def edit(stage, dset): """Edit GNSS data Args: stage (str): Name of current stage. dset (Dataset): A dataset containing the data. """ cleaners.apply_editors("editors", dset) cleaners.apply_removers("removers", dset) dset.write_as(stage=stage)
def edit(stage, dset): """Edit GNSS data Args: stage (str): Name of current stage. dset (Dataset): A dataset containing the data. """ cleaners.apply_editors("editors", dset) cleaners.apply_removers("removers", dset) dset.write_as(stage=stage) dset.read() # TODO: workaround because caching does not work correctly
def edit(stage, dset): """Edit the observations Args: rundate (Datetime): The model run date. session (String): Name of session. prev_stage (String): Name of previous stage. stage (String): Name of current stage. """ cleaners.apply_editors("editors", dset) cleaners.apply_removers("removers", dset) dset.write_as(stage=stage, label=0)
def edit(rundate, session, prev_stage, stage): """Edit the observations Args: rundate (Datetime): The model run date. session (String): Name of session. prev_stage (String): Name of previous stage. stage (String): Name of current stage. """ dset = data.Dataset(rundate, tech=TECH, stage=prev_stage, dataset_name=session, dataset_id="last") cleaners.apply_editors("editors", dset) cleaners.apply_removers("removers", dset) dset.write_as(stage=stage, dataset_id=0)
def edit(stage, dset): """Edit the data by applying editor Args: stage: Name of current stage dset: Dataset containing the data """ # Clean up dataset cleaners.apply_removers("removers", dset) # Indicate if range and time bias are estimated or not # and apply biases dset.add_float("range_bias", np.zeros(dset.num_obs), unit="meter") dset.add_float("time_bias", np.zeros(dset.num_obs), unit="meter") dset.add_bool("estimate_range", np.zeros(dset.num_obs)) dset.add_bool("estimate_time", np.zeros(dset.num_obs)) for station in config.tech.slr_range_bias.estimate_stations.list: int_idx = dset.filter(station=station) if np.any(int_idx): log.info( f"Config file: Will estimate range bias for station {station} in estimation stage" ) dset.estimate_range[:] = np.logical_or(int_idx, dset.estimate_range[:]) for station in config.tech.slr_time_bias.estimate_stations.list: int_idx = dset.filter(station=station) if np.any(int_idx): log.info( f"Config file: Will estimate time bias for station {station} in estimation stage" ) dset.estimate_time[:] = np.logical_or(int_idx, dset.estimate_time[:]) cleaners.apply_editors("editors", dset) # Write dataset dset.write_as(stage=stage, label=0)