Source code for openquake.calculators.ucerf_event_based

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2015-2017 GEM Foundation
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <>.

import os
import copy
import time
import math
import os.path
import logging
import collections
import h5py
import numpy

from openquake.baselib.general import AccumDict
from openquake.baselib.python3compat import zip
from openquake.baselib import parallel
from openquake.hazardlib import nrml
from openquake.risklib import riskinput
from openquake.commonlib import readinput, source, calc, util
from openquake.calculators import base, event_based
from openquake.calculators.event_based_risk import (
    EbriskCalculator, event_based_risk)

from openquake.hazardlib.geo.surface.multi import MultiSurface
from openquake.hazardlib.pmf import PMF
from openquake.hazardlib.geo.point import Point
from openquake.hazardlib.geo.geodetic import min_idx_dst, min_geodetic_distance
from openquake.hazardlib.geo.surface.planar import PlanarSurface
from openquake.hazardlib.geo.nodalplane import NodalPlane
from openquake.hazardlib.tom import PoissonTOM
from openquake.hazardlib.source.rupture import ParametricProbabilisticRupture
from openquake.hazardlib.source.characteristic import CharacteristicFaultSource
from openquake.hazardlib.source.point import PointSource
from openquake.hazardlib.scalerel.wc1994 import WC1994
from openquake.hazardlib.calc.filters import SourceFilter, FarAwayRupture
from openquake.hazardlib.mfd import EvenlyDiscretizedMFD
from openquake.hazardlib.sourceconverter import SourceConverter

# ######################## rupture calculator ############################ #

U16 = numpy.uint16
U32 = numpy.uint32
U64 = numpy.uint64
F32 = numpy.float32

DEFAULT_TRT = "Active Shallow Crust"
HDD = PMF([(0.2, 3.0), (0.6, 6.0), (0.2, 9.0)])
NPD = PMF([(0.15, NodalPlane(0.0, 90.0, 0.0)),
           (0.15, NodalPlane(45.0, 90.0, 0.0)),
           (0.15, NodalPlane(90.0, 90.0, 0.0)),
           (0.15, NodalPlane(135.0, 90.0, 0.0)),
           (0.05, NodalPlane(0.0, 45.0, 90.)),
           (0.05, NodalPlane(45.0, 45.0, 90.)),
           (0.05, NodalPlane(90.0, 45.0, 90.)),
           (0.05, NodalPlane(135.0, 45.0, 90.)),
           (0.05, NodalPlane(180.0, 45.0, 90.)),
           (0.05, NodalPlane(225.0, 45.0, 90.)),
           (0.05, NodalPlane(270.0, 45.0, 90.)),
           (0.05, NodalPlane(325.0, 45.0, 90.))])

[docs]class ImperfectPlanarSurface(PlanarSurface): """ The planar surface class sets a narrow tolerance for the rectangular plane to be distorted in cartesian space. Ruptures with aspect ratios << 1.0, and with a dip of less than 90 degrees, cannot be generated in a manner that is consistent with the definitions - and thus cannot be instantiated. This subclass modifies the original planar surface class such that the tolerance checks are over-ridden. We find that distance errors with respect to a simple fault surface with a mesh spacing of 0.001 km are only on the order of < 0.15 % for Rrup (< 2 % for Rjb, < 3.0E-5 % for Rx) """ IMPERFECT_RECTANGLE_TOLERANCE = numpy.inf
[docs]def get_rupture_dimensions(mag, nodal_plane, msr, rupture_aspect_ratio, upper_seismogenic_depth, lower_seismogenic_depth): """ Calculate and return the rupture length and width for given magnitude ``mag`` and nodal plane. :param nodal_plane: Instance of :class:`openquake.hazardlib.geo.nodalplane.NodalPlane`. :returns: Tuple of two items: rupture length in width in km. The rupture area is calculated using method :meth:`~openquake.hazardlib.scalerel.base.BaseMSR.get_median_area` of source's magnitude-scaling relationship. In any case the returned dimensions multiplication is equal to that value. Than