def test_decimal_time2(self):
'''Tests the function utils.decimal_time'''
self.year = np.array([1990])
np.testing.assert_allclose(
utils.decimal_time(self.year, np.array([]), np.array([]),
np.array([]), np.array([]), np.array([])),
np.array([1990.]))
def get_decimal_time(self):
'''
Returns the time of the catalogue as a decimal
'''
return decimal_time(self.data['year'], self.data['month'],
self.data['day'], self.data['hour'],
self.data['minute'], self.data['second'])
def completeness(self, catalogue, config):
'''Gets the completeness table
:param catalogue:
Earthquake catalogue as instance of
:class: openquake.hmtk.seismicity.catalogue.Catalogue
:param dict config:
Configuration parameters of the algorithm, containing the
following information:
'magnitude_bin' Size of magnitude bin (non-negative float)
'time_bin' Size (in dec. years) of the time window (non-negative float) 'increment_lock' Boolean to indicate whether to ensure
completeness magnitudes always decrease with more recent bins
:returns:
2-column table indicating year of completeness and corresponding
magnitude numpy.ndarray
'''
# If mag_bin is an array then bins are input, otherwise a single
# parameter is input
dyear = decimal_time(
catalogue.data['year'],
catalogue.data['month'],
catalogue.data['day'],
catalogue.data['hour'],
catalogue.data['minute'],
catalogue.data['second'])
mag = catalogue.data['magnitude']
# Get magnitude bins
self.magnitude_bin = self._get_magnitudes_from_spacing(
catalogue.data['magnitude'],
config['magnitude_bin'])
# Get time bins
_s_year, time_bin = self._get_time_limits_from_config(config, dyear)
# Count magnitudes
self.sigma, _counter, n_mags, n_times, self.time_values = (
self._count_magnitudes(mag, dyear, time_bin))
# Get completeness magnitudes
comp_time, _gradient_2, self.model_line = (
self.get_completeness_points(self.time_values, self.sigma, n_mags,
n_times))
# If the increment lock is selected then ensure completeness time
# does not decrease
if config['increment_lock']:
for iloc in range(0, len(comp_time)):
cond = (
(iloc > 0 and (comp_time[iloc] < comp_time[iloc - 1])) or
np.isnan(comp_time[iloc]))
if cond:
comp_time[iloc] = comp_time[iloc - 1]
self.completeness_table = np.column_stack([
np.floor(self.end_year - comp_time),
self.magnitude_bin[:-1]])
return self.completeness_table
def completeness(self, catalogue, config):
'''
Gets the completeness table.
:param catalogue:
Earthquake catalogue as instance of
:class:`openquake.hmtk.seismicity.catalogue.Catalogue`
:param dict config:
Configuration parameters of the algorithm, containing the
following information:
'magnitude_bin' Size of magnitude bin (non-negative float)
'time_bin' Size (in dec. years) of the time window
(non-negative float)
'increment_lock' Boolean to indicate whether to ensure
completeness magnitudes always decrease with more recent bins
:returns:
2-column table indicating year of completeness and corresponding
magnitude numpy.ndarray
'''
# If mag_bin is an array then bins are input, otherwise a single
# parameter is input
dyear = decimal_time(catalogue.data['year'], catalogue.data['month'],
catalogue.data['day'], catalogue.data['hour'],
catalogue.data['minute'],
catalogue.data['second'])
mag = catalogue.data['magnitude']
# Get magnitude bins
self.magnitude_bin = self._get_magnitudes_from_spacing(
catalogue.data['magnitude'], config['magnitude_bin'])
# Get time bins
_s_year, time_bin = self._get_time_limits_from_config(config, dyear)
# Count magnitudes
self.sigma, _counter, n_mags, n_times, self.time_values = (
self._count_magnitudes(mag, dyear, time_bin))
# Get completeness magnitudes
comp_time, _gradient_2, self.model_line = (
self.get_completeness_points(self.time_values, self.sigma, n_mags,
n_times))
# If the increment lock is selected then ensure completeness time
# does not decrease
if config['increment_lock']:
for iloc in range(0, len(comp_time)):
cond = ((iloc > 0 and (comp_time[iloc] < comp_time[iloc - 1]))
or np.isnan(comp_time[iloc]))
if cond:
comp_time[iloc] = comp_time[iloc - 1]
self.completeness_table = np.column_stack(
[np.floor(self.end_year - comp_time), self.magnitude_bin[:-1]])
