def from_plateifu(cls, plateifu, res_basedir, pca_system, cosmo=cosmo, mlband='i'):
plate, ifu = plateifu.split('-')
results = read_results.PCAOutput.from_plateifu(basedir=res_basedir, plate=plate, ifu=ifu)
drp = m.load_drp_logcube(plate, ifu, mpl_v)
dap = m.load_dap_maps(plate, ifu, mpl_v, daptype)
drpall = m.load_drpall(mpl_v, 'plateifu')
drpall_row = drpall.loc['{}-{}'.format(plate, ifu)]
return cls(results, pca_system, drp, dap, drpall_row, cosmo, mlband)
def from_plateifu(cls, plate, ifu, MPL_v, kind, row=None, **kwargs):
'''
load a MaNGA galaxy from a plateifu specification
'''
plate, ifu = str(plate), str(ifu)
if row is None:
drpall = m.load_drpall(MPL_v, index='plateifu')
row = drpall.loc['{}-{}'.format(plate, ifu)]
drp_hdulist = m.load_drp_logcube(plate, ifu, MPL_v)
dap_hdulist = m.load_dap_maps(plate, ifu, MPL_v, kind)
return cls(drp_hdulist, dap_hdulist, row, **kwargs)
def from_plateifu(cls, plate, ifu, MPL_v, kind, row=None,
**kwargs):
'''
load a MaNGA galaxy from a plateifu specification
'''
plate, ifu = str(plate), str(ifu)
if row is None:
drpall = m.load_drpall(MPL_v, index='plateifu')
row = drpall.loc['{}-{}'.format(plate, ifu)]
drp_hdulist = m.load_drp_logcube(plate, ifu, MPL_v)
dap_hdulist = m.load_dap_maps(plate, ifu, MPL_v, kind)
return cls(drp_hdulist, dap_hdulist, row, **kwargs)
def from_plateifu(cls,
plateifu,
res_basedir,
pca_system,
cosmo=cosmo,
mlband='i'):
plate, ifu = plateifu.split('-')
results = read_results.PCAOutput.from_plateifu(basedir=res_basedir,
plate=plate,
ifu=ifu)
drp = m.load_drp_logcube(plate, ifu, mpl_v)
dap = m.load_dap_maps(plate, ifu, mpl_v, daptype)
drpall = m.load_drpall(mpl_v, 'plateifu')
drpall_row = drpall.loc['{}-{}'.format(plate, ifu)]
return cls(results, pca_system, drp, dap, drpall_row, cosmo, mlband)
def from_fakedata(cls, plate, ifu, MPL_v, basedir='fakedata', row=None,
kind='SPX-MILESHC-MILESHC', **kwargs):
'''
load fake data based on a particular already-observed galaxy
'''
plate, ifu = str(plate), str(ifu)
if row is None:
drpall = m.load_drpall(MPL_v, index='plateifu')
row = drpall.loc['{}-{}'.format(plate, ifu)]
drp_hdulist = fits.open(
os.path.join(basedir, '{}-{}_drp.fits'.format(plate, ifu)))
dap_hdulist = fits.open(
os.path.join(basedir, '{}-{}_dap.fits'.format(plate, ifu)))
return cls(drp_hdulist, dap_hdulist, row, **kwargs)
from astropy import units as u
from astropy.cosmology import WMAP9
from astropy.utils.console import ProgressBar
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
from matplotlib import gridspec
from matplotlib.legend_handler import HandlerTuple
from statsmodels.nonparametric.smoothers_lowess import lowess
from statsmodels.regression.linear_model import OLS
from statsmodels.tools.tools import add_constant as sm_add_constant
drpall = m.load_drpall(mpl_v, index='plateifu')
dapall = m.load_dapall(mpl_v)
dapall = dapall[dapall['DAPDONE'] * (dapall['DAPTYPE'] == daptype)]
dapall.add_index('PLATEIFU')
pca_system = read_results.PCASystem.fromfile(os.path.join(csp_basedir, 'pc_vecs.fits'))
jhumpa = t.Table.read('/usr/data/minhas/zpace/stellarmass_pca/jhu_mpa_{}.fits'.format(
mpl_v.replace('-', '').lower()))
jhumpa['plateifu'] = [plateifu.strip(' ') for plateifu in jhumpa['PLATEIFU']]
jhumpa = jhumpa['plateifu', 'LOG_MSTAR']
jhumpa = jhumpa[jhumpa['LOG_MSTAR'] > 0.]
