def rtree_filter(self):
"""
:returns: an RtreeFilter
"""
return RtreeFilter(self.src_filter.sitecol,
self.oqparam.maximum_distance,
self.src_filter.filename)
def plot_sites(calc_id):
"""
Plot the sites and the bounding boxes of the sources, enlarged by
the maximum distance
"""
import matplotlib.pyplot as p
from matplotlib.patches import Rectangle
dstore = datastore.read(calc_id)
sitecol = dstore['sitecol']
csm = dstore['composite_source_model']
oq = dstore['oqparam']
rfilter = RtreeFilter(sitecol, oq.maximum_distance)
fig = p.figure()
ax = fig.add_subplot(111)
ax.grid(True)
for src in csm.get_sources():
llcorner, width, height = rfilter.get_rectangle(src)
ax.add_patch(Rectangle(llcorner, width, height, fill=False))
p.scatter(sitecol.lons, sitecol.lats, marker='+')
p.show()
def filter_csm(self):
"""
:returns: (filtered CompositeSourceModel, SourceFilter)
"""
oq = self.oqparam
src_filter = SourceFilter(self.sitecol.complete, oq.maximum_distance)
monitor = self.monitor('prefiltering')
if (oq.prefilter_sources == 'numpy' or rtree is None):
csm = self.csm.filter(src_filter, monitor)
elif oq.prefilter_sources == 'rtree':
prefilter = RtreeFilter(self.sitecol.complete, oq.maximum_distance)
csm = self.csm.filter(prefilter, monitor)
else:
csm = self.csm.filter(BaseFilter(), monitor)
return csm, src_filter
def filter_csm(self):
"""
:returns: (filtered CompositeSourceModel, SourceFilter)
"""
oq = self.oqparam
mon = self.monitor('prefilter')
self.hdf5cache = self.datastore.hdf5cache()
src_filter = SourceFilter(self.sitecol.complete, oq.maximum_distance,
self.hdf5cache)
if (oq.prefilter_sources == 'numpy' or rtree is None):
csm = self.csm.filter(src_filter, mon)
elif oq.prefilter_sources == 'rtree':
prefilter = RtreeFilter(self.sitecol.complete, oq.maximum_distance,
self.hdf5cache)
csm = self.csm.filter(prefilter, mon)
else: # prefilter_sources='no'
csm = self.csm.filter(SourceFilter(None, {}), mon)
return csm, src_filter
def get_filter(self):
"""
:returns: a SourceFilter/RtreeFilter or None
"""
oq = self.oqparam
self.hdf5cache = self.datastore.hdf5cache()
self.src_filter = SourceFilter(self.sitecol.complete,
oq.maximum_distance, self.hdf5cache)
if 'ucerf' in oq.calculation_mode:
# do not preprocess
return
elif oq.prefilter_sources == 'rtree':
# rtree can be used only with processpool, otherwise one gets an
# RTreeError: Error in "Index_Create": Spatial Index Error:
# IllegalArgumentException: SpatialIndex::DiskStorageManager:
# Index/Data file cannot be read/writen.
src_filter = RtreeFilter(self.sitecol.complete,
oq.maximum_distance, self.hdf5cache)
else:
src_filter = self.src_filter
return src_filter
def filter_csm(self):
"""
:returns: (filtered CompositeSourceModel, SourceFilter)
"""
oq = self.oqparam
mon = self.monitor('prefilter')
self.hdf5cache = self.datastore.hdf5cache()
src_filter = SourceFilter(self.sitecol.complete, oq.maximum_distance,
self.hdf5cache)
if (oq.prefilter_sources == 'numpy' or rtree is None):
logging.info('Prefiltering the sources with numpy')
csm = self.csm.pfilter(src_filter, oq.concurrent_tasks, mon)
elif oq.prefilter_sources == 'rtree':
logging.info('Prefiltering the sources with rtree')
prefilter = RtreeFilter(self.sitecol.complete, oq.maximum_distance,
self.hdf5cache)
csm = self.csm.pfilter(prefilter, oq.concurrent_tasks, mon)
else: # prefilter_sources='no'
logging.info('Not prefiltering the sources')
csm = self.csm
logging.info('There are %d realizations', csm.info.get_num_rlzs())
return src_filter, csm