coeff_novert = genfromtxt(path + 'coefficients/' + 'novert.coeff')
coeff_all = genfromtxt(path + 'coefficients/' + 'all.coeff')
#Get coefficient uncertainties
sigma_novert = 1.96 * genfromtxt(path + 'coefficients/novert.boot',
usecols=1)
sigma_novert[1] = -sigma_novert[1]
sigma_novert[2] = -sigma_novert[2]
sigma_all = 1.96 * genfromtxt(path + 'coefficients/novert.boot',
usecols=1)
sigma_all[1] = -sigma_all[1]
sigma_all[2] = -sigma_all[2]
if len(dnov) >= minsta:
#print "using "+str(len(dnov))+' stations'
Mw_nov[kt] = scaling.PGD((dnov + delta) * 100,
R,
coefficients=coeff_novert,
weight=False,
norm=norm)
Mw_all[kt] = scaling.PGD((dall + delta) * 100,
R,
coefficients=coeff_all,
weight=False,
norm=norm)
#Now get upper and lower magnitude bound
Mw_nov_plus[kt] = scaling.PGD(dnov * 100,
R,
coefficients=coeff_novert +
sigma_novert,
weight=True,
norm=norm)
Mw_all_plus[kt] = scaling.PGD(dall * 100,
dnov=r_[dnov,pgd[i,1]]
dall=r_[dall,pgd[i,2]]
R=r_[R,pgd[i,5]]
#print R
#print dall
#Solve regression
coeff_novert=genfromtxt(path+'coefficients/'+'novert.coeff')
coeff_all=genfromtxt(path+'coefficients/'+'all.coeff')
#Get coefficient uncertainties
sigma_novert=1.96*genfromtxt(path+'coefficients/novert.boot',usecols=1)
sigma_novert[1]=-sigma_novert[1] ; sigma_novert[2]=-sigma_novert[2]
sigma_all=1.96*genfromtxt(path+'coefficients/novert.boot',usecols=1)
sigma_all[1]=-sigma_all[1] ; sigma_all[2]=-sigma_all[2]
if len(dnov)>=minsta:
#print "using "+str(len(dnov))+' stations'
Mw_nov[kt]=scaling.PGD(dnov*100,R,coefficients=coeff_novert,weight=weight,norm=norm)
Mw_all[kt]=scaling.PGD(dall*100,R,coefficients=coeff_all,weight=weight,norm=norm)
#Now get upper and lower magnitude bound
Mw_nov_plus[kt]=scaling.PGD(dnov*100,R,coefficients=coeff_novert+sigma_novert,weight=weight,norm=norm)
Mw_all_plus[kt]=scaling.PGD(dall*100,R,coefficients=coeff_all+sigma_all,weight=weight,norm=norm)
Mw_nov_minus[kt]=scaling.PGD(dnov*100,R,coefficients=coeff_novert-sigma_novert,weight=weight,norm=norm)
Mw_all_minus[kt]=scaling.PGD(dall*100,R,coefficients=coeff_all-sigma_all,weight=weight,norm=norm)
else:
Mw_nov[kt]=nan
Mw_all[kt]=nan
#Write to file
savetxt(path+'PGD/magnitudes/'+event+'.mag',c_[tpgd,Mw_nov,Mw_all,Mw_nov_minus,Mw_nov_plus,Mw_all_minus,Mw_all_plus],fmt='%5.1f\t%5.4f\t%5.4f\t%5.4f\t%5.4f\t%5.4f\t%5.4f',header='t,Mw_nov,Mw_all,Mw_nov_minus,Mw_nov_plus,Mw_all_minus,Mw_all_plus')
if plot:
coeff_all = genfromtxt(path + 'coefficients/' + 'all.coeff')
#Get coefficient uncertainties
sigma_novert = 1.96 * genfromtxt(path + 'coefficients/novert.boot',
usecols=1)
sigma_novert[1] = -sigma_novert[1]
sigma_novert[2] = -sigma_novert[2]
sigma_all = 1.96 * genfromtxt(path + 'coefficients/novert.boot',
usecols=1)
sigma_all[1] = -sigma_all[1]
sigma_all[2] = -sigma_all[2]
if len(dnov) >= minsta:
#print "using "+str(len(dnov))+' stations'
#Mw_nov[kt],res_nov[kt]=scaling.PGD(dnov*100,R,coefficients=coeff_novert,weight=False,norm=2,residual=True)
Mw_all, res_all = scaling.PGD(dall * 100,
R,
coefficients=coeff_all,
weight=False,
norm=2,
residual=True)
#Now get upper and lower magnitude bound
#Mw_nov_plus[kt]=scaling.PGD(dnov*100,R,coefficients=coeff_novert+sigma_novert,weight=True,norm=2)
#Mw_all_plus[kt]=scaling.PGD(dall*100,R,coefficients=coeff_all+sigma_all,weight=True,norm=2)
#Mw_nov_minus[kt]=scaling.PGD(dnov*100,R,coefficients=coeff_novert-sigma_novert,weight=True,norm=2)
#Mw_all_minus[kt]=scaling.PGD(dall*100,R,coefficients=coeff_all-sigma_all,weight=True,norm=2)
else:
Mw_nov[kt] = nan
Mw_all[kt] = nan
Mw_nov = Mw_all
Mw_nov_plus = Mw_all
Mw_nov_minus = Mw_all
Mw_all_plus = Mw_all