Finish wireup of HIP1 and TYC2 supplement 1 data

celestia_gaia/make_stardb.py

@@ -33,7 +33,7 @@
 from .spparse import CEL_UNKNOWN_STAR, parse_spectrum
 from .utils import WorkaroundCDSReader, open_cds_tarfile
 
-VERSION = "1.1.0-beta.1"
+VERSION = "1.1.0"
 
 # remove the following objects from the output
 
@@ -234,7 +234,7 @@ def merge_all() -> Table:
         data['HIP'] < 1000000,
         data['HIP'],
         make_tyc(data['HIP']//1000000, (data['HIP']//10) % 100000, data['HIP']%10)
-    ).astype('uint32')
+    ).astype(np.uint32)
 
     data['bp_rp'] = data['phot_bp_mean_mag'] - data['phot_rp_mean_mag']
 

celestia_gaia/parse_hip.py

@@ -19,15 +19,18 @@
 
 import warnings
 
-import astropy.io.ascii as io_ascii
-import astropy.units as u
-import numpy as np
 from astropy.coordinates import ICRS, SkyCoord
+import astropy.io.ascii as io_ascii
 from astropy.table import Table, join, unique
+from astropy.table.column import MaskedColumn
 from astropy.time import Time
+import astropy.units as u
+
 from erfa import ErfaWarning
 
-from .directories import AUXFILES_DIR, VIZIER_DIR, XMATCH_DIR
+import numpy as np
+
+from .directories import AUXFILES_DIR, GAIA_EDR3_DIR, VIZIER_DIR, XMATCH_DIR
 from .utils import open_cds_tarfile
 
 
@@ -64,6 +67,20 @@ def load_xhip() -> Table:
         return join(hip_data, biblio_data, join_type='left', keys='HIP')
 
 
+def load_hip1() -> Table:
+    """Load data for HIP1 stars."""
+    print("Loading HIP1 data")
+    data = Table.read(GAIA_EDR3_DIR/'hip1_subset.vot.gz', format='votable')
+    data.remove_columns(['rahms', 'dedms', 'hpmag'])
+    data.rename_columns(
+        ['hip', 'hd', 'vmag', 'b_v', 'e_b_v', 'v_i', 'e_v_i', 'sptype'],
+        ['HIP', 'HD', 'Vmag', 'B-V', 'e_B-V', 'V-I', 'e_V-I', 'SpType'],
+    )
+    data['SpType'] = data['SpType'].astype(np.str)
+    data['SpType'].mask = data['SpType'] == ''
+    return data
+
+
 def load_tyc2specnew() -> Table:
     """Load revised spectral types."""
     print("Loading revised TYC2 spectral types")
@@ -167,6 +184,25 @@ def process_hip(data: Table) -> Table:
         metadata_conflicts='silent',
     )
 
+    data = join(
+        data,
+        load_hip1(),
+        keys=['HIP'],
+        join_type='left',
+        table_names=['gaia', 'hip1'],
+    )
+
+    for hip1_col in [c for c in data.colnames]:
+        if not hip1_col.endswith('_hip1'):
+            continue
+        base_col = hip1_col[:-5]
+        gaia_col = base_col + '_gaia'
+        data[base_col] = MaskedColumn(
+            data[gaia_col].filled(data[hip1_col]),
+            mask=np.logical_and(data[hip1_col].mask, data[gaia_col].mask)
+        )
+        data.remove_columns([hip1_col, gaia_col])
+
     data = join(data, load_sao(), keys=['HIP'], join_type='left')
 
     data['r_gaia_score'] = np.where(

celestia_gaia/parse_tyc.py

@@ -166,6 +166,28 @@ def load_ascc() -> Table:
     return data
 
 
+def load_tyc2_suppl1() -> Table:
+    """Loads the Tycho-2 supplement 1 data."""
+    print('Loading TYC2 supplement 1')
+    reader = io_ascii.get_reader(
+        io_ascii.Cds,
+        readme=str(VIZIER_DIR/'tyc2.readme'),
+        include_names=['TYC1', 'TYC2', 'TYC3', 'BTmag', 'VTmag']
+    )
+    reader.data.table_name = 'suppl_1.dat'
+    with gzip.open(VIZIER_DIR/'tyc2suppl_1.dat.gz') as gzf:
+        data = reader.read(gzf)
+
+    parse_tyc_cols(data)
+    data = data[np.logical_not(np.logical_and(data['VTmag'].mask, data['BTmag'].mask))]
+    # Magnitude transformation formulae from Section 2.2 "Contents of the Tycho Catalogue"
+    data['BT-VT'] = data['BTmag'] - data['VTmag']
+    data['Vmag'] = data['VTmag'] - 0.090*data['BT-VT']
+    data['Bmag'] = data['Vmag'] + 0.850*data['BT-VT']
+    data.remove_columns(['BTmag', 'VTmag', 'BT-VT'])
+    return data
+
+
 def load_tyc_hd() -> Table:
     """Load the Tycho-HD cross index."""
     print('Loading TYC-HD cross index')
@@ -278,6 +300,7 @@ def process_tyc(data: Table) -> Table:
         table_names=('gaia', 'tspec'),
         metadata_conflicts='silent',
     )
+
     data = join(
         data, load_ascc(),
         keys=['HIP'],
@@ -300,12 +323,32 @@ def process_tyc(data: Table) -> Table:
         data[base_col] = MaskedColumn(data[base_col].filled(data[ascc_col]), mask=mask)
         data.remove_column(ascc_col)
 
+    data = join(
+        data, load_tyc2_suppl1(),
+        keys=['HIP'],
+        join_type='left',
+        table_names=['gaia', 'tyc2s1'],
+        metadata_conflicts='silent',
+    )
+
+    data['Vmag'] = MaskedColumn(
+        data['Vmag_gaia'].filled(data['Vmag_tyc2s1']),
+        mask=np.logical_and(data['Vmag_gaia'].mask, data['Vmag_tyc2s1'].mask),
+    )
+
+    data['Bmag'] = MaskedColumn(
+        data['Bmag_gaia'].filled(data['Bmag_tyc2s1']),
+        mask=np.logical_and(data['Bmag_gaia'].mask, data['Bmag_tyc2s1'].mask),
+    )
+
+    data.remove_columns(['Vmag_gaia', 'Vmag_tyc2s1', 'Bmag_gaia', 'Bmag_tyc2s1'])
+
     data = join(
         data, load_tyc_hd(),
         keys=['HIP'],
         join_type='left',
         table_names=['gaia', 'hd'],
-        metadata_conflicts='silent'
+        metadata_conflicts='silent',
     )
     data['HD'] = MaskedColumn(data['HD_hd'].filled(data['HD_gaia'].filled(0)))
     data['HD'].mask = data['HD'] == 0