fit. [IN]

  • no_pol_variation (Index, optional) – Set to 1 if the baseline off-set is the same for all Stokes components. Defaults to 0 [IN]

  • no_los_variation (Index, optional) – Set to 1 if the baseline off-set is the same for all line-of-sights (inside each measurement block). Defaults to 0 [IN]

  • no_mblock_variation (Index, optional) – Set to 1 if the baseline off-set is the same for all measurement blocks. Defaults to 0 [IN]

  • verbosity (Verbosity) – ARTS verbosity. See verbosity, defaults to self.verbosity [IN]