def main(mdlname,dispdic,title):
os.system('gpdcreport '+mdlname+' >tmp.mdl')
models, data, nd, ne, nrow = get_models('tmp.mdl')
gmt = GMT(config={'BASEMAP_TYPE':'plain','ANOT_FONT_SIZE':8,
'LABEL_FONT_SIZE':10,'COLOR_BACKGROUND':'255/255/255',
'COLOR_FOREGROUND':'0/0/0','COLOR_NAN':'255/255/255',
'PAGE_ORIENTATION':'landscape',
'HEADER_FONT_SIZE':15} )
xyz=gmt.tempfilename('testxyz.txt')
xyz2=gmt.tempfilename('testxyz2.txt')
grd=gmt.tempfilename('tmp.grd')
grdcpt=gmt.tempfilename('tmp.cpt')
fileout='dens_test.ps'
rng='1/5/0/40'
scl='X4.2/-6'
dreso = 0.2
sreso = 0.05
misfit = 0.1
#grid1, grid2, x, y, smean, dmean = dplot.dplot(models,data,nd,ne,dreso=dreso, sreso=sreso,mf=misfit)
grid1, grid2, x, y, smean, dmean = dplot.dplot(models,data,nd,ne,dreso=dreso, sreso=sreso,mf=misfit)
#grid1, grid2, x, y = dplot.dplotpy(models,data,nd,ne,dreso=dreso, sreso=sreso,mf=misfit)
# matshow(grid1)
# show()
f = open(xyz,'w')
for ii in range(len(y)):
for jj in range(len(x)):
if grid1[ii,jj]>0.0:
print >>f, x[jj],y[ii], grid1[ii,jj]
f.close()
f = open(xyz2,'w')
for ii in range(len(y)):
for jj in range(len(x)):
if grid2[ii,jj] > 0:
print >>f, x[jj], y[ii], '0.5'
f.close()
anot = int(grid1.max()/1000.)*1000/2.
tick = anot/2
gmt.xyz2grd(xyz,G=grd,R=rng,I='%f/%f'%(sreso,dreso),out_discard=True)
gmt.grd2cpt(grd,C="wysiwyg",Z=True,out_filename=grdcpt)
gmt.psmask(xyz2,R=rng,T=True,J=scl,I='%f/%f'%(sreso,dreso),G='lightgray')
gmt.grdimage(grd,J=scl,R=rng,Q=True,C=grdcpt)
gmt.psbasemap(R=rng,J=scl,B='a1f.5:S-velocity [km/s]:/a10f5:Depth [km]::.%s:WnSe'%title)
gmt.psxy(R=True,J=True,B=True,W='3,black',in_columns=[smean,dmean])
f = open('/home/behrya/dev/data/mt_fixed_layers_ray_c_u_mean.txt','w')
for _p,_v in zip(dmean,smean):
print >>f,_p,_v
f.close()
gmt.psscale(C=grdcpt,D='1.0/1./4c/.4ch',B='a%df%d:No. of models:/::'%(anot,tick))
### plot dispersion curves
gmt.psbasemap(R='5/30/2.0/5.0',J='X4.2/2.5',X='5',B='a1f.5:Period [s]:/a1f.5:Velocity [km/s]:WnSe')
for _d in dispdic.keys():
vo = load(dispdic[_d][0])
p,v = gpdccurve(mdlname,wtype=dispdic[_d][1],ptype=dispdic[_d][2])
gmt.psxy(R=True,J=True,B=True,W='3,black',in_columns=[p,v])
gmt.psxy(R=True,J=True,B=True,W='3,red',in_columns=[vo[:,0],vo[:,1]])
gmt.save(fileout)
os.system('gv '+fileout+'&')
def plotnad(fnad,fout):
gmt = GMT(config={'BASEMAP_TYPE':'plain','ANOT_FONT_SIZE':8,
'LABEL_FONT_SIZE':10,'COLOR_BACKGROUND':'255/255/255',
'COLOR_FOREGROUND':'0/0/0','COLOR_NAN':'255/255/255'} )
grd=gmt.tempfilename('tmp.grd')
grdcpt=gmt.tempfilename('tmp.cpt')
xyz=gmt.tempfilename('xyz.txt')
xyz2=gmt.tempfilename('xyz2.txt')
rng='1/5/0/40'
scl='X4.2/-6'
kosu1,kosu2,x,y,dbest,sbest,dmean,smean = nadplot(fnad,smin=1.5)
f = open(xyz,'w')
for ii in range(len(y)):
for jj in range(len(x)):
if kosu1[ii,jj] > 0:
print >>f, x[jj], y[ii], kosu1[ii,jj]
f.close()
f = open(xyz2,'w')
for ii in range(len(y)):
for jj in range(len(x)):
if kosu2[ii,jj] > 0:
print >>f, x[jj], y[ii], '0.5'
f.close()
gmt.xyz2grd(xyz,G=grd,R=rng,I='.02/.5',out_discard=True)
