for n in range(100,200,1):
if n < 10:
i = '0' + str(n)
else:
i = str(n)
#same system case
df = pd.read_csv('df_binary_test{}.csv'.format(i))
dar = Dartmouth_Isochrone()
t = ObservationTree.from_df(df, name='test{}'.format(i))
t.define_models(dar)
mod = StarModel(dar, obs=t)
mod.fit_multinest(n_live_points=1000,
basename='test{}_bound'.format(i))
#if rank == 0:
f1 = open('evidence_bound2.txt','a')
evi = mod.evidence
evi = str(evi)
f1.write('case{}: '.format(i) + evi + '\n')
#mod.corner(['mass_0_0','mass_0_1','distance_0','AV_0'])
fig = mod.corner_physical(props=['mass', 'distance', 'AV'])
fig.savefig('test{}_bound_corner_physical.png'.format(i))
plt.close(fig)
fig = mod.corner_observed()
fig.savefig('test{}_bound_corner_observed.png'.format(i))
plt.close(fig)
else:
return str(n)
n = sys.argv[1]
i = get_index(n)
df = pd.read_csv('/tigress/np5/dataFrame/df_triplet_test{}.csv'.format(i))
#-------------------------------------------------------------------------------
#triplet0 - all in same system
dar = Dartmouth_Isochrone()
t = ObservationTree.from_df(df, name='test{}'.format(i))
t.define_models(dar)
mod = StarModel(dar, obs=t)
mod.fit_multinest(n_live_points=1000,
basename='/tigress/np5/chains/test{}_triplet0'.format(i))
#if rank == 0:
f1 = open('/tigress/np5/evidence_triplet0.txt','a')
evi = mod.evidence
evi = str(evi)
f1.write('case{}: '.format(i) + evi + '\n')
f1.close()
fig = mod.corner_physical(props=['mass', 'distance', 'AV'])
fig.savefig('/tigress/np5/figures/test{}_triplet0_corner_physical.png'.format(i))
plt.close(fig)
fig = mod.corner_observed()
fig.savefig('/tigress/np5/figures/test{}_triplet0_corner_observed.png'.format(i))
plt.close(fig)
#-------------------------------------------------------------------------------
else:
return str(n)
n = sys.argv[1]
i = get_index(n)
df = pd.read_csv('/tigress/np5/dataFrame/df_quad_test{}.csv'.format(i))
#-------------------------------------------------------------------------------
#quad0 - all in same system
dar = Dartmouth_Isochrone()
t = ObservationTree.from_df(df, name='test{}'.format(i))
t.define_models(dar)
mod = StarModel(dar, obs=t)
mod.fit_multinest(n_live_points=1000,
basename='/tigress/np5/chains/test{}_quad0'.format(i))
if rank == 0:
f1 = open('/tigress/np5/evidence_quad0.txt','a')
evi = mod.evidence
evi = str(evi)
f1.write('case{}: '.format(i) + evi + '\n')
f1.close()
fig = mod.corner_physical(props=['mass', 'distance', 'AV'])
fig.savefig('/tigress/np5/figures/test{}_quad0_corner_physical.png'.format(i))
plt.close(fig)
fig = mod.corner_observed()
fig.savefig('/tigress/np5/figures/test{}_quad0_corner_observed.png'.format(i))
plt.close(fig)
#-------------------------------------------------------------------------------
df = pd.read_csv('/tigress/np5/dataFrame/df_binary_test{}.csv'.format(i))
dar = Dartmouth_Isochrone()
t = ObservationTree.from_df(df, name='test{}'.format(i))
leaves = t._get_leaves()
boolean1 = np.isfinite(leaves[0].value[0])
boolean2 = np.isfinite(leaves[1].value[0])
boolean = boolean1 and boolean2
if boolean:
t.define_models(dar)
mod = StarModel(dar, obs=t)
mod.fit_multinest(n_live_points=1000,
basename='/tigress/np5/chains/test{}_bound'.format(i))
f1 = open('/tigress/np5/evidence_bound.txt','a')
evi = mod.evidence
evi = str(evi)
f1.write('case{}: '.format(i) + evi + '\n')
f1.close()
fig = mod.corner_physical(props=['mass', 'distance', 'AV'])
fig.savefig('/tigress/np5/figures/test{}_bound_corner_physical.png'.format(i))
plt.close(fig)
fig = mod.corner_observed()
fig.savefig('/tigress/np5/figures/test{}_bound_corner_observed.png'.format(i))
plt.close(fig)
#unassociated case
import pandas as pd
from isochrones.dartmouth import Dartmouth_Isochrone
from isochrones.observation import ObservationTree
from isochrones.starmodel import StarModel
from datetime import datetime
df = pd.read_csv('df.csv')
dar = Dartmouth_Isochrone()
t = ObservationTree.from_df(df, name='test-triplet')
t.define_models(dar, index=[0,0,1])
t.add_limit(logg=(3.0,None))
mod = StarModel(dar, obs=t)
startTime = datetime.now()
mod.fit_multinest(n_live_points=1000)
time = datetime.now() - startTime
evi = mod.evidence
print 'evidence = {}'.format(evi)
print 'total time = {}'.format(time)