def test_hypocentres_as_mesh(self):
# Tests the function to render the hypocentres to a
# hazardlib.geo.mesh.Mesh object.
cat = Catalogue()
cat.data['longitude'] = np.array([2., 3.])
cat.data['latitude'] = np.array([2., 3.])
cat.data['depth'] = np.array([2., 3.])
self.assertTrue(isinstance(cat.hypocentres_as_mesh(), Mesh))
def test_hypocentres_as_mesh(self):
# Tests the function to render the hypocentres to a
# hazardlib.geo.mesh.Mesh object.
cat = Catalogue()
cat.data['longitude'] = np.array([2., 3.])
cat.data['latitude'] = np.array([2., 3.])
cat.data['depth'] = np.array([2., 3.])
self.assertTrue(isinstance(cat.hypocentres_as_mesh(), Mesh))
class TestSelector(unittest.TestCase):
'''
Tests the hmtk.seismicity.selector.Selector class
'''
def setUp(self):
'''
'''
self.catalogue = Catalogue()
self.polygon = None
def test_check_on_depth_limits(self):
'''
Tests the checks on depth limits
'''
test_dict = {'upper_depth': None, 'lower_depth': None}
self.assertTupleEqual((0.0, np.inf), _check_depth_limits(test_dict))
test_dict = {'upper_depth': 2.0, 'lower_depth': None}
self.assertTupleEqual((2.0, np.inf), _check_depth_limits(test_dict))
test_dict = {'upper_depth': None, 'lower_depth': 10.0}
self.assertTupleEqual((0.0, 10.0), _check_depth_limits(test_dict))
test_dict = {'upper_depth': -4.2, 'lower_depth': None}
self.assertRaises(ValueError, _check_depth_limits, test_dict)
test_dict = {'upper_depth': 5.0, 'lower_depth': 1.0}
self.assertRaises(ValueError, _check_depth_limits, test_dict)
def test_convert_datetime_to_decimal(self):
'''
Tests the function to convert a time from a datetime object to a
decimal - simple test to check conversion
NB Still will not work for BCE dates
'''
simple_time = datetime.datetime(1900, 6, 6, 1, 1, 1, 0)
self.assertAlmostEqual(_get_decimal_from_datetime(simple_time),
1900.42751335)
def test_catalogue_selection(self):
'''
Tests the tools for selecting events within the catalogue
'''
self.catalogue.data['longitude'] = np.arange(1.,6., 1.)
self.catalogue.data['latitude'] = np.arange(6., 11., 1.)
self.catalogue.data['depth'] = np.ones(5, dtype=bool)
# No events selected
flag_none = np.zeros(5, dtype=bool)
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.select_catalogue(flag_none)
self.assertEqual(len(test_cat1.data['longitude']), 0)
self.assertEqual(len(test_cat1.data['latitude']), 0)
self.assertEqual(len(test_cat1.data['depth']), 0)
# All events selected
flag_all = np.ones(5, dtype=bool)
test_cat1 = selector0.select_catalogue(flag_all)
self.assertTrue(np.allclose(test_cat1.data['longitude'],
self.catalogue.data['longitude']))
self.assertTrue(np.allclose(test_cat1.data['latitude'],
self.catalogue.data['latitude']))
self.assertTrue(np.allclose(test_cat1.data['depth'],
self.catalogue.data['depth']))
# Some events selected
flag_1 = np.array([True, False, True, False, True])
test_cat1 = selector0.select_catalogue(flag_1)
self.assertTrue(np.allclose(test_cat1.data['longitude'],
np.array([1., 3., 5.])))
self.assertTrue(np.allclose(test_cat1.data['latitude'],
np.array([6., 8., 10])))
self.assertTrue(np.allclose(test_cat1.data['depth'],
np.array([1., 1., 1.])))
