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analysis3.py
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analysis3.py
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import pandas as pd
from isochrones.dartmouth import Dartmouth_Isochrone
from isochrones.starmodel import StarModel
from isochrones.observation import ObservationTree
import numpy as np
df_data = pd.DataFrame()
for i in range(6000,7000,1):
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))
t.define_models(dar, index=[0,1])
mod = StarModel(dar, obs=t)
mod.fit_multinest(n_live_points=1000,
basename='/tigress/np5/chains/test{}_unassociated'.format(i))
M1 = mod.samples.mass_0_0.median()
M2 = mod.samples.mass_1_0.median()
distance1 = mod.samples.distance_0.median()
distance2 = mod.samples.distance_1.median()
index = 'case'+str(i)
df_data = df_data.append(pd.DataFrame({'M1_fit':M1,
'M2_fit':M2,
'distance1_fit':distance1,
'distance2_fit':distance2},index=[index]))
df_data.to_csv(path_or_buf='/tigress/np5/df_fit_params.csv')