def compare_gmd(dict, folder, include_met=False):
'''
Compare mass calculated from Prospector with mass calculated from FAST
:param dict: dictionary, with mass calculated from FAST (output of get_fast() function)
:param folder: output folder in which Prospector output of relevant galaxies are stored
:return: mass_diff, which is a dictionary with the FAST mass, Prospector mass stored for each object
'''
exists = []
out = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/out/' + folder
for thing in os.listdir(out):
if thing.endswith(".h5"):
exists.append(thing)
### NEW COMP
mass_diff = {}
met_dict = {}
dust_dict = {}
count = 0
for thing in exists:
for key in dict:
if thing.startswith(key):
get = gmd.printer(out + thing)
mass_diff[key] = [dict[key][1], get[0]]
dust_dict = get[1]
met_dict[key] = get[2]
print(count)
if include_met:
return mass_diff, met_dict # , dust_dict
else:
return mass_diff # mass_diff[key][0] is the FAST mass, mass_diff[key][1] is the Prospector mass
# GET FAST MASS
with open(mass) as tm:
for line in tm:
if line[0] != '#':
cols = line.split()
print(cols[0], str(fc_ob))
if cols[0] == str(fc_ob):
fast_mass = cols[2]
print(fast_mass)
# GET PROSP MASS
out = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/out/' + out_fold
for plop in os.listdir(out):
if plop.startswith(str(
eelg_objs[i])) and plop.endswith(".h5"):
get = gmd.printer(out + plop)
prosp_mass = get[0]
print(prosp_mass)
print('these!')
print(fast_file)
with open(fast_file, 'r') as ffile:
wls = []
flx = []
for line in ffile:
if line[0] != '#':
cols = line.split()
wls.append(float(cols[0]) / (1 + red))
# 1 Jy = 10-23 erg s-1 cm-2 Hz-1 --> erg * 10^-19
# so 1 erg s-1 cm-2 Hz-1 = 10^23 Jy
# so 10^-19 erg s-1 cm-2 Hz-1 = 10^4 Jy
# ergs
if file.endswith(".h5"):
eelgs1.append(file)
sfgs1 = []
for file in os.listdir(l_out):
if file.endswith(".h5"):
sfgs1.append(file)
for glxy in eelgs:
c += 1
print(c)
# file = glxy[0] + '_' + glxy[1] + '_' + glxy[2] + '_extra_out.pkl'
file = pkls + glxy + '_extra_out.pkl'
if os.path.exists(file):
for mfile in eelgs1:
if mfile.startswith(glxy):
use_mfile = mfile
get_e = gmd.printer(out + use_mfile, percs=False, quiet=True)
nummy += 1
# temp = randraw(file) # temp[0] lists num=1000 random posterior samples; temp[1] = time vector
temp = randraw(
file, get_e[np.random.randint(len(get_e))], num=n_samps
) # temp[0] lists num=1000 random posterior samples; temp[1] = time vector
# temp = bootdraw(file) # temp[0] lists num=1000 random posterior samples; temp[1] = time vector
draws.append(temp[0]) # append random draw of ssfr
# boots.append(bootstrap(temp[0]))
t1.append(temp[1])
print(len(temp[0])) # 22, 1000
else:
print(file)
lfile_loc = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/sfg_ssfrs'
for glxy in lbgs:
pklsf = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/' + pkls[
1]
for file in os.listdir(outl):
if file.endswith(".h5"):
fasts.append(file)
# get_e = np.zeros(shape=(4, len(gals))) # 4 rows (dust, mass, gaslogz, logzsol), each row as long as eelgs
onedraw = np.zeros(shape=(4, len(gals), 10**3)) # *10**3))
onedrawf = np.zeros(shape=(4, len(fasts), 10**3)) # *10**3))
for i in range(len(gals)):
if os.path.exists(oute + gals[i]):
# print('reg', printer(oute + gals[i]))
# print('fast', printer(outl + fasts[i], percs=False, fast=True))
onedraw[:, i, :] = gmd.printer(oute + gals[i],
percs=False,
draw1=True)
onedrawf[:, i, :] = gmd.printer(outl + fasts[i],
percs=False,
fast=True,
draw1=True)
# for k in range(10**3):
glxy = gnames[i]
