def test_get_mfd(self):
'''
Tests the main function to get the magnitude frequency distribution
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
self.model.setUp(self.config)
# Same fault case as for test_cumulative_value - now comparing incremenetal
# rates
self.model.get_mmax(self.config, self.msr, 0., 7200.)
output1 = self.model.get_mfd(1.0, 7200.)
np.testing.assert_array_almost_equal(YC_EXP_DATA[:, 2], output1[2])
# Test case for when b > 1.5 - should produce array of NaN
self.model = YoungsCoppersmithExponential()
self.config['b_value'] = [1.6, 0.1]
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
_, _, _ = self.model.get_mfd(1.0, 7200.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
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 = YoungsCoppersmithExponential()
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 = YoungsCoppersmithExponential()
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 main function to get the magnitude frequency distribution
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
self.model.setUp(self.config)
# Same fault case as for test_cumulative_value - now comparing incremenetal
# rates
self.model.get_mmax(self.config, self.msr, 0., 7200.)
output1 = self.model.get_mfd(1.0, 7200.)
np.testing.assert_array_almost_equal(YC_EXP_DATA[:, 2], output1[2])
# Test case for when b > 1.5 - should produce array of NaN
self.model = YoungsCoppersmithExponential()
self.config['b_value'] = [1.6, 0.1]
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
_, _, _ = self.model.get_mfd(1.0, 7200.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
def test_cumulative_value(self):
'''
Tests the calculation of the cumulative rate M > Mref
Data and tests taken from Bungum (2007). Current parameters should
reproduce Model 4 line in Figure 1 of Bungum (2007)
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
# Test case 1 - Fault of 120 km length and 60 km width (7200 km ** 2 area)
# b-value 1, slip = 1 mm/yr
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
moment_rate = (30. * 1E9) * (7200. * 1E6) * (1.0 / 1000.)
momax = _scale_moment(self.model.mmax, in_nm=True)
beta = log(10.)
expected_result = YC_EXP_DATA[:, 1]
mags = np.arange(5.0, 8.1, 0.1)
for iloc, mag in enumerate(mags):
self.assertAlmostEqual(
expected_result[iloc],
self.model.cumulative_value(mag, moment_rate, beta, momax))
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 = YoungsCoppersmithExponential()
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 = YoungsCoppersmithExponential()
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_return_oq_mfd(self):
"""
Tests the function to return the mfd as an instance of the openquake
EvenlyDiscretizedMFD class
"""
self.model = YoungsCoppersmithExponential()
self.config = {
'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]
}
self.model.setUp(self.config)
# Same fault case as for test_cumulative_value - now comparing incremenetal
# rates
self.model.get_mmax(self.config, self.msr, 0., 7200.)
_ = self.model.get_mfd(1.0, 7200.)
oq_mfd = self.model.to_evenly_discretized_mfd()
self.assertTrue(isinstance(oq_mfd, EvenlyDiscretizedMFD))
self.assertAlmostEqual(oq_mfd.min_mag, 5.05)
self.assertAlmostEqual(oq_mfd.bin_width, 0.1)
np.testing.assert_array_almost_equal(YC_EXP_DATA[:, 2],
np.array(oq_mfd.occurrence_rates))
def setUp(self):
'''
'''
self.model = YoungsCoppersmithExponential()
self.msr = WC1994()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
def test_cumulative_value(self):
'''
Tests the calculation of the cumulative rate M > Mref
Data and tests taken from Bungum (2007). Current parameters should
reproduce Model 4 line in Figure 1 of Bungum (2007)
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
# Test case 1 - Fault of 120 km length and 60 km width (7200 km ** 2 area)
# b-value 1, slip = 1 mm/yr
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
moment_rate = (30. * 1E9) * (7200. * 1E6) * (1.0 / 1000.)
momax = _scale_moment(self.model.mmax, in_nm=True)
beta = log(10.)
expected_result = YC_EXP_DATA[:, 1]
mags = np.arange(5.0, 8.1, 0.1)
for iloc, mag in enumerate(mags):
self.assertAlmostEqual(
expected_result[iloc],
self.model.cumulative_value(mag, moment_rate, beta, momax))
def setUp(self):
'''
'''
self.model = YoungsCoppersmithExponential()
self.msr = WC1994()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
def test_return_oq_mfd(self):
"""
Tests the function to return the mfd as an instance of the openquake
EvenlyDiscretizedMFD class
"""
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
self.model.setUp(self.config)
# Same fault case as for test_cumulative_value - now comparing incremenetal
# rates
self.model.get_mmax(self.config, self.msr, 0., 7200.)
