def test_weichert_factor(self): ''' Tests the Weichert adjustment factor to compensate for time varying completeness ''' # Test 1: Comparison against the USGS Implementation beta = 0.8 * np.log(10.) end_year = 2006. comp_table = np.array([[1933., 4.0], [1900., 5.0], [1850., 6.0], [1850., 7.0]]) self.assertAlmostEqual( 0.0124319686, utils.get_weichert_factor(beta, comp_table[:, 1], comp_table[:, 0], end_year)[0]) # Test 2: Single value of completeness comp_table = np.array([[1960., 4.0]]) self.assertAlmostEqual( 1. / (2006. - 1960. + 1.), utils.get_weichert_factor(beta, comp_table[:, 1], comp_table[:, 0], end_year)[0])
def test_weichert_factor(self): ''' Tests the Weichert adjustment factor to compensate for time varying completeness ''' # Test 1: Comparison against the USGS Implementation beta = 0.8 * np.log(10.) end_year = 2006. comp_table = np.array([[1933., 4.0], [1900., 5.0], [1850., 6.0], [1850., 7.0]]) self.assertAlmostEqual(0.0124319686, utils.get_weichert_factor(beta, comp_table[:, 1], comp_table[:, 0], end_year)[0]) # Test 2: Single value of completeness comp_table = np.array([[1960., 4.0]]) self.assertAlmostEqual(1. / (2006. - 1960. + 1.), utils.get_weichert_factor(beta, comp_table[:, 1], comp_table[:, 0], end_year)[0])
def run_analysis(self, catalogue, config, completeness_table=None, smoothing_kernel=None): ''' Runs an analysis of smoothed seismicity in the manner originally implemented by Frankel (1995) :param catalogue: Instance of the openquake.hmtk.seismicity.catalogue.Catalogue class catalogue.data dictionary containing the following - 'year' - numpy.ndarray vector of years 'longitude' - numpy.ndarray vector of longitudes 'latitude' - numpy.ndarray vector of latitudes 'depth' - numpy.ndarray vector of depths :param dict config: Configuration settings of the algorithm: * 'Length_Limit' - Maximum number of bandwidths for use in smoothing (Float) * 'BandWidth' - Bandwidth (km) of the Smoothing Kernel (Float) * 'increment' - Output incremental (True) or cumulative a-value (False) :param np.ndarray completeness_table: Completeness of the catalogue assuming evenly spaced magnitudes from most recent bin to oldest bin [year, magnitude] :param smoothing_kernel: Smoothing kernel as instance of :class: `openquake.hmtk.seismicity.smoothing.kernels.base.BaseSmoothingKernel` :returns: Full smoothed seismicity data as np.ndarray, of the form [Longitude, Latitude, Depth, Observed, Smoothed] ''' self.catalogue = catalogue if smoothing_kernel: self.kernel = smoothing_kernel else: self.kernel = IsotropicGaussian() # If no grid limits are specified then take from catalogue if isinstance(self.grid_limits, list): self.grid_limits = Grid.make_from_list(self.grid_limits) assert self.grid_limits['xmax'] >= self.grid_limits['xmin'] assert self.grid_limits['xspc'] > 0.0 assert self.grid_limits['ymax'] >= self.grid_limits['ymin'] assert self.grid_limits['yspc'] > 0.0 elif isinstance(self.grid_limits, float): self.grid_limits = Grid.make_from_catalogue( self.catalogue, self.grid_limits, config['Length_Limit'] * config['BandWidth']) completeness_table, mag_inc = utils.get_even_magnitude_completeness( completeness_table, self.catalogue) end_year = self.catalogue.end_year # Get Weichert factor t_f, _ = utils.get_weichert_factor(self.beta, completeness_table[:, 1], completeness_table[:, 0], end_year) # Get the grid self.create_3D_grid(self.catalogue, completeness_table, t_f, mag_inc) if config['increment']: # Get Hermann adjustment factors fval, fival = utils.hermann_adjustment_factors( self.bval, completeness_table[0, 1], config['increment']) self.data[:, -1] = fval * fival * self.data[:, -1] # Apply smoothing smoothed_data, sum_data, sum_smooth = self.kernel.smooth_data( self.data, config, self.use_3d) print('Smoothing Total Rate Comparison - ' 'Observed: %.6g, Smoothed: %.6g' % (sum_data, sum_smooth)) self.data = np.column_stack([self.data, smoothed_data]) return self.data