def bigplots(agb_tracks, infile):
if type(agb_tracks[0]) == str:
agb_tracks = [fileIO.get_numeric_data(a) for a in agb_tracks]
out_fig = os.path.join(infile.diagnostic_dir, 'hrd_%.4f.png' % agb_tracks[0].metallicity)
plot_title = '$\dot{M}_{\\rm M13}\ Z=%.4f$' % agb_tracks[0].metallicity
nagb_tracks = len(agb_tracks)
fig, (axs) = rspg.setup_multiplot(nagb_tracks,
ylabel='$\log\ L\ (L_\odot)$',
xlabel='$\log\ T_{\\rm eff}\ (K)$',
title =plot_title,
subplots_kwargs={'figsize': (30,30),
'squeeze': True})
axs = axs.flatten()
[hrd_slopes(agb_tracks[i], ax=axs[i]) for i in range(nagb_tracks)]
plt.savefig(out_fig, dpi=300)
ylabel = ['$C/O$', '$\log\ L\ (L_\odot)$', '$\log\ T_{\\rm eff}\ (K)$']
ycol = ['C/O', 'logl', 'logt']
for i in range(len(ylabel)):
fig, (axs) = rspg.setup_multiplot(nagb_tracks,
ylabel=ylabel[i],
xlabel='${\\rm Age (yr)}$',
title =plot_title,
subplots_kwargs={'figsize': (30,30),
'squeeze': True})
axs = axs.flatten()
[age_vs_plot(agb_tracks[j], infile, ycol=ycol[i], ax=axs[j], annotate=True,
xlabels=False, ylabels=False, save_plot=False)
for j in range(len(agb_tracks))]
out_fig = out_fig.replace('hrd', 'age_v_%s' % ycol[i].lower().replace('c/o',
'co'))
plt.savefig(out_fig, dpi=300)
def do_everything(infile):
'''
This script formats Paola's tracks and creates the files needed to use them
with TRILEGAL as well as the option to make diagnostic plots.
infile is an input_file object. See class InputFile
WHAT'S GOING ON:
Here is what it takes to go from Paola's agb tracks to trilegal:
1. Paola's tracks
2. Paola's tracks formatted for trilegal
3. trilegal files that link to Paola's formatted tracks
1. Paola's tracks should have naming scheme
[mix]/[set]/[Trash]_[metallicity]_[Y]/[track_identifier]
ex agb_caf09_z0.008/S1/agb_*Z*.dat
ex CAF09/S_SCS/*Z*/agb_*Z*.dat
These can go anywhere, and do not need to be included in trilegal
directories.
2. Paola's tracks are formatted for trilegal with no header file.
These go in trilegal_1.3/isotrack/AGB_TRACKS/Z[metallicity]_[mix]_[set].dat
They only include the quiescent phases and also a column with dL/dT
See AGBTracks class.
3. trilegal needs two files to link to Paola's formatted tracks
a. track file goes here: trilegal_1.3/isotrack/tracce_[mix]_[set].dat
b. cmd_input_file that links to the track file
goes here trilegal_1.3/cmd_input_[mix]_[set].dat
'''
# set up file names and directories, cd to paola's tracks.
AGB_file_setup(infile)