sfrsd_tab = t.Table.read('/usr/data/minhas/zpace/stellarmass_pca/sigma_sfr.fits')
sfrsd_tab['plateifu'] = sfrsd_tab['names']
linefluxes_noise = real_unc * np.random.randn(*linefluxes_real.shape)
linefluxes_obs = linefluxes_real + linefluxes_noise
obs_unc = real_unc / unc_factor
mask_obs = np.any(linefluxes_obs < 0., axis=1)
print(linefluxes_obs.shape)
'''
'''
fakemodel, faketrace = metallicity.find_ism_params(
grid=cloudy_fsps_grid, dustlaw=fitzpatrick99,
line_obs=[linefluxes_obs[~mask_obs], obs_unc[~mask_obs], mask_obs[~mask_obs]],
line_ls=line_ls, drpall_row={'nsa_zdist': zdist})
'''
#####
drpall = m.load_drpall(metallicity.mpl_v)
drpall.add_index('plateifu')
drpall_row = drpall.loc['9497-9101']
plate, ifu = drpall_row['plateifu'].split('-')
el = metallicity.Elines.DAP_from_plateifu(
plate,
ifu,
mpl_v,
'SPX-GAU-MILESHC',
data_colname='MPL-6-name',
lines_used=cloudy_fsps_grid.observable_names,
elines_table=elines)
pcares = from_pca.PCAOutput.from_plateifu(basedir=os.path.join(
pca_basedir, 'results'),
def make_color_compare(CSP_dir,
mpl_v,
n_obs=10,
model_zcolors=False,
randomseed=None,
snr_min=5.):
'''
make (g-r) vs (r-i) plot
'''
if randomseed is not None:
np.random.seed(randomseed)
drpall = m.load_drpall(mpl_v, index='plateifu')
drpall = drpall[(drpall['mngtarg2'] == 0) * (drpall['nsa_z'] != -9999)]
plateifus = np.random.choice(drpall['plateifu'], replace=False, size=n_obs)
# cols are g, r, and i fluxes in order
obs_fluxes = [
m.get_gal_bpfluxes(*plateifu.split('-'), mpl_v, ['g', 'r', 'i'],
snr_min) for plateifu in plateifus
]
obs_ext = np.concatenate([
np.repeat(drpall.loc[plateifu]['nsa_extinction'][None, 3:6],
f.shape[0],
axis=0) for f, plateifu in zip(obs_fluxes, plateifus)
])
obs_fluxes = np.row_stack(obs_fluxes)
integrated_g = drpall['nsa_elpetro_absmag'][:, 3] - \
drpall['nsa_extinction'][:, 3]
integrated_r = drpall['nsa_elpetro_absmag'][:, 4] - \
drpall['nsa_extinction'][:, 4]
integrated_i = drpall['nsa_elpetro_absmag'][:, 5] - \
drpall['nsa_extinction'][:, 5]
integrated_gr = integrated_g - integrated_r
integrated_ri = integrated_r - integrated_i
obs_gr = -2.5 * np.log10(obs_fluxes[:, 0] / obs_fluxes[:, 1]) - \
(obs_ext[:, 0] - obs_ext[:, 1])
obs_ri = -2.5 * np.log10(obs_fluxes[:, 1] / obs_fluxes[:, 2]) - \
(obs_ext[:, 1] - obs_ext[:, 2])
models_fnames = glob.glob(os.path.join(CSP_dir, 'CSPs_*.fits'))
if model_zcolors:
color1 = 'Cgr_z015'
color2 = 'Cri_z015'
color1TeX = r'$^{.15}C_{gr}$'
color2TeX = r'$^{.15}C_{ri}$'
else:
color1 = 'Cgr'
color2 = 'Cri'
color1TeX = r'$C_{gr}$'
color2TeX = r'$C_{ri}$'
models_colors = t.vstack(
[t.Table.read(fn_)[color1, color2] for fn_ in models_fnames])
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='scatter_density')
ax.scatter([-100], [-100], c='g', s=1, marker='s', label='models')
ax.scatter([-100], [-100], c='b', s=1, marker='s', label='spax')
ax.scatter([-100], [-100], c='r', s=1, marker='s', label='integrated')
ax.scatter_density(obs_gr, obs_ri, color='b')
