def test_get_mmax(self):
'''
Tests the function to get Mmax
Values come from WC1994 (tested in openquake.hazardlib) - only
functionality is tested for here!
'''
# Case 1 MMmax and uncertainty specified in config
self.config['Maximum_Magnitude'] = 8.0
self.config['Maximum_Magnitude_Uncertainty'] = 0.2
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 8.0)
self.assertAlmostEqual(self.model.mmax_sigma, 0.2)
# Case 2: Mmax and uncertainty not specified in config
self.config['Maximum_Magnitude'] = None
self.config['Maximum_Magnitude_Uncertainty'] = None
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 7.9880073)
self.assertAlmostEqual(self.model.mmax_sigma, 0.23)
def test_get_mmax(self):
'''
Tests the function to get Mmax
Values come from WC1994 (tested in openquake.hazardlib) - only
functionality is tested for here!
'''
# Case 1 MMmax and uncertainty specified in config
self.config['Maximum_Magnitude'] = 8.0
self.config['Maximum_Magnitude_Uncertainty'] = 0.2
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 8.0)
self.assertAlmostEqual(self.model.mmax_sigma, 0.2)
# Case 2: Mmax and uncertainty not specified in config
self.config['Maximum_Magnitude'] = None
self.config['Maximum_Magnitude_Uncertainty'] = None
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 7.9880073)
self.assertAlmostEqual(self.model.mmax_sigma, 0.23)
def setUp(self):
self.model = AndersonLucoArbitrary()
self.config = {
'Model_Type': 'First',
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]
}
self.msr = WC1994()
def setUp(self):
self.model = AndersonLucoArbitrary()
self.config = {'Model_Type': 'First',
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]}
self.msr = WC1994()
def test_get_mfd(self):
'''
Tests the function to get magnitude frequency distribution
'''
self.msr = WC1994()
# Test 1: For a fault with 20 mm/yr slip, and an area of 30000 km ** 2
self.msr = WC1994()
# Testing all three calculators!
for iloc, model_type in enumerate(['First', 'Second', 'Third']):
self.model = AndersonLucoArbitrary()
self.config = {
'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]
}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
test_output = self.model.get_mfd(20., 30000.)
print AL83_INC_DATA[:, iloc], test_output[2]
np.testing.assert_array_almost_equal(AL83_INC_DATA[:, iloc],
test_output[2])
# Test case when b-value greater than d-value (raises warning!)
self.model = AndersonLucoArbitrary()
self.config = {
'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [2.0, 0.1]
}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
self.model.get_mfd(20., 30000.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
def test_get_mfd(self):
'''
Tests the function to get magnitude frequency distribution
'''
self.msr = WC1994()
# Test 1: For a fault with 20 mm/yr slip, and an area of 30000 km ** 2
self.msr = WC1994()
# Testing all three calculators!
for iloc, model_type in enumerate(['First', 'Second', 'Third']):
self.model = AndersonLucoArbitrary()
self.config = {'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
test_output = self.model.get_mfd(20., 30000.)
print AL83_INC_DATA[:, iloc], test_output[2]
np.testing.assert_array_almost_equal(AL83_INC_DATA[:, iloc],
test_output[2])
# Test case when b-value greater than d-value (raises warning!)
self.model = AndersonLucoArbitrary()
self.config = {'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [2.0, 0.1]}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
self.model.get_mfd(20., 30000.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
class TestAndersonLucoArbitrary(unittest.TestCase):
'''
Tests the Anderson & Luco Arbitrary models
:class hmtk.faults.mfd.anderson_luco_arbitrary.AndersonLucoArbitrary
'''
def setUp(self):
self.model = AndersonLucoArbitrary()
self.config = {'Model_Type': 'First',
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]}
self.msr = WC1994()
def test_case_setup(self):
'''
Tests the basic setup
'''
expected_dict = {'b_value': 1.0,
'b_value_sigma': 0.1,
'bin_width': 0.1,
'mfd_model': 'Anderson & Luco (Arbitrary) First',
'mfd_type': 'First',
'mfd_weight': 1.0,
'mmax': None,
'mmax_sigma': None,
'mmin': 5.0,
'occurrence_rate': None}
self.model.setUp(self.config)
self.assertDictEqual(expected_dict, self.model.__dict__)
def test_get_mmax(self):
'''
Tests the function to get Mmax
Values come from WC1994 (tested in openquake.hazardlib) - only
functionality is tested for here!
