def setup_vtk_map_actor(lat, lon, radius, super_elevation=1, decimation=1,
smoothing=False):
m = Map(lat=lat, lon=lon, radius=radius)
m._setup()
fn, ilum = m._prep_topo('land')
topodata = gmtpy.loadgrd(fn)
return get_topography_actor(*topodata, super_elevation=super_elevation,
decimation=decimation, smoothing=smoothing)
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)
def call(self):
if not self.viewer_connected:
self.get_viewer().about_to_close.connect(
self.file_serving_worker.stop)
self.viewer_connected = True
try:
from OpenGL import GL # noqa
except ImportError:
logger.warn(
'Could not find package OpenGL, '
'if the map does not work try installing OpenGL\n'
'e.g. sudo pip install PyOpenGL')
self.cleanup()
try:
viewer = self.get_viewer()
cli_mode = False
except NoViewerSet:
viewer = None
cli_mode = True
if not cli_mode:
if self.only_active:
_, active_stations = \
self.get_active_event_and_stations()
else:
active_stations = viewer.stations.values()
elif cli_mode:
active_stations = self.stations
station_list = []
if active_stations:
for stat in active_stations:
is_blacklisted = util.match_nslc(viewer.blacklist, stat.nsl())
if (viewer and not is_blacklisted) or cli_mode:
xml_station_marker = XMLStationMarker(
nsl='.'.join(stat.nsl()),
longitude=float(stat.lon),
latitude=float(stat.lat),
active='yes')
station_list.append(xml_station_marker)
active_station_list = StationMarkerList(stations=station_list)
if self.only_active:
markers = [viewer.get_active_event_marker()]
else:
if cli_mode:
markers = self.markers
else:
markers = self.get_selected_markers()
if len(markers) == 0:
tmin, tmax = self.get_selected_time_range(fallback=True)
markers = [m for m in viewer.get_markers()
if isinstance(m, gui_util.EventMarker) and
m.tmin >= tmin and m.tmax <= tmax]
ev_marker_list = []
for m in markers:
if not isinstance(m, gui_util.EventMarker):
continue
xmleventmarker = convert_event_marker(m)
if xmleventmarker is None:
continue
ev_marker_list.append(xmleventmarker)
event_list = EventMarkerList(events=ev_marker_list)
event_station_list = MarkerLists(
station_marker_list=active_station_list,
event_marker_list=event_list)
event_station_list.validate()
if self.map_kind != 'GMT':
tempdir = self.marker_tempdir
if self.map_kind == 'Google Maps':
map_fn = 'map_googlemaps.html'
elif self.map_kind == 'OpenStreetMap':
map_fn = 'map_osm.html'
url = 'http://localhost:' + str(self.port) + '/%s' % map_fn
files = ['loadxmldoc.js', 'map_util.js', 'plates.kml', map_fn]
snuffling_dir = op.dirname(op.abspath(__file__))
for entry in files:
shutil.copy(os.path.join(snuffling_dir, entry),
os.path.join(tempdir, entry))
logger.debug('copied data to %s' % tempdir)
markers_fn = os.path.join(self.marker_tempdir, 'markers.xml')
self.data_proxy.content_to_serve.emit(self.port)
dump_xml(event_station_list, filename=markers_fn)
if self.open_external:
qg.QDesktopServices.openUrl(qc.QUrl(url))
else:
global g_counter
g_counter += 1
self.web_frame(
url,
name='Map %i (%s)' % (g_counter, self.map_kind))
else:
lats_all = []
lons_all = []
slats = []
slons = []
slabels = []
for s in active_stations:
slats.append(s.lat)
slons.append(s.lon)
slabels.append('.'.join(s.nsl()))
elats = []
elons = []
elats = []
elons = []
psmeca_input = []
markers = self.get_selected_markers()
for m in markers:
if isinstance(m, gui_util.EventMarker):
e = m.get_event()
elats.append(e.lat)
elons.append(e.lon)
if e.moment_tensor is not None:
mt = e.moment_tensor.m6()
psmeca_input.append(
(e.lon, e.lat, e.depth/1000., mt[0], mt[1],
mt[2], mt[3], mt[4], mt[5],
1., e.lon, e.lat, e.name))
else:
if e.magnitude is None:
moment = -1.
else:
moment = moment_tensor.magnitude_to_moment(
e.magnitude)
psmeca_input.append(
(e.lon, e.lat, e.depth/1000.,
moment/3., moment/3., moment/3.,
0., 0., 0., 1., e.lon, e.lat, e.name))
lats_all.extend(elats)
lons_all.extend(elons)
lats_all.extend(slats)
lons_all.extend(slons)
lats_all = num.array(lats_all)
lons_all = num.array(lons_all)
if len(lats_all) == 0:
return
center_lat, center_lon = ortho.geographic_midpoint(
lats_all, lons_all)
ntotal = len(lats_all)
clats = num.ones(ntotal) * center_lat
clons = num.ones(ntotal) * center_lon
dists = ortho.distance_accurate50m_numpy(
clats, clons, lats_all, lons_all)
maxd = num.max(dists) or 0.
m = Map(
lat=center_lat, lon=center_lon,
radius=max(10000., maxd) * 1.1,
width=35, height=25,
show_grid=True,
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)
m.gmt.psxy(in_columns=(slons, slats), S='t15p', G='black', *m.jxyr)
for i in range(len(active_stations)):
m.add_label(slats[i], slons[i], slabels[i])
m.gmt.psmeca(
in_rows=psmeca_input, S='m1.0', G='red', C='5p,0/0/0', *m.jxyr)
tmpdir = self.tempdir()
self.outfn = os.path.join(tmpdir, '%i.png' % self.figcount)
m.save(self.outfn)
f = self.pixmap_frame(self.outfn) # noqa