the area is decomposed to length and width with respect to source's rupture aspect ratio. If calculated rupture width being inclined by nodal plane's dip angle would not fit in between upper and lower seismogenic depth, the rupture width is shrunken to a maximum possible and rupture length is extended to preserve the same area. """ area = msr.get_median_area(mag, nodal_plane.rake) rup_length = math.sqrt(area * rupture_aspect_ratio) rup_width = area / rup_length seismogenic_layer_width = (lower_seismogenic_depth - upper_seismogenic_depth) max_width = (seismogenic_layer_width / math.sin(math.radians(nodal_plane.dip))) if rup_width > max_width: rup_width = max_width rup_length = area / rup_width return rup_length, rup_width
[docs]def get_rupture_surface(mag, nodal_plane, hypocenter, msr, rupture_aspect_ratio, upper_seismogenic_depth, lower_seismogenic_depth, mesh_spacing=1.0): """ Create and return rupture surface object with given properties. :param mag: Magnitude value, used to calculate rupture dimensions, see :meth:`_get_rupture_dimensions`. :param nodal_plane: Instance of :class:`openquake.hazardlib.geo.nodalplane.NodalPlane` describing the rupture orientation. :param hypocenter: Point representing rupture's hypocenter. :returns: Instance of :class:`~openquake.hazardlib.geo.surface.planar.PlanarSurface`. """ assert (upper_seismogenic_depth <= hypocenter.depth and lower_seismogenic_depth >= hypocenter.depth) rdip = math.radians(nodal_plane.dip) # precalculated azimuth values for horizontal-only and vertical-only # moves from one point to another on the plane defined by strike # and dip: azimuth_right = nodal_plane.strike azimuth_down = (azimuth_right + 90) % 360 azimuth_left = (azimuth_down + 90) % 360 azimuth_up = (azimuth_left + 90) % 360 rup_length, rup_width = get_rupture_dimensions( mag, nodal_plane, msr, rupture_aspect_ratio, upper_seismogenic_depth, lower_seismogenic_depth) # calculate the height of the rupture being projected # on the vertical plane: rup_proj_height = rup_width * math.sin(rdip) # and it's width being projected on the horizontal one: rup_proj_width = rup_width * math.cos(rdip) # half height of the vertical component of rupture width # is the vertical distance between the rupture geometrical # center and it's upper and lower borders: hheight = rup_proj_height / 2 # calculate how much shallower the upper border of the rupture # is than the upper seismogenic depth: vshift = upper_seismogenic_depth - hypocenter.depth + hheight # if it is shallower (vshift > 0) than we need to move the rupture # by that value vertically. if vshift < 0: # the top edge is below upper seismogenic depth. now we need # to check that we do not cross the lower border. vshift = lower_seismogenic_depth - hypocenter.depth - hheight if vshift > 0: # the bottom edge of the rupture is above the lower sesmogenic # depth. that means that we don't need to move the rupture # as it fits inside seismogenic layer. vshift = 0 # if vshift < 0 than we need to move the rupture up by that value. # now we need to find the position of rupture's geometrical center. # in any case the hypocenter point must lie on the surface, however # the rupture center might be off (below or above) along the dip. rupture_center = hypocenter if vshift != 0: # we need to move the rupture center to make the rupture fit # inside the seismogenic layer. hshift = abs(vshift / math.tan(rdip)) rupture_center = rupture_center.point_at( horizontal_distance=hshift, vertical_increment=vshift, azimuth=(azimuth_up if vshift < 0 else azimuth_down) ) # from the rupture center we can now compute the coordinates of the # four coorners by moving along the diagonals of the plane. This seems # to be better then