for ii in magname:
labels.append(ii)
# predicted Kp magnitude of the primary star
kpmag = np.zeros(len(results[:, 0]))
blue = results[:, 0] - results[:, 1] <= 0.3
kpmag[blue] = 0.25 * results[blue, 0] + 0.75 * results[blue, 1]
kpmag[~blue] = 0.3 * results[~blue, 0] + 0.7 * results[~blue, 2]
# get the WD properties and flux ratio
wdage = np.zeros(len(age))
msages = np.zeros(len(age))
wdmag = np.zeros(len(age))
F2F1 = np.zeros(len(age))
for ii in np.arange(len(age)):
msages[ii] = msage(x[ii, 5], x[ii, 8], isobundle)
wdage[ii] = np.log10(10.**age[ii] - 10.**(msages[ii]))
wdmag[ii] = wdmagfunc(np.array([[x[ii, 6], wdage[ii]]]))[0]
F2F1[ii] = 10.**((wdmag[ii] - kpmag[ii])/(-2.5))
# add the flux ratio
F2F1 = F2F1.reshape((len(x[:, 0]), 1))
x = np.concatenate((x, F2F1), axis=1)
labels.append('$F_2/F_1$')
wdpreds = np.zeros((len(wdage), 2))
wdpreds[:, 0] = x[:, 6]
wdpreds[:, 1] = wdage
# get the WD temperature
wdmodels = getwdmodels()
wdtemp = interpolate.griddata(wdmodels[:, 0:2],
wdmodels[:, 2], wdpreds)
rotation=90, fontsize=24)
fig5.text(0.07, 0.5, 'Relative Flux', ha='center', va='center',
rotation=90, fontsize=24)
# ========================================================================== #
# the rest is all to produce Figure S4
# most of this is copied from the light_curve_model function
# set up a range of WD masses
M2s = np.linspace(0.1, 1.453, 1000)
(magobs, magerr, maglam, magname, interps, limits, fehs, ages,
maxmasses, wdmagfunc) = isobundle
# calculate their magnitudes based on the best model
wdage = np.log10(10.**age - 10.**(msage(M2init, FeH, isobundle)))
wdmag = wdmagfunc(np.array([[M2, wdage]]))[0]
# get the magnitudes of the primary star in the best model
mags = isointerp(M1, FeH, age, isobundle)
# pull out the stellar radius
R1 = mags[-3]
# get the flux ratio between the two stars in the Kepler band
F2F1 = 0.
if np.isfinite(wdmag):
# get the Kp magnitude of the main star
gind = np.where(magname == 'g')[0][0]
rind = np.where(magname == 'r')[0][0]
iind = np.where(magname == 'i')[0][0]
