def build_ruptures(sources, src_filter, param, monitor):
"""
:param sources: a list with a single UCERF source
:param param: extra parameters
:param monitor: a Monitor instance
:returns: an AccumDict grp_id -> EBRuptures
"""
[src] = sources
res = AccumDict()
res.calc_times = []
sampl_mon = monitor('sampling ruptures', measuremem=True)
res.trt = DEFAULT_TRT
background_sids = src.get_background_sids(src_filter)
samples = getattr(src, 'samples', 1)
n_occ = AccumDict(accum=0)
t0 = time.time()
with sampl_mon:
for sam_idx in range(samples):
for ses_idx, ses_seed in param['ses_seeds']:
seed = sam_idx * TWO16 + ses_seed
rups, occs = generate_event_set(src, background_sids,
src_filter, ses_idx, seed)
for rup, occ in zip(rups, occs):
n_occ[rup] += occ
tot_occ = sum(n_occ.values())
dic = {'eff_ruptures': {src.src_group_id: src.num_ruptures}}
eb_ruptures = [
EBRupture(rup, src.id, src.src_group_id, n, samples)
for rup, n in n_occ.items()
]
dic['rup_array'] = stochastic.get_rup_array(eb_ruptures, src_filter)
dt = time.time() - t0
n = len(src_filter.sitecol)
dic['calc_times'] = {src.id: numpy.array([tot_occ, n, dt], F32)}
return dic
def build_ruptures(sources, src_filter, param, monitor):
"""
:param sources: a list with a single UCERF source
:param param: extra parameters
:param monitor: a Monitor instance
:returns: an AccumDict grp_id -> EBRuptures
"""
[src] = sources
res = AccumDict()
res.calc_times = []
sampl_mon = monitor('sampling ruptures', measuremem=True)
res.trt = DEFAULT_TRT
background_sids = src.get_background_sids(src_filter)
samples = getattr(src, 'samples', 1)
n_occ = AccumDict(accum=0)
t0 = time.time()
with sampl_mon:
for sam_idx in range(samples):
for ses_idx, ses_seed in param['ses_seeds']:
seed = sam_idx * TWO16 + ses_seed
rups, occs = generate_event_set(
src, background_sids, src_filter, ses_idx, seed)
for rup, occ in zip(rups, occs):
n_occ[rup] += occ
tot_occ = sum(n_occ.values())
dic = {'eff_ruptures': {src.src_group_id: src.num_ruptures}}
eb_ruptures = [EBRupture(rup, src.id, src.src_group_id, n, samples)
for rup, n in n_occ.items()]
dic['rup_array'] = stochastic.get_rup_array(eb_ruptures, src_filter)
dt = time.time() - t0
dic['calc_times'] = {src.id: numpy.array([tot_occ, dt], F32)}
return dic
def pre_execute(self):
"""
Read the site collection and initialize GmfComputer and seeds
"""
oq = self.oqparam
cinfo = source.CompositionInfo.fake(readinput.get_gsim_lt(oq))
self.datastore['csm_info'] = cinfo
if 'rupture_model' not in oq.inputs:
logging.warn('There is no rupture_model, the calculator will just '
'import data without performing any calculation')
super().pre_execute()
return
self.rup = readinput.get_rupture(oq)
self.gsims = readinput.get_gsims(oq)
R = len(self.gsims)
self.cmaker = ContextMaker(self.gsims, oq.maximum_distance,
{'filter_distance': oq.filter_distance})
super().pre_execute()
self.datastore['oqparam'] = oq
self.rlzs_assoc = cinfo.get_rlzs_assoc()
rlzs_by_gsim = self.rlzs_assoc.get_rlzs_by_gsim(0)
E = oq.number_of_ground_motion_fields
n_occ = numpy.array([E])
ebr = EBRupture(self.rup, 0, 0, self.sitecol.sids, n_occ)
events = numpy.zeros(E * R, events_dt)
for rlz, eids in ebr.get_eids_by_rlz(rlzs_by_gsim).items():
events[rlz * E:rlz * E + E]['eid'] = eids
events[rlz * E:rlz * E + E]['rlz'] = rlz
self.datastore['events'] = events
rupser = calc.RuptureSerializer(self.datastore)
rupser.save(get_rup_array([ebr]))
rupser.close()
self.computer = GmfComputer(ebr, self.sitecol, oq.imtls, self.cmaker,
oq.truncation_level, oq.correl_model)
def _read_scenario_ruptures(self):