moving along the perimeter, because in this case # errors are accumulated that induce distorsions in the shape with # consequent raise of exceptions when creating PlanarSurface objects # theta is the angle between the diagonal of the surface projection # and the line passing through the rupture center and parallel to the # top and bottom edges. Theta is zero for vertical ruptures (because # rup_proj_width is zero) theta = math.degrees( math.atan((rup_proj_width / 2.) / (rup_length / 2.)) ) hor_dist = math.sqrt( (rup_length / 2.) ** 2 + (rup_proj_width / 2.) ** 2 ) left_top = rupture_center.point_at( horizontal_distance=hor_dist, vertical_increment=-rup_proj_height / 2, azimuth=(nodal_plane.strike + 180 + theta) % 360 ) right_top = rupture_center.point_at( horizontal_distance=hor_dist, vertical_increment=-rup_proj_height / 2, azimuth=(nodal_plane.strike - theta) % 360 ) left_bottom = rupture_center.point_at( horizontal_distance=hor_dist, vertical_increment=rup_proj_height / 2, azimuth=(nodal_plane.strike + 180 - theta) % 360 ) right_bottom = rupture_center.point_at( horizontal_distance=hor_dist, vertical_increment=rup_proj_height / 2, azimuth=(nodal_plane.strike + theta) % 360 ) return PlanarSurface(mesh_spacing, nodal_plane.strike, nodal_plane.dip, left_top, right_top, right_bottom, left_bottom)
[docs]def generate_background_ruptures(tom, locations, occurrence, mag, npd, hdd, upper_seismogenic_depth, lower_seismogenic_depth, msr=WC1994(), aspect=1.5, trt=DEFAULT_TRT): """ :param tom: Temporal occurrence model as instance of :class: openquake.hazardlib.tom.TOM :param numpy.ndarray locations: Array of locations [Longitude, Latitude] of the point sources :param numpy.ndarray occurrence: Annual rates of occurrence :param float mag: Magnitude :param npd: Nodal plane distribution as instance of :class: openquake.hazardlib.pmf.PMF :param hdd: Hypocentral depth distribution as instance of :class: openquake.hazardlib.pmf.PMF :param float upper_seismogenic_depth: Upper seismogenic depth (km) :param float lower_seismogenic_depth: Lower seismogenic depth (km) :param msr: Magnitude scaling relation :param float aspect: Aspect ratio :param str trt: Tectonic region type :returns: List of ruptures """ ruptures = [] n_vals = len(locations) depths = hdd.sample_pairs(n_vals) nodal_planes = npd.sample_pairs(n_vals) for i, (x, y) in enumerate(locations): hypocentre = Point(x, y, depths[i][1]) surface = get_rupture_surface(mag, nodal_planes[i][1], hypocentre, msr, aspect, upper_seismogenic_depth, lower_seismogenic_depth) rupture_probability = (occurrence[i] * nodal_planes[i][0] * depths[i][0]) ruptures.append(ParametricProbabilisticRupture( mag, nodal_planes[i][1].rake, trt, hypocentre, surface, PointSource, rupture_probability, tom)) return ruptures
[docs]def sample_background_model( hdf5, branch_key, tom, seed, filter_idx, min_mag, npd, hdd, upper_seismogenic_depth, lower_seismogenic_depth, msr=WC1994(), aspect=1.5, trt=DEFAULT_TRT): """ Generates a rupture set from a sample of the background model :param branch_key: Key to indicate the branch for selecting the background model :param tom: Temporal occurrence model as instance of :class: openquake.hazardlib.tom.TOM :param seed: Random seed to use in the call to tom.sample_number_of_occurrences :param filter_idx: Sites for consideration (can be None!) :param float min_mag: Minimim magnitude for consideration of background sources :param npd: Nodal plane distribution as instance of :class: openquake.hazardlib.pmf.PMF :param hdd: Hypocentral depth distribution as instance of :class: openquake.hazardlib.pmf.PMF :param float aspect: Aspect ratio :param float upper_seismogenic_depth: Upper seismogenic depth (km) :param