if opts.geo:
dlon = -lal.GreenwichMeanSiderealTime(lal.LIGOTimeGPS(metadata['gps_time'])) % (2*np.pi)
else:
dlon = 0
# Convert sky map from probability to probability per square degree.
probperdeg2 = skymap / hp.nside2pixarea(nside, degrees=True)
# Plot sky map.
vmax = probperdeg2.max()
plot.healpix_heatmap(
probperdeg2, dlon=dlon, nest=metadata['nest'], vmin=0., vmax=vmax)
# Add colorbar.
if opts.colorbar:
cb = plot.colorbar()
cb.set_label(r'prob. per deg$^2$')
# Add contours.
if opts.contour:
cls = 100 * postprocess.find_greedy_credible_levels(skymap)
cs = plot.healpix_contour(
cls, dlon=dlon, nest=metadata['nest'],
colors='k', linewidths=0.5, levels=opts.contour)
fmt = r'%g\%%' if rcParams['text.usetex'] else '%g%%'
plt.clabel(cs, fmt=fmt, fontsize=6, inline=True)
# Add continents.
if opts.geo:
geojson_filename = os.path.join(os.path.dirname(plot.__file__),
'ne_simplified_coastline.json')
dlon = -lal.GreenwichMeanSiderealTime(lal.LIGOTimeGPS(metadata['gps_time'])) % (2*np.pi)
else:
dlon = 0
# Convert sky map from probability to probability per square degree.
probperdeg2 = skymap / hp.nside2pixarea(nside, degrees=True)
# Plot sky map.
vmax = probperdeg2.max()
plot.healpix_heatmap(
probperdeg2, dlon=dlon, nest=metadata['nest'],
vmin=0., vmax=vmax, cmap=plt.get_cmap(opts.colormap))
if opts.colorbar:
# Plot colorbar.
cb = plot.colorbar()
# Set colorbar label.
cb.set_label(r'prob. per deg$^2$')
# Add contours.
if opts.contour:
indices = np.argsort(-skymap)
region = np.empty(skymap.shape)
region[indices] = 100 * np.cumsum(skymap[indices])
cs = plot.healpix_contour(
region, dlon=dlon, nest=metadata['nest'],
colors='k', linewidths=0.5, levels=opts.contour)
fmt = r'%g\%%' if rcParams['text.usetex'] else '%g%%'
plt.clabel(cs, fmt=fmt, fontsize=6, inline=True)