def decluster_GK74(catalogue):
from hmtk.seismicity.declusterer.dec_gardner_knopoff import GardnerKnopoffType1
from hmtk.seismicity.declusterer.distance_time_windows import GardnerKnopoffWindow
decluster_config = {
'time_distance_window': GardnerKnopoffWindow(),
'fs_time_prop': 1.0
}
#####################################################
# decluster here
#####################################################
print 'Running GK declustering...'
decluster_method = GardnerKnopoffType1()
#---------------------------------------------
# declustering
cluster_index_gk, cluster_flags_gk = decluster_method.decluster(
catalogue, decluster_config)
#---------------------------------------------
# adding to the catalog
# The cluster flag (main shock or after/foreshock) and cluster index to the catalogue keys
catalogue.data['cluster_index_gk'] = cluster_index_gk
catalogue.data['cluster_flags_gk'] = cluster_flags_gk
#####################################################
# purge remove non-poissonian events
#####################################################
# create a copy from the catalogue object to preserve it
catalogue_gk = deepcopy(catalogue)
catalogue_gk.purge_catalogue(
cluster_flags_gk == 0) # cluster_flags == 0: mainshocks
print 'Gardner-Knopoff\tbefore: ', catalogue.get_number_events(
), " after: ", catalogue_gk.get_number_events()
#####################################################
# write declustered catalogue
#####################################################
# setup the writer
declustered_catalog_file = hmtk_csv.split('.')[0] + '_declustered_GK74.csv'
# if it exists, delete previous file
try:
remove(declustered_catalog_file)
except:
print declustered_catalog_file, 'does not exist'
# set-up writer
writer = CsvCatalogueWriter(declustered_catalog_file)
# write
writer.write_file(catalogue_gk)
#writer.write_file(catalogue_af)
print 'Declustered catalogue: ok\n'
def test_dec_gardner_knopoff(self):
"""
Testing the Gardner and Knopoff algorithm
"""
config = {
'time_distance_window': GardnerKnopoffWindow(),
'fs_time_prop': 1.0
}
# Instantiate the declusterer and process the sample catalogue
dec = GardnerKnopoffType1()
vcl, flagvector = dec.decluster(self.cat, config)
print 'vcl:', vcl
print 'flagvector:', flagvector, self.cat.data['flag']
self.assertTrue(np.allclose(flagvector, self.cat.data['flag']))
# Set-up the file writer
output_file_name = 'data_input/hmtk_sa3.csv'
writer = CsvCatalogueWriter(output_file_name)
# Write the catalogue to file
writer.write_file(catalogue)
#exit()
print 'File %s written' % output_file_name
f = open(input_catalogue_file + ".pkl", 'wb')
pickle.dump(catalogue, f)
f.close()
# Set up the declustering algorithm
# Step 1 - set-up the tool
gardner_knopoff = GardnerKnopoffType1()
declust_config = {
'time_distance_window': GardnerKnopoffWindow(),
'fs_time_prop': 1.0
}
print declust_config
print 'Running declustering ...'
vcl, flag_vector = gardner_knopoff.decluster(catalogue, declust_config)
print 'done!'
print '%s clusters found' % np.max(vcl)
print '%s Non-poissionian events identified' % np.sum(flag_vector != 0)
# In[ ]:
def decluster_catalogue(catalogue, config):
###
### Catalogue cache or read/cache
###
# Set up the declustering algorithm
# Step 1 - set-up the tool
if config['decluster_method'] == 'afteran':
decluster_method = Afteran()
elif config['decluster_method'] == 'gardner_knopoff':
decluster_method = GardnerKnopoffType1()
else:
print "invalid decluster_method configuration: use [afteran|gardner_knopoff]"
return None
print 'Running declustering ...'
cluster_vector, flag_vector = decluster_method.decluster(catalogue, config)
print 'done!'
print '%s clusters found' % np.max(cluster_vector)
print '%s Non-poissionian events identified' % np.sum(flag_vector != 0)
if config['plot']:
###
### Map Config
###
map_dpi = 90
add_geology = True
add_sourcemodel = True
savefig=False
#map_title = 'Brazilian Seismic Zones'
map_title = 'Clusters'
#map_title = 'ISC-GEM Catalogue'
#map_title = 'South-American Lithology'
# Configure the limits of the map and the coastline resolution
map_config = {'min_lon': -80.0, 'max_lon': -30.0, 'min_lat': -37.0, 'max_lat': 14.0, 'resolution':'l'}
#map_config = {'min_lon': -72.0, 'max_lon': -68.0, 'min_lat': -22.0, 'max_lat': -18.0, 'resolution':'l'}
#map_config = {'min_lon': -95.0, 'max_lon': -25.0, 'min_lat': -65.0, 'max_lat': 25.0, 'resolution':'l'}
basemap = HMTKBaseMap(map_config, map_title, dpi=map_dpi)
#basemap.add_catalogue(catalogue, linewidth=0.2, alpha=0.1, overlay=True)
idx = cluster_vector != 0
x = catalogue.data['longitude'][idx]
y = catalogue.data['latitude'][idx]
c = cluster_vector[idx]
basemap.add_colour_scaled_points(x, y, c,
overlay=True,
shape='s', alpha=0.5, size=100,
linewidth=0.5, facecolor='none',
cmap=plt.cm.get_cmap('Paired'),
)
plt.show()
if config['figname']:
basemap.savemap(config['figname'])
print 'Original catalogue had %s events' % catalogue.get_number_events()
catalogue.select_catalogue_events(flag_vector == 0)
print 'Purged catalogue now contains %s events' % catalogue.get_number_events()
if config['filename']:
writer = CsvCatalogueWriter(config['filename'])
writer.write_file(catalogue)
return catalogue
# parse HMTK catalogue
inputsheef = path.join(hmtkfile)
parser = CsvCatalogueParser(inputsheef)
catalogue = parser.read_file()
decluster_config = {
'time_distance_window': GardnerKnopoffWindow(),
'fs_time_prop': 1.0
}
#####################################################
# decluster here
#####################################################
print 'Running GK declustering...'
decluster_method = GardnerKnopoffType1()
#---------------------------------------------
# declustering
cluster_index_gk, cluster_flags_gk = decluster_method.decluster(
catalogue, decluster_config)
#---------------------------------------------
# adding to the catalog
# The cluster flag (main shock or after/foreshock) and cluster index to the catalogue keys
catalogue.data['cluster_index_gk'] = cluster_index_gk
catalogue.data['cluster_flags_gk'] = cluster_flags_gk
#####################################################
# purge remove non-poissonian events
#####################################################