def get_data(table_file='default'):
if table_file == 'default':
table_file = snap_src + '/tables/ancients_0.1_0.2_galaxies.dat'
ags = sfh_tests_multi_proc.AncientGalaxies()
ags.read_trgb_table(table_file)
data_dict = {}
for i, target in enumerate(ags.data.target):
for band in ['opt', 'ir']:
ratio = ags.data[i]['n%s_agb' % band] / \
ags.data[i]['n%s_rgb' % band]
data_dict['%s_%s' % (target, band)] = ratio
data_dict['%s_%s_err' % (target, band)] = \
galaxy_tests.count_uncert_ratio(ags.data[i]['n%s_agb' % band],
ags.data[i]['n%s_rgb' % band])
return data_dict
def data_table(targets, table_file='default'):
# target, av, dist, [opt: frac comp, trgb, nrgb, nagb ratio] [ir: ..]
if table_file == 'default':
table_file = snap_src + '/tables/ancients_0.1_0.2_galaxies.dat'
ags = sfh_tests_multi_proc.AncientGalaxies()
ags.read_trgb_table(table_file)
data_dict = get_data(table_file=table_file)
comp_data = tables.read_completeness_table()
row = ''
row2 = ''
ts = list(set([t.lower() for t in targets]) & set(ags.data.target))
assert len(ts) == len(targets), 'cant find all targets in ags.data'
inds = list([np.where(t.lower() == ags.data.target)[0][0] for t in targets])
opt_agb_tot = np.sum(ags.data.nopt_agb[inds])
opt_rgb_tot = np.sum(ags.data.nopt_rgb[inds])
ir_agb_tot = np.sum(ags.data.nir_agb[inds])
ir_rgb_tot = np.sum(ags.data.nir_rgb[inds])
totfmt = 'Total & %i & %i & $%.3f\\pm%.3f$ & %i & %i & $%.3f\\pm%.3f$ \\\\'
total = totfmt % (opt_agb_tot, opt_rgb_tot, opt_agb_tot/opt_rgb_tot,
galaxy_tests.count_uncert_ratio(opt_agb_tot, opt_rgb_tot),
ir_agb_tot, ir_rgb_tot, ir_agb_tot/ir_rgb_tot,
galaxy_tests.count_uncert_ratio(ir_agb_tot, ir_rgb_tot))
for target in targets:
if target.upper() == 'NGC2976-DEEP':
extra_key='F606W,F814W'
else:
extra_key=None
(Av, dmod) = [angst_data.get_item(target, i, extra_key=extra_key)
for i in ['Av', 'dmod']]
comp_row = rsp.fileIO.get_row(comp_data, 'target', target)
nstars_row = rsp.fileIO.get_row(ags.data, 'target', target)
sub_dict = {}
opt_err_pct = []
ir_err_pct = []
for (k,v) in data_dict.items():
if '404' in target:
target = target.lower().replace('-deep', '')
if target in k or target.lower() in k:
sub_dict[k] = v
opt_err_pct.append(sub_dict['%s_opt_err' % target.lower()] /
sub_dict['%s_opt' % target.lower()])
ir_err_pct.append(sub_dict['%s_ir_err' % target.lower()] /
sub_dict['%s_ir' % target.lower()])
row += '%s & %.2f & %.2f & ' % (target, Av, dmod)
row += '%(opt_filter2).2f & ' % comp_row
row += '%(opt_trgb).2f & ' % nstars_row
row += '%(ir_filter2).2f & ' % comp_row
row += '%(ir_trgb).2f \\\\ \n' % nstars_row
row2 += '%s & ' % target
row2 += '%(nopt_agb)i & %(nopt_rgb)i & ' % nstars_row
row2 += '$%.3f\\pm%.3f$ & ' % (sub_dict['%s_opt' % target.lower()],
sub_dict['%s_opt_err' % target.lower()])
row2 += '%(nir_agb)i & %(nir_rgb)i & ' % nstars_row
row2 += '$%.3f\\pm%.3f$ \\\\ \n' % (sub_dict['%s_ir' % target.lower()],
sub_dict['%s_ir_err' % target.lower()])
with open('data_table.tex', 'w') as out:
out.write(row)
out.write(row2)
out.write(total)
out.write('# max err pct. opt: %.3f ir: %.3f \n' % \
(np.max(opt_err_pct), np.max(ir_err_pct)))
return total
def narratio_table(narratio_files, table_file='default'):
'''write the latex table'''
data_dict = get_data(table_file=table_file)
nar_dict = result2dict(narratio_files)
targets = list(np.unique([k.split('_')[0] for k in nar_dict.keys()]))
agb_mods = list(np.unique(['_'.join(k.split('_')[1:4])
for k in nar_dict.keys()]))
