def color_color_diagnostic(trilegal_output_file,
filter1,
filter2,
filter3,
filter4,
ax=None,
**pltkwargs):
print 'reading', trilegal_output_file
tstart = time.time()
t = read_table(trilegal_output_file)
tend = time.time()
print 'reading took %.2f seconds' % (tend - tstart)
#mag1 = np.array(t[filter1])
#mag2 = np.array(t[filter2])
#mag3 = np.array(t[filter3])
#mag4 = np.array(t[filter4])
mag1 = Table.get_col(t, filter1)
mag2 = Table.get_col(t, filter2)
mag3 = Table.get_col(t, filter3)
mag4 = Table.get_col(t, filter4)
if ax == None: ax = plt.axes()
ax.plot(np.array(mag1) - np.array(mag2),
np.array(mag3) - np.array(mag4),
',',
label=trilegal_output_file,
**pltkwargs)
ax.set_ylabel('$%s-%s$' % (filter1, filter2))
ax.set_xlabel('$%s-%s$' % (filter3, filter4))
return ax
def reddening_vector(Filter1, Filter2, camera, Rv, Teff=15000):
'''
wfc3uvis data from Leo: TABLE_DIR+'extinction_coeff.dat'
'''
R = [0]
if camera == 'wfc3uvis':
try:
ec = read_table(TABLE_DIR + 'tables/extinction_coeff.dat')
except NameError:
from GenUtils import read_table
ec = read_table(TABLE_DIR + 'extinction_coeff.dat')
Teffs = ec.get_col('Teff')
Rvs = ec.get_col('Rv')
A1s = ec.get_col('A(' + Filter1 + ')')
A2s = ec.get_col('A(' + Filter2 + ')')
pick = np.nonzero((Rvs == Rv) & (Teffs == Teff))[0]
A1 = A1s[pick]
A2 = A2s[pick]
R = A2 / (A1 - A2)
else:
print 'A_i/A_V information only for wfc3uvis.'
return R[0]
def reddening_vector(Filter1,Filter2,camera,Rv,Teff=15000):
'''
wfc3uvis data from Leo: TABLE_DIR+'extinction_coeff.dat'
'''
R = [0]
if camera == 'wfc3uvis':
try:
ec = read_table(TABLE_DIR+'tables/extinction_coeff.dat')
except NameError:
from GenUtils import read_table
ec = read_table(TABLE_DIR+'extinction_coeff.dat')
Teffs = ec.get_col('Teff')
Rvs = ec.get_col('Rv')
A1s = ec.get_col('A('+Filter1+')')
A2s = ec.get_col('A('+Filter2+')')
pick = np.nonzero((Rvs == Rv) & (Teffs == Teff))[0]
A1 = A1s[pick]
A2 = A2s[pick]
R = A2/(A1-A2)
else:
print 'A_i/A_V information only for wfc3uvis.'
return R[0]
def color_color_diagnostic(trilegal_output_file,filter1,filter2,filter3,filter4,ax=None,**pltkwargs):
print 'reading',trilegal_output_file
tstart = time.time()
t = read_table(trilegal_output_file)
tend = time.time()
print 'reading took %.2f seconds'%(tend-tstart)
#mag1 = np.array(t[filter1])
#mag2 = np.array(t[filter2])
#mag3 = np.array(t[filter3])
#mag4 = np.array(t[filter4])
mag1 = Table.get_col(t,filter1)
mag2 = Table.get_col(t,filter2)
mag3 = Table.get_col(t,filter3)
mag4 = Table.get_col(t,filter4)
if ax == None: ax = plt.axes()
ax.plot(np.array(mag1)-np.array(mag2),np.array(mag3)-np.array(mag4),',',label=trilegal_output_file,**pltkwargs)
ax.set_ylabel('$%s-%s$'%(filter1,filter2))
ax.set_xlabel('$%s-%s$'%(filter3,filter4))
return ax
def mc_tests(ID, dir_name, outdir="MC_TESTS", bestfit_loc="MODELS/"):
'''
ID is the Galaxy name
dir_name is PropID_GalaxyName
Will put mc tests in MC_TESTS/*/dirname
'''
# Make new folders
folders = ['PARS/', 'INPUT/', 'OUTPUT/']
outdir = check_mkdir(outdir)
dummy = [check_mkdir(os.path.join(outdir, folder)) for folder in folders]
this_outdir = check_mkdir(os.path.join(outdir, folder, dir_name))
# A place to write the commands if this needs to be run again
cmds_out = check_mkdir(os.path.join(outdir, 'MC_COMMANDS/'))
cmds_file = open('%s/%s_MC_commands.dat' % (cmds_out, ID), 'r')
# Place for the output table
table_out = check_mkdir(os.path.join(outdir, 'TABLES/'))
out = open('%s/%s_MC.dat' % (table_out, ID), 'w')
out.write(
'# mc_ID p_value NRGB_data NAGB_data NRGB_model NAGB_model mass_model N_wind Flux1_wind Flux2_wind\n'
)
#best fits: bfs[0] = pars for run_trilegal, bfs[1] = input for trilegal bfs[2] = output for trilegal
bfs = [
get_afile(bestfit_loc + folder, '*' + ID + '*')[0]
for folder in folders
]
