def draw_albedo_map(nside, view_map, bright_spot):
nside = nside # map resolution
# Gaussian process properties
whitenoise_relative_amp = 0.02
length_scale = 30. * np.pi / 180
albedo_mean = .5
albedo_std = 0.2
# Draw a valid albedo map (i.e., 0 < albedo < 1)
while True:
simulated_map = draw_map(nside, albedo_mean, albedo_std,
whitenoise_relative_amp, length_scale)
if min(simulated_map) > 0 and max(simulated_map) < 1:
break
for i in range(0, simulated_map.size):
if i == bright_spot:
simulated_map[i] = 1.00
else:
simulated_map[i] = 0.00
if view_map == True:
hp.mollview(simulated_map, title='albedo', cmap='gist_gray')
return simulated_map
from exocartographer import IlluminationMapPosterior
from exocartographer.util import logit, inv_logit
from astropy_healpix import HEALPix
import pdb
# Potential Nside values = 1,2,4,8
# Map:
nside = 1
map = HEALPix(nside=nside, order='nested')
whitenoise_relative_amp = 0.2
length_scale = 30 * np.pi / 2
albedo_mean = 0.5
albedo_std = 0.2
while True:
one_point_map = draw_map(nside, albedo_mean, albedo_std,
whitenoise_relative_amp, length_scale)
if min(one_point_map) > 0 and max(one_point_map) < 1:
break
bright_spot = 1
for i in range(0, one_point_map.size):
if i == bright_spot:
one_point_map[i] = 1.00
else:
one_point_map[i] = 0.00
# Parameters
p_rotation = 1
p_orbit = 365.256363
lat, lng = map.healpix_to_lonlat([bright_spot])
w_rot = 2 * np.pi / p_rotation
w_orb = 2 * np.pi / p_orbit
from exocartographer import IlluminationMapPosterior
from exocartographer.util import logit, inv_logit
import pdb
from astropy_healpix import HEALPix
# resolution
nside = 4
# Gaussian process properties
whitenoise_relative_amp = 0.02
length_scale = 30. * np.pi / 2
albedo_mean = 0.5
albedo_std = 0.2
# drawing an albedo map
while True:
simulated_map = draw_map(nside, albedo_mean, albedo_std,
whitenoise_relative_amp, length_scale)
if min(simulated_map) > 0 and max(simulated_map) < 1:
break
#
# # simulating a map that's all black everywhere except for one bright spot
#
for i in range(0, simulated_map.size):
if i == 100:
simulated_map[i] = 1.00
else:
simulated_map[i] = 0.000
hp.mollview(simulated_map, title='albedo', cmap='gist_gray')
# obtaining the lon and lat of this point
map = HEALPix(nside=nside, order='nested')
pt_lng, pt_lat = map.healpix_to_lonlat([100])
import healpy as hp
from exocartographer.gp_map import draw_map
# Map resolution
# The resolution is currently set to 1 (lowest) since we fit only only for the period
# With this resolution, get 12 pixels
# For the conversion between resolution and number of pixels, see exocartographer page on GitHub
sim_nside = 1
# Gaussian process properties with which the map is generated
# Those properties were kept the same as in the exocartographer tutorial
sim_wn_rel_amp = 0.02 # Relative amplitude of white noise
sim_length_scale = 30. * np.pi/180 # Length scale of the albedo features, in degrees
sim_albedo_mean = .5 # Mean albedo, set to 0.5 for convenience (lower for Earth)
sim_albedo_std = 0.25 # Standard deviation of albedo distribution
# Draw a simplified albedo map, constrained between 0 and 1
while True:
simulated_map = draw_map(sim_nside, sim_albedo_mean,
sim_albedo_std, sim_wn_rel_amp,
sim_length_scale)
if min(simulated_map) > 0 and max(simulated_map) < 1:
break
# Visualize the map; the color can be changed by changing cmap
hp.mollview(simulated_map, min=0, max=1,
title='Simulated Albedo Map', cmap='gist_gray')
# Save the albedo map in a csv file
np.savetxt('sim_map.csv', simulated_map, delimiter=',')