ApJdataFrames Cottaar_2014Title: IN-SYNC I: Homogeneous Stellar Parameters from High-resolution APOGEE Spectra for Thousands of Pre-main Sequence Stars
Authors: Michiel Cottaar, Kevin R Covey, Michael R Meyer, David L Nidever, Keivan G. Stassun, Jonathan B Foster, Jonathan C Tan, S Drew Chojnowski, Nicola da Rio, Kevin M Flaherty, Peter M Frinchaboy, Michael Skrutskie, Steven R Majewski, John C Wilson, and Gail Zasowski
Data is from this paper:
http://iopscience.iop.org/article/10.1088/0004-637X/794/2/125/meta
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%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
pd.options.display.max_columns = 150
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import astropy
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from astropy.io import fits
hdulist1 = fits.open('../data/Cottaar2014/per_epoch.fit')
hdulist2 = fits.open('../data/Cottaar2014/per_star.fit')
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table1 = hdulist1[1]
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table1.columns
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table1.data.shape
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table1.size
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table1
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from astropy.table import Table
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tt = Table(data=table1.data)
tt.write('../data/Cottaar2014/per_epoch.csv', format='csv')
dat = pd.read_csv('../data/Cottaar2014/per_epoch.csv')
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dat.head()
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dat.columns
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sns.set_context('talk', font_scale=1.0)
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%config InlineBackend.figure_format = 'svg'
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dat.columns
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cmap = sns.cubehelix_palette(light=1, as_cmap=True)
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plt.figure(figsize=[10, 6])
sc = plt.scatter(dat['Teff'], dat['log(g)'], c=dat['R_H'], vmin=0, vmax=2, s=35, cmap=cmap, alpha=0.5)
plt.colorbar(sc)
plt.xlabel('$T_{eff}$')
plt.ylabel('$\log{g}$')
plt.title('Cottaar et al. 2014 APOGEE/INSYNC data')
plt.xlim(7000, 2500)
plt.ylim(5.5, 2.7)
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import numpy as np
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plt.figure(figsize=[6, 4])
plt.hist(dat['R_H'], bins=np.arange(0, 3, 0.15));
plt.xlabel('$R-H$')
plt.ylabel('$N$')
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Find a source with specific properties.
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Tfi = (dat.Teff > 4000) & (dat.Teff < 4200)
lgi = (dat['log(g)'] > 3.5) & (dat['log(g)'] < 4.0)
gi = Tfi & lgi
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dat.shape
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gi.sum()
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dat['2MASS'][gi]
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table2 = hdulist2[1]
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table2.columns
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table2.data.shape
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t2 = Table(data=table2.data)
t2.write('../data/Cottaar2014/per_star.csv', format='csv')
data = pd.read_csv('../data/Cottaar2014/per_star.csv')
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data.head()
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data.Cluster.unique()
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data.columns
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ic = data.Cluster == 'IC 348'
pl = data.Cluster == 'Pleiades'
Read in the Chabrier and Baraffe models
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bcah = pd.read_csv('../data/BCAH2002/BCAH2002_isochrones.csv', sep = '\t')
groups =bcah.groupby(by='Age')
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plt.figure(figsize=[10, 6])
plt.scatter(data['Teff'][ic], data['log(g)'][ic], label='IC 348', c='r')
plt.scatter(data['Teff'][pl], data['log(g)'][pl], label='Pleiades')
plt.xlabel('$T_{eff}$')
plt.ylabel('$\log{g}$')
plt.title('Cottaar et al. 2014 APOGEE/INSYNC data')
plt.legend(loc='best')
for age, group in groups:
no_decimal = np.abs(np.mod(age, 1)) <0.001
if no_decimal:
plt.plot(group.Teff, group.logg, 'k-', alpha=0.5, label='{:0.1f} Myr'.format(age))
plt.xlim(7000, 2500)
plt.ylim(5.5, 2.7)
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data.columns
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data.shape
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sns.distplot(data['R_H'][ic], hist=False, label='IC 348')
sns.distplot(data['R_H'][pl], hist=False, label='Pleiades')
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