# and taking advantage of the %g format
if row[4] == 0:
continue
row_dict = {
'Longitude': '%g' % row[0],
'Latitude': '%g' % row[1],
'Depth': '%g' % row[2],
'Observed Count': '%d' % row[3],
'Smoothed Rate': '%.6g' % row[4],
'b-value': '%g' % self.bval
}
writer.writerow(row_dict)
fid.close()
SMOOTHED_SEISMICITY_METHODS = CatalogueFunctionRegistry()
@SMOOTHED_SEISMICITY_METHODS.add("run",
completeness=True,
b_value=float,
use_3d=bool,
grid_limits=Grid,
Length_Limit=float,
BandWidth=float,
increment=bool)
class IsotropicGaussianMethod(object):
def run(self, catalogue, config, completeness=None):
ss = SmoothedSeismicity(config['grid_limits'], config['use_3d'],
config['b_value'])
return ss.run_analysis(catalogue,
# The GEM Foundation, and the authors of the software, assume no
# liability for use of the software.
"""
Module :mod:'openquake.hmtk.seismicity.completeness.base' defines an abstract base class
for :class:'CataloguCompleteness <BaseCatalogueCompleteness>
"""
import abc
from openquake.hmtk.registry import CatalogueFunctionRegistry
class BaseCatalogueCompleteness(object):
'''
Abstract base class for implementation of the completeness algorithms
'''
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def completeness(self, catalogue, config):
'''
:param catalogue:
Earthquake catalogue as instance of
:class: openquake.hmtk.seismicity.catalogue.Catalogue
:param dict config:
Configuration parameters of the algorithm
'''
return
COMPLETENESS_METHODS = CatalogueFunctionRegistry()
"""
"""
import abc
from openquake.hmtk.registry import CatalogueFunctionRegistry
class SeismicityOccurrence(object):
'''Implements recurrence calculations for instrumental seismicity'''
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def calculate(self, catalogue, config, completeness=None):
"""Implements recurrence calculation
:param catalogue:
An instance of :class:`openquake.hmtk.seismicity.catalogue`
:param dict config:
The config contains the necessary information to run a specific
algorithm.
:param numpy.ndarray completeness:
The completeness matrix
"""
return
OCCURRENCE_METHODS = CatalogueFunctionRegistry()
return neq, mmin
class BaseMaximumMagnitude(object):
'''
Abstract base class for implementation of the maximum magnitude estimation
based on instrumental/historical seismicity
'''
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def get_mmax(self, catalogue, config):
'''
Analyses the catalogue to infer the maximum magnitude from a
statistical process
:param catalogue:
Earthquake catalogue as instance of the :class:
'openquake.hmtk.seismicity.catalogue.Catalogue'
:param dict config:
Configuration parameters of the algorithm
:returns:
* Maximum magnitude (float)
* Maximum magnitude uncertainty (float)
'''
MAX_MAGNITUDE_METHODS = CatalogueFunctionRegistry()
for :class:`CatalogueParser <BaseCatalogueDecluster>`.
"""
import abc
from openquake.hmtk.registry import CatalogueFunctionRegistry
class BaseCatalogueDecluster(object):
"""
Abstract base class for implementation of declustering algorithms
"""
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def decluster(self, catalogue, config):
"""
Implements declustering algorithms
:param catalogue:
Catalogue of earthquakes
:type catalogue:
:param config:
Declustering configuration dictionary
:type config: Dictionary
Returns two vectors
"""
return
DECLUSTERER_METHODS = CatalogueFunctionRegistry()