def test_get_3d_grid(self):
'''
Tests the module to count the events in a 3D grid
'''
comp_table = np.array([[1960., 4.0]])
self.catalogue = Catalogue()
self.catalogue.data['longitude'] = np.hstack([
np.arange(35., 41.0, 1.0),
np.arange(35., 41.0, 1.0)])
self.catalogue.data['latitude'] = np.hstack([
np.arange(40., 46.0, 1.0),
np.arange(40., 46.0, 1.0)])
self.catalogue.data['depth'] = np.hstack([10.0 * np.ones(6),
30.0 * np.ones(6)])
self.catalogue.data['magnitude'] = 4.5 * np.ones(12)
self.catalogue.data['year'] = 1990. * np.ones(12)
# Case 1 - one depth layer
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40.0, 45., 0.5, 0., 40., 40.])
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
[gx, gy] = np.meshgrid(np.arange(35.25, 40., 0.5),
np.arange(40.25, 45., 0.5))
ngp = np.shape(gx)[0] * np.shape(gy)[1]
gx = np.reshape(gx, [ngp, 1])
gy = np.reshape(gy, [ngp, 1])
gz = 20. * np.ones(ngp)
expected_count = np.zeros(ngp, dtype=float)
expected_count[[9, 28, 46, 64, 82, 90]] = 2.0
expected_result = np.column_stack([gx, np.flipud(gy), gz,
expected_count])
self.model.create_3D_grid(self.catalogue, comp_table)
np.testing.assert_array_almost_equal(expected_result, self.model.data)
# Case 2 - multiple depth layers
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40., 45., 0.5, 0., 40., 20.])
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
expected_result = np.vstack([expected_result, expected_result])
expected_count = np.zeros(200)
expected_count[[9, 28, 46, 64, 82, 90,
109, 128, 146, 164, 182, 190]] = 1.0
expected_result[:, -1] = expected_count
expected_result[:, 2] = np.hstack([10. * np.ones(100),
30. * np.ones(100)])
self.model.create_3D_grid(self.catalogue, comp_table)
np.testing.assert_array_almost_equal(expected_result, self.model.data)
def test_get_2d_grid(self):
'''
Tests the module to count the events across a grid
'''
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40., 45.0, 0.5, 0., 40., 20.])
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
# Case 1 - all events in grid (including borderline cases)
comp_table = np.array([[1960., 4.0]])
lons = np.arange(35.0, 41.0, 1.0)
lats = np.arange(40.0, 46.0, 1.0)
mags = 5.0 * np.ones(6)
years = 2000. * np.ones(6)
expected_result = np.zeros(100, dtype=int)
expected_result[[9, 28, 46, 64, 82, 90]] = 1
np.testing.assert_array_almost_equal(
expected_result,
self.model.create_2D_grid_simple(lons, lats, years, mags,
comp_table))
self.assertEqual(np.sum(expected_result), 6)
# Case 2 - some events outside grid
lons = np.arange(35.0, 42.0, 1.0)
lats = np.arange(40.0, 47.0, 1.0)
mags = 5.0 * np.ones(7)
years = 2000. * np.ones(7)
np.testing.assert_array_almost_equal(
expected_result,
self.model.create_2D_grid_simple(lons, lats, years, mags,
comp_table))
self.assertEqual(np.sum(expected_result), 6)
def test_instantiation(self):
'''
Tests the instantiation of the class
'''
# Test 1: Good Grid Limits
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40., 45.0, 0.5, 0., 40., 20.])
expected_dict = {
'beta': None,
'bval': None,
'catalogue': None,
'data': None,
'grid': None,
'grid_limits': {
'xmax': 40.0,
'xmin': 35.0,
'xspc': 0.5,
'ymax': 45.0,
'ymin': 40.0,
'yspc': 0.5,
'zmax': 40.0,
'zmin': 0.0,
'zspc': 20.0
},
'kernel': None,
'use_3d': False
}
self.model = SmoothedSeismicity(self.grid_limits)
self.assertDictEqual(self.model.__dict__, expected_dict)
# Test 2 - with b-value set
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
expected_dict['bval'] = 1.0
expected_dict['beta'] = np.log(10.)
self.assertDictEqual(self.model.__dict__, expected_dict)
def test_get_2d_grid(self):
'''
Tests the module to count the events across a grid
'''
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40., 45.0, 0.5, 0., 40., 20.])