# list of isofiles, zs, and ys to send to tracce file.
isofiles, Zs, Ys = [], [], []
imfr_data = np.array([])
lifetime_data = np.array([])
for metal_dir in infile.metal_dirs:
metallicity, Y = metallicity_from_dir(metal_dir)
print 'Z = %.4f' % metallicity
if infile.diagnostic_dir0 is not None:
diagnostic_dir = os.path.join(infile.diagnostic_dir0,
infile.agb_mix,
infile.set_name,
metal_dir) + '/'
rsp.fileIO.ensure_dir(diagnostic_dir)
# update infile class to place plots in this directory
infile.diagnostic_dir = diagnostic_dir
agb_tracks = rsp.fileIO.get_files(os.path.join(infile.working_dir,
metal_dir),
infile.track_identifier)
agb_tracks.sort()
iso_name_conv = '_'.join(('Z%.4f' % metallicity, infile.name_conv))
isofile = os.path.join(infile.home, infile.isotrack_dir, iso_name_conv)
if infile.over_write is False and os.path.isfile(isofile):
print 'not over writing %s' % isofile
out = None
if infile.over_write is True:
out = open(isofile, 'w')
out.write('# age(yr) logL logTe m_act mcore c/o period ip')
out.write(' Mdot(Msun/yr) logTe X Y CNO dlogTe/dlogL \n')
isofile_rel_name = os.path.join('isotrack', infile.isotrack_dir,
iso_name_conv)
print 'found %i tracks' % len(agb_tracks)
for agb_track in agb_tracks:
# load track
track = fileIO.get_numeric_data(agb_track)
if track == -1:
continue
if track.bad_track is True:
continue
#if not track.mass in infile.masses:
# continue
assert metallicity == track.metallicity, \
'directory and track metallicity do not match'
# make iso file for trilegal
if out is not None:
fileIO.make_iso_file(track, out)
# save information for lifetime file.
lifetime_datum = np.array([metallicity, track.mass, track.tauc,
track.taum])
lifetime_data = np.append(lifetime_data, lifetime_datum)
# make diagnostic plots
if infile.diagnostic_dir0 is not None and infile.diag_plots is True:
assert metallicity_from_dir(infile.diagnostic_dir)[0] == \
track.metallicity, 'diag dir met wrong!'
graphics.diag_plots(track, infile)
# save information for imfr
if infile.make_imfr is True:
M_s = track.get_col('M_star')
imfr_datum = np.array([M_s[0], M_s[-1], float(metallicity)])
imfr_data = np.append(imfr_data, imfr_datum)
if out is not None:
out.close()
print 'wrote', isofile
fileIO.make_local_copy(isofile, dest=infile.make_copy)
# keep information for tracce file
isofiles.append(isofile_rel_name)
Ys.append(Y)
Zs.append(metallicity)
#graphics.bigplots(agb_tracks, infile)
# make file to link cmd_input to formatted agb tracks
fileIO.make_met_file(infile.tracce_file, Zs, Ys, isofiles)
fileIO.make_local_copy(infile.tracce_file, dest=infile.make_copy)
# make cmd_input file
cmd_in_kw = {'cmd_input_file': infile.cmd_input_file,
'file_tpagb': infile.tracce_file_rel,
'mass_loss': infile.mass_loss,
'file_isotrack': infile.file_isotrack}
fileIO.write_cmd_input_file(**cmd_in_kw)
if infile.make_imfr is True and infile.diagnostic_dir0 is not None:
ifmr_file = os.path.join(infile.diagnostic_dir0, infile.agb_mix,
infile.set_name,
'_'.join(('ifmr', infile.name_conv)))
ncols = 3
nrows = imfr_data.size/ncols
fileIO.savetxt(ifmr_file, imfr_data.reshape(nrows, ncols),
header='# M_i M_f Z \n')
graphics.plot_ifmr(ifmr_file)
if infile.diagnostic_dir0 is not None and infile.diag_plots is True:
lifetime_file = os.path.join(infile.diagnostic_dir0, infile.agb_mix,
infile.set_name,
'_'.join(('tau_cm', infile.name_conv)))
ncols = 4
nrows = lifetime_data.size/ncols
fileIO.savetxt(lifetime_file, lifetime_data.reshape(nrows, ncols),
header='# z mass tauc taum\n')
graphics.plot_cluster_test(lifetime_file, infile)
os.chdir(infile.home)
return infile.cmd_input_file
def compare_mass_loss(masses=1.0, z=0.001, sets=['NOV13', 'OCT13', 'NOV13eta0'],
paola=False):
'''
made to plot a comparison between several mass prescriptions.
Labels for the plot are set up stupidly, maybe in in_dict or labels arg...
