def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), "job.ini")
expected_curve_poes_b1_b2 = [0.00995, 0.00076, 9.7e-5, 0.0]
expected_curve_poes_b1_b3 = [0.00995, 0.00076, 0.000104, 0.0]
job = self.run_hazard(cfg)
# Test the poe values for the two curves:
curve_b1_b2, curve_b1_b3 = models.HazardCurveData.objects.filter(
hazard_curve__output__oq_job=job.id
).order_by("hazard_curve__lt_realization__sm_lt_path")
# Sanity check, to make sure we have the curves ordered correctly:
self.assertEqual(["b1", "b2"], curve_b1_b2.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(["b1", "b3"], curve_b1_b3.hazard_curve.lt_realization.sm_lt_path)
numpy.testing.assert_array_almost_equal(expected_curve_poes_b1_b2, curve_b1_b2.poes, decimal=4)
numpy.testing.assert_array_almost_equal(expected_curve_poes_b1_b3, curve_b1_b3.poes, decimal=4)
# Test the exports as well:
[exported_file_b1_b2] = hazard_export.export(curve_b1_b2.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_B1_B2), exported_file_b1_b2)
[exported_file_b1_b3] = hazard_export.export(curve_b1_b3.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_B1_B3), exported_file_b1_b3)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes_b1 = [0.86466, 0.82460, 0.36525]
expected_curve_poes_b2 = [0.63212, 0.61186, 0.25110]
expected_mean_poes = [0.794898, 0.760778, 0.331005]
job = self.run_hazard(cfg)
# Test the poe values for the two curves.
actual_curve_b1, actual_curve_b2 = \
models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__lt_realization__isnull=False)\
.order_by('hazard_curve__lt_realization__sm_lt_path')
# Sanity check, to make sure we have the curves ordered correctly:
self.assertEqual(
['b1'], actual_curve_b1.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b2'], actual_curve_b2.hazard_curve.lt_realization.sm_lt_path)
numpy.testing.assert_array_almost_equal(expected_curve_poes_b1,
actual_curve_b1.poes,
decimal=3)
numpy.testing.assert_array_almost_equal(expected_curve_poes_b2,
actual_curve_b2.poes,
decimal=3)
# Test the mean curve:
[mean_curve] = models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__statistics='mean')
numpy.testing.assert_array_almost_equal(expected_mean_poes,
mean_curve.poes,
decimal=3)
# Test the exports as well:
exported_file_b1 = hazard_export.export(
actual_curve_b1.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_B1),
exported_file_b1)
exported_file_b2 = hazard_export.export(
actual_curve_b2.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_B2),
exported_file_b2)
# mean:
exported_file_mean = hazard_export.export(
mean_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_MEAN),
exported_file_mean)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes_b1 = [0.86466, 0.82460, 0.36525]
expected_curve_poes_b2 = [0.63212, 0.61186, 0.25110]
expected_mean_poes = [0.794898, 0.760778, 0.331005]
job = self.run_hazard(cfg)
