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parse_harris_1996ed2010.py
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parse_harris_1996ed2010.py
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import sys
import logging
import numpy as np
import pandas as pd
from astropy import units as u
from astropy.coordinates import SkyCoord
logger = logging.getLogger("console")
logger.logLevel = logging.DEBUG
BASEDIR = "/".join(__file__.split("/")[:-1]) + "/MW_GCS_Harris1996e2010/"
class Cluster(object):
def __init__(self, logger):
self.logger = logger
# General
self.gid = "" # Cluster identification
self.name = None # Other commonly used cluster name
# Coordinates
self.ra = None # Right ascension (Epoch J2000)
self.dec = None # Declination (Epoch J2000)
self.longitude = None # Galactic longitude (Degrees)
self.latitude = None # Galactic latitude (Degrees)
self.dist_from_sun = None # Distance from sum (kpc)
self.dist_from_gal_cen = None # Distance from galactic center (kpc)
self.X = None # Galactic distance component X (kpc)
self.Y = None # Galactic distance component Y (kpc)
self.Z = None # Galactic distance component Z (kpc)
# Metallicity
self.metallicity = None # Metallicity [Fe/H]
self.w_mean_met = None # Weight of mean metallicity
# Photometry
self.eb_v = None # Foreground reddening, E(B-V)
self.v_hb = None # V magnitude level of the HB, V_HB
self.app_vd_mod = None # Apparent visual distance modulus, (m-M)V
self.v_t = None # Integrated V magnitude, V_t
self.m_v_t = None # Cluster luminosity, M_V,t = V_t - (m-M)V
self.ph_u_b = None # U-B
self.ph_b_v = None # B-V
self.ph_v_r = None # V-R
self.ph_v_i = None # V-i
self.spt = "" # Spectral type
self.ellipticity = None # Projected ellipticity of isophotes, e = 1-(b/a)
# Velocities
self.v_r = None # Heliocentric radial velocity (km/s)
self.v_r_err = None # Observational uncertainty in radial velocity
self.c_LSR = None # Radial velocity relative to solar neighbourhood
self.sig_v = None # Central velocity dispersion (km/s)
self.sig_v_err = None # Observational uncertainty in velocity dispersion
# Structural parameters
self.sp_c = None # King-model central concentration, c=log(r_t/r_c)
self.sp_r_c = None # Core radius (arcmin)
self.sp_r_h = None # Half-light radius (arcmin)
self.sp_mu_V = None # Central surface brightness (V magnitudes per arcsec^2)
self.sp_rho_0 = None # Central luminosity density, log_10(solar_lum/pc^3)
self.sp_lg_tc = None # Core relaxation time t(r_c) in log_10(yr)
self.sp_lg_th = None # Mean relaxation time t(r_h) in log_10(yr)
def fill_in(self, do):
if self.name:
do.name = self.name
if self.ra:
do.ra = self.ra
do.dec = self.dec
if self.longitude:
do.gallon = self.longitude
do.gallat = self.latitude
if self.dist_from_sun:
do.dfs = self.dist_from_sun
if self.dist_from_gal_cen:
do.dfgc = self.dist_from_gal_cen
do.x_helio = self.X
do.y_helio = self.Y
do.z_helio = self.Z
if self.metallicity:
do.metallicity = self.metallicity
if self.eb_v:
do.ebv = self.eb_v
if self.v_t:
do.MVt = self.v_t
if self.m_v_t:
do.L = self.m_v_t
if self.ellipticity:
do.ellipticity = self.ellipticity
if self.v_r:
do.v_r = self.v_r
do.ev_r = self.v_r_err
if self.sig_v:
do.sig_v = self.sig_v
do.esig_v = self.sig_v_err
if self.sp_c:
do.c = self.sp_c
if self.sp_r_c:
do.r_c = self.sp_r_c
if self.sp_r_h:
do.r_h = self.sp_r_h
if self.sp_mu_V:
do.muV = self.sp_mu_V
def parse_harris1996ed2010(logger, debug=False, save_as_xlsx=False):
if debug:
logger.debug("\nParsing Harris 1996, 2010 ed.\n")
cluster_list = {}
def read_float(s):
try:
val = float(s.strip())
except:
val = None
return val
def read_str(s):
s = s.strip()
return None if s == "" else s
