def plot_map(stations, center, events=None, savename=None):
from pyrocko.plot.automap import Map
from pyrocko.example import get_example_data
from pyrocko import model, gmtpy
from pyrocko import moment_tensor as pmt
gmtpy.check_have_gmt()
# Generate the basic map
m = Map(lat=center[0],
lon=center[1],
radius=150000.,
width=30.,
height=30.,
show_grid=False,
show_topo=True,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=False)
# Draw some larger cities covered by the map area
m.draw_cities()
# Generate with latitute, longitude and labels of the stations
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
labels = ['.'.join(s.nsl()) for s in stations]
# Stations as black triangles.
m.gmt.psxy(in_columns=(lons, lats), S='t20p', G='black', *m.jxyr)
# Station labels
for i in range(len(stations)):
m.add_label(lats[i], lons[i], labels[i])
beachball_symbol = 'd'
factor_symbl_size = 5.0
if events is not None:
for ev in events:
mag = ev.magnitude
if ev.moment_tensor is None:
ev_symb = 'c' + str(mag * factor_symbl_size) + 'p'
m.gmt.psxy(in_rows=[[ev.lon, ev.lat]],
S=ev_symb,
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
beachball_size = mag * factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(M=True,
S='%s%g' % (beachball_symbol[0],
(beachball_size) / gmtpy.cm))
else:
kwargs = dict(S='%s%g' % (beachball_symbol[0],
(beachball_size) * 2 / gmtpy.cm))
m.gmt.psmeca(in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
*m.jxyr,
**kwargs)
if savename is None:
if events is None:
m.save('pics/stations_ridgecrest.png')
else:
m.save('pics/mechanisms_scedc_ridgecrest.png')
else:
m.save(savename)
lon=35.5,
radius=150000.,
width=30.,
height=30.,
show_grid=False,
show_topo=True,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=True)
# Draw some larger cities covered by the map area
m.draw_cities()
# Generate with latitute, longitude and labels of the stations
stations = model.load_stations('stations_deadsea.pf')
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
labels = ['.'.join(s.nsl()) for s in stations]
# Stations as black triangles. Genuine GMT commands can be parsed by the maps'
# gmt attribute. Last argument of the psxy function call pipes the maps'
# pojection system.
m.gmt.psxy(in_columns=(lons, lats), S='t20p', G='black', *m.jxyr)
# Station labels
for i in range(len(stations)):
m.add_label(lats[i], lons[i], labels[i])
lat=31.5,
lon=35.5,
radius=150000.,
width=30., height=30.,
show_grid=False,
show_topo=True,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=True)
# Draw some larger cities covered by the map area
m.draw_cities()
# Generate with latitute, longitude and labels of the stations
stations = model.load_stations('stations_deadsea.pf')
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
labels = ['.'.join(s.nsl()) for s in stations]
# Stations as black triangles. Genuine GMT commands can be parsed by the maps'
# gmt attribute. Last argument of the psxy function call pipes the maps'
# pojection system.
m.gmt.psxy(in_columns=(lons, lats), S='t20p', G='black', *m.jxyr)
# Station labels
for i in range(len(stations)):
m.add_label(lats[i], lons[i], labels[i])