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
# Case 1 - all events in grid (including borderline cases)
comp_table = np.array([[1960., 4.0]])
lons = np.arange(35.0, 41.0, 1.0)
lats = np.arange(40.0, 46.0, 1.0)
mags = 5.0 * np.ones(6)
years = 2000. * np.ones(6)
expected_result = np.zeros(100, dtype=int)
expected_result[[9, 28, 46, 64, 82, 90]] = 1
np.testing.assert_array_almost_equal(expected_result,
self.model.create_2D_grid_simple(lons, lats, years, mags,
comp_table))
self.assertEqual(np.sum(expected_result), 6)
# Case 2 - some events outside grid
lons = np.arange(35.0, 42.0, 1.0)
lats = np.arange(40.0, 47.0, 1.0)
mags = 5.0 * np.ones(7)
years = 2000. * np.ones(7)
np.testing.assert_array_almost_equal(expected_result,
self.model.create_2D_grid_simple(lons, lats, years, mags,
comp_table))
self.assertEqual(np.sum(expected_result), 6)
def test_instantiation(self):
'''
Tests the instantiation of the class
'''
# Test 1: Good Grid Limits
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40., 45.0, 0.5, 0., 40., 20.])
expected_dict = {'beta': None,
'bval': None,
'catalogue': None,
'data': None,
'grid': None,
'grid_limits': {'xmax': 40.0,
'xmin': 35.0,
'xspc': 0.5,
'ymax': 45.0,
'ymin': 40.0,
'yspc': 0.5,
'zmax': 40.0,
'zmin': 0.0,
'zspc': 20.0},
'kernel': None,
'use_3d': False}
self.model = SmoothedSeismicity(self.grid_limits)
self.assertDictEqual(self.model.__dict__, expected_dict)
# Test 2 - with b-value set
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
expected_dict['bval'] = 1.0
expected_dict['beta'] = np.log(10.)
self.assertDictEqual(self.model.__dict__, expected_dict)
def test_get_3d_grid(self):
'''
Tests the module to count the events in a 3D grid
'''
comp_table = np.array([[1960., 4.0]])
self.catalogue = Catalogue()
self.catalogue.data['longitude'] = np.hstack(
[np.arange(35., 41.0, 1.0),
np.arange(35., 41.0, 1.0)])
self.catalogue.data['latitude'] = np.hstack(
[np.arange(40., 46.0, 1.0),
np.arange(40., 46.0, 1.0)])
self.catalogue.data['depth'] = np.hstack(
[10.0 * np.ones(6), 30.0 * np.ones(6)])
self.catalogue.data['magnitude'] = 4.5 * np.ones(12)
self.catalogue.data['year'] = 1990. * np.ones(12)
# Case 1 - one depth layer
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40.0, 45., 0.5, 0., 40., 40.])
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
[gx, gy] = np.meshgrid(np.arange(35.25, 40., 0.5),
np.arange(40.25, 45., 0.5))
ngp = np.shape(gx)[0] * np.shape(gy)[1]
gx = np.reshape(gx, [ngp, 1])
gy = np.reshape(gy, [ngp, 1])
gz = 20. * np.ones(ngp)
expected_count = np.zeros(ngp, dtype=float)
expected_count[[9, 28, 46, 64, 82, 90]] = 2.0
expected_result = np.column_stack(
[gx, np.flipud(gy), gz, expected_count])
self.model.create_3D_grid(self.catalogue, comp_table)
np.testing.assert_array_almost_equal(expected_result, self.model.data)
# Case 2 - multiple depth layers
self.grid_limits = Grid.make_from_list(
[35.0, 40., 0.5, 40., 45., 0.5, 0., 40., 20.])