_ = self.model.get_mfd(1.0, 7200.)
oq_mfd = self.model.to_evenly_discretized_mfd()
self.assertTrue(isinstance(oq_mfd, EvenlyDiscretizedMFD))
self.assertAlmostEqual(oq_mfd.min_mag, 5.05)
self.assertAlmostEqual(oq_mfd.bin_width, 0.1)
np.testing.assert_array_almost_equal(YC_EXP_DATA[:, 2],
np.array(oq_mfd.occurrence_rates))
class TestYoungsCoppersmithExponential(unittest.TestCase):
'''
Tests the :class: YoungsCoppersmithExponential
'''
def setUp(self):
'''
'''
self.model = YoungsCoppersmithExponential()
self.msr = WC1994()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
def test_class_setup(self):
'''
Tests the basic setup of the class
'''
expected_dict = {'b_value': 1.0,
'b_value_sigma': 0.1,
'bin_width': 0.1,
'mfd_model': 'Youngs & Coppersmith Exponential',
'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 = YoungsCoppersmithExponential()
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 = YoungsCoppersmithExponential()
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_cumulative_value(self):
'''
Tests the calculation of the cumulative rate M > Mref
Data and tests taken from Bungum (2007). Current parameters should
reproduce Model 4 line in Figure 1 of Bungum (2007)
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
# Test case 1 - Fault of 120 km length and 60 km width (7200 km ** 2 area)
# b-value 1, slip = 1 mm/yr
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
moment_rate = (30. * 1E9) * (7200. * 1E6) * (1.0 / 1000.)
momax = _scale_moment(self.model.mmax, in_nm=True)
beta = log(10.)
expected_result = YC_EXP_DATA[:, 1]
mags = np.arange(5.0, 8.1, 0.1)
for iloc, mag in enumerate(mags):
self.assertAlmostEqual(
expected_result[iloc],
self.model.cumulative_value(mag, moment_rate, beta, momax))
def test_get_mfd(self):
'''
Tests the main function to get the magnitude frequency distribution
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
self.model.setUp(self.config)
# Same fault case as for test_cumulative_value - now comparing incremenetal
# rates
self.model.get_mmax(self.config, self.msr, 0., 7200.)
output1 = self.model.get_mfd(1.0, 7200.)
np.testing.assert_array_almost_equal(YC_EXP_DATA[:, 2], output1[2])
# Test case for when b > 1.5 - should produce array of NaN
self.model = YoungsCoppersmithExponential()
self.config['b_value'] = [1.6, 0.1]
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
_, _, _ = self.model.get_mfd(1.0, 7200.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
class TestYoungsCoppersmithExponential(unittest.TestCase):
'''
Tests the :class: YoungsCoppersmithExponential
'''
def setUp(self):
'''
'''
self.model = YoungsCoppersmithExponential()
self.msr = WC1994()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
def test_class_setup(self):
'''
Tests the basic setup of the class
'''
expected_dict = {'b_value': 1.0,
'b_value_sigma': 0.1,
'bin_width': 0.1,
'mfd_model': 'Youngs & Coppersmith Exponential',
'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 = YoungsCoppersmithExponential()
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 = YoungsCoppersmithExponential()
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_cumulative_value(self):
'''
Tests the calculation of the cumulative rate M > Mref
Data and tests taken from Bungum (2007). Current parameters should
reproduce Model 4 line in Figure 1 of Bungum (2007)
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
# Test case 1 - Fault of 120 km length and 60 km width (7200 km ** 2 area)
# b-value 1, slip = 1 mm/yr
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
moment_rate = (30. * 1E9) * (7200. * 1E6) * (1.0 / 1000.)
momax = _scale_moment(self.model.mmax, in_nm=True)
beta = log(10.)
expected_result = YC_EXP_DATA[:, 1]
mags = np.arange(5.0, 8.1, 0.1)
for iloc, mag in enumerate(mags):
self.assertAlmostEqual(
expected_result[iloc],
self.model.cumulative_value(mag, moment_rate, beta, momax))
def test_get_mfd(self):
'''
Tests the main function to get the magnitude frequency distribution
'''
self.model = YoungsCoppersmithExponential()
self.config = {'MFD_spacing': 0.1,
'Maximum_Magnitude': 8.0,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Weight': 1.0,
'b_value': [1.0, 0.1]}
self.model.setUp(self.config)
# Same fault case as for test_cumulative_value - now comparing incremenetal
# rates
self.model.get_mmax(self.config, self.msr, 0., 7200.)
output1 = self.model.get_mfd(1.0, 7200.)
np.testing.assert_array_almost_equal(YC_EXP_DATA[:, 2], output1[2])
# Test case for when b > 1.5 - should produce array of NaN
self.model = YoungsCoppersmithExponential()
self.config['b_value'] = [1.6, 0.1]
self.model.setUp(self.config)
self.model.get_mmax(self.config, self.msr, 0., 7200.)
_, _, _ = self.model.get_mfd(1.0, 7200.)
self.assertTrue(np.all(np.isnan(self.model.occurrence_rate)))