# find model from file!!! This is not general! !
model = bfs[-1].split('model_')[-1].replace('.dat.dat', '.dat')
# Switch to the MC test directories
new_place = [
bf.replace(bestfit_loc, 'MC_TESTS/').replace(folder,
folder + dir_name + '/')
for bf in bfs
]
# Best fit pars is the template, we'll swap out sfh file
in_pars = open(bfs[0]).readlines()
# Load SFHs
sfhs = get_afile(mc_dir + '/', 'SFR*mc*dat')
for i, sfh in enumerate(sfhs):
mcid = sfh.split('/')[-1].split('.')[1] # need to change jason/me
new_names = [
np.replace(ext, '.' + mcid + ext)
for np, ext in zip(new_place, ['.pars', '.dat', '.dat.dat'])
]
# New pars file for run_trilgal.py
pfile = open(new_names[0], 'w')
[pfile.write(inpar)
for inpar in in_pars[:-1]] #sfh line is at the bottom.
pfile.write("%-18s %s\n" % ('object_sfr ', sfh))
pfile.close()
cmd = "/Users/Phil/research/Italy/WXTRILEGAL/run_trilegal.py "
#cmd="/home/philrose/WXTRILEGAL/run_trilegal.py "
cmd += "-e code_2.0/main "
cmd += "-a "
cmd += "-i %s " % new_names[1]
cmd += "-o %s " % new_names[2]
cmd += "-f %s " % model
cmd += new_names[0]
cmds_file.write('%s \n' % cmd)
print 'running TRILEGAL:', model, ID
p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)
p = subprocess.Popen(cmd, shell=True)
sts = os.waitpid(p.pid, 0)[1]
fak_file = get_fakFILE(ID, jason=jason)
ast_file = new_names[2].split('/')[0] + '/ast_' + new_names[2].split(
'/')[-1]
cmd = "AST/code/spread_angst <<EOF \n"
cmd += fak_file + "\n"
cmd += new_names[2] + "\n"
cmd += ast_file + "\n"
cmd += "EOF \n"
print " ... completeness using %s" % fak_file
print " %s -> %s" % (new_names[2], ast_file)
print 'Running spread_angst...'
p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)
sts = os.waitpid(p.pid, 0)[1]
os.system("wc -l %s %s|head -2" % (new_names[2], ast_file))
cmds_file.write('%s \n' % cmd)
synthcmd = read_table(ast_file)
s_mag2 = synthcmd.get_col('mag2') + synthcmd.get_col(
'diff_mag2'.strip())
s_mag2 = s_mag2[np.nonzero(
abs(synthcmd.get_col('diff_mag2'.strip())) < 90.)[0]]
s_mag1 = synthcmd.get_col('mag1') + synthcmd.get_col(
'diff_mag1'.strip())
s_mag1 = s_mag1[np.nonzero(
abs(synthcmd.get_col('diff_mag1'.strip())) < 90.)[0]]
s_color = s_mag1 - s_mag2
Norm = trgb + 1.5
ind, nB_AGB, nNorm, ps_nNorm, ps_nB_AGBm, hist, bins, s_hist_normed, p_value, normalization = calc_LF(
mag2, s_mag2, Norm, trgb)
Nstars, flux_rates = flux_from_mass_loss(synthcmd,
rates, [filt1, filt2],
ast_inds=ind,
rel_flux=True)
out.write(
'# mc_ID p_value NRGB_data NAGB_data NRGB_model NAGB_model mass_model N_wind Flux1_wind Flux2_wind\n'
)
out.write('%s %.3f %i %i %i %i %e %i %e %e \n' %
(mcid, p_value, nNorm, nB_AGB, ps_nNorm, ps_nB_AGBm,
object_mass, Nstars[0], flux_rates[0][1], flux_rates[1][0]))
os.remove(ast_file)
print 'deleted', ast_file
os.remove(new_names[2])
print 'deleted', new_names[2]
out.close()
cmds_file.close()
def mc_tests(ID,dir_name,outdir="MC_TESTS",bestfit_loc = "MODELS/"):
'''
ID is the Galaxy name
dir_name is PropID_GalaxyName
Will put mc tests in MC_TESTS/*/dirname
'''
# Make new folders
folders = ['PARS/','INPUT/','OUTPUT/']
outdir = check_mkdir(outdir)
dummy = [check_mkdir(os.path.join(outdir,folder)) for folder in folders]
this_outdir = check_mkdir(os.path.join(outdir,folder,dir_name))
# A place to write the commands if this needs to be run again
cmds_out = check_mkdir(os.path.join(outdir,'MC_COMMANDS/'))
cmds_file = open('%s/%s_MC_commands.dat'%(cmds_out,ID),'r')
# Place for the output table
table_out = check_mkdir(os.path.join(outdir,'TABLES/'))
out = open('%s/%s_MC.dat'%(table_out,ID),'w')
out.write('# mc_ID p_value NRGB_data NAGB_data NRGB_model NAGB_model mass_model N_wind Flux1_wind Flux2_wind\n')
#best fits: bfs[0] = pars for run_trilegal, bfs[1] = input for trilegal bfs[2] = output for trilegal
bfs = [get_afile(bestfit_loc+folder,'*'+ID+'*')[0] for folder in folders]
