def loadSingleGmMap(rupt_name):
#Load station rot dict
station_rot_dict = pdx.loadRotStationDict('rot_station_dict.csv')
#Get grid size
x_grid_max = np.max(np.asarray(list(station_rot_dict.values()))[:, 0])
y_grid_max = np.max(np.asarray(list(station_rot_dict.values()))[:, 1])
#Name of IM to save
IM_name = ['PGA', 'PGV', 'AI', 'pSA_0.5', 'pSA_1.0', 'pSA_3.0']
#Ensure IM IDs are well sorted
lbl_IM = pdx.loadGM_CS(rupt_name)[0]
IM_pos = []
for i in range(len(lbl_IM)):
for j in range(len(IM_name)):
if IM_name[j] == lbl_IM[i]:
IM_pos.append(i)
break
#Initialize array
GM = np.ones((x_grid_max, y_grid_max, len(IM_name)))
for i in range(len(IM_name)):
if IM_name[i] == 'PGV':
GM[:, :, i] = GM[:, :, i] * (0.25)
elif IM_name[i] == 'AI':
GM[:, :, i] = GM[:, :, i] * (-2.)
elif IM_name[i] == 'pSA_3.0':
GM[:, :, i] = GM[:, :, i] * (-6.)
else:
GM[:, :, i] = GM[:, :, i] * (-5.)
#Load data
GM_i = pdx.loadGM_CS(rupt_name)
unfoundStation = []
for j in range(1, len(GM_i)):
for k in range(len(IM_pos)):
try:
GM[station_rot_dict[GM_i[j][0]][0],
station_rot_dict[GM_i[j][0]][1],
k] = np.log(GM_i[j][IM_pos[k]])
except:
unfoundStation.append(GM_i[j][0])
GM = np.transpose(GM, (1, 0, 2))
'''
print(unfoundStation)
print(len(unfoundStation))
'''
return GM
def loadGM_1D(str_rupt, realID, IM_ID):
#Load GM
GM = pdx.loadGM_CS(str_rupt)
#Populate matrix
GM_prep = np.ones((len(realID))) * (-8.0)
for i in range(len(GM)):
GM_prep[int(realID[GM[i][0]])] = np.log(GM[i][IM_ID])
return GM_prep
#Initialize dictionary of used stations
station_virt_dict = {}
#Folder and file names
dir_path = './data/'
if not os.path.exists(dir_path):
os.mkdir(dir_path)
#Initialize list of unfound faults
unfoundFault = []
for i in range(len(rupt_lbl)):
#Load current GM
str_GM = './raw_data/' + rupt_lbl[i] + '.csv'
try:
GM = pdx.loadGM_CS(str_GM)
#Remove all non-geometric mean lines
for j in range(len(GM) - 1, 0, -1):
if not GM[j][1] == 'geom':
del GM[j]
#Add station location
GM_save = [[GM[0][0], 'easting', 'northing']]
for j in range(len(GM[0]) - 2):
GM_save[0].append(GM[0][j + 2])
for j in range(1, len(GM)):
GM_save.append(
[GM[j][0], station_CS[GM[j][0]][0], station_CS[GM[j][0]][1]])
for k in range(len(GM[j]) - 2):
#Initialize array
GM = np.ones((n_file, x_grid_max, y_grid_max, len(IM_name)))
for i in range(len(IM_name)):
if IM_name[i] == 'PGV':
GM[:, :, :, i] = GM[:, :, :, i] * (0.25)
elif IM_name[i] == 'AI':
GM[:, :, :, i] = GM[:, :, :, i] * (-2.)
elif IM_name[i] == 'pSA_3.0':
GM[:, :, :, i] = GM[:, :, :, i] * (-6.)
else:
GM[:, :, :, i] = GM[:, :, :, i] * (-5.)
GM_name = []
GM_lbl = []
#Get IM position given names
lbl_IM = pdx.loadGM_CS(file_name[i])[0]
IM_pos = []
for i in range(len(lbl_IM)):
for j in range(len(IM_name)):
if IM_name[j] == lbl_IM[i]:
IM_pos.append(i)
break
#Treat map one after another (memory efficiency)
unfoundStation = []
for i in range(n_file):
GM_i = pdx.loadGM_CS(file_name[i])
for j in range(1, len(GM_i)):
for k in range(len(IM_pos)):
try:
GM[i, station_rot_dict2[GM_i[j][0]][0],
