module: increments¶
- exception increments.InvalidVarianceError¶
Exception raised for errors in the input variance.
- increments.obs_increment_eakf(ensemble, observation, obs_error_var)¶
Computes increments for an ensemble adjustment Kalman filter (EAKF).
Parameters: - ensemble: numpy array representing the ensemble of prior state estimates. - observation: scalar representing the observation. - obs_error_var: scalar representing the observation error variance.
Raises: - InvalidVarianceError: If both prior and observation error variance are <= 0.
Returns: - obs_increments: numpy array representing the observation increments.
- increments.obs_increment_enkf(ensemble, observation, obs_error_var)¶
Computes increments for an ensemble Kalman filter with perturbed obs mean correction.
Parameters: - ensemble: numpy array representing the ensemble of prior state estimates. - observation: scalar representing the observation. - obs_error_var: scalar representing the observation error variance.
Raises: - InvalidVarianceError: If both prior and observation error variance <= 0.
Returns: - obs_increments: numpy array representing the observation increments.
- increments.obs_increment_rhf(ensemble, observation, obs_error_var)¶
Computes increments for a rank histogram filter.
- increments.weighted_norm_inv(alpha, mean, sd, p)¶
Find the value of x for which the cdf of a N(mean, sd) multiplied times alpha has value p.