# table columns: target, data ratio, (ratio, frac diff) per agb mod
ir_table = np.empty(shape=(len(targets) + 1, len(agb_mods)*2 + 1),
dtype='|S20')
ir_table[:, :] = ''
opt_table = np.empty(shape=(len(targets) + 1, len(agb_mods)*2 + 1),
dtype='|S20')
opt_table[:, :] = ''
fmt = r'$%.3f\pm%.3f$ & '
fmt2 = r'$%.3f\pm%.3f$ \\'
for key, val in nar_dict.items():
# go through half the dict (see below)
if 'err' in key:
continue
# choose which table
if 'ir' in key:
table = ir_table
band = 'ir'
if 'opt' in key:
table = opt_table
band = 'opt'
# choose the correct row and column placement in the table
target = key.split('_')[0]
agb_mod = '_'.join(key.split('_')[1:4])
row = targets.index(target)
# column 0 is target, columns 1, 3, 5 have ratios
column = (agb_mods.index(agb_mod) * 2) + 1
#print row, column
# target
table[row, 0] = '%s &' % target.upper()
# data
dnarr = data_dict['%s_%s' % (target.lower(), band)]
derr = data_dict['%s_%s_err' % (target.lower(), band)]
#dstr = fmt % (dnarr, derr)
#table[row, 1] = dstr
# model
mnarr = val
# grab the error from the dict
err_key = key.replace('mean', 'err_mean')
mnerr = nar_dict[err_key]
mstr = fmt % (mnarr, mnerr)
table[row, column] = mstr
# frac difference
#pct_diff = (mnarr - dnarr) / dnarr
#pct_diff_err = np.abs(pct_diff * (mnerr/mnarr + derr/dnarr))
pct_diff = (mnarr / dnarr)
pct_diff_err = np.abs(pct_diff * (mnerr/mnarr + derr/dnarr))
f = fmt
# if final column, put \\ not &
if column + 1 == table.shape[1] - 1:
f = fmt2
pdstr = f % (pct_diff, pct_diff_err)
table[row, column + 1] = pdstr
# totals:
nar_dict = result2dict(narratio_files, search='all')
data_total = data_table(targets)
data_total = np.array(data_total.translate(None, '\\$Total&').replace('pm', ' ').split(), dtype=float)
for i, agb_mod in enumerate(agb_mods):
for band, table in zip(['ir', 'opt'], [ir_table, opt_table]):
f = fmt
column = (i * 2) + 1
nrgb = np.sum([v for k, v in nar_dict.items()
if agb_mod in k and band in k and 'rgb' in k])
nagb = np.sum([v for k, v in nar_dict.items()
if agb_mod in k and band in k and 'agb' in k])
ratio = nagb / nrgb
err = galaxy_tests.count_uncert_ratio(nagb, nrgb)
table[-1, column] = f % (ratio, err)
column += 1
if column == table.shape[1] - 1:
f = fmt2
# frac difference
if band == 'ir':
j = 6
if band == 'opt':
j = 2
dratio = data_total[j]
derr = data_total[j+1]
pct_diff = (ratio / dratio)
pct_diff_err = np.abs(pct_diff * (err/ratio + derr/dratio))
#table[-1, column] = f % (pct_diff, pct_diff_err)
#table[-1, 0] = 'Total & '
# mean
for i, agb_mod in enumerate(agb_mods):
for table in [ir_table, opt_table]:
f = fmt
column = (i * 2) + 1
val, err = \
np.mean(np.array([l.translate(None, ' $&\\').split('pm')
for l in table[:, column][:-1]], dtype=float), axis=0)
print agb_mod, err/val
table[-1, column] = f % (val, err)
column += 1
if column == table.shape[1] - 1:
f = fmt2
val, err = \
np.mean(np.array([l.translate(None, ' $&\\').split('pm')
for l in table[:, column][:-1]], dtype=float), axis=0)
table[-1, column] = f % (val, err)
table[-1, 0] = 'Mean & '
# write the file
ratio_str = '$\\frac{N_{\\rm TP-AGB}}{N_{\\rm RGB}}$'
header = 'Target & '
for i in range(len(agb_mods)):
header += '%s %s & Frac. Difference & ' % (ratio_str,
agb_mods[i].split('_')[-1])
header = header[:-2] + '\\\\ \n \\hline \n'
outfile_dir = os.path.split(narratio_files[0])[0]
for band, table in zip(['opt', 'ir'], [opt_table, ir_table]):
outfile = os.path.join(outfile_dir, '%s_narratio_table.tex' % band)
with open(outfile, 'w') as out:
out.write(header)
np.savetxt(out, table, fmt='%s')
return ir_table, opt_table
