def plot_canada_map():
d = defaultdict(list)
gmt = GMT(config={'PAGE_ORIENTATION':'landscape'})
rng = '-70/-52/40/52.'
scl = 'M10c'
gmt.pscoast(R=rng,J=scl,B='a0.5wsne',D='l',W='thinnest',m=True,A='2/1/1')
a = gmt.output.getvalue().split('\n')
z = 0.
cnt = 0
connections = list()
for _l in a:
if _l.startswith('#'):continue
if _l.startswith('>'):
cnt += 1
continue
try:
d[cnt].append(map(float,_l.split('\t')))
except ValueError:
print _l
for _k in d.keys():
ar = array(d[_k])
x = (6371)*cos(2*pi*ar[:,1]/360.)*cos(2*pi*ar[:,0]/360.)
y = (6371)*cos(2*pi*ar[:,1]/360.)*sin(2*pi*ar[:,0]/360.)
z = (6371)*sin(2*pi*ar[:,1]/360.)
pts = mlab.plot3d(x,y,z,tube_radius=2.0,color=(0,0,0))
def grafica_track(satelite, debris):
gmt = GMT(config={'BASEMAP_TYPE': 'fancy'})
gmt.pscoast(
R='0/280/-75/75', #g
J='M6i', #'G70/-51/5i'
B='30g30', # grid
N='1',
S=(173, 216, 230), # wet fill color
G=(144, 238, 144), # dry fill color
W='thinnest') # shoreline pen
gmt.psxy(
satelite, #'../Encuentro/archivos/15482U',
R='',
J='',
O='-',
S='t0.05',
K='K',
G='red')
gmt.psxy(
debris, #'../Encuentro/archivos/27386U',
R='',
J='',
O='',
S='t0.05',
K='K',
G='blue')
gmt.save('../visual/archivos/ploteo_track.ps')
print 'Grafico Terminado'
def gmt_map(event_lats=None,
event_lons=None,
station_lats=None,
station_lons=None,
**kwargs):
with_stations = False
if kwargs.get('stations', False):
with_stations = True
with_events = False
if kwargs.get('events', False):
with_events = True
gmt = GMT(config={'BASEMAP_TYPE': 'fancy'})
lat_min = min(station_lats + event_lats)
lat_max = max(station_lats + event_lats)
lon_min = min(station_lons + event_lons)
lon_max = max(station_lons + event_lons)
lat_offset = (lat_max - lat_min) * 0.3
lon_offset = (lon_max - lon_min) * 0.3
gmt.pscoast(R='%i/%i/%i/%i' % (lon_min - lon_offset, lon_max + lon_offset,
lat_min - lat_offset, lat_max + lat_offset),
J='M10c',
B='4g4',
D='f',
S=(114, 159, 207),
G=(233, 185, 110),
W='thinnest')
if station_lats and station_lons and with_stations:
gmt.psxy('-St0.5c',
R=True,
J=True,
G=(0, 255, 123),
in_columns=[station_lons, station_lats])
if event_lats and event_lons and with_events:
gmt.psxy('-Sa0.2c',
R=True,
J=True,
G=(255, 0, 0),
in_columns=[event_lons, event_lats])
gmt.save('mapplot.pdf')
def gmt_map(event_lats=None, event_lons=None, station_lats=None,
station_lons=None, **kwargs):
with_stations = False
if kwargs.get('stations', False):
with_stations = True
with_events= False
if kwargs.get('events', False):
with_events = True
gmt = GMT( config={'BASEMAP_TYPE':'fancy'} )
lat_min = min(station_lats+ event_lats)
lat_max = max(station_lats+ event_lats)
lon_min = min(station_lons+ event_lons)
lon_max = max(station_lons+ event_lons)
lat_offset = (lat_max-lat_min)*0.3
lon_offset = (lon_max-lon_min)*0.3
gmt.pscoast( R='%i/%i/%i/%i'%(lon_min-lon_offset,
lon_max+lon_offset,
lat_min-lat_offset,
lat_max+lat_offset),
J='M10c',
B='4g4',
D='f',
S=(114,159,207),
G=(233,185,110),
W='thinnest')
if station_lats and station_lons and with_stations:
gmt.psxy('-St0.5c', R=True, J=True, G=(0,255,123),
in_columns=[station_lons, station_lats])
if event_lats and event_lons and with_events:
gmt.psxy('-Sa0.2c', R=True, J=True, G=(255,0,0),
in_columns=[event_lons, event_lats])
gmt.save('mapplot.pdf')
from gmtpy import GMT
gmt = GMT(config={'BASEMAP_TYPE': 'fancy'})
gmt.pscoast(
R='5/15/52/58', # region
J='B10/55/55/60/10c', # projection
B='4g4', # grid
D='f', # resolution
S=(114, 159, 207), # wet fill color
G=(233, 185, 110), # dry fill color
W='thinnest') # shoreline pen
gmt.save('example1.pdf')
gmt.save('example1.eps')
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 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)
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]])
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)
from gmtpy import GMT
gmt = GMT( config={'BASEMAP_TYPE':'fancy'})
gmt.pscoast( R='5/15/52/58', # region
J='B10/55/55/60/10c', # projection
B='4g4', # grid
D='f', # resolution
S=(114,159,207), # wet fill color
G=(233,185,110), # dry fill color
W='thinnest' ) # shoreline pen
gmt.save('example1.pdf')
gmt.save('example1.eps')