# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2012-2016 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/>.
"""
:mod:`openquake.hazardlib.calc.hazard_curve` implements
:func:`calc_hazard_curves`.
"""
import sys
import time
import operator
import numpy
from openquake.baselib.python3compat import raise_, zip
from openquake.baselib.performance import Monitor
from openquake.baselib.general import groupby, DictArray
from openquake.hazardlib.probability_map import ProbabilityMap
from openquake.hazardlib.calc import filters
from openquake.hazardlib.gsim.base import ContextMaker, FarAwayRupture
from openquake.hazardlib.imt import from_string
[docs]def zero_curves(num_sites, imtls):
"""
:param num_sites: the number of sites
:param imtls: the intensity measure levels dictionary
:returns: an array of zero curves with length num_sites
"""
# numpy dtype for the hazard curves
imt_dt = numpy.dtype([(imt, float, 1 if imls is None else len(imls))
for imt, imls in imtls.items()])
zero = numpy.zeros(num_sites, imt_dt)
return zero
[docs]def zero_maps(num_sites, imts, poes=()):
"""
:param num_sites: the number of sites
:param imts: the intensity measure types
:returns: an array of zero curves with length num_sites
"""
# numpy dtype for the hazard maps
if poes:
imt_dt = numpy.dtype([('%s-%s' % (imt, poe), numpy.float32)
for imt in imts for poe in poes])
else:
imt_dt = numpy.dtype([(imt, numpy.float32) for imt in imts])
return numpy.zeros(num_sites, imt_dt)
[docs]def agg_curves(acc, curves):
"""
Aggregate hazard curves by composing the probabilities.
:param acc: an accumulator array
:param curves: an array of hazard curves
:returns: a new accumulator
"""
new = numpy.array(acc) # copy of the accumulator
for imt in curves.dtype.fields:
new[imt] = 1. - (1. - curves[imt]) * (1. - acc[imt])
return new
[docs]def array_of_curves(pmap, nsites, imtls, gsim_idx=0):
"""
Convert a probability map into an array of length `nsites`
and dtype `imt_dt`.
:param pmap: a dictionary sid -> ProbabilityCurve
:param nsites: the number of sites in the full site collection
:param imtls: intensity measure types and levels
:param gsims_idx: extract the data corresponding to a specific GSIM
"""
curves = numpy.zeros(nsites, imtls.imt_dt)
for sid in pmap:
array = pmap[sid].array[:, gsim_idx]
for imt in imtls:
curves[imt][sid] = array[imtls.slicedic[imt]]
# NB: curves[sid][imt] does not work on h5py 2.2
return curves
[docs]def calc_hazard_curves(
sources, sites, imtls, gsim_by_trt, truncation_level=None,
source_site_filter=filters.source_site_noop_filter,
maximum_distance=None):
"""
Compute hazard curves on a list of sites, given a set of seismic sources
and a set of ground shaking intensity models (one per tectonic region type
considered in the seismic sources).
Probability of ground motion exceedance is computed using the following
formula ::
P(X≥x|T) = 1 - ∏ ∏ Prup_ij(X<x|T)
where ``P(X≥x|T)`` is the probability that the ground motion parameter
``X`` is exceeding level ``x`` one or more times in a time span ``T``, and
``Prup_ij(X<x|T)`` is the probability that the j-th rupture of the i-th
source is not producing any ground motion exceedance in time span ``T``.
The first product ``∏`` is done over sources, while the second one is done
over ruptures in a source.
The above formula computes the probability of having at least one ground
motion exceedance in a time span as 1 minus the probability that none of
the ruptures in none of the sources is causing a ground motion exceedance
in the same time span. The basic assumption is that seismic sources are
independent, and ruptures in a seismic source are also independent.
:param sources:
A sequence of seismic sources objects (instances of subclasses
of :class:`~openquake.hazardlib.source.base.BaseSeismicSource`).
:param sites:
Instance of :class:`~openquake.hazardlib.site.SiteCollection` object,
representing sites of interest.
:param imtls:
Dictionary mapping intensity measure type strings
to lists of intensity measure levels.
:param gsim_by_trt:
Dictionary mapping tectonic region types (members
of :class:`openquake.hazardlib.const.TRT`) to
:class:`~openquake.hazardlib.gsim.base.GMPE` or
:class:`~openquake.hazardlib.gsim.base.IPE` objects.
:param truncation_level:
Float, number of standard deviations for truncation of the intensity
distribution.
:param source_site_filter:
Optional source-site filter function. See
:mod:`openquake.hazardlib.calc.filters`.
:returns:
An array of size N, where N is the number of sites, which elements
are records with fields given by the intensity measure types; the
size of each field is given by the number of levels in ``imtls``.
