def assoc_assets_sites(self, sitecol):
"""
:param sitecol: a sequence of sites
:returns: a pair (filtered sites, asset collection)
The new site collection is different from the original one
if some assets were discarded or if there were missing assets
for some sites.
"""
asset_hazard_distance = self.oqparam.asset_hazard_distance
siteobjects = geo.utils.GeographicObjects(
Site(sid, lon, lat)
for sid, lon, lat in zip(sitecol.sids, sitecol.lons, sitecol.lats))
assets_by_sid = general.AccumDict()
for assets in self.assetcol.assets_by_site():
if len(assets):
lon, lat = assets[0].location
site, distance = siteobjects.get_closest(lon, lat)
if distance <= asset_hazard_distance:
# keep the assets, otherwise discard them
assets_by_sid += {site.sid: list(assets)}
if not assets_by_sid:
raise AssetSiteAssociationError(
'Could not associate any site to any assets within the '
'asset_hazard_distance of %s km' % asset_hazard_distance)
mask = numpy.array([sid in assets_by_sid for sid in sitecol.sids])
assets_by_site = [assets_by_sid.get(sid, []) for sid in sitecol.sids]
return sitecol.filter(mask), asset.AssetCollection(
assets_by_site,
self.exposure.tagnames,
self.exposure.cost_calculator,
self.oqparam.time_event,
occupancy_periods=hdf5.array_of_vstr(
sorted(self.exposure.occupancy_periods)))
def get_sitecol_assetcol(oqparam, haz_sitecol=None, cost_types=()):
"""
:param oqparam: calculation parameters
:param haz_sitecol: the hazard site collection
:param cost_types: the expected cost types
:returns: (site collection, asset collection, discarded)
"""
global exposure
asset_hazard_distance = oqparam.asset_hazard_distance['default']
if exposure is None:
# haz_sitecol not extracted from the exposure
exposure = get_exposure(oqparam)
if haz_sitecol is None:
haz_sitecol = get_site_collection(oqparam)
if oqparam.region_grid_spacing:
haz_distance = oqparam.region_grid_spacing * 1.414
if haz_distance != asset_hazard_distance:
logging.info('Using asset_hazard_distance=%d km instead of %d km',
haz_distance, asset_hazard_distance)
else:
haz_distance = asset_hazard_distance
if haz_sitecol.mesh != exposure.mesh:
# associate the assets to the hazard sites
sitecol, assets_by, discarded = geo.utils.assoc(
exposure.assets_by_site, haz_sitecol, haz_distance, 'filter',
exposure.asset_refs)
assets_by_site = [[] for _ in sitecol.complete.sids]
num_assets = 0
for sid, assets in zip(sitecol.sids, assets_by):
assets_by_site[sid] = assets
num_assets += len(assets)
logging.info('Associated %d assets to %d sites', num_assets,
len(sitecol))
else:
# asset sites and hazard sites are the same
sitecol = haz_sitecol
assets_by_site = exposure.assets_by_site
discarded = []
logging.info('Read %d sites and %d assets from the exposure',
len(sitecol), sum(len(a) for a in assets_by_site))
assetcol = asset.AssetCollection(exposure, assets_by_site,
oqparam.time_event)
if assetcol.occupancy_periods:
missing = set(cost_types) - set(exposure.cost_types['name']) - set(
['occupants'])
else:
missing = set(cost_types) - set(exposure.cost_types['name'])
if missing and not oqparam.calculation_mode.endswith('damage'):
raise InvalidFile('The exposure %s is missing %s' %
(oqparam.inputs['exposure'], missing))
if (not oqparam.hazard_calculation_id and 'gmfs' not in oqparam.inputs
and 'hazard_curves' not in oqparam.inputs
and sitecol is not sitecol.complete):
# for predefined hazard you cannot reduce the site collection; instead
# you can in other cases, typically with a grid which is mostly empty
# (i.e. there are many hazard sites with no assets)
assetcol.reduce_also(sitecol)
return sitecol, assetcol, discarded
def get_sitecol_assetcol(oqparam, haz_sitecol):
"""
:param oqparam: calculation parameters
:param haz_sitecol: the hazard site collection
:returns: (site collection, asset collection) instances
"""
global exposure
if exposure is None:
# haz_sitecol not extracted from the exposure
exposure = get_exposure(oqparam)
if oqparam.region_grid_spacing and not oqparam.region:
# extract the hazard grid from the exposure
exposure.mesh = exposure.mesh.get_convex_hull().dilate(
oqparam.region_grid_spacing).discretize(
oqparam.region_grid_spacing)
haz_sitecol = get_site_collection(oqparam)
haz_distance = oqparam.region_grid_spacing
if haz_distance != oqparam.asset_hazard_distance:
logging.info('Using asset_hazard_distance=%d km instead of %d km',
haz_distance, oqparam.asset_hazard_distance)
else:
haz_distance = oqparam.asset_hazard_distance
if haz_sitecol.mesh != exposure.mesh:
# associate the assets to the hazard sites
tot_assets = sum(len(assets) for assets in exposure.assets_by_site)
mode = 'strict' if oqparam.region_grid_spacing else 'filter'
sitecol, assets_by = geo.utils.assoc(exposure.assets_by_site,
haz_sitecol, haz_distance, mode)
assets_by_site = [[] for _ in sitecol.complete.sids]
num_assets = 0
for sid, assets in zip(sitecol.sids, assets_by):
assets_by_site[sid] = assets
num_assets += len(assets)
logging.info('Associated %d assets to %d sites', num_assets,
len(sitecol))
if num_assets < tot_assets:
logging.warn(
'Discarded %d assets outside the '
'asset_hazard_distance of %d km', tot_assets - num_assets,
haz_distance)
else:
# asset sites and hazard sites are the same
sitecol = haz_sitecol
assets_by_site = exposure.assets_by_site
asset_refs = [
exposure.asset_refs[asset.ordinal] for assets in assets_by_site
for asset in assets
]
assetcol = asset.AssetCollection(asset_refs, assets_by_site,
exposure.tagcol, exposure.cost_calculator,
oqparam.time_event,
exposure.occupancy_periods)
return sitecol, assetcol
def read_exposure(self, haz_sitecol=None):
"""
Read the exposure, the riskmodel and update the attributes .exposure,
.sitecol, .assetcol
"""
logging.info('Reading the exposure')
with self.monitor('reading exposure', autoflush=True):
self.exposure = readinput.get_exposure(self.oqparam)
mesh, assets_by_site = (readinput.get_mesh_assets_by_site(
self.oqparam, self.exposure))
if haz_sitecol:
tot_assets = sum(len(assets) for assets in assets_by_site)
all_sids = haz_sitecol.complete.sids
sids = set(haz_sitecol.sids)
# associate the assets to the hazard sites
asset_hazard_distance = self.oqparam.asset_hazard_distance
siteobjects = geo.utils.GeographicObjects(
Site(sid, lon, lat) for sid, lon, lat in zip(
haz_sitecol.sids, haz_sitecol.lons, haz_sitecol.lats))
assets_by_sid = general.AccumDict(accum=[])
for assets in assets_by_site:
if len(assets):
lon, lat = assets[0].location
site, distance = siteobjects.get_closest(lon, lat)
if site.sid in sids and distance <= asset_hazard_distance:
# keep the assets, otherwise discard them
assets_by_sid += {site.sid: list(assets)}
if not assets_by_sid:
raise AssetSiteAssociationError(
'Could not associate any site to any assets within the '
'asset_hazard_distance of %s km' % asset_hazard_distance)
mask = numpy.array([sid in assets_by_sid for sid in all_sids])
assets_by_site = [assets_by_sid[sid] for sid in all_sids]
num_assets = sum(len(assets) for assets in assets_by_site)
logging.info('Associated %d/%d assets to the hazard sites',
num_assets, tot_assets)
self.sitecol = haz_sitecol.complete.filter(mask)
else: # use the exposure sites as hazard sites
self.sitecol = readinput.get_site_collection(self.oqparam, mesh)
self.assetcol = asset.AssetCollection(
self.exposure.asset_refs,
assets_by_site,
self.exposure.tagcol,
self.exposure.cost_calculator,
self.oqparam.time_event,
occupancy_periods=hdf5.array_of_vstr(
sorted(self.exposure.occupancy_periods)))
logging.info('Considering %d assets on %d sites', len(self.assetcol),
len(self.sitecol))
def get_sitecol_assetcol(oqparam, exposure):
"""
:param oqparam:
an :class:`openquake.commonlib.oqvalidation.OqParam` instance
:returns:
the site collection and the asset collection
"""
assets_by_loc = groupby(exposure.assets, key=lambda a: a.location)
lons, lats = zip(*sorted(assets_by_loc))
mesh = geo.Mesh(numpy.array(lons), numpy.array(lats))
sitecol = get_site_collection(oqparam, mesh)
assets_by_site = []
for lonlat in zip(sitecol.lons, sitecol.lats):
assets = assets_by_loc[lonlat]
assets_by_site.append(sorted(assets, key=operator.attrgetter('idx')))
assetcol = asset.AssetCollection(
assets_by_site, exposure.assets_by_tag, exposure.cost_calculator,
oqparam.time_event, time_events=hdf5.array_of_vstr(
sorted(exposure.time_events)))
return sitecol, assetcol
def get_sitecol_assetcol(oqparam, haz_sitecol=None, cost_types=()):
"""
:param oqparam: calculation parameters
:param haz_sitecol: the hazard site collection
:param cost_types: the expected cost types
:returns: (site collection, asset collection) instances
"""
global exposure
if exposure is None:
# haz_sitecol not extracted from the exposure
exposure = get_exposure(oqparam)
if haz_sitecol is None:
haz_sitecol = get_site_collection(oqparam)
missing = set(cost_types) - set(exposure.cost_types['name']) - set(
['occupants']) # TODO: remove occupants and fragility special cases
if missing and not oqparam.calculation_mode.endswith('damage'):
