def print_for_galstar(ra_dec, mags, errs, params):
N = len(ra_dec)
# Determine mean l, b
avg_l, avg_b = 0., 0.
for i in range(N):
l,b = equatorial2galactic(ra_dec[i][0], ra_dec[i][1])
avg_l += l
avg_b += b
avg_l /= N
avg_b /= N
outtxt = '%.3f\t%.3f' % (avg_l, avg_b)
truth = ''
count = 0
for i,m in enumerate(mags):
print_line = True
line = '\n'
truthline = ''
for j,m_X in enumerate(m):
if m_X == float('inf'):
print_line = False
break
if j != 0:
line += '\t'
line += '%.3f' % m_X
if print_line:
for s in errs[i]:
line += '\t%.3f' % s
for p in params[i]:
truthline += '%f\t' % p
truthline = truthline.rstrip('\t') + '\n'
if print_line:
outtxt += line
truth += truthline
count += 1
outtxt += '\n'
return count, outtxt, truth
def main():
parser = argparse.ArgumentParser(prog='plot_prior.py',
description='Plot galstar priors along a line of sight',
add_help=True)
parser.add_argument('RA',
type=str, help='Right Ascension (hh:mm:ss) or degrees')
parser.add_argument('DEC',
type=str, help='Declination (deg:mm:ss) or degrees')
parser.add_argument('Radius',
type=str,
nargs='?',
default="'1d'",
help='Radius (hh:mm:ss) or degrees')
parser.add_argument('--lb',
action='store_true',
help='Interpret RA and DEC as Galactic l and b, respectively')
parser.add_argument('--correct',
action='store_true',
help='Correct for Malmquist bias.')
#parser.add_argument('--density', action='store_true', help='Plot stellar number density rather than p(mu)')
parser.add_argument('--output',
type=str,
default=None,
help='Save output to file (default: open window with output)')
if sys.argv[0] == 'python':
offset = 2
else:
offset = 1
args = []
for arg in sys.argv[offset:]:
args.append(arg)
if '--' not in arg: args[-1] = "'%s'" % args[-1]
values = parser.parse_args(args)
# Get Galactic coordinates
if values.lb:
l = float(values.RA[1:-1])
b = float(values.DEC[1:-1])
else:
# Parse RA and DEC
RA = parse_dhms(values.RA[1:-1])
if RA == None: RA = parse_RA(values.RA[1:-1])
DEC = parse_dhms(values.DEC[1:-1])
if DEC == None: DEC = parse_DEC(values.DEC[1:-1])
l, b = equatorial2galactic(RA, DEC)
# Parse Radius
radius = parse_dhms(values.Radius[1:-1])
if radius == None: radius = float(values.Radius[1:-1])
radius = deg2rad(radius)
print '# Galactic Coordinates (l, b): %d %d' % (round(l) , round(b))
# Set up figure
mplib.rc('text',usetex=True)
mplib.rc('xtick.major', size=6)
mplib.rc('xtick.minor', size=4)
mplib.rc('axes', grid=True)
fig = plt.figure(figsize=(8.5, 11.))
fig.suptitle(r'$\mathrm{Priors \ for} \ ( \ell = %d^{\circ} , \, b = %d^{\circ} )$' % (round(l) , round(b)), fontsize=24, y=0.97)
ax = []
for i in range(2):
ax.append(fig.add_subplot(2, 1, i+1))
#fig.subplots_adjust(left=0.12, right=0.90, hspace=0.25)
fig.subplots_adjust(left=0.14, right=0.90, top=0.88, bottom=0.08, hspace=0.20)
# Intialize Galactic model
model = TGalacticModel(fh=0.0030)
model.L_epsilon = 500.
# Precompute trigonometric functions
l, b = deg2rad(l), deg2rad(b)
cos_l, sin_l, cos_b, sin_b = cos(l), sin(l), cos(b), sin(b)
# Determine total number of stars along line of sight
f_disk = lambda x: model.dn_dDM(x, cos_l, sin_l, cos_b, sin_b,
radius, component='disk',
correct=values.correct)
N_disk = quad(f_disk, 0.01, 20., epsrel=1.e-5)[0]
print '# of stars in disk: %d' % int(N_disk)
f_halo = lambda x: model.dn_dDM(x, cos_l, sin_l, cos_b, sin_b,
radius, component='halo',
correct=values.correct)
N_halo = quad(f_halo, 0.01, 40., epsrel=1.e-5)[0]
print '# of stars in halo: %d' % int(N_halo)
f_bulge = lambda x: model.dn_dDM(x, cos_l, sin_l, cos_b, sin_b,
radius, component='bulge',
correct=values.correct)
N_bulge = quad(f_bulge, 0.01, 40., epsrel=1.e-5)[0]
print '# of stars in bulge: %d' % int(N_bulge)
# Calculate dn/dDM and rho
DM_range = np.linspace(4., 20., 500)
dn_dDM_disk, dn_dDM_halo, dn_dDM_bulge = [np.empty(500, dtype='f8') for i in xrange(3)]
rho_disk, rho_halo, rho_bulge = [np.empty(500, dtype='f8') for i in xrange(3)]
for i,DM in enumerate(DM_range):
rho_halo[i] = model.rho(DM, cos_l, sin_l, cos_b, sin_b, component='halo')
rho_disk[i] = model.rho(DM, cos_l, sin_l, cos_b, sin_b, component='disk')
rho_bulge[i] = model.rho(DM, cos_l, sin_l, cos_b, sin_b, component='bulge')
dn_dDM_halo[i] = 1./(N_halo+N_disk+N_bulge) * model.dn_dDM(DM,
cos_l, sin_l,
cos_b, sin_b,
radius, component='halo',
correct=values.correct)
dn_dDM_disk[i] = 1./(N_halo+N_disk+N_bulge) * model.dn_dDM(DM,
cos_l, sin_l,
cos_b, sin_b,
radius, component='disk',
correct=values.correct)
dn_dDM_bulge[i] = 1./(N_halo+N_disk+N_bulge) * model.dn_dDM(DM,
cos_l, sin_l,
cos_b, sin_b,
radius, component='bulge',
correct=values.correct)
rho_bulge[~np.isfinite(rho_bulge)] = 0.