# Test the poe values for the two curves.
actual_curve_b1, actual_curve_b2 = (
models.HazardCurveData.objects
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__lt_realization__isnull=False)
.order_by('hazard_curve__lt_realization__lt_model__sm_lt_path')
)
# Sanity check, to make sure we have the curves ordered correctly:
self.assertEqual(
['b1'], actual_curve_b1.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b2'], actual_curve_b2.hazard_curve.lt_realization.sm_lt_path)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b1, actual_curve_b1.poes, decimal=3)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b2, actual_curve_b2.poes, decimal=3)
# Test the mean curve:
[mean_curve] = models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__statistics='mean')
numpy.testing.assert_array_almost_equal(
expected_mean_poes, mean_curve.poes, decimal=3)
# Test the exports as well:
exported_file_b1 = hazard_export.export(
actual_curve_b1.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1), exported_file_b1)
exported_file_b2 = hazard_export.export(
actual_curve_b2.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B2), exported_file_b2)
# mean:
exported_file_mean = hazard_export.export(
mean_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_MEAN), exported_file_mean)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes_b1_b2 = [0.095163, 0.012362, 0.002262, 0.0]
expected_curve_poes_b1_b3 = [0.009950, 0.00076, 9.99995E-6, 0.0]
expected_curve_poes_b1_b4 = [0.0009995, 4.5489E-5, 4.07365E-6, 0.0]
job = self.run_hazard(cfg)
# Test the poe values for the three curves:
curve_b1_b2, curve_b1_b3, curve_b1_b4 = \
models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id)\
.order_by('hazard_curve__lt_realization__sm_lt_path')
# Sanity check, to make sure we have the curves ordered correctly:
self.assertEqual(
['b1', 'b2'],
curve_b1_b2.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b3'],
curve_b1_b3.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b4'],
curve_b1_b4.hazard_curve.lt_realization.sm_lt_path)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b1_b2, curve_b1_b2.poes, decimal=3)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b1_b3, curve_b1_b3.poes, decimal=3)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b1_b4, curve_b1_b4.poes, decimal=3)
# Test the exports as well:
[exported_file_b1_b2] = hazard_export.export(
curve_b1_b2.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B2),
exported_file_b1_b2)
[exported_file_b1_b3] = hazard_export.export(
curve_b1_b3.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B3),
exported_file_b1_b3)
[exported_file_b1_b4] = hazard_export.export(
curve_b1_b4.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B4),
exported_file_b1_b4)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes_b1_b2 = [0.095163, 0.012362, 0.002262, 0.0]
expected_curve_poes_b1_b3 = [0.009950, 0.00076, 9.99995E-6, 0.0]
expected_curve_poes_b1_b4 = [0.0009995, 4.5489E-5, 4.07365E-6, 0.0]
job = self.run_hazard(cfg)
# Test the poe values for the three curves:
curve_b1_b2, curve_b1_b3, curve_b1_b4 = \
models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id)\
.order_by('hazard_curve__lt_realization__sm_lt_path')
# Sanity check, to make sure we have the curves ordered correctly:
self.assertEqual(
['b1', 'b2'],
curve_b1_b2.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b3'],
curve_b1_b3.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b4'],
curve_b1_b4.hazard_curve.lt_realization.sm_lt_path)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b1_b2, curve_b1_b2.poes, decimal=3)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b1_b3, curve_b1_b3.poes, decimal=3)
numpy.testing.assert_array_almost_equal(
expected_curve_poes_b1_b4, curve_b1_b4.poes, decimal=3)
# Test the exports as well:
exported_file_b1_b2 = hazard_export.export(
curve_b1_b2.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B2),
exported_file_b1_b2)
exported_file_b1_b3 = hazard_export.export(
curve_b1_b3.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B3),
exported_file_b1_b3)
exported_file_b1_b4 = hazard_export.export(
curve_b1_b4.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B4),
exported_file_b1_b4)
finally:
shutil.rmtree(result_dir)
def export(self, *args, **kwargs):
"""
If requested by the user, automatically export all result artifacts to
the specified format. (NOTE: The only export format supported at the
moment is NRML XML.
:returns:
A list of the export filenames, including the absolute path to each
file.
