# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2015-2016 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
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# 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 <http://www.gnu.org/licenses/>.
import os
import time
import os.path
import logging
import math
import random
import functools
import h5py
import numpy
from openquake.baselib.general import AccumDict
from openquake.baselib.python3compat import zip
from openquake.risklib import valid
from openquake.commonlib import readinput, parallel, datastore, source
from openquake.calculators import base, event_based
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_distance, 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.commonlib.calc import MAX_INT
from openquake.commonlib.sourceconverter import SourceConverter
# ######################## rupture calculator ############################ #
U16 = numpy.uint16
U32 = numpy.uint32
F32 = numpy.float32
# DEFAULT VALUES FOR UCERF BACKGROUND MODELS
DEFAULT_MESH_SPACING = 1.0
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]def prefilter_ruptures(hdf5, ridx, idx_set, sites, integration_distance):
"""
Determines if a rupture is likely to be inside the integration distance
by considering the set of fault plane centroids.
:param hdf5:
Source of UCERF file as h5py.File object
:param list ridx:
List of indices composing the rupture sections
:param dict idx_set:
Set of indices for the branch
:param sites:
Sites for consideration (can be None!)
:param float integration_distance:
Maximum distance from rupture to site for consideration
"""
# Generate array of sites
if not sites:
return True
centroids = numpy.array([[0., 0., 0.]], dtype="f")
for idx in ridx:
trace_idx = "{:s}/{:s}".format(idx_set["sec_idx"], str(idx))
centroids = numpy.vstack([
centroids,
hdf5[trace_idx + "/Centroids"][:].astype("float64")])
centroids = centroids[1:, :]
distance = min_geodetic_distance(centroids[:, 0], centroids[:, 1],
sites.lons, sites.lats)
return numpy.any(distance <= integration_distance)
[docs]def get_ucerf_rupture(hdf5, iloc, idx_set, tom, sites,
integration_distance, mesh_spacing=DEFAULT_MESH_SPACING,
trt=DEFAULT_TRT):
"""
: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 dict idx_set:
Set of indices for the branch
Generates a rupture set from a sample of the background model
:param tom:
Temporal occurrence model as instance of :class:
openquake.hazardlib.tom.TOM
:param sites:
Sites for consideration (can be None!)
"""
ridx = hdf5[idx_set["geol_idx"] + "/RuptureIndex"][iloc]
surface_set = []
if not prefilter_ruptures(
hdf5, ridx, idx_set, sites, integration_distance):
return None, None
for idx in ridx:
# Build simple fault surface
trace_idx = "{:s}/{:s}".format(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(PlanarSurface.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(
hdf5[idx_set["mag_idx"]][iloc], # Magnitude
hdf5[idx_set["rake_idx"]][iloc], # Rake
trt, # Tectonic Region Type
surface_set[len(surface_set)/2].get_middle_point(), # Hypocentre
MultiSurface(surface_set),
CharacteristicFaultSource,
hdf5[idx_set["rate_idx"]][iloc], # Rate of events
tom)
# Get rupture index code string
ridx_string = "-".join(str(val) for val in ridx)
return rupture, ridx_string
[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 prefilter_background_model(hdf5, sites, integration_distance, msr=WC1994(),
aspect=1.5):
"""
Identify those points within the integration distance
:param sites:
Sites for consideration (can be None!)
