import matplotlib.pyplot as plt
import numpy as num
uncertainty=False
output_path='/Users/francesco/Desktop/Single_Station_Location/MOLQUAKE_V_0.3/ridge_2staz'
data_path='/Users/francesco/Desktop/Single_Station_Location/MOLQUAKE_V_0.3/ridge_2staz'
datafiles=['ridgecrest_refcat_15.dat','ridgecrest_picks_2sta_15.dat']
catalogue_file='refcat_15.dat'
out_catalogue='outcat_ridgecrest_two_stations.txt'
Vp=6000 #velocities in m/s !!!!!
Vps=1.73
Vs=Vp/Vps
nref=20
datafile='ridgecrest_Vp_'+str(Vp)
dataobj=molquake.molquake_dat(data_path,datafiles,one_sta=False)
locobj=molquake.molquake_loc(Vp,Vs)
references=dataobj.references
nref=num.size(references[:,0])
locobj.location_2stations(dataobj.data, references)
catevs=dataobj.read_catalogue(data_path,catalogue_file)
locobj.catalogue_creation(dataobj.evids, dataobj.origin, nref, out_catalogue, output_path)
if uncertainty:
print('uncertainty estimation')
multiloc=locobj.uncertainty_estimation_2sta(dataobj.data, references, 25, [5500,6500], 1.73)
locboot=num.array([0.,0.,0])
for i in range(25):
locboot=num.vstack((locboot,multiloc[i,:,:]))
num.save('locboot_real.npy',locboot)
num.save('locreal.npy',dataobj.references)
num.save('catevs.npy',catevs)
import molquake
import matplotlib.pyplot as plt
import numpy as num
output_path = '/Users/francesco/Desktop/Single_Station_Location/MOLQUAKE_V_0.3/real_data'
data_path = '/Users/francesco/Desktop/Single_Station_Location/MOLQUAKE_V_0.3/real_data'
datafiles = ['napa_refcat_4.dat', 'napa_picks.dat']
out_catalogue = 'outcat.txt'
datafile = 'vp6800'
Vp = 6800 #velocities in m/s !!!!!
Vps = 1.73
Vs = Vp / Vps
nref = 4
dataobj = molquake.molquake_dat(data_path, datafiles)
locobj = molquake.molquake_loc(Vp, Vs)
references = dataobj.references
nref = num.size(references[:, 0])
locobj.location(dataobj.data, references)
locobj.catalogue_creation(dataobj.evids, dataobj.origin, nref, out_catalogue,
output_path)
#multiloc=locobj.uncertainty_estimation(dataobj.data, references, 25, [6500,7500], 1.73)
#print(num.shape(multiloc))
#locboot=num.array([0.,0.,0])
#for i in range(20):
# locboot=num.vstack((locboot,multiloc[i,:,:]))
#num.save('locboot_real.npy',locboot)
#num.save('locreal.npy',dataobj.references)
nref, mref = num.shape(references)
err_svd = num.sort(