"""
exported_files = []
logs.LOG.debug('> starting exports')
if 'exports' in kwargs and 'xml' in kwargs['exports']:
outputs = export_core.get_outputs(self.job.id)
if not self.hc.export_multi_curves:
outputs = outputs.exclude(output_type='hazard_curve_multi')
for output in outputs:
with self.monitor('exporting %s' % output.output_type):
fname = hazard_export.export(
output.id, self.job.hazard_calculation.export_dir)
exported_files.extend(fname)
logs.LOG.debug('exported %s' % fname)
logs.LOG.debug('< done with exports')
return exported_files
def test_export_for_scenario(self):
target_dir = tempfile.mkdtemp()
try:
cfg = helpers.demo_file('scenario_hazard/job.ini')
# run the calculation to create something to export
retcode = helpers.run_hazard_job_sp(cfg, silence=True)
self.assertEqual(0, retcode)
job = models.OqJob.objects.latest('id')
outputs = export_core.get_outputs(job.id)
self.assertEqual(1, len(outputs)) # 1 GMF
gmf_outputs = outputs.filter(output_type='gmf_scenario')
self.assertEqual(1, len(gmf_outputs))
exported_files = hazard.export(gmf_outputs[0].id, target_dir)
self.assertEqual(1, len(exported_files))
# Check the file paths exist, is absolute, and the file isn't
# empty.
f = exported_files[0]
self._test_exported_file(f)
# Check for the correct number of GMFs in the file:
tree = etree.parse(f)
self.assertEqual(10, number_of('nrml:gmf', tree))
finally:
shutil.rmtree(target_dir)
def export(self, *args, **kwargs):
"""
If requested by the user, automatically export all result artifacts to
the specified format. (NOTE: The only export format supported at the
moment is NRML XML.
:returns:
A list of the export filenames, including the absolute path to each
file.
"""
exported_files = []
logs.LOG.debug('> starting exports')
if 'exports' in kwargs and 'xml' in kwargs['exports']:
outputs = export_core.get_outputs(self.job.id)
for output in outputs:
exported_files.extend(hazard_export.export(
output.id, self.job.hazard_calculation.export_dir))
for exp_file in exported_files:
logs.LOG.debug('exported %s' % exp_file)
logs.LOG.debug('< done with exports')
return exported_files
def check_export(output_id, target):
"""
Call hazard.export by checking that the exported file is valid
according to our XML schema.
"""
out_file = hazard.export(output_id, target, 'xml')
nrmllib.assert_valid(out_file)
return out_file
def _do_export(self, output_id, export_dir, export_type):
"""
Hazard-specific implementation of
:meth:`openquake.engine.calculators.base.Calculator._do_export`.
Calls the hazard exporter.
"""
return hazard_export.export(output_id, export_dir, export_type)
def check_export(output_id, target):
"""
Call hazard.export by checking that the exported file is valid
according to our XML schema.
"""
out_file = hazard.export(output_id, target, 'xml')
nrmllib.assert_valid(out_file)
return out_file
def _do_export(self, output_id, export_dir, export_type):
"""
Hazard-specific implementation of
:meth:`openquake.engine.calculators.base.Calculator._do_export`.
Calls the hazard exporter.
"""
return hazard_export.export(output_id, export_dir, export_type)
def test_classical_hazard_export(self):
# Run a hazard calculation to compute some curves and maps
# Call the exporter and verify that files were created
# Since the hazard curve XML writer is concerned with correctly
# generating XML, we won't test that here.
target_dir = tempfile.mkdtemp()
try:
cfg = helpers.demo_file('simple_fault_demo_hazard/job.ini')
# run the calculation to create something to export
retcode = helpers.run_hazard_job_sp(cfg, silence=True)
self.assertEqual(0, retcode)
job = models.OqJob.objects.latest('id')
outputs = export_core.get_outputs(job.id)
expected_outputs = 18 # 6 hazard curves + 12 hazard maps
self.assertEqual(expected_outputs, len(outputs))
# Export the hazard curves:
curves = outputs.filter(output_type='hazard_curve')
hc_files = []
for curve in curves:
hc_files.extend(hazard.export(curve.id, target_dir))
self.assertEqual(6, len(hc_files))
for f in hc_files:
self._test_exported_file(f)