:param float integration_distance:
Maximum distance from rupture to site for consideration
:param msr:
Magnitude scaling relation
:param float aspect:
Aspect ratio
:returns:
Boolean vector indicating if sites are within (True) or outside (False)
the integration distance
"""
bg_locations = hdf5["Grid/Locations"][:].astype("float64")
n_locations = bg_locations.shape[0]
if not sites:
# Apply no filtering - all sources valid
return numpy.ones(n_locations, dtype=bool)
distances = min_distance(sites.lons, sites.lats,
numpy.zeros_like(sites.lons),
bg_locations[:, 0],
bg_locations[:, 1],
numpy.zeros(n_locations))
# Add buffer equal to half of length of median area from Mmax
mmax_areas = msr.get_median_area(hdf5["Grid/MMax"][:], 0.0)
mmax_lengths = numpy.sqrt(mmax_areas / aspect)
return distances <= (0.5 * mmax_lengths + integration_distance)
[docs]def sample_background_model(
hdf5, tom, 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 tom:
Temporal occurrence model as instance of :class:
openquake.hazardlib.tom.TOM
: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["Grid/Magnitudes"][:]
# Select magnitudes above the minimum magnitudes
mag_idx = bg_magnitudes >= min_mag
mags = bg_magnitudes[mag_idx]
# Filter out sites beyond integration distance
# valid_idx = prefilter_background_model(sites, integration_distance, msr)
rates = hdf5["Grid/RateArray"][filter_idx, :]
rates = rates[:, mag_idx]
valid_locs = hdf5["Grid/Locations"][filter_idx, :]
# Sample remaining rates
sampler = tom.sample_number_of_occurrences(rates)
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
# this is a fake source object built around the HDF5 UCERF file
# there is one object per branch, so there are 1,400 UCERFSESControls
# this approach cannot work on a cluster unless the HDF5 file is
# on a shared file system
[docs]class UCERFSESControl(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 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, 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)
self.source_file = source_file
self.source_id = id
self.inv_time = investigation_time
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
self.seed = random.randint(0, MAX_INT)
self.rnd = None
self.integration_distance = integration_distance
self.sites = None
self.background_idx = None
self.num_ruptures = 0
[docs] def update_background_site_filter(self, sites, integration_distance=1000.):
"""
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
"""
self.sites = sites
self.integration_distance = integration_distance
with h5py.File(self.source_file, 'r') as hdf5:
self.background_idx = prefilter_background_model(
hdf5, self.sites, integration_distance, self.msr, self.aspect)
[docs] def update_seed(self, seed):
"""
Updates the random seed associated with the source
"""
self.rnd = random.Random(seed)
def _get_tom(self):
"""
Returns the temporal occurence model as a Poisson TOM
"""
return PoissonTOM(self.inv_time)
def __len__(self):
return 1
[docs] def generate_event_set(self, branch_id, sites=None,
integration_distance=1000.):
"""
Generates the event set corresponding to a particular branch
"""
if sites:
self.update_background_site_filter(sites, integration_distance)
idxset = self.build_idx_set(branch_id)
# get rates from file
with h5py.File(self.source_file, 'r') as hdf5:
rates = hdf5[idxset["rate_idx"]][:]
occurrences = self.tom.sample_number_of_occurrences(rates)
indices = numpy.where(occurrences)[0]
logging.info('Considering %s %s', branch_id, indices)
# get ruptures from the indices
ruptures = []
rupture_occ = []
for idx, n_occ in zip(indices, occurrences[indices]):
ucerf_rup, _ = get_ucerf_rupture(
hdf5, idx, idxset, self.tom, self.sites,
self.integration_distance, self.mesh_spacing,
self.tectonic_region_type)
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.tom,
self.background_idx,
self.min_mag,
self.npd, self.hdd,
self.usd, self.lsd,
self.msr, self.aspect,
self.tectonic_region_type)
ruptures.extend(background_ruptures)
rupture_occ.extend(background_n_occ)
return ruptures, rupture_occ
@staticmethod
[docs] def build_idx_set(branch_code):
"""
Builds a dictionary of indices based on the branch code
:param str branch_code:
Code for the branch
"""
code_set = branch_code.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]
idx_set["total_key"] = branch_code.replace("/", "|")
return idx_set
# #################################################################### #
[docs]class UCERFSourceConverter(SourceConverter):
"""
Adjustment of the UCERF Source Converter to return the source information
as an instance of the UCERF SES Control object
"""
[docs] def convert_UCERFSource(self, node):
"""
Converts the Ucerf Source node into an SES Control object
"""
dirname = os.path.dirname(self.fname) # where the source_model_file is
source_file = os.path.join(dirname, node["filename"])
return UCERFSESControl(
source_file,
node["id"],
self.tom.time_span,