'''
from matplotlib.ticker import NullFormatter
teff_max = 3.5
track_files = None
if paola is True:
# hack to use specific tracks from paola
track_dir = research_path + '/TP-AGBcalib/AGBTracks/plots_for_paperI/'
file_end = '_Mc0.00_dMc0.00_Tbd6.40_L0.00_dL0.00_C0.00_Nr3.00_rates0_KOPv_KMOLv.dat'
if masses == 2.0:
track_files = \
[track_dir + 'agb_2.00_Z0.00100000_Mdot50_eta0.00' + file_end,
track_dir + 'agb_2.00_Z0.00100000_Mdot49_eta0.40' + file_end,
track_dir + 'agb_2.00_Z0.00100000_Mdot48_eta8.00' + file_end,
track_dir + 'agb_2.00_Z0.00100000_Mdot50_eta0.40' + file_end]
teff_max = 3.4
if masses == 1.0:
track_files = \
[track_dir + 'agb_1.00_Z0.00100000_Mdot50_eta0.00' + file_end,
track_dir + 'agb_1.00_Z0.00100000_Mdot49_eta0.40' + file_end,
track_dir + 'agb_1.00_Z0.00100000_Mdot48_eta8.00' + file_end,
track_dir + 'agb_1.00_Z0.00100000_Mdot50_eta0.40' + file_end]
teff_max = 3.4
labels = ['$\\dot{M}_{\\rm{pre-dust}}=0.0$','$\\rm{R75}$',
'$\\rm{SC05}$', '$\\rm{mSC05}$']
if track_files is not None:
nrows = len(track_files)
else:
nrows = len(sets)
fig, axs = plt.subplots(nrows=nrows, ncols=2, figsize=(8, 8))
anorm = 1e6
xlab0 = '\\rm{Age}\ (10^6\ \\rm{yr})'
ylab0 = '\log\ \dot{M}\ (\\rm{M_\odot\ yr}^{-1})'
ylab1 = '\log\ L\ (L_\odot)'
xlab1 = '\log\ T_{\\rm eff}\ (\\rm{K})'
agb_tracks_dir = research_path + 'TP-AGBcalib/AGBTracks/CAF09'
if type(masses) is not list:
masses = [masses]
cols = ['k']
for j, mass in enumerate(masses):
if track_files is None:
tnames = []
labels = []
for tset in sets:
label = translate_model_name(tset)
direc = os.path.join(agb_tracks_dir, 'S_' + tset)
direc, = [os.path.join(direc, d)
for d in os.listdir(direc) if str(z) in d]
tname = rsp.fileIO.get_files(direc, 'agb_%.2f*' % mass)[0]
tnames.append(tname)
labels.append('$%s$' % label)
tracks = [fileIO.get_numeric_data(t) for t in tnames]
else:
tracks = [fileIO.get_numeric_data(t) for t in track_files]
for i in range(len(tracks)):
axs[i][0].plot(tracks[i].data_array['ageyr']/anorm,
tracks[i].data_array['dMdt'],
label='$M=%g\ M_\odot$' % mass, lw=1, color=cols[j])
axs[i][0].plot(tracks[i].data_array['ageyr'][tracks[i].cstar]/anorm,
tracks[i].data_array['dMdt'][tracks[i].cstar],
lw=1, color='darkred')
axs[i][1].plot(tracks[i].data_array['T_star'],
tracks[i].data_array['L_star'],
label='$M=%g\ M_\odot$' % mass, lw=1, color=cols[j])
axs[i][1].plot(tracks[i].data_array['T_star'][tracks[i].cstar],
tracks[i].data_array['L_star'][tracks[i].cstar],
lw=1, color='darkred')
axs[i][0].annotate(labels[i], (0.03, 0.96), fontsize=fontlarge,
xycoords='axes fraction', va='top')
axs[-1, 0].set_xlabel('$%s$' % xlab0, fontsize=fontlarge)
axs[-1, 1].set_xlabel('$%s$' % xlab1, fontsize=fontlarge)
plt.annotate('$%s$' % ylab0, (0.03, 0.5), fontsize=fontlarge, va='center',
xycoords='figure fraction', rotation='vertical')
plt.annotate('$%s$' % ylab1, (0.95, 0.5), fontsize=fontlarge, va='center',
xycoords='figure fraction', rotation='vertical')
[ax.yaxis.tick_right() for ax in axs.flatten()[1::2]]