float lower_seismogenic_depth: Lower seismogenic depth (km) :param msr: Magnitude scaling relation :param float integration_distance: Maximum distance from rupture to site for consideration """ bg_magnitudes = hdf5["/".join(["Grid", branch_key, "Magnitude"])].value # Select magnitudes above the minimum magnitudes mag_idx = bg_magnitudes >= min_mag mags = bg_magnitudes[mag_idx] rates = hdf5["/".join(["Grid", branch_key, "RateArray"])][filter_idx, :] rates = rates[:, mag_idx] valid_locs = hdf5["Grid/Locations"][filter_idx, :] # Sample remaining rates sampler = tom.sample_number_of_occurrences(rates, seed) background_ruptures = [] background_n_occ = [] for i, mag in enumerate(mags): rate_idx = numpy.where(sampler[:, i])[0] rate_cnt = sampler[rate_idx, i] occurrence = rates[rate_idx, i] locations = valid_locs[rate_idx, :] ruptures = generate_background_ruptures( tom, locations, occurrence, mag, npd, hdd, upper_seismogenic_depth, lower_seismogenic_depth, msr, aspect, trt) background_ruptures.extend(ruptures) background_n_occ.extend(rate_cnt.tolist()) return background_ruptures, background_n_occ
[docs]class UCERFControl(object): """ :param source_file: Path to an existing HDF5 file containing the UCERF model :param str id: Valid branch of UCERF :param float investigation_time: Investigation time of event set (years) :param start_date: Starting date of the investigation (None for time independent) :param float min_mag: Minimim magnitude for consideration of background sources :param npd: Nodal plane distribution as instance of :class: openquake.hazardlib.pmf.PMF :param hdd: Hypocentral depth distribution as instance of :class: openquake.hazardlib.pmf.PMF :param float aspect: Aspect ratio :param float upper_seismoge nic_depth: Upper seismogenic depth (km) :param float lower_seismogenic_depth: Lower seismogenic depth (km) :param msr: Magnitude scaling relation :param float mesh_spacing: Spacing (km) of fault mesh :param str trt: Tectonic region type :param float integration_distance: Maximum distance from rupture to site for consideration """ def __init__( self, source_file, id, investigation_time, start_date, min_mag, npd=NPD, hdd=HDD, aspect=1.5, upper_seismogenic_depth=0.0, lower_seismogenic_depth=15.0, msr=WC1994(), mesh_spacing=1.0, trt="Active Shallow Crust", integration_distance=1000): assert os.path.exists(source_file), source_file self.source_file = source_file self.source_id = id self.inv_time = investigation_time self.start_date = start_date self.tom = self._get_tom() self.min_mag = min_mag self.npd = npd self.hdd = hdd self.aspect = aspect self.usd = upper_seismogenic_depth self.lsd = lower_seismogenic_depth self.msr = msr self.mesh_spacing = mesh_spacing self.tectonic_region_type = trt
[docs] def get_min_max_mag(self): """ Called when updating the SourceGroup """ return self.min_mag, None
def _get_tom(self): """ Returns the temporal occurence model as a Poisson TOM """ return PoissonTOM(self.inv_time)
[docs]class UcerfSource(object): """ Source-like class for use in UCERF calculations. It is build on top of an UCERFControl object which wraps the input file in HDF5 format. Each source has attributes `.source_id` (the name of the branch), `.src_group_id` (the number of the group i.e. of the source model), `.num_ruptures` (the number of ruptures in that branch) and `.idx_set`, a dictionary of HDF5 keys determined by the `branch_id` string. :param control: a :class:`UCERFControl` instance :param grp_id: ordinal of the source group :param branch_name: name of the UCERF branch :param branch_id: string associated to the branch """ tectonic_region_type = DEFAULT_TRT def __init__(self, control, grp_id, branch_name, branch_id): self.control = control self.src_group_id = grp_id self.source_id = branch_id self.idx_set = build_idx_set(branch_id, control.start_date) with h5py.File(self.control.source_file, "r") as hdf5: self.num_ruptures = len(hdf5[self.idx_set["rate_idx"]]) @property def weight(self): """ Weight of the source, equal to the number of ruptures contained """ return self.num_ruptures
