def __init__(self, **names_vals):
super(OqParam, self).__init__(**names_vals)
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 '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)
# check the IMTs vs the GSIMs
if 'gsim_logic_tree' in self.inputs:
if self.gsim:
raise ValueError('If `gsim_logic_tree_file` is set, there '
'must be no `gsim` key')
path = os.path.join(
self.base_path, self.inputs['gsim_logic_tree'])
self._gsims_by_trt = logictree.GsimLogicTree(path, []).values
for gsims in self._gsims_by_trt.values():
self.check_gsims(gsims)
elif self.gsim is not None:
self.check_gsims([self.gsim])
def __init__(self, **names_vals):
super(OqParam, self).__init__(**names_vals)
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 '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)
# check the IMTs vs the GSIMs
if 'gsim_logic_tree' in self.inputs:
if self.gsim:
raise ValueError('If `gsim_logic_tree_file` is set, there '
'must be no `gsim` key')
path = os.path.join(
self.base_path, self.inputs['gsim_logic_tree'])
self._gsims_by_trt = logictree.GsimLogicTree(path, ['*']).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 disaggregation
if self.calculation_mode == 'disaggregation':
if not self.individual_curves:
raise ValueError(
'For disaggregation the flag `individual_curves` '
'must be true')
elif not self.poes_disagg and not self.iml_disagg:
raise ValueError('poes_disagg or iml_disagg must be set '
'in the job.ini file')
elif self.poes_disagg and self.iml_disagg:
logging.warn(
'iml_disagg=%s will not be computed from poes_disagg=%s',
str(self.iml_disagg), self.poes_disagg)
# 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')
def is_valid_intensity_measure_types(self):
"""
If the IMTs and levels are extracted from the risk models,
they must not be set directly. Moreover, if
`intensity_measure_types_and_levels` is set directly,
`intensity_measure_types` must not be set.
"""
if self.ground_motion_correlation_model:
for imt in self.imtls:
if not (imt.startswith('SA') or imt == 'PGA'):
raise ValueError(
'Correlation model %s does not accept IMT=%s' %
(self.ground_motion_correlation_model, imt))
_, risk_files = get_risk_files(self.inputs)
if risk_files: # IMTLs extracted from the risk files
return (self.intensity_measure_types is None
and self.intensity_measure_types_and_levels is None)
elif not hasattr(self, 'hazard_imtls') and not hasattr(
self, 'risk_imtls'):
return False
return True
def is_valid_intensity_measure_types(self):
"""
If the IMTs and levels are extracted from the risk models,
they must not be set directly. Moreover, if
`intensity_measure_types_and_levels` is set directly,
`intensity_measure_types` must not be set.
"""
if self.ground_motion_correlation_model:
for imt in self.imtls:
if not (imt.startswith('SA') or imt == 'PGA'):
raise ValueError(
'Correlation model %s does not accept IMT=%s' % (
self.ground_motion_correlation_model, imt))
_, risk_files = get_risk_files(self.inputs)
if risk_files: # IMTLs extracted from the risk files
return (self.intensity_measure_types is None
and self.intensity_measure_types_and_levels is None)
elif not hasattr(self, 'hazard_imtls') and not hasattr(
self, 'risk_imtls'):
return False
return True
def __init__(self, **names_vals):
super(OqParam, self).__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)
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():
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 self.gsim:
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')
elif (self.calculation_mode == 'event_based_risk'
and self.conditional_loss_poes and not self.asset_loss_table):
raise InvalidFile(
'%s: asset_loss_table is not set, probably you want to remove'
' conditional_loss_poes' % job_ini)
# 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)
# 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):
super(OqParam, self).__init__(**names_vals)
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 '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)
# check the gsim_logic_tree
if 'gsim_logic_tree' in self.inputs:
if self.gsim:
raise ValueError('If `gsim_logic_tree_file` is set, there '
'must be no `gsim` key')
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 for a scenario calculation must contain a single '
'branchset, found %d!' % (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 disaggregation
if self.calculation_mode == 'disaggregation':
if not self.poes_disagg and not self.iml_disagg:
raise ValueError('poes_disagg or iml_disagg must be set '
'in the job.ini file')
elif self.poes_disagg and self.iml_disagg:
logging.warn(
'iml_disagg=%s will not be computed from poes_disagg=%s',
str(self.iml_disagg), self.poes_disagg)
# checks for classical_damage
if self.calculation_mode == 'classical_damage':
if self.quantile_loss_curves:
raise ValueError('quantile_loss_curves are not defined '
'for classical_damage calculations: '
'remove them for the .ini file')
if self.conditional_loss_poes:
raise ValueError('conditional_loss_poes are not defined '
'for classical_damage calculations: '
'remove them for the .ini file')
# 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 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 all_cost_types(self):
"""
Return the cost types of the computation (including `occupants`
if it is there) in order.
"""
return sorted(get_risk_files(self.inputs)[1])
def all_cost_types(self):
"""
Return the cost types of the computation (including `occupants`
if it is there) in order.
"""
return sorted(get_risk_files(self.inputs)[1])