def test_bcr_risk_export(self):
# Tests that outputs of a risk classical calculation are
# exported
target_dir = tempfile.mkdtemp()
try:
cfg = helpers.demo_file('classical_bcr/job.ini')
# run the calculation to create something to export
retcode = helpers.run_risk_job_sp(cfg, self.hazard_id,
silence=True)
self.assertEqual(0, retcode)
job = models.OqJob.objects.latest('id')
outputs = export_core.get_outputs(job.id)
expected_outputs = 1 # 1 bcr distribution
self.assertEqual(expected_outputs, len(outputs))
# Export the loss curves:
distribution = outputs.filter(output_type='bcr_distribution')[0]
rc_files = risk.export(distribution.id, target_dir)
self.assertEqual(1, len(rc_files))
for f in rc_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)
def run_risk(self, cfg, hazard_id):
"""
Given the path to job config file, run the job and assert that it was
successful. If this assertion passes, return the completed job.
:param str cfg:
Path to a job config file.
:param int hazard_id:
ID of the hazard output used by the risk calculation
:returns:
The completed :class:`~openquake.engine.db.models.OqJob`.
:raises:
:exc:`AssertionError` if the job was not successfully run.
"""
job_status = helpers.run_risk_job_sp(cfg, hazard_id, silence=True)
self.assertEqual(0, job_status)
completed_job = models.OqJob.objects.latest('last_update')
self.assertEqual('complete', completed_job.status)
return completed_job
def test_classical_risk_export(self):
# Tests that outputs of a risk classical calculation are exported
target_dir = tempfile.mkdtemp()
try:
cfg = helpers.demo_file('classical_psha_based_risk/job.ini')
# run the calculation to create something to export
retcode = helpers.run_risk_job_sp(cfg, self.hazard_id,
silence=True)
self.assertEqual(0, retcode)
job = models.OqJob.objects.latest('id')
outputs = export_core.get_outputs(job.id)
expected_outputs = 4 # 1 loss curve set + 3 loss curve map set
self.assertEqual(expected_outputs, len(outputs))
# Export the loss curves:
curves = outputs.filter(output_type='loss_curve')
rc_files = []
for curve in curves:
rc_files.extend(risk.export(curve.id, target_dir))
self.assertEqual(1, len(rc_files))
for f in rc_files:
self._test_exported_file(f)
# Test loss map export as well.
maps = outputs.filter(output_type='loss_map')
lm_files = sum(
[risk.export(loss_map.id, target_dir)
for loss_map in maps], [])
self.assertEqual(3, len(lm_files))
for f in lm_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)
def test_event_based_risk_export(self):
# Tests that outputs of a risk classical calculation are exported
target_dir = tempfile.mkdtemp()
try:
# use get_risk_job to create a fake GmfCollection
job, _ = helpers.get_risk_job('event_based_risk/job.ini',
'event_based_hazard/job.ini',
'gmf')
cfg = helpers.demo_file('event_based_risk/job.ini')
# run the calculation to create something to export
# at the moment, only gmf for a specific realization are
# supported as hazard input
retcode = helpers.run_risk_job_sp(
cfg, silence=True,
hazard_id=job.risk_calculation.hazard_output.id)
self.assertEqual(0, retcode)
job = models.OqJob.objects.latest('id')
outputs = export_core.get_outputs(job.id)
# 1 loss curve set + 3 loss curve map set + 1 insured + 1 aggregate
expected_outputs = 6
self.assertEqual(expected_outputs, len(outputs))
# Export the loss curves...
curves = outputs.filter(output_type='loss_curve')
rc_files = []
for curve in curves:
rc_files.extend(risk.export(curve.id, target_dir))
self.assertEqual(1, len(rc_files))
for f in rc_files:
self._test_exported_file(f)
# ... loss map ...
maps = outputs.filter(output_type='loss_map')
lm_files = sum(
[risk.export(loss_map.id, target_dir)
for loss_map in maps], [])
self.assertEqual(3, len(lm_files))
for f in lm_files:
self._test_exported_file(f)
# ... aggregate losses...
maps = outputs.filter(output_type='agg_loss_curve')
lm_files = sum(
[risk.export(loss_map.id, target_dir)
for loss_map in maps], [])
self.assertEqual(1, len(lm_files))
for f in lm_files:
self._test_exported_file(f)
# and insured losses.
maps = outputs.filter(output_type='ins_loss_curve')
lm_files = sum(
[risk.export(loss_map.id, target_dir)
for loss_map in maps], [])
self.assertEqual(1, len(lm_files))
for f in lm_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)