[docs] def get_rupture_sites(self, hdf5, ridx, src_filter, mag): """ Determines if a rupture is likely to be inside the integration distance by considering the set of fault plane centroids and returns the affected sites if any. :param hdf5: Source of UCERF file as h5py.File object :param ridx: List of indices composing the rupture sections :param src_filter: SourceFilter instance :param mag: Magnitude of the rupture for consideration :returns: The sites affected by the rupture (or None) """ centroids = [] for idx in ridx: trace_idx = "{:s}/{:s}".format(self.idx_set["sec_idx"], str(idx)) centroids.append(hdf5[trace_idx + "/Centroids"].value) centroids = numpy.concatenate(centroids) lons, lats = src_filter.sitecol.lons, src_filter.sitecol.lats distance = min_geodetic_distance( centroids[:, 0], centroids[:, 1], lons, lats) idist = src_filter.integration_distance(DEFAULT_TRT, mag) return src_filter.sitecol.filter(distance <= idist)
[docs] def get_background_sids(self, src_filter): """ We can apply the filtering of the background sites as a pre-processing step - this is done here rather than in the sampling of the ruptures themselves """ ctl = self.control branch_key = self.idx_set["grid_key"] idist = src_filter.integration_distance(DEFAULT_TRT) lons, lats = src_filter.sitecol.lons, src_filter.sitecol.lats with h5py.File(ctl.source_file, 'r') as hdf5: bg_locations = hdf5["Grid/Locations"].value n_locations = bg_locations.shape[0] distances = min_idx_dst(lons, lats, numpy.zeros_like(lons), bg_locations[:, 0], bg_locations[:, 1], numpy.zeros(n_locations))[1] # Add buffer equal to half of length of median area from Mmax mmax_areas = ctl.msr.get_median_area( hdf5["/".join(["Grid", branch_key, "MMax"])].value, 0.0) # for instance hdf5['Grid/FM0_0_MEANFS_MEANMSR/MMax'] mmax_lengths = numpy.sqrt(mmax_areas / ctl.aspect) ok = distances <= (0.5 * mmax_lengths + idist) # get list of indices from array of booleans return numpy.where(ok)[0].tolist()
[docs] def get_ucerf_rupture(self, hdf5, iloc, src_filter): """ :param hdf5: Source Model hdf5 object as instance of :class: h5py.File :param int iloc: Location of the rupture plane in the hdf5 file :param src_filter: Sites for consideration and maximum distance """ ctl = self.control mesh_spacing = ctl.mesh_spacing trt = ctl.tectonic_region_type ridx = hdf5[self.idx_set["geol_idx"] + "/RuptureIndex"][iloc] mag = hdf5[self.idx_set["mag_idx"]][iloc] surface_set = [] r_sites = self.get_rupture_sites(hdf5, ridx, src_filter, mag) if r_sites is None: return None, None for idx in ridx: # Build simple fault surface trace_idx = "{:s}/{:s}".format(self.idx_set["sec_idx"], str(idx)) rup_plane = hdf5[trace_idx + "/RupturePlanes"][:].astype("float64") for jloc in range(0, rup_plane.shape[2]): top_left = Point(rup_plane[0, 0, jloc], rup_plane[0, 1, jloc], rup_plane[0, 2, jloc]) top_right = Point(rup_plane[1, 0, jloc], rup_plane[1, 1, jloc], rup_plane[1, 2, jloc]) bottom_right = Point(rup_plane[2, 0, jloc], rup_plane[2, 1, jloc], rup_plane[2, 2, jloc]) bottom_left = Point(rup_plane[3, 0, jloc], rup_plane[3, 1, jloc], rup_plane[3, 2, jloc]) try: surface_set.append( ImperfectPlanarSurface.from_corner_points( mesh_spacing, top_left, top_right, bottom_right, bottom_left)) except ValueError as evl: raise ValueError(evl, trace_idx, top_left, top_right, bottom_right, bottom_left) rupture = ParametricProbabilisticRupture( mag, hdf5[self.idx_set["rake_idx"]][iloc], trt, surface_set[len(surface_set) // 2].get_middle_point(), MultiSurface(surface_set), CharacteristicFaultSource, hdf5[self.idx_set["rate_idx"]][iloc], ctl.tom) # Get rupture index code string ridx_string = "-".join(str(val) for val in ridx) return rupture, ridx_string