df = pd.DataFrame(columns=["cname", "altname", "RA", "Dec", "L", "B", "R_Sun",
"r_c", "r_h", "c", "[Fe/H]", "E(B-V)", "sig_v",
"esig_v", "ellip", "mu_V", "V_r", "eV_r",
"V_t"])
# Ruler for f1
#0 1 2 3 4 5 6 7 8 9 100
#01234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890
# NGC 104 47 Tuc 00 24 05.67 -72 04 52.6 305.89 -44.89 4.5 7.4 1.9 -2.6 -3.1
# Parsing first file
f1 = open(BASEDIR+"/f1.dat")
df1 = pd.DataFrame(columns=["cname", "altname", "RA", "Dec", "L", "B", "R_Sun"])
for line in f1:
c = Cluster(logger)
c.gid = line[:12].strip()
c.name = read_str(line[12:25])
ra_str = read_str(line[25:38])
dec_str = read_str(line[38:50])
c.longitude = read_float(line[50:58])
c.latitude = read_float(line[58:66])
c.dist_from_sun = read_float(line[66:73])
c.dist_from_gal_cen = read_float(line[73:79])
c.X = read_float(line[79:85])
c.Y = read_float(line[85:91])
c.Z = read_float(line[91:])
coo = SkyCoord(ra=ra_str, dec=dec_str, unit=(u.hourangle, u.degree))
c.ra = np.round(coo.ra.deg,4)
c.dec = np.round(coo.dec.deg,4)
df1.loc[c.gid] = pd.Series({"cname": c.gid,
"altname": c.name,
"RA": c.ra,
"Dec": c.dec,
"L": c.longitude,
"B": c.latitude,
"R_Sun": c.dist_from_sun,
})
cluster_list[c.gid] = c
f1.close()
# Ruler for f2
#0 1 2 3 4 5 6 7 8 9 100
#01234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890
# NGC 104 -0.72 10 0.04 14.06 13.37 3.95 -9.42 0.37 0.88 0.53 1.14 G4 0.09
# Now parsing second file
f2 = open(BASEDIR+"f2.dat")
df2 = pd.DataFrame(columns=["[Fe/H]", "E(B-V)", "ellip", "V_t"])
for line in f2:
gid = line[:12].strip()
c = cluster_list[gid]
c.metallicity = read_float(line[13:18])
c.w_mean_met = read_float(line[18:21])
c.eb_v = read_float(line[21:28])
c.v_hb = read_float(line[28:34])
c.app_vd_mod = read_float(line[34:40])
c.v_t = read_float(line[40:46])
c.m_v_t = read_float(line[46:53])
c.ph_u_b = read_float(line[53:60])
c.ph_b_v = read_float(line[60:66])
c.ph_v_r = read_float(line[66:72])
c.ph_v_i = read_float(line[72:78])
c.spt = read_str(line[78:82])
c.ellipticity = read_float(line[82:])
df2.loc[gid] = pd.Series({"[Fe/H]": c.metallicity,
"E(B-V)": c.eb_v,
"V_t": c.v_t,
"ellip": c.ellipticity,
})
f2.close()
# Ruler for f3
#0 1 2 3 4 5 6 7 8 9 100
#01234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890
# NGC 104 -18.0 0.1 -26.7 11.0 0.3 2.07 0.36 3.17 14.38 4.88 7.84 9.55
f3 = open(BASEDIR+"f3.dat")
df3 = pd.DataFrame(columns=["r_c", "r_h", "c", "sig_v", "esig_v", "mu_V", "V_r", "eV_r"])
for line in f3:
gid = line[:12].strip()
c = cluster_list[gid]
c.v_r = read_float(line[12:19])
c.v_r_err = read_float(line[19:25])
c.c_LSR = read_float(line[25:33])
c.sig_v = read_float(line[33:41])
c.sig_err = read_float(line[41:47])
c.sp_c = read_float(line[47:54])
c.sp_r_c = read_float(line[54:64])
c.sp_r_h = read_float(line[64:70])
c.sp_mu_V = read_float(line[70:78])
c.rho_0 = read_float(line[78:85])
c.lg_tc = read_float(line[85:92])
c.lg_th = read_float(line[92:])
df3.loc[gid] = pd.Series({"V_r": c.v_r,
"eV_r": c.v_r_err,
"sig_v": c.sig_v,
"esig_v": c.sig_v_err,
"c": c.sp_c,
"r_c": c.sp_r_c,
"r_h": c.sp_r_h,
"mu_V": c.sp_mu_V,
})
f3.close()
df = pd.concat([df1, df2, df3], axis=1)
if save_as_xlsx:
try:
import openpyxl
writer = pd.ExcelWriter("output.xlsx")
df.to_excel(writer, "Harris")
writer.save()
except ImportError:
logger.error("ERROR: Use 'pip install openpyxl' to save Harris data to xlsx")
do_continue = input("Press any key to continue...")
if debug:
logger.debug(df)
return cluster_list
if __name__ == "__main__":
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format="%(message)s")
logger = logging.getLogger(__file__)
logger.info("Running {0}".format(__file__))
cluster_list = parse_harris1996ed2010(logger, debug=True, save_as_xlsx=False)