# fgal = fnames[i]
file = pkls + glxy + '_extra_out.pkl'
# ffile = pklsf + fgal + '_extra_out.pkl'
print(i)
randomdraws = sfh.randraw(
file, onedraw[0, i, np.random.randint(10**3)])[0] # size 22, num
# note: above random randint chooses a random value of mass for galaxy
print(time, 'time')
frac = np.zeros(shape=(len(eelgs), 10**3))
s_frac = frac
frac2 = np.zeros(shape=(len(eelgs), 10**3))
frac100 = np.zeros(shape=(len(eelgs), 10**3))
regs = np.zeros(shape=(len(eelgs), 10**3))
frac_l = np.zeros(shape=(len(lbgs), 10**3))
if write:
eel_file = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/eelg_fracs.txt'
sfg_file = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/sfg_fracs.txt'
with open(eel_file, 'w+') as write_eel:
write_eel.write('# ID SSFR\n\n')
for i in range(len(eelgs)):
print(i)
get_e = gmd.printer(out + eelgs1[i], percs=False)
for k in range(10**3):
# print((get_e[np.random.randint(len(get_e))]))
# print(sfh[i][np.random.randint(len(sfh[i]))])
regs[i, k] = np.percentile(sfh[i], [16., 50., 84.])[1] * time / \
(10 ** np.percentile(get_e, [16., 50., 84.])[1])
s_frac[i, k] = sfh[i][np.random.randint(len(sfh[i]))]
frac[i,
k] = sfh[i][np.random.randint(len(sfh[i]))] * time / (
10**get_e[np.random.randint(len(get_e))])
frac2[i, k] = second[i][np.random.randint(len(second[i]))] * time / \
(10 ** get_e[np.random.randint(len(get_e))])
frac100[i, k] = frac[i, k] + frac2[i, k]
print(np.percentile(s_frac[i], [16., 50., 84.]), 'sfr')
write_eel.write(
eelgs[i] + ' ' +
# for ind in range(len(allkeys)):
#offsets = np.zeros(shape=(80, 6)) # [mass, dust, metal, sfh1, sfh2, sfh1/sfh2]
#meds = np.zeros(shape=(80, 6)) # [mass, dust, metal, sfh1, sfh2, sfh1/sfh2]
offsets = np.zeros(
shape=(100, 6)) # [mass, dust, metal, sfh1, sfh2, sfh1/sfh2] # BUCKET
meds = np.zeros(
shape=(100, 6)) # [mass, dust, metal, sfh1, sfh2, sfh1/sfh2] # BUCKET
#for i in range(20, 100): # for each galaxy (0 through 99)
for i in range(100): # for each galaxy (0 through 99)
# i = allkeys[ind]
print(i, gals[str(i)]) # i = key
#j = i - 20 # BUCKET
if os.path.exists(oute + gals[str(i)]):
#onedraw[j, :, :] = gmd.printer(oute + gals[str(i)], percs=False, sfhtest=True, draw1=True)
onedraw[i, :, :] = gmd.printer(oute + gals[str(i)],
percs=False,
sfhtest=True,
draw1=True) # BUCKET
# pars = git + 'eetest/sfhtest_' + str(i) + '_params.py'
pars = git + 'new/sfhtest_' + str(i) + '_params.py'
#i = j # BUCKET
with open(pars, 'r') as parfile:
for line in parfile:
if line.startswith("# Codename: "):
spaces = 0
inmass, indust, inmet, insfr1, insfr2 = '', '', '', '', ''
for char in line:
if char == ' ' or char == '_':
spaces += 1
elif spaces == 2:
inmass += char
def printer(out_file, cvg=-1000, masstest=False, obj_true=None):
objname = ''
count = 0
field = ''
for i in kwargs['outname']:
if i == '_':
count += 1
elif count == 0:
objname += i
elif count == 1:
field += i
elif count == 2:
break
print(field)
res, pr, mod = bread.results_from(out_file)
# print(res['chain'], 'chain')
# ''' #
# PRINT TRACE SHOWING HOW ITERATIONS CONVERGE FOR EACH PARAMETER
bread.param_evol(res) # print tracefig
plt.show()
# plt.savefig('delete' + '_tracefig2.png', bbox_inches='tight')
# FIND WALKER, ITERATION THAT GIVE MAX (AND MIN) PROBABILITY
# print(prob)
prob = res['lnprobability'][..., cvg:]
print('max', prob.max())
row = prob.argmax() / len(prob[0])
col = prob.argmax() - row * len(prob[0])
walker, iteration = row, col
print(walker, iteration)
# ''' #
truths = None
print(objname)
if masstest:
print('hi?')
