]
field_names = copy.copy(field_names_for_indexing)
fprdict = defaultdict(list)
tprdict = defaultdict(list)
pvalues = defaultdict(list)
aucdict = defaultdict(list)
testingfields = defaultdict(list)
# Loop over each of the csv files in the testing data set
for (ff, file_name) in enumerate(file_names_testing):
print('Reading in ' + file_name)
# Read in .csv file to dictionary
file = '../Data/AllCSV/' + str(file_name)
data = modelfunctions.read_file_to_dict(file)
# Binarize aftershocks
grid_aftershock_count = np.double(data['aftershocksyn'])
aftershock_count = preprocessing.binarize(
grid_aftershock_count.reshape(1, -1))[0]
#skip if no aftershocks
if len(np.unique(aftershock_count)) < 2:
continue
# find best-performing sign convention for Coulomb failure stress change for this slip distribution
num = modelfunctions.FindWhichCFS(data, aftershock_count)
if num == 1: field_names[0] = 'stresses_full_cfs_1'
if num == 2: field_names[0] = 'stresses_full_cfs_2'
if num == 3: field_names[0] = 'stresses_full_cfs_3'
'file_names_training')
file_names_testing = modelfunctions.readHDF('../Data/Testing_FileNames.h5',
'file_names_testing')
training = defaultdict(list)
testing = defaultdict(list)
field_names = [
'stresses_full_xx', 'stresses_full_yy', 'stresses_full_xy',
'stresses_full_xz', 'stresses_full_yz', 'stresses_full_zz'
]
for i, file_name in enumerate(file_names_testing):
print(i, file_name)
print('testing eq')
data = modelfunctions.read_file_to_dict(pathtofiles + str(file_name))
grid_aftershock_count = np.double(data['aftershocksyn'])
if len(np.unique(grid_aftershock_count)) < 2:
continue
tmp = grid_aftershock_count.tolist()
testing['aftershocksyn'].extend(tmp)
for j in range(0, len(field_names)):
testing[field_names[j]].extend(np.double(data[field_names[j]]))
for i, file_name in enumerate(file_names_training):
print(i, file_name)
print('training')
data = modelfunctions.read_file_to_dict(pathtofiles + str(file_name))
grid_aftershock_count = np.double(data['aftershocksyn'])
if len(np.unique(grid_aftershock_count)) < 2:
continue