def compute_gmfs_curves(self, monitor):
"""
:returns: a dict with keys gmfdata, hcurves
"""
oq = self.oqparam
mon = monitor('getting ruptures', measuremem=True)
hcurves = {} # key -> poes
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
gmfdata = self.get_gmfdata(mon) # returned later
hazard = self.get_hazard_by_sid(data=gmfdata)
for sid, hazardr in hazard.items():
dic = general.group_array(hazardr, 'rlz')
for rlzi, array in dic.items():
with hc_mon:
poes = gmvs_to_poes(
array['gmv'].T, oq.imtls,
oq.ses_per_logic_tree_path)
for m, imt in enumerate(oq.imtls):
hcurves[rsi2str(rlzi, sid, imt)] = poes[m]
if not oq.ground_motion_fields:
return dict(gmfdata=(), hcurves=hcurves)
if not oq.hazard_curves_from_gmfs:
gmfdata = self.get_gmfdata(mon)
if len(gmfdata) == 0:
return dict(gmfdata=[])
times = numpy.array([tup + (monitor.task_no,) for tup in self.times],
time_dt)
times.sort(order='rup_id')
res = dict(gmfdata=gmfdata, hcurves=hcurves, times=times,
sig_eps=numpy.array(self.sig_eps, self.sig_eps_dt))
return res
def compute_gmfs_curves(self, monitor):
"""
:returns: a dict with keys gmfdata, hcurves
"""
oq = self.oqparam
mon = monitor('getting ruptures', measuremem=True)
hcurves = {} # key -> poes
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
gmfdata = self.get_gmfdata(mon) # returned later
if len(gmfdata) == 0:
return dict(gmfdata=(), hcurves=hcurves)
for (sid, rlz), df in gmfdata.groupby(['sid', 'rlz']):
with hc_mon:
poes = calc.gmvs_to_poes(
df, oq.imtls, oq.ses_per_logic_tree_path)
for m, imt in enumerate(oq.imtls):
hcurves[rsi2str(rlz, sid, imt)] = poes[m]
if not oq.ground_motion_fields:
return dict(gmfdata=(), hcurves=hcurves)
if not oq.hazard_curves_from_gmfs:
gmfdata = self.get_gmfdata(mon)
if len(gmfdata) == 0:
return dict(gmfdata=[])
times = numpy.array([tup + (monitor.task_no,) for tup in self.times],
time_dt)
times.sort(order='rup_id')
res = dict(gmfdata=strip_zeros(gmfdata), hcurves=hcurves, times=times,
sig_eps=numpy.array(self.sig_eps, self.sig_eps_dt))
return res
def compute_gmfs_and_curves(getters, oq, monitor):
"""
:param getters:
a list of GmfGetter instances
:param oq:
an OqParam instance
:param monitor:
a Monitor instance
:returns:
a list of dictionaries with keys gmfcoll and hcurves
"""
results = []
for getter in getters:
with monitor('GmfGetter.init', measuremem=True):
getter.init()
hcurves = {} # key -> poes
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
duration = oq.investigation_time * oq.ses_per_logic_tree_path
with monitor('building hazard', measuremem=True):
gmfdata = numpy.fromiter(getter.gen_gmv(), getter.gmf_data_dt)
hazard = getter.get_hazard(data=gmfdata)
for sid, hazardr in zip(getter.sids, hazard):
for rlzi, array in hazardr.items():
if len(array) == 0: # no data
continue
with hc_mon:
gmvs = array['gmv']
for imti, imt in enumerate(getter.imtls):
poes = calc._gmvs_to_haz_curve(
gmvs[:, imti], oq.imtls[imt],
oq.investigation_time, duration)
hcurves[rsi2str(rlzi, sid, imt)] = poes
else: # fast lane
with monitor('building hazard', measuremem=True):
gmfdata = numpy.fromiter(getter.gen_gmv(), getter.gmf_data_dt)
indices = []
if oq.ground_motion_fields:
gmfdata.sort(order=('sid', 'rlzi', 'eid'))
start = stop = 0
for sid, rows in itertools.groupby(gmfdata['sid']):
for row in rows:
stop += 1
indices.append((sid, start, stop))
start = stop
else:
gmfdata = None
res = dict(gmfdata=gmfdata,
hcurves=hcurves,
gmdata=getter.gmdata,
taskno=monitor.task_no,
indices=numpy.array(indices, (U32, 3)))
if len(getter.gmdata):
results.append(res)
return results
def compute_gmfs_and_curves(getter, rlzs, monitor):
"""
:param eb_ruptures:
a list of blocks of EBRuptures of the same SESCollection
:param sitecol:
a :class:`openquake.hazardlib.site.SiteCollection` instance