[ax.xaxis.set_major_formatter(NullFormatter())
for ax in axs.flatten()[:-2]]
# mass loss
[ax.set_ylim(-11.5, -4.5) for ax in axs[:, 0]]
# log l
[ax.set_ylim(2.81, 4.25) for ax in axs[:, 1]]
# log te
[ax.set_xlim(3.66, teff_max) for ax in axs[:, 1]]
# age Myr
[ax.set_xlim(0, 2.45) for ax in axs[:, 0]]
# top left plot only
if paola is False:
[ax.legend(loc=4, fontsize=fontlarge, frameon=False)
for ax in [axs.flatten()[0]]]
fig.subplots_adjust(wspace=0.02, hspace=0.02)
plt.savefig('compare_massloss_M%g_Z%g.png' % (masses[0], z), dpi=150)
return axs
def compare_agb_lifetimes():
import glob
track_loc = research_path + \
'TP-AGBcalib/AGBTracks/plots_for_paperI/agbz001_3dup/'
models = ['NOV13', 'NOV13eta0', 'OCT13']
model_name = translate_model_name('nov13')
# these two have to line up:
search_formats = ['*dL0.0*', '*dL0.50*', '*dL2*']
labels = [r'%s' % model_name,
r'%s: $0.5\lambda$' % model_name,
r'%s: $2\lambda$' % model_name]
track_sets = [rsp.fileIO.get_files(track_loc, sf) for sf in search_formats]
cols1 = ['k', '#d73027', '#fee090', '#e0f3f8', '#91bfdb', '#4575b4']
bmap = brewer2mpl.get_map('Blues', 'Sequential', 9)
cols2 = bmap.mpl_colors[3::2]
fig, axs = plt.subplots(ncols=2, figsize=(10, 5), sharex=True, sharey=True)
for i, track_set in enumerate(track_sets):
tracks = np.array([fileIO.get_numeric_data(t) for t in track_set])
tracks = tracks[np.argsort([t.mass for t in tracks])]
masses = np.array([t.mass for t in tracks])
taus = np.array([np.sum(t.data_array['dt']) for t in tracks])
plt_kw = {'lw': 3, 'label': labels[i], 'color': cols1[i]}
if i == 0:
for ax in axs:
ax.plot(masses, taus/1e6, lw=4, color='k')
plt_kw['color'] = cols2[0]
ax.plot(masses, taus/1e6, **plt_kw)
else:
axs[1].plot(masses, taus/1e6, lw=4, color='k')
axs[1].plot(masses, taus/1e6, **plt_kw)
for j in range(len(models)):
model_name = models[j].replace('.dat', '').split('_')[-1]
if models[j].lower() == 'nov13':
continue
base = research_path + \
'TP-AGBcalib/AGBTracks/CAF09/S_%s' % model_name
agb_track_loc = os.path.join(base, glob.glob1(base, '*0.001*')[0])
track_names = [os.path.join(agb_track_loc, a)
for a in os.listdir(agb_track_loc)
if a.startswith('agb_') and not 'b_1.75' in a
and not 'b_1.80' in a]
tracks = [fileIO.get_numeric_data(t) for t in track_names]
tracks = [t for t in tracks if not t == -1 and t.data_array.size > 1]
tracks = np.array(tracks)[np.argsort([t.mass for t in tracks])]
masses = np.array([t.mass for t in tracks])
taus = np.array([np.sum(t.data_array['dt']) for t in tracks])
model_name = translate_model_name(model_name)
plt_kw = {'lw': 3, 'label': model_name, 'color': cols2[j]}
axs[0].plot(masses, taus/1e6, lw=4, color='k')
axs[0].plot(masses, taus/1e6, **plt_kw)
for ax in axs:
ax.legend(loc=0, frameon=False, fontsize=fontsmall)
ax.set_xlim(1, 2.95)
ax.set_ylim(.25, 3.7)
ax.set_xlabel(r'${\rm Initial\ Mass\ (M_\odot)}$', fontsize=fontlarge)
ax.tick_params(labelsize=fontmid)
fig.subplots_adjust(left=0.08, right=0.98, bottom=0.15, top=0.95,