ax.scatter_density(models_colors[color1], models_colors[color2], color='g')
#ax.scatter_density(integrated_gr, integrated_ri, color='r')
ax.set_xlim([-.2, 1.4])
ax.set_ylim([-.1, 0.6])
ax.set_xlabel(color1TeX, size='small')
ax.set_ylabel(color2TeX, size='small')
ax.legend(loc='best')
fig.suptitle(CSP_dir.replace('_', '-'), size='x-small')
fig.tight_layout()
ax.tick_params(labelsize='x-small')
basename = 'Cgr_Cri'
if model_zcolors:
basename = '_'.join((basename, 'z015'))
savefig(fig, ''.join((basename, '.png')), CSP_dir, close=True)
def from_mpl_v(cls, v):
drpall = m.load_drpall(v)
return cls(drpall)
from astropy import table as t
from astropy import units as u
from astropy.cosmology import WMAP9
from astropy.utils.console import ProgressBar
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
from matplotlib import gridspec
from statsmodels.nonparametric.smoothers_lowess import lowess
from statsmodels.regression.linear_model import OLS
from statsmodels.tools.tools import add_constant as sm_add_constant
drpall = m.load_drpall(mpl_v, index='plateifu')
dapall = m.load_dapall(mpl_v)
dapall = dapall[dapall['DAPDONE'] * (dapall['DAPTYPE'] == daptype)]
dapall.add_index('PLATEIFU')
pca_system = read_results.PCASystem.fromfile(os.path.join(basedir, 'pc_vecs.fits'))
jhumpa = t.Table.read('/usr/data/minhas/zpace/stellarmass_pca/jhu_mpa_{}.fits'.format(
mpl_v.replace('-', '').lower()))
jhumpa['plateifu'] = [plateifu.strip(' ') for plateifu in jhumpa['PLATEIFU']]
jhumpa = jhumpa['plateifu', 'LOG_MSTAR']
jhumpa = jhumpa[jhumpa['LOG_MSTAR'] > 0.]
sfrsd_tab = t.Table.read('/usr/data/minhas/zpace/stellarmass_pca/sigma_sfr.fits')
sfrsd_tab['plateifu'] = sfrsd_tab['names']
def from_mpl_v(cls, v):
drpall = m.load_drpall(v)
return cls(drpall)
def make_color_compare(CSP_dir, mpl_v, n_obs=10, model_zcolors=False,
randomseed=None, snr_min=5.):
'''
make (g-r) vs (r-i) plot
'''
if randomseed is not None:
np.random.seed(randomseed)
drpall = m.load_drpall(mpl_v, index='plateifu')
drpall = drpall[(drpall['mngtarg2'] == 0) * (drpall['nsa_z'] != -9999)]
plateifus = np.random.choice(drpall['plateifu'], replace=False, size=n_obs)
# cols are g, r, and i fluxes in order
obs_fluxes = [m.get_gal_bpfluxes(*plateifu.split('-'), mpl_v,
['g', 'r', 'i'], snr_min)
for plateifu in plateifus]
obs_ext = np.concatenate(
[np.repeat(drpall.loc[plateifu]['nsa_extinction'][None, 3:6],
f.shape[0], axis=0)
for f, plateifu in zip(obs_fluxes, plateifus)])
obs_fluxes = np.row_stack(obs_fluxes)
integrated_g = drpall['nsa_elpetro_absmag'][:, 3] - \
drpall['nsa_extinction'][:, 3]
integrated_r = drpall['nsa_elpetro_absmag'][:, 4] - \
drpall['nsa_extinction'][:, 4]
integrated_i = drpall['nsa_elpetro_absmag'][:, 5] - \
drpall['nsa_extinction'][:, 5]
integrated_gr = integrated_g - integrated_r
integrated_ri = integrated_r - integrated_i
obs_gr = -2.5 * np.log10(obs_fluxes[:, 0] / obs_fluxes[:, 1]) - \
(obs_ext[:, 0] - obs_ext[:, 1])
obs_ri = -2.5 * np.log10(obs_fluxes[:, 1] / obs_fluxes[:, 2]) - \
(obs_ext[:, 1] - obs_ext[:, 2])
