Source code for openquake.hmtk.faults.fault_models

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4

# Copyright (c) 2010-2017, GEM Foundation, G. Weatherill, M. Pagani,
# D. Monelli.
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Module: openquake.hmtk.faults.fault_model implements the set of classes to allow for a
calculation of the magnitude frequency distribution from the geological
slip rate
import numpy as np
from math import fabs

from openquake.hazardlib.scalerel import get_available_scalerel
from openquake.hazardlib.mfd.evenly_discretized import EvenlyDiscretizedMFD
from openquake.hmtk.models import IncrementalMFD
from openquake.hmtk.faults.fault_geometries import (SimpleFaultGeometry,
from openquake.hmtk.sources.simple_fault_source import mtkSimpleFaultSource
from openquake.hmtk.sources.complex_fault_source import mtkComplexFaultSource
from openquake.hmtk.faults import mfd

MFD_MAP = mfd.get_available_mfds()
SCALE_REL_MAP = get_available_scalerel()
DEFAULT_MSR_SIGMA = [(0., 1.0)]

def _update_slip_rates_with_aseismic(slip_rate, aseismic):
    For all the slip rates in the slip rate tuple, multiply by the aseismic
    :param list slip_rate:
        List of tuples (Slip Value, Weight) defining the slip distribution
    :param float aseismic:
        Fractional proportion of slip release aseismically

        slip - List of tuples (Slip Value, Weight) for adjusted slip rates

    return [(slip_val * (1.0 - aseismic), weight)
            for slip_val, weight in slip_rate]

