In [1]:

    

import numpy as np
import splat
import wisps
import pandas as pd
from scipy import stats
import numba


    

In [2]:

    

stype='std'


    

In [3]:

    

spex_df=pd.read_pickle(wisps.OUTPUT_FILES+'/'+str(stype)+'spex_sample.pkl' )


    

In [4]:

    

spex_df.shape


    

    
Out[4]:





(2649, 3)

In [5]:

    

forbidden=['J0148+1202',  'J0331+4130', 'J0338-4409', 'J0343+3155',
' J0344+3204', '0344+3200', 'J0344+3156', 'J0344+3203',
'J0345+3205','J0419+2712', 'J0435+2254','J0438+2519',
'J0448-4432', 'J0448-4432', 'J0501-3341', 'J0512-2949',
'J0610-2151','J0621+6558','J0624-1045', 'J0628-0959',
'J0815+1041','J0822+1700', 'J0935+0019','J0950+0540',
'J1004+5023','J1050-2940','J1132-3018','J1132-3018',
'J1132-3018','J1132-3018','J1132-3018','J1132-3018',
'J1132-3018','J1132-3018', 'J1132-3018','J1132-3018',
'J1138-1314','J1209-3041','J1211-2821','J1224-2744',
'J1257-0204','J1303+2351','J1312+0051','J1317-1427',
'J1325-2128', 'J1420-1752', 'J1423+0116','J1629+1415',
'J1642-2355','J1642-2355','J1659+3515','J1726-1158',
'J1729+4352','J1829+5032','J1839-3744','J1924+5506',
'J1932+0133', 'J1932-3921', 'J1945-4149', 'J2001-3805',
'J2024-3422', 'J2028+6925', 'J2034+6727','J2151-3349']


    

In [6]:

    

spex_df


    

    
Out[6]:







  

    

      

      
splat
      
wisps
      
shortname
    
  
  

    

      
0
      
SPEX-PRISM spectrum of 2MASS J0000286-124515
      
anon spectrum
      
J0000-1245
    
    

      
1
      
SPEX-PRISM spectrum of 2MASS J0000286-124515
      
anon spectrum
      
J0000-1245
    
    

      
2
      
SPEX-PRISM spectrum of SDSS J000112.18+153535.5
      
anon spectrum
      
J0001+1535
    
    

      
3
      
SPEX-PRISM spectrum of 2MASS J00013044+1010146
      
anon spectrum
      
J0001+1010
    
    

      
4
      
SPEX-PRISM spectrum of WISE J000131.93-084126.9
      
anon spectrum
      
J0001-0841
    
    

      
...
      
...
      
...
      
...
    
    

      
2644
      
SPEX-PRISM spectrum of SSSPM J2356-3426
      
anon spectrum
      
J2356-3426
    
    

      
2645
      
SPEX-PRISM spectrum of 2MASSI J2356547-155310
      
anon spectrum
      
J2356-1553
    
    

      
2646
      
SPEX-PRISM spectrum of WISE J235716.49+122741.8
      
anon spectrum
      
J2357+1227
    
    

      
2647
      
SPEX-PRISM spectrum of 2MASS J23590855+2338326
      
anon spectrum
      
J2359+2338
    
    

      
2648
      
SPEX-PRISM spectrum of SSSPM J2400-2008
      
anon spectrum
      
J2359-2007
    
  

2649 rows × 3 columns

In [7]:

    

spex_df['shortname']=spex_df.splat.apply(lambda x:x.shortname)


    

In [8]:

    

spex_df=(spex_df[~ spex_df.shortname.isin(forbidden)]).reset_index(drop=True)


    

In [9]:

    

spex_df.shape


    

    
Out[9]:





(2566, 3)

In [10]:

    

def add_new_columns(row):
    return pd.concat([pd.Series(row.wisps.indices), pd.Series(row.wisps.snr)])


    

In [11]:

    

indices=pd.DataFrame(spex_df.apply(add_new_columns, axis=1))
#snr=pd.DataFrame(spex_df.apply(add_new_columns, axis=1))


    

In [12]:

    

all_spex=splat.searchLibrary(vlm=True, giant=False)


    

In [13]:

    

spex_df['data_file']=[x.data_file for x in spex_df.splat]


    

In [14]:

    

all_spex.columns=[x.lower() for x in all_spex.columns]


    

In [15]:

    

merged=spex_df.merge(all_spex, on='data_file', how='inner')


    

In [16]:

    

for c in ['shortname', 'wisps', 'data_file', 'metallicity_class', 'gravity_class_nir', 'sbinary', 'h_2mass', 'j_2mass' ]:
          indices[c]=merged[c]


    

In [17]:

    

indices['f_test']=(indices['wisps']).apply(lambda x: x.f_test)
indices['line_chi']=(indices['wisps']).apply(lambda x: x.line_chi)
indices['spex_chi']=(indices['wisps']).apply(lambda x: x.spex_chi)
indices['spt']=(indices['wisps']).apply(lambda x: x.spectral_type)


    

In [18]:

    

indices.drop( columns='wisps').to_pickle(wisps.LIBRARIES+'/spex_data_set_table.pkl')


    

In [ ]: