def all_cost_types(self):
"""
Return the cost types of the computation (including `occupants`
if it is there) in order.
"""
# rt has the form 'vulnerability/structural', 'fragility/...', ...
costtypes = sorted(rt.rsplit('/')[1] for rt in self.risk_files)
if not costtypes and self.hazard_calculation_id:
with util.read(self.hazard_calculation_id) as ds:
parent = ds['oqparam']
self._risk_files = get_risk_files(parent.inputs)
costtypes = sorted(rt.rsplit('/')[1] for rt in self.risk_files)
return costtypes
def all_cost_types(self):
"""
Return the cost types of the computation (including `occupants`
if it is there) in order.
"""
# rt has the form 'vulnerability/structural', 'fragility/...', ...
costtypes = set(rt.rsplit('/')[1] for rt in self.risk_files)
if not costtypes and self.hazard_calculation_id:
with util.read(self.hazard_calculation_id) as ds:
parent = ds['oqparam']
self._risk_files = get_risk_files(parent.inputs)
costtypes = set(rt.rsplit('/')[1] for rt in self.risk_files)
return sorted(costtypes)
def __init__(self, **names_vals):
# support legacy names
for name in list(names_vals):
if name == 'quantile_hazard_curves':
names_vals['quantiles'] = names_vals.pop(name)
elif name == 'mean_hazard_curves':
names_vals['mean'] = names_vals.pop(name)
elif name == 'max':
names_vals['max'] = names_vals.pop(name)
super().__init__(**names_vals)
job_ini = self.inputs['job_ini']
if 'calculation_mode' not in names_vals:
raise InvalidFile('Missing calculation_mode in %s' % job_ini)
if 'region_constraint' in names_vals:
if 'region' in names_vals:
raise InvalidFile('You cannot have both region and '
'region_constraint in %s' % job_ini)
logging.warning(
'region_constraint is obsolete, use region instead')
self.region = valid.wkt_polygon(
names_vals.pop('region_constraint'))
self.risk_investigation_time = (self.risk_investigation_time
or self.investigation_time)
if ('intensity_measure_types_and_levels' in names_vals
and 'intensity_measure_types' in names_vals):
logging.warning('Ignoring intensity_measure_types since '
'intensity_measure_types_and_levels is set')
if 'iml_disagg' in names_vals:
self.iml_disagg.pop('default')
# normalize things like SA(0.10) -> SA(0.1)
self.iml_disagg = {
str(from_string(imt)): val
for imt, val in self.iml_disagg.items()
}
self.hazard_imtls = self.iml_disagg
if 'intensity_measure_types_and_levels' in names_vals:
raise InvalidFile(
'Please remove the intensity_measure_types_and_levels '
'from %s: they will be inferred from the iml_disagg '
'dictionary' % job_ini)
elif 'intensity_measure_types_and_levels' in names_vals:
self.hazard_imtls = self.intensity_measure_types_and_levels
delattr(self, 'intensity_measure_types_and_levels')
elif 'intensity_measure_types' in names_vals:
self.hazard_imtls = dict.fromkeys(self.intensity_measure_types)
delattr(self, 'intensity_measure_types')
self._risk_files = get_risk_files(self.inputs)
self.check_source_model()
if self.hazard_precomputed() and self.job_type == 'risk':
self.check_missing('site_model', 'debug')
self.check_missing('gsim_logic_tree', 'debug')
self.check_missing('source_model_logic_tree', 'debug')
# check the gsim_logic_tree
if self.inputs.get('gsim_logic_tree'):
if self.gsim != '[FromFile]':
raise InvalidFile('%s: if `gsim_logic_tree_file` is set, there'
' must be no `gsim` key' % job_ini)
path = os.path.join(self.base_path, self.inputs['gsim_logic_tree'])
gsim_lt = logictree.GsimLogicTree(path, ['*'])
# check the number of branchsets
branchsets = len(gsim_lt._ltnode)
if 'scenario' in self.calculation_mode and branchsets > 1:
raise InvalidFile(
'%s: %s for a scenario calculation must contain a single '
'branchset, found %d!' % (job_ini, path, branchsets))
# check the IMTs vs the GSIMs
self._gsims_by_trt = gsim_lt.values
for gsims in gsim_lt.values.values():
self.check_gsims(gsims)
elif self.gsim is not None:
self.check_gsims([valid.gsim(self.gsim, self.base_path)])
# check inputs
unknown = set(self.inputs) - self.KNOWN_INPUTS
if unknown:
raise ValueError('Unknown key %s_file in %s' %
(unknown.pop(), self.inputs['job_ini']))
# checks for disaggregation
if self.calculation_mode == 'disaggregation':
if not self.poes_disagg and not self.iml_disagg:
raise InvalidFile('poes_disagg or iml_disagg must be set '
'in %(job_ini)s' % self.inputs)
elif self.poes_disagg and self.iml_disagg:
raise InvalidFile(
'%s: iml_disagg and poes_disagg cannot be set '
'at the same time' % job_ini)
for k in ('mag_bin_width', 'distance_bin_width',
'coordinate_bin_width', 'num_epsilon_bins'):
if k not in vars(self):
raise InvalidFile('%s must be set in %s' % (k, job_ini))
# checks for classical_damage
if self.calculation_mode == 'classical_damage':
if self.conditional_loss_poes:
raise InvalidFile('%s: conditional_loss_poes are not defined '
'for classical_damage calculations' %
job_ini)
# checks for event_based_risk
if (self.calculation_mode == 'event_based_risk'
and self.asset_correlation not in (0, 1)):
raise ValueError('asset_correlation != {0, 1} is no longer'
' supported')
# checks for ebrisk
if self.calculation_mode == 'ebrisk':
if self.risk_investigation_time is None:
raise InvalidFile('Please set the risk_investigation_time in'
' %s' % job_ini)
# check for GMFs from file
if (self.inputs.get('gmfs', '').endswith('.csv')
and 'sites' not in self.inputs and self.sites is None):
raise InvalidFile('%s: You forgot sites|sites_csv' % job_ini)
elif self.inputs.get('gmfs', '').endswith('.xml'):
raise InvalidFile('%s: GMFs in XML are not supported anymore' %
job_ini)
# checks for event_based
if 'event_based' in self.calculation_mode:
if self.ses_per_logic_tree_path >= TWO32:
raise ValueError('ses_per_logic_tree_path too big: %d' %
self.ses_per_logic_tree_path)
if self.number_of_logic_tree_samples >= TWO16:
raise ValueError('number_of_logic_tree_samples too big: %d' %
self.number_of_logic_tree_samples)
# check grid + sites
if self.region_grid_spacing and ('sites' in self.inputs or self.sites):
raise ValueError('You are specifying grid and sites at the same '
'time: which one do you want?')
# check for amplification
if 'amplification' in self.inputs and self.imtls:
check_same_levels(self.imtls)
def risk_files(self):
try:
return self._risk_files
except AttributeError:
self._risk_files = get_risk_files(self.inputs)
return self._risk_files
def __init__(self, **names_vals):
super().__init__(**names_vals)
job_ini = self.inputs['job_ini']
if 'calculation_mode' not in names_vals:
raise InvalidFile('Missing calculation_mode in %s' % job_ini)
if 'region_constraint' in names_vals:
if 'region' in names_vals:
raise InvalidFile('You cannot have both region and '
'region_constraint in %s' % job_ini)
logging.warn('region_constraint is obsolete, use region instead')
self.region = valid.wkt_polygon(
names_vals.pop('region_constraint'))
self.risk_investigation_time = (self.risk_investigation_time
or self.investigation_time)
if ('intensity_measure_types_and_levels' in names_vals
and 'intensity_measure_types' in names_vals):
logging.warn('Ignoring intensity_measure_types since '
'intensity_measure_types_and_levels is set')
if 'iml_disagg' in names_vals:
self.hazard_imtls = self.iml_disagg
if 'intensity_measure_types_and_levels' in names_vals:
raise InvalidFile(
'Please remove the intensity_measure_types_and_levels '
'from %s: they will be inferred from the iml_disagg '
'dictionary' % job_ini)
elif 'intensity_measure_types_and_levels' in names_vals:
self.hazard_imtls = self.intensity_measure_types_and_levels
delattr(self, 'intensity_measure_types_and_levels')
elif 'intensity_measure_types' in names_vals:
self.hazard_imtls = dict.fromkeys(self.intensity_measure_types)
delattr(self, 'intensity_measure_types')
self._file_type, self._risk_files = get_risk_files(self.inputs)
self.check_source_model()
if self.hazard_precomputed() and self.job_type == 'risk':
self.check_missing('site_model', 'warn')
self.check_missing('gsim_logic_tree', 'warn')
self.check_missing('source_model_logic_tree', 'warn')
# check the gsim_logic_tree
if self.inputs.get('gsim_logic_tree'):
if not isinstance(self.gsim, valid.FromFile):
raise InvalidFile('%s: if `gsim_logic_tree_file` is set, there'
' must be no `gsim` key' % job_ini)
path = os.path.join(self.base_path, self.inputs['gsim_logic_tree'])
gsim_lt = logictree.GsimLogicTree(path, ['*'])
# check the number of branchsets
branchsets = len(gsim_lt._ltnode)
if 'scenario' in self.calculation_mode and branchsets > 1:
raise InvalidFile(
'%s: %s for a scenario calculation must contain a single '
'branchset, found %d!' % (job_ini, path, branchsets))
# check the IMTs vs the GSIMs
self._gsims_by_trt = gsim_lt.values
for gsims in self._gsims_by_trt.values():
self.check_gsims(gsims)
elif self.gsim is not None:
self.check_gsims([self.gsim])
# checks for hazard outputs
if not self.hazard_stats():
if self.uniform_hazard_spectra:
raise InvalidFile(
'%(job_ini)s: uniform_hazard_spectra=true is inconsistent '
'with mean_hazard_curves=false' % self.inputs)
elif self.hazard_maps:
raise InvalidFile(
'%(job_ini)s: hazard_maps=true is inconsistent '
'with mean_hazard_curves=false' % self.inputs)
# checks for disaggregation
if self.calculation_mode == 'disaggregation':
if not self.poes_disagg and not self.iml_disagg:
raise InvalidFile('poes_disagg or iml_disagg must be set '
'in %(job_ini)s' % self.inputs)
elif self.poes_disagg and self.iml_disagg:
raise InvalidFile(
'%s: iml_disagg and poes_disagg cannot be set '
'at the same time' % job_ini)
for k in ('mag_bin_width', 'distance_bin_width',
'coordinate_bin_width', 'num_epsilon_bins'):
if k not in vars(self):
raise InvalidFile('%s must be set in %s' % (k, job_ini))
# checks for classical_damage
if self.calculation_mode == 'classical_damage':
if self.conditional_loss_poes:
raise InvalidFile('%s: conditional_loss_poes are not defined '
'for classical_damage calculations' %
job_ini)
# checks for event_based_risk
if (self.calculation_mode == 'event_based_risk'
and self.asset_correlation not in (0, 1)):
raise ValueError('asset_correlation != {0, 1} is no longer'
' supported')
# check for GMFs from file
if (self.inputs.get('gmfs', '').endswith('.csv') and not self.sites
and 'sites' not in self.inputs):
raise InvalidFile('%s: You forgot sites|sites_csv' % job_ini)
elif (self.inputs.get('gmfs', '').endswith('.xml')
and 'sites' in self.inputs):
raise InvalidFile('%s: You cannot have both sites_csv and '
'gmfs_file' % job_ini)
# checks for ucerf
if 'ucerf' in self.calculation_mode:
if self.ses_per_logic_tree_path >= TWO16:
raise ValueError('ses_per_logic_tree_path too big: %d' %
self.ses_per_logic_tree_path)
if self.number_of_logic_tree_samples >= TWO16:
raise ValueError('number_of_logic_tree_samples too big: %d' %
self.number_of_logic_tree_samples)
def file_type(self):
try:
return self._file_type
except AttributeError:
self._file_type, self._risk_files = get_risk_files(self.inputs)
return self._file_type
def __init__(self, **names_vals):
if '_job_id' in names_vals:
# assume most attributes already validated
vars(self).update(names_vals)
if 'hazard_calculation_id' in names_vals:
self.hazard_calculation_id = int(
names_vals['hazard_calculation_id'])
if 'maximum_distance' in names_vals:
self.maximum_distance = valid.MagDepDistance.new(
str(names_vals['maximum_distance']))
if 'pointsource_distance' in names_vals:
self.pointsource_distance = valid.MagDepDistance.new(
str(names_vals['pointsource_distance']))
if 'region_constraint' in names_vals:
self.region = valid.wkt_polygon(
names_vals['region_constraint'])
if 'minimum_magnitude' in names_vals:
self.minimum_magnitude = valid.floatdict(
str(names_vals['minimum_magnitude']))
if 'minimum_intensity' in names_vals:
self.minimum_intensity = valid.floatdict(
str(names_vals['minimum_intensity']))
if 'sites' in names_vals:
self.sites = valid.coordinates(names_vals['sites'])
return
# support legacy names
for name in list(names_vals):
if name == 'quantile_hazard_curves':
names_vals['quantiles'] = names_vals.pop(name)
elif name == 'mean_hazard_curves':
names_vals['mean'] = names_vals.pop(name)
elif name == 'max':
names_vals['max'] = names_vals.pop(name)
super().__init__(**names_vals)
if 'job_ini' not in self.inputs:
self.inputs['job_ini'] = '<in-memory>'
job_ini = self.inputs['job_ini']
if 'calculation_mode' not in names_vals:
raise InvalidFile('Missing calculation_mode in %s' % job_ini)
if 'region_constraint' in names_vals:
if 'region' in names_vals:
raise InvalidFile('You cannot have both region and '
'region_constraint in %s' % job_ini)
logging.warning(
'region_constraint is obsolete, use region instead')
self.region = valid.wkt_polygon(
names_vals.pop('region_constraint'))
self.risk_investigation_time = (self.risk_investigation_time
or self.investigation_time)
self.collapse_level = int(self.collapse_level)
if ('intensity_measure_types_and_levels' in names_vals
and 'intensity_measure_types' in names_vals):
logging.warning('Ignoring intensity_measure_types since '
'intensity_measure_types_and_levels is set')
if 'iml_disagg' in names_vals:
self.iml_disagg.pop('default')
# normalize things like SA(0.10) -> SA(0.1)
self.iml_disagg = {
str(from_string(imt)): val
for imt, val in self.iml_disagg.items()
}
self.hazard_imtls = self.iml_disagg
if 'intensity_measure_types_and_levels' in names_vals:
raise InvalidFile(
'Please remove the intensity_measure_types_and_levels '
'from %s: they will be inferred from the iml_disagg '
'dictionary' % job_ini)
elif 'intensity_measure_types_and_levels' in names_vals:
self.hazard_imtls = self.intensity_measure_types_and_levels
delattr(self, 'intensity_measure_types_and_levels')
lens = set(map(len, self.hazard_imtls.values()))
if len(lens) > 1:
dic = {imt: len(ls) for imt, ls in self.hazard_imtls.items()}
raise ValueError(
'Each IMT must have the same number of levels, instead '
'you have %s' % dic)
elif 'intensity_measure_types' in names_vals:
self.hazard_imtls = dict.fromkeys(self.intensity_measure_types)
if 'maximum_intensity' in names_vals:
minint = self.minimum_intensity or {'default': 1E-2}
for imt in self.hazard_imtls:
i1 = calc.filters.getdefault(minint, imt)
i2 = calc.filters.getdefault(self.maximum_intensity, imt)
self.hazard_imtls[imt] = list(valid.logscale(i1, i2, 20))
delattr(self, 'intensity_measure_types')
self._risk_files = get_risk_files(self.inputs)
if self.hazard_precomputed() and self.job_type == 'risk':
self.check_missing('site_model', 'debug')
self.check_missing('gsim_logic_tree', 'debug')
self.check_missing('source_model_logic_tree', 'debug')
# check investigation_time
if (self.investigation_time
and self.calculation_mode.startswith('scenario')):
raise ValueError('%s: there cannot be investigation_time in %s' %
(self.inputs['job_ini'], self.calculation_mode))
# check the gsim_logic_tree
if self.inputs.get('gsim_logic_tree'):
if self.gsim != '[FromFile]':
raise InvalidFile('%s: if `gsim_logic_tree_file` is set, there'
' must be no `gsim` key' % job_ini)
path = os.path.join(self.base_path, self.inputs['gsim_logic_tree'])
gsim_lt = logictree.GsimLogicTree(path, ['*'])
# check the IMTs vs the GSIMs
self._trts = set(gsim_lt.values)
for gsims in gsim_lt.values.values():
self.check_gsims(gsims)
elif self.gsim is not None:
self.check_gsims([valid.gsim(self.gsim, self.base_path)])
# check inputs
unknown = set(self.inputs) - self.KNOWN_INPUTS
if unknown:
raise ValueError('Unknown key %s_file in %s' %
(unknown.pop(), self.inputs['job_ini']))
# checks for disaggregation
if self.calculation_mode == 'disaggregation':