def test_select_within_polygon(self):
'''
Tests the selection of points within polygon
'''
# Setup polygon
nodes = np.array([[5.0, 6.0], [6.0, 6.0], [6.0, 5.0], [5.0, 5.0]])
polygon0 = Polygon([Point(nodes[iloc, 0], nodes[iloc, 1])
for iloc in range(0, 4)])
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
# Simple case with nodes inside, outside and on the border of polygon
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.within_polygon(polygon0)
self.assertTrue(np.allclose(test_cat1.data['longitude'],
np.array([5.0, 5.5, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['latitude'],
np.array([5.0, 5.5, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['depth'],
np.array([1.0, 1.0, 1.0])))
# CASE 2: As case 1 with one of the inside nodes outside of the depths
self.catalogue.data['depth'] = \
np.array([1.0, 1.0, 1.0, 50.0, 1.0, 1.0, 1.0], dtype=float)
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.within_polygon(polygon0, upper_depth=0.0,
lower_depth=10.0)
self.assertTrue(np.allclose(test_cat1.data['longitude'],
np.array([5.0, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['latitude'],
np.array([5.0, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['depth'],
np.array([1.0])))
def test_point_in_circular_distance(self):
'''
Tests point in circular distance
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
test_point = Point(5.5, 5.5)
test_mesh = self.catalogue.hypocentres_as_mesh()
selector0 = CatalogueSelector(self.catalogue)
# Within 10 km
test_cat_10 = selector0.circular_distance_from_point(
test_point, 10., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_10.data['longitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['latitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['depth'],
np.array([1.0]))
# Within 100 km
test_cat_100 = selector0.circular_distance_from_point(
test_point, 100., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Within 1000 km
test_cat_1000 = selector0.circular_distance_from_point(
test_point, 1000., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_1000.data['longitude'],
self.catalogue.data['longitude'])
np.testing.assert_array_equal(test_cat_1000.data['latitude'],
self.catalogue.data['latitude'])
np.testing.assert_array_equal(test_cat_1000.data['depth'],
self.catalogue.data['depth'])
def test_cartesian_square_on_point(self):
'''
Tests the cartesian square centres on point
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
test_point = Point(5.5, 5.5)
test_mesh = self.catalogue.hypocentres_as_mesh()
selector0 = CatalogueSelector(self.catalogue)
# Within 10 km
test_cat_10 = selector0.cartesian_square_centred_on_point(
test_point, 10., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_10.data['longitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['latitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['depth'],
np.array([1.0]))
# Within 100 km
test_cat_100 = selector0.cartesian_square_centred_on_point(
test_point, 100., distance_type='epicentral')
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Within 1000 km
test_cat_1000 = selector0.cartesian_square_centred_on_point(
test_point, 1000., distance_type='epicentral')
np.testing.assert_array_almost_equal(test_cat_1000.data['longitude'],
self.catalogue.data['longitude'])
np.testing.assert_array_almost_equal(test_cat_1000.data['latitude'],
self.catalogue.data['latitude'])
np.testing.assert_array_almost_equal(test_cat_1000.data['depth'],
self.catalogue.data['depth'])
def test_within_joyner_boore_distance(self):
'''
Tests the function to select within Joyner-Boore distance
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
selector0 = CatalogueSelector(self.catalogue)
# Construct Fault
trace0 = np.array([[5.5, 6.0], [5.5, 5.0]])
fault_trace = Line([Point(trace0[i, 0], trace0[i, 1])
for i in range(0, 2)])
# Simple fault with vertical dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 90.,
1.)
# Within 100 km
test_cat_100 = selector0.within_joyner_boore_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Simple fault with 30 degree dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 30.,
1.)
# Within 100 km
test_cat_100 = selector0.within_joyner_boore_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0, 1.0]))
def test_within_rupture_distance(self):
'''
Tests the function to select within Joyner-Boore distance
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
selector0 = CatalogueSelector(self.catalogue)
# Construct Fault
trace0 = np.array([[5.5, 6.0], [5.5, 5.0]])
fault_trace = Line([Point(trace0[i, 0], trace0[i, 1])
for i in range(0, 2)])
# Simple fault with vertical dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 90.,
1.)
# Within 100 km
test_cat_100 = selector0.within_rupture_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Simple fault with 30 degree dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 30.,
1.)