# find model from file!!! This is not general! !
model = bfs[-1].split('model_')[-1].replace('.dat.dat','.dat')
# Switch to the MC test directories
new_place = [bf.replace(bestfit_loc,'MC_TESTS/').replace(folder,folder+dir_name+'/') for bf in bfs]
# Best fit pars is the template, we'll swap out sfh file
in_pars = open(bfs[0]).readlines()
# Load SFHs
sfhs = get_afile(mc_dir+'/','SFR*mc*dat')
for i,sfh in enumerate(sfhs):
mcid = sfh.split('/')[-1].split('.')[1] # need to change jason/me
new_names = [np.replace(ext,'.'+mcid+ext) for np,ext in zip(new_place,['.pars','.dat','.dat.dat'])]
# New pars file for run_trilgal.py
pfile=open(new_names[0],'w')
[pfile.write(inpar) for inpar in in_pars[:-1]] #sfh line is at the bottom.
pfile.write("%-18s %s\n"%('object_sfr ',sfh))
pfile.close()
cmd="/Users/Phil/research/Italy/WXTRILEGAL/run_trilegal.py "
#cmd="/home/philrose/WXTRILEGAL/run_trilegal.py "
cmd+="-e code_2.0/main "
cmd+="-a "
cmd+="-i %s "%new_names[1]
cmd+="-o %s "%new_names[2]
cmd+="-f %s "%model
cmd+=new_names[0]
cmds_file.write('%s \n'%cmd)
print 'running TRILEGAL:',model,ID
p = subprocess.Popen(cmd, shell=True,stdout=subprocess.PIPE)
p = subprocess.Popen(cmd, shell=True)
sts = os.waitpid(p.pid, 0)[1]
fak_file=get_fakFILE(ID,jason=jason)
ast_file = new_names[2].split('/')[0]+'/ast_'+new_names[2].split('/')[-1]
cmd="AST/code/spread_angst <<EOF \n"
cmd+=fak_file+"\n"
cmd+=new_names[2]+"\n"
cmd+=ast_file+"\n"
cmd+="EOF \n"
print " ... completeness using %s"%fak_file
print " %s -> %s"%(new_names[2],ast_file)
print 'Running spread_angst...'
p = subprocess.Popen(cmd, shell=True,stdout=subprocess.PIPE)
sts = os.waitpid(p.pid, 0)[1]
os.system("wc -l %s %s|head -2"%(new_names[2],ast_file))
cmds_file.write('%s \n'%cmd)
synthcmd = read_table(ast_file)
s_mag2 = synthcmd.get_col('mag2') + synthcmd.get_col('diff_mag2'.strip())
s_mag2 = s_mag2[np.nonzero(abs(synthcmd.get_col('diff_mag2'.strip())) < 90.)[0]]
s_mag1 = synthcmd.get_col('mag1') + synthcmd.get_col('diff_mag1'.strip())
s_mag1 = s_mag1[np.nonzero(abs(synthcmd.get_col('diff_mag1'.strip())) < 90.)[0]]
s_color = s_mag1-s_mag2
Norm = trgb + 1.5
ind,nB_AGB,nNorm,ps_nNorm,ps_nB_AGBm,hist,bins,s_hist_normed,p_value,normalization = calc_LF(mag2,s_mag2,Norm,trgb)
Nstars, flux_rates = flux_from_mass_loss(synthcmd,rates,[filt1,filt2],ast_inds=ind,rel_flux=True)
out.write('# mc_ID p_value NRGB_data NAGB_data NRGB_model NAGB_model mass_model N_wind Flux1_wind Flux2_wind\n')
out.write('%s %.3f %i %i %i %i %e %i %e %e \n' %(mcid,p_value,nNorm,nB_AGB,ps_nNorm,ps_nB_AGBm,object_mass,Nstars[0],flux_rates[0][1],flux_rates[1][0]))
os.remove(ast_file)
print 'deleted',ast_file
os.remove(new_names[2])
print 'deleted',new_names[2]
out.close()
cmds_file.close()
