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psflib minor bug fixes
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Ell Bogat committed Feb 20, 2025
1 parent c72bd4c commit 6706c5d
Showing 1 changed file with 54 additions and 31 deletions.
85 changes: 54 additions & 31 deletions spaceKLIP/psflib.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,6 @@
# - How finely to sample the OPD maps in time? Every 2 days?
# - Estimate computation time as a function of # of dates to compare


# imports
import os
import warnings
Expand Down Expand Up @@ -98,6 +97,8 @@ def decode_simbad_sptype(input_sptypes):

# TODO:
# - test this!
# - figure out all the weird edge cases or find documentation
# on SIMBAD spectypes

if isinstance(input_sptypes,str):
input_sptypes = [input_sptypes]
Expand All @@ -108,7 +109,14 @@ def decode_simbad_sptype(input_sptypes):
sp_lclasses = []

for simbad_spectype in input_sptypes:


if not isinstance(simbad_spectype,str):
warnings.warn('Spectral type decoder encountered a non-string spectral type. Skipping.')
sp_classes.append('')
sp_subclasses.append('')
sp_lclasses.append('')
continue

m = re.search(r'([OBAFGKMTY])(\d\.*\d*)[-+/]*(\d\.*\d*)*[-+/]*(I*V*I*)[-/]*(I*V*I*)',simbad_spectype)

if m is None:
Expand Down Expand Up @@ -201,10 +209,11 @@ def build_refdb(idir,odir='.',suffix='calints',overwrite=False,
calints file in the input directory.
Args:
idir (path): Path to pre-processed (stage 2) JWST images to be added
to the database
idir (str or list): Path to directory containing JWST images, or list of
individual file paths, to construct the database from.
odir (path, optional): Location to save the database. Defaults to '.'.
suffix (str, optional): Input filename suffix, e.g. 'uncal' or 'calints'. Defaults to 'calints'.
suffix (str, optional): Input filename suffix, e.g. 'uncal' or 'calints'.
Defaults to 'calints'. Does not apply if list of fpaths is provided to idir.
overwrite (bool, optional): If true, overwrite the existing caldb.
prefer_SIMBAD (bool, optional): Default to choosing database info SIMBAD as opposed to MOCA
database. Defaults to True.
Expand All @@ -216,14 +225,16 @@ def build_refdb(idir,odir='.',suffix='calints',overwrite=False,

# TODO:
# - describe each column & its units
# - write tests for build_refdb()
# - write tests for build_refdb()
# - directory vs filelist input
# - nonexistent input directory
# - empty input directory
# - no calints files in input directory
# - header kw missing
# - duplicate science target with different program names
# - synthetic PSFs
# - slightly wrong SIMBAD names
# - logic for if 'HAS_DISK','HAS_CANDS' have a mix of 'unknown' and bool values
# - think about how to incorporate synthetic PSFs, which wouldn't have a SIMBAD entry

# Check that you won't accidentally overwrite an existing csv.
outpath = os.path.join(odir,'ref_lib.csv')
Expand All @@ -239,9 +250,19 @@ def build_refdb(idir,odir='.',suffix='calints',overwrite=False,
# Read input files
log.info('Reading input files...')
suffix = suffix.strip('_')
fpaths = sorted(glob.glob(os.path.join(idir,f"*_{suffix}.fits")))
if len(fpaths) == 0:
raise Exception(f'No "{suffix}" files found in input directory {idir} .')
if isinstance(idir,str):
fpaths = sorted(glob.glob(os.path.join(idir,f"*_{suffix}.fits")))
if len(fpaths) == 0:
raise Exception(f'No "{suffix}" files found in input directory {idir} .')
elif isinstance(idir,list):
fpaths = idir
for path in fpaths:
if not (f'{suffix}.fits' in path and os.path.exists(path)):
fpaths.remove(path)
if len(fpaths) == 0:
raise Exception(f'No existing "{suffix}" files found in input file list.')