[docs] def generate_event_set(self, background_sids, src_filter, seed): """ Generates the event set corresponding to a particular branch """ # get rates from file ctl = self.control with h5py.File(ctl.source_file, 'r') as hdf5: rates = hdf5[self.idx_set["rate_idx"]].value occurrences = ctl.tom.sample_number_of_occurrences(rates, seed) indices = numpy.where(occurrences)[0] logging.debug( 'Considering "%s", %d ruptures', self.source_id, len(indices)) # get ruptures from the indices ruptures = [] rupture_occ = [] for idx, n_occ in zip(indices, occurrences[indices]): ucerf_rup, _ = self.get_ucerf_rupture(hdf5, idx, src_filter) if ucerf_rup: ruptures.append(ucerf_rup) rupture_occ.append(n_occ) # sample background sources background_ruptures, background_n_occ = sample_background_model( hdf5, self.idx_set["grid_key"], ctl.tom, seed, background_sids, ctl.min_mag, ctl.npd, ctl.hdd, ctl.usd, ctl.lsd, ctl.msr, ctl.aspect, ctl.tectonic_region_type) ruptures.extend(background_ruptures) rupture_occ.extend(background_n_occ) return ruptures, rupture_occ
[docs] def iter_ruptures(self): """ Yield ruptures for the current set of indices (.rupset_idx) """ ctl = self.control with h5py.File(ctl.source_file, "r") as hdf5: try: # the source has set a subset of indices rupset_idx = self.rupset_idx except AttributeError: # use all indices rupset_idx = numpy.arange(self.num_ruptures) rate = hdf5[self.idx_set["rate_idx"]] for ridx in rupset_idx: # Get the ucerf rupture rate from the MeanRates array if not rate[ridx]: # ruptures may have have zero rate continue rup, ridx_string = self.get_ucerf_rupture( hdf5, ridx, self.src_filter) if rup: yield rup
[docs] def get_background_sources(self, src_filter): """ Turn the background model of a given branch into a set of point sources :param src_filter: SourceFilter instance """ ctl = self.control background_sids = self.get_background_sids(src_filter) with h5py.File(ctl.source_file, "r") as hdf5: grid_loc = "/".join(["Grid", self.idx_set["grid_key"]]) mags = hdf5[grid_loc + "/Magnitude"].value mmax = hdf5[grid_loc + "/MMax"][background_sids] rates = hdf5[grid_loc + "/RateArray"][background_sids, :] locations = hdf5["Grid/Locations"][background_sids, :] sources = [] for i, bg_idx in enumerate(background_sids): src_id = "_".join([self.idx_set["grid_key"], str(bg_idx)]) src_name = "|".join([self.idx_set["total_key"], str(bg_idx)]) # Get MFD mag_idx = numpy.logical_and( mags >= ctl.min_mag, mags < mmax[i]) src_mags = mags[mag_idx] src_rates = rates[i, :] src_mfd = EvenlyDiscretizedMFD( src_mags[0], src_mags[1] - src_mags[0], src_rates[mag_idx].tolist()) ps = PointSource( src_id, src_name, ctl.tectonic_region_type, src_mfd, ctl.mesh_spacing, ctl.msr, ctl.aspect, ctl.tom, ctl.usd, ctl.lsd, Point(locations[i, 0], locations[i, 1]), ctl.npd, ctl.hdd) sources.append(ps) return sources
[docs]def build_idx_set(branch_id, start_date): """ Builds a dictionary of indices based on the branch code """ code_set = branch_id.split("/") idx_set = { "sec_idx": "/".join([code_set[0], code_set[1], "Sections"]), "mag_idx": "/".join([code_set[0], code_set[1], code_set[2], "Magnitude"])} code_set.insert(3, "Rates") idx_set["rate_idx"] = "/".join(code_set) idx_set["rake_idx"] = "/".join([code_set[0], code_set[1], "Rake"]) idx_set["msr_idx"] = "-".join([code_set[0], code_set[1], code_set[2]]) idx_set["geol_idx"] = code_set[0] if start_date: # time-dependent source idx_set["grid_key"] = "_".join( branch_id.replace("/", "_").split("_")[:-1]) else: # time-independent source idx_set["grid_key"] = branch_id.replace("/", "_") idx_set["total_key"] = branch_id.replace("/", "|") return idx_set
