def setUp(self):
filename = os.path.join(BASE_DATA_PATH, 'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'algorithm': None, 'number_bootstraps': None}
self.model = CumulativeMoment()
def test_complete_stepp_analysis_basic(self):
'''
Basic test of the entire completeness analysis using a synthetic
test catalogue with in-built completeness periods
'''
parser0 = CsvCatalogueParser(INPUT_FILE_1)
self.catalogue = parser0.read_file()
self.config = {'magnitude_bin': 0.5,
'time_bin': 5.0,
'increment_lock': True,
'filename': None}
expected_completeness_table = np.array([[1990., 4.25],
[1962., 4.75],
[1959., 5.25],
[1906., 5.75],
[1906., 6.25],
[1904., 6.75],
[1904., 7.25]])
self.assertTrue(np.allclose(
expected_completeness_table,
self.process.completeness(self.catalogue, self.config)
))
def setUp(self):
"""
Read the sample catalogue
"""
flnme = 'gardner_knopoff_test_catalogue.csv'
filename = os.path.join(self.BASE_DATA_PATH, flnme)
parser = CsvCatalogueParser(filename)
self.cat = parser.read_file()
def setUp(self):
parser0 = CsvCatalogueParser(TEST_CAT_1)
self.catalogue = parser0.read_file()
self.config = {'maximum_iterations': 1000,
'number_earthquakes': 100,
'number_samples': 51,
'tolerance': 0.05}
self.model = KijkoNonParametricGaussian()
def setUp(self):
"""
Read the sample catalogue
"""
flnme = 'gardner_knopoff_test_catalogue.csv'
filename = os.path.join(self.BASE_DATA_PATH, flnme)
parser = CsvCatalogueParser(filename)
self.cat = parser.read_file()
def setUp(self):
filename = os.path.join(BASE_DATA_PATH,'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'algorithm': None,
'number_bootstraps': None}
self.model = CumulativeMoment()
def setUp(self):
filename = os.path.join(BASE_DATA_PATH,'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'maximum_iterations': 1000,
'number_earthquakes': 100,
'number_samples': 51,
'tolerance': 0.05}
self.model = KijkoNonParametricGaussian()
def setUp(self):
filename = os.path.join(BASE_DATA_PATH,'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'maximum_iterations': 1000,
'number_earthquakes': 100,
'number_samples': 51,
'tolerance': 0.05}
self.model = KijkoNonParametricGaussian()
def setUp(self):
"""
Read the sample catalogue
"""
flnme = 'afteran_test_catalogue.csv'
filename = os.path.join(self.BASE_DATA_PATH, flnme)
parser = CsvCatalogueParser(filename)
self.cat = parser.read_file()
self.dec = Afteran()
def setUp(self):
test_data = np.genfromtxt(TEST_CAT_1, delimiter=',', skip_header=1)
parser0 = CsvCatalogueParser(TEST_CAT_1)
self.catalogue = parser0.read_file()
self.config = {'algorithm': None,
'number_bootstraps': None}
self.model = CumulativeMoment()
def setUp(self):
parser0 = CsvCatalogueParser(TEST_CAT_1)
self.catalogue = parser0.read_file()
self.config = {'b-value': 1.0,
'sigma-b': 0.05,
'input_mmin': 5.0,
'input_mmax': None,
'input_mmax_uncertainty': None,
'tolerance': 0.001,
'maximum_iterations': 1000}
self.model = KijkoSellevolBayes()
def setUp(self):
filename = os.path.join(BASE_DATA_PATH,'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'b-value': 1.0,
'sigma-b': 0.05,
'input_mmin': 5.0,
'input_mmax': None,
'input_mmax_uncertainty': None,
'tolerance': 0.001,
'maximum_iterations': 1000}
self.model = KijkoSellevolBayes()
def setUp(self):
'''
Set up test class
'''
parser0 = CsvCatalogueParser(TEST_CAT_1)
self.catalogue = parser0.read_file()
self.config = {'b-value': 1.0,
'input_mmin': 5.0,
'input_mmax': None,
'tolerance': 0.001,
'maximum_iterations': 1000}
self.model = KijkoSellevolFixedb()
def setUp(self):
filename = os.path.join(BASE_DATA_PATH,'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'b-value': 1.0,
'sigma-b': 0.05,
'input_mmin': 5.0,
'input_mmax': None,
'input_mmax_uncertainty': None,
'tolerance': 0.001,
'maximum_iterations': 1000}
self.model = KijkoSellevolBayes()
def setUp(self):
'''
Set up test class
'''
filename = os.path.join(BASE_DATA_PATH,'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'b-value': 1.0,
'input_mmin': 5.0,
'input_mmax': None,
'tolerance': 0.001,
'maximum_iterations': 1000}
self.model = KijkoSellevolFixedb()
def setUp(self):
'''
Set up test class
'''
filename = os.path.join(BASE_DATA_PATH,'completeness_test_cat.csv')
parser0 = CsvCatalogueParser(filename)
self.catalogue = parser0.read_file()
self.config = {'b-value': 1.0,
'input_mmin': 5.0,
'input_mmax': None,
'tolerance': 0.001,
'maximum_iterations': 1000}
self.model = KijkoSellevolFixedb()
def test_complete_stepp_analysis_basic(self):
'''
Basic test of the entire completeness analysis using a synthetic
test catalogue with in-built completeness periods
'''
parser0 = CsvCatalogueParser(INPUT_FILE_1)
self.catalogue = parser0.read_file()
self.config = {
'magnitude_bin': 0.5,
'time_bin': 5.0,
'increment_lock': True,
'filename': None
}
expected_completeness_table = np.array([[1990., 4.0], [1962., 4.5],
[1959., 5.0], [1906., 5.5],
[1906., 6.0], [1904., 6.5],
[1904., 7.0]])
np.testing.assert_array_almost_equal(
expected_completeness_table,
self.process.completeness(self.catalogue, self.config))
# Set up paralell
proc = pypar.size() # Number of processors as specified by mpirun
myid = pypar.rank() # Id of of this process (myid in [0, proc-1])
node = pypar.get_processor_name(
) # Host name on which current process is running
print 'I am proc %d of %d on node %s' % (myid, proc, node)
t0 = pypar.time()
config_params = params_from_shp(
domains_shp, trt_ignore=['Interface', 'Active', 'Oceanic', 'Intraslab'])
for config in config_params:
print config
#sys.exit()
# Read and clean the catalogue
parser = CsvCatalogueParser(ifile)
catalogue = parser.read_file(start_year=1900, end_year=2016)
# How many events in the catalogue?
print "The catalogue contains %g events" % catalogue.get_number_events()
neq = len(catalogue.data['magnitude'])
print "The catalogue contains %g events" % neq
# What is the geographical extent of the catalogue?
bbox = catalogue.get_bounding_box()
print "Catalogue ranges from %.4f E to %.4f E Longitude and %.4f N to %.4f N Latitude\n" % bbox
catalogue.sort_catalogue_chronologically()
index = np.logical_and(catalogue.data["magnitude"] > 1.5,
catalogue.data["depth"] >= 0.0)
#index = np.logical_and(catalogue.data["magnitude"] > 1.5, catalogue.data["magnitude"] < 4.0)
catalogue.purge_catalogue(index)
catalogue.get_number_events()
# Copying the catalogue and saving it under a new name "catalogue_clean"
np.arange(map_config['min_lon'], map_config['max_lon'], 5))
plt.colorbar(label='log10(Smoothed rate per cell)')
plt.legend()
figname = smoother_filename[:-4] + '_smoothed_rates_map.png'
plt.savefig(figname)
# Set up paralell
proc = pypar.size() # Number of processors as specified by mpirun
myid = pypar.rank() # Id of of this process (myid in [0, proc-1])
node = pypar.get_processor_name(
) # Host name on which current process is running
print 'I am proc %d of %d on node %s' % (myid, proc, node)
t0 = pypar.time()
parser = CsvCatalogueParser(catalogue_filename) # From .csv to hmtk
# Read and process the catalogue content in a variable called "catalogue"
catalogue = parser.read_file(start_year=1965, end_year=2016)
# How many events in the catalogue?
print "The catalogue contains %g events" % catalogue.get_number_events()
# What is the geographical extent of the catalogue?
bbox = catalogue.get_bounding_box()
print "Catalogue ranges from %.4f E to %.4f E Longitude and %.4f N to %.4f N Latitude\n" % bbox
catalogue.sort_catalogue_chronologically()
catalogue.data['magnitude']
index = catalogue.data['magnitude'] > 1.5
from openquake.hazardlib.geo.point import Point from openquake.hazardlib.mfd import TruncatedGRMFD from openquake.hazardlib.geo.nodalplane import NodalPlane from openquake.hazardlib.pmf import PMF #from nrml.models import HypocentralDepth #nrml.models import HypocentralDepth print "Everything Imported OK!" # In[25]: bvalue = float(sys.argv[1]) print 'b value', bvalue #Importing catalogue catalogue_filename = "../../catalogue/data/AUSTCAT_V0.12_hmtk_declustered.csv" #catalogue_filename = "../../catalogue/data/AUSTCAT_V0.12_hmtk_mx_orig.csv" parser = CsvCatalogueParser(catalogue_filename) # From .csv to hmtk # Read and process the catalogue content in a variable called "catalogue" catalogue = parser.read_file(start_year=1965, end_year=2010) # How many events in the catalogue? print "The catalogue contains %g events" % catalogue.get_number_events() # What is the geographical extent of the catalogue? bbox = catalogue.get_bounding_box() print "Catalogue ranges from %.4f E to %.4f E Longitude and %.4f N to %.4f N Latitude\n" % bbox # In[26]: catalogue.sort_catalogue_chronologically() catalogue.data['magnitude']
from openquake.hazardlib.mfd import TruncatedGRMFD from openquake.hazardlib.geo.nodalplane import NodalPlane from openquake.hazardlib.pmf import PMF #from nrml.models import HypocentralDepth #nrml.models import HypocentralDepth print "Everything Imported OK!" bvalue = float(sys.argv[1]) catalogue_filename = sys.argv[2] print 'b value', bvalue #Importing catalogue #catalogue_filename = "../../catalogue/data/AUSTCAT_V0.12_hmtk_declustered.csv" #catalogue_filename = "../../catalogue/data/AUSTCAT_V0.12_hmtk_mx_orig.csv" parser = CsvCatalogueParser(catalogue_filename) # Read and process the catalogue content in a variable called "catalogue" catalogue = parser.read_file(start_year=1788, end_year=2010) # How many events in the catalogue? print "The catalogue contains %g events" % catalogue.get_number_events() # What is the geographical extent of the catalogue? bbox = catalogue.get_bounding_box() print "Catalogue ranges from %.4f E to %.4f E Longitude and %.4f N to %.4f N Latitude\n" % bbox # In[26]: catalogue.sort_catalogue_chronologically()
from hmtk.seismicity.smoothing.kernels.isotropic_gaussian import IsotropicGaussian
#from hmtk.parsers.catalogue.csv_catalogue_parser import CsvCatalogueWriter
import helmstetter_werner_2012 as h_w
# To build source model
from hmtk.sources.source_model import mtkSourceModel
from hmtk.sources.point_source import mtkPointSource
from openquake.hazardlib.geo.point import Point
from openquake.hazardlib.mfd import TruncatedGRMFD
from openquake.hazardlib.geo.nodalplane import NodalPlane
from openquake.hazardlib.pmf import PMF
print "Everything Imported OK!"
ifile = "../../catalogue/data/AUSTCAT_V0.12_hmtk_declustered.csv"
parser = CsvCatalogueParser(ifile)
catalogue = parser.read_file(start_year=1837, end_year=2010)
# How many events in the catalogue?
print "The catalogue contains %g events" % catalogue.get_number_events()
neq = len(catalogue.data['magnitude'])
print "The catalogue contains %g events" % neq
# What is the geographical extent of the catalogue?
bbox = catalogue.get_bounding_box()
print "Catalogue ranges from %.4f E to %.4f E Longitude and %.4f N to %.4f N Latitude\n" % bbox
catalogue.sort_catalogue_chronologically()
index = np.logical_and(catalogue.data["magnitude"] > 1.5,
catalogue.data["depth"] >= 0.0)
catalogue.purge_catalogue(index)
catalogue.get_number_events()