# Test hazard map export as well.
maps = outputs.filter(output_type='hazard_map')
hm_files = []
for haz_map in maps:
hm_files.extend(hazard.export(haz_map.id, target_dir))
self.assertEqual(12, len(hm_files))
for f in hm_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_pga = [0.4570, 0.0587, 0.0069]
expected_curve_sa = [
0.608675003748, 0.330831513139, 0.201472214825
]
job = self.run_hazard(cfg)
# Test the poe values of the single curve:
curves = models.HazardCurveData.objects.filter(
hazard_curve__output__oq_job=job.id
)
[pga_curve] = curves.filter(hazard_curve__imt='PGA')
numpy.testing.assert_array_almost_equal(
expected_curve_pga, pga_curve.poes, decimal=4
)
[sa_curve] = curves.filter(
hazard_curve__imt='SA', hazard_curve__sa_period=0.1
)
numpy.testing.assert_array_almost_equal(
expected_curve_sa, sa_curve.poes, decimal=4
)
# Test the exports as well:
exported_file = hazard_export.export(
pga_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_PGA_XML), exported_file)
exported_file = hazard_export.export(
sa_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_SA_XML), exported_file)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_pga = [0.4570, 0.0587, 0.0069]
expected_curve_sa = [
0.608675003748, 0.330831513139, 0.201472214825
]
job = self.run_hazard(cfg)
# Test the poe values of the single curve:
curves = models.HazardCurveData.objects.filter(
hazard_curve__output__oq_job=job.id
)
[pga_curve] = curves.filter(hazard_curve__imt='PGA')
numpy.testing.assert_array_almost_equal(
expected_curve_pga, pga_curve.poes, decimal=4
)
[sa_curve] = curves.filter(
hazard_curve__imt='SA', hazard_curve__sa_period=0.1
)
numpy.testing.assert_array_almost_equal(
expected_curve_sa, sa_curve.poes, decimal=4
)
# Test the exports as well:
[exported_file] = hazard_export.export(
pga_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_PGA_XML), exported_file)
[exported_file] = hazard_export.export(
sa_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_SA_XML), exported_file)
finally:
shutil.rmtree(result_dir)
def test(self):
aaae = numpy.testing.assert_array_almost_equal
# TODO(LB): This is a temporary test case which tests for stability
# until we can write proper QA tests.
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
job = self.run_hazard(cfg)
results = models.DisaggResult.objects.filter(output__oq_job=job)
poe_002_pga = results.filter(imt='PGA', poe=0.02)
rlz1, rlz2 = poe_002_pga.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_002_PGA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_002_PGA, rlz2.matrix)
poe_002_sa = results.filter(imt='SA', poe=0.02)
rlz1, rlz2 = poe_002_sa.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_002_SA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_002_SA, rlz2.matrix)
poe_01_pga = results.filter(imt='PGA', poe=0.1)
rlz1, rlz2 = poe_01_pga.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_01_PGA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_01_PGA, rlz2.matrix)
poe_01_sa = results.filter(imt='SA', poe=0.1)
rlz1, rlz2 = poe_01_sa.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_01_SA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_01_SA, rlz2.matrix)
