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import numpy as np
import matplotlib.pyplot as plt
from astropy import units as u
from desisim.transients import transients
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def plot_transient(tr, ax):
wlmin = np.maximum(2500., tr.minwave().value)
wlmax = np.minimum(9500., tr.maxwave().value)
wl = np.arange(wlmin, wlmax, 1.) * u.Angstrom
t = 0*u.day
ax.plot(wl, tr.flux(0*u.day, wl),
label='{} ({})'.format(tr.model, tr.type))
ax.set(xlabel=r'wavelength [$\AA$]',
ylabel=r'flux [arb. units]')
ax.legend(fontsize=10)
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print(transients)
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fig, ax = plt.subplots(1,1, figsize=(6,4), tight_layout=True)
model = transients.get_model('hsiao')
print(model.mintime(), model.maxtime())
plot_transient(model, ax)
You can grab a model by type. The desisim.transients model will randomly select one of the avaialable models of that type. Types are just strings, and if you try one that is not available in the model you'll just get an exception.
Below, loop over several types, randomly select a model from each, and plot the spectrum from t0 (max light) for that model.
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types = ['Ia', 'Ib', 'Ib/c', 'Ic', 'IIn', 'IIP', 'IIL', 'IIL/P', 'II-pec']
ntype = len(types)
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ncol = 3
nrow = int(np.ceil(ntype / ncol))
fig, axes = plt.subplots(nrow, ncol, figsize=(4*ncol, 3*nrow), tight_layout=True)
axes = axes.flatten()
for t, ax in zip(types, axes):
s = transients.get_type(t)
print(vars(s))
plot_transient(s, ax)
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