[docs]class RecurrenceBranch(object): ''' :class:`openquake.hmtk.faults.fault_model.RecurrenceBranch` is an object to store a set of parameters for recurrence calculations and the corresponding total weight :param str branch_id: Unique branch id :param float area: Fault area (km ^ 2) :param float slip: Fault slip rate (mm / yr) :param msr: Magnitude scaling relation as instance of :class: openquake.hazardlib.scale_rel.base.BaseASR :param float rake: Rake of fault (degrees) :param float shear_modulus: Shear modulus of fault (GPa) :param float disp_length_ratio: Displacement to length ratio of the fault :param float weight: Weight of recurrence model branch :param recurrence: Magnitude frquency distribution as instance of :class: openquake.hmtk.models.IncrementalMFD :param float max_mag: Maximum magnitude from the magnitude frequency distribution :param numpy.ndarray magnitudes: Magnitudes of MFD ''' def __init__(self, area, slip, msr, rake, shear_modulus, disp_length_ratio=None, msr_sigma=0., weight=1.0): self.branch_id = None self.area = area self.slip = slip self.msr = msr self.msr_sigma = msr_sigma self.rake = rake self.shear_modulus = shear_modulus self.disp_length_ratio = disp_length_ratio self.weight = weight self.recurrence = None self.max_mag = None self.magnitudes = None
[docs] def update_weight(self, new_weight): ''' Updates the weight by multiplying by the new weight :param float new_weight: Weight to be multiplied by existing weight ''' self.weight = self.weight * new_weight
[docs] def get_recurrence(self, config): ''' Calculates the recurrence model for the given settings as an instance of the openquake.hmtk.models.IncrementalMFD :param dict config: Configuration settings of the magnitude frequency distribution. ''' model = MFD_MAP[config['Model_Name']]() model.setUp(config) model.get_mmax(config, self.msr, self.rake, self.area) model.mmax = model.mmax + (self.msr_sigma * model.mmax_sigma) # As the Anderson & Luco arbitrary model requires the input of the # displacement to length ratio if 'AndersonLucoAreaMmax' in config['Model_Name']: if not self.disp_length_ratio: # If not defined then default to 1.25E-5 self.disp_length_ratio = 1.25E-5 min_mag, bin_width, occur_rates = model.get_mfd( self.slip, self.area, self.shear_modulus, self.disp_length_ratio) else: min_mag, bin_width, occur_rates = model.get_mfd(self.slip, self.area, self.shear_modulus) self.recurrence = IncrementalMFD(min_mag, bin_width, occur_rates) self.magnitudes = min_mag + np.cumsum( bin_width * np.ones(len(occur_rates), dtype=float)) - bin_width self.max_mag = np.max(self.magnitudes)
[docs]class mtkActiveFault(object): ''' Main class to represent fault source :param int identifier: Identifier Code :param str name: Fault Name :param geometry: Instance of :class:`openquake.hmtk.faults.fault_model.SimpleFaultGeometry` or :class:`openquake.hmtk.faults.fault_model.ComplexFaultGeometry` :param list slip_rate: Slip rate (mm/yr) as list of tuples [(Value, Weight)] :param float aseismic: Aseismic slip coefficient :param float rake: Rake of the fault slip (degrees) :param neotectonic_fault: Instance of :class:`openquake.hmtk.faults.faulted_earth.NeotectonicFault` :param str trt: Tectonic region type :param scale_rel: Scaling relation as list of tuples [(:class: openquake.hazardlib.scalerel.base.BaseASR, Weight)] :param float aspect_ratio: Aspect ratio on fault :param tuple mfd: Tuple ([MFD], [Weight], [Scale_Rel]) defining the magnitude frequency distribution :param list shear_modulus: Shear Modulus (GPa) as list of tuples [(Value, Weight)] :param list disp_length_ratio: Displacement to length ratio as list of tuples [(Value, Weight)] :param list mfd_models: Magnitude frequency distributions as list of instances of :class: openquake.hmtk.faults.fault_model.RecurrenceBranch :param list mfd_models: Magnitude frequency distributions as list of instances of :class: openquake.hmtk.models.IncrementalMFD :param float area: Area of fault (km ^ 2) :param dict config: Dictionary of configuration paramters for magnitude freuency distribution calculation ''' def __init__(self, identifier, name, geometry, slip_rate, rake, trt, aseismic=0.0, msr_sigma=None, neotectonic_fault=None, scale_rel=None, aspect_ratio=None, shear_modulus=None, disp_length_ratio=None): ''' ''' = identifier = name msr_sigma = msr_sigma or DEFAULT_MSR_SIGMA cond = (not isinstance(geometry, SimpleFaultGeometry) and not isinstance(geometry, ComplexFaultGeometry)) if cond: raise IOError('Geometry must be instance of ' 'openquake.hmtk.faults.fault_geometries.BaseFaultGeometry') self.geometry = geometry self.aseismic = aseismic # Assert that the sum of the slip rates is 1.0 if fabs(np.sum([val[1] for val in slip_rate]) - 1.) > 1E-7: raise ValueError('Slip rate weightings must sum to 1.0') self.slip = _update_slip_rates_with_aseismic(slip_rate, self.aseismic) self.rake = rake self.neotectonic_fault = neotectonic_fault self.trt = trt self.rupt_aspect_ratio = aspect_ratio self.mfd = ([], [], []) self.shear_modulus = shear_modulus self.disp_length_ratio = disp_length_ratio self.mfd_models = [] self.msr = scale_rel self.msr_sigma = msr_sigma self.area = self.geometry.get_area() self.config = None self.regionalisation = None self.catalogue = None
