def compare_ttVSubv(mname, path, bands=['U', 'B', 'V', 'R', 'I'], t_cut=1., is_plot_time_points=False):
dic_results = {}
model = Stella(mname, path=path)
tt = model.read_tt_data()
# time cut days
mags = tt[tt['time'] > t_cut]
n1 = mags.dtype.names
def f(x):
if len(x) == 2 and x.startswith('M'):
return x.replace('M', '')
else:
return x
n2 = map(lambda x: f(x), n1)
mags.dtype.names = n2
dic_results['tt'] = mags
# ubv
serial_spec = model.read_series_spectrum(t_diff=1.05)
mags = serial_spec.mags_bands(bands)
dic_results['ubv'] = mags
plot_all(dic_results, bands, title=mname, is_time_points=is_plot_time_points)
def compute_vel(name, path, z=0., t_beg=1., t_end=None, t_diff=1.05):
model = Stella(name, path=path)
if not model.is_res_data or not model.is_tt_data:
if not model.is_res_data:
print "There are no res-file for %s in the directory: %s " % (name, path)
if not model.is_tt_data:
print "There are no tt-file for %s in the directory: %s " % (name, path)
return None
if t_end is None:
t_end = float('inf')
res = model.get_res()
tt = model.read_tt_data()
tt = tt[tt['time'] >= t_beg] # time cut days
radiuses = list()
vels = list()
times = list()
Rph_spline = interpolate.splrep(tt['time'], tt['Rph'], s=0)
for nt in range(len(tt['time'])):
t = tt['time'][nt]
if t > t_end:
break
if t < t_beg or np.abs(t / t_beg < t_diff):
continue
t_beg = t
radius = interpolate.splev(t, Rph_spline)
if np.isnan(radius):
radius = np.interp(t, tt['time'], tt['Rph'], 0, 0) # One-dimensional linear interpolation.
block = res.read_at_time(time=t)
if block is None:
break
if True:
vel = np.interp(radius, block['R14']*1e14, block['V8'], 0, 0) # One-dimensional linear interpolation.
vels.append(vel * 1e8)
else:
idx = np.abs(block['R14'] - radius / 1e14).argmin()
vels.append(block['V8'][idx] * 1e8)
radiuses.append(radius)
times.append(t * (1. + z)) # redshifted time
# show results
res = np.array(np.zeros(len(vels)),
dtype=np.dtype({'names': ['time', 'vel', 'r'],
'formats': [np.float] * 3}))
res['time'] = times
res['vel'] = vels
res['r'] = radiuses
return res
def compute_tcolor(name, path, bands, d=rf.pc_to_cm(10.0), z=0.0, t_cut=1.0):
model = Stella(name, path=path)
if not model.is_ph_data:
print "No ph-data for: " + str(model)
return None
if not model.is_tt_data:
print "No tt-data for: " + str(model)
return None
# serial_spec = model.read_series_spectrum(t_diff=1.)
# curves = serial_spec.flux_to_curves(bands, d=distance)
serial_spec = model.read_series_spectrum(t_diff=1.05, t_beg=t_cut)
# curves = serial_spec.
mags = serial_spec.mags_bands(bands, z=z, d=d)
# read R_ph
tt = model.read_tt_data()
tt = tt[tt["time"] > t_cut] # time cut days
# compute Tnu, W
Tnu, Teff, W = compute_Tnu_w(serial_spec, tt=tt)
# fit mags by B(T_col) and get \zeta\theta & T_col
Tcolors, zetaR, times = compute_Tcolor_zeta(mags, tt=tt, bands=bands, freq=serial_spec.Freq, d=d, z=z)
# show results
res = np.array(
np.zeros(len(Tcolors)),
dtype=np.dtype({"names": ["time", "Tcol", "zeta", "Tnu", "Teff", "W"], "formats": [np.float64] * 6}),
)
res["time"] = times
res["Tcol"] = Tcolors
res["zeta"] = zetaR
res["Tnu"] = Tnu
res["Teff"] = Teff
res["W"] = W
return res
