read_ybc.py

import numpy as np
import pandas as pd

__all__ = ['readYBC']


def readYBC(filename='bsc5.dat', path=None):
	"""Read in the Yale Bright Star Catalog. Originally downloaded from:
	http://tdc-www.harvard.edu/catalogs/bsc5.html
	"""

	names = ['HR', 'Name', 'DM', 'HD', 'SAO', 'FK5', 'IRflag', 'r_IRflag', 'Multiple','ADS', 'ADScomp', 'VarID',
			 'RAh1900', 'RAm1900', 'RAs1900', 'DE-1900', 'DEd1900', 'DEm1900', 'DEs1900', 'RAh', 'RAm', 'RAs',
			 'DE-', 'DEd', 'DEm', 'DEs', 'GLON', 'GLAT', 'Vmag', 'n_Vmag', 'u_Vmag', 'B-V', 'u_B-v', 'U-B',
			 'u_U-B', 'R-I', 'n_R-I', 'SpType', 'n_SpType', 'pmRA', 'pmDE', 'pmDE', 'Parallax', 'RadVel',
			 'n_RadVel', 'l_RotVel', 'RotVel', 'u_RotVel', 'Dmag', 'Sep', 'MultID', 'MultCnt',
			 'NoteFlag']

	colspecs = [(0, 3), (4, 13), (14, 24), (25, 30), (31, 36), (37, 40), (41, 41), (42, 42),
				(43, 43), (44, 48), (49, 50), (51, 59), (60, 61), (62, 63), (64, 67), (68, 68),
				(69, 70), (71, 72), (73, 74), (75, 76), (77, 78), (79, 82), (83, 83), (84, 85),
				(86, 87), (88, 89), (90, 95), (96, 101), (102, 106), (107, 107), (108, 108),
				(109, 113), (114, 114), (115, 119), (120, 120), (121, 125), (126, 126), (127, 146),
				(147, 147), (148, 153), (154, 159), (160, 160), (161, 165), (166, 169), (170, 173),
				(174, 175), (176, 178), (179, 179), (180, 183), (184, 189), (190, 193), (194, 195),
				(196, 196)]
	fix_colspecs = [(spec[0], spec[1]+1) for spec in colspecs]

	# data = pd.read_fwf(file, names=names, colspecs=fix_colspecs) # Doesn't work with pandas 0.25.3
	data = pd.read_fwf(filename, colspecs=fix_colspecs, header=None) # So just read it in without names...
	data.columns = names # ...and add the column names afterwards
	data['RA'] = (data['RAh'] + data['RAm']/60. + data['RAs']/3600.)*360./24.
	data['Dec'] = data['DEd'] + data['DEm']/60. + data['DEs']/3600.
	sign = np.ones(data['RAh'].size)
	sign[np.where(data['DE-'] == '-')] *= -1
	data['Dec'] = data['Dec'] * sign

	return data