if not self.poes_disagg and self.poes:
self.poes_disagg = self.poes
elif not self.poes and self.poes_disagg:
self.poes = self.poes_disagg
elif self.poes != self.poes_disagg:
raise InvalidFile(
'poes_disagg != poes: %s!=%s in %s' %
(self.poes_disagg, self.poes, self.inputs['job_ini']))
if not self.poes_disagg and not self.iml_disagg:
raise InvalidFile('poes_disagg or iml_disagg must be set '
'in %(job_ini)s' % self.inputs)
elif self.poes_disagg and self.iml_disagg:
raise InvalidFile(
'%s: iml_disagg and poes_disagg cannot be set '
'at the same time' % job_ini)
for k in ('mag_bin_width', 'distance_bin_width',
'coordinate_bin_width', 'num_epsilon_bins'):
if k not in vars(self):
raise InvalidFile('%s must be set in %s' % (k, job_ini))
if self.disagg_outputs and not any('Eps' in out
for out in self.disagg_outputs):
self.num_epsilon_bins = 1
if (self.rlz_index is not None
and self.num_rlzs_disagg is not None):
raise InvalidFile('%s: you cannot set rlzs_index and '
'num_rlzs_disagg at the same time' % job_ini)
# checks for classical_damage
if self.calculation_mode == 'classical_damage':
if self.conditional_loss_poes:
raise InvalidFile('%s: conditional_loss_poes are not defined '
'for classical_damage calculations' %
job_ini)
# checks for event_based_risk
if (self.calculation_mode == 'event_based_risk'
and self.asset_correlation not in (0, 1)):
raise ValueError('asset_correlation != {0, 1} is no longer'
' supported')
# checks for ebrisk
if self.calculation_mode == 'ebrisk':
if self.risk_investigation_time is None:
raise InvalidFile('Please set the risk_investigation_time in'
' %s' % job_ini)
# check for GMFs from file
if (self.inputs.get('gmfs', '').endswith('.csv')
and 'sites' not in self.inputs and self.sites is None):
raise InvalidFile('%s: You forgot sites|sites_csv' % job_ini)
elif self.inputs.get('gmfs', '').endswith('.xml'):
raise InvalidFile('%s: GMFs in XML are not supported anymore' %
job_ini)
# checks for event_based
if 'event_based' in self.calculation_mode:
if self.ses_per_logic_tree_path >= TWO32:
raise ValueError('ses_per_logic_tree_path too big: %d' %
self.ses_per_logic_tree_path)
if self.number_of_logic_tree_samples >= TWO16:
raise ValueError('number_of_logic_tree_samples too big: %d' %
self.number_of_logic_tree_samples)
# check grid + sites
if self.region_grid_spacing and ('sites' in self.inputs or self.sites):
raise ValueError('You are specifying grid and sites at the same '
'time: which one do you want?')
# check for amplification
if ('amplification' in self.inputs and self.imtls
and self.calculation_mode
in ['classical', 'classical_risk', 'disaggregation']):
check_same_levels(self.imtls)
def __init__(self, **names_vals):
for name in list(names_vals):
if name == 'quantile_hazard_curves':
names_vals['quantiles'] = names_vals.pop(name)
super().__init__(**names_vals)
job_ini = self.inputs['job_ini']
if 'calculation_mode' not in names_vals:
raise InvalidFile('Missing calculation_mode in %s' % job_ini)
if 'region_constraint' in names_vals:
if 'region' in names_vals:
raise InvalidFile('You cannot have both region and '
'region_constraint in %s' % job_ini)
logging.warning(
'region_constraint is obsolete, use region instead')
self.region = valid.wkt_polygon(
names_vals.pop('region_constraint'))
self.risk_investigation_time = (
self.risk_investigation_time or self.investigation_time)
if ('intensity_measure_types_and_levels' in names_vals and
'intensity_measure_types' in names_vals):
logging.warning('Ignoring intensity_measure_types since '
'intensity_measure_types_and_levels is set')
if 'iml_disagg' in names_vals:
self.iml_disagg.pop('default')
# normalize things like SA(0.10) -> SA(0.1)
self.iml_disagg = {str(from_string(imt)): val
for imt, val in self.iml_disagg.items()}
self.hazard_imtls = self.iml_disagg
if 'intensity_measure_types_and_levels' in names_vals:
raise InvalidFile(