# Within 100 km
test_cat_100 = selector0.within_rupture_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0, 1.0]))
def test_select_within_time(self):
'''
Tests the function to select within a time period
'''
self.catalogue.data['year'] = np.arange(1900, 2010, 20)
self.catalogue.data['month'] = np.arange(1, 12, 2)
self.catalogue.data['day'] = np.ones(6, dtype=int)
self.catalogue.data['hour'] = np.ones(6, dtype=int)
self.catalogue.data['minute'] = np.zeros(6, dtype=int)
self.catalogue.data['second'] = np.ones(6, dtype=float)
selector0 = CatalogueSelector(self.catalogue)
# Start time and End time not defined
test_cat_1 = selector0.within_time_period()
self._compare_time_data_dictionaries(test_cat_1.data,
self.catalogue.data)
# Start time defined - end time not defined
begin_time = datetime.datetime(1975, 1, 1, 0, 0, 0, 0)
expected_data = {'year': np.array([1980, 2000]),
'month': np.array([9, 11]),
'day': np.array([1, 1]),
'hour': np.array([1, 1]),
'minute': np.array([0, 0]),
'second': np.array([1., 1.])}
test_cat_1 = selector0.within_time_period(start_time=begin_time)
self._compare_time_data_dictionaries(expected_data, test_cat_1.data)
# Test 3 - Start time not defined, end-time defined
finish_time = datetime.datetime(1965, 1, 1, 0, 0, 0, 0)
expected_data = {'year': np.array([1900, 1920, 1940, 1960]),
'month': np.array([1, 3, 5, 7]),
'day': np.array([1, 1, 1, 1]),
'hour': np.array([1, 1, 1, 1]),
'minute': np.array([0, 0, 0, 0]),
'second': np.array([1., 1., 1., 1.])}
test_cat_1 = selector0.within_time_period(end_time=finish_time)
self._compare_time_data_dictionaries(expected_data, test_cat_1.data)
# Test 4 - both start time and end-time defined
begin_time = datetime.datetime(1935, 1, 1, 0, 0, 0, 0)
finish_time = datetime.datetime(1995, 1, 1, 0, 0, 0, 0)
expected_data = {'year': np.array([1940, 1960, 1980]),
'month': np.array([5, 7, 9]),
'day': np.array([1, 1, 1]),
'hour': np.array([1, 1, 1]),
'minute': np.array([0, 0, 0]),
'second': np.array([1., 1., 1.])}
test_cat_1 = selector0.within_time_period(begin_time, finish_time)
self._compare_time_data_dictionaries(expected_data, test_cat_1.data)
def _compare_time_data_dictionaries(self, expected, modelled):
'''
Compares the relevent time and date information in the catalogue
data dictionaries
'''
time_keys = ['year', 'month', 'day', 'hour', 'minute', 'second']
for key in time_keys:
# The second value is a float - all others are integers
if 'second' in key:
np.testing.assert_array_almost_equal(expected[key],
modelled[key])
else:
np.testing.assert_array_equal(expected[key], modelled[key])
def test_select_within_depth_range(self):
'''
Tests the function to select within the depth range
'''
# Setup function
self.catalogue = Catalogue()
self.catalogue.data['depth'] = np.array([5., 15., 25., 35., 45.])
selector0 = CatalogueSelector(self.catalogue)
# Test case 1: No limits specified - all catalogue valid
test_cat_1 = selector0.within_depth_range()
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
self.catalogue.data['depth'])
# Test case 2: Lower depth limit specfied only
test_cat_1 = selector0.within_depth_range(lower_depth=30.)
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
np.array([5., 15., 25.]))
# Test case 3: Upper depth limit specified only
test_cat_1 = selector0.within_depth_range(upper_depth=20.)
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
np.array([25., 35., 45.]))
# Test case 4: Both depth limits specified
test_cat_1 = selector0.within_depth_range(upper_depth=20.,
lower_depth=40.)
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
np.array([25., 35.]))
def test_select_within_magnitude_range(self):
'''
Tests the function to select within the magnitude range
'''
# Setup function
self.catalogue = Catalogue()
self.catalogue.data['magnitude'] = np.array([4., 5., 6., 7., 8.])
selector0 = CatalogueSelector(self.catalogue)
# Test case 1: No limits specified - all catalogue valid
test_cat_1 = selector0.within_magnitude_range()
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
self.catalogue.data['magnitude'])
# Test case 2: Lower depth limit specfied only
test_cat_1 = selector0.within_magnitude_range(lower_mag=5.5)
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
np.array([6., 7., 8.]))
# Test case 3: Upper depth limit specified only
test_cat_1 = selector0.within_magnitude_range(upper_mag=5.5)
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
np.array([4., 5.]))
