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)