'''
# Case 1 MMmax and uncertainty specified in config
self.config['Maximum_Magnitude'] = 8.0
self.config['Maximum_Magnitude_Uncertainty'] = 0.2
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 8.0)
self.assertAlmostEqual(self.model.mmax_sigma, 0.2)
# Case 2: Mmax and uncertainty not specified in config
self.config['Maximum_Magnitude'] = None
self.config['Maximum_Magnitude_Uncertainty'] = None
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 7.9880073)
self.assertAlmostEqual(self.model.mmax_sigma, 0.23)
def test_get_mfd(self):
'''
Tests the function to get magnitude frequency distribution
'''
self.msr = WC1994()
# Test 1: For a fault with 20 mm/yr slip, and an area of 30000 km ** 2
self.msr = WC1994()
# Testing all three calculators!
for iloc, model_type in enumerate(['First', 'Second', 'Third']):
self.model = AndersonLucoArbitrary()
self.config = {'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
test_output = self.model.get_mfd(20., 30000.)
print AL83_INC_DATA[:, iloc], test_output[2]
np.testing.assert_array_almost_equal(AL83_INC_DATA[:, iloc],
test_output[2])
# Test case when b-value greater than d-value (raises warning!)
self.model = AndersonLucoArbitrary()
self.config = {'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [2.0, 0.1]}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
self.model.get_mfd(20., 30000.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
class TestAndersonLucoArbitrary(unittest.TestCase):
'''
Tests the Anderson & Luco Arbitrary models
:class hmtk.faults.mfd.anderson_luco_arbitrary.AndersonLucoArbitrary
'''
def setUp(self):
self.model = AndersonLucoArbitrary()
self.config = {
'Model_Type': 'First',
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]
}
self.msr = WC1994()
def test_case_setup(self):
'''
Tests the basic setup
'''
expected_dict = {
'b_value': 1.0,
'b_value_sigma': 0.1,
'bin_width': 0.1,
'mfd_model': 'Anderson & Luco (Arbitrary) First',
'mfd_type': 'First',
'mfd_weight': 1.0,
'mmax': None,
'mmax_sigma': None,
'mmin': 5.0,
'occurrence_rate': None
}
self.model.setUp(self.config)
self.assertDictEqual(expected_dict, self.model.__dict__)
def test_get_mmax(self):
'''
Tests the function to get Mmax
Values come from WC1994 (tested in openquake.hazardlib) - only
functionality is tested for here!
'''
# Case 1 MMmax and uncertainty specified in config
self.config['Maximum_Magnitude'] = 8.0
self.config['Maximum_Magnitude_Uncertainty'] = 0.2
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 8.0)
self.assertAlmostEqual(self.model.mmax_sigma, 0.2)
# Case 2: Mmax and uncertainty not specified in config
self.config['Maximum_Magnitude'] = None
self.config['Maximum_Magnitude_Uncertainty'] = None
self.model = AndersonLucoArbitrary()
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 8500.)
self.assertAlmostEqual(self.model.mmax, 7.9880073)
self.assertAlmostEqual(self.model.mmax_sigma, 0.23)
def test_get_mfd(self):
'''
Tests the function to get magnitude frequency distribution
'''
self.msr = WC1994()
# Test 1: For a fault with 20 mm/yr slip, and an area of 30000 km ** 2
self.msr = WC1994()
# Testing all three calculators!
for iloc, model_type in enumerate(['First', 'Second', 'Third']):
self.model = AndersonLucoArbitrary()
self.config = {
'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [1.0, 0.1]
}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
test_output = self.model.get_mfd(20., 30000.)
print AL83_INC_DATA[:, iloc], test_output[2]
np.testing.assert_array_almost_equal(AL83_INC_DATA[:, iloc],
test_output[2])
# Test case when b-value greater than d-value (raises warning!)
self.model = AndersonLucoArbitrary()
self.config = {
'Model_Type': model_type,
'MFD_spacing': 0.1,
'Model_Weight': 1.0,
'Minimum_Magnitude': 5.0,
'Maximum_Magnitude': None,
'b_value': [2.0, 0.1]
}
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 30000.)
self.model.get_mfd(20., 30000.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
