oemAddOverlappingMagneticField

Workspace.oemAddOverlappingMagneticField(self, jac_targets: JacobianTargets = self.jac_targets, oem: OptimalEstimationData = self.oem, matrix: BlockMatrix, inverse: BlockMatrix = []) → None

Set magnetic field derivative for overlapping fields.

An overlapping field means that the derivative is computed but that the x-component of the jacobian is at the same position as another Jacobian target.

The reason for this method is that it allows representing the (signed) absolute magnetic field derivative as a combination of the three magnetic field components.

To call this method, you first have added 1 component of the magnetic field derivative, and then you call this method to add the second and third component.

This method wraps jac_targetsAddOverlappingMagneticField() together with adding the covariance matrices, to oem.covmat_diagonal_blocks for assembly by oemFinalizeDiagonal().

The input covariance matrices must fit the size of the later computed model state represented by jac_targets. The inverse block is optional.

Warning

Automatic size constraints are not checked for this method. Group-invariant checks on read-only inputs still apply.

Author: Richard Larsson

Parameters:

  • jac_targets (~pyarts3.arts.JacobianTargets, optional) – A list of targets for the Jacobian Matrix calculations. Defaults to self.jac_targets. [INOUT]

  • oem (~pyarts3.arts.OptimalEstimationData, optional) – Numerical problem and results for oemCalc() and oemCalcReduced(). Defaults to self.oem. [INOUT]

  • matrix (BlockMatrix) – The covariance diagonal block matrix. [IN]

  • inverse (~pyarts3.arts.BlockMatrix, optional) – The inverse covariance diagonal block matrix. Defaults to pyarts3.arts.BlockMatrix() [IN]