def computemag(z, l, limb, L, tau, omega, inc, M, Z, av, bands):
# array of magnitudes
shape = tuple((len(omega), len(inc), len(M), len(bands), len(av)))
# use a less memory intensive data type
result = np.full(shape, np.nan, dtype=np.float32)
for m in np.arange(len(M)):
for o in np.arange(len(omega)):
try:
# pre-calculate inclination-independent quantities
st = star.Star(omega[o], L[l], M[m], 1, ut.D10, 100, ld=limb)
for i in np.arange(len(inc)):
# calculate the magnitudes at this inclination;
# these should be a 1D array, corresponding to bands and reddenings as follows:
# (b0, av0), (b0, av1), ..., (b0, avm), (b1, av0), ..., (bn, avm)
mags = st.integrate(inc[i])
result[o, i, m, :, :] = mags.reshape(len(bands), len(av))
except mp.InterpolationError as err:
pass
print('.', end='', flush=True)
return result
k = (4 * math.pi * ut.sigma * ut.G * ut.Msun / (g * ut.Lsun))**(7. / 5)
# the stars' luminosities in solar luminosities
L = k * temp**m
# the stars' masses in solar masses
M = L**(2. / 7)
# radii of the stars in solar radii
R = L**(1. / 7) * np.sqrt(ut.G * ut.Msun / g) / ut.Rsun
print('Non-rotating stars')
print('Temperatures in Kelvin ' + str(temp))
print('Luminosities in solar luminosities ' + str(L))
print('Masses in solar masses ' + str(M))
print('Radii in solar radii ' + str(R))
# stars with linear temperature interpolaion and full limb darkening information
stars = [st.Star(omega, l, m, r, ut.D10, n, ld=ld) for l, m, r in zip(L, M, R)]
# the light from such stars
light = np.array([s.integrate(inclination) for s in stars])
# remove the limb darkening information at the gravity of the stars
ind_g = np.searchsorted(ld.g, logg)
print('Gravity removed from intensity information: ' + str(ld.g[ind_g]) + \
'. \nThese should be the same as the star gravity.')
print('Gravities between which we are interpolating: ' + str(ld.g[ind_g - 1]) +\
' and ' + str(ld.g[ind_g + 1]) )
ld.fit_params = np.delete(ld.fit_params, ind_g, axis=1)
ld.g = np.delete(ld.g, ind_g)
# stars with missing limb darkening information and log gravity interpolation
stars = [st.Star(omega, l, m, r, ut.D10, n, ld=ld) for l, m, r in zip(L, M, R)]
# the light from such stars
ld = pickle.load(f)
iV = ld.bands.index('V')
iB = ld.bands.index('B')
# star parameters
omega, luminosity, mass, Req, distance = [
0.6151, 40.346, 2.165, 2.815, 2.3694e19
] # vega
n_z = 100
incs = np.arccos(np.linspace(1, 0,
50)) # inclinations, equally spaced in cos(i)
# the observed inclination and record the index
iobs = 0.08683
# create star
star = st.Star(omega, luminosity, mass, Req, distance, n_z, ld)
# compute its magnitudes at both filters at all inclinations
V = []
B = []
for i in incs:
mags = star.integrate(i)
V.append(mags[iV])
B.append(mags[iB])
V = np.array(V)
B = np.array(B)
# colors
color = B - V
# compute the observed values
mags = star.integrate(iobs)
Vobs = mags[iV]
Bobs = mags[iB]
k = (4 * math.pi * ut.sigma * ut.G * ut.Msun / (g * ut.Lsun))**(7. / 5)
# the stars' luminosities in solar luminosities
L = k * temp**m
# the stars' masses in solar masses
M = L**(2. / 7)
# radii of the stars in solar radii
R = L**(1. / 7) * np.sqrt(ut.G * ut.Msun / g) / ut.Rsun
print('Non-rotating stars')
print('Temperatures in Kelvin ' + str(temp))
print('Luminosities in solar luminosities ' + str(L))
print('Masses in solar masses ' + str(M))
print('Radii in solar radii ' + str(R))
# stars with linear temperature interpolaion and full limb darkening information
stars = [st.Star(omega, l, m, r, ut.D10, n, ld=ld) for l, m, r in zip(L, M, R)]
# the light from such stars
light = np.array([s.integrate(inclination) for s in stars])
# remove the limb darkening information at the temperatures of the stars
ind_temp = np.searchsorted(ld.T, temp)
print('Temperatures removed from intensity information: ' + str(ld.T[ind_temp]) + \
'. \n\t These should be the same as the star temperatures.')