oq = self.oqparam
gsim_lt = readinput.get_gsim_lt(self.oqparam)
G = gsim_lt.get_num_paths()
if oq.calculation_mode.startswith('scenario'):
ngmfs = oq.number_of_ground_motion_fields
if oq.inputs['rupture_model'].endswith('.xml'):
self.gsims = [gsim_rlz.value[0] for gsim_rlz in gsim_lt]
self.cmaker = ContextMaker('*', self.gsims, {
'maximum_distance': oq.maximum_distance,
'imtls': oq.imtls
})
rup = readinput.get_rupture(oq)
if self.N > oq.max_sites_disagg: # many sites, split rupture
ebrs = [
EBRupture(copyobj(rup, rup_id=rup.rup_id + i),
0,
0,
G,
e0=i * G) for i in range(ngmfs)
]
else: # keep a single rupture with a big occupation number
ebrs = [EBRupture(rup, 0, 0, G * ngmfs, rup.rup_id)]
aw = get_rup_array(ebrs, self.srcfilter)
if len(aw) == 0:
raise RuntimeError(
'The rupture is too far from the sites! Please check the '
'maximum_distance and the position of the rupture')
elif oq.inputs['rupture_model'].endswith('.csv'):
aw = readinput.get_ruptures(oq.inputs['rupture_model'])
num_gsims = numpy.array(
[len(gsim_lt.values[trt]) for trt in gsim_lt.values], U32)
if oq.calculation_mode.startswith('scenario'):
# rescale n_occ
aw['n_occ'] *= ngmfs * num_gsims[aw['trt_smr']]
rup_array = aw.array
hdf5.extend(self.datastore['rupgeoms'], aw.geom)
if len(rup_array) == 0:
raise RuntimeError(
'There are no sites within the maximum_distance'
' of %s km from the rupture' %
oq.maximum_distance(rup.tectonic_region_type, rup.mag))
# check the number of branchsets
branchsets = len(gsim_lt._ltnode)
if len(rup_array) == 1 and branchsets > 1:
raise InvalidFile(
'%s for a scenario calculation must contain a single '
'branchset, found %d!' % (oq.inputs['job_ini'], branchsets))
fake = logictree.FullLogicTree.fake(gsim_lt)
self.realizations = fake.get_realizations()
self.datastore['full_lt'] = fake
self.store_rlz_info({}) # store weights
self.save_params()
imp = calc.RuptureImporter(self.datastore)
imp.import_rups_events(rup_array, get_rupture_getters)
def _read_scenario_ruptures(self):
oq = self.oqparam
gsim_lt = readinput.get_gsim_lt(self.oqparam)
G = gsim_lt.get_num_paths()
if oq.inputs['rupture_model'].endswith('.xml'):
ngmfs = oq.number_of_ground_motion_fields
self.gsims = readinput.get_gsims(oq)
self.cmaker = ContextMaker('*', self.gsims, {
'maximum_distance': oq.maximum_distance,
'imtls': oq.imtls
})
rup = readinput.get_rupture(oq)
mesh = surface_to_array(rup.surface).transpose(1, 2, 0).flatten()
if self.N > oq.max_sites_disagg: # many sites, split rupture
ebrs = [
EBRupture(copyobj(rup, rup_id=rup.rup_id + i),
0,
0,
G,
e0=i * G) for i in range(ngmfs)
]
meshes = numpy.array([mesh] * ngmfs, object)
else: # keep a single rupture with a big occupation number
ebrs = [EBRupture(rup, 0, 0, G * ngmfs, rup.rup_id)]
meshes = numpy.array([mesh] * ngmfs, object)
rup_array = get_rup_array(ebrs, self.srcfilter).array
hdf5.extend(self.datastore['rupgeoms'], meshes)
elif oq.inputs['rupture_model'].endswith('.csv'):
aw = readinput.get_ruptures(oq.inputs['rupture_model'])
aw.array['n_occ'] = G
rup_array = aw.array
hdf5.extend(self.datastore['rupgeoms'], aw.geom)
if len(rup_array) == 0:
raise RuntimeError(
'There are no sites within the maximum_distance'
' of %s km from the rupture' %
oq.maximum_distance(rup.tectonic_region_type, rup.mag))
# check the number of branchsets
branchsets = len(gsim_lt._ltnode)
if len(rup_array) == 1 and branchsets > 1:
raise InvalidFile(
'%s for a scenario calculation must contain a single '
'branchset, found %d!' % (oq.inputs['job_ini'], branchsets))
