def sanity_check(self):
"""
Sanity check on the total number of assets
"""
if self.R == 1:
arr = self.datastore.sel('damages-rlzs') # shape (A, 1, L, D)
else:
arr = self.datastore.sel('damages-stats', stat='mean')
avg = arr.sum(axis=(0, 1)) # shape (L, D)
if not len(self.datastore['dd_data/aid']):
logging.warning('There is no damage at all!')
else:
df = views.portfolio_damage_error(self.datastore, avg[:, 1:])
rst = views.rst_table(numpy.array(df), list(df.columns))
logging.info('Portfolio damage\n%s' % rst)
num_assets = avg.sum(axis=1) # by loss_type
expected = self.assetcol['number'].sum()
nums = set(num_assets) | {expected}
if len(nums) > 1:
numdic = dict(expected=expected)
for lt, num in zip(self.oqparam.loss_names, num_assets):
numdic[lt] = num
logging.info(
'Due to numeric errors the total number of assets'
' is imprecise: %s', numdic)
def sanity_check(self):
"""
Sanity check on the total number of assets
"""
if self.R == 1:
arr = self.datastore.sel('damages-rlzs') # shape (A, 1, L, D)
else:
arr = self.datastore.sel('damages-stats', stat='mean')
avg = arr.sum(axis=(0, 1)) # shape (L, D)
if not len(self.datastore['risk_by_event/agg_id']):
logging.warning('There is no damage at all!')
elif 'avg_portfolio_damage' in self.datastore:
df = views.portfolio_damage_error('avg_portfolio_damage',
self.datastore)
rst = views.text_table(df, ext='org')
logging.info('Portfolio damage\n%s' % rst)
num_assets = avg.sum(axis=1) # by loss_type
expected = self.assetcol['value-number'].sum()
nums = set(num_assets) | {expected}
if len(nums) > 1:
numdic = dict(expected=expected)
for lt, num in zip(self.oqparam.loss_names, num_assets):
numdic[lt] = num
logging.info(
'Due to rounding errors inherent in floating-point arithmetic,'
' the total number of assets is not exact: %s', numdic)