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,
"""
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()
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()
# 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)
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 = cmaker.get_pmap_by_grp(
src_filter, group)
extra['task_no'] = getattr(monitor, 'task_no', 0)
group_probability = getattr(group, 'grp_probability', None)
if src_mutex and group_probability:
pmap[src.src_group_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)