return self.completeness_table
def get_decimal_time(self):
'''
Returns the time of the catalogue as a decimal
'''
return decimal_time(self.data['year'],
self.data['month'],
self.data['day'],
self.data['hour'],
self.data['minute'],
self.data['second'])
def test_decimal_time(self):
'''Tests the function utils.decimal_time'''
self.year = np.array([1990, 1995, 2000])
self.month = np.array([1, 6, 12])
self.day = np.array([1, 30, 31])
self.hour = np.array([0, 12, 23])
self.minute = np.array([0, 30, 59])
self.second = np.array([0.0, 30.0, 59.0])
np.testing.assert_allclose(
utils.decimal_time(self.year, self.month, self.day, self.hour,
self.minute, self.second),
np.array([1990., 1995.49457858, 2000.99999997]))
def test_decimal_time1(self):
'''Tests the function utils.decimal_time'''
self.year = np.array([1990])
self.month = np.array([1])
self.day = np.array([1])
self.hour = np.array([0])
self.minute = np.array([0])
self.second = np.array([0.0, 30.0, 59.0])
np.testing.assert_allclose(
utils.decimal_time(self.year, self.month, self.day, self.hour,
self.minute, self.second),
np.array([1990., 1990.000001, 1990.000002]))
def _get_decimal_from_datetime(time):
'''
As the decimal time function requires inputs in the form of numpy
arrays need to convert each value in the datetime object to a single
numpy array
'''
# Get decimal seconds from seconds + microseconds
temp_seconds = np.float(time.second) + (np.float(time.microsecond) / 1.0E6)
return decimal_time(np.array([time.year], dtype=int),
np.array([time.month], dtype=int),
np.array([time.day], dtype=int),
np.array([time.hour], dtype=int),
np.array([time.minute], dtype=int),
np.array([temp_seconds], dtype=int))
def _get_decimal_from_datetime(time):
'''
As the decimal time function requires inputs in the form of numpy
arrays need to convert each value in the datetime object to a single
numpy array
'''
# Get decimal seconds from seconds + microseconds
temp_seconds = np.float(time.second) + (np.float(time.microsecond) / 1.0E6)
return decimal_time(np.array([time.year], dtype=int),
np.array([time.month], dtype=int),
np.array([time.day], dtype=int),
np.array([time.hour], dtype=int),
np.array([time.minute], dtype=int),
np.array([temp_seconds], dtype=int))
def test_get_decimal_time(self):
# Tests the decimal time function. The function itself is tested in
# tests.seismicity.utils so only minimal testing is undertaken here to
# ensure coverage
time_dict = {
'year': np.array([1990, 2000]),
'month': np.array([3, 9]),
'day': np.ones(2, dtype=int),
'hour': np.ones(2, dtype=int),
'minute': np.ones(2, dtype=int),
'second': np.ones(2, dtype=float)
}
expected_dec_time = decimal_time(time_dict['year'], time_dict['month'],
time_dict['day'], time_dict['hour'],
time_dict['minute'],
time_dict['second'])
cat = Catalogue()
for key in ['year', 'month', 'day', 'hour', 'minute', 'second']:
cat.data[key] = np.copy(time_dict[key])
np.testing.assert_array_almost_equal(expected_dec_time,
cat.get_decimal_time())
def test_get_decimal_time(self):
# Tests the decimal time function. The function itself is tested in
# tests.seismicity.utils so only minimal testing is undertaken here to
# ensure coverage
time_dict = {'year': np.array([1990, 2000]),
'month': np.array([3, 9]),
'day': np.ones(2, dtype=int),
'hour': np.ones(2, dtype=int),
'minute': np.ones(2, dtype=int),
'second': np.ones(2, dtype=float)}
expected_dec_time = decimal_time(time_dict['year'],
time_dict['month'],
time_dict['day'],
time_dict['hour'],
time_dict['minute'],
time_dict['second'])
cat = Catalogue()
for key in ['year', 'month', 'day', 'hour', 'minute', 'second']:
cat.data[key] = np.copy(time_dict[key])
np.testing.assert_array_almost_equal(expected_dec_time,
cat.get_decimal_time())
def test_decimal_time2(self):
'''Tests the function utils.decimal_time'''
self.year = np.array([1990])
self.assertTrue(
np.allclose(utils.decimal_time(self.year, [], [], [], [], []),
np.array([1990.])))
def test_decimal_time2(self):
'''Tests the function utils.decimal_time'''
self.year = np.array([1990])
self.assertTrue(np.allclose(
utils.decimal_time(self.year, [], [], [], [], []),
np.array([1990.])))