Source code for openquake.hmtk.faults.active_fault_model
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# D. Monelli.
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'''
Module :mod:`openquake.hmtk.faults.active_fault_model.mtkActiveFaultModel`
implements a wrapper class for a set of active fault sources
'''
from copy import deepcopy
import numpy as np
from openquake.hazardlib.scalerel.wc1994 import WC1994
from openquake.hmtk.sources.source_model import mtkSourceModel
[docs]class mtkActiveFaultModel(object):
'''
Class to define a compilation of active fault sources
:param str id:
Identifier for the model
:param str name:
Fault model name
:param list faults:
Active faults as a list of tuples where each tuple is an instance
of (openquake.hmtk.faults.fault_model.mtkActiveFault,
[list of MFD configurations for that fault])
:param source_model:
Instance of openquake.hmtk.source.source_model.mtkSourceModel class
'''
def __init__(self, identifier=None, name=None, faults=None):
'''
'''
self.id = identifier
self.name = name
if isinstance(faults, list):
self.faults = faults
else:
if faults:
raise ValueError('Faults must be input as list')
else:
self.faults = []
self.source_model = None
[docs] def get_number_faults(self):
'''
Returns the number of faults in the model
'''
return len(self.faults)
[docs] def build_fault_model(self, collapse=False, rendered_msr=WC1994(),
mfd_config=None):
'''
Constructs a full fault model with epistemic uncertainty by
enumerating all the possible recurrence models of each fault as
separate faults, with the recurrence rates multiplied by the
corresponding weights.
:param bool collapse:
Determines whether or not to collapse the branches
:param rendered_msr:
If the option is taken to collapse the branches then a recurrence
model for rendering must be defined
:param list/dict mfd_config:
Universal list or dictionay of configuration parameters for the
magnitude frequency distribution - will overwrite whatever is
previously defined for the fault!
'''
self.source_model = mtkSourceModel(self.id, self.name)
for fault in self.faults:
fault.generate_recurrence_models(collapse,
config=mfd_config,
rendered_msr=rendered_msr)
src_model, src_weight = fault.generate_fault_source_model()
for iloc, model in enumerate(src_model):
new_model = deepcopy(model)
new_model.id = str(model.id) + '_%g' % (iloc + 1)
new_model.mfd.occurrence_rates = \
(np.array(new_model.mfd.occurrence_rates) *
src_weight[iloc]).tolist()
self.source_model.sources.append(new_model)