def test_filtering_non_empty_eq_catalog(self):
eq_internal_point = [2000, 1, 2, -0.25, 0.25]
eq_side_point = [2000, 1, 2, -0.5, 0.25]
eq_external_point = [2000, 1, 2, 0.5, 0.25]
eq_catalog = np.array([eq_internal_point, eq_side_point, eq_external_point])
sm_filter = SourceModelCatalogFilter()
expected_catalog = np.array([eq_internal_point])
self.assertTrue(np.array_equal(expected_catalog, sm_filter.filter_eqs(self.sm_geometry, eq_catalog)))
def test_source_model_calling_a_filter(self):
sm_filter = SourceModelCatalogFilter()
sm_filter.filter_eqs = Mock()
sm_filter.filter_eqs.return_value = []
catalog_filter = CatalogFilter(sm_filter)
gen = catalog_filter.filter_eqs([dict(a=1), dict(b=2)], [])
self.assertEqual((dict(a=1), []), gen.next())
self.assertEqual((dict(b=2), []), gen.next())
self.assertEqual(dict(a=1), sm_filter.filter_eqs.call_args_list[0][0][0])
self.assertEqual(dict(b=2), sm_filter.filter_eqs.call_args_list[1][0][0])
def test_filtering_non_empty_eq_catalog(self):
eq_internal_point = [2000, 1, 2, -0.25, 0.25]
eq_side_point = [2000, 1, 2, -0.5, 0.25]
eq_external_point = [2000, 1, 2, 0.5, 0.25]
eq_catalog = np.array(
[eq_internal_point, eq_side_point, eq_external_point])
sm_filter = SourceModelCatalogFilter()
expected_catalog = np.array([eq_internal_point])
self.assertTrue(
np.array_equal(expected_catalog,
sm_filter.filter_eqs(self.sm_geometry, eq_catalog)))
def test_source_model_calling_a_filter(self):
sm_filter = SourceModelCatalogFilter()
sm_filter.filter_eqs = Mock()
sm_filter.filter_eqs.return_value = []
catalog_filter = CatalogFilter(sm_filter)
gen = catalog_filter.filter_eqs([dict(a=1), dict(b=2)], [])
self.assertEqual((dict(a=1), []), gen.next())
self.assertEqual((dict(b=2), []), gen.next())
self.assertEqual(dict(a=1),
sm_filter.filter_eqs.call_args_list[0][0][0])
self.assertEqual(dict(b=2),
sm_filter.filter_eqs.call_args_list[1][0][0])
from mtoolkit.catalog_filter import CatalogFilter, SourceModelCatalogFilter
if __name__ == '__main__':
CMD_LINE_ARGS = cmd_line()
if CMD_LINE_ARGS:
INPUT_CONFIG_FILENAME = CMD_LINE_ARGS.input_file[0]
LOG_LEVEL = logging.DEBUG if CMD_LINE_ARGS.detailed else logging.INFO
build_logger(LOG_LEVEL)
CONTEXT = Context(INPUT_CONFIG_FILENAME)
PIPELINE_PREPROCESSING = PreprocessingBuilder().build(CONTEXT.config)
PIPELINE_PROCESSING = ProcessingBuilder().build(CONTEXT.config)
if CONTEXT.config['source_model_file']:
CATALOG_FILTER = CatalogFilter(SourceModelCatalogFilter())
else:
CATALOG_FILTER = CatalogFilter()
WORKFLOW = Workflow(PIPELINE_PREPROCESSING, PIPELINE_PROCESSING)
WORKFLOW.start(CONTEXT, CATALOG_FILTER)
WRITER = AreaSourceWriter(CONTEXT.config['result_file'])
WRITER.serialize(CONTEXT.sm_definitions)
def test_filtering_an_empty_eq_catalog(self):
sm_filter = SourceModelCatalogFilter()
self.assertTrue(np.allclose(self.empty_catalog, sm_filter.filter_eqs(self.sm_geometry, self.empty_catalog)))
def test_a_bad_polygon_raises_exception(self):
self.sm_geometry = build_geometry([1, 1, 1, 2, 2, 1, 2, 2])
sm_filter = SourceModelCatalogFilter()
self.assertRaises(RuntimeError, sm_filter.filter_eqs, self.sm_geometry,
self.empty_catalog)
def test_filtering_an_empty_eq_catalog(self):
sm_filter = SourceModelCatalogFilter()
self.assertTrue(
np.allclose(
self.empty_catalog,
sm_filter.filter_eqs(self.sm_geometry, self.empty_catalog)))
def run(workflow, context):
"""Run the workflow with source model filtering"""
return workflow.start(context, CatalogFilter(SourceModelCatalogFilter()))
