def setUp(self):
self.mixin = self.create_job_with_mixin({'CALCULATION_MODE': 'Hazard'},
opensha.ClassicalMixin)
# Store the canned result data in the KVS.
key = self.mixin.job_id
for realization in xrange(2):
key = "%s/%s" % (self.mixin.job_id, realization + 1)
TestStore.put(key, self.mock_results[realization])
self.keys.append(key)
LOG.debug("keys = '%s'" % self.keys)
# Initialize the mixin instance.
self.mixin.params = dict(NUMBER_OF_LOGIC_TREE_SAMPLES=2,
WIDTH_OF_MFD_BIN=1)
self.mixin.calc = self.FakeLogicTreeProcessor()
self.mixin.cache = dict()
def test_map_serializer_called_when_configured(self):
"""
The quantile map serialization function is called when the
POES parameter is specified in the configuration file.
"""
def fake_serializer(*args):
"""Fake serialization function to be used in this test."""
fake_serializer.number_of_calls += 1
fake_serializer.number_of_calls = 0
def fake_map_func(*args):
return ["quantile_hazard_map!10!-122.9!38.0!0.2",
"quantile_hazard_map!10!-121.9!38.0!0.2",
"quantile_hazard_map!10!-122.8!38.0!0.4",
"quantile_hazard_map!10!-121.8!38.0!0.4"]
key = TestStore.put(self.job_ctxt.job_id,
self.mock_results)
self.keys.append(key)
self.job_ctxt.params["POES"] = "0.6 0.8"
self.calculator.do_quantiles(
self.sites, 1, [0.2, 0.4],
curve_serializer=lambda _, __: True,
curve_task=test_data_reflector,
map_func=fake_map_func,
map_serializer=fake_serializer)
# The serializer is called once for each quantile.
self.assertEqual(2, fake_serializer.number_of_calls)
def test_map_serializer_called_when_configured(self):
"""
The mean map serialization function is called when the POES
parameter is specified in the configuration file.
"""
def fake_serializer(*args):
"""Fake serialization function to be used in this test."""
# Check that the data returned is the one we expect for the current
# realization.
fake_serializer.number_of_calls += 1
def fake_map_func(*args):
return list(xrange(3))
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.job_ctxt.params["POES"] = "0.6 0.8"
self.calculator.do_means(self.sites, 1,
curve_serializer=lambda _: True,
curve_task=test_data_reflector,
map_func=fake_map_func,
map_serializer=fake_serializer)
self.assertEqual(1, fake_serializer.number_of_calls)
def test_map_serializer_called_when_configured(self):
"""
The mean map serialization function is called when the POES
parameter is specified in the configuration file.
"""
def fake_serializer(*args):
"""Fake serialization function to be used in this test."""
# Check that the data returned is the one we expect for the current
# realization.
fake_serializer.number_of_calls += 1
def fake_map_func(*args):
return list(xrange(3))
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.job_ctxt.params["POES"] = "0.6 0.8"
self.calculator.do_means(self.sites,
1,
curve_serializer=lambda _: True,
curve_task=test_data_reflector,
map_func=fake_map_func,
map_serializer=fake_serializer)
self.assertEqual(1, fake_serializer.number_of_calls)
def test_map_serializer_called_when_configured(self):
"""
The quantile map serialization function is called when the
POES parameter is specified in the configuration file.
"""
def fake_serializer(*args):
"""Fake serialization function to be used in this test."""
fake_serializer.number_of_calls += 1
fake_serializer.number_of_calls = 0
def fake_map_func(*args):
return [
"quantile_hazard_map!10!-122.9!38.0!0.2",
"quantile_hazard_map!10!-121.9!38.0!0.2",
"quantile_hazard_map!10!-122.8!38.0!0.4",
"quantile_hazard_map!10!-121.8!38.0!0.4"
]
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.job_ctxt.params["POES"] = "0.6 0.8"
self.calculator.do_quantiles(self.sites,
1, [0.2, 0.4],
curve_serializer=lambda _, __: True,
curve_task=test_data_reflector,
map_func=fake_map_func,
map_serializer=fake_serializer)
# The serializer is called once for each quantile.
self.assertEqual(2, fake_serializer.number_of_calls)
def setUp(self):
params = dict(
CALCULATION_MODE='Hazard',
SOURCE_MODEL_LOGIC_TREE_FILE_PATH=SIMPLE_FAULT_SRC_MODEL_LT,
GMPE_LOGIC_TREE_FILE_PATH=SIMPLE_FAULT_GMPE_LT,
BASE_PATH=SIMPLE_FAULT_BASE_PATH, OUTPUT_DIR="output",
NUMBER_OF_LOGIC_TREE_SAMPLES=2, WIDTH_OF_MFD_BIN=1)
self.job_ctxt = create_job(params, job_id=99)
self.calculator = classical.ClassicalHazardCalculator(self.job_ctxt)
# Store the canned result data in the KVS.
key = self.job_ctxt.job_id
for realization in xrange(2):
key = "%s/%s" % (self.job_ctxt.job_id, realization + 1)
TestStore.put(key, self.mock_results[realization])
self.keys.append(key)
LOG.debug("keys = '%s'" % self.keys)
self.calculator.calc = self.FakeLogicTreeProcessor()
self.calculator.cache = dict()
def setUp(self):
params = dict(
CALCULATION_MODE='Hazard',
SOURCE_MODEL_LOGIC_TREE_FILE_PATH=SIMPLE_FAULT_SRC_MODEL_LT,
GMPE_LOGIC_TREE_FILE_PATH=SIMPLE_FAULT_GMPE_LT,
BASE_PATH=SIMPLE_FAULT_BASE_PATH, OUTPUT_DIR="output",
NUMBER_OF_LOGIC_TREE_SAMPLES=2, WIDTH_OF_MFD_BIN=1)
self.job_ctxt = create_job(params)
self.calculator = classical.ClassicalHazardCalculator(self.job_ctxt)
