salvus.project.tools.data_selection.seismology.receiver_weighting

def apply_receiver_weighting(
    ewws: salvus.flow.collections.event_window_and_weight_set.EventWindowAndWeightSet,
    weighting_chain: List[Dict],
    normalize: bool,
) -> None:
    ...

Entry point to apply a number of receiver weighting functions.

The items in weighting_chain each describe a different weighting function. The weights from all functions/stages are multiplied together to yield the final receiver weight.

Only receivers that do have at least one window on any component will be passed to the weighting functions.

Each item in weighting_chain must be a dictionary of the form:

{
    "weighting_scheme": "name_of_the_schema",
    "function_kwargs": {"extra": "function_arguments"},
}

The "weighting_scheme" can be a function that must accept at least two arguments listed in the following.

• event: The event objects for which to set weights.
• receiver: A dictionary of receiver name -> coordinates.

Additionally it can take any number of extra arguments that are passed via the "function_kwargs" key. The function must return a dictionary of receiver name -> receiver weight.

Currently available built-in receiver weighting schemes:

• "ruan_et_al_2019": See the receiver_weighting_ruan_et_al_2019
  • function for details.
• "mute_near_source_receivers": See the receiver_weighting_mute_near_source_receivers function for details.

def receiver_weighting_mute_near_source_receivers(
    event: salvus.flow.collections.event.Event,
    receivers: Dict,
    minimum_receiver_distance_in_m: float,
    maximum_receiver_mute_distance_in_m: float,
    taper_type: str,
) -> Dict[str, float]:
    ...

Mute near source receivers.

def receiver_weighting_ruan_et_al_2019(
    event: salvus.flow.collections.event.Event,
    receivers: Dict,
    ref_distance_condition_fraction: float,
) -> Dict[str, float]:
    ...

Receiver/station weighting after:

Ruan, Y. et al. (2019) Balancing unevenly distributed data in seismic tomography: a global adjoint tomography example, Geophysical Journal International, Volume 219, Issue 2, https://doi.org/10.1093/gji/ggz356

It will give smaller weights stations in dense cluster and larger weights to isolated stations in an effort to alleviate the uneven station distribution in the real world.