def validate_gsim(self, value):
"""
Checks that the value is a class name in the dictionary reported
by get_available_gsims, i.e. a GSIM class.
:param str value: the name of an existing GSIM class
"""
try:
valid.gsim(value)
except ValueError as e:
raise NameError('%s in file %r' % (e, self.fname))
def validate_gsim(self, value):
"""
Checks that the value is a class name in the dictionary reported
by get_available_gsims, i.e. a GSIM class.
:param str value: the name of an existing GSIM class
"""
try:
valid.gsim(value)
except ValueError as e:
raise NameError('%s in file %r' % (e, self.fname))
def get_gsims(oqparam):
"""
Return an ordered list of GSIM instances from the gsim name in the
configuration file or from the gsim logic tree file.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
return [valid.gsim(str(rlz)) for rlz in get_gsim_lt(oqparam)]
def get_gsims(oqparam):
"""
Return an ordered list of GSIM instances from the gsim name in the
configuration file or from the gsim logic tree file.
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
"""
return [valid.gsim(str(rlz)) for rlz in get_gsim_lt(oqparam)]
def test_gsim(self):
class FakeGsim(object):
def __init__(self, arg):
self.arg = arg
def __repr__(self):
return '<FakeGsim(%s)>' % self.arg
valid.GSIM['FakeGsim'] = FakeGsim
gsim = valid.gsim('FakeGsim(0.1)')
self.assertEqual(repr(gsim), '<FakeGsim(0.1)>')
def get_rlzs_assoc(self, get_weight=lambda tm: tm.num_ruptures):
"""
Return a RlzsAssoc with fields realizations, gsim_by_trt,
rlz_idx and trt_gsims.
:param get_weight: a function trt_model -> positive number
"""
assoc = RlzsAssoc(self.get_info())
random_seed = self.source_model_lt.seed
num_samples = self.source_model_lt.num_samples
idx = 0
for smodel in self.source_models:
# collect the effective tectonic region types
trts = set(tm.trt for tm in smodel.trt_models if get_weight(tm))
# recompute the GSIM logic tree if needed
if trts != set(smodel.gsim_lt.tectonic_region_types):
before = smodel.gsim_lt.get_num_paths()
smodel.gsim_lt.reduce(trts)
after = smodel.gsim_lt.get_num_paths()
logging.warn(
'Reducing the logic tree of %s from %d to %d '
'realizations', smodel.name, before, after)
if num_samples: # sampling
rnd = random.Random(random_seed + idx)
rlzs = logictree.sample(smodel.gsim_lt, smodel.samples, rnd)
else: # full enumeration
rlzs = logictree.get_effective_rlzs(smodel.gsim_lt)
if rlzs:
idx = assoc._add_realizations(idx, smodel, rlzs, trts)
for trt_model in smodel.trt_models:
trt_model.gsims = smodel.gsim_lt.values[trt_model.trt]
else:
logging.warn('No realizations for %s, %s',
'_'.join(smodel.path), smodel.name)
if assoc.realizations:
if num_samples:
assert len(assoc.realizations) == num_samples
for rlz in assoc.realizations:
rlz.weight = 1. / num_samples
else:
tot_weight = sum(rlz.weight for rlz in assoc.realizations)
if tot_weight == 0:
raise ValueError('All realizations have zero weight??')
elif abs(tot_weight - 1) > 1E-12: # allow for rounding errors
logging.warn('Some source models are not contributing, '
'weights are being rescaled')
for rlz in assoc.realizations:
rlz.weight = rlz.weight / tot_weight
assoc.gsims_by_trt_id = groupby(
assoc.rlzs_assoc, operator.itemgetter(0),
lambda group: sorted(valid.gsim(gsim) for trt_id, gsim in group))
return assoc
def test_gsim(self):
class FakeGsim(object):
def __init__(self, arg):
self.arg = arg
def __repr__(self):
return '<FakeGsim(%s)>' % self.arg
valid.GSIM['FakeGsim'] = FakeGsim
gsim = valid.gsim('FakeGsim(0.1)')
self.assertEqual(repr(gsim), '<FakeGsim(0.1)>')
def get_rlzs_assoc(self, get_weight=lambda tm: tm.num_ruptures):
"""
Return a RlzsAssoc with fields realizations, gsim_by_trt,
rlz_idx and trt_gsims.