models_fnames = glob.glob(os.path.join(CSP_dir, 'CSPs_*.fits'))
if model_zcolors:
color1 = 'Cgr_z015'
color2 = 'Cri_z015'
color1TeX = r'$^{.15}C_{gr}$'
color2TeX = r'$^{.15}C_{ri}$'
else:
color1 = 'Cgr'
color2 = 'Cri'
color1TeX = r'$C_{gr}$'
color2TeX = r'$C_{ri}$'
models_colors = t.vstack([t.Table.read(fn_)[color1, color2]
for fn_ in models_fnames])
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='scatter_density')
ax.scatter([-100], [-100], c='g', s=1, marker='s', label='models')
ax.scatter([-100], [-100], c='b', s=1, marker='s', label='spax')
ax.scatter([-100], [-100], c='r', s=1, marker='s', label='integrated')
ax.scatter_density(obs_gr, obs_ri, color='b')
ax.scatter_density(models_colors[color1], models_colors[color2], color='g')
#ax.scatter_density(integrated_gr, integrated_ri, color='r')
ax.set_xlim([-.2, 1.4])
ax.set_ylim([-.1, 0.6])
ax.set_xlabel(color1TeX, size='small')
ax.set_ylabel(color2TeX, size='small')
ax.legend(loc='best')
fig.suptitle(CSP_dir.replace('_', '-'), size='x-small')
fig.tight_layout()
ax.tick_params(labelsize='x-small')
basename = 'Cgr_Cri'
if model_zcolors:
basename = '_'.join((basename, 'z015'))
savefig(fig, ''.join((basename, '.png')), CSP_dir, close=True)
mass_table['outer_mass_cmlr'] = \
(mass_table['outer_lum_{}'.format(mlband)] + \
mass_table['outer_ml_cmlr']).to(u.Msun)
return mass_table['plateifu', 'mass_in_ifu', 'outer_mass_cmlr',
'outer_mass_ring']
def chunks(l, nchunks):
"""Yield n number of striped chunks from l."""
for i in range(0, nchunks):
yield l[i::nchunks]
if __name__ == '__main__':
drpall = m.load_drpall(mpl_v, 'plateifu')
mlband = 'i'
mass_table_fname = os.path.join(csp_basedir, 'mass_table.fits')
# what galaxies are available to aggregate?
res_fnames = glob(os.path.join(csp_basedir, 'results/*-*/*-*_res.fits'))
mass_table = None
for i, rfn in enumerate(res_fnames):
if mass_table is None:
mass_table = mass_agg_onegal(rfn, mlband, drpall)
else:
mass_table.add_row(mass_agg_onegal(rfn, mlband, drpall)[0])
print('{:^6} / {:^6} completed'.format(i + 1, len(res_fnames)),
return os.path.exists(os.path.join(status_file_dir, '{}.log'.format(plateifu)))
def write_log_file(plateifu, msg):
'''write a log file
'''
status_file_dir = os.path.join(
os.environ['STELLARMASS_PCA_RESULTSDIR'], 'results',
plateifu)
if not os.path.exists(status_file_dir):
os.makedirs(status_file_dir)
with open(os.path.join(status_file_dir, '{}.log'.format(plateifu)), 'w') as logf:
logf.write(msg)
def summary_remaining(drpall, group_col='ifudesignsize'):
remaining = drpall[
~np.array(list(map(log_file_exists, drpall['plateifu'])))]
ifusize_grps = remaining.group_by(group_col)
print('remaining galaxies by {}'.format(group_col))
for k, g in zip(ifusize_grps.groups.keys, ifusize_grps.groups):
print(k[group_col], ':', len(g))
if __name__ == '__main__':
import manga_tools as m
drpall = m.load_drpall(mpl_v)
drpall = drpall[(drpall['ifudesignsize'] > 0) * (drpall['nsa_z'] != -9999.)]
print(drpall)
summary_remaining(drpall)