# Test case 4: Both depth limits specified
test_cat_1 = selector0.within_magnitude_range(upper_mag=7.5,
lower_mag=5.5)
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
np.array([6., 7.]))
class TestSelector(unittest.TestCase):
'''
Tests the hmtk.seismicity.selector.Selector class
'''
def setUp(self):
'''
'''
self.catalogue = Catalogue()
self.polygon = None
def test_check_on_depth_limits(self):
'''
Tests the checks on depth limits
'''
test_dict = {'upper_depth': None, 'lower_depth': None}
self.assertTupleEqual((0.0, np.inf), _check_depth_limits(test_dict))
test_dict = {'upper_depth': 2.0, 'lower_depth': None}
self.assertTupleEqual((2.0, np.inf), _check_depth_limits(test_dict))
test_dict = {'upper_depth': None, 'lower_depth': 10.0}
self.assertTupleEqual((0.0, 10.0), _check_depth_limits(test_dict))
test_dict = {'upper_depth': -4.2, 'lower_depth': None}
self.assertRaises(ValueError, _check_depth_limits, test_dict)
test_dict = {'upper_depth': 5.0, 'lower_depth': 1.0}
self.assertRaises(ValueError, _check_depth_limits, test_dict)
def test_convert_datetime_to_decimal(self):
'''
Tests the function to convert a time from a datetime object to a
decimal - simple test to check conversion
NB Still will not work for BCE dates
'''
simple_time = datetime.datetime(1900, 6, 6, 1, 1, 1, 0)
self.assertAlmostEqual(_get_decimal_from_datetime(simple_time),
1900.42751335)
def test_catalogue_selection(self):
'''
Tests the tools for selecting events within the catalogue
'''
self.catalogue.data['longitude'] = np.arange(1., 6., 1.)
self.catalogue.data['latitude'] = np.arange(6., 11., 1.)
self.catalogue.data['depth'] = np.ones(5, dtype=bool)
# No events selected
flag_none = np.zeros(5, dtype=bool)
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.select_catalogue(flag_none)
self.assertEqual(len(test_cat1.data['longitude']), 0)
self.assertEqual(len(test_cat1.data['latitude']), 0)
self.assertEqual(len(test_cat1.data['depth']), 0)
# All events selected
flag_all = np.ones(5, dtype=bool)
test_cat1 = selector0.select_catalogue(flag_all)
self.assertTrue(
np.allclose(test_cat1.data['longitude'],
self.catalogue.data['longitude']))
self.assertTrue(
np.allclose(test_cat1.data['latitude'],
self.catalogue.data['latitude']))
self.assertTrue(
np.allclose(test_cat1.data['depth'], self.catalogue.data['depth']))
# Some events selected
flag_1 = np.array([True, False, True, False, True])
test_cat1 = selector0.select_catalogue(flag_1)
self.assertTrue(
np.allclose(test_cat1.data['longitude'], np.array([1., 3., 5.])))
self.assertTrue(
np.allclose(test_cat1.data['latitude'], np.array([6., 8., 10])))
self.assertTrue(
np.allclose(test_cat1.data['depth'], np.array([1., 1., 1.])))
def test_select_within_polygon(self):
'''
Tests the selection of points within polygon
'''
# Setup polygon
nodes = np.array([[5.0, 6.0], [6.0, 6.0], [6.0, 5.0], [5.0, 5.0]])
polygon0 = Polygon(
[Point(nodes[iloc, 0], nodes[iloc, 1]) for iloc in range(0, 4)])
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
# Simple case with nodes inside, outside and on the border of polygon
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.within_polygon(polygon0)
self.assertTrue(
np.allclose(test_cat1.data['longitude'], np.array([5.0, 5.5,
6.0])))
self.assertTrue(
np.allclose(test_cat1.data['latitude'], np.array([5.0, 5.5, 6.0])))
self.assertTrue(
np.allclose(test_cat1.data['depth'], np.array([1.0, 1.0, 1.0])))
# CASE 2: As case 1 with one of the inside nodes outside of the depths
self.catalogue.data['depth'] = \
np.array([1.0, 1.0, 1.0, 50.0, 1.0, 1.0, 1.0], dtype=float)
selector0 = CatalogueSelector(self.catalogue)
test_cat1 = selector0.within_polygon(polygon0,
upper_depth=0.0,
lower_depth=10.0)
self.assertTrue(
np.allclose(test_cat1.data['longitude'], np.array([5.0, 6.0])))
self.assertTrue(
np.allclose(test_cat1.data['latitude'], np.array([5.0, 6.0])))
self.assertTrue(np.allclose(test_cat1.data['depth'], np.array([1.0])))
def test_point_in_circular_distance(self):
'''
Tests point in circular distance
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
test_point = Point(5.5, 5.5)
test_mesh = self.catalogue.hypocentres_as_mesh()
selector0 = CatalogueSelector(self.catalogue)
# Within 10 km
test_cat_10 = selector0.circular_distance_from_point(
test_point, 10., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_10.data['longitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['latitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['depth'],
np.array([1.0]))
