ForecastGRRateGrid#

class seismostats.ForecastGRRateGrid(data=None, *args, n_grids=None, **kwargs)#

A seismicity forecast on a grid where for each grid cell, the GR parameters (a-value, b-value, mc) are defined. Additionally to the GRRateGrid, this class has a grid_id column to identify each possible realization of the grid.

To be a valid RateGrid object, it must have the following columns: longitude_min, longitude_max, latitude_min, latitude_max, depth_min, depth_max, number_events, a, b, mc, and grid_id.

Parameters:

  • data – Data to initialize the catalog with.

  • name – Name of the catalog.

  • starttime – Start time of the catalog. If a string, it must be in a format that can be parsed by pandas.to_datetime.

  • endtime – End time of the catalog. If a string, it must be in a format that can be parsed by pandas.to_datetime.

  • kwargs – Additional arguments and keyword arguments to pass to pandas DataFrame constructor.

Notes

The ForecastRateGrid class is a subclass of pandas.DataFrame, and inherits all of its methods and attributes.

Examples

Create a ForecastGRRateGrid from a dictionary with two grid cells, each having two realizations (as indicated by grid_id).

>>> import pandas as pd
>>> from seismostats import ForecastGRRateGrid
>>> data = {
...     'longitude_min': [9, 9, 10, 10],
...     'longitude_max': [10, 10, 11, 11],
...     'latitude_min': [45, 45, 46, 46],
...     'latitude_max': [46, 46, 47, 47],
...     'depth_min': [10, 10, 20, 20],
...     'depth_max': [20, 20, 30, 30],
...     'number_events': [5, 6, 10, 12],
...     'a': [0.8, 0.9, 1.0, 1.1],
...     'b': [0.95, 1.0, 1.05, 1.1],
...     'mc': [1.2, 1.2, 1.3, 1.3],
...     'grid_id': [0, 0, 1, 1]
... }
>>> forecast = ForecastGRRateGrid(
...     data,
...     starttime=pd.Timestamp('2023-01-01'),
...     endtime=pd.Timestamp('2023-01-02'))
>>> forecast

   longitude_min longitude_max  ...    a     b   mc  grid_id
0            9.0          10.0  ...  0.8  0.95  1.2        0
1            9.0          10.0  ...  0.9  1.00  1.2        0
2           10.0          11.0  ...  1.0  1.05  1.3        1
3           10.0          11.0  ...  1.1  1.10  1.3        1

Attributes

Methods

calculate_statistics

Get statistics for a, b, alpha, mc and number_events, if present, per timestep and grid cell, aggregated over all realizations of the grid (i.e. over all grid_id values).
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