def get_unclassified(tot_lab, pck_fname, out_cata, path_out):
"""
Create a text file (.csv formatted) with the unclassified earthquakes
:param tot_lab:
:param pck_fname:
Name of the pickle file with the catalogue
:param out_cata:
Name of the .csv output catalogue
:param path_out:
Path to output folder
"""
# ID of the unclassified earthquakes
tr_undef = abs(tot_lab - 1)
# Load the catalogue of unclassified earthquakes
catalogue = pickle.load(open(pck_fname, 'rb'))
# Select the unclassified
selector = CatalogueSelector(catalogue, create_copy=False)
catalogue = selector.select_catalogue(tr_undef)
print('')
print('# earthquakes: {:d}'.format(len(catalogue.data['longitude'])))
# Sub-catalogue
csv_filename = out_cata + "_TR_unclassified.csv"
csv_filename = os.path.join(path_out, csv_filename)
# Write the purged catalogue
csvcat = CsvCatalogueWriter(csv_filename)
csvcat.write_file(catalogue)
print("Catalogue successfully written to %s" % csv_filename)
def test_catalogue_writer_no_purging(self):
'''
Tests the writer without any purging
'''
# Write to file
writer = CsvCatalogueWriter(self.output_filename)
writer.write_file(self.catalogue)
parser = CsvCatalogueParser(self.output_filename)
cat2 = parser.read_file()
self.check_catalogues_are_equal(self.catalogue, cat2)
def test_catalogue_writer_no_purging(self):
'''
Tests the writer without any purging
'''
# Write to file
writer = CsvCatalogueWriter(self.output_filename)
writer.write_file(self.catalogue)
parser = CsvCatalogueParser(self.output_filename)
cat2 = parser.read_file()
self.check_catalogues_are_equal(self.catalogue, cat2)
def test_catalogue_writer_only_mag_table_purging(self):
'''
Tests the writer only purging according to the magnitude table
'''
# Write to file
writer = CsvCatalogueWriter(self.output_filename)
writer.write_file(self.catalogue, magnitude_table=self.magnitude_table)
parser = CsvCatalogueParser(self.output_filename)
cat2 = parser.read_file()
expected_catalogue = Catalogue()
expected_catalogue.data['eventID'] = ['1', '3', '5']
expected_catalogue.data['magnitude'] = np.array([5.6, 4.8, 5.0])
expected_catalogue.data['year'] = np.array([1960, 1970, 1990])
expected_catalogue.data['ErrorStrike'] = np.array(
[np.nan, np.nan, np.nan])
self.check_catalogues_are_equal(expected_catalogue, cat2)
def test_catalogue_writer_only_flag_purging(self):
'''
Tests the writer only purging according to the flag
'''
# Write to file
writer = CsvCatalogueWriter(self.output_filename)
writer.write_file(self.catalogue, flag_vector=self.flag)
parser = CsvCatalogueParser(self.output_filename)
cat2 = parser.read_file()
expected_catalogue = Catalogue()
expected_catalogue.data['eventID'] = ['1', '2', '3', '4']
expected_catalogue.data['magnitude'] = np.array([5.6, 5.4, 4.8, 4.3])
expected_catalogue.data['year'] = np.array([1960, 1965, 1970, 1980])
expected_catalogue.data['ErrorStrike'] = np.array(
[np.nan, np.nan, np.nan, np.nan])
self.check_catalogues_are_equal(expected_catalogue, cat2)
def test_catalogue_writer_only_mag_table_purging(self):
'''
Tests the writer only purging according to the magnitude table
'''
# Write to file
writer = CsvCatalogueWriter(self.output_filename)
writer.write_file(self.catalogue, magnitude_table=self.magnitude_table)
parser = CsvCatalogueParser(self.output_filename)
cat2 = parser.read_file()
expected_catalogue = Catalogue()
expected_catalogue.data['eventID'] = ['1', '3', '5']
expected_catalogue.data['magnitude'] = np.array([5.6, 4.8, 5.0])
expected_catalogue.data['year'] = np.array([1960, 1970, 1990])
expected_catalogue.data['ErrorStrike'] = np.array([np.nan, np.nan,
np.nan])
self.check_catalogues_are_equal(expected_catalogue, cat2)
def test_catalogue_writer_only_flag_purging(self):
'''
Tests the writer only purging according to the flag
'''
# Write to file
writer = CsvCatalogueWriter(self.output_filename)
writer.write_file(self.catalogue, flag_vector=self.flag)
parser = CsvCatalogueParser(self.output_filename)
cat2 = parser.read_file()
expected_catalogue = Catalogue()
expected_catalogue.data['eventID'] = ['1', '2', '3', '4']
expected_catalogue.data['magnitude'] = np.array([5.6, 5.4, 4.8, 4.3])
expected_catalogue.data['year'] = np.array([1960, 1965, 1970, 1980])
expected_catalogue.data['ErrorStrike'] = np.array([np.nan, np.nan,
np.nan, np.nan])
self.check_catalogues_are_equal(expected_catalogue, cat2)
def create_sub_catalogue(alen, aaa, pck_fname, treg_fname, out_cata, out_path):
"""
Creates .csv files with the subcatalogues
:param alen:
Number of earthquakes in the original catalogue
:param aaa:
List of the labels used to define the various tectonic regions
:param pck_fname:
Name of the file with the pickled catalogue
:param treg_fname:
Name of the .hdf5 file with the classification of the catalogue
:param out_cata:
Name of the .hdf5 file with the classification of the catalogue
:param out_path:
Name of the .hdf5 file with the classification of the catalogue
:returns:
A :class:`numpy.ndarray` vector of length N where N is the number of
earthquakes in the original catalogue.
"""
# The output vector
tot_lab = np.zeros(alen)
print(' ')
fmt = '# earthquakes in the catalogue: {:d}'
print(fmt.format(len(tot_lab)))
# Loop over the tectonic regions
for label in (aaa):
# Output file name
csv_filename = out_cata + "_TR_{:s}.csv".format(label)
csv_filename = os.path.join(out_path, csv_filename)
# Read the TR classification
f = h5py.File(treg_fname, 'r')
tr = f[label][:]
f.close()
if sum(tr) > 0:
tmp_lab = tr * 1
tot_lab = tot_lab + tmp_lab
catalogue = pickle.load(open(pck_fname, 'rb'))
for lab in ['month', 'day', 'hour', 'minute', 'second']:
idx = np.isnan(catalogue.data[lab])
if lab == 'day' or lab == 'month':
catalogue.data[lab][idx] = 1
elif lab == 'second':
catalogue.data[lab][idx] = 0.0
else:
catalogue.data[lab][idx] = 0
selector = CatalogueSelector(catalogue, create_copy=False)
catalogue = selector.select_catalogue(tr)
catalogue.data['hour'] = catalogue.data['hour'].astype(int)
catalogue.data['minute'] = catalogue.data['minute'].astype(int)
print(' ')
fmt = '# earthquakes in this TR : {:d}'
print(fmt.format(len(catalogue.data['longitude'])))
# Sub-catalogue
print(csv_filename)
csvcat = CsvCatalogueWriter(csv_filename)
# Write the purged catalogue
csvcat.write_file(catalogue)
print("Catalogue successfully written to %s" % csv_filename)
return tot_lab