import get_mass_dust as gmd
oute = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/out/out_efico/'
for file in os.listdir(oute):
if file.endswith(".h5") and file.startswith(obj_true):
print(file, 'file')
params = gmd.printer(oute + file, percs=False, masstest=True)
mass = params[0]
dust = params[6]
met = params[7]
gasmet = params[8]
sfh = []
for i in [1, 2, 3, 4, 5]:
sfh.append(params[i])
truths = [np.log10(10**mass + 6.5*10**8), sfh[0], sfh[1], sfh[2], sfh[3], sfh[4], dust, met, gasmet]
# PRINT CORNERFIG CONTOURS/HISTOGRAMS FOR EACH PARAMETER
# truths now corrected for masses of efico output + 6.5e8
# truths = [9.466 + 6.5e8, 0.22, 0.12, 0.22, 0.12, 0.1, 0.0737, -1.79, -0.33] # 12552
# truths = [9.83 + 6.5e8, 0.43, 0.08, 0.04, 0.12, 0.1, 0.32, -1.57, -0.35] # 12105
# truths = [9.51 + 6.5e8, 0.80, 0.02, 0.01, 0.04, 0.04, 0.54, -1.94, -0.31] # 21442
print(truths)
bread.subtriangle(res, start=cvg, thin=5, truths=truths, show_titles=True) # set start by when kl converges!
plt.show()
# plt.savefig('delete' + '_ctracefig2.png', bbox_inches='tight')
# For FAST: truths = [mass, age, tau, dust2] (for 1824: [9.78, 0.25, -1., 0.00])
return objname, field, res, mod, walker, iteration
def load_model(objname, field, agelims=[], **extras):
# REDSHIFT
# open file, load data
photname, zname, filtername, filts = get_names(field)
with open(photname, 'r') as f:
hdr = f.readline().split()
dtype = np.dtype([(hdr[1], 'S20')] + [(n, np.float) for n in hdr[2:]])
dat = np.loadtxt(photname, comments='#', delimiter=' ', dtype=dtype)
with open(zname, 'r') as fz:
hdr_z = fz.readline().split()
dtype_z = np.dtype([(hdr_z[1], 'S20')] + [(n, np.float) for n in hdr_z[2:]])
zout = np.loadtxt(zname, comments='#', delimiter=' ', dtype=dtype_z)
idx = dat['id'] == objname # creates array of True/False: True when dat[id] = objname
# zred = zout['z_spec'][idx][0] # use z_spec
# if zred == -99: # if z_spec doesn't exist
# zred = zout['z_peak'][idx][0] # use z_phot
zred = 3.5
print(zred, 'zred')
# CALCULATE AGE OF THE UNIVERSE (TUNIV) AT REDSHIFT ZRED
tuniv = WMAP9.age(zred).value
print(tuniv, 'tuniv')
n = [p['name'] for p in model_params]
# model_params[n.index('tage')]['prior_args']['maxi'] = tuniv
# NONPARAMETRIC SFH # NEW
'''
agelims = [0.0, 8.0, 8.7, 9.0, (9.0 + (np.log10(tuniv*1e9) - 9.0)/3), (9.0 + 2 * (np.log10(tuniv*1e9) - 9.0)/3),
np.log10(tuniv*1e9)]
'''
agelims = [0.0, 7.7, 8.0, 9.0, (9.0 + (np.log10(tuniv*1e9) - 9.0)/3), (9.0 + 2 * (np.log10(tuniv*1e9) - 9.0)/3),
np.log10(tuniv*1e9)]
ncomp = len(agelims) - 1
agebins = np.array([agelims[:-1], agelims[1:]]) # why agelims[1:] instead of agelims[0:]?
