# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2018-2022 GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
import time
import operator
import numpy
from openquake.baselib import general, hdf5
from openquake.baselib.python3compat import decode
from openquake.hazardlib import probability_map, stats
from openquake.hazardlib.source.rupture import (
BaseRupture, RuptureProxy, to_arrays)
from openquake.commonlib import datastore
U16 = numpy.uint16
U32 = numpy.uint32
F32 = numpy.float32
by_taxonomy = operator.attrgetter('taxonomy')
code2cls = BaseRupture.init()
weight = operator.itemgetter('n_occ')
[docs]class NotFound(Exception):
pass
[docs]def build_stat_curve(pcurve, imtls, stat, weights):
"""
Build statistics by taking into account IMT-dependent weights
"""
poes = pcurve.array.T # shape R, L
assert len(poes) == len(weights), (len(poes), len(weights))
L = imtls.size
array = numpy.zeros((L, 1))
if isinstance(weights, list): # IMT-dependent weights
# this is slower since the arrays are shorter
for imt in imtls:
slc = imtls(imt)
ws = [w[imt] for w in weights]
if sum(ws) == 0: # expect no data for this IMT
continue
array[slc, 0] = stat(poes[:, slc], ws)
else:
array[:, 0] = stat(poes, weights)
return probability_map.ProbabilityCurve(array)
[docs]def sig_eps_dt(imts):
"""
:returns: a composite data type for the sig_eps output
"""
lst = [('eid', U32), ('rlz_id', U16)]
for imt in imts:
lst.append(('sig_inter_' + imt, F32))
for imt in imts:
lst.append(('eps_inter_' + imt, F32))
return numpy.dtype(lst)
[docs]class HcurvesGetter(object):
"""
Read the contribution to the hazard curves coming from each source
in a calculation with a source specific logic tree
"""
def __init__(self, dstore):
self.dstore = dstore
self.imtls = dstore['oqparam'].imtls
self.full_lt = dstore['full_lt']
self.sslt = self.full_lt.source_model_lt.decompose()
self.source_info = dstore['source_info'][:]
self.disagg_by_grp = dstore['disagg_by_grp'][:]
gsim_lt = self.full_lt.gsim_lt
self.bysrc = {} # src_id -> (start, gsims, weights)
for row in self.source_info:
dis = self.disagg_by_grp[row['grp_id']]
trt = decode(dis['grp_trt'])
weights = gsim_lt.get_weights(trt)
self.bysrc[decode(row['source_id'])] = (
dis['grp_start'], gsim_lt.values[trt], weights)
[docs] def get_hcurve(self, src_id, imt=None, site_id=0, gsim_idx=None):
"""
Return the curve associated to the given src_id, imt and gsim_idx
as an array of length L
"""
assert ';' in src_id, src_id # must be a realization specific src_id
imt_slc = self.imtls(imt) if imt else slice(None)
start, gsims, weights = self.bysrc[src_id]
dset = self.dstore['_poes']
if gsim_idx is None:
curves = dset[start:start + len(gsims), site_id, imt_slc]
return weights @ curves
return dset[start + gsim_idx, site_id, imt_slc]
[docs] def get_hcurves(self, src, imt=None, site_id=0, gsim_idx=None):
"""
Return the curves associated to the given src, imt and gsim_idx
as an array of shape (R, L)
"""
assert ';' not in src, src # not a rlz specific source ID
curves = []
for i in range(self.sslt[src].num_paths):
src_id = '%s;%d' % (src, i)
curves.append(self.get_hcurve(src_id, imt, site_id, gsim_idx))
return numpy.array(curves)
[docs] def get_mean_hcurve(self, src=None, imt=None, site_id=0, gsim_idx=None):
"""
Return the mean curve associated to the given src, imt and gsim_idx
as an array of shape L
"""
if src is None:
hcurves = [self.get_mean_hcurve(src) for src in self.sslt]
return general.agg_probs(*hcurves)
weights = [rlz.weight for rlz in self.sslt[src]]
curves = self.get_hcurves(src, imt, site_id, gsim_idx)
return weights @ curves
[docs]class PmapGetter(object):
"""
Read hazard curves from the datastore for all realizations or for a
specific realization.