fake = logictree.FullLogicTree.fake(gsim_lt)
self.realizations = fake.get_realizations()
self.datastore['full_lt'] = fake
self.store_rlz_info({}) # store weights
self.save_params()
calc.RuptureImporter(self.datastore).import_rups(rup_array)
def pre_execute(self):
"""
Read the site collection and initialize GmfComputer and seeds
"""
oq = self.oqparam
cinfo = logictree.FullLogicTree.fake(readinput.get_gsim_lt(oq))
self.realizations = cinfo.get_realizations()
self.datastore['full_lt'] = cinfo
if 'rupture_model' not in oq.inputs:
logging.warning(
'There is no rupture_model, the calculator will just '
'import data without performing any calculation')
super().pre_execute()
return
self.rup = readinput.get_rupture(oq)
self.gsims = readinput.get_gsims(oq)
R = len(self.gsims)
self.cmaker = ContextMaker(
'*', self.gsims, {
'maximum_distance': oq.maximum_distance,
'filter_distance': oq.filter_distance
})
super().pre_execute()
self.datastore['oqparam'] = oq
self.store_rlz_info({})
rlzs_by_gsim = cinfo.get_rlzs_by_gsim(0)
E = oq.number_of_ground_motion_fields
n_occ = numpy.array([E])
ebr = EBRupture(self.rup, 0, 0, n_occ)
ebr.e0 = 0
events = numpy.zeros(E * R, events_dt)
for rlz, eids in ebr.get_eids_by_rlz(rlzs_by_gsim).items():
events[rlz * E:rlz * E + E]['id'] = eids
events[rlz * E:rlz * E + E]['rlz_id'] = rlz
self.datastore['events'] = self.events = events
rupser = calc.RuptureSerializer(self.datastore)
rup_array = get_rup_array([ebr], self.src_filter())
if len(rup_array) == 0:
maxdist = oq.maximum_distance(self.rup.tectonic_region_type,
self.rup.mag)
raise RuntimeError('There are no sites within the maximum_distance'
' of %s km from the rupture' % maxdist)
rupser.save(rup_array)
rupser.close()
self.computer = GmfComputer(ebr, self.sitecol, oq.imtls, self.cmaker,
oq.truncation_level, oq.correl_model,
self.amplifier)
M32 = (numpy.float32, len(self.oqparam.imtls))
self.sig_eps_dt = [('eid', numpy.uint64), ('sig', M32), ('eps', M32)]
def _read_scenario_ruptures(self):
oq = self.oqparam
if oq.inputs['rupture_model'].endswith(('.xml', '.toml', '.txt')):
self.gsims = readinput.get_gsims(oq)
self.cmaker = ContextMaker(
'*', self.gsims,
{'maximum_distance': oq.maximum_distance,
'filter_distance': oq.filter_distance})
n_occ = numpy.array([oq.number_of_ground_motion_fields])
rup = readinput.get_rupture(oq)
ebr = EBRupture(rup, 0, 0, n_occ)
ebr.e0 = 0
rup_array = get_rup_array([ebr], self.srcfilter).array
mesh = surface_to_array(rup.surface).transpose(1, 2, 0).flatten()
hdf5.extend(self.datastore['rupgeoms'],
numpy.array([mesh], object))
elif oq.inputs['rupture_model'].endswith('.csv'):
aw = readinput.get_ruptures(oq.inputs['rupture_model'])
rup_array = aw.array
hdf5.extend(self.datastore['rupgeoms'], aw.geom)
if len(rup_array) == 0:
raise RuntimeError(
'There are no sites within the maximum_distance'
' of %s km from the rupture' % oq.maximum_distance(
rup.tectonic_region_type, rup.mag))
gsim_lt = readinput.get_gsim_lt(self.oqparam)
# check the number of branchsets
branchsets = len(gsim_lt._ltnode)
if len(rup_array) == 1 and branchsets > 1:
raise InvalidFile(
'%s for a scenario calculation must contain a single '
'branchset, found %d!' % (oq.inputs['job_ini'], branchsets))
fake = logictree.FullLogicTree.fake(gsim_lt)
self.realizations = fake.get_realizations()
self.datastore['full_lt'] = fake
self.store_rlz_info({}) # store weights
self.save_params()
calc.RuptureImporter(self.datastore).import_rups(rup_array)
def build_ruptures(sources, src_filter, param, monitor):
"""
:param sources: a list with a single UCERF source
:param src_filter: a SourceFilter instance
:param param: extra parameters
:param monitor: a Monitor instance
:returns: an AccumDict grp_id -> EBRuptures
"""
[src] = sources
res = AccumDict()
res.calc_times = []
sampl_mon = monitor('sampling ruptures', measuremem=True)
filt_mon = monitor('filtering ruptures', measuremem=False)
res.trt = DEFAULT_TRT
background_sids = src.get_background_sids(src_filter)
sitecol = src_filter.sitecol
cmaker = ContextMaker(param['gsims'], src_filter.integration_distance)
num_ses = param['ses_per_logic_tree_path']
samples = getattr(src, 'samples', 1)
n_occ = AccumDict(accum=0)
t0 = time.time()
with sampl_mon:
for sam_idx in range(samples):
for ses_idx, ses_seed in param['ses_seeds']:
seed = sam_idx * TWO16 + ses_seed
rups, occs = generate_event_set(src, background_sids,
src_filter, ses_idx, seed)
for rup, occ in zip(rups, occs):
n_occ[rup] += occ
tot_occ = sum(n_occ.values())
dic = {'eff_ruptures': {src.src_group_id: src.num_ruptures}}
with filt_mon:
eb_ruptures = stochastic.build_eb_ruptures(src, num_ses, cmaker,
sitecol, n_occ.items())
dic['rup_array'] = (stochastic.get_rup_array(eb_ruptures)
if eb_ruptures else ())
dt = time.time() - t0
dic['calc_times'] = {src.id: numpy.array([tot_occ, len(sitecol), dt], F32)}
return dic
def _read_scenario_ruptures(self):
oq = self.oqparam
gsim_lt = readinput.get_gsim_lt(self.oqparam)
G = gsim_lt.get_num_paths()
if oq.calculation_mode.startswith('scenario'):
ngmfs = oq.number_of_ground_motion_fields
if oq.inputs['rupture_model'].endswith('.xml'):
# check the number of branchsets
bsets = len(gsim_lt._ltnode)
if bsets > 1:
raise InvalidFile(
'%s for a scenario calculation must contain a single '
'branchset, found %d!' % (oq.inputs['job_ini'], bsets))
[(trt, rlzs_by_gsim)] = gsim_lt.get_rlzs_by_gsim_trt().items()
self.cmaker = ContextMaker(
trt, rlzs_by_gsim, {
'maximum_distance': oq.maximum_distance(trt),
'minimum_distance': oq.minimum_distance,
'truncation_level': oq.truncation_level,
'imtls': oq.imtls
})
rup = readinput.get_rupture(oq)
if self.N > oq.max_sites_disagg: # many sites, split rupture
ebrs = [
EBRupture(copyobj(rup, rup_id=rup.rup_id + i),
'NA',
0,
G,
e0=i * G,
scenario=True) for i in range(ngmfs)
]
else: # keep a single rupture with a big occupation number
ebrs = [
EBRupture(rup,
'NA',
0,
G * ngmfs,
rup.rup_id,
scenario=True)
]
srcfilter = SourceFilter(self.sitecol, oq.maximum_distance(trt))
aw = get_rup_array(ebrs, srcfilter)
if len(aw) == 0:
raise RuntimeError(
'The rupture is too far from the sites! Please check the '
'maximum_distance and the position of the rupture')
elif oq.inputs['rupture_model'].endswith('.csv'):
aw = get_ruptures(oq.inputs['rupture_model'])
if len(gsim_lt.values) == 1: # fix for scenario_damage/case_12
aw['trt_smr'] = 0 # a single TRT
if oq.calculation_mode.startswith('scenario'):
# rescale n_occ by ngmfs and nrlzs
aw['n_occ'] *= ngmfs * gsim_lt.get_num_paths()
else:
raise InvalidFile("Something wrong in %s" % oq.inputs['job_ini'])
rup_array = aw.array
hdf5.extend(self.datastore['rupgeoms'], aw.geom)
if len(rup_array) == 0:
raise RuntimeError(
'There are no sites within the maximum_distance'
' of %s km from the rupture' %
oq.maximum_distance(rup.tectonic_region_type)(rup.mag))
fake = logictree.FullLogicTree.fake(gsim_lt)
self.realizations = fake.get_realizations()
self.datastore['full_lt'] = fake
self.store_rlz_info({}) # store weights
self.save_params()
imp = calc.RuptureImporter(self.datastore)
imp.import_rups_events(rup_array, get_rupture_getters)