# print(agebins, 'grab these agebins')
# INSERT REDSHIFT INTO MODEL PARAMETER DICTIONARY
zind = n.index('zred')
model_params[zind]['init'] = zred
# model_params[n.index('tage')]['init'] = tuniv # set tage to the age of the Universe
# set dust and metallicity to be the same dust and metallicity you find in the actual fits:
get_out = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/out/out_efico/'
for plop in os.listdir(get_out):
if plop.startswith(str(objname)) and plop.endswith(".h5"):
# print(str(objname))
get = gmd.printer(get_out + plop) # [mass, dust, metal, gasmet]
model_params[n.index('logmass')]['init'] = 9.9 # 9. # get[0]
model_params[n.index('dust2')]['init'] = 0.3 # get[1]
model_params[n.index('logzsol')]['init'] = -0.06 # -1.7 # get[2]
model_params[n.index('gas_logz')]['init'] = get[3]
# SET UP AGEBINS
model_params[n.index('agebins')]['N'] = ncomp
model_params[n.index('agebins')]['init'] = agebins.T
# FRACTIONAL MASS INITIALIZATION # NEW
# N-1 bins, last is set by x = 1 - np.sum(sfr_fraction)
model_params[n.index('sfr_fraction')]['N'] = ncomp-1
model_params[n.index('sfr_fraction')]['prior_args'] = {
'maxi': np.full(ncomp-1, 1.0),
'mini': np.full(ncomp-1, 0.0),
# NOTE: ncomp instead of ncomp-1 makes the prior take into
# account the implicit Nth variable too
}
eelg_frac1 = 0.3 # mfrac in most recent bin
eelg_frac2 = 0.05 # mfrac in second most recent bin
sf_inits = np.zeros(ncomp-1)+(1.-(eelg_frac1 + eelg_frac2))/(ncomp-2.)
sf_inits[0] = eelg_frac1
sf_inits[1] = eelg_frac2
# print(sf_inits, 'look at me!!!')
model_params[n.index('sfr_fraction')]['init'] = sf_inits # np.zeros(ncomp-1)+1./ncomp
model_params[n.index('sfr_fraction')]['init_disp'] = 0.02
# CREATE MODEL
model = BurstyModel(model_params)
print('model')
# print(model_params)
# print(model_params[n.index('sfr_fraction')])
return model
def preplot(order=None,
keys='e',
file=None,
line_idx=5,
line_idx2=[5, 3],
ratio=[False, False],
outfold=None,
fs_text=30,
fs=20,
color='purple',
font={'fontname': 'Times'},
types=False):
'''
:param keys:
:param files:
:param line_idx: single idx for desired line flux or EW, OR [idx1, idx2] for desired line ratios
:param line_idx2: (if no ssfr) single idx for desired line flux or EW, OR [idx1, idx2] for desired line ratios
:param ratio:
:param fs_text:
:param fs:
:param font:
:return:
'''
lines = [
'[NII]6585', '[OII]3726', r'H$\alpha$6563', '[OII]3729', '[OIII]4960',
'[OIII]5007', r'H$\beta$4861', r'H$\delta$4102'
]
# names = '[NII]6585', '[OII]3726', 'Halpha6563', '[OII]3729', '[OIII]4960', '[OIII]5007', 'Hbeta4861', 'Hdelta4102'
if keys != 's':
ew, ew_order = list_ewflux(file, line_idx=line_idx,
ratio=ratio[0]) # line1
# xy[1] = list_ewflux(files[1], line_idx=line_idx2, ratio=ratio[1]) # line2
labels = [
r'Stellar Mass [$\log_{10}(\textrm{M} / \textrm{M}_\odot$)]',
lines[line_idx] + r' Equivalent Width [\AA]'
]
# labels[1] = lines[line_idx2[0]] + '/' + lines[line_idx2[1]]
else: # want ssfr
ew = list_ssfr(file) # ssfr
labels = [
r'Stellar Mass [log_{10}(M / M$_\odot$)]', 'SSFR [Gyr$^{-1}$]'
]
out = outfold
gals1 = []
for file in os.listdir(out):
if file.endswith(".h5"):
gals1.append(file)
gals = []
relevent_idcs = []
for ln in range(len(order)):
for id in range(len(gals1)):
if gals1[id].startswith(str(order[ln])):
if order[ln] == 11462 or order[ln] == 21076 or order[
ln] == 21442:
relevent_idcs.append(ln)
gals.append(gals1[id])
