def test_get_adjustment_factor(self):
'''
Tests the function that should return an input adjustment factor if
the magnitude is from a "complete" event - and a zero otherwise
'''
# Good case - when event is in the first completeness period
comp_table = np.array([[1990., 4.0], [1960., 4.5], [1900., 5.5]])
self.catalogue.data['magnitude'] = np.array([4.5, 5.7])
comp_table = utils.get_even_magnitude_completeness(
comp_table, self.catalogue)[0]
tfact = 0.5
self.assertAlmostEqual(
tfact,
_get_adjustment(4.2, 1995., comp_table[0, 1], comp_table[:, 0],
tfact))
# Good case - when event is in a previous completeness period
self.assertAlmostEqual(
tfact,
_get_adjustment(4.7, 1985., comp_table[0, 1], comp_table[:, 0],
tfact))
# Bad case - below minimum completeness in file
self.assertFalse(
_get_adjustment(3.8, 1990., comp_table[0, 1], comp_table[:, 0],
tfact))
# Bad case - below an earlier completeness threshold
self.assertFalse(
_get_adjustment(4.8, 1950., comp_table[0, 1], comp_table[:, 0],
tfact))
# Good case when only one completeness period is needed
comp_table = np.array([[1960., 4.5]])
self.assertAlmostEqual(
1.0,
_get_adjustment(5.0, 1990., comp_table[0, 1], comp_table[:, 0],
tfact))
# Bad case when only one completeness period is needed
self.assertFalse(
_get_adjustment(4.0, 1990., comp_table[0, 1], comp_table[:, 0],
tfact))
def test_get_adjustment_factor(self):
'''
Tests the function that should return an input adjustment factor if
the magnitude is from a "complete" event - and a zero otherwise
'''
# Good case - when event is in the first completeness period
comp_table = np.array([[1990., 4.0],
[1960., 4.5],
[1900., 5.5]])
self.catalogue.data['magnitude'] = np.array([4.5, 5.7])
comp_table = utils.get_even_magnitude_completeness(comp_table,
self.catalogue)[0]
tfact = 0.5
self.assertAlmostEqual(tfact,
_get_adjustment(4.2, 1995., comp_table[0, 1], comp_table[:, 0],
tfact))
# Good case - when event is in a previous completeness period
self.assertAlmostEqual(tfact,
_get_adjustment(4.7, 1985., comp_table[0, 1], comp_table[:, 0],
tfact))
# Bad case - below minimum completeness in file
self.assertFalse(_get_adjustment(3.8, 1990., comp_table[0, 1],
comp_table[:, 0], tfact))
# Bad case - below an earlier completeness threshold
self.assertFalse(_get_adjustment(4.8, 1950., comp_table[0, 1],
comp_table[:, 0], tfact))
# Good case when only one completeness period is needed
comp_table = np.array([[1960., 4.5]])
self.assertAlmostEqual(1.0,
_get_adjustment(5.0, 1990., comp_table[0, 1], comp_table[:, 0],
tfact))
# Bad case when only one completeness period is needed
self.assertFalse(_get_adjustment(4.0, 1990., comp_table[0, 1],
comp_table[:, 0], tfact))