self.model = SmoothedSeismicity(self.grid_limits, bvalue=1.0)
expected_result = np.vstack([expected_result, expected_result])
expected_count = np.zeros(200)
expected_count[[9, 28, 46, 64, 82, 90, 109, 128, 146, 164, 182,
190]] = 1.0
expected_result[:, -1] = expected_count
expected_result[:, 2] = np.hstack(
[10. * np.ones(100), 30. * np.ones(100)])
self.model.create_3D_grid(self.catalogue, comp_table)
np.testing.assert_array_almost_equal(expected_result, self.model.data)
def on_click(self):
try:
ll = float(self.fields['Length_Limit'].widget.text())
bw = float(self.fields['BandWidth'].widget.text())
dilate = ll * bw
except ValueError:
dilate = 0
self.grid_dialog.set_grid(
Grid.make_from_catalogue(self.catalogue, 1, dilate))
if self.grid_dialog.exec_():
self.grid = self.grid_dialog.get_grid()
def get_grid(self):
table = self.tableWidget
ret = []
for row in range(table.rowCount()):
data = [table.item(row, 0).data(0),
table.item(row, 1).data(0),
table.item(row, 2).data(0)]
ret.extend([float(d) for d in data])
return Grid.make_from_list(ret)
res, spc = 1, 50
#res, spc = 0.2, 250
# model
#[xmin, xmax, spcx, ymin, ymax, spcy, zmin, spcz]
map_config = {
'min_lon': -95.0,
'max_lon': -25.0,
'min_lat': -65.0,
'max_lat': 25.0,
'resolution': 'l'
}
#_l = [ 118.5, 124, res, 20.0, 26.5, res, 0, 300, 300]
#_l = [ -95., -25, res, -65, 25, res, 0, 800, 800]
_l = [-80, -30, res, -37, 13, res, 0, 30, 30]
grid_limits = Grid.make_from_list(_l)
nx = round((_l[1] - _l[0]) / _l[2], 0)
ny = round((_l[4] - _l[3]) / _l[5], 0)
grid_shape = (nx, ny)
print grid_shape
model = SmoothedSeismicity(grid_limits, bvalue=1.0)
# Time-varying completeness
comp_table = np.array([[1980., 3.5], [1970., 4.5], [1960., 5.0]])
if model_name == 'hmtk_sa3':
comp_table = np.array([[1986, 3.], [1986, 3.5], [1986, 4.], [1960, 4.5],
[1958, 5.], [1958, 5.5], [1927, 6.], [1898, 6.5],
[1885, 7.], [1885, 7.5], [1885, 8.]])
else:
catalogue.sort_catalogue_chronologically()
# print catalogue.get_number_events()
# res, spc = 0.5, 100
res, spc = 1, 50
# res, spc = 0.2, 250
# model
# [xmin, xmax, spcx, ymin, ymax, spcy, zmin, spcz]
map_config = {"min_lon": -95.0, "max_lon": -25.0, "min_lat": -65.0, "max_lat": 25.0, "resolution": "l"}
# _l = [ 118.5, 124, res, 20.0, 26.5, res, 0, 300, 300]
# _l = [ -95., -25, res, -65, 25, res, 0, 800, 800]
_l = [-80, -30, res, -37, 13, res, 0, 30, 30]
grid_limits = Grid.make_from_list(_l)
nx = round((_l[1] - _l[0]) / _l[2], 0)
ny = round((_l[4] - _l[3]) / _l[5], 0)
grid_shape = (nx, ny)
print grid_shape
model = SmoothedSeismicity(grid_limits, bvalue=1.0)
# Time-varying completeness
comp_table = np.array([[1980.0, 3.5], [1970.0, 4.5], [1960.0, 5.0]])
if model_name == "hmtk_sa3":
comp_table = np.array(
[
[1986, 3.0],
