openghg_inversions.models.fixed_error#

Gaussian observations without inferred model-data mismatch.

For reported observation-error variance \(s_y^2\) and optional fixed aggregation covariance \(C_{agg}\), this component constructs the independent variance

\[v = \max\left(|s_y|, 10^{-12}\bar{y}\right)^2.\]

The tiny scale guard preserves the historical no-model-error behaviour for zero reported errors. No inferred sigma or prepared minimum-error floor is part of this model.

openghg_inversions.models.fixed_error.add_fixed_error_likelihood(*, observations: DataArray, observation_error: DataArray, aggregation_error: AggregationError, mean: TensorVariable, output_dim: str = 'nmeasure', observation_error_name: str = 'error') → TensorVariable#

Add a Gaussian likelihood without inferred model-data mismatch.

Parameters:

  • observations – Observed mole fractions.

  • observation_error – Reported observation-error standard deviations.

  • aggregation_error – Validated fixed aggregation-error representation.

  • mean – Completed forward-model concentration aligned with output_dim.

  • output_dim – Observation dimension used for named PyMC variables.

  • observation_error_name – PyMC data name for the reported error.

Returns:

The observed Gaussian variable, named y. The total marginal error scale is also recorded in the active model as epsilon.

Raises:

ValueError – If the observation or aggregation-error inputs are inconsistent with output_dim.