# Start a dataframe with the header info we want from each file
csv_list = []
Expand Down Expand Up @@ -280,23 +301,26 @@ def build_refdb(idir,odir='.',suffix='calints',overwrite=False,
# Make a df with only one entry for each unique target
targnames = np.unique(df['TARGNAME'])
df_unique = pd.DataFrame(np.transpose([targnames]),columns=['TARGNAME'])

# Get 2MASS IDs
log.info('Collecting SIMBAD IDs...')
i = 0
simbad_ids = []
for targname in targnames:
result_table = Simbad.query_objectids(targname)
#display(result_table)
if result_table is None:
simbad_ids.append('')
warnings.warn(f'No SIMBAD object found for targname {targname}, this is likely a synthetic PSF.')

if result_table is None or len(result_table)==0:
simbad_ids.append(f'UNKNOWN STAR {i}')
i += 1
warnings.warn(f'No SIMBAD object found for targname {targname}, this is likely a synthetic PSF.')
continue

gaia_ids_found = []
for name in list(result_table['ID']):
if name.startswith('Gaia DR3'):
gaia_ids_found.append(name)
if len(gaia_ids_found) == 1:
simbad_ids.extend(gaia_ids_found)
if len(gaia_ids_found) < 1:
elif len(gaia_ids_found) < 1:
simbad_ids.append(list(result_table['ID'])[0])
else:
raise Exception(f'Multiple Gaia DR3 IDs found for targname {targname}: {gaia_ids_found}')
Expand All @@ -312,14 +336,19 @@ def build_refdb(idir,odir='.',suffix='calints',overwrite=False,
'flux(K)', 'flux_error(K)',
'plx', 'plx_error')
simbad_list = list(df_unique.index)
while "" in simbad_list:
simbad_list.remove("")
scistar_simbad_table = customSimbad.query_objects(simbad_list)
short_simbad_list = list(df_unique.index)
for st_name in short_simbad_list:
if st_name.startswith('UNKNOWN STAR'):
short_simbad_list.remove(st_name)
scistar_simbad_table = customSimbad.query_objects(short_simbad_list)

# Convert to pandas df and make SIMBAD IDs the index
df_simbad = scistar_simbad_table.to_pandas()
df_simbad['SIMBAD_ID'] = simbad_list
df_simbad.set_index('SIMBAD_ID',inplace=True)
short_df_simbad = scistar_simbad_table.to_pandas()
short_df_simbad['SIMBAD_ID'] = short_simbad_list
short_df_simbad.set_index('SIMBAD_ID',inplace=True)
# Add empty rows for stars not in SIMBAD (e.g. synthetic PSFs)
df_simbad = pd.DataFrame(index=simbad_list, columns=short_df_simbad.columns, dtype='object')
df_simbad.loc[short_df_simbad.index] = short_df_simbad.values

# Rename some columns
simbad_cols = { # Full column list here: http://simbad.u-strasbg.fr/Pages/guide/sim-fscript.htx
Expand Down Expand Up @@ -359,10 +388,12 @@ def build_refdb(idir,odir='.',suffix='calints',overwrite=False,
df_unique['COMMENTS'] = ''
df_unique['DB_SOURCES'] = ''

# Sort all the dfs by index so they match up
# Sort all the dfs by index and check that they match up
df_unique.sort_index(inplace=True)
df_simbad.sort_index(inplace=True)
mdf.sort_index(inplace=True)
assert np.all(np.array(df_unique.index)==np.array(df_simbad.index)), "Index Error"
assert np.all(np.array(df_unique.index)==np.array(mdf.index)), "Index Error"

# Replace values and update DB_SOURCES column
cols_overlap = list(set(list(simbad_cols.keys())).intersection(list(moca_cols.keys())))
Expand All @@ -381,14 +412,6 @@ def build_refdb(idir,odir='.',suffix='calints',overwrite=False,
df_unique[col] = mdf[col]
df_unique.loc[~isnone(mdf[col]),'DB_SOURCES'] += f"{col} adopted from MOCA. "

# # Replace values
# df_unique.loc[df_unique['SPTYPE']=='','SPTYPE'] = None
# df_unique_replaced = df_unique.loc[:,cols_overlap].combine_first(mdf.loc[:,cols_overlap])
# df_unique.loc[:,cols_overlap] = df_unique_replaced.loc[:,cols_overlap]
# cols_overlap = ['SPTYPE','PLX','PLX_ERR']
# df_unique.loc[isnone(df_unique.loc[:,cols_overlap]),cols_overlap] = mdf.loc[isnone(df_unique.loc[:,cols_overlap]),cols_overlap]
# df_unique.loc[:,cols_overlap].where(not_isnone,other=mdf,inplace=True)

# Calculate distances from plx in mas
df_unique['DIST'] = 1. / (df_unique['PLX'] / 1000)
df_unique['DIST_ERR'] = df_unique['PLX_ERR'] / 1000 / ((df_unique['PLX'] / 1000)**2)
Expand Down

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