def gmt_north_america(**kwargs):
'''
Give rf_data as ([values],[time])
'''
from gmtpy import GMT
#get kwargs
fname = kwargs.get('fname','USA_map.pdf')
station_data = kwargs.get('station_data','none')
quake_locs = kwargs.get('quake_locs','none')
rf_data = kwargs.get('rf_data','none')
header = kwargs.get('header','none')
#topo data
etopo='/geo/home/romaguir/utils/ETOPO5.grd'
topo_grad='/geo/home/romaguir/utils/topo_grad.grd'
#colormap
colombia='/geo/home/romaguir/utils/colors/colombia'
region = '-128/-66/24/52'
scale = 'l-100/35/33/45/1:30000000'
#initialize gmt
gmt = GMT(config={'BASEMAP_TYPE':'fancy',
'HEADER_FONT_SIZE':'14'})
#'COLOR_BACKGROUND':'-', :setting this to '-' plots z are transparent
#'COLOR_FOREGROUND':'-'})
#make colormap
cptfile = gmt.tempfilename()
gmt.makecpt(C=colombia,T='-4000/4950/100',Z=True,out_filename=cptfile,D='i')
#make gradient
#topo_grad = gmt.tempfilename()
#gmt.grdgradient(etopo,V=True,A='100',N='e0.8',M=True,G=topo_grad,K=False)
#plot topography
gmt.grdimage( etopo,
R = region,
J = scale,
C = cptfile,
E = '200')
#I = '0.5')#topo_grad)
#plot coastlines
gmt.pscoast( R=region,
J=scale,
B='a10',
D='l',
A='500',
W='thinnest,black,-',
N='all')
#plot stations
if station_data != 'none':
gmt.psxy( R=region,
J=scale,
B='a10',
S='t0.1',
G='red',
in_rows = station_data )
if quake_locs != 'none':
eq_region = 'g'
eq_scale = 'E-100/40/2.25i'
gmt.pscoast( R = eq_region,
J = eq_scale,
B = 'p',
A = '10000',
G = 'lightgrey',
W = 'thinnest',
Y = '3.5i',
X = '-0.5i' )
gmt.psxy( R = eq_region,
J = eq_scale,
S = 'a0.05',
G = 'blue',
in_rows = quake_locs )
#plot receiver function stack
if rf_data != 'none':
rf_region = '-0.20/0.20/0/100'
rf_scale = 'X1i/-5i'
gmt.psxy( R = rf_region,
J = rf_scale,
#G = 'grey', #fill
B = '0.25::/10:time (s):NE',
W = 'thin',
X = '9i',
Y = '-3.5i',
in_columns = rf_data )
#plot shaded area for positive values
vals = rf_data[0]
time = rf_data[1]
poly_vals_pos = []
poly_time_pos = []
for i in range(0,len(vals)):
val_here = max(0,np.float(vals[i]))
poly_time_pos.append(time[i])
poly_vals_pos.append(val_here)
poly_vals_pos.append(0.0)
poly_time_pos.append(time[::-1][0])
poly_vals_pos.append(0.0)
poly_time_pos.append(time[0])
gmt.psxy( R = rf_region,
J = rf_scale,
G = 'red',
B = '0.25::/10:time (s):NE',
W = 'thin',
in_columns = (poly_vals_pos,poly_time_pos) )
#plot shaded area for negative values
'''
vals = rf_data[0]
time = rf_data[1]
poly_vals_neg = []
poly_time_neg = []
for i in range(0,len(vals)):
val_here = min(0,np.float(vals[i]))
poly_time_neg.append(time[i])
poly_vals_neg.append(val_here)
poly_vals_neg.append(0.0)
poly_time_neg.append(time[::-1][0])
poly_vals_neg.append(0.0)
poly_time_neg.append(time[0])
gmt.psxy( R = rf_region,
J = rf_scale,
G = 'blue',
B = '0.25::/10:time (s):NE',
W = 'thin',
in_columns = (poly_vals_neg,poly_time_neg) )