:param imts:
a list of intensity measure type strings
:param rlzs_by_gsim:
a dictionary gsim -> associated realizations
:param monitor:
a Monitor instance
:returns:
a dictionary with keys gmfcoll and hcurves
"""
oq = monitor.oqparam
haz = {sid: {} for sid in getter.sids}
gmfcoll = {} # rlz -> gmfa
for rlz in rlzs:
gmfcoll[rlz] = []
for sid, gmvdict in zip(getter.sids, getter(rlz)):
if gmvdict:
for imti, imt in enumerate(getter.imts):
if oq.hazard_curves_from_gmfs:
try:
gmv = gmvdict[imt]
except KeyError:
# no gmv for the given imt, this may happen
pass
else:
haz[sid][imt, rlz] = gmv
for rec in gmvdict.get(imt, []):
gmfcoll[rlz].append(
(sid, rec['eid'], imti, rec['gmv']))
for rlz in gmfcoll:
gmfcoll[rlz] = numpy.array(gmfcoll[rlz], gmv_dt)
result = dict(gmfcoll=gmfcoll if oq.ground_motion_fields else None,
hcurves={})
if oq.hazard_curves_from_gmfs:
with monitor('building hazard curves', measuremem=False):
duration = oq.investigation_time * oq.ses_per_logic_tree_path
for sid, haz_by_imt_rlz in haz.items():
for imt, rlz in haz_by_imt_rlz:
gmvs = haz_by_imt_rlz[imt, rlz]['gmv']
poes = calc._gmvs_to_haz_curve(
gmvs, oq.imtls[imt], oq.investigation_time, duration)
key = rsi2str(rlz.ordinal, sid, imt)
result['hcurves'][key] = poes
return result
def compute_gmfs_and_curves(getter, oq, monitor):
"""
:param getter:
a GmfGetter instance
:param oq:
an OqParam instance
:param monitor:
a Monitor instance
:returns:
a dictionary with keys gmfcoll and hcurves
"""
with monitor('making contexts', measuremem=True):
getter.init()
grp_id = getter.grp_id
hcurves = {} # key -> poes
gmfcoll = {} # grp_id, rlz -> gmfa
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
duration = oq.investigation_time * oq.ses_per_logic_tree_path
for gsim in getter.rlzs_by_gsim:
with monitor('building hazard', measuremem=True):
gmfcoll[grp_id,
gsim] = data = numpy.fromiter(getter.gen_gmv(gsim),
gmf_data_dt)
hazard = getter.get_hazard(gsim, data)
for r, rlz in enumerate(getter.rlzs_by_gsim[gsim]):
hazardr = hazard[r]
lst = []
for sid in getter.sids:
for imti, imt in enumerate(getter.imts):
array = hazardr[sid, imti]
if len(array) == 0: # no data
continue
for rec in array:
lst.append((sid, rec['eid'], imti, rec['gmv']))
with hc_mon:
poes = calc._gmvs_to_haz_curve(
array['gmv'], oq.imtls[imt],
oq.investigation_time, duration)
hcurves[rsi2str(rlz.ordinal, sid, imt)] = poes
else: # fast lane
for gsim in getter.rlzs_by_gsim:
with monitor('building hazard', measuremem=True):
gmfcoll[grp_id, gsim] = numpy.fromiter(getter.gen_gmv(gsim),
gmf_data_dt)
return dict(gmfcoll=gmfcoll if oq.ground_motion_fields else None,
hcurves=hcurves,
gmdata=getter.gmdata)
def compute_gmfs_curves(self, monitor):
"""
:returns: a dict with keys gmdata, gmfdata, indices, hcurves
"""
oq = self.oqparam
dt = oq.gmf_data_dt()
with monitor('GmfGetter.init', measuremem=True):
self.init()
hcurves = {} # key -> poes
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
duration = oq.investigation_time * oq.ses_per_logic_tree_path
with monitor('building hazard', measuremem=True):
gmfdata = numpy.fromiter(self.gen_gmv(), dt)
hazard = self.get_hazard(data=gmfdata)
for sid, hazardr in zip(self.sids, hazard):
for rlzi, array in hazardr.items():
if len(array) == 0: # no data
continue
with hc_mon:
gmvs = array['gmv']
for imti, imt in enumerate(oq.imtls):
poes = _gmvs_to_haz_curve(gmvs[:, imti],
oq.imtls[imt],
oq.investigation_time,
duration)
hcurves[rsi2str(rlzi, sid, imt)] = poes
elif oq.ground_motion_fields: # fast lane
with monitor('building hazard', measuremem=True):
gmfdata = numpy.fromiter(self.gen_gmv(), dt)
else:
return {}
indices = []
gmfdata.sort(order=('sid', 'rlzi', 'eid'))
start = stop = 0
for sid, rows in itertools.groupby(gmfdata['sid']):
