def des_stream_min_depths(survey='LSST10', maglim=None):
if maglim is None:
maglim_g = mock_sim.getMagLimit('g', survey)
maglim_r = mock_sim.getMagLimit('r', survey)
else:
maglim_g, maglim_r = [maglim] * 2
depths = []
for stream in STREAMS.keys():
min_detectable_depth = min_gap_depth(
STREAMS[stream]['distance'], STREAMS[stream]['surface_brightness'],
STREAMS[stream]['width'], maglim_g, maglim_r, survey)
depths.append(min_detectable_depth)
print stream, min_detectable_depth
output = np.vstack([STREAMS.keys(), depths]).T
try:
np.savetxt('min_depths_%s.txt' % survey,
output,
delimiter=', ',
fmt='%s')
except:
print 'saving error'
return depths
def plot_output_distance(filename, mus=[30.], distances=[20.], velocities=[150.], impact_parameters=[1.], maglims=[None], latitudes=[60.], surveys=['LSST'], gap_fill=True):
output = np.genfromtxt('output.txt', unpack=True, delimiter=', ', dtype=None, names=['dist', 'w', 'b', 'maglim', 'lat', 'gap_fill', 'survey', 'mu', 'mass'], encoding='bytes')
plt.figure()
for survey in surveys:
for lat in latitudes:
for maglim in maglims:
for b in impact_parameters:
for w in velocities:
for mu in mus:
ret = []
if maglim == None:
maglim = mock_sim.getMagLimit('g', survey)
for distance in distances:
idx = (output['dist'] == distance) & (output['w'] == w) & (output['b'] == b) & (output['maglim'] == np.around(
maglim, 2)) & (output['survey'] == survey) & (output['gap_fill'] == gap_fill) & (output['mu'] == mu)
# print idx
mass = output['mass'][idx][0]
ret.append(mass)
try:
label = ''
if len(mus) > 1:
label += r'$ \mu = %d$' % mu # \ \mathrm{mag/arcsec^2}
if len(velocities) > 1:
label += r'$ w = %d \mathrm{km/s}$' % w
if len(impact_parameters) > 1:
label += r'$ b = %d \mathrm{r_s}$' % b
if len(maglims) > 1:
label += r'$\mathrm{ maglim =} %d$' % maglim
if len(latitudes) > 1:
label += r'$\mathrm{ lat = %d}$' % lat
if len(surveys) > 1:
label += r'$\mathrm{ %s}$' % survey
if label == '':
label = r'$\mathrm{mu=%d, w=%d, b=%d, mag=%d, lat=%d, %s}$' % (mu, w, b, maglim, lat, survey)
except:
label = r'$\mathrm{d=%d, w=%d, b=%d, mag=%d, lat=%d, %s}$' % (mu, w, b, maglim, lat, survey)
plt.semilogy(distances, ret, 'o-', label=label) # label='d = %d, w = %d, b = %d' % (distance, w, b)
plt.legend(loc='upper left', fontsize=10)
plt.title(r'$\mathrm{Minimum\ Detectable\ Halo\ Mass}$')
plt.xlabel(r'$\mathrm{Distance}\ \mathrm{(kpc)}$',)
plt.ylabel(r'$M_{\mathrm{halo}}\ \mathrm{(M_{\odot})}$',)
plt.tight_layout()
plt.savefig('%s.png' % filename)
def final_plot(filename=None,
mus=[30., 31., 32., 33.],
surveys=['SDSS', 'LSST10'],
w=150.,
b=1.,
maglim=None,
lat=60.,
gap_fill=True):
output = np.genfromtxt('output.txt',
unpack=True,
delimiter=', ',
dtype=None,
names=[
'dist', 'w', 'b', 'maglim', 'lat', 'gap_fill',
'survey', 'mu', 'mass'
],
encoding='bytes')
colors = ['cornflowerblue', 'seagreen', 'darkslateblue']
markers = ['s', 'o', 'd']
plt.figure()
for i, survey in enumerate(surveys):
maglim = mock_sim.getMagLimit('g', survey)
ret10 = []
ret20 = []
ret40 = []
for mu in mus:
idx = (output['w'] == w) & (output['b'] == b) & (
output['maglim'] == np.around(
maglim, 2)) & (output['survey'] == survey) & (
output['gap_fill'] == gap_fill) & (output['mu'] == mu)
idx10 = idx & (output['dist'] == 10)
idx20 = idx & (output['dist'] == 20)
idx40 = idx & (output['dist'] == 40)
mass10 = output['mass'][idx10][0]
mass20 = output['mass'][idx20][0]
mass40 = output['mass'][idx40][0]
ret10.append(mass10)
ret20.append(mass20)
ret40.append(mass40)
label = r'$\mathrm{%s}$' % survey
plt.semilogy(
mus,
ret20,
'o-',
label=label,
c=colors[i],
marker=markers[i],
zorder=1) # label='d = %d, w = %d, b = %d' % (distance, w, b)
plt.fill_between(mus,
ret10,
ret40,
alpha=0.2,
color=colors[i],
zorder=0)
plt.legend(loc='upper left', fontsize=12)
plt.ylabel(r'$M_{\mathrm{vir}}(z=0)\ \mathrm{(M_{\odot})}$', )
plt.xlabel(r'$\mu\ \mathrm{(mag/arcsec^2)}$', )
ax1 = plt.gca()
ax2 = ax1.twinx()
ax1.set_ylim(2e4, 2e11)
mn, mx = ax1.get_ylim()