[docs] def get_tectonic_regionalisation(self, regionalisation, region_type=None): ''' Defines the tectonic region and updates the shear modulus, magnitude scaling relation and displacement to length ratio using the regional values, if not previously defined for the fault :param regionalistion: Instance of the :class: openquake.hmtk.faults.tectonic_regionalisaion.TectonicRegionalisation :param str region_type: Name of the region type - if not in regionalisation an error will be raised ''' if region_type: self.trt = region_type if not self.trt in regionalisation.key_list: raise ValueError('Tectonic region classification missing or ' 'not defined in regionalisation') for iloc, key_val in enumerate(regionalisation.key_list): if self.trt in key_val: self.regionalisation = regionalisation.regionalisation[iloc] # Update undefined shear modulus from tectonic regionalisation if not self.shear_modulus: self.shear_modulus = self.regionalisation.shear_modulus # Update undefined scaling relation from tectonic # regionalisation if not self.msr: self.msr = self.regionalisation.scaling_rel # Update undefined displacement to length ratio from tectonic # regionalisation if not self.disp_length_ratio: self.disp_length_ratio = \ self.regionalisation.disp_length_ratio break return
[docs] def select_catalogue(self, selector, distance, distance_metric="rupture", upper_eq_depth=None, lower_eq_depth=None): """ Select earthquakes within a specied distance of the fault """ if selector.catalogue.get_number_events() < 1: raise ValueError('No events found in catalogue!') # rupture metric is selected if ('rupture' in distance_metric): # Use rupture distance self.catalogue = selector.within_rupture_distance( self.geometry.surface, distance, upper_depth=upper_eq_depth, lower_depth=lower_eq_depth) else: # Use Joyner-Boore distance self.catalogue = selector.within_joyner_boore_distance( self.geometry.surface, distance, upper_depth=upper_eq_depth, lower_depth=lower_eq_depth)
def _generate_branching_index(self): ''' Generates a branching index (i.e. a list indicating the number of branches in each branching level. Current branching levels are: 1) Slip 2) MSR 3) Shear Modulus 4) DLR 5) MSR_Sigma 6) Config :returns: * branch_index - A 2-D numpy.ndarray where each row is a pointer to a particular combination of values * number_branches - Total number of branches (int) ''' branch_count = np.array([len(self.slip), len(self.msr), len(self.shear_modulus), len(self.disp_length_ratio), len(self.msr_sigma), len(self.config)]) n_levels = len(branch_count) number_branches = branch_index = np.zeros([number_branches, n_levels], dtype=int) cumval = 1 dstep = 1E-9 for iloc in range(0, n_levels): idx = np.linspace(0., float(branch_count[iloc]) - dstep, number_branches / cumval) branch_index[:, iloc] = np.reshape(np.tile(idx, [cumval, 1]), number_branches) cumval *= branch_count[iloc] return branch_index.tolist(), number_branches
[docs] def generate_config_set(self, config): ''' Generates a list of magnitude frequency distributions and renders as a tuple :param dict/list config: Configuration paramters of magnitude frequency distribution ''' if isinstance(config, dict): # Configuration list contains only one element self.config = [(config, 1.0)] elif isinstance(config, list): # Multiple configurations with correscponding weights total_weight = 0. self.config = [] for params in config: weight = params['Model_Weight'] total_weight += params['Model_Weight'] self.config.append((params, weight)) if fabs(total_weight - 1.0) > 1E-7: raise ValueError('MFD config weights do not sum to 1.0 for ' 'fault %s' % else: raise ValueError('MFD config must be input as dictionary or list!')