# print('1', gals) # print('2', order) # print('3', ew_order) # yay is good!
mass = []
for i in range(len(gals)):
mass.append(gmd.printer(out + gals[i], percs=True)[0]) # median mass
if types:
return ew, mass, labels, relevent_idcs
else:
return ew, mass, labels
def return_fracs(gals,
order,
pklfolder='pkl_efico/',
outfold='out_efico/',
base='fico',
ls=False):
import ssfr_now as sfnow
eelgs, lbgs1 = sa.get_gal_lists(base=[base, base], normal=True)
git = '/home/jonathan/.conda/envs/snowflakes/lib/python2.7/site-packages/prospector/git/'
out = git + 'out/' + outfold
f_folder = git + pklfolder
gals1 = gals
if ls:
gals1 = []
for i in range(len(lbgs1)):
file = f_folder + lbgs1[i] + '_extra_out.pkl'
if os.path.exists(file):
for ga in gals:
print(str(ga))
if file.startswith(f_folder + str(ga)):
gals1.append(lbgs1[i])
# print(lbgs1)
print(len(gals1), 'look')
'''
ordered = []
for go in range(len(order)):
for ga in range(len(gals1)):
if gals1[ga].startswith(order[go]):
ordered.append(gals1[ga])
'''
ordered = gals1
time = 0.5 * 10**8
sfh = []
highfracs = []
# print('masses', masses)
frac = np.zeros(shape=(len(ordered), 10**3))
for ord in range(len(ordered)):
# print(ordered[ord])
# file = f_folder + str(glxy) + '*_extra_out.pkl'
for pkls in os.listdir(f_folder):
if pkls.startswith(str(
ordered[ord])) and pkls.endswith('_extra_out.pkl'):
file = f_folder + pkls
sfh.append(sfnow.get_sfh(file)[0]) # 1st bin
# for i in range(len(ordered)):
# print(ord)
file_i = None
for outs in os.listdir(out):
if outs.startswith(str(ordered[ord])) and outs.endswith('.h5'):
file_i = out + outs
get_e = gmd.printer(file_i, percs=False, quiet=True)
for k in range(10**3):
frac[ord, k] = sfh[ord][np.random.randint(len(
sfh[ord]))] * time / (10**get_e[np.random.randint(len(get_e))])
# print(frac)
all_true = []
for fr in range(len(frac)):
for k in range(10**3):
all_true.append(frac[fr, k])
# print(all_fracs)
return np.percentile(all_true, [16., 50., 84.])
def mass_match_plot(x1,
y1,
color,
order,
lims=[9.5, 10.],
errs=True,
outfold=None,
ssfr_file=None,
fs_text=30,
fs=20,
font={'fontname': 'Times'}):
x = []
y = []
do_these = []
for i in range(len(x1)):
if lims[0] <= x1[i] <= lims[1]: # 9.55 <= x1[i] <= 9.9:
do_these.append(order[i])
x.append(x1[i])
y.append(y1[i])
plt.scatter(x=x, y=y, color=color, s=fs * 2)
if errs:
'''
errx = np.percentile(x, [16., 50., 84.])
erry = np.percentile(y, [16., 50., 84.])
plt.errorbar(x=[errx[1]], y=[erry[1]], xerr=[[errx[1] - errx[0]], [errx[2] - errx[1]]],
yerr=[[erry[1] - erry[0]], [erry[2] - erry[1]]], color=color, fmt='*')
'''
X, Y, Z = density_estimation(x, y)
# levels = np.arange(0.5, np.amax(Z), 0.02) + 0.02
levels = np.arange(np.amax(Z) / 7., np.amax(Z),
np.amax(Z) / 7.) + (np.amax(Z) / 7.)
if color == 'b':
cmap = 'Blues'
else:
cmap = 'Purples'
plt.contourf(X, Y, Z, levels=levels, cmap=cmap,
alpha=0.5) # levels=levels # [0.1, 0.2, 0.5, 1., 25.]
out = outfold
gals1 = []
for file in os.listdir(out):
if file.endswith(".h5"):
gals1.append(file)
gals = []
for ln in range(len(do_these)):
for id in range(len(gals1)):
if gals1[id].startswith(str(do_these[ln])):
gals.append(gals1[id])
mass = []
dust = []
met = []
for i in range(len(gals)):
get = gmd.printer(out + gals[i],
percs=True) # median mass, dust, gasmet, metallicity
mass.append(get[0])
dust.append(get[1])
met.append(get[2])
ssfrs = []
counter = 0
with open(ssfr_file, 'r') as ssfr:
for line in ssfr:
print(line)
if line[0] != '#':
cols = line.split()
print(cols)
for dt in range(len(do_these)):
if cols[0].startswith(str(do_these[dt])):
ssfrs.append(
float(cols[1]) * 10**9
) # ssfrs are stored in 2nd column in file; convert to Gyr^-1
counter += 1
return mass, dust, met, ssfrs, do_these