:param dstore: a DataStore instance or file system path to it
:param sids: the subset of sites to consider (if None, all sites)
"""
def __init__(self, dstore, weights, slices, imtls=(), poes=()):
self.filename = dstore if isinstance(dstore, str) else dstore.filename
if len(weights[0].dic) == 1: # no weights by IMT
self.weights = numpy.array([w['weight'] for w in weights])
else:
self.weights = weights
self.imtls = imtls
self.poes = poes
self.num_rlzs = len(weights)
self.eids = None
self.rlzs_by_g = dstore['rlzs_by_g'][()]
self.slices = slices
self._pmap = {}
@property
def sids(self):
self.init()
return list(self._pmap)
@property
def imts(self):
return list(self.imtls)
@property
def L(self):
return self.imtls.size
@property
def N(self):
self.init()
return len(self._pmap)
@property
def M(self):
return len(self.imtls)
@property
def R(self):
return len(self.weights)
[docs] def init(self):
"""
Build the probability curves from the underlying dataframes
"""
if self._pmap:
return self._pmap
G = len(self.rlzs_by_g)
with hdf5.File(self.filename) as dstore:
for start, stop in self.slices:
poes_df = dstore.read_df('_poes', slc=slice(start, stop))
for sid, df in poes_df.groupby('sid'):
try:
array = self._pmap[sid].array
except KeyError:
array = numpy.zeros((self.L, G))
self._pmap[sid] = probability_map.ProbabilityCurve(
array)
array[df.lid, df.gid] = df.poe
return self._pmap
# used in risk calculations where there is a single site per getter
[docs] def get_hazard(self, gsim=None):
"""
:param gsim: ignored
:returns: a probability curve of shape (L, R) for the given site
"""
self.init()
if not self.sids:
# this happens when the poes are all zeros, as in
# classical_risk/case_3 for the first site
return probability_map.ProbabilityCurve(
numpy.zeros((self.L, self.num_rlzs)))
return self.get_pcurve(self.sids[0])
[docs] def get_pcurve(self, sid): # used in classical
"""
:returns: a ProbabilityCurve of shape L, R
"""
pmap = self.init()
pc0 = probability_map.ProbabilityCurve(
numpy.zeros((self.L, self.num_rlzs)))
try:
pc0.combine(pmap[sid], self.rlzs_by_g)
except KeyError: # no hazard for sid
pass
return pc0
[docs] def get_mean(self):
"""
Compute the mean curve as a ProbabilityMap
:param grp:
if not None must be a string of the form "grp-XX"; in that case
returns the mean considering only the contribution for group XX
"""
self.init()
if len(self.weights) == 1: # one realization
# the standard deviation is zero
pmap = self.get(0)
for sid, pcurve in pmap.items():
array = numpy.zeros(pcurve.array.shape)
array[:, 0] = pcurve.array[:, 0]
pcurve.array = array
return pmap
L = self.imtls.size
pmap = probability_map.ProbabilityMap.build(L, 1, self.sids)
for sid in self.sids:
pmap[sid] = build_stat_curve(
self.get_pcurve(sid),
self.imtls, stats.mean_curve, self.weights)
return pmap
time_dt = numpy.dtype(
[('rup_id', U32), ('nsites', U16), ('time', F32), ('task_no', U16)])
[docs]def get_rupture_getters(dstore, ct=0, slc=slice(None), srcfilter=None):
"""
:param dstore: a :class:`openquake.commonlib.datastore.DataStore`
:param ct: number of concurrent tasks
:returns: a list of RuptureGetters
"""
full_lt = dstore['full_lt']
rlzs_by_gsim = full_lt.get_rlzs_by_gsim()
rup_array = dstore['ruptures'][slc]
if len(rup_array) == 0:
raise NotFound('There are no ruptures in %s' % dstore)
rup_array.sort(order=['trt_smr', 'n_occ'])
scenario = 'scenario' in dstore['oqparam'].calculation_mode
proxies = [RuptureProxy(rec, scenario) for rec in rup_array]