# Within 100 km
test_cat_100 = selector0.circular_distance_from_point(
test_point, 100., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Within 1000 km
test_cat_1000 = selector0.circular_distance_from_point(
test_point, 1000., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_1000.data['longitude'],
self.catalogue.data['longitude'])
np.testing.assert_array_equal(test_cat_1000.data['latitude'],
self.catalogue.data['latitude'])
np.testing.assert_array_equal(test_cat_1000.data['depth'],
self.catalogue.data['depth'])
def test_cartesian_square_on_point(self):
'''
Tests the cartesian square centres on point
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
test_point = Point(5.5, 5.5)
test_mesh = self.catalogue.hypocentres_as_mesh()
selector0 = CatalogueSelector(self.catalogue)
# Within 10 km
test_cat_10 = selector0.cartesian_square_centred_on_point(
test_point, 10., distance_type='epicentral')
np.testing.assert_array_equal(test_cat_10.data['longitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['latitude'],
np.array([5.5]))
np.testing.assert_array_equal(test_cat_10.data['depth'],
np.array([1.0]))
# Within 100 km
test_cat_100 = selector0.cartesian_square_centred_on_point(
test_point, 100., distance_type='epicentral')
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Within 1000 km
test_cat_1000 = selector0.cartesian_square_centred_on_point(
test_point, 1000., distance_type='epicentral')
np.testing.assert_array_almost_equal(test_cat_1000.data['longitude'],
self.catalogue.data['longitude'])
np.testing.assert_array_almost_equal(test_cat_1000.data['latitude'],
self.catalogue.data['latitude'])
np.testing.assert_array_almost_equal(test_cat_1000.data['depth'],
self.catalogue.data['depth'])
def test_within_joyner_boore_distance(self):
'''
Tests the function to select within Joyner-Boore distance
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
selector0 = CatalogueSelector(self.catalogue)
# Construct Fault
trace0 = np.array([[5.5, 6.0], [5.5, 5.0]])
fault_trace = Line(
[Point(trace0[i, 0], trace0[i, 1]) for i in range(0, 2)])
# Simple fault with vertical dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 90.,
1.)
# Within 100 km
test_cat_100 = selector0.within_joyner_boore_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Simple fault with 30 degree dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 30.,
1.)
# Within 100 km
test_cat_100 = selector0.within_joyner_boore_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0, 1.0]))
def test_within_rupture_distance(self):
'''
Tests the function to select within Joyner-Boore distance
'''
self.catalogue.data['longitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['latitude'] = np.arange(4.0, 7.5, 0.5)
self.catalogue.data['depth'] = np.ones(7, dtype=float)
selector0 = CatalogueSelector(self.catalogue)
# Construct Fault
trace0 = np.array([[5.5, 6.0], [5.5, 5.0]])
fault_trace = Line(
[Point(trace0[i, 0], trace0[i, 1]) for i in range(0, 2)])
# Simple fault with vertical dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 90.,
1.)
# Within 100 km
test_cat_100 = selector0.within_rupture_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0]))
# Simple fault with 30 degree dip
fault0 = SimpleFaultSurface.from_fault_data(fault_trace, 0., 20., 30.,
1.)
# Within 100 km
test_cat_100 = selector0.within_rupture_distance(fault0, 100.)
np.testing.assert_array_almost_equal(test_cat_100.data['longitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['latitude'],
np.array([4.5, 5.0, 5.5, 6.0]))
np.testing.assert_array_almost_equal(test_cat_100.data['depth'],
np.array([1.0, 1.0, 1.0, 1.0]))
def test_select_within_time(self):
'''
Tests the function to select within a time period
'''
self.catalogue.data['year'] = np.arange(1900, 2010, 20)
self.catalogue.data['month'] = np.arange(1, 12, 2)
self.catalogue.data['day'] = np.ones(6, dtype=int)
self.catalogue.data['hour'] = np.ones(6, dtype=int)
self.catalogue.data['minute'] = np.zeros(6, dtype=int)
self.catalogue.data['second'] = np.ones(6, dtype=float)
selector0 = CatalogueSelector(self.catalogue)
# Start time and End time not defined
test_cat_1 = selector0.within_time_period()
self._compare_time_data_dictionaries(test_cat_1.data,
self.catalogue.data)
# Start time defined - end time not defined
begin_time = datetime.datetime(1975, 1, 1, 0, 0, 0, 0)
expected_data = {
'year': np.array([1980, 2000]),
'month': np.array([9, 11]),
'day': np.array([1, 1]),
'hour': np.array([1, 1]),
'minute': np.array([0, 0]),
'second': np.array([1., 1.])