:param get_weight: a function trt_model -> positive number
"""
assoc = RlzsAssoc(self.get_info())
random_seed = self.source_model_lt.seed
num_samples = self.source_model_lt.num_samples
idx = 0
for smodel in self.source_models:
# collect the effective tectonic region types
trts = set(tm.trt for tm in smodel.trt_models if get_weight(tm))
# recompute the GSIM logic tree if needed
if trts != set(smodel.gsim_lt.tectonic_region_types):
before = smodel.gsim_lt.get_num_paths()
smodel.gsim_lt.reduce(trts)
after = smodel.gsim_lt.get_num_paths()
logging.warn('Reducing the logic tree of %s from %d to %d '
'realizations', smodel.name, before, after)
if num_samples: # sampling
rnd = random.Random(random_seed + idx)
rlzs = logictree.sample(smodel.gsim_lt, smodel.samples, rnd)
else: # full enumeration
rlzs = logictree.get_effective_rlzs(smodel.gsim_lt)
if rlzs:
idx = assoc._add_realizations(idx, smodel, rlzs, trts)
for trt_model in smodel.trt_models:
trt_model.gsims = smodel.gsim_lt.values[trt_model.trt]
else:
logging.warn('No realizations for %s, %s',
'_'.join(smodel.path), smodel.name)
if assoc.realizations:
if num_samples:
assert len(assoc.realizations) == num_samples
for rlz in assoc.realizations:
rlz.weight = 1. / num_samples
else:
tot_weight = sum(rlz.weight for rlz in assoc.realizations)
if tot_weight == 0:
raise ValueError('All realizations have zero weight??')
elif abs(tot_weight - 1) > 1E-12: # allow for rounding errors
logging.warn('Some source models are not contributing, '
'weights are being rescaled')
for rlz in assoc.realizations:
rlz.weight = rlz.weight / tot_weight
assoc.gsims_by_trt_id = groupby(
assoc.rlzs_assoc, operator.itemgetter(0),
lambda group: sorted(valid.gsim(gsim) for trt_id, gsim in group))
return assoc
def test_compute_gmf(self):
hc = mock.Mock()
hc.ground_motion_correlation_model = None
hc.truncation_level = None
hc.maximum_distance = 200.
trt = 'Subduction Interface'
gsim = valid.gsim('AkkarBommer2010')
num_sites = 5
site_coll = make_site_coll(-78, 15.5, num_sites)
rup_id, rup_seed = 42, 44
rup = FakeRupture(rup_id, trt)
rlz = mock.Mock()
rlz.id = 1
ses_coll = mock.Mock()
ses_coll.ordinal = 0
ses_coll.trt_model.id = 1
calc = core.GmfCalculator(
['PGA'], [gsim], ses_coll, truncation_level=3)
calc.calc_gmfs(site_coll, rup, [(rup.id, rup_seed)])
expected_rups = {
('AkkarBommer2010', 'PGA', 0): [rup_id],
('AkkarBommer2010', 'PGA', 1): [rup_id],
('AkkarBommer2010', 'PGA', 2): [rup_id],
('AkkarBommer2010', 'PGA', 3): [rup_id],
('AkkarBommer2010', 'PGA', 4): [rup_id],
}
expected_gmvs = {
('AkkarBommer2010', 'PGA', 0): [0.1027847118266612],
('AkkarBommer2010', 'PGA', 1): [0.02726361912605336],
('AkkarBommer2010', 'PGA', 2): [0.0862595971325641],
('AkkarBommer2010', 'PGA', 3): [0.04727148908077005],
('AkkarBommer2010', 'PGA', 4): [0.04750575818347277],
}
numpy.testing.assert_equal(calc.ruptures_per_site, expected_rups)
for i, gmvs in expected_gmvs.iteritems():
numpy.testing.assert_allclose(gmvs, expected_gmvs[i])
# 5 curves (one per each site) for 3 levels, 1 IMT
[(gname, [curves])] = calc.to_haz_curves(
site_coll.sids, dict(PGA=[0.03, 0.04, 0.05]),