'''
#header_file = open('header_file','w')
#header_file.write('<< EOF')
#header_file.close()
#write header information
if header != 'none':
stations_text = header['N_traces'] + ' traces in stack'
events_text = header['N_events'] + ' events'
freq_text = header['frequency']
decon_text = 'deconvolution method : ' + header['decon']
gmt.pstext( in_rows = [(-96,60,12,0,1,'MC',stations_text)],
R = region,
J = scale,
N = True,
X = '-8.5i' )
gmt.pstext( in_rows = [(-96,59,12,0,1,'MC',events_text)],
R = region,
J = scale,
N = True )
gmt.pstext( in_rows = [(-96,58,12,0,1,'MC',freq_text)],
R = region,
J = scale,
N = True )
gmt.pstext( in_rows = [(-96,57,12,0,1,'MC',decon_text)],
R = region,
J = scale,
N = True )
#save figure
gmt.save(fname)
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())
def gmt_north_america(**kwargs):
'''
Give rf_data as ([values],[time])
'''
from gmtpy import GMT
#get kwargs
fname = kwargs.get('fname','USA_map.pdf')
station_data = kwargs.get('station_data','none')
quake_locs = kwargs.get('quake_locs','none')
rf_data = kwargs.get('rf_data','none')
header = kwargs.get('header','none')
#topo data
etopo='/geo/home/romaguir/utils/ETOPO5.grd'
topo_grad='/geo/home/romaguir/utils/topo_grad.grd'
#colormap
colombia='/geo/home/romaguir/utils/colors/colombia'
region = '-128/-66/24/52'
scale = 'l-100/35/33/45/1:30000000'
#initialize gmt
gmt = GMT(config={'BASEMAP_TYPE':'fancy',
'HEADER_FONT_SIZE':'14'})
#'COLOR_BACKGROUND':'-', :setting this to '-' plots z are transparent
#'COLOR_FOREGROUND':'-'})
#make colormap
cptfile = gmt.tempfilename()
gmt.makecpt(C=colombia,T='-4000/4950/100',Z=True,out_filename=cptfile,D='i')
#make gradient
#topo_grad = gmt.tempfilename()
#gmt.grdgradient(etopo,V=True,A='100',N='e0.8',M=True,G=topo_grad,K=False)
#plot topography
gmt.grdimage( etopo,
R = region,
J = scale,
C = cptfile,
E = '200')
#I = '0.5')#topo_grad)
#plot coastlines
gmt.pscoast( R=region,
J=scale,
B='a10',
D='l',
A='500',
W='thinnest,black,-',
N='all')
#plot stations
if station_data != 'none':
gmt.psxy( R=region,
J=scale,
B='a10',
S='t0.1',
G='red',
in_rows = station_data )
if quake_locs != 'none':
eq_region = 'g'
eq_scale = 'E-100/40/2.25i'
gmt.pscoast( R = eq_region,
J = eq_scale,
B = 'p',
A = '10000',
G = 'lightgrey',
W = 'thinnest',
Y = '3.5i',
X = '-0.5i' )
gmt.psxy( R = eq_region,
J = eq_scale,
S = 'a0.05',
G = 'blue',
in_rows = quake_locs )
#plot receiver function stack
if rf_data != 'none':
rf_region = '-0.20/0.20/0/100'
rf_scale = 'X1i/-5i'
gmt.psxy( R = rf_region,
J = rf_scale,
#G = 'grey', #fill
B = '0.25::/10:time (s):NE',
W = 'thin',
X = '9i',
Y = '-3.5i',
in_columns = rf_data )
#plot shaded area for positive values
vals = rf_data[0]
time = rf_data[1]
poly_vals_pos = []
poly_time_pos = []
for i in range(0,len(vals)):