float(node["minMag"]),
npd=self.convert_npdist(node),
hdd=self.convert_hpdist(node),
aspect=~node.ruptAspectRatio,
upper_seismogenic_depth=~node.pointGeometry.upperSeismoDepth,
lower_seismogenic_depth=~node.pointGeometry.lowerSeismoDepth,
msr=valid.SCALEREL[~node.magScaleRel](),
mesh_spacing=self.rupture_mesh_spacing,
trt=node["tectonicRegion"])
@parallel.litetask
[docs]def compute_ruptures(branch_info, source, sitecol, oqparam, monitor):
"""
Returns the ruptures as a TRT set
:param str branch_info:
Tuple of (ltbr, branch_id, branch_weight)
:param source:
Instance of the UCERFSESControl object
:param sitecol:
Site collection :class: openquake.hazardlib.site.SiteCollection
:param info:
Instance of the :class: openquake.commonlib.source.CompositionInfo
:returns:
Dictionary of rupture instances associated to a TRT ID
"""
integration_distance = oqparam.maximum_distance[DEFAULT_TRT]
res = AccumDict()
res.calc_times = AccumDict()
serial = 1
filter_mon = monitor('update_background_site_filter', measuremem=False)
event_mon = monitor('sampling ruptures', measuremem=False)
for trt_model_id, (ltbrid, branch_id, _) in enumerate(branch_info):
t0 = time.time()
with filter_mon:
source.update_background_site_filter(sitecol, integration_distance)
# set the seed before calling generate_event_set
numpy.random.seed(oqparam.random_seed + trt_model_id)
ses_ruptures = []
for ses_idx in range(1, oqparam.ses_per_logic_tree_path + 1):
with event_mon:
rups, n_occs = source.generate_event_set(
branch_id, sitecol, integration_distance)
for i, rup in enumerate(rups):
rup.seed = oqparam.random_seed # to think
rrup = rup.surface.get_min_distance(sitecol.mesh)
r_sites = sitecol.filter(rrup <= integration_distance)
if r_sites is None:
continue
indices = r_sites.indices
events = []
for j in range(n_occs[i]):
# NB: the first 0 is a placeholder for the eid that will be
# set later, in EventBasedRuptureCalculator.post_execute;
# the second 0 is the sampling ID
events.append((0, ses_idx, j, 0))
if len(events):
ses_ruptures.append(
event_based.EBRupture(
rup, indices,
numpy.array(events, event_based.event_dt),
source.source_id, trt_model_id, serial))
serial += 1
dt = time.time() - t0
res.calc_times[trt_model_id] = (ltbrid, dt)
res[trt_model_id] = ses_ruptures
res.trt = DEFAULT_TRT
return res
@base.calculators.add('ucerf_event_based_rupture')
[docs]class UCERFEventBasedRuptureCalculator(
event_based.EventBasedRuptureCalculator):
"""
Event based PSHA calculator generating the ruptures only
"""
core_task = compute_ruptures
etags = datastore.persistent_attribute('etags')
is_stochastic = True
[docs] def pre_execute(self):
"""
parse the logic tree and source model input
"""
self.sitecol = readinput.get_site_collection(self.oqparam)
self.gsim_lt = readinput.get_gsim_lt(self.oqparam, [DEFAULT_TRT])
self.smlt = readinput.get_source_model_lt(self.oqparam)
parser = source.SourceModelParser(
UCERFSourceConverter(self.oqparam.investigation_time,
self.oqparam.rupture_mesh_spacing))
[self.source] = parser.parse_sources(
self.oqparam.inputs["source_model"])
branches = sorted(self.smlt.branches.items())
min_mag, max_mag = self.source.min_mag, None
source_models = []
num_gsim_paths = self.gsim_lt.get_num_paths()
for ordinal, (name, branch) in enumerate(branches):
tm = source.TrtModel(DEFAULT_TRT, [], min_mag, max_mag,
ordinal, eff_ruptures=-1)
sm = source.SourceModel(
name, branch.weight, [name], [tm], num_gsim_paths, ordinal, 1)
source_models.append(sm)
self.csm = source.CompositeSourceModel(
self.gsim_lt, self.smlt, source_models, set_weight=False)
self.rup_data = {}
self.infos = []
[docs] def execute(self):
"""
Run the ucerf rupture calculation
"""
id_set = [(key, self.smlt.branches[key].value,
self.smlt.branches[key].weight)
for key in self.smlt.branches]
ruptures_by_trt_id = parallel.apply_reduce(
compute_ruptures,
(id_set, self.source, self.sitecol, self.oqparam, self.monitor),
concurrent_tasks=self.oqparam.concurrent_tasks, agg=self.agg)
self.rlzs_assoc = self.csm.info.get_rlzs_assoc(
functools.partial(self.count_eff_ruptures, ruptures_by_trt_id))
self.datastore['csm_info'] = self.csm.info
self.datastore['source_info'] = numpy.array(
self.infos, source.source_info_dt)
return ruptures_by_trt_id
[docs] def agg(self, acc, val):
"""
Aggregated the ruptures and the calculation times
"""
for trt_id in val:
ltbrid, dt = val.calc_times[trt_id]
info = source.SourceInfo(
trt_id, ltbrid,
source_class=UCERFSESControl.__class__.__name__,
weight=1, sources=1, filter_time=0, split_time=0, calc_time=dt)
self.infos.append(info)
return acc + val
@base.calculators.add('ucerf_event_based')
[docs]class UCERFEventBasedCalculator(event_based.EventBasedCalculator):
"""
Event based PSHA calculator generating the ground motion fields and
the hazard curves from the ruptures, depending on the configuration
parameters. Specialized for the UCERF model.
"""
pre_calculator = 'ucerf_event_based_rupture'