# #################################################################### # @util.reader
[docs]def compute_ruptures(sources, src_filter, gsims, param, monitor): """ :param sources: a list with a single UCERF source :param src_filter: a SourceFilter instance :param gsims: a list of GSIMs :param param: extra parameters :param monitor: a Monitor instance :returns: an AccumDict grp_id -> EBRuptures """ [src] = sources res = AccumDict() res.calc_times = AccumDict() serial = 1 sampl_mon = monitor('sampling ruptures', measuremem=True) filt_mon = monitor('filtering ruptures', measuremem=False) res.trt = DEFAULT_TRT t0 = time.time() ebruptures = [] background_sids = src.get_background_sids(src_filter) sitecol = src_filter.sitecol idist = src_filter.integration_distance for sample in range(param['samples']): for ses_idx, ses_seed in param['ses_seeds']: seed = sample * event_based.TWO16 + ses_seed with sampl_mon: rups, n_occs = src.generate_event_set( background_sids, src_filter, seed) with filt_mon: for rup, n_occ in zip(rups, n_occs): rup.seed = seed try: r_sites, rrup = idist.get_closest(sitecol, rup) except FarAwayRupture: continue indices = r_sites.indices events = [] for _ in range(n_occ): events.append((0, ses_idx, sample)) if events: evs = numpy.array(events, calc.event_dt) ebruptures.append( calc.EBRupture(rup, indices, evs, src.src_group_id, serial)) serial += 1 res.num_events = event_based.set_eids( ebruptures, getattr(monitor, 'task_no', 0)) res[src.src_group_id] = ebruptures res.calc_times[src.src_group_id] = ( src.source_id, len(sitecol), time.time() - t0) if not param['save_ruptures']: res.events_by_grp = {grp_id: event_based.get_events(res[grp_id]) for grp_id in res} res.eff_ruptures = {src.src_group_id: src.num_ruptures} return res
[docs]def get_composite_source_model(oq): """ :param oq: :class:`openquake.commonlib.oqvalidation.OqParam` instance :returns: a `class:`openquake.commonlib.source.CompositeSourceModel` """ gsim_lt = readinput.get_gsim_lt(oq, [DEFAULT_TRT]) smlt = readinput.get_source_model_lt(oq) [src_group] = nrml.parse( oq.inputs["source_model"], SourceConverter(oq.investigation_time, oq.rupture_mesh_spacing)) [src] = src_group source_models = [] for sm in smlt.gen_source_models(gsim_lt): sg = copy.copy(src_group) = sm.ordinal sm.src_groups = [sg] sg.sources = [UcerfSource(sg[0], sm.ordinal, sm.path[0],] source_models.append(sm) return source.CompositeSourceModel(gsim_lt, smlt, source_models)
[docs]class UCERFRuptureCalculator(event_based.EventBasedRuptureCalculator): """ Event based PSHA calculator generating the ruptures only """ core_task = compute_ruptures
[docs] def pre_execute(self): """ parse the logic tree and source model input """ logging.warn('%s is still experimental', self.__class__.__name__) oq = self.oqparam self.read_risk_data() # read the site collection self.src_filter = SourceFilter(self.sitecol, oq.maximum_distance) self.csm = get_composite_source_model(oq)'Found %d source model logic tree branches', len(self.csm.source_models)) self.datastore['csm_info'] = self.csm_info = self.rlzs_assoc = self.csm_info.get_rlzs_assoc() self.infos = [] self.eid = collections.Counter() # sm_id -> event_id self.sm_by_grp = self.csm_info.get_sm_by_grp() if not self.oqparam.imtls: raise ValueError('Missing intensity_measure_types!') self.rupser = calc.RuptureSerializer(self.datastore)