'Please remove the intensity_measure_types_and_levels '
'from %s: they will be inferred from the iml_disagg '
'dictionary' % job_ini)
elif 'intensity_measure_types_and_levels' in names_vals:
self.hazard_imtls = self.intensity_measure_types_and_levels
delattr(self, 'intensity_measure_types_and_levels')
elif 'intensity_measure_types' in names_vals:
self.hazard_imtls = dict.fromkeys(self.intensity_measure_types)
delattr(self, 'intensity_measure_types')
self._risk_files = get_risk_files(self.inputs)
self.check_source_model()
if (self.hazard_calculation_id and
self.calculation_mode == 'ucerf_risk'):
raise ValueError('You cannot use the --hc option with ucerf_risk')
if self.hazard_precomputed() and self.job_type == 'risk':
self.check_missing('site_model', 'debug')
self.check_missing('gsim_logic_tree', 'debug')
self.check_missing('source_model_logic_tree', 'debug')
# check the gsim_logic_tree
if self.inputs.get('gsim_logic_tree'):
if self.gsim != '[FromFile]':
raise InvalidFile('%s: if `gsim_logic_tree_file` is set, there'
' must be no `gsim` key' % job_ini)
path = os.path.join(
self.base_path, self.inputs['gsim_logic_tree'])
gsim_lt = logictree.GsimLogicTree(path, ['*'])
# check the number of branchsets
branchsets = len(gsim_lt._ltnode)
if 'scenario' in self.calculation_mode and branchsets > 1:
raise InvalidFile(
'%s: %s for a scenario calculation must contain a single '
'branchset, found %d!' % (job_ini, path, branchsets))
# check the IMTs vs the GSIMs
self._gsims_by_trt = gsim_lt.values
for gsims in self._gsims_by_trt.values():
self.check_gsims(gsims)
elif self.gsim is not None:
self.check_gsims([valid.gsim(self.gsim)])
# checks for disaggregation
if self.calculation_mode == 'disaggregation':
if not self.poes_disagg and not self.iml_disagg:
raise InvalidFile('poes_disagg or iml_disagg must be set '
'in %(job_ini)s' % self.inputs)
elif self.poes_disagg and self.iml_disagg:
raise InvalidFile(
'%s: iml_disagg and poes_disagg cannot be set '
'at the same time' % job_ini)
for k in ('mag_bin_width', 'distance_bin_width',
'coordinate_bin_width', 'num_epsilon_bins'):
if k not in vars(self):
raise InvalidFile('%s must be set in %s' % (k, job_ini))
# checks for classical_damage
if self.calculation_mode == 'classical_damage':
if self.conditional_loss_poes:
raise InvalidFile(
'%s: conditional_loss_poes are not defined '
'for classical_damage calculations' % job_ini)
# checks for event_based_risk
if (self.calculation_mode == 'event_based_risk' and
self.asset_correlation not in (0, 1)):
raise ValueError('asset_correlation != {0, 1} is no longer'
' supported')
# checks for ebrisk
if self.calculation_mode == 'ebrisk':
pass
# elif self.number_of_logic_tree_samples == 0:
# logging.warning('ebrisk is not meant for full enumeration')
# check for GMFs from file
if (self.inputs.get('gmfs', '').endswith('.csv') and not self.sites and
'sites' not in self.inputs):
raise InvalidFile('%s: You forgot sites|sites_csv' % job_ini)
elif (self.inputs.get('gmfs', '').endswith('.xml') and
'sites' in self.inputs):
raise InvalidFile('%s: You cannot have both sites_csv and '
'gmfs_file' % job_ini)
# checks for event_based
if 'event_based' in self.calculation_mode:
if self.ses_per_logic_tree_path >= TWO32:
raise ValueError('ses_per_logic_tree_path too big: %d' %
self.ses_per_logic_tree_path)
if self.number_of_logic_tree_samples >= TWO16:
raise ValueError('number_of_logic_tree_samples too big: %d' %
self.number_of_logic_tree_samples)
# check grid + sites
if (self.region_grid_spacing and 'site_model' in self.inputs
and 'exposure' in self.inputs):
logging.warning(
'You are specifying a grid, a site model and an exposure at '
'the same time: consider using `oq prepare_site_model`')
def risk_files(self):
try:
return self._risk_files
except AttributeError:
self._risk_files = get_risk_files(self.inputs)
return self._risk_files