Source code for openquake.hazardlib.calc.hazard_curve

# -*- coding: utf-8 -*-
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#
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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
   import logging
   from openquake.baselib import parallel
   from openquake.hazardlib.calc.filters import SourceFilter
   from openquake.hazardlib.calc.hazard_curve import calc_hazard_curves
   from openquake.commonlib import readinput

   def main(job_ini):
       logging.basicConfig(level=logging.INFO)
       oq = readinput.get_oqparam(job_ini)
       sitecol = readinput.get_site_collection(oq)
       src_filter = SourceFilter(sitecol, oq.maximum_distance)
       csm = readinput.get_composite_source_model(oq).filter(src_filter)
       rlzs_assoc = csm.info.get_rlzs_assoc()
       for i, sm in enumerate(csm.source_models):
           for rlz in rlzs_assoc.rlzs_by_smodel[i]:
               gsim_by_trt = rlzs_assoc.gsim_by_trt[rlz.ordinal]
               hcurves = calc_hazard_curves(
                   sm.src_groups, src_filter, oq.imtls,
                   gsim_by_trt, oq.truncation_level,
                   parallel.Starmap.apply)
           print('rlz=%s, hcurves=%s' % (rlz, hcurves))

   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 sys
import time
import operator
import numpy
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
from openquake.hazardlib.calc.filters import SourceFilter
from openquake.hazardlib.sourceconverter import SourceGroup


[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 {grp_id: pmap} with attributes .grp_ids, .calc_times, .eff_ruptures """ grp_ids = set() for src in group: if not src.num_ruptures: # src.num_ruptures is set when parsing the XML, but not when # the source is instantiated manually, so it is set here src.num_ruptures = src.count_ruptures() grp_ids.update(src.src_group_ids) maxdist = src_filter.integration_distance imtls = param['imtls'] trunclevel = param.get('truncation_level') cmaker = ContextMaker(gsims, maxdist, param, monitor) pmap = AccumDict({grp_id: ProbabilityMap(len(imtls.array), len(gsims)) for grp_id in grp_ids}) # AccumDict of arrays with 4 elements weight, nsites, calc_time, split pmap.calc_times = AccumDict(accum=numpy.zeros(4)) pmap.eff_ruptures = AccumDict() # grp_id -> num_ruptures for src, s_sites in src_filter(group): # filter now mutex_weight = getattr(src, 'mutex_weight', None) t0 = time.time() indep = group.rup_interdep == 'indep' if mutex_weight else True try: poemap = cmaker.poe_map(src, s_sites, imtls, trunclevel, indep) except Exception as err: etype, err, tb = sys.exc_info() msg = '%s (source id=%s)' % (str(err), src.source_id) raise etype(msg).with_traceback(tb) if mutex_weight: # mutex sources for sid in poemap: pcurve = pmap[group.id].setdefault(sid, 0) pcurve += poemap[sid] * mutex_weight elif poemap: for grp_id in src.src_group_ids: pmap[grp_id] |= poemap src_id = src.source_id.split(':', 1)[0] pmap.calc_times[src_id] += numpy.array( [src.weight, len(s_sites), time.time() - t0, 1]) # storing the number of contributing ruptures too pmap.eff_ruptures += {grp_id: getattr(poemap, 'eff_ruptures', 0) for grp_id in src.src_group_ids} if mutex_weight and group.grp_probability is not None: pmap[group.id] *= group.grp_probability return pmap
[docs]def calc_hazard_curves( groups, ss_filter, imtls, gsim_by_trt, truncation_level=None, apply=sequential_apply, filter_distance='rjb', reqv=None): """ 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 ss_filter: 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] for i, grp in enumerate(groups): for src in grp: if src.src_group_id is None: src.src_group_id = i if hasattr(ss_filter, 'sitecol'): # a filter, as it should be sitecol = ss_filter.sitecol else: # backward compatibility, a site collection was passed sitecol = ss_filter ss_filter = SourceFilter(sitecol, {}) imtls = DictArray(imtls) param = dict(imtls=imtls, truncation_level=truncation_level, filter_distance=filter_distance, reqv=reqv) pmap = ProbabilityMap(len(imtls.array), 1) # Processing groups with homogeneous tectonic region gsim = gsim_by_trt[groups[0][0].tectonic_region_type] mon = Monitor() for group in groups: if group.src_interdep == 'mutex': # do not split the group it = [classical(group, ss_filter, [gsim], param, mon)] else: # split the group and apply `classical` in parallel it = apply( classical, (group, ss_filter, [gsim], param, mon), weight=operator.attrgetter('weight')) for res in it: for grp_id in res: pmap |= res[grp_id] return pmap.convert(imtls, len(sitecol.complete))