Retrieval transformations

ARTS provides built-in retrieval transformations described in Optimal estimation. Custom transformations can be assigned directly to any Jacobian target from Python by providing its three operators:

target = ws.jac_targets.atm[-1]
target.transform_state = lambda t, field: A @ (t - b)
target.inverse_state = lambda x, field: A_inv @ x + b
target.inverse_jacobian = lambda J, x, field: J @ A_inv

Here field is the complete owning field or data object, allowing mappings that need information beyond the target itself. Each callable must return a vector or matrix with the same shape as the target block. The example supports a general invertible affine transformation; A need not be diagonal or orthogonal. The same interface can express bounded and other reversible functional transformations.

See Optimal estimation for the forward/inverse transformation definitions and the Jacobian chain rule used by these operators.