expo = oqparam.inputs.get('exposure', '')
raise InvalidFile(
'Expected cost types %s but the exposure %r contains %s' %
(cost_types, expo, exposure.cost_types['name']))
if oqparam.region_grid_spacing and not oqparam.region:
# extract the hazard grid from the exposure
poly = exposure.mesh.get_convex_hull()
mesh = poly.dilate(oqparam.region_grid_spacing).discretize(
oqparam.region_grid_spacing)
if len(mesh) > len(haz_sitecol):
raise LargeExposureGrid(mesh, haz_sitecol.mesh,
oqparam.region_grid_spacing)
haz_sitecol = get_site_collection(oqparam, mesh) # redefine
haz_distance = oqparam.region_grid_spacing
if haz_distance != oqparam.asset_hazard_distance:
logging.info('Using asset_hazard_distance=%d km instead of %d km',
haz_distance, oqparam.asset_hazard_distance)
else:
haz_distance = oqparam.asset_hazard_distance
if haz_sitecol.mesh != exposure.mesh:
# associate the assets to the hazard sites
tot_assets = sum(len(assets) for assets in exposure.assets_by_site)
mode = 'strict' if oqparam.region_grid_spacing else 'filter'
sitecol, assets_by = geo.utils.assoc(exposure.assets_by_site,
haz_sitecol, haz_distance, mode)
assets_by_site = [[] for _ in sitecol.complete.sids]
num_assets = 0
for sid, assets in zip(sitecol.sids, assets_by):
assets_by_site[sid] = assets
num_assets += len(assets)
logging.info('Associated %d assets to %d sites', num_assets,
len(sitecol))
if num_assets < tot_assets:
logging.warn(
'Discarded %d assets outside the '
'asset_hazard_distance of %d km', tot_assets - num_assets,
haz_distance)
else:
# asset sites and hazard sites are the same
sitecol = haz_sitecol
assets_by_site = exposure.assets_by_site
asset_refs = numpy.array([
exposure.asset_refs[asset.ordinal] for assets in assets_by_site
for asset in assets
])
assetcol = asset.AssetCollection(asset_refs, assets_by_site,
exposure.tagcol, exposure.cost_calculator,
oqparam.time_event,
exposure.occupancy_periods)
return sitecol, assetcol
def get_sitecol_assetcol(oqparam, haz_sitecol=None, cost_types=()):
"""
:param oqparam: calculation parameters
:param haz_sitecol: the hazard site collection
:param cost_types: the expected cost types
:returns: (site collection, asset collection) instances
"""
global exposure
if exposure is None:
# haz_sitecol not extracted from the exposure
exposure = get_exposure(oqparam)
if haz_sitecol is None:
haz_sitecol = get_site_collection(oqparam)
missing = set(cost_types) - set(exposure.cost_types['name']) - set(
['occupants']) # TODO: remove occupants and fragility special cases
if missing and not oqparam.calculation_mode.endswith('damage'):
expo = oqparam.inputs.get('exposure', '')
raise InvalidFile(
'Expected cost types %s but the exposure %r contains %s' %
(cost_types, expo, exposure.cost_types['name']))
if oqparam.region_grid_spacing:
haz_distance = oqparam.region_grid_spacing
if haz_distance != oqparam.asset_hazard_distance:
logging.info('Using asset_hazard_distance=%d km instead of %d km',
haz_distance, oqparam.asset_hazard_distance)
else:
haz_distance = oqparam.asset_hazard_distance
if haz_sitecol.mesh != exposure.mesh:
# associate the assets to the hazard sites
tot_assets = sum(len(assets) for assets in exposure.assets_by_site)
mode = 'filter' if oqparam.region_grid_spacing else 'warn'
sitecol, assets_by, discarded = geo.utils.assoc(
exposure.assets_by_site, haz_sitecol, haz_distance, mode)
if oqparam.region_grid_spacing: # it is normal to discard sites
discarded = []
assets_by_site = [[] for _ in sitecol.complete.sids]
num_assets = 0
for sid, assets in zip(sitecol.sids, assets_by):
assets_by_site[sid] = assets
num_assets += len(assets)
logging.info('Associated %d assets to %d sites', num_assets,
len(sitecol))
if num_assets < tot_assets:
logging.warn(
'Discarded %d assets outside the '
'asset_hazard_distance of %d km', tot_assets - num_assets,
haz_distance)
else:
# asset sites and hazard sites are the same
sitecol = haz_sitecol
assets_by_site = exposure.assets_by_site
discarded = []
asset_refs = numpy.array([
exposure.asset_refs[asset.ordinal] for assets in assets_by_site
for asset in assets
])
assetcol = asset.AssetCollection(asset_refs, assets_by_site,
exposure.tagcol, exposure.cost_calculator,
oqparam.time_event,
exposure.occupancy_periods)
if (not oqparam.hazard_calculation_id and 'gmfs' not in oqparam.inputs
and 'hazard_curves' not in oqparam.inputs):
# TODO: think if we should remove this in presence of GMF-correlation
assetcol = assetcol.reduce_also(sitecol)
return sitecol, assetcol, discarded