# Lastly, we should an export of at least one of these results to
# ensure that the disagg export/serialization is working properly.
# The export isn't just a simple dump from the database; it requires
# extraction of PMFs (Probability Mass Function) from a 6d matrix,
# which are then serialized to XML.
# This is not a trivial operation.
try:
target_dir = tempfile.mkdtemp()
[result_file] = haz_export.export(rlz1.output.id, target_dir)
expected = StringIO.StringIO(test_data.EXPECTED_XML_DISAGG)
self.assert_xml_equal(expected, result_file)
self.assertTrue(qa_utils.validates_against_xml_schema(result_file))
finally:
shutil.rmtree(target_dir)
def test_disagg_hazard_export(self):
target_dir = tempfile.mkdtemp()
try:
cfg = helpers.demo_file('disaggregation/job.ini')
retcode = helpers.run_hazard_job_sp(cfg, silence=True)
self.assertEqual(0, retcode)
job = models.OqJob.objects.latest('id')
outputs = export_core.get_outputs(job.id)
# Test curve export:
curves = outputs.filter(output_type='hazard_curve')
self.assertEqual(4, len(curves))
curve_files = []
for curve in curves:
curve_files.extend(hazard.export(curve.id, target_dir))
self.assertEqual(4, len(curve_files))
for f in curve_files:
self._test_exported_file(f)
# Test disagg matrix export:
matrices = outputs.filter(output_type='disagg_matrix')
self.assertEqual(8, len(matrices))
disagg_files = []
for matrix in matrices:
disagg_files.extend(hazard.export(matrix.id, target_dir))
self.assertEqual(8, len(disagg_files))
for f in disagg_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)
def test(self):
# TODO(LB): This is a temporary test case which tests for stability
# until we can write proper QA tests.
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
job = self.run_hazard(cfg)
results = models.DisaggResult.objects.filter(output__oq_job=job)
poe_002_pga = results.filter(imt='PGA', poe=0.02)
rlz1, rlz2 = poe_002_pga.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_002_PGA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_002_PGA, rlz2.matrix)
poe_002_sa = results.filter(imt='SA', poe=0.02)
rlz1, rlz2 = poe_002_sa.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_002_SA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_002_SA, rlz2.matrix)
poe_01_pga = results.filter(imt='PGA', poe=0.1)
rlz1, rlz2 = poe_01_pga.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_01_PGA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_01_PGA, rlz2.matrix)
poe_01_sa = results.filter(imt='SA', poe=0.1)
rlz1, rlz2 = poe_01_sa.order_by('lt_realization')
aaae(test_data.RLZ_1_POE_01_SA, rlz1.matrix)
aaae(test_data.RLZ_2_POE_01_SA, rlz2.matrix)
# Lastly, we should check an export of at least one of these results to
# ensure that the disagg export/serialization is working properly.
# The export isn't just a simple dump from the database; it requires
# extraction of PMFs (Probability Mass Function) from a 6d matrix,
# which are then serialized to XML.
# This is not a trivial operation.
try:
target_dir = tempfile.mkdtemp()
result_file = haz_export.export(rlz1.output.id, target_dir)
expected = StringIO.StringIO(test_data.EXPECTED_XML_DISAGG)
self.assert_disagg_xml_almost_equal(expected, result_file)
self.assertTrue(qa_utils.validates_against_xml_schema(result_file))
finally:
shutil.rmtree(target_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), "job.ini")
expected_curve_poes = [0.86466, 0.82460, 0.36525]
job = self.run_hazard(cfg)
# Test the poe values of the single curve:
[actual_curve] = models.HazardCurveData.objects.filter(hazard_curve__output__oq_job=job.id)
numpy.testing.assert_array_almost_equal(expected_curve_poes, actual_curve.poes, decimal=2)
# Test the export as well:
[exported_file] = hazard_export.export(actual_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML), exported_file)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
aaae = numpy.testing.assert_array_almost_equal
try:
cfg = os.path.join(os.path.dirname(__file__), "job.ini")
expected_curve_poes = [0.75421006, 0.08098179, 0.00686616]
job = self.run_hazard(cfg)
