def __call__(self, sources, sites=None):
if sites is None:
sites = self.sitecol
if self.sitecol is None: # do not filter
for source in sources:
yield source, sites
return
for src in sources:
if not self.integration_distance: # do not filter
yield src, sites
elif self.use_rtree: # Rtree filtering, used in the controller
box = self.get_affected_box(src)
sids = numpy.array(sorted(self.index.intersection(box)))
if len(set(sids)) < len(sids):
# MS: sanity check against rtree bugs; what happened to me
# is that by following the advice in http://toblerity.org/rtree/performance.html#use-stream-loading
# self.index.intersection(box) started reporting duplicate
# and wrong sids!
raise ValueError('sids=%s' % sids)
if len(sids):
src.nsites = len(sids)
yield src, FilteredSiteCollection(sids, sites.complete)
else: # normal filtering, used in the workers
maxdist = self.integration_distance(src.tectonic_region_type)
with context(src):
s_sites = src.filter_sites_by_distance_to_source(
maxdist, sites)
if s_sites is not None:
src.nsites = len(s_sites)
yield src, s_sites
def __call__(self, sources, sites=None):
if sites is None:
sites = self.sitecol
if self.sitecol is None: # do not filter
for source in sources:
yield source, sites
return
for source in sources:
if self.use_rtree: # Rtree filtering
box = self.get_affected_box(source)
sids = numpy.array(sorted(self.index.intersection(box)))
if len(sids):
source.nsites = len(sids)
yield source, FilteredSiteCollection(sids, sites.complete)
elif not self.integration_distance:
yield source, sites
else: # normal filtering
try:
maxdist = self.integration_distance[
source.tectonic_region_type]
except TypeError: # passed a scalar, not a dictionary
maxdist = self.integration_distance
with context(source):
s_sites = source.filter_sites_by_distance_to_source(
maxdist, sites)
if s_sites is not None:
source.nsites = len(s_sites)
yield source, s_sites
def get_gmfs_by_imt(fname, sitecol, imts):
"""
Return a list of dictionaries with a ground motion field per IMT,
one dictionary per rupture.
:param fname: path to the CSV file
:param sitecol: the underlying site collection
:param imts: the IMTs corresponding to the columns in the CSV file
"""
dicts = []
with open(fname) as f:
for row in csv.reader(f):
indices = map(int, row[1].split())
sc = FilteredSiteCollection(indices, sitecol)
dic = AccumDict()
for imt, col in zip(imts, row[2:]):
gmf = numpy.array(map(float, col.split()))
dic[imt] = sc.expand(gmf, 0)
dic.tag = row[0]
dicts.append(dic)
return sorted(dicts, key=lambda dic: dic.tag)
def __iter__(self):
gmfset = []
for imt_str in self.imts:
gmfs = self.gmfs_by_imt[imt_str]
imt, sa_period, sa_damping = from_string(imt_str)
for rupture, gmf in zip(self.ruptures, gmfs):
if hasattr(rupture, 'indices'): # event based
indices = (list(range(len(self.sitecol)))
if rupture.indices is None else rupture.indices)
sites = FilteredSiteCollection(indices, self.sitecol)
else: # scenario
sites = self.sitecol
nodes = (GroundMotionFieldNode(gmv, site.location)
for site, gmv in zip(sites, gmf))
gmfset.append(
GroundMotionField(imt, sa_period, sa_damping, rupture.tag,
nodes))
yield GmfSet(gmfset, self.investigation_time)
def __call__(self, sources, sites=None):
if sites is None:
sites = self.sitecol
for source in sources:
if rtree: # Rtree filtering
box = self.get_affected_box(source)
sids = numpy.array(sorted(self.index.intersection(box)))
if len(sids):
source.nsites = len(sids)
yield source, FilteredSiteCollection(sids, sites.complete)
else: # normal filtering
with context(source):
s_sites = source.filter_sites_by_distance_to_source(
self.integration_distance[source.tectonic_region_type],
sites)
if s_sites is not None:
source.nsites = len(s_sites)
yield source, s_sites