dn_dDM_bulge[~np.isfinite(dn_dDM_bulge)] = 0.
print np.sum(dn_dDM_bulge)
rho = rho_disk + rho_halo + rho_bulge
dn_dDM = dn_dDM_halo + dn_dDM_disk + dn_dDM_bulge
# Plot dn/dDM
y_min = min(dn_dDM_disk.min(), dn_dDM_halo.min())
ax[0].fill_between(DM_range, y_min, dn_dDM, alpha=0.4, facecolor='k', label='__nolabel__')
ax[0].fill_between(DM_range, y_min, dn_dDM_disk, alpha=0.4, facecolor='g')
rect = Rectangle((0,0), 0, 0, facecolor='g', label=r'$\mathrm{disk}$', alpha=0.6)
ax[0].add_patch(rect)
ax[0].fill_between(DM_range, y_min, dn_dDM_halo, alpha=0.4, facecolor='b')
rect = Rectangle((0,0), 0, 0, facecolor='b', label=r'$\mathrm{halo}$', alpha=0.6)
ax[0].add_patch(rect)
ax[0].fill_between(DM_range, y_min, dn_dDM_bulge, alpha=0.4, facecolor='r')
rect = Rectangle((0,0), 0, 0, facecolor='r', label=r'$\mathrm{bulge}$', alpha=0.6)
ax[0].add_patch(rect)
ax[0].set_title(r'$\mathrm{Probability}$', fontsize=20)
ax[0].set_xlabel(r'$\mu$', fontsize=20)
ax[0].set_ylabel(r'$p(\mu)$', fontsize=18)
ax[0].yaxis.set_major_locator(MaxNLocator(nbins=5))
ax[0].yaxis.set_minor_locator(MaxNLocator(nbins=20))
y_max = ax[0].get_ylim()[1]
ax[0].set_ylim(0., y_max)
ax[0].legend(loc='upper left')
ax[0].get_legend().get_frame().set_alpha(0.)
# Plot rho
y_min = min(dn_dDM_disk.min(), dn_dDM_halo.min())
ax[1].fill_between(DM_range, y_min, rho, alpha=0.4, facecolor='k')
ax[1].fill_between(DM_range, y_min, rho_disk, alpha=0.4, facecolor='g')
ax[1].fill_between(DM_range, y_min, rho_halo, alpha=0.4, facecolor='b')
ax[1].fill_between(DM_range, y_min, rho_bulge, alpha=0.4, facecolor='r')
ax[1].set_title(r'$\mathrm{Density}$', fontsize=20)
ax[1].set_xlabel(r'$\mu$', fontsize=20)
ax[1].set_ylabel(r'$n (\mu)$', fontsize=18)
ax[1].set_yscale('log')
y_min = max(dn_dDM_disk.min(), dn_dDM_halo.min())
y_max = ax[1].get_ylim()[1]
ax[1].set_ylim(y_min, y_max)
'''
# dn/dFeH
FeH_range = np.linspace(-2.5, 0.5, 100)
p_FeH_range = np.empty(100, dtype=float)
for i,FeH in enumerate(FeH_range):
p_FeH_range[i] = model.p_FeH_los(FeH, cos_l, sin_l, cos_b, sin_b, DM_max=20.)
func = lambda x: model.p_FeH_los(x, cos_l, sin_l, cos_b, sin_b, DM_max=20.)
norm = quad(func, -2.5, 0.5, epsrel=1.e-3)[0]
for i in range(len(FeH_range)): FeH_range[i] /= norm
ax[1].fill_between(FeH_range, 0, p_FeH_range, alpha=0.8)
ax[1].set_xlabel(r'$[Fe/H]$', fontsize=17)
ax[1].set_ylabel(r'$p([Fe/H])$', fontsize=16)
y_max = ax[1].get_ylim()[1]
ax[1].set_ylim(0., y_max)
ax[1].set_xlim(-2.5, 0.5)
ax[1].xaxis.set_major_locator(MaxNLocator(nbins=4, prune='lower'))
ax[1].xaxis.set_minor_locator(MaxNLocator(nbins=20))
'''
for ax_i in ax:
ax_i.set_xlim(4., 20.)
ax_i.xaxis.set_major_locator(MultipleLocator(4.))
ax_i.xaxis.set_minor_locator(MultipleLocator(1.))
#for tick in ax_i.xaxis.get_major_ticks() + ax_i.xaxis.get_minor_ticks() + ax_i.yaxis.get_major_ticks() + ax_i.yaxis.get_minor_ticks():
# tick.tick2On = False
ax_i.grid(which='minor', alpha=0.3)
if values.output == None:
plt.show()
else:
fn = values.output[1:-1]
if '.' not in fn: fn += '.png'
fig.savefig(fn, dpi=300)
return 0
