def engines(nm=None):
switcher = {
'mpfit': ps.FitMPFit(),
# 'mcmc': ps.FitMCMC(nwalkers=200, nburn=100, nsteps=500),
'mcmc': ps.FitMCMC(),
# 'mcmc': ps.FitMCMC(nwalkers=100, nburn=50, nsteps=200),
}
if nm is not None:
return switcher.get(nm)
return list(switcher.keys())
def test_fit_mpfit_curves_Stella_SN1999em(self):
from pystella.rf import light_curve_func as lcf
from pystella.rf import light_curve_plot as lcp
# matplotlib.rcParams['backend'] = "TkAgg"
# matplotlib.rcParams['backend'] = "Qt4Agg"
# from matplotlib import pyplot as plt
# Get observations
D = 11.5e6 # pc
dm = -5. * np.log10(D) + 5
# dm = -30.4 # D = 12.e6 pc
curves_obs = sn1999em.read_curves()
curves_obs.set_mshift(dm)
# Get model
name = 'cat_R500_M15_Ni006_E12'
path = join(dirname(dirname(abspath(__file__))), 'data', 'stella')
curves_mdl = lcf.curves_compute(name, path, curves_obs.BandNames)
# fit
# fitter = FitLcMcmc()
fitter = ps.FitMPFit()
fitter.is_debug = True
res = fitter.fit_curves(curves_obs, curves_mdl)
# print
# txt = '{0:10} {1:.4e} \n'.format('tshift:', res.tshift) + \
# '{0:10} {1:.4e} \n'.format('tsigma:', res.tsigma) + \
# '{0}\n'.format(res.comm)
txt = '{:10s} {:.4f}+-{:.4f} \n'.format('tshift:', res.tshift, res.tsigma) + \
'{:10s} {:.4f}+-{:.4f}\n'.format('msigma:', res.mshift, res.msigma) + \
'{0}\n'.format(res.comm)
print(txt)
# plot model
curves_obs.set_tshift(res.tshift)
# curves_mdl.set_tshift(0.)
ax = lcp.curves_plot(curves_mdl)
lt = {lc.Band.Name: 'o' for lc in curves_obs}
lcp.curves_plot(curves_obs, ax, lt=lt, xlim=(-10, 300), is_line=False)
ax.text(0.1, 0.1, txt, transform=ax.transAxes)
plt.show()
def test_FitMPFit_best_curves_gp_SN1999em(self):
from pystella.rf import light_curve_func as lcf
from pystella.rf import light_curve_plot as lcp
# matplotlib.rcParams['backend'] = "TkAgg"
# matplotlib.rcParams['backend'] = "Qt4Agg"
# from matplotlib import pyplot as plt
# Get observations
D = 11.5e6 # pc
ebv_sn = 0.1
dm = -5. * np.log10(D) + 5
# dm = -30.4 # D = 12.e6 pc
curves_obs = sn1999em.read_curves()
curves_obs.set_mshift(dm)
# Get model
name = 'cat_R500_M15_Ni006_E12'
path = join(dirname(dirname(abspath(__file__))), 'data', 'stella')
curves_mdl = lcf.curves_compute(name, path, curves_obs.BandNames)
# fit
# fitter = FitLcMcmc()
fitter = ps.FitMPFit()
fitter.is_info = True
fitter.is_debug = True
res = fitter.best_curves_gp(curves_mdl, curves_obs, dt0=0., dm0=0.)
# print
txt = '{0:10} {1:.4e} \n'.format('tshift:', res