val_here = max(0,np.float(vals[i]))
poly_time_pos.append(time[i])
poly_vals_pos.append(val_here)
poly_vals_pos.append(0.0)
poly_time_pos.append(time[::-1][0])
poly_vals_pos.append(0.0)
poly_time_pos.append(time[0])
gmt.psxy( R = rf_region,
J = rf_scale,
G = 'red',
B = '0.25::/10:time (s):NE',
W = 'thin',
in_columns = (poly_vals_pos,poly_time_pos) )
#plot shaded area for negative values
'''
vals = rf_data[0]
time = rf_data[1]
poly_vals_neg = []
poly_time_neg = []
for i in range(0,len(vals)):
val_here = min(0,np.float(vals[i]))
poly_time_neg.append(time[i])
poly_vals_neg.append(val_here)
poly_vals_neg.append(0.0)
poly_time_neg.append(time[::-1][0])
poly_vals_neg.append(0.0)
poly_time_neg.append(time[0])
gmt.psxy( R = rf_region,
J = rf_scale,
G = 'blue',
B = '0.25::/10:time (s):NE',
W = 'thin',
in_columns = (poly_vals_neg,poly_time_neg) )
'''
#header_file = open('header_file','w')
#header_file.write('<< EOF')
#header_file.close()
#write header information
if header != 'none':
stations_text = header['N_traces'] + ' traces in stack'
events_text = header['N_events'] + ' events'
freq_text = header['frequency']
decon_text = 'deconvolution method : ' + header['decon']
gmt.pstext( in_rows = [(-96,60,12,0,1,'MC',stations_text)],
R = region,
J = scale,
N = True,
X = '-8.5i' )
gmt.pstext( in_rows = [(-96,59,12,0,1,'MC',events_text)],
R = region,
J = scale,
N = True )
gmt.pstext( in_rows = [(-96,58,12,0,1,'MC',freq_text)],
R = region,
J = scale,
N = True )
gmt.pstext( in_rows = [(-96,57,12,0,1,'MC',decon_text)],
R = region,
J = scale,
N = True )
#save figure
gmt.save(fname)
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)
#test(field)
"ANOT_FONT_SIZE": 14,
"LABEL_FONT_SIZE": 14,
"ANNOT_OFFSET_SECONDARY": "0.1c",
"ANNOT_OFFSET_PRIMARY": "0.1c",
"LABEL_OFFSET": "0.1c",
"FRAME_PEN": ".5p",
"PLOT_DEGREE_FORMAT": "-D",
}
)
rng = "-145/-50/41/85"
scl = "L-97.5/63/41/85/15c"
markers = "markers.xyp"
gmt.psbasemap(R=rng, J=scl, B="a15f5WSne", Y="2c", X="2c")
gmt.pscoast("-N1", R=True, J=True, D="i", W="0.5p,black", N="2")
cnt = 0
for _slon, _slat, _elon, _elat in zip(slon, slat, elon, elat):
gmt.project(C="%f/%f" % (_slon, _slat), E="%f/%f" % (_elon, _elat), G=100, Q=True, out_filename=markers)
gmt.psxy(R=True, J=True, W="2p,red,", in_rows=[[_slon, _slat], [_elon, _elat]])
# gmt.psxy(markers,R=True,J=True,S='y0.1c',W='1p,blue')
gmt.psxy(markers, R=True, J=True, S="s0.1c", W="1p,blue")
lbl1, lbl2 = anot[cnt]
txtstr1 = """%f %f 10 0 1 RB %s""" % (_slon, _slat, lbl1)
txtstr2 = """%f %f 10 0 1 LB %s""" % (_elon, _elat, lbl2)
gmt.pstext(R=True, J=True, W="white", G="blue", N=True, in_string=txtstr1)
gmt.pstext(R=True, J=True, W="white", G="blue", N=True, in_string=txtstr2)
cnt += 1
for lon, lat in invres:
gmt.psxy(R=True, J=True, S="t0.5c", G="red", in_rows=[[lon, lat]])
gmt.save(foutmap)