[docs] def gen_args(self, csm, monitor): """ Generate a task for each branch """ oq = self.oqparam allargs = [] # it is better to return a list; if there is single # branch then `parallel.Starmap` will run the task in core for sm_id in range(len(csm.source_models)): ssm = csm.get_model(sm_id) [sm] = ssm.source_models gsims = ssm.gsim_lt.values[DEFAULT_TRT] srcs = ssm.get_sources() for ses_idx in range(1, oq.ses_per_logic_tree_path + 1): ses_seeds = [(ses_idx, oq.ses_seed + ses_idx)] param = dict(ses_seeds=ses_seeds, samples=sm.samples, save_ruptures=oq.save_ruptures) allargs.append((srcs, self.src_filter, gsims, param, monitor)) return allargs
[docs]class List(list): """Trivial container returned by compute_losses"""
[docs]def compute_losses(ssm, src_filter, param, riskmodel, imts, trunc_level, correl_model, min_iml, monitor): """ Compute the losses for a single source model. Returns the ruptures as an attribute `.ruptures_by_grp` of the list of losses. :param ssm: CompositeSourceModel containing a single source model :param sitecol: a SiteCollection instance :param param: a dictionary of parameters :param riskmodel: a RiskModel instance :param imts: a list of Intensity Measure Types :param trunc_level: truncation level :param correl_model: correlation model :param min_iml: vector of minimum intensities, one per IMT :param monitor: a Monitor instance :returns: a List containing the losses by taxonomy and some attributes """ [grp] = ssm.src_groups res = List() gsims = ssm.gsim_lt.values[DEFAULT_TRT] ruptures_by_grp = compute_ruptures( grp, src_filter, gsims, param, monitor) [(grp_id, ebruptures)] = ruptures_by_grp.items() rlzs_assoc = num_rlzs = len(rlzs_assoc.realizations) rlzs_by_gsim = rlzs_assoc.get_rlzs_by_gsim(grp_id) getter = riskinput.GmfGetter( grp_id, rlzs_by_gsim, ebruptures, src_filter.sitecol, imts, min_iml, trunc_level, correl_model, rlzs_assoc.samples[grp_id]) ri = riskinput.RiskInputFromRuptures(getter) res.append(event_based_risk(ri, riskmodel, param, monitor)) res.sm_id = ssm.sm_id res.num_events = len(ri.hazard_getter.eids) start = res.sm_id * num_rlzs res.rlz_slice = slice(start, start + num_rlzs) res.events_by_grp = ruptures_by_grp.events_by_grp return res
[docs]class UCERFHazardCalculator(event_based.EventBasedCalculator): """ Runs a standard event based calculation starting from UCERF ruptures """ pre_calculator = 'ucerf_rupture'
[docs]class UCERFRiskCalculator(EbriskCalculator): """ Event based risk calculator for UCERF, parallelizing on the source models """ pre_execute = UCERFRuptureCalculator.__dict__['pre_execute']
[docs] def gen_args(self): """ Yield the arguments required by build_ruptures, i.e. the source models, the asset collection, the riskmodel and others. """ oq = self.oqparam self.L = len(self.riskmodel.lti) self.I = oq.insured_losses + 1 correl_model = oq.get_correl_model() min_iml = self.get_min_iml(oq) imts = list(oq.imtls) elt_dt = numpy.dtype([('eid', U64), ('loss', (F32, (self.L, self.I)))]) monitor = self.monitor('compute_losses') for sm in self.csm.source_models: ssm = self.csm.get_model(sm.ordinal) for ses_idx in range(1, oq.ses_per_logic_tree_path + 1): param = dict(ses_seeds=[(ses_idx, oq.ses_seed + ses_idx)], samples=1, assetcol=self.assetcol, save_ruptures=False, ses_ratio=oq.ses_ratio, avg_losses=oq.avg_losses, loss_ratios=oq.loss_ratios, elt_dt=elt_dt, asset_loss_table=False, insured_losses=oq.insured_losses) yield (ssm, self.src_filter, param, self.riskmodel, imts, oq.truncation_level, correl_model, min_iml, monitor)
[docs] def execute(self): num_rlzs = len(self.rlzs_assoc.realizations) self.grp_trt = self.csm_info.grp_trt() res = parallel.Starmap(compute_losses, self.gen_args()).submit_all() self.vals = self.assetcol.values() num_events = self.save_results(res, num_rlzs) return num_events