print('Temperatures between we are interpolating: ' + str(ld.T[ind_temp - 1]) +\
' and ' + str(ld.T[ind_temp + 1]) )
ld.fit_params = np.delete(ld.fit_params, ind_temp, axis=0)
ld.T = np.delete(ld.T, ind_temp)
# stars with linear temperature interpolaion and missing limb darkening information
stars = [
st.Star(omega, l, m, r, ut.D10, n, ld=ld, temp_method='linear')
Req = np.float(line.split()[-1])
elif 'inclination' in line:
inclination = np.float(line.split()[-1])
if 'z values' in line:
nz = np.int(line.split()[-1])
f.close()
# the wavelengths and the synthetic spectrum
wl_syn, I_syn = np.loadtxt(iodir + 'data/vega/vega0_088418.txt').T
m = wl_syn < w
wl_syn = wl_syn[m]
I_syn = I_syn[m]
# a star without limb darkening information for the temperature plot
star = st.Star(omega, luminosity, mass, Req, nz)
# observed spectrum
wl_obs, I_obs = np.loadtxt(iodir + 'data/vega/vega2.dat').T
m = wl_obs < w
wl_obs = wl_obs[m]
I_obs = I_obs[m]
# spectrum at inclination = pi/2
wl_inc, I_inc = np.loadtxt(iodir + 'data/vega/vega1_570796.txt').T
m = wl_inc < w
wl_inc = wl_inc[m]
I_inc = I_inc[m]
## plot
rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], 'size': 18})
def run():
parser = argparse.ArgumentParser(description="Examples: \n" +\
"calc_star data/limbdark_m01.pkl data/vega.pkl 0.6151 40.346 2.165 2.815 2.3694e19 100; " +\
"calc_star data/limbdark/limbdark_p02f.pkl data/altair.pkl 0.744 10.6 1.86 2.008 1.583e19 100; " +\
"calc_star data/limbdark/limbdark_m01f.pkl data/achernar.pkl 0.838 3020 6.1 9.16 1.319e20 100")
parser.add_argument("ld_file",
help="the limb darkening .pkl file to access")
parser.add_argument("output",
help="an output file containing the pickled star")
parser.add_argument(
"omega",
help="rotation speed divided by its Keplerian value at the equator",
type=float)
parser.add_argument("luminosity",
help="luminosity in solar luminosities",
type=float)
parser.add_argument("mass", help="mass in solar masses", type=float)
parser.add_argument("Req",
help="equatorial radius in solar radii",
type=float)
parser.add_argument("d", help="distance in cm", type=float)
parser.add_argument(
"nz",
help="number of z coordinates in the upper hemisphere (normally 100)",
type=int)
parser.add_argument("-t", help="temperature interpolation: 0=planck(default), 1=linear, 2=log", type=int, \
default=0)
parser.add_argument("-n", help="number of steps in the Newton's method for temperature calculation (default is 15)", type=int, \
default=15)
args = parser.parse_args()
## input files
pkl_sfile = args.output # star pickle file
pkl_lfile = args.ld_file # limb darkening file
## star parameter inputs
omega = args.omega # dimensionless rotation speed
luminosity = args.luminosity # luminosity of the star in solar luminosities
mass = args.mass # mass of the star in solar masses
Req = args.Req # equatorial radius of the star in solar radii
distance = args.d # distance to the star in cm
# integration parameter
nz = args.nz
# temperature interpolation parameter
if args.t == 0:
tm = 'planck'
if args.t == 1:
tm = 'linear'
elif args.t == 2:
tm = 'log'
# Newton's method parameter
nm = args.n
## unpickle the limb darkening information
with open(pkl_lfile, 'rb') as f:
ld = pickle.load(f)
# print a message
ut.printf ("Mass: " + str(mass) + " sun(s)\nLuminosity: "+ str(luminosity) + " sun(s)\n" +\
"Equatorial radius: " + str(Req) + " solar radi(i/us)\nRotation speed: " + str(omega) +\
" of the Keplerian angular velocity at the equator\n")
## For a star with given physical parameters, resolution of map,
## and limb darkening information, pre-compute quantities that are needed for
## integrating the starlight and are independent of the inclination
st = star.Star(omega,
luminosity,
mass,
Req,
distance,
nz=nz,
ld=ld,
temp_method=tm,
nm=nm)
### Pickle the star
with open(pkl_sfile, 'wb') as f:
pickle.dump(st, f)
wl = 511.
ind = np.where(lam == wl)[0][0]
# number of z values: log2 scale
low, high = [3, 13]
m = high - low + 1
n_z = np.logspace(low, high, num=m, base=2.)
diff_trap = []
diff_cubic = []
omega, luminosity, mass, Req, distance, inclination = [
0.6151, 40.346, 2.165, 2.815, 2.3694e19, math.pi / 4
]
print("calculating the etalon spectrum with N = 10,000...")
st = star.Star(omega, luminosity, mass, Req, distance, 1e4, ld=ld)
ref = st.integrate(inclination, method='cubic')
mask = ref > 0
print("calculating the flux at the indicator wavelength")
for i, n in np.ndenumerate(n_z):
st = star.Star(omega, luminosity, mass, Req, distance, n, ld=ld)
light = st.integrate(inclination, method='cubic')
sd = np.abs(1 - light[ind] / ref[ind])
diff_cubic.append(sd)
light = st.integrate(inclination, method='trapezoid')
sd = np.abs(1 - light[ind] / ref[ind])
diff_trap.append(sd)
