def plot_spatial_with_dcs(events, eventsclusters, clusters, conf, plotdir):
'''
Plot map of seismicity clusters, with focal mechanisms
'''
lats = [ev.lat for ev in events]
lons = [ev.lon for ev in events]
# deps = [ev.depth for ev in events]
# colors = [cluster_to_color(clid) for clid in eventsclusters]
if conf.sw_filterevent:
latmin, latmax = conf.latmin, conf.latmax
lonmin, lonmax = conf.lonmin, conf.lonmax
# depmin, depmax = conf.depthmin, conf.depthmax
if latmin > latmax:
print('cases over lon +-180 still to be implemented')
sys.exit()
center = model.event(0.5 * (latmin + latmax), 0.5 * (lonmin + lonmax))
else:
latmin, latmax = min(lats) - 0.1, max(lats) + 0.1
lonmin, lonmax = min(lons) - 0.1, max(lons) + 0.1
# depmin = 0.*km
# depmax = 1.05*max(deps)
center = od.Loc(0.5 * (latmin + latmax), 0.5 * (lonmin + lonmax))
# Map size
if conf.sw_manual_radius:
safe_radius = conf.map_radius
else:
corners = [od.Loc(latmin, lonmin), od.Loc(latmin, lonmax)]
dist1 = od.distance_accurate50m(center, corners[0])
dist2 = od.distance_accurate50m(center, corners[1])
safe_radius = max(dist1, dist2)
# Generate the basic map
m = Map(lat=center.lat,
lon=center.lon,
radius=safe_radius,
width=30.,
height=30.,
show_grid=False,
show_topo=False,
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)
if conf.sw_filterevent:
rectlons = [lonmin, lonmin, lonmax, lonmax, lonmin]
rectlats = [latmin, latmax, latmax, latmin, latmin]
m.gmt.psxy(in_columns=(rectlons, rectlats),
W='thin,0/0/0,dashed',
*m.jxyr)
# Draw some larger cities covered by the map area
m.draw_cities()
# Events in clusters
factor_symbl_size = 5.
beachball_symbol = 'd'
for id_cluster in clusters:
col = cluster_to_color(id_cluster)
g_col = color2rgb(col)
for iev, evcl in enumerate(eventsclusters):
if evcl == id_cluster:
ev = events[iev]
if ev.moment_tensor is not None:
factor_symbl_size = ev.magnitude
devi = ev.moment_tensor.deviatoric()
beachball_size = 3. * 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)
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))
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
m.gmt.psmeca(in_rows=[data],
G=g_col,
E='white',
W='1p,%s' % g_col,
*m.jxyr,
**kwargs)
figname = os.path.join(plotdir, 'plot_map_with_dcs.' + conf.figure_format)
m.save(figname)
def plot_spatial(events, eventsclusters, clusters, conf, plotdir):
'''
Plot map of seismicity clusters
'''
lats = [ev.lat for ev in events]
lons = [ev.lon for ev in events]
# deps = [ev.depth for ev in events]
# colors = [cluster_to_color(clid) for clid in eventsclusters]
if conf.sw_filterevent:
latmin, latmax = conf.latmin, conf.latmax
lonmin, lonmax = conf.lonmin, conf.lonmax
# depmin, depmax = conf.depthmin, conf.depthmax
if latmin > latmax:
print('cases over lon +-180 still to be implemented')
sys.exit()
center = model.event(0.5 * (latmin + latmax), 0.5 * (lonmin + lonmax))
else:
latmin, latmax = min(lats) - 0.1, max(lats) + 0.1
lonmin, lonmax = min(lons) - 0.1, max(lons) + 0.1
# depmin = 0.*km
# depmax = 1.05*max(deps)
center = od.Loc(0.5 * (latmin + latmax), 0.5 * (lonmin + lonmax))
# Map size
if conf.map_radius is not None:
safe_radius = conf.map_radius
else:
corners = [od.Loc(latmin, lonmin), od.Loc(latmin, lonmax)]
dist1 = od.distance_accurate50m(center, corners[0])
dist2 = od.distance_accurate50m(center, corners[1])
safe_radius = max(dist1, dist2)
# Generate the basic map
m = Map(lat=center.lat,
lon=center.lon,
radius=safe_radius,
width=30.,
height=30.,
show_grid=False,
show_topo=False,
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)
if conf.sw_filterevent:
rectlons = [lonmin, lonmin, lonmax, lonmax, lonmin]
rectlats = [latmin, latmax, latmax, latmin, latmin]
m.gmt.psxy(in_columns=(rectlons, rectlats),
W='thin,0/0/0,dashed',
*m.jxyr)
# Draw some larger cities covered by the map area
m.draw_cities()
# Events in clusters
for id_cluster in clusters:
col = cluster_to_color(id_cluster)
mylats, mylons = [], []
for iev, evcl in enumerate(eventsclusters):
if evcl == id_cluster:
mylats.append(events[iev].lat)
mylons.append(events[iev].lon)
m.gmt.psxy(in_columns=(mylons, mylats),
S='c7p',
G=color2rgb(col),
*m.jxyr)
figname = os.path.join(plotdir, 'plot_map.' + conf.figure_format)
m.save(figname)