wspace=0.01)
axs[0].set_ylabel(r'${\rm Lifetime\ (Myr)}$', fontsize=fontlarge)
plt.savefig('lambda_plot.png', dpi=150)
return axs
def agb_lifetimes(models, z=0.002):
import glob
tauss = []
btauss = []
for j in range(len(models)):
print models[j]
print
fig, ax = plt.subplots()
fig2, ax2 = plt.subplots()
model_name = models[j].replace('.dat', '').split('_')[-1]
agb_track_loc = research_path + \
'TP-AGBcalib/AGBTracks/CAF09/S_%s/' % model_name
base = research_path + \
'TP-AGBcalib/AGBTracks/CAF09/S_%s' % model_name
if z == 'all':
zs = np.array([d.split('_')[1].replace('Z','')
for d in glob.glob1(base, '*')], dtype=float)
else:
zs = [z]
zs = np.array([i for i in zs if i <= 0.008])
if len(zs) > 8.:
zs = zs[::2]
print zs
cnum = np.max([len(zs), 3])
bmap = brewer2mpl.get_map('Blues', 'Sequential', cnum + 1)
cols = bmap.mpl_colors[1:]
for i, z in enumerate(np.sort(zs)):
try:
agb_track_loc = os.path.join(base, glob.glob1(base, '*%g*' % z)[0])
except IndexError:
print 'no Z=%g tracks in %s' % (z, base)
continue
if not os.path.isdir(agb_track_loc) is True:
print model_name, 'no agb tracks found'
model_name = translate_model_name(models[j])
agb_track_names = [os.path.join(agb_track_loc, a)
for a in os.listdir(agb_track_loc)
if a.startswith('agb_')]
tracks = [fileIO.get_numeric_data(agb_track)
for agb_track in agb_track_names]
tracks = [t for t in tracks if not t == -1 and t.data_array.size > 1]
masses = np.array([t.mass for t in tracks])
sort = np.argsort(masses)
masses = masses[sort]
tracks = np.array(tracks)[sort]
logls = np.array([t.get_col('L_star') for t in tracks])
brights = np.array([np.nonzero(logl > 3.4)[0] for logl in logls])
#m_cs = np.array([t.get_col('M_c')[0] for t in tracks])
#ax2.plot(masses, m_cs, lw=2, color='black')
taus = np.array([np.sum(t.data_array['dt']) for t in tracks])
btaus = np.array([np.sum(t.data_array['dt'][b])
for t, b in zip(tracks, brights)])
tauss.append(taus)
btauss.append(btaus)
plt_kw = {'lw': 3, 'label': '$Z=%g$' % z, 'color': cols[i]}
ax.plot(masses, taus/1e6, lw=4, color='k')
ax2.plot(masses, btaus/1e6, lw=4, color='k')
ax.plot(masses, taus/1e6, **plt_kw)
ax2.plot(masses, btaus/1e6, **plt_kw)
with open('tpagb_lifetimes_S_%s_Z%g.dat' % (models[j], z), 'w') as out:
out.write('# mass tpagb_tau tpagb_tau_bright \n')
np.savetxt(out, np.array([masses, taus, btaus]).T, fmt='%.3f')
for ax in [ax, ax2]:
ax.set_xlabel('${\\rm Initial\ Mass\ (M_\odot)}$', fontsize=fontlarge)
ax.set_ylabel('${\\rm Lifetime\ (Myr)}$', fontsize=fontlarge)
ax.legend(loc=0, frameon=False)
ax.set_xlim(0, 5)
ax.set_ylim(0, 5)
ax2.annotate('$\log L/L_\odot > 3.4$', (0.03, 0.97), xycoords='axes fraction',
fontsize=fontlarge, va='top')
ax2.set_ylabel(ax2.get_ylabel().replace('(Myr)', '(Myr)'))
#ax2.set_ylabel('${\\rm Pre\!-\!Flash\ Core\ Mass\ (M_\odot)}$', fontsize=24)
fig.savefig('tpagb_lifetime_%s.png' % (models[j]), dpi=150)
fig2.savefig('tpagb_lifetime_bright_%s.png' % (models[j]), dpi=150)
return