invest_time=50., duration=500)
self.assertEqual(gname, 'AkkarBommer2010')
numpy.testing.assert_array_almost_equal(
curves,
[[0.09516258, 0.09516258, 0.09516258], # curve site1
[0.00000000, 0.00000000, 0.00000000], # curve site2
[0.09516258, 0.09516258, 0.09516258], # curve site3
[0.09516258, 0.09516258, 0.00000000], # curve site4
[0.09516258, 0.09516258, 0.00000000], # curve site5
])
def _build_trts_branches(self):
# do the parsing, called at instantiation time to populate .values
trts = []
branches = []
branchsetids = set()
for branching_level in self._ltnode:
if len(branching_level) > 1:
raise InvalidLogicTree(
'Branching level %s has multiple branchsets' %
branching_level['branchingLevelID'])
for branchset in branching_level:
if branchset['uncertaintyType'] != 'gmpeModel':
raise InvalidLogicTree(
'only uncertainties of type '
'"gmpeModel" are allowed in gmpe logic tree')
bsid = branchset['branchSetID']
if bsid in branchsetids:
raise InvalidLogicTree('Duplicated branchSetID %s' % bsid)
else:
branchsetids.add(bsid)
trt = branchset.attrib.get('applyToTectonicRegionType')
if trt:
trts.append(trt)
effective = trt in self.tectonic_region_types
weights = []
for branch in branchset:
weight = Decimal(branch.uncertaintyWeight.text)
weights.append(weight)
branch_id = branch['branchID']
uncertainty = branch.uncertaintyModel
try:
gsim = valid.gsim(uncertainty.text.strip(),
**uncertainty.attrib)
except:
etype, exc, tb = sys.exc_info()
raise_(etype, '%s in file %r' % (exc, self.fname), tb)
self.values[trt].append(gsim)
bt = BranchTuple(branchset, branch_id, gsim, weight,
effective)
branches.append(bt)
assert sum(weights) == 1, weights
if len(trts) > len(set(trts)):
raise InvalidLogicTree(
'Found duplicated applyToTectonicRegionType=%s' % trts)
branches.sort(key=lambda b: (b.bset['branchSetID'], b.id))
return trts, branches
def create_ruptures(self):
oqparam = models.oqparam(self.job.id)
self.imts = map(from_string, oqparam.imtls)
self.rupture = readinput.get_rupture(oqparam)
# check filtering
trunc_level = oqparam.truncation_level
maximum_distance = oqparam.maximum_distance
self.sites = filters.filter_sites_by_distance_to_rupture(
self.rupture, maximum_distance, self.site_collection)
if self.sites is None:
raise RuntimeError(
'All sites where filtered out! '
'maximum_distance=%s km' % maximum_distance)
# create ses output
output = models.Output.objects.create(
oq_job=self.job,
display_name='SES Collection',
output_type='ses')
self.ses_coll = models.SESCollection.create(output=output)
# create gmf output
output = models.Output.objects.create(
oq_job=self.job,
display_name="GMF",
output_type="gmf_scenario")
self.gmf = models.Gmf.objects.create(output=output)
with self.monitor('saving ruptures', autoflush=True):
self.tags = ['scenario-%010d' % i for i in xrange(
oqparam.number_of_ground_motion_fields)]
_, self.rupids, self.seeds = create_db_ruptures(
self.rupture, self.ses_coll, self.tags,
self.oqparam.random_seed)
correlation_model = models.get_correl_model(
models.OqJob.objects.get(pk=self.job.id))
gsim = valid.gsim(oqparam.gsim)