for row in rows:
stop += 1
indices.append((sid, start, stop))
start = stop
res = dict(gmfdata=gmfdata,
hcurves=hcurves,
gmdata=self.gmdata,
indices=numpy.array(indices, (U32, 3)))
return res
def compute_gmfs_curves(self, rlzs, monitor):
"""
:param rlzs: an array of shapeE
:returns: a dict with keys gmfdata, indices, hcurves
"""
oq = self.oqparam
mon = monitor('getting ruptures', measuremem=True)
hcurves = {} # key -> poes
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
gmfdata = self.get_gmfdata(mon) # returned later
hazard = self.get_hazard_by_sid(data=gmfdata)
for sid, hazardr in hazard.items():
dic = group_by_rlz(hazardr, rlzs)
for rlzi, array in dic.items():
with hc_mon:
gmvs = array['gmv']
for imti, imt in enumerate(oq.imtls):
poes = _gmvs_to_haz_curve(
gmvs[:, imti], oq.imtls[imt],
oq.ses_per_logic_tree_path)
hcurves[rsi2str(rlzi, sid, imt)] = poes
if not oq.ground_motion_fields:
return dict(gmfdata=(), hcurves=hcurves)
gmfdata = self.get_gmfdata(mon)
if len(gmfdata) == 0:
return dict(gmfdata=[])
indices = []
gmfdata.sort(order=('sid', 'eid'))
start = stop = 0
for sid, rows in itertools.groupby(gmfdata['sid']):
for row in rows:
stop += 1
indices.append((sid, start, stop))
start = stop
times = numpy.array([tup + (monitor.task_no, ) for tup in self.times],
time_dt)
times.sort(order='rup_id')
res = dict(gmfdata=gmfdata,
hcurves=hcurves,
times=times,
sig_eps=numpy.array(self.sig_eps, self.sig_eps_dt),
indices=numpy.array(indices, (U32, 3)))
return res
def compute_gmfs_curves(self, monitor):
"""
:returns: a dict with keys gmfdata, indices, hcurves
"""
oq = self.oqparam
with monitor('GmfGetter.init', measuremem=True):
self.init()
hcurves = {} # key -> poes
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
with monitor('building hazard', measuremem=True):
gmfdata = self.get_gmfdata() # returned later
hazard = self.get_hazard_by_sid(data=gmfdata)
for sid, hazardr in hazard.items():
dic = group_by_rlz(hazardr, self.eid2rlz)
for rlzi, array in dic.items():
with hc_mon:
gmvs = array['gmv']
for imti, imt in enumerate(oq.imtls):
poes = _gmvs_to_haz_curve(
gmvs[:, imti], oq.imtls[imt],
oq.ses_per_logic_tree_path)
hcurves[rsi2str(rlzi, sid, imt)] = poes
elif oq.ground_motion_fields: # fast lane
with monitor('building hazard', measuremem=True):
gmfdata = self.get_gmfdata()
else:
return dict(gmfdata=(), hcurves=hcurves)
if len(gmfdata) == 0:
return dict(gmfdata=[])
indices = []
gmfdata.sort(order=('sid', 'eid'))
start = stop = 0
for sid, rows in itertools.groupby(gmfdata['sid']):
for row in rows:
stop += 1
indices.append((sid, start, stop))
start = stop
res = dict(gmfdata=gmfdata,
hcurves=hcurves,
sig_eps=numpy.array(self.sig_eps, self.sig_eps_dt),
indices=numpy.array(indices, (U32, 3)))
return res
def compute_gmfs_and_curves(getter, oq, monitor):
"""
:param getter:
a GmfGetter instance
:param oq:
an OqParam instance
:param monitor:
a Monitor instance
:returns:
a dictionary with keys gmfcoll and hcurves
"""
with monitor('making contexts', measuremem=True):
getter.init()
grp_id = getter.grp_id
hcurves = {} # key -> poes
gmfcoll = {} # grp_id, rlz -> gmfa
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
duration = oq.investigation_time * oq.ses_per_logic_tree_path
with monitor('building hazard', measuremem=True):
gmfcoll[grp_id] = data = numpy.fromiter(getter.gen_gmv(),
getter.gmf_data_dt)
hazard = sorted(getter.get_hazard(data).items())
for rlzi, hazardr in hazard:
for sid in getter.sids:
array = hazardr[sid]
if len(array) == 0: # no data
continue
with hc_mon:
gmvs = array['gmv']
for imti, imt in enumerate(getter.imts):
poes = calc._gmvs_to_haz_curve(gmvs[:, imti],
oq.imtls[imt],
oq.investigation_time,
duration)
hcurves[rsi2str(rlzi, sid, imt)] = poes
