def lqbol(self):
"""Calculate the quasi-bolometric lightcurve using direct integration
with trapezoidal integration of the fluxes
"""
self.convert_magnitudes_to_fluxes()
self.deredden_fluxes()
self.get_lbol_epochs()
self.distance_cm, self.distance_cm_err = self.get_distance_cm()
self.qbol_lc = np.array([[0.0, 0.0, 0.0, 0.0, 0.0]])
for jd in self.lbol_epochs:
wavelengths = np.array([x["wavelength"] for x in self.converted_obs if x["jd"] == jd])
fluxes = np.array([x["flux"] for x in self.converted_obs if x["jd"] == jd])
flux_errs = np.array([x["uncertainty"] for x in self.converted_obs if x["jd"] == jd])
names = np.array([x["name"] for x in self.converted_obs if x["jd"] == jd])
sort_indices = np.argsort(wavelengths)
wavelengths = wavelengths[sort_indices]
fluxes = fluxes[sort_indices]
flux_errs = flux_errs[sort_indices]
names = names[sort_indices]
fqbol, fqbol_err = fqbol_trapezoidal(wavelengths, fluxes, flux_errs)
lqbol = fqbol * 4.0 * np.pi * self.distance_cm ** 2.0
lqbol_err = np.sqrt(
(4.0 * np.pi * self.distance_cm ** 2 * fqbol_err) ** 2
+ (8.0 * np.pi * fqbol * self.distance_cm * self.distance_cm_err) ** 2
)
phase = jd - self.parameter_table.cols.explosion_JD[0]
phase_err = self.parameter_table.cols.explosion_JD_err[0]
# Quick and dirty fix for IR-only nights (don't want those in qbol calc)
if min(wavelengths) < 10000.0:
self.qbol_lc = np.append(self.qbol_lc, [[jd, phase, phase_err, lqbol, lqbol_err]], axis=0)
self.qbol_lc = np.delete(self.qbol_lc, (0), axis=0)
self.write_lbol_plaintext(self.qbol_lc, "qbol")
def lbol_direct_bh09(self):
"""Calculate the bolometric lightcurve using the direct integration
method published in Bersten & Hamuy 2009 (2009ApJ...701..200B)
"""
self.convert_magnitudes_to_fluxes()
self.deredden_fluxes()
self.get_lbol_epochs()
self.distance_cm, self.distance_cm_err = self.get_distance_cm()
self.lc = np.array([[0.0, 0.0, 0.0, 0.0, 0.0]])
for jd in self.lbol_epochs:
names = np.array([x["name"] for x in self.converted_obs if x["jd"] == jd and x["name"] != "z"])
wavelengths = np.array([x["wavelength"] for x in self.converted_obs if x["jd"] == jd and x["name"] != "z"])
fluxes = np.array([x["flux"] for x in self.converted_obs if x["jd"] == jd and x["name"] != "z"])
flux_errs = np.array([x["uncertainty"] for x in self.converted_obs if x["jd"] == jd and x["name"] != "z"])
sort_indices = np.argsort(wavelengths)
wavelengths = wavelengths[sort_indices]
fluxes = fluxes[sort_indices]
flux_errs = flux_errs[sort_indices]
fqbol, fqbol_err = fqbol_trapezoidal(wavelengths, fluxes, flux_errs)
temperature, angular_radius, perr = bb_fit_parameters(wavelengths, fluxes, flux_errs)
temperature_err = perr[0]
angular_radius_err = perr[1]
shortest_wl = np.amin(wavelengths)
shortest_flux = np.amin(fluxes)
shortest_flux_err = np.amin(flux_errs)
longest_wl = np.amax(wavelengths)
ir_corr, ir_corr_err = ir_correction(
temperature, temperature_err, angular_radius, angular_radius_err, longest_wl
)
if "U" in names:
idx = np.nonzero(names == "U")[0][0]
U_flux = fluxes[idx]
U_wl = wavelengths[idx]
if U_flux < bb_flux_nounits(U_wl, temperature, angular_radius):
uv_corr, uv_corr_err = uv_correction_linear(shortest_wl, shortest_flux, shortest_flux_err)
else:
uv_corr, uv_corr_err = uv_correction_blackbody(
temperature, temperature_err, angular_radius, angular_radius_err, shortest_wl
)
else:
uv_corr, uv_corr_err = uv_correction_blackbody(
temperature, temperature_err, angular_radius, angular_radius_err, shortest_wl
)
fbol = fqbol + ir_corr + uv_corr
fbol_err = np.sqrt(np.sum(x * x for x in [fqbol_err, ir_corr_err, uv_corr_err]))
lum = fbol * 4.0 * np.pi * self.distance_cm ** 2.0
lum_err = np.sqrt(
(4.0 * np.pi * self.distance_cm ** 2 * fbol_err) ** 2
+ (8.0 * np.pi * fbol * self.distance_cm * self.distance_cm_err) ** 2
)
phase = jd - self.parameter_table.cols.explosion_JD[0]
phase_err = self.parameter_table.cols.explosion_JD_err[0]
self.lc = np.append(self.lc, [[jd, phase, phase_err, lum, lum_err]], axis=0)
self.lc = np.delete(self.lc, (0), axis=0)
self.write_lbol_plaintext(self.lc, "direct")