"""
imtls = DictArray(imtls)
sources_by_trt = groupby(
sources, operator.attrgetter('tectonic_region_type'))
pmap = ProbabilityMap()
for trt in sources_by_trt:
pmap |= hazard_curves_per_trt(
sources_by_trt[trt], sites, imtls, [gsim_by_trt[trt]],
truncation_level, source_site_filter)
return array_of_curves(pmap, len(sites), imtls)
# NB: it is important for this to be fast since it is inside an inner loop
[docs]def get_probability_no_exceedance(
rupture, sctx, rctx, dctx, imtls, gsims, trunclevel):
"""
:param rupture: a Rupture instance
:param sctx: the corresponding SiteContext instance
:param rctx: the corresponding RuptureContext instance
:param dctx: the corresponding DistanceContext instance
:param imtls: a dictionary-like object providing the intensity levels
:param gsims: the list of GSIMs to use
:param trunclevel: the truncation level
:returns: an array of shape (num_sites, num_levels, num_gsims)
"""
pne_array = numpy.zeros((len(sctx.sites), len(imtls.array), len(gsims)))
for i, gsim in enumerate(gsims):
pnos = [] # list of arrays nsites x nlevels
for imt in imtls:
poes = gsim.get_poes(
sctx, rctx, dctx, from_string(imt), imtls[imt], trunclevel)
pnos.append(rupture.get_probability_no_exceedance(poes))
pne_array[:, :, i] = numpy.concatenate(pnos, axis=1)
return pne_array
[docs]def poe_map(src, s_sites, imtls, cmaker, trunclevel, bbs,
ctx_mon, pne_mon, disagg_mon):
"""
Compute the ProbabilityMap generated by the given source. Also,
store some information in the monitors and optionally in the
bounding boxes.
"""
pmap = ProbabilityMap.build(
len(imtls.array), len(cmaker.gsims), s_sites.sids, initvalue=1.)
try:
for rup in src.iter_ruptures():
with ctx_mon: # compute distances
try:
sctx, rctx, dctx = cmaker.make_contexts(s_sites, rup)
except FarAwayRupture:
continue
with pne_mon: # compute probabilities and updates the pmap
pnes = get_probability_no_exceedance(
rup, sctx, rctx, dctx, imtls, cmaker.gsims, trunclevel)
for sid, pne in zip(sctx.sites.sids, pnes):
pmap[sid].array *= pne
# add optional disaggregation information (bounding boxes)
if bbs:
with disagg_mon:
sids = set(sctx.sites.sids)
jb_dists = dctx.rjb
closest_points = rup.surface.get_closest_points(
sctx.sites.mesh)
bs = [bb for bb in bbs if bb.site_id in sids]
# NB: the assert below is always true; we are
# protecting against possible refactoring errors
assert len(bs) == len(jb_dists) == len(closest_points)
for bb, dist, p in zip(bs, jb_dists, closest_points):
bb.update([dist], [p.longitude], [p.latitude])
except Exception as err:
etype, err, tb = sys.exc_info()
msg = 'An error occurred with source id=%s. Error: %s'
msg %= (src.source_id, str(err))
raise_(etype, msg, tb)
return ~pmap
# this is used by the engine
[docs]def hazard_curves_per_trt(
sources, sites, imtls, gsims, truncation_level=None,
source_site_filter=filters.source_site_noop_filter,
maximum_distance=None, bbs=(), monitor=Monitor()):
"""
Compute the hazard curves for a set of sources belonging to the same
tectonic region type for all the GSIMs associated to that TRT.
The arguments are the same as in :func:`calc_hazard_curves`, except
for ``gsims``, which is a list of GSIM instances.
:returns: a ProbabilityMap instance
"""
imtls = DictArray(imtls)
cmaker = ContextMaker(gsims, maximum_distance)
sources_sites = ((source, sites) for source in sources)
ctx_mon = monitor('making contexts', measuremem=False)
pne_mon = monitor('computing poes', measuremem=False)
disagg_mon = monitor('get closest points', measuremem=False)
monitor.calc_times = [] # pairs (src_id, delta_t)
pmap = ProbabilityMap()
for src, s_sites in source_site_filter(sources_sites):
t0 = time.time()
pmap |= poe_map(src, s_sites, imtls, cmaker, truncation_level, bbs,
ctx_mon, pne_mon, disagg_mon)
# we are attaching the calculation times to the monitor
# so that oq-lite (and the engine) can store them
monitor.calc_times.append((src.id, time.time() - t0))
# NB: source.id is an integer; it should not be confused
# with source.source_id, which is a string
monitor.eff_ruptures = pne_mon.counts # contributing ruptures
return pmap