def create_nc(nc_params=None):
if nc_params is None:
nc_params = {"wl": WL}
nc_params["broken_pl"] = False
nc_params["slope1"] = draw_from_sample.gaussian(
PARS["pl_slope_min"], PARS["pl_slope_max"])
max_template_flux = 1e-13
nc_params["norm_PL"] = draw_from_sample.gaussian(
PARS["pl_norm_min"], max_template_flux)
print("NC params: {}".format(nc_params))
nc = NuclearContinuumComponent(nc_params["broken_pl"])
# Make a Spectrum object with dummy flux
spectrum = Spectrum(nc_params["wl"])
spectrum.dispersion = nc_params["wl"]
nc.initialize(spectrum)
if nc_params["broken_pl"] == True:
comp_params = [
nc_params["wave_break"], nc_params["norm_PL"], nc_params["slope1"],
nc_params["slope2"]
]
else:
comp_params = [nc_params["norm_PL"], nc_params["slope1"]]
nc_flux = NuclearContinuumComponent.flux(nc, spectrum, comp_params)
nc_err = nc_flux * 0.05
return nc_params["wl"], nc_flux, nc_err, nc_params
def create_fe(fe_params=None):
"""
Args:
fe_params (dictionary): Iron component parameters. Required keys are:
- no_templates (number of templates)
- wl (wavelength range of Fe model, redshift must be accounted for already)
- fe_width (in km/s)
- fe_norm_{} (1,2,3 depending on number of templates)
"""
if fe_params is None:
fe_params = {"no_templates": 3, "wl": WL}
max_template_flux = 1.8119e-14
samples = draw_from_sample.gaussian(PARS["fe_norm_min"],
max_template_flux, 3)
fe_params["fe_norm_1"] = samples[0]
fe_params["fe_norm_2"] = samples[1]
fe_params["fe_norm_3"] = samples[2]
sample = draw_from_sample.gaussian(PARS["fe_width_min"],
PARS["fe_width_max"])
fe_params["fe_width"] = sample
print("Fe params: {}".format(fe_params))
fe = FeComponent()
# Make a Spectrum object with dummy flux
spectrum = Spectrum(fe_params["wl"])
spectrum.dispersion = fe_params["wl"]
fe.initialize(spectrum)
comp_params = [
fe_params["fe_norm_{}".format(x)]
for x in range(1, fe_params["no_templates"] + 1)
] + [fe_params["fe_width"]]
fe_flux = FeComponent.flux(fe, spectrum, comp_params)
fe_err = fe_flux * 0.05
# pl.errorbar(fe_params["wl"], fe_flux, fe_err)
# pl.savefig("fe_data.png")
return fe_params["wl"], fe_flux, fe_err, fe_params
def create_hg(hg_params=None):
"""
Args:
hg_params (dictionary): Host galaxy component parameters. Required keys are:
- no_templates (number of templates)
- wl (wavelength range of HG model, redshift must be accounted for already)
- hg_norm_{} (1,2,3 depending on number of templates)
"""
if hg_params is None:
hg_params = {"no_templates": 3, "wl": WL}
max_template_flux = 6e-12
samples = draw_from_sample.gaussian(PARS["hg_norm_min"],
max_template_flux, 3)
hg_params["hg_norm_1"] = samples[0]
hg_params["hg_norm_2"] = samples[1]
hg_params["hg_norm_3"] = samples[2]
hg_params["hg_stellar_disp"] = draw_from_sample.gaussian(
PARS["hg_stellar_disp_min"], PARS["hg_stellar_disp_max"])
print("HG params: {}".format(hg_params))
hg = HostGalaxyComponent()
# Make a Spectrum object with dummy flux
spectrum = Spectrum(hg_params["wl"])
spectrum.dispersion = hg_params["wl"]
hg.initialize(spectrum)
comp_params = [
hg_params["hg_norm_{}".format(x)]
for x in range(1, hg_params["no_templates"] + 1)
] + [hg_params["hg_stellar_disp"]]
hg_flux = HostGalaxyComponent.flux(hg, spectrum, comp_params)
hg_err = hg_flux * 0.05
# pl.errorbar(hg_params["wl"], hg_flux, hg_err)
# pl.savefig("hg_data.png")
return hg_params["wl"], hg_flux, hg_err, hg_params
var_arr[jj, xx] = flux_errresize[sorted[1]]**2
flux = np.sum(fluxes_arr, axis=0)
var = np.sum(var_arr, axis=0)
flux_err = np.sqrt(var)
print('sizes', np.shape(flux), np.shape(wavelengths))
#spectrum = Spectrum()#maskType="Emission lines reduced")#"Cont+Fe")#
#spectrum.wavelengths = wavelengths
#spectrum.flux = flux
#spectrum.flux_error = flux_err
mask = Mask(wavelengths=wavelengths, maskType=maskType)
spectrum = Spectrum(flux)
spectrum.mask = mask
spectrum.dispersion = wavelengths
spectrum.flux_error = flux_err
# ------------
# Initialize model
# ------------
model = Model()
model.print_parameters = False #True#
# -----------------
# Initialize components
# -----------------
if PL:
nuclear_comp = NuclearContinuumComponent()
model.components.append(nuclear_comp)