def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/HIP.fits')
data = fits.getdata(catfile)
mask = data['HIP'] > 0
data = data[mask]
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_hip.png', size=1, alpha=0.2)
# plot magnitude histogram
mask = np.isnan(data['Vmag'])
vmag = data[~mask]['Vmag']
plot_histogram(
vmag,
bins=np.arange(-2, 16),
figfile='maghist_hip.png',
xlabel='$V$',
xticks=np.arange(-2, 17, 2),
)
#---------------------------------------------------------------------------
# plot HRD
mask1 = ~np.isnan(data['Plx'])
mask2 = ~np.isnan(data['B-V'])
data = data[mask1 * mask2]
mask = data['Plx'] > 0
data = data[mask]
Mv = data['Vmag'] - 5 * np.log10(1000. / data['Plx']) + 5
Teff = _BV_to_Teff_Flower1996(data['B-V'])
mask = Teff > 0
Teff = Teff[mask]
BC = np.array([_Teff_to_BC_Flower1996(t) for t in Teff])
Mbol = Mv[mask] + BC
logL = 0.4 * (4.74 - Mbol)
plot_histogram2d(
Teff,
logL,
xbins=np.arange(3000, 12001, 100),
ybins=np.arange(-2, 4.01, 0.1),
xlabel='$T_\mathrm{eff}$ (K)',
ylabel='$\log(L/L_\odot)$',
figfile='hrdhist_hip.png',
reverse_x=True,
scale='log',
)
def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/HIP.fits')
data = fits.getdata(catfile)
mask = data['HIP']>0
data = data[mask]
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_hip.png', size=1, alpha=0.2)
# plot magnitude histogram
mask = np.isnan(data['Vmag'])
vmag = data[~mask]['Vmag']
plot_histogram(vmag,
bins = np.arange(-2, 16),
figfile = 'maghist_hip.png',
xlabel ='$V$',
xticks = np.arange(-2, 17, 2),
)
#---------------------------------------------------------------------------
# plot HRD
mask1 = ~np.isnan(data['Plx'])
mask2 = ~np.isnan(data['B-V'])
data = data[mask1*mask2]
mask = data['Plx']>0
data = data[mask]
Mv = data['Vmag'] - 5*np.log10(1000./data['Plx']) + 5
Teff = _BV_to_Teff_Flower1996(data['B-V'])
mask = Teff>0
Teff=Teff[mask]
BC = np.array([_Teff_to_BC_Flower1996(t) for t in Teff])
Mbol = Mv[mask] + BC
logL = 0.4*(4.74-Mbol)
plot_histogram2d(Teff, logL,
xbins = np.arange(3000, 12001, 100),
ybins = np.arange(-2, 4.01, 0.1),
xlabel = '$T_\mathrm{eff}$ (K)',
ylabel = '$\log(L/L_\odot)$',
figfile = 'hrdhist_hip.png',
reverse_x = True,
scale = 'log',
)
def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/KIC.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_kic.png', size=1, alpha=0.2)
# plot magnitude histogram
mask = np.isnan(data['kepmag'])
kpmag = data['kepmag'][~mask]
plot_histogram(
kpmag,
bins=np.arange(0, 26),
figfile='maghist_kic.png',
xlabel='$K_\mathrm{p}$ Magnitude',
xticks=np.arange(0, 27, 2),
)
#---------------------------------------------------------------------------
# plot HRD
mask1 = np.isnan(data['Teff'])
mask2 = np.isnan(data['logg'])
mask3 = (~mask1) * (~mask2)
data3 = data[mask3]
Teff = data3['Teff']
logg = data3['logg']
plot_histogram2d(
Teff,
logg,
xbins=np.arange(3000, 12001, 100),
ybins=np.arange(0, 6.01, 0.1),
xlabel='$T_\mathrm{eff}$ (K)',
ylabel='$\log{g}$',
figfile='kielhist_kic.png',
reverse_x=True,
reverse_y=True,
scale='log',
)
def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/SAO.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_sao.png', size=1, alpha=0.2)
# plot magnitude histogram
mask = np.isnan(data['Vmag'])
vmag = data[~mask]['Vmag']
plot_histogram(vmag,
bins = np.arange(0, 13),
figfile = 'maghist_sao.png',
xlabel = '$V$',
xticks = np.arange(0, 13, 2),
)
def main():
ra_lst = np.array([])
dec_lst = np.array([])
kp_lst = np.array([])
teff_lst = np.array([])
logg_lst = np.array([])
for i in range(1,7):
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/EPIC_%d.fits'%i)
data = fits.getdata(catfile)
mask = data['EPIC']>0
# plot skymap
ra_lst = np.append(ra_lst, data[mask]['RAdeg'])
dec_lst = np.append(dec_lst, data[mask]['DEdeg'])
kp_lst = np.append(kp_lst, data[mask]['kepmag'])
mask1 = data['Teff']>0
teff_lst = np.append(teff_lst, data[mask1]['Teff'])
