def read_index(self, **kwargs) -> pd.DataFrame:
"""
Read the index and return a dataframe containing the event info.
Parameters
----------
{get_events_params}
"""
self.ensure_bank_path_exists()
# Make sure all times are numpy datetime64
kwargs = _dict_times_to_npdatetimes(kwargs)
# a simple switch to prevent infinite recursion
allow_update = kwargs.pop("_allow_update", True)
# Circular search requires work to be done on the dataframe - we need
# to get the whole dataframe then calculate the distances and search in
# that
circular_kwargs, kwargs = _sanitize_circular_search(**kwargs)
with sql_connection(self.index_path) as con:
try:
df = _read_table(self._index_node, con, **kwargs)
except pd.io.sql.DatabaseError:
# if this database has never been updated, update now
if allow_update and self.last_updated_timestamp < 1:
self.update_index()
return self.read_index(_allow_update=False, **kwargs)
# else return empty index
df = pd.DataFrame(columns=list(EVENT_TYPES_OUTPUT))
df = _ints_to_time_columns(df, columns=INT_COLUMNS).pipe(
self._prepare_dataframe, dtypes=EVENT_TYPES_OUTPUT)
if len(circular_kwargs) >= 3:
# Requires at least latitude, longitude and min or max radius
circular_ids = _get_ids(df, circular_kwargs)
df = df[df.event_id.isin(circular_ids)]
return df
def get_events(cat: obspy.Catalog, **kwargs) -> obspy.Catalog:
"""
Return a subset of a events filtered on input parameters.
Parameters
----------
{get_event_parameters}
"""
# If not kwargs are passed just return all events
if not kwargs:
return cat
# Make sure all inputs are supported
if not set(kwargs).issubset(SUPPORTED_PARAMS):
bad_params = set(kwargs) - SUPPORTED_PARAMS
msg = f"{bad_params} are not supported get_events parameters"
raise TypeError(msg)
# Ensure all times are numpy datetimes
kwargs = _dict_times_to_npdatetimes(kwargs)
event_ids = _get_ids(obsplus.events_to_df(cat), kwargs)
events = [eve for eve in cat if str(eve.resource_id) in event_ids]
return obspy.Catalog(events=events)