ekxms0 = -( e1[:,:6]-e1[:,4:5] ) # NGA and Ref
ekxms0[:,4:5] = e1[:,4:5] # CS
else:
ekxms0 = e1
tmp1.append( ekxms0 )
tmp_ekxms.append( tmp1 )
tmp_ekxms = np.array( tmp_ekxms ) # [Nhypo, NMw, Nsta, Nmodels]
# standard deviation and average over hypocenters
tmp_sd_xs = np.sqrt( np.average( tmp_ekxms**2, axis=1,weights=pdf_m) )
tmp_sd0 = np.average( tmp_sd_xs, axis=0, weights = pdf_x )
tmp_vd0 = np.average( tmp_sd_xs**2, axis=0, weights = pdf_x )
tmp_sd = []; tmp_vd = []
for imodel in xrange( tmp_sd0.shape[1] ):
NewValue = interp( lons0, lats0, tmp_sd0[:,imodel], SiteLon1D, SiteLat1D, eps=eps, method=method )
tmp_sd.append( NewValue )
NewValue = interp( lons0, lats0, tmp_vd0[:,imodel], SiteLon1D, SiteLat1D, eps=eps, method=method )
tmp_vd.append( NewValue )
sigma_M_ks.append( tmp_vd ) # variance unit
pafile = mapout + '/CyberShake.NGAs.%s.Source%s.Seks'%(T,sid)
fid = open( pafile, 'w' )
Nrow = len(SiteLon1D)
for irow in xrange( Nrow ):
fid.write( '%s %s %s %s %s %s %s %s\n'%(SiteLon1D[irow],SiteLat1D[irow], \
tmp_sd[0][irow],
tmp_sd[1][irow],
tmp_sd[2][irow],
tmp_sd[3][irow],
Input uninterpolated maps and do the interpolation based on the SiteInterpMesh
"""
import os, sys
import numpy as np
from my_util.numer import interp
# interpolation (used in GMT)
infile = sys.argv[1] # file full path with name
outfile = sys.argv[2]
inputs = np.loadtxt( infile )
SiteLon = inputs[:,0]
SiteLat = inputs[:,1]
Value = inputs[:,2]
site_locs1 = './SiteInterpMesh.txt'
sites = np.loadtxt( site_locs1 )
SiteLon1D = sites[:,0]
SiteLat1D = sites[:,1]
eps = 0.001
smooth = 0.01
method = {'name':'exp','smooth':smooth}
newValue = interp( SiteLon, SiteLat, Value, SiteLon1D, SiteLat1D, eps=eps, method=method )
fid = open( outfile, 'w' )
for i in xrange( len(SiteLon1D) ):
fid.write( '%s %s %s\n'%(SiteLon1D[i], SiteLat1D[i], newValue[i]) )
fid.close()