Source code for openquake.hazardlib.calc.hazard_curve

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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""":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 calculators

   def main(job_ini):
       with logs.init('job', job_ini) as log:
           calc = calculators(log.get_oqparam(), log.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
import numpy
from openquake.baselib.performance import Monitor
from openquake.baselib.parallel import sequential_apply
from openquake.baselib.general import DictArray, groupby
from openquake.hazardlib.probability_map import (
    ProbabilityMap, ProbabilityCurve)
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 PoissonTOM, FatedTOM

def _cluster(imtls, tom, gsims, pmap):
    Computes the probability map in case of a cluster group
    L, G = imtls.size, len(gsims)
    pmapclu = 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 = (~pmap)**nocc * prob_n_occ
            first = False
            pmapclu += (~pmap)**nocc * prob_n_occ
    pmap = ~pmapclu
    return pmap

[docs]def classical(group, sitecol, cmaker): """ 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, source_data, rup_data, extra """ src_filter = SourceFilter(sitecol, cmaker.maximum_distance) cluster = getattr(group, 'cluster', None) trts = set() 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) [trt] = trts # there must be a single tectonic region type if cmaker.trt != '*': assert trt == cmaker.trt, (trt, cmaker.trt) try: cmaker.tom = group.temporal_occurrence_model except AttributeError: # got a list of sources, not a group time_span = cmaker.investigation_time # None for nonparametric cmaker.tom = PoissonTOM(time_span) if time_span else None if cluster: cmaker.tom = FatedTOM(time_span=1) dic = PmapMaker(cmaker, src_filter, group).make() if cluster: tom = getattr(group, 'temporal_occurrence_model') dic['pmap'] = _cluster(cmaker.imtls, tom, cmaker.gsims, dic['pmap']) return dic
# 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, 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 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] idx = 0 span = None for i, grp in enumerate(groups): for src in grp: tom = getattr(src, 'temporal_occurrence_model', None) if tom: span = tom.time_span src.weight = src.count_ruptures() src.grp_id = i = 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, reqv=reqv, cluster=grp.cluster, shift_hypo=shift_hypo, investigation_time=kwargs.get('investigation_time', span)) pmap = ProbabilityMap(imtls.size, 1) # Processing groups with homogeneous tectonic region mon = Monitor() sitecol = getattr(srcfilter, 'sitecol', srcfilter) for group in groups: trt = group.trt if sitecol is not srcfilter: param['maximum_distance'] = srcfilter.integration_distance(trt) cmaker = ContextMaker(trt, [gsim_by_trt[trt]], param, mon) if group.atomic: # do not split it = [classical(group, sitecol, cmaker)] else: # split the group and apply `classical` in parallel it = apply( classical, (group.sources, sitecol, cmaker), weight=operator.attrgetter('weight')) for dic in it: pmap |= dic['pmap'] return pmap.convert(imtls, len(sitecol.complete))
# called in adv-manual/developing.rst and in SingleSiteOptTestCase
[docs]def calc_hazard_curve(site1, src, gsims, oqparam, monitor=Monitor()): """ :param site1: site collection with a single site :param src: a seismic source object :param gsims: a list of GSIM objects :param oqparam: an object with attributes .maximum_distance, .imtls :param monitor: a Monitor instance (optional) :returns: a ProbabilityCurve object """ assert len(site1) == 1, site1 trt = src.tectonic_region_type cmaker = ContextMaker(trt, gsims, vars(oqparam), monitor) cmaker.tom = src.temporal_occurrence_model srcfilter = SourceFilter(site1, oqparam.maximum_distance) pmap = PmapMaker(cmaker, srcfilter, [src]).make()['pmap'] if not pmap: # filtered away zero = numpy.zeros((oqparam.imtls.size, len(gsims))) return ProbabilityCurve(zero) return pmap[0] # pcurve with shape (L, G) on site 0