def select_catalogue(self, valid_id):
'''
Method to post-process the catalogue based on the selection options
:param numpy.ndarray valid_id:
Boolean vector indicating whether each event is selected (True)
or not (False)
:returns:
Catalogue of selected events as instance of
hmtk.seismicity.catalogue.Catalogue class
'''
if not np.any(valid_id):
# No events selected - create clean instance of class
output = Catalogue()
output.processes = self.catalogue.processes
output
elif np.all(valid_id):
if self.copycat:
output = deepcopy(self.catalogue)
else:
output = self.catalogue
else:
if self.copycat:
output = deepcopy(self.catalogue)
else:
output = self.catalogue
output.purge_catalogue(valid_id)
return output
def select_catalogue(self, valid_id):
'''
Method to post-process the catalogue based on the selection options
:param numpy.ndarray valid_id:
Boolean vector indicating whether each event is selected (True)
or not (False)
:returns:
Catalogue of selected events as instance of
hmtk.seismicity.catalogue.Catalogue class
'''
if not np.any(valid_id):
# No events selected - create clean instance of class
output = Catalogue()
output.processes = self.catalogue.processes
elif np.all(valid_id):
if self.copycat:
output = deepcopy(self.catalogue)
else:
output = self.catalogue
else:
if self.copycat:
output = deepcopy(self.catalogue)
else:
output = self.catalogue
output.purge_catalogue(valid_id)
return output
def test_purge_catalogue(self):
# Tests the function to purge the catalogue of invalid events
cat1 = Catalogue()
cat1.data['eventID'] = np.array([100, 101, 102], dtype=int)
cat1.data['magnitude'] = np.array([4., 5., 6.], dtype=float)
cat1.data['Agency'] = ['XXX', 'YYY', 'ZZZ']
flag_vector = np.array([False, True, False])
cat1.purge_catalogue(flag_vector)
np.testing.assert_array_almost_equal(cat1.data['magnitude'],
np.array([5.]))
np.testing.assert_array_equal(cat1.data['eventID'], np.array([101]))
self.assertListEqual(cat1.data['Agency'], ['YYY'])
def test_purge_catalogue(self):
# Tests the function to purge the catalogue of invalid events
cat1 = Catalogue()
cat1.data['eventID'] = np.array([100, 101, 102], dtype=int)
cat1.data['magnitude'] = np.array([4., 5., 6.], dtype=float)
cat1.data['Agency'] = ['XXX', 'YYY', 'ZZZ']
flag_vector = np.array([False, True, False])
cat1.purge_catalogue(flag_vector)
np.testing.assert_array_almost_equal(cat1.data['magnitude'],
np.array([5.]))
np.testing.assert_array_equal(cat1.data['eventID'],
np.array([101]))
self.assertListEqual(cat1.data['Agency'], ['YYY'])
