def fit_observation(
self,
sme,
star,
segments="all",
parameters=["teff", "logg", "monh", "vsini", "vmac", "vmic"],
):
# Fit the observation with SME
print("Fit stellar spectrum with PySME")
# sme.cscale_flag = "linear"
# sme.cscale_type = "mask"
# sme.vrad_flag = "whole"
solver = SME_Solver()
sme = solver.solve(sme, param_names=parameters, segments=segments)
fig = plot_plotly.FinalPlot(sme)
fig.save(filename="solved.html")
# Save output
print("Save results")
for param in parameters:
unit = getattr(star, param).unit
print(f"{param}: {sme[param]} {unit}")
setattr(star, param, sme[param] * unit)
# TODO: + barycentric correction
star.radial_velocity = sme.vrad[0] << (u.km / u.s)
return sme, star
# Start the logging to the file
makedirs(dirname(log_file), exist_ok=True)
util.start_logging(log_file)
# Load your existing SME structure or create your own
sme = SME.SME_Structure.load(in_file)
# Change parameters if your want
sme.vrad = 0.35
sme.vrad_flag = "whole"
sme.cscale_flag = "linear"
sme.cscale_type = "match"
# Apply the parameters set via the command line
sme.teff = teff
sme.logg = logg
sme.monh = monh
# Start SME solver
sme = synthesize_spectrum(sme)
# Save results
makedirs(dirname(out_file), exist_ok=True)
sme.save(out_file)
# Plot results
makedirs(dirname(plot_file), exist_ok=True)
fig = plot_plotly.FinalPlot(sme)
fig.save(filename=plot_file)
orig = sme.synth.copy()
sme.cscale_flag = "linear"
sme.cscale_type = "match+mask"
sme.cscale[0] = [0, 1]
rvel = 100
wmin, wmax = sme.wran[0]
wmin *= 1 - rvel / 3e5
wmax *= 1 + rvel / 3e5
sme.linelist = sme.linelist.trim(wmin, wmax)
sme.specific_intensities_only = True
wmod, smod, cmod = synthesize_spectrum(sme, segments=[0])
orig = readsav(in_file)["sme"]
sint = orig["SINT"][0]
wint = orig["JINT"][0]
wind = orig["WIND"][0]
sint = sint[0, 0:wind[0]]
wint = wint[0:wind[0]]
plt.plot(wint, sint)
plt.plot(wmod[0], smod[0] * cmod[0])
plt.show()
# Plot results
fig = plot_plotly.FinalPlot(sme, orig=orig)
fig.save(filename=plot_file)
print(f"Finished: {target}")
# idl.nlte.set_nlte("Al", "nlte_Al_ama51_pysme.grd")
# idl.nlte.set_nlte("Ba", "nlte_Ba_ama51_pysme.grd")
# idl.nlte.set_nlte("Ca", "nlte_Ca_ama51_pysme.grd")
# idl.nlte.set_nlte("C", "nlte_C_ama51_pysme.grd")
# idl.nlte.set_nlte("H", "nlte_H_ama51_pysme.grd")
# idl.nlte.set_nlte("K", "nlte_K_ama51_pysme.grd")
# idl.nlte.set_nlte("Li", "nlte_Li_ama51_pysme.grd")
# idl.nlte.set_nlte("Mg", "nlte_Mg_ama51_pysme.grd")
# idl.nlte.set_nlte("Mn", "nlte_Mn_ama51_pysme.grd")
# idl.nlte.set_nlte("Na", "nlte_Na_ama51_pysme.grd")
# idl.nlte.set_nlte("N", "nlte_Na_ama51_pysme.grd")
# idl.nlte.set_nlte("O", "nlte_O_ama51_pysme.grd")
# idl.nlte.set_nlte("Si", "nlte_Si_ama51_pysme.grd")
# idl.nlte.set_nlte("Fe", "marcs2012_Fe2016.grd")
# idl = synthesize_spectrum(idl)
# fp = ["teff", "logg", "monh", "vmic", "vmac", "vsini"]
# idl = solve(idl, fp)
# idl.save(join(cwd, "results/Cnc55_tanja.sme"))
# idl_solved = SME_Structure.load(join(cwd, "results/Cnc55_tanja.sme"))
fig = plot_plotly.FinalPlot(idl,
orig=orig,
labels={
"synth": "IDL SME",
"orig": "PySME"
})
fig.save(filename=join(cwd, "Cnc55_tanja.html"))
pass
plot_file = os.path.join(examples_dir, f"results/{target}.html")
log_file = os.path.join(examples_dir, f"results/{target}.log")
# Start the logging to the file
util.start_logging(log_file)
# Load your existing SME structure or create your own
sme = SME.SME_Structure.load(in_file)
idl = SME.SME_Structure.load(idl_file)
sme.cscale = [0, 1]
sme.cscale_type = "match+mask"
sme.vrad = idl.vrad
sme.vrad_flag = "none"
sme.cscale_flag = "none"
sme = synthesize_spectrum(sme)
# Save results
sme.save(out_file)
# Plot results
fig = plot_plotly.FinalPlot(sme,
orig=idl.synth,
labels={
"synth": "PySME",
"orig": "IDL SME"
})
fig.save(filename=plot_file)
pass