# Store the canned result data in the KVS.
key = self.job_ctxt.job_id
for realization in xrange(2):
key = "%s/%s" % (self.job_ctxt.job_id, realization + 1)
TestStore.put(key, self.mock_results[realization])
self.keys.append(key)
LOG.debug("keys = '%s'" % self.keys)
self.calculator.calc = self.FakeLogicTreeProcessor()
self.calculator.cache = dict()
def test_curve_serializer_called_when_passed(self):
"""The passed quantile curve serialization function is called."""
def fake_serializer(**kwargs):
"""Fake serialization function to be used in this test."""
fake_serializer.number_of_calls += 1
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.calculator.do_quantiles(
self.sites, 1, [0.2, 0.4], curve_serializer=fake_serializer,
curve_task=test_async_data_reflector)
# The serializer is called only once (for all quantiles).
self.assertEqual(1, fake_serializer.number_of_calls)
def test_curve_serializer_called_when_passed(self):
"""The passed quantile curve serialization function is called."""
def fake_serializer(**kwargs):
"""Fake serialization function to be used in this test."""
fake_serializer.number_of_calls += 1
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.calculator.do_quantiles(self.sites,
1, [0.2, 0.4],
curve_serializer=fake_serializer,
curve_task=test_async_data_reflector)
# The serializer is called only once (for all quantiles).
self.assertEqual(1, fake_serializer.number_of_calls)
def test_missing_map_serializer_assertion(self):
"""
When the quantile map serialization function is not set an
`AssertionError` is raised.
TODO: once everyone is on python rev. > 2.7 extend the test to check
for the specific assertion message.
"""
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.job_ctxt.params["POES"] = "0.6 0.8"
self.assertRaises(
AssertionError, self.calculator.do_quantiles,
self.sites, 1, [0.5],
curve_serializer=lambda _, __: True,
curve_task=test_data_reflector, map_func=lambda _: [1, 2, 3])
def test_missing_map_function_assertion(self):
"""
When the mean map calculation function is not set an `AssertionError`
is raised.
TODO: once everyone is on python rev. > 2.7 extend the test to check
for the specific assertion message.
"""
key = TestStore.put(self.mixin.job_id, self.mock_results)
self.keys.append(key)
self.mixin.params["POES"] = "0.6 0.8"
self.assertRaises(
AssertionError, self.mixin.do_means,
self.sites, 1,
curve_serializer=lambda _: True, curve_task=test_data_reflector,
map_serializer=lambda _: True, map_func=None)
def test_missing_map_serializer_assertion(self):
"""
When the quantile map serialization function is not set an
`AssertionError` is raised.
TODO: once everyone is on python rev. > 2.7 extend the test to check
for the specific assertion message.
"""
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.job_ctxt.params["POES"] = "0.6 0.8"
self.assertRaises(
AssertionError, self.calculator.do_quantiles,
self.sites, 1, [0.5],
curve_serializer=lambda _, __: True,
curve_task=test_data_reflector, map_func=lambda _: [1, 2, 3])
def test_curve_serializer_called_when_passed(self):
"""The passed mean curve serialization function is called."""
def fake_serializer(sites, **kwargs):
"""Fake serialization function to be used in this test."""
self.assertEqual(self.sites, sites)
fake_serializer.number_of_calls += 1
# Count the number of invocations using this property of the fake
# serializer function.
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.calculator.do_means(
self.sites, 1, curve_serializer=fake_serializer,
curve_task=test_async_data_reflector)
self.assertEqual(1, fake_serializer.number_of_calls)
def test_curve_serializer_called_when_passed(self):
"""The passed mean curve serialization function is called."""
def fake_serializer(sites, **kwargs):
"""Fake serialization function to be used in this test."""
self.assertEqual(self.sites, sites)
fake_serializer.number_of_calls += 1
# Count the number of invocations using this property of the fake
# serializer function.
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.calculator.do_means(self.sites,
1,
curve_serializer=fake_serializer,
curve_task=test_async_data_reflector)
self.assertEqual(1, fake_serializer.number_of_calls)
def test_map_serializer_not_called_unless_configured(self):
"""
The mean map serialization function is not called unless the
POES parameter was specified in the configuration file.
"""
def fake_serializer(kvs_keys):
"""Fake serialization function to be used in this test."""
# Check that the data returned is the one we expect for the current
# realization.
fake_serializer.number_of_calls += 1
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.calculator.do_means(self.sites, 1,
curve_serializer=lambda _: True,
curve_task=test_data_reflector)
self.assertEqual(0, fake_serializer.number_of_calls)
def test_map_serializer_not_called_unless_configured(self):
"""
The mean map serialization function is not called unless the
POES parameter was specified in the configuration file.
"""
def fake_serializer(kvs_keys):
"""Fake serialization function to be used in this test."""
# Check that the data returned is the one we expect for the current
# realization.
fake_serializer.number_of_calls += 1
fake_serializer.number_of_calls = 0
key = TestStore.put(self.job_ctxt.job_id, self.mock_results)
self.keys.append(key)
self.calculator.do_means(self.sites,
1,
curve_serializer=lambda _: True,
curve_task=test_data_reflector)
self.assertEqual(0, fake_serializer.number_of_calls)