logg_lst = np.append(logg_lst, data[mask1]['logg'])
plot_skymap(ra_lst, dec_lst, 'skymap_epic.png', size=1, alpha=0.01)
plot_histogram(kp_lst,
bins = np.arange(0, 20),
figfile = 'maghist_epic.png',
xlabel = '$K_\mathrm{p}$',
xticks = np.arange(0, 21, 2),
)
# plot Kiel histogram
plot_histogram2d(teff_lst, logg_lst,
xbins = np.arange(2000, 12001, 100),
ybins = np.arange(0, 6.01, 0.1),
xlabel = '$T_\mathrm{eff}$ (K)',
ylabel = '$\log{g}$',
figfile = 'kielhist_epic.png',
reverse_x = True,
reverse_y = True,
scale = 'log',
)
def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/KIC.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_kic.png', size=1, alpha=0.2)
# plot magnitude histogram
mask = np.isnan(data['kepmag'])
kpmag = data['kepmag'][~mask]
plot_histogram(kpmag,
bins = np.arange(0, 26),
figfile = 'maghist_kic.png',
xlabel ='$K_\mathrm{p}$ Magnitude',
xticks = np.arange(0, 27, 2),
)
#---------------------------------------------------------------------------
# plot HRD
mask1 = np.isnan(data['Teff'])
mask2 = np.isnan(data['logg'])
mask3 = (~mask1)*(~mask2)
data3 = data[mask3]
Teff = data3['Teff']
logg = data3['logg']
plot_histogram2d(Teff, logg,
xbins = np.arange(3000, 12001, 100),
ybins = np.arange(0, 6.01, 0.1),
xlabel = '$T_\mathrm{eff}$ (K)',
ylabel = '$\log{g}$',
figfile = 'kielhist_kic.png',
reverse_x = True,
reverse_y = True,
scale = 'log',
)
def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/BSC.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_bsc.png', size=2, alpha=0.7)
# plot magnitude histogram
mask = np.isnan(data['Vmag'])
vmag = data[~mask]['Vmag']
plot_histogram(
vmag,
bins=np.arange(-2, 10),
figfile='maghist_bsc.png',
xlabel='$V$',
xticks=np.arange(-2, 9, 2),
)
def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/TYC2.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_tyc2.png', size=1, alpha=0.1)
# plot magnitude histogram
mask = np.isnan(data['VTmag'])
vtmag = data[~mask]['VTmag']
plot_histogram(vtmag,
bins = np.arange(-2,16),
figfile = 'maghist_tyc2.png',
xlabel = '$V_\mathrm{T}$',
ylim = (0.5, 2e6),
xticks = np.arange(-2, 17, 2))
#---------------------------------------------------------------------------
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/TYC.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_tyc.png', size=1, alpha=0.1)
# plot magnitude histogram
mask = np.isnan(data['VTmag'])
vtmag = data[~mask]['VTmag']
plot_histogram(vtmag,
bins = np.arange(-2,16),
figfile = 'maghist_tyc.png',
xlabel = '$V_\mathrm{T}$',
ylim = (0.5, 2e6),
xticks = np.arange(-2, 17, 2))
def main():
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/TYC2.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_tyc2.png', size=1, alpha=0.1)
# plot magnitude histogram
mask = np.isnan(data['VTmag'])
vtmag = data[~mask]['VTmag']
plot_histogram(vtmag,
bins=np.arange(-2, 16),
figfile='maghist_tyc2.png',
xlabel='$V_\mathrm{T}$',
ylim=(0.5, 2e6),
xticks=np.arange(-2, 17, 2))
#---------------------------------------------------------------------------
# read data file
catfile = os.path.join(os.getenv('STELLA_DATA'), 'catalog/TYC.fits')
data = fits.getdata(catfile)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_tyc.png', size=1, alpha=0.1)
# plot magnitude histogram
mask = np.isnan(data['VTmag'])
vtmag = data[~mask]['VTmag']
plot_histogram(vtmag,
bins=np.arange(-2, 16),
figfile='maghist_tyc.png',
xlabel='$V_\mathrm{T}$',
ylim=(0.5, 2e6),
xticks=np.arange(-2, 17, 2))
def main():
# read data file
path = os.getenv('STELLA_DATA')
filename = os.path.join(path, 'catalog/HD.fits')
data = fits.getdata(filename)
# plot skymap
ra = data['RAdeg']
dec = data['DEdeg']
plot_skymap(ra, dec, 'skymap_hd.png', size=1, alpha=0.2)
# plot magnitude histogram
mask = np.isnan(data['Ptm'])
ptm = data['Ptm'][~mask]
plot_histogram(
ptm,
bins=np.arange(0, 15),
figfile='maghist_hd.png',
xlabel='$V$',
xticks=np.arange(0, 15, 2),
)