csep.core.catalogs.AbstractBaseCatalog

class csep.core.catalogs.AbstractBaseCatalog(filename=None, data=None, catalog_id=None, format=None, name=None, region=None, compute_stats=True, filters=None, metadata=None, date_accessed=None)[source]

Abstract catalog base class for PyCSEP catalogs. This class should not and cannot be used on its own. This just provides the interface for implementing custom catalog classes.

__init__(filename=None, data=None, catalog_id=None, format=None, name=None, region=None, compute_stats=True, filters=None, metadata=None, date_accessed=None)[source]
Standard catalog format for CSEP catalogs. Primary event data are stored in structured numpy array. Additional

metadata are available by the event_id in the catalog metadata information.

Parameters
  • filename – location of catalog

  • catalog (numpy.ndarray or eventlist) – catalog data

  • catalog_id – catalog id number (used for stochastic event set forecasts)

  • format – identification used for serialization

  • name – human readable name of catalog

  • region – spatial and magnitude region

  • compute_stats – whether statistics should be computed for the catalog

  • filters (str or list) – filtering operations to apply to the catalog

  • metadata (dict) – additional information for events

  • date_accessed (str) – time string when catalog was accessed

Methods

__init__([filename, data, catalog_id, …])

Standard catalog format for CSEP catalogs. Primary event data are stored in structured numpy array. Additional

apply_mct(m_main, event_epoch[, mc])

Applies time-dependent magnitude of completeness following a mainshock.

filter([statements, in_place])

Filters the catalog based on statements.

filter_spatial([region, update_stats])

Removes events outside of the region.

from_dataframe(df, **kwargs)

Creates catalog from dataframe.

from_dict(adict, **kwargs)

Creates a class from the dictionary representation of the class state.

get_bvalue([mag_bins, return_error])

Estimates the b-value of a catalog from Marzocchi and Sandri (2003).

get_csep_format()

This method should be overwritten for catalog formats that do not adhere to the CSEP ZMAP catalog format.

get_cumulative_number_of_events()

Returns the cumulative number of events in the catalog.

get_datetimes()

Returns datetime object from timestamp representation in catalog

get_depths()

Returns depths of all events in catalog

get_epoch_times()

Returns the datetime of the event as the UTC epoch time (aka unix timestamp)

get_event_ids()

get_latitudes()

Returns latitudes of all events in catalog

get_longitudes()

Returns longitudes of all events in catalog

get_mag_idx()

Return magnitude index from region magnitudes

get_magnitudes()

Returns magnitudes of all events in catalog

get_number_of_events()

Computes the number of events from a catalog by checking its length.

get_spatial_idx()

Return spatial index of region for a longitudes and latitudes in catalog.

length_in_seconds()

Returns catalog length in seconds assuming that the catalog is sorted by time.

load_catalog(filename[, loader])

load_json(filename, **kwargs)

Loads catalog from JSON file

magnitude_counts([mag_bins, retbins])

Computes the count of events within mag_bins

spatial_counts()

Returns counts of events within discrete spatial region

spatial_event_probability()

spatial_magnitude_counts([mag_bins, ret_skipped])

Return counts of events in space-magnitude region.

to_dataframe([with_datetime])

Returns pandas Dataframe describing the catalog.

to_dict()

Serializes class to json dictionary.

update_catalog_stats()

Compute summary statistics of events in catalog

write_ascii(filename[, write_header, …])

Write catalog in csep2 ascii format.

write_json(filename)

Writes catalog to json file

Attributes

catalog

data

dtype

event_count

Number of events in catalog

log