}
test_cat_1 = selector0.within_time_period(start_time=begin_time)
self._compare_time_data_dictionaries(expected_data, test_cat_1.data)
# Test 3 - Start time not defined, end-time defined
finish_time = datetime.datetime(1965, 1, 1, 0, 0, 0, 0)
expected_data = {
'year': np.array([1900, 1920, 1940, 1960]),
'month': np.array([1, 3, 5, 7]),
'day': np.array([1, 1, 1, 1]),
'hour': np.array([1, 1, 1, 1]),
'minute': np.array([0, 0, 0, 0]),
'second': np.array([1., 1., 1., 1.])
}
test_cat_1 = selector0.within_time_period(end_time=finish_time)
self._compare_time_data_dictionaries(expected_data, test_cat_1.data)
# Test 4 - both start time and end-time defined
begin_time = datetime.datetime(1935, 1, 1, 0, 0, 0, 0)
finish_time = datetime.datetime(1995, 1, 1, 0, 0, 0, 0)
expected_data = {
'year': np.array([1940, 1960, 1980]),
'month': np.array([5, 7, 9]),
'day': np.array([1, 1, 1]),
'hour': np.array([1, 1, 1]),
'minute': np.array([0, 0, 0]),
'second': np.array([1., 1., 1.])
}
test_cat_1 = selector0.within_time_period(begin_time, finish_time)
self._compare_time_data_dictionaries(expected_data, test_cat_1.data)
def _compare_time_data_dictionaries(self, expected, modelled):
'''
Compares the relevent time and date information in the catalogue
data dictionaries
'''
time_keys = ['year', 'month', 'day', 'hour', 'minute', 'second']
for key in time_keys:
# The second value is a float - all others are integers
if 'second' in key:
np.testing.assert_array_almost_equal(expected[key],
modelled[key])
else:
np.testing.assert_array_equal(expected[key], modelled[key])
def test_select_within_depth_range(self):
'''
Tests the function to select within the depth range
'''
# Setup function
self.catalogue = Catalogue()
self.catalogue.data['depth'] = np.array([5., 15., 25., 35., 45.])
selector0 = CatalogueSelector(self.catalogue)
# Test case 1: No limits specified - all catalogue valid
test_cat_1 = selector0.within_depth_range()
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
self.catalogue.data['depth'])
# Test case 2: Lower depth limit specfied only
test_cat_1 = selector0.within_depth_range(lower_depth=30.)
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
np.array([5., 15., 25.]))
# Test case 3: Upper depth limit specified only
test_cat_1 = selector0.within_depth_range(upper_depth=20.)
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
np.array([25., 35., 45.]))
# Test case 4: Both depth limits specified
test_cat_1 = selector0.within_depth_range(upper_depth=20.,
lower_depth=40.)
np.testing.assert_array_almost_equal(test_cat_1.data['depth'],
np.array([25., 35.]))
def test_select_within_magnitude_range(self):
'''
Tests the function to select within the magnitude range
'''
# Setup function
self.catalogue = Catalogue()
self.catalogue.data['magnitude'] = np.array([4., 5., 6., 7., 8.])
selector0 = CatalogueSelector(self.catalogue)
# Test case 1: No limits specified - all catalogue valid
test_cat_1 = selector0.within_magnitude_range()
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
self.catalogue.data['magnitude'])
# Test case 2: Lower depth limit specfied only
test_cat_1 = selector0.within_magnitude_range(lower_mag=5.5)
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
np.array([6., 7., 8.]))
# Test case 3: Upper depth limit specified only
test_cat_1 = selector0.within_magnitude_range(upper_mag=5.5)
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
np.array([4., 5.]))
# Test case 4: Both depth limits specified
test_cat_1 = selector0.within_magnitude_range(upper_mag=7.5,
lower_mag=5.5)
np.testing.assert_array_almost_equal(test_cat_1.data['magnitude'],
np.array([6., 7.]))