self.computer = GmfComputer(
self.rupture, self.sites, oqparam.imtls, [gsim],
trunc_level, correlation_model)
def _build_trts_branches(self):
# do the parsing, called at instantiation time to populate .values
trts = []
branches = []
branchsetids = set()
for branching_level in self._ltnode:
if len(branching_level) > 1:
raise InvalidLogicTree(
"Branching level %s has multiple branchsets" % branching_level["branchingLevelID"]
)
for branchset in branching_level:
if branchset["uncertaintyType"] != "gmpeModel":
raise InvalidLogicTree("only uncertainties of type " '"gmpeModel" are allowed in gmpe logic tree')
bsid = branchset["branchSetID"]
if bsid in branchsetids:
raise InvalidLogicTree("Duplicated branchSetID %s" % bsid)
else:
branchsetids.add(bsid)
trt = branchset.attrib.get("applyToTectonicRegionType")
if trt:
trts.append(trt)
effective = trt in self.tectonic_region_types
weights = []
for branch in branchset:
weight = Decimal(branch.uncertaintyWeight.text)
weights.append(weight)
branch_id = branch["branchID"]
uncertainty = branch.uncertaintyModel
try:
gsim = valid.gsim(uncertainty.text.strip(), **uncertainty.attrib)
except:
etype, exc, tb = sys.exc_info()
raise_(etype, "%s in file %r" % (exc, self.fname), tb)
self.values[trt].append(gsim)
bt = BranchTuple(branchset, branch_id, gsim, weight, effective)
branches.append(bt)
assert sum(weights) == 1, weights
if len(trts) > len(set(trts)):
raise InvalidLogicTree("Found duplicated applyToTectonicRegionType=%s" % trts)
branches.sort(key=lambda b: (b.bset["branchSetID"], b.id))
return trts, branches
def create_ruptures(self):
oqparam = models.oqparam(self.job.id)
self.imts = map(from_string, oqparam.imtls)
self.rupture = readinput.get_rupture(oqparam)
# check filtering
trunc_level = oqparam.truncation_level
maximum_distance = oqparam.maximum_distance
self.sites = filters.filter_sites_by_distance_to_rupture(
self.rupture, maximum_distance, self.site_collection)
if self.sites is None:
raise RuntimeError('All sites where filtered out! '
'maximum_distance=%s km' % maximum_distance)
# create ses output
output = models.Output.objects.create(oq_job=self.job,
display_name='SES Collection',
output_type='ses')
self.ses_coll = models.SESCollection.create(output=output)
# create gmf output
output = models.Output.objects.create(oq_job=self.job,
display_name="GMF",
output_type="gmf_scenario")
self.gmf = models.Gmf.objects.create(output=output)
with self.monitor('saving ruptures', autoflush=True):
self.tags = [
'scenario-%010d' % i
for i in xrange(oqparam.number_of_ground_motion_fields)
]
_, self.rupids, self.seeds = create_db_ruptures(
self.rupture, self.ses_coll, self.tags,
self.oqparam.random_seed)
correlation_model = models.get_correl_model(
models.OqJob.objects.get(pk=self.job.id))
gsim = valid.gsim(oqparam.gsim)
self.computer = GmfComputer(self.rupture, self.sites, oqparam.imtls,
[gsim], trunc_level, correlation_model)
def get_gsims_by_trt_id(self):
"""Returns associations trt_id -> [GSIM instance, ...]"""
return groupby(
self.rlzs_assoc, operator.itemgetter(0),
lambda group: sorted(valid.gsim(gsim)
for trt_id, gsim in group))