maxweight = rup_array['n_occ'].sum() / (ct / 2 or 1)
rgetters = []
for block in general.block_splitter(
proxies, maxweight, operator.itemgetter('n_occ'),
key=operator.itemgetter('trt_smr')):
trt_smr = block[0]['trt_smr']
rbg = rlzs_by_gsim[trt_smr]
rg = RuptureGetter(block, dstore.filename, trt_smr,
full_lt.trt_by(trt_smr), rbg)
rgetters.append(rg)
return rgetters
[docs]def get_ebruptures(dstore):
"""
Extract EBRuptures from the datastore
"""
ebrs = []
for rgetter in get_rupture_getters(dstore):
for proxy in rgetter.get_proxies():
ebrs.append(proxy.to_ebr(rgetter.trt))
return ebrs
[docs]def line(points):
return '(%s)' % ', '.join('%.5f %.5f %.5f' % tuple(p) for p in points)
[docs]def multiline(array3RC):
"""
:param array3RC: array of shape (3, R, C)
:returns: a MULTILINESTRING
"""
D, R, C = array3RC.shape
assert D == 3, D
lines = 'MULTILINESTRING(%s)' % ', '.join(
line(array3RC[:, r, :].T) for r in range(R))
return lines
# this is never called directly; get_rupture_getters is used instead
[docs]class RuptureGetter(object):
"""
:param proxies:
a list of RuptureProxies
:param filename:
path to the HDF5 file containing a 'rupgeoms' dataset
:param trt_smr:
source group index
:param trt:
tectonic region type string
:param rlzs_by_gsim:
dictionary gsim -> rlzs for the group
"""
def __init__(self, proxies, filename, trt_smr, trt, rlzs_by_gsim):
self.proxies = proxies
self.weight = sum(proxy['n_occ'] for proxy in proxies)
self.filename = filename
self.trt_smr = trt_smr
self.trt = trt
self.rlzs_by_gsim = rlzs_by_gsim
self.num_events = sum(int(proxy['n_occ']) for proxy in proxies)
@property
def num_ruptures(self):
return len(self.proxies)
[docs] def get_rupdict(self): # used in extract_event_info and show rupture
"""
:returns: a dictionary with the parameters of the rupture
"""
assert len(self.proxies) == 1, 'Please specify a slice of length 1'
dic = {'trt': self.trt}
with datastore.read(self.filename) as dstore:
rupgeoms = dstore['rupgeoms']
rec = self.proxies[0].rec
geom = rupgeoms[rec['id']]
arrays = to_arrays(geom) # one array per surface
for a, array in enumerate(arrays):
dic['surface_%d' % a] = multiline(array)
rupclass, surclass = code2cls[rec['code']]
dic['rupture_class'] = rupclass.__name__
dic['surface_class'] = surclass.__name__
dic['hypo'] = rec['hypo']
dic['occurrence_rate'] = rec['occurrence_rate']
dic['trt_smr'] = rec['trt_smr']
dic['n_occ'] = rec['n_occ']
dic['seed'] = rec['seed']
dic['mag'] = rec['mag']
dic['srcid'] = rec['source_id']
return dic
[docs] def get_proxies(self, min_mag=0):
"""
:returns: a list of RuptureProxies
"""
proxies = []
with datastore.read(self.filename) as dstore:
rupgeoms = dstore['rupgeoms']
for proxy in self.proxies:
if proxy['mag'] < min_mag:
continue
proxy.geom = rupgeoms[proxy['geom_id']]
proxies.append(proxy)
return proxies
# called in ebrisk calculations
[docs] def split(self, srcfilter, maxw):
"""
:returns: RuptureProxies with weight < maxw
"""
proxies = []
for proxy in self.proxies:
sids = srcfilter.close_sids(proxy.rec, self.trt)
if len(sids):
proxies.append(proxy)
rgetters = []
for block in general.block_splitter(proxies, maxw, weight):
rg = RuptureGetter(block, self.filename, self.trt_smr, self.trt,
self.rlzs_by_gsim)
rgetters.append(rg)
return rgetters
def __len__(self):
return len(self.proxies)
def __repr__(self):
wei = ' [w=%d]' % self.weight if hasattr(self, 'weight') else ''
return '<%s trt_smr=%d, %d rupture(s)%s>' % (
self.__class__.__name__, self.trt_smr, len(self), wei)