# Test the poe values of the single curve:
[curve] = models.HazardCurveData.objects.filter(hazard_curve__output__oq_job=job.id)
aaae(expected_curve_poes, curve.poes, decimal=2)
# Test the exports as well:
exported_file = hazard_export.export(curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML), exported_file)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes = [0.63212, 0.61186, 0.25110]
job = self.run_hazard(cfg)
# Test the poe values of the single curve:
[actual_curve] = models.HazardCurveData.objects.filter(
hazard_curve__output__oq_job=job.id)
numpy.testing.assert_array_almost_equal(
expected_curve_poes, actual_curve.poes, decimal=3)
# Test the export as well:
exported_file = hazard_export.export(
actual_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML), exported_file)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
aaae = numpy.testing.assert_array_almost_equal
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes = [0.75421006, 0.08098179, 0.00686616]
job = self.run_hazard(cfg)
# Test the poe values of the single curve:
[curve] = models.HazardCurveData.objects.filter(
hazard_curve__output__oq_job=job.id)
aaae(expected_curve_poes, curve.poes, decimal=2)
# Test the exports as well:
exported_file = hazard_export.export(
curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML),
exported_file)
finally:
shutil.rmtree(result_dir)
def test(self):
result_dir = tempfile.mkdtemp()
aaae = numpy.testing.assert_array_almost_equal
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes_b1_b2 = [0.0055, 0.00042, 5.77E-5, 0.0]
expected_curve_poes_b1_b3 = [0.00995, 0.00076, 9.7E-5, 0.0]
expected_curve_poes_b1_b4 = [0.018, 0.0013, 0.00014, 0.0]
expected_mean_poes = [0.01067, 0.0008, 9.774E-5, 0.0]
expected_q0_1_poes = [0.0055, 0.00042, 5.77E-5, 0.0]
expected_q0_9_poes = [0.013975, 0.00103, 0.0001185, 0.0]
job = self.run_hazard(cfg)
# Test the poe values for the two curves:
curve_b1_b2, curve_b1_b3, curve_b1_b4 = \
models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__lt_realization__isnull=False)\
.order_by('hazard_curve__lt_realization__sm_lt_path')
# Sanity check, to make sure we have the curves ordered correctly:
self.assertEqual(
['b1', 'b2'],
curve_b1_b2.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b3'],
curve_b1_b3.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b4'],
curve_b1_b4.hazard_curve.lt_realization.sm_lt_path)
aaae(expected_curve_poes_b1_b2, curve_b1_b2.poes, decimal=4)
aaae(expected_curve_poes_b1_b3, curve_b1_b3.poes, decimal=4)
aaae(expected_curve_poes_b1_b4, curve_b1_b4.poes, decimal=4)
# Test the mean curve:
[mean_curve] = models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__statistics='mean')
aaae(expected_mean_poes, mean_curve.poes, decimal=4)
# Test the quantile curves:
quantile_0_1_curve, quantile_0_9_curve = \
models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__statistics='quantile')\
.order_by('hazard_curve__quantile')
aaae(expected_q0_1_poes, quantile_0_1_curve.poes, decimal=4)
aaae(expected_q0_9_poes, quantile_0_9_curve.poes, decimal=4)
# Test the exports as well:
exported_file_b1_b2 = hazard_export.export(
curve_b1_b2.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_B1_B2),
exported_file_b1_b2)
exported_file_b1_b3 = hazard_export.export(
curve_b1_b3.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_B1_B3),
exported_file_b1_b3)
exported_file_b1_b4 = hazard_export.export(
curve_b1_b4.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_B1_B4),
exported_file_b1_b4)
exported_file_mean = hazard_export.export(
mean_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(StringIO.StringIO(self.EXPECTED_XML_MEAN),
exported_file_mean)
q01_file = hazard_export.export(
quantile_0_1_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_QUANTILE_0_1), q01_file)
q09_file = hazard_export.export(
quantile_0_9_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_QUANTILE_0_9), q09_file)
finally:
shutil.rmtree(result_dir)
def check_export(output_id, target_dir):
"""
Call hazard.export by checking that the exported file is valid
according to our XML schema.
