Source code for openquake.hmtk.faults.active_fault_model

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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): ''' ''' = identifier = 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(), bin_width=0.1, 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(, for fault in self.faults: fault.generate_recurrence_models(collapse, bin_width=bin_width, 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) = str( + '_%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)