Source code for openquake.hazardlib.calc.hazard_curve

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2012-2020 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 <>.

""":mod:`openquake.hazardlib.calc.hazard_curve` implements
:func:`calc_hazard_curves`. Here is an example of a classical PSHA
parallel calculator computing the hazard curves per each realization in less
than 20 lines of code:

.. code-block:: python

   import sys
   from openquake.commonlib import logs
   from openquake.calculators.base import get_calc

   def main(job_ini):
       calc_id = logs.init()
       calc = get_calc(job_ini, calc_id)'true', shutdown=True)
       print('The hazard curves are in %s::/hcurves-rlzs'
             % calc.datastore.filename)

   if __name__ == '__main__':
       main(sys.argv[1])  # path to a job.ini file

NB: the implementation in the engine is smarter and more
efficient. Here we start a parallel computation per each realization,
the engine manages all the realizations at once.

import operator
from openquake.baselib.performance import Monitor
from openquake.baselib.parallel import sequential_apply
from openquake.baselib.general import DictArray, groupby, AccumDict
from openquake.hazardlib.probability_map import ProbabilityMap
from openquake.hazardlib.gsim.base import ContextMaker, PmapMaker
from openquake.hazardlib.calc.filters import SourceFilter
from openquake.hazardlib.sourceconverter import SourceGroup
from openquake.hazardlib.tom import FatedTOM

def _cluster(imtls, tom, gsims, pmap):
    Computes the probability map in case of a cluster group
    L, G = len(imtls.array), len(gsims)
    pmapclu = AccumDict(accum=ProbabilityMap(L, G))
    # Get temporal occurrence model
    # Number of occurrences for the cluster
    first = True
    for nocc in range(0, 50):
        # TODO fix this once the occurrence rate will be used just as
        # an object attribute
        ocr = tom.occurrence_rate
        prob_n_occ = tom.get_probability_n_occurrences(ocr, nocc)
        if first:
            pmapclu = prob_n_occ * (~pmap)**nocc
            first = False
            pmapclu += prob_n_occ * (~pmap)**nocc
    pmap = ~pmapclu
    return pmap

[docs]def classical(group, src_filter, gsims, param, 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 dictionary with keys pmap, calc_times, rup_data, extra """ if not hasattr(src_filter, 'sitecol'): # do not filter src_filter = SourceFilter(src_filter, {}) # Get the parameters assigned to the group src_mutex = getattr(group, 'src_interdep', None) == 'mutex' cluster = getattr(group, 'cluster', None) trts = set() maxradius = 0 for src in group: if not src.num_ruptures: # src.num_ruptures may not be set, so it is set here src.num_ruptures = src.count_ruptures() # set the proper TOM in case of a cluster if cluster: src.temporal_occurrence_model = FatedTOM(time_span=1) trts.add(src.tectonic_region_type) if hasattr(src, 'radius'): # for prefiltered point sources maxradius = max(maxradius, src.radius) param['maximum_distance'] = src_filter.integration_distance [trt] = trts # there must be a single tectonic region type cmaker = ContextMaker(trt, gsims, param, monitor) pmap, rup_data, calc_times, extra = PmapMaker( cmaker, src_filter, group).make() extra['task_no'] = getattr(monitor, 'task_no', 0) extra['trt'] = trt extra['source_id'] = src.source_id extra['maxradius'] = maxradius group_probability = getattr(group, 'grp_probability', None) if src_mutex and group_probability: pmap[src.grp_id] *= group_probability if cluster: tom = getattr(group, 'temporal_occurrence_model') pmap = _cluster(param['imtls'], tom, gsims, pmap) return dict(pmap=pmap, calc_times=calc_times, rup_data=rup_data, extra=extra)
# not used in the engine, only in tests and possibly notebooks
[docs]def calc_hazard_curves( groups, srcfilter, imtls, gsim_by_trt, truncation_level=None, apply=sequential_apply, filter_distance='rjb', reqv=None, **kwargs): """ Compute hazard curves on a list of sites, given a set of seismic source groups and a dictionary of ground shaking intensity models (one per tectonic region type). Probability of ground motion exceedance is computed in different ways depending if the sources are independent or mutually exclusive. :param groups: A sequence of groups of seismic sources objects (instances of of :class:`~openquake.hazardlib.source.base.BaseSeismicSource`). :param srcfilter: A source filter over the site collection or the site collection itself :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 apply: apply function to use (default sequential_apply) :param filter_distance: The distance used to filter the ruptures (default rjb) :param reqv: If not None, an instance of RjbEquivalent :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``. """ # This is ensuring backward compatibility i.e. processing a list of # sources if not isinstance(groups[0], SourceGroup): # sent a list of sources odic = groupby(groups, operator.attrgetter('tectonic_region_type')) groups = [SourceGroup(trt, odic[trt], 'src_group', 'indep', 'indep') for trt in odic] # ensure the sources have the right grp_id idx = 0 for i, grp in enumerate(groups): for src in grp: if not hasattr(src, 'grp_id'): src.grp_id = i # fix grp_id = idx idx += 1 imtls = DictArray(imtls) shift_hypo = kwargs['shift_hypo'] if 'shift_hypo' in kwargs else False param = dict(imtls=imtls, truncation_level=truncation_level, filter_distance=filter_distance, reqv=reqv, cluster=grp.cluster, shift_hypo=shift_hypo) pmap = ProbabilityMap(len(imtls.array), 1) # Processing groups with homogeneous tectonic region mon = Monitor() for group in groups: gsim = gsim_by_trt[group[0].tectonic_region_type] if group.atomic: # do not split it = [classical(group, srcfilter, [gsim], param, mon)] else: # split the group and apply `classical` in parallel it = apply( classical, (group.sources, srcfilter, [gsim], param), weight=operator.attrgetter('weight')) for dic in it: for grp_id, pval in dic['pmap'].items(): pmap |= pval sitecol = getattr(srcfilter, 'sitecol', srcfilter) return pmap.convert(imtls, len(sitecol.complete))
[docs]def calc_hazard_curve(site1, src, gsims_by_trt, oqparam): """ :param site1: site collection with a single site :param src: a seismic source object :param gsims_by_trt: a dictionary trt -> gsims :param oqparam: an object with attributes .maximum_distance, .imtls :returns: a ProbabilityCurve object """ assert len(site1) == 1, site1 trt = src.tectonic_region_type gsims = gsims_by_trt['*'] if '*' in gsims_by_trt else gsims_by_trt[trt] cmaker = ContextMaker(trt, gsims, vars(oqparam)) srcfilter = SourceFilter(site1, oqparam.maximum_distance) pmap_by_grp, rup_data, calc_times, extra = PmapMaker( cmaker, srcfilter, [src]).make() pmap = pmap_by_grp[src.grp_ids[0]] return pmap[0] # pcurve with shape (L, G)