else: # fast lane
with monitor('building hazard', measuremem=True):
gmfcoll[grp_id] = numpy.fromiter(getter.gen_gmv(),
getter.gmf_data_dt)
return dict(gmfcoll=gmfcoll if oq.ground_motion_fields else None,
hcurves=hcurves,
gmdata=getter.gmdata)
def compute_gmfs_curves(self, monitor):
"""
:returns: a dict with keys gmfdata, indices, hcurves
"""
oq = self.oqparam
with monitor('GmfGetter.init', measuremem=True):
self.init()
hcurves = {} # key -> poes
if oq.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
with monitor('building hazard', measuremem=True):
gmfdata = self.get_gmfdata() # returned later
hazard = self.get_hazard(data=gmfdata)
for sid, hazardr in hazard.items():
dic = group_by_rlz(hazardr, self.eid2rlz)
for rlzi, array in dic.items():
with hc_mon:
gmvs = array['gmv']
for imti, imt in enumerate(oq.imtls):
poes = _gmvs_to_haz_curve(
gmvs[:, imti], oq.imtls[imt],
oq.ses_per_logic_tree_path)
hcurves[rsi2str(rlzi, sid, imt)] = poes
elif oq.ground_motion_fields: # fast lane
with monitor('building hazard', measuremem=True):
gmfdata = self.get_gmfdata()
else:
return {}
if len(gmfdata) == 0:
return dict(gmfdata=[])
indices = []
gmfdata.sort(order=('sid', 'eid'))
start = stop = 0
for sid, rows in itertools.groupby(gmfdata['sid']):
for row in rows:
stop += 1
indices.append((sid, start, stop))
start = stop
res = dict(gmfdata=gmfdata, hcurves=hcurves,
sig_eps=numpy.array(self.sig_eps, self.sig_eps_dt),
indices=numpy.array(indices, (U32, 3)))
return res
def event_based(proxies, full_lt, oqparam, dstore, monitor):
"""
Compute GMFs and optionally hazard curves
"""
alldata = AccumDict(accum=[])
sig_eps = []
times = [] # rup_id, nsites, dt
hcurves = {} # key -> poes
trt_smr = proxies[0]['trt_smr']
fmon = monitor('filtering ruptures', measuremem=False)
cmon = monitor('computing gmfs', measuremem=False)
with dstore:
trt = full_lt.trts[trt_smr // len(full_lt.sm_rlzs)]
srcfilter = SourceFilter(dstore['sitecol'],
oqparam.maximum_distance(trt))
rupgeoms = dstore['rupgeoms']
rlzs_by_gsim = full_lt._rlzs_by_gsim(trt_smr)
param = vars(oqparam).copy()
param['imtls'] = oqparam.imtls
param['min_iml'] = oqparam.min_iml
param['maximum_distance'] = oqparam.maximum_distance(trt)
cmaker = ContextMaker(trt, rlzs_by_gsim, param)
min_mag = getdefault(oqparam.minimum_magnitude, trt)
for proxy in proxies:
t0 = time.time()
with fmon:
if proxy['mag'] < min_mag:
continue
sids = srcfilter.close_sids(proxy, trt)
if len(sids) == 0: # filtered away
continue
proxy.geom = rupgeoms[proxy['geom_id']]
ebr = proxy.to_ebr(cmaker.trt) # after the geometry is set
try:
computer = GmfComputer(ebr,
srcfilter.sitecol.filtered(sids),
cmaker, oqparam.correl_model,
oqparam.cross_correl,
oqparam._amplifier,
oqparam._sec_perils)
except FarAwayRupture:
continue
with cmon:
data = computer.compute_all(sig_eps)
dt = time.time() - t0
times.append((computer.ebrupture.id, len(computer.ctx.sids), dt))
for key in data:
alldata[key].extend(data[key])
for key, val in sorted(alldata.items()):
if key in 'eid sid rlz':
alldata[key] = U32(alldata[key])
else:
alldata[key] = F32(alldata[key])
gmfdata = strip_zeros(pandas.DataFrame(alldata))
if len(gmfdata) and oqparam.hazard_curves_from_gmfs:
hc_mon = monitor('building hazard curves', measuremem=False)
for (sid, rlz), df in gmfdata.groupby(['sid', 'rlz']):
with hc_mon:
poes = calc.gmvs_to_poes(df, oqparam.imtls,
oqparam.ses_per_logic_tree_path)
for m, imt in enumerate(oqparam.imtls):
hcurves[rsi2str(rlz, sid, imt)] = poes[m]
times = numpy.array([tup + (monitor.task_no, ) for tup in times], time_dt)
times.sort(order='rup_id')
if not oqparam.ground_motion_fields:
gmfdata = ()
return dict(gmfdata=gmfdata,
hcurves=hcurves,
times=times,
sig_eps=numpy.array(sig_eps, sig_eps_dt(oqparam.imtls)))