ax2.set_ylim(mn, mx)
ax2.set_yscale('log')
ax2.minorticks_off()
ticks = ax1.get_yticks()
wdm = wdm_mass(np.asarray(ticks))
labels = [r'$%.1f$' % t for t in wdm]
ax2.set_yticklabels(labels)
ax2.set_ylabel(r'$m_{\mathrm{WDM}\ \mathrm{(keV)}}$')
mn2, mx2 = ax2.get_ylim()
ax2.fill_between([29.5, 33.5],
[halo_mass(2.95), halo_mass(2.95)], [3e8, 3e8],
facecolor='none',
edgecolor='k',
alpha=0.3,
hatch='/',
lw=2,
zorder=4) # MW satellite constraint
#plt.plot([29.5, 33.5], [halo_mass(2.95), halo_mass(2.95)], c='0.5', lw=2, linestyle='-')#, label=r'$\mathrm{MW\ satellites}$')
plt.text(30.45,
6e8,
r'$\mathrm{MW\ satellites}$',
horizontalalignment='center',
verticalalignment='center',
size=10,
bbox=dict(facecolor='white', alpha=1, edgecolor='none'),
zorder=-1)
plt.plot([29.5, 33.5], [halo_mass(5.30), halo_mass(5.30)],
c='0.5',
lw=2,
linestyle='-',
zorder=1) #, label=r'$\mathrm{Lyman}\ \alpha$')
plt.text(30.45,
halo_mass(5.30),
r'$\mathrm{Lyman}\ \alpha$',
horizontalalignment='center',
verticalalignment='center',
size=10,
bbox=dict(facecolor='white', alpha=1, ec='none'),
zorder=2)
#plt.plot([31.9,31.9], [mn2,mx2], c='0.5', lw=2, linestyle='--')#, label=r'$\mathrm{MW\ satellites}$')
#plt.plot([33.0,33.0], [mn2,mx2], c='0.5', lw=2, linestyle='--')#, label=r'$\mathrm{Lyman}\ \alpha$')
#plt.text(31,3e4,r'$\mathrm{GD-1}$',rotation=90., horizontalalignment='center', verticalalignment='bottom', size=10,bbox=dict(facecolor='white', alpha=0, ec='none'),zorder=-10)
plt.text(32,
3e4,
r'$\mathrm{Indus}$',
rotation=90.,
horizontalalignment='center',
verticalalignment='bottom',
size=10,
bbox=dict(facecolor='white', alpha=1, ec='none'),
zorder=-1)
plt.text(33,
3e4,
r'$\mathrm{ATLAS}$',
rotation=90.,
horizontalalignment='center',
verticalalignment='bottom',
size=10,
bbox=dict(facecolor='white', alpha=1, ec='none'),
zorder=-1)
plt.xlim(29.9, 33.1)
plt.title(r'$\mathrm{Minimum\ Detectable\ Halo\ Mass}$')
plt.tight_layout()
if filename is not None:
plt.savefig('%s.png' % filename)
plt.show()
def save_output(filename='output.txt',
mus=[30.],
distances=[20.],
velocities=[150.],
impact_parameters=[1.],
maglims=[None],
latitudes=[60.],
surveys=['LSST'],
gap_fill=True,
**kwargs):
if os.path.exists(filename):
pass
else:
output_file = open(filename, 'w')
output_file.write(
'# distance (kpc), flyby_velocity (km/s), impact_parameter (r_s), magnitude_limit (mag), latitude (deg), gap_fill (True/False), survey, surface_brightness (mag/arcsec^2), minimum_mass (M_sun)\n'
)
output_file.close()
output = np.genfromtxt(filename,
unpack=True,
delimiter=', ',
dtype=None,
names=[
'dist', 'w', 'b', 'maglim', 'lat', 'gap_fill',
'survey', 'mu', 'mass'
],
encoding='bytes')
for survey in surveys:
for lat in latitudes:
for maglim in maglims:
for b in impact_parameters:
for w in velocities:
for distance in distances:
ret = []
if maglim == None:
maglim_label = mock_sim.getMagLimit(
'g', survey)
else:
maglim_label = maglim
for mu in mus:
# print mu, distance, w, b, maglim, lat, survey
# check if output already saved for these params
try:
idx = (output['dist'] == distance) & (
output['w']
== w) & (output['b'] == b) & (
output['maglim'] == np.around(
maglim_label, 2)
) & (output['survey'] == survey) & (
output['gap_fill']
== gap_fill) & (output['mu'] == mu)
if np.sum(idx) > 0:
print 'Output exists'
continue
except:
pass
mockfile = '%d_deg_mock.fits' % lat
mass, gapt, gapo = mock_sim.predict_gap_depths(
mu,
distance,
survey,
width_pc=20,
maglim=maglim,
timpact=0.5,
gap_fill=gap_fill,
w=w,
X=b,
mockfile=mockfile,
**kwargs)
xind = np.isfinite(gapo / gapt)
try:
II1 = scipy.interpolate.UnivariateSpline(
np.log10(mass)[xind],
(gapo / gapt - 1)[xind],
s=0)
except:
print 'Spline error'
ret.append(np.nan)
continue
R = scipy.optimize.root(II1, 6)
ret.append(10**R['x'])
with open(filename, 'a') as output_file:
output_file.write(
'%.2f, %.2f, %.2f, %.2f, %.2f, %d, %s, %.2f, %.2f\n'
% (distance, w, b, maglim_label, lat,
gap_fill, survey, mu, ret[-1]))