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
from gmtpy import GMT
gmt = GMT( config={'PAGE_COLOR':'247/247/240'} )
gmt.psbasemap( R=(0,5,0,5),
J='X%gi/%gi' % (5,3),
B='%g:Time:/%g:Amplitude:SWne' % (1,1) )
# Make four different datasets
# (1) a nested list, with the first dim corresponding to columns
data_as_columns = [ [ 0,1,2,3,4,5 ], [0,1,0.5,1,0.5,1] ]
# (2) a nested list, with the first dim corresponding to rows
data_as_rows = [ [0,1], [1,2], [2,3], [3,3.5], [4,3], [5,2] ]
# (3) a string containing an ascii table
data_as_string = '''0 5
1 4
2 3.5
3 4
4 4.5
5 5'''
# (4) write ascii table in a temporary file...
# Get a filename in the private tempdir of the GMT instance.
# Files in that directory get deleted automatically.
filename = gmt.tempfilename('table.txt')
import numpy as np
# some data to plot...
x = np.linspace(0, 5, 101)
ys = (np.sin(x) + 2.5, np.cos(x) + 2.5)
gmt = GMT(config={'PAGE_COLOR': '247/247/240'})
layout = GridLayout(1, 2)
widgets = []
for iwidget in range(2):
inner_layout = FrameLayout()
layout.set_widget(0, iwidget, inner_layout)
widget = inner_layout.get_widget('center')
widget.set_horizontal(7 * cm)
widget.set_vertical(7 * cm / golden_ratio)
widgets.append(widget)
#gmt.draw_layout( layout )
#print layout
for widget, y in zip(widgets, ys):
gmt.psbasemap(R=(0, 5, 0, 5),
B='%g:Time [ s ]:/%g:Amplitude [ m ]:SWne' % (1, 1),
*widget.XYJ())
gmt.psxy(R=True, W='2p,blue,o', in_columns=(x, y), *widget.XYJ())
gmt.save('example4.pdf', bbox=layout.bbox())
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())
# plot cross-section on map
gmt = GMT(
config={
"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]])
from gmtpy import GMT
gmt = GMT(config={'PAGE_COLOR': '247/247/240'})
gmt.psbasemap(R=(0, 5, 0, 5),
J='X%gi/%gi' % (5, 3),
B='%g:Time:/%g:Amplitude:SWne' % (1, 1))
# Make four different datasets
# (1) a nested list, with the first dim corresponding to columns
data_as_columns = [[0, 1, 2, 3, 4, 5], [0, 1, 0.5, 1, 0.5, 1]]
# (2) a nested list, with the first dim corresponding to rows
data_as_rows = [[0, 1], [1, 2], [2, 3], [3, 3.5], [4, 3], [5, 2]]
# (3) a string containing an ascii table
data_as_string = '''0 5
1 4
2 3.5
3 4
4 4.5
5 5'''
# (4) write ascii table in a temporary file...
# Get a filename in the private tempdir of the GMT instance.
# Files in that directory get deleted automatically.
filename = gmt.tempfilename('table.txt')
f = open(filename, 'w')
f.write('0 3\n1 3\n5 1.2\n')
# We will plot in the 'center' widget:
plot_widget = layout.get_widget('center')
# Set width of plot area to 8 cm and height of the 'top' margin
# to 1 cm. The other values are calculated automatically.
plot_widget.set_horizontal( 8*cm )
layout.get_widget('top').set_vertical( 1*cm )
# Define how the widget's output parameters are translated
# into -X, -Y and -J option arguments. (This could be skipped
# in this example, because the following templates
# are just the built-in defaults)
plot_widget['X'] = '-Xa%(xoffset)gp'
plot_widget['Y'] = '-Ya%(yoffset)gp'
plot_widget['J'] = '-JX%(width)gp/%(height)gp'
gmt.psbasemap( R=(0,5,0,5),
B='%g:Time [ s ]:/%g:Amplitude [ m ]:SWne' % (1,1),
*plot_widget.XYJ())
gmt.psxy( R=True,
W='2p,blue,o',
in_columns=(x,y),
*plot_widget.XYJ() )
# Save the output, while replacing GMT's default bounding box
# with the exact box of the layout.
gmt.save('example3.pdf', bbox=layout.bbox())