gmt.grd2cpt(grd,C="wysiwyg",Q='o',Z=True,out_filename=grdcpt)
gmt.psmask(xyz2,R=rng,T=True,J=scl,I='.02/.5',G='lightgray')
gmt.grdimage(grd,J=scl,R=rng,Q=True,P=True,C=grdcpt)
gmt.psbasemap(R=rng,J=scl,B='a1f.5:Velocity [km/s]:/a10f5:Depth [km]:WNse')
gmt.psxy(R=True,J=True,B=True,W='3,red',in_columns=[sbest,dbest])
gmt.psxy(R=True,J=True,B=True,W='3,white',in_columns=[smean,dmean])
gmt.psscale(C=grdcpt,D='1.0/1./4c/.4ch',B='a40f10:No. of models:/::')
gmt.save(fout)
os.system('gv '+fout+'&')
return 1
cnt = 1
for _slat,_slon,_elat,_elon in zip(slat,slon,elat,elon):
print "plotting profile %d"%cnt
ndist, nd, values = plot_2d(field,_slat,_slon,_elat,_elon,pdepth,new=True)
lbl1,lbl2 = anot[cnt-1]
fstr = cStringIO.StringIO()
for dist,depth,vs in zip(ndist,nd,values):
fstr.write("%f %f %f\n"%(dist,depth,vs))
sclx = 18.*ndist.max()/xscale
scly = yscale
scl = 'X%fc/%fc'%(sclx,scly)
print scl
rng = '%f/%f/%f/%f'%(ndist.min(),ndist.max(),nd.min(),nd.max())
grdws = gmt.tempfilename('ws.grd')
grdgd = gmt.tempfilename('grdgd.cpt')
gmt.xyz2grd(G=grdws,R=rng,I='50./1.',out_discard=True,in_string=fstr.getvalue())
gmt.grdgradient(grdws,G=grdgd,out_discard=True,A='180',N='e0.8')
if cnt == 1:
gmt.grdimage(grdws,I=grdgd,R=True,J=scl,C=cptws,
B='a500f100:Distance [km]:/a20f10:Depth [km]:WSne',X='1c',Y='3c')
else:
gmt.grdimage(grdws,I=grdgd,R=True,J=scl,C=cptws,
B='a500f100:Distance [km]:/a20f10:Depth [km]:WSne',Y='%fc'%(scly+2.5))
txtstr1 = """%f %f 12 0 1 LB %s"""%(0.0,8.,lbl1)
txtstr2 = """%f %f 12 0 1 RB %s"""%(ndist.max(),8.,lbl2)
gmt.pstext(R=True,J=True,G='0/0/0',N=True,in_string=txtstr1)
gmt.pstext(R=True,J=True,G='0/0/0',N=True,in_string=txtstr2)
cnt += 1
gmt.save(foutprofiles)
def plot_rep(repfile, paramfile, wtype, pixfile, show=True, misfit=0.1,
minmax=True):
"""
Plot 1D velocity profile.
"""
# ## read in models from dinver-output
os.system('gpdcreport ' + repfile + ' >tmp.mdl')
models, data, nd, ne, nrow, nlayer = get_models('tmp.mdl')
os.remove('tmp.mdl')
if misfit == 'all':
misfit = data.max()
elif misfit <= data.min():
misfit = median(data)
# ## calculate density
sreso = 0.05 # horizontal resolution
dreso = .5 # vertical resolution
grid1, grid2, x, y, smean, dmean = dplot(models, data, nd, ne, dreso=dreso,
sreso=sreso, mf=misfit, nlayer=nlayer, dmax=120)
# ## write output into temporary files that can be plotted by gmt
xyz = tempfile.mktemp()
xyz2 = tempfile.mktemp()
grd = tempfile.mktemp()
grdcpt = tempfile.mktemp()
fout = pixfile
f = open(xyz, 'w')
for ii in range(len(y)):
for jj in range(len(x)):
if grid1[ii, jj] > 0.0:
print >> f, x[jj], -y[ii], grid1[ii, jj]
f.close()
f = open(xyz2, 'w')
for ii in range(len(y)):
for jj in range(len(x)):
if grid2[ii, jj] > 0:
print >> f, x[jj], -y[ii], '0.5'
f.close()
lat, lon = dissect_fname(repfile)
if wtype == 'love':
wt = 'L'
if wtype == 'rayleigh':
wt = 'R'
# print repfile, lat, lon
# ## gmt plot
rng = '1/5/-120/0'
step = '%f/%f' % (sreso, dreso)
anot = int(grid1.max() / 1000.) * 1000 / 2.
tick = anot / 2
gmt = GMT(config={'ANOT_FONT_SIZE':8, 'LABEL_FONT_SIZE':10,
'ANNOT_OFFSET_SECONDARY':'0.1c',
'ANNOT_OFFSET_PRIMARY':'0.1c',
'LABEL_OFFSET':'0.1c',
'FRAME_PEN':'.5p'})
widgets, layout = make_widget()
if 1:
widget = widgets[2]
gmt.xyz2grd(xyz, G=grd, R=rng, I='%f/%f' % (sreso, dreso), out_discard=True)
gmt.grd2cpt(grd, L='0/%d' % 3000, C="wysiwyg", D=True, Z=True, out_filename=grdcpt)
gmt.psbasemap(R=True, B='a1f.5:S-velocity [km/s]:/a10f5:Depth [km]:WnSe', *widget.XYJ())
# gmt.psmask(xyz2, R=True, T=True, I='%f/%f' % (sreso, dreso), G='lightgray', *widget.XYJ())
gmt.grdimage(grd, R=True, Q=True, C=grdcpt, *widget.XYJ())
gmt.psxy(R=True, B=True, W='3,black', in_columns=[smean, -dmean], *widget.XYJ())
bmdl = get_best_model(repfile, dreso, dmax=120., dmin=0.)
gmt.psxy(R=True, B=True, W='3,black,-', in_rows=bmdl, *widget.XYJ())
gmt.psscale(widget.XYJ()[0], widget.XYJ()[1], C=grdcpt, D='1.7c/1.5c/2.5c/.4ch', B='a%df%d10:No. of models:/::' % (1000, 500))
txtstr = "1.2 -7. 8 0 1 LT lat = %3.2f" % lat
gmt.pstext(R=rng, G='0/0/0', N=True, in_string=txtstr, *widget.XYJ())
txtstr = "1.2 -12. 8 0 1 LT lon = %3.2f" % lon
gmt.pstext(R=True, G='0/0/0', N=True, in_string=txtstr, *widget.XYJ())
# plot the minimum and maximum model that is allowed
# by the parameterisation
if minmax:
mdl_min, mdl_max = minmax_mdl(paramfile)
gmt.psxy(R=True, B=True, W='3,red,-', in_rows=mdl_min, *widget.XYJ())
gmt.psxy(R=True, B=True, W='3,red,-', in_rows=mdl_max, *widget.XYJ())
if 1:
p, v, e = get_disp(repfile, wtype='phase')
plot_disp(gmt, repfile, widgets[1], p, v, e, 'phase', ptype='p', wtype=wt, mode=0, misfit=misfit)
p, v, e = get_disp(repfile, wtype='group')
plot_disp(gmt, repfile, widgets[0], p, v, e, 'group', ptype='g', wtype=wt, mode=0, misfit=misfit)
if 0:
p, v, e = get_disp(repfile, wtype='grouponly')
plot_disp(gmt, repfile, widgets[0], p, v, e, 'group', ptype='g', wtype=wt, mode=0, misfit=misfit)
if 0:
plot_hist(gmt, widgets, models, nd, ne)
gmt.save(fout)
meanfout = fout.replace('.eps', '_mean.txt')
savetxt(meanfout, vstack((-dmean, smean)).T)
if show:
os.system('gv %(fout)s&' % vars())
for lat in runlat:
for lon in runlon:
print >>f, lon, lat
f.close()
### Plot original
na04_moho = loadtxt('./LITH5.0/NA04_moho.xyf')
gmt = GMT(config={'PAGE_ORIENTATION':'landscape'})
rng = '-145/-50/35/80'
scl = 'L-100/60/45/65/12c'
anot = 'a20f10/a25f5WSne'
fout = 'na04_moho.eps'
tmpgrd = gmt.tempfilename('moho_temp.grd')
mohogrd = gmt.tempfilename('moho.grd')
mohocpt = gmt.tempfilename('moho.cpt')
gmt.xyz2grd(G=mohogrd,I='%f/%f'%(0.25,0.25),R=rng,out_discard=True,in_rows=na04_moho)
gmt.grd2cpt(mohogrd,E=50,L='10/60',C="seis",out_filename=mohocpt)
gmt.grdtrack(xyfile,G=mohogrd,R=True,out_filename=xyzfile)
gmt.grdimage(mohogrd,R=True,J=scl,C=mohocpt)
gmt.pscoast(R=True,J=scl,B=anot,D='i',W='thinnest' )
### Plot resampled
na04_moho = loadtxt(xyzfile)
gmt.xyz2grd(G=mohogrd,I='%f/%f'%(1.,1.),R=rng,out_discard=True,in_rows=na04_moho)
gmt.grdimage(mohogrd,R=True,J=scl,C=mohocpt,X='13c')
gmt.pscoast(R=True,J=scl,B=anot,D='i',W='thinnest' )
gmt.psscale(C=mohocpt,V=True,D='0c/-.7c/6c/.2ch',B='10::/:km:')
gmt.save(fout)
os.system('gv %s&'%fout)