"""
return hazard.export(output_id, target_dir, check_schema=True)
def test_classical_hazard_export(self):
# Run a hazard calculation to compute some curves and maps
# Call the exporter and verify that files were created
# Since the hazard curve XML writer is concerned with correctly
# generating XML, we won't test that here.
target_dir = tempfile.mkdtemp()
try:
cfg = helpers.get_data_path('simple_fault_demo_hazard/job.ini')
# run the calculation to create something to export
helpers.run_hazard_job(cfg)
job = models.OqJob.objects.latest('id')
self.assertEqual(job.status, 'complete')
outputs = export_core.get_outputs(job.id)
# 10 hazard curves, 20 maps, 10 uhs, 5 multi curves
expected_outputs = 45
self.assertEqual(expected_outputs, outputs.count())
# Number of curves:
# (2 imts * 2 realizations)
# + (2 imts * (1 mean + 2 quantiles)
# = 10
curves = outputs.filter(output_type='hazard_curve')
self.assertEqual(10, curves.count())
# Number of multi-curves
# (2 realizations + 1 mean + 2 quantiles)
multi_curves = outputs.filter(output_type="hazard_curve_multi")
self.assertEqual(5, multi_curves.count())
# Number of maps:
# (2 poes * 2 imts * 2 realizations)
# + (2 poes * 2 imts * (1 mean + 2 quantiles))
# = 20
# Number of UHS:
maps = outputs.filter(output_type='hazard_map')
self.assertEqual(20, maps.count())
# Number of UHS:
# (20 maps_PGA_SA / 2 poes)
# = 10
uhs = outputs.filter(output_type='uh_spectra')
self.assertEqual(10, uhs.count())
# Test hazard curve export:
hc_files = []
for curve in curves:
hc_files.extend(check_export(curve.id, target_dir))
self.assertEqual(10, len(hc_files))
# Test multi hazard curve export:
hc_files = []
for curve in multi_curves:
hc_files.extend(hazard.export(curve.id, target_dir))
self.assertEqual(5, len(hc_files))
for f in hc_files:
self._test_exported_file(f)
# Test hazard map export:
hm_files = []
for haz_map in maps:
hm_files.extend(check_export(haz_map.id, target_dir))
self.assertEqual(20, len(hm_files))
for f in hm_files:
self._test_exported_file(f)
# Test UHS export:
uhs_files = []
for u in uhs:
uhs_files.extend(check_export(u.id, target_dir))
for f in uhs_files:
self._test_exported_file(f)
finally:
shutil.rmtree(target_dir)
def test(self):
result_dir = tempfile.mkdtemp()
aaae = numpy.testing.assert_array_almost_equal
try:
cfg = os.path.join(os.path.dirname(__file__), 'job.ini')
expected_curve_poes_b1_b2 = [0.0055, 0.00042, 5.77E-5, 0.0]
expected_curve_poes_b1_b3 = [0.00995, 0.00076, 9.7E-5, 0.0]
expected_curve_poes_b1_b4 = [0.018, 0.0013, 0.00014, 0.0]
expected_mean_poes = [0.01067, 0.0008, 9.774E-5, 0.0]
expected_q0_1_poes = [0.0055, 0.00042, 5.77E-5, 0.0]
expected_q0_9_poes = [0.013975, 0.00103, 0.0001185, 0.0]
job = self.run_hazard(cfg)
# Test the poe values for the two curves:
curve_b1_b2, curve_b1_b3, curve_b1_b4 = \
models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__lt_realization__isnull=False)\
.order_by('hazard_curve__lt_realization__sm_lt_path')
# Sanity check, to make sure we have the curves ordered correctly:
self.assertEqual(
['b1', 'b2'],
curve_b1_b2.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b3'],
curve_b1_b3.hazard_curve.lt_realization.sm_lt_path)
self.assertEqual(
['b1', 'b4'],
curve_b1_b4.hazard_curve.lt_realization.sm_lt_path)
aaae(expected_curve_poes_b1_b2, curve_b1_b2.poes, decimal=4)
aaae(expected_curve_poes_b1_b3, curve_b1_b3.poes, decimal=4)
aaae(expected_curve_poes_b1_b4, curve_b1_b4.poes, decimal=4)
# Test the mean curve:
[mean_curve] = models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__statistics='mean')
aaae(expected_mean_poes, mean_curve.poes, decimal=4)
# Test the quantile curves:
quantile_0_1_curve, quantile_0_9_curve = \
models.HazardCurveData.objects\
.filter(hazard_curve__output__oq_job=job.id,
hazard_curve__statistics='quantile')\
.order_by('hazard_curve__quantile')
aaae(expected_q0_1_poes, quantile_0_1_curve.poes, decimal=4)
aaae(expected_q0_9_poes, quantile_0_9_curve.poes, decimal=4)
# Test the exports as well:
[exported_file_b1_b2] = hazard_export.export(
curve_b1_b2.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B2),
exported_file_b1_b2)
[exported_file_b1_b3] = hazard_export.export(
curve_b1_b3.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B3),
exported_file_b1_b3)
[exported_file_b1_b4] = hazard_export.export(
curve_b1_b4.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_B1_B4),
exported_file_b1_b4)
[exported_file_mean] = hazard_export.export(
mean_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_MEAN),
exported_file_mean)
[q01_file] = hazard_export.export(
quantile_0_1_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_QUANTILE_0_1),
q01_file)
[q09_file] = hazard_export.export(
quantile_0_9_curve.hazard_curve.output.id, result_dir)
self.assert_xml_equal(
StringIO.StringIO(self.EXPECTED_XML_QUANTILE_0_9),
q09_file)
finally:
shutil.rmtree(result_dir)
def test_export_for_event_based(self):
# Run an event-based hazard calculation to compute SESs and GMFs
# Call the exporters for both SES and GMF results and verify that
# files were created
# Since the XML writers (in `openquake.nrmllib.writers`) are concerned
# with correctly generating the XML, we don't test that here...
# but we should still have an end-to-end QA test.
target_dir = tempfile.mkdtemp()
try:
cfg = helpers.demo_file('event_based_hazard/job.ini')
# run the calculation to create something to export
retcode = helpers.run_hazard_job_sp(cfg, silence=True)
self.assertEqual(0, retcode)
job = models.OqJob.objects.latest('id')
outputs = export_core.get_outputs(job.id)
# 2 GMFs, 2 SESs, 1 complete logic tree SES, 1 complete LT GMF,
# and 4 hazard curve collections
self.assertEqual(18, len(outputs))
#######
# SESs:
ses_outputs = outputs.filter(output_type='ses')
self.assertEqual(2, len(ses_outputs))
exported_files = []
for ses_output in ses_outputs:
files = hazard.export(ses_output.id, target_dir)
exported_files.extend(files)
self.assertEqual(2, len(exported_files))
for f in exported_files:
self._test_exported_file(f)
##################
# Complete LT SES:
[complete_lt_ses] = outputs.filter(output_type='complete_lt_ses')
[exported_file] = hazard.export(complete_lt_ses.id, target_dir)
self._test_exported_file(exported_file)
#######
# GMFs:
gmf_outputs = outputs.filter(output_type='gmf')
self.assertEqual(2, len(gmf_outputs))
exported_files = []
for gmf_output in gmf_outputs:
files = hazard.export(gmf_output.id, target_dir)
exported_files.extend(files)
self.assertEqual(2, len(exported_files))
# Check the file paths exist, are absolute, and the files aren't
# empty.
for f in exported_files:
self._test_exported_file(f)
##################
# Complete LT GMF:
[complete_lt_gmf] = outputs.filter(output_type='complete_lt_gmf')
[exported_file] = hazard.export(complete_lt_gmf.id, target_dir)
self._test_exported_file(exported_file)
# Check for the correct number of GMFs in the file:
tree = etree.parse(exported_file)
self.assertEqual(442, number_of('nrml:gmf', tree))
################
# Hazard curves:
haz_curves = outputs.filter(output_type='hazard_curve')
for curve in haz_curves:
[exported_file] = hazard.export(curve.id, target_dir)
self._test_exported_file(exported_file)
finally:
shutil.rmtree(target_dir)