[docs] def generate_recurrence_models( self, collapse=False, bin_width=0.1, config=None, rendered_msr=None): ''' Iterates over the lists of values defining epistemic uncertainty in the parameters and calculates the corresponding recurrence model At present epistemic uncertainty is supported for: 1) slip rate, 2) magnitude scaling relation, 3) shear modulus, 4) displacement to length ratio) and 5) recurrence model. :param list config: List of MFD model configurations :param bool collapse: Boolean flag indicating whether to collapse the logic tree branches :param float bin_width: If collapsing the logic tree branches the reference mfd must be defined. The minimum and maximum magnitudes are updated from the model, but the bin width must be specified here :param list/dict config: Configuration (or sets of configurations) of the recurrence calculations :param rendered_msr: If collapsing the logic tree branches a resulting magnitude scaling relation must be defined as instance of :class: openquake.hazardlib.scalerel.base.BaseASR ''' if collapse and not rendered_msr: raise ValueError('Collapsing logic tree branches requires input ' 'of a single msr for rendering sources') # Generate a set of tuples with corresponding weights if config is not None: self.generate_config_set(config) if not isinstance(self.config, list): raise ValueError('MFD configuration missing or incorrectly ' 'formatted') # Generate the branching index branch_index, _number_branches = self._generate_branching_index() mmin = np.inf mmax = -np.inf for idx in branch_index: tuple_list = [] # Get slip tuple_list.append(self.slip[idx[0]]) # Get msr tuple_list.append(self.msr[idx[1]]) # Get shear modulus tuple_list.append(self.shear_modulus[idx[2]]) # Get displacement length ratio tuple_list.append(self.disp_length_ratio[idx[3]]) # Get msr sigma tuple_list.append(self.msr_sigma[idx[4]]) # Get config tuple_list.append(self.config[idx[5]]) # Calculate branch weight as product of tuple weights branch_weight =[val[1] for val in tuple_list])) # Instantiate recurrence model model = RecurrenceBranch(self.area, tuple_list[0][0], tuple_list[1][0], self.rake, tuple_list[2][0], tuple_list[3][0], tuple_list[4][0], weight=branch_weight) model.get_recurrence(tuple_list[5][0]) self.mfd_models.append(model) # Update the total minimum and maximum magnitudes for the fault if model.recurrence.min_mag < mmin: mmin = model.recurrence.min_mag if np.max(model.magnitudes) > mmax: mmax = np.max(model.magnitudes) if collapse: self.mfd = ([self.collapse_branches(mmin, bin_width, mmax)], [1.0], [rendered_msr]) else: mfd_mods = [] mfd_wgts = [] mfd_msr = [] for model in self.mfd_models: mfd_mods.append(IncrementalMFD(model.recurrence.min_mag, model.recurrence.bin_width, model.recurrence.occur_rates)) mfd_wgts.append(model.weight) mfd_msr.append(model.msr) self.mfd = (mfd_mods, mfd_wgts, mfd_msr)
[docs] def collapse_branches(self, mmin, bin_width, mmax): ''' Collapse the logic tree branches into a single IncrementalMFD :param float mmin: Minimum magnitude of reference mfd :param float bin_width: Bin width of reference mfd :param float mmax: Maximum magnitude of reference mfd :returns: :class: openquake.hmtk.models.IncrementalMFD ''' master_mags = np.arange(mmin, mmax + (bin_width / 2.), bin_width) master_rates = np.zeros(len(master_mags), dtype=float) for model in self.mfd_models: id0 = np.logical_and( master_mags >= np.min(model.magnitudes) - 1E-9, master_mags <= np.max(model.magnitudes) + 1E-9) # Use interpolation in log10-y values yvals = np.log10(model.recurrence.occur_rates) interp_y = np.interp(master_mags[id0], model.magnitudes, yvals) master_rates[id0] = master_rates[id0] + (model.weight * 10. ** interp_y) return IncrementalMFD(mmin, bin_width, master_rates)
[docs] def generate_fault_source_model(self): ''' Creates a resulting `openquake.hmtk` fault source set. :returns: source_model - list of instances of either the :class: `openquake.hmtk.sources.simple_fault_source.mtkSimpleFaultSource` or :class: `openquake.hmtk.sources.complex_fault_source.mtkComplexFaultSource` model_weight - Corresponding weights for each source model ''' source_model = [] model_weight = [] for iloc in range(0, self.get_number_mfd_models()): model_mfd = EvenlyDiscretizedMFD( self.mfd[0][iloc].min_mag, self.mfd[0][iloc].bin_width, self.mfd[0][iloc].occur_rates.tolist()) if isinstance(self.geometry, ComplexFaultGeometry): # Complex fault class source = mtkComplexFaultSource(,, self.trt, self.geometry.surface, self.mfd[2][iloc], self.rupt_aspect_ratio, model_mfd, self.rake) source.fault_edges = self.geometry.trace else: # Simple Fault source source = mtkSimpleFaultSource(,, self.trt, self.geometry.surface, self.geometry.dip, self.geometry.upper_depth, self.geometry.lower_depth, self.mfd[2][iloc], self.rupt_aspect_ratio, model_mfd, self.rake) source.fault_trace = self.geometry.trace source_model.append(source) model_weight.append(self.mfd[1][iloc]) return source_model, model_weight
[docs] def get_number_mfd_models(self): ''' Returns the number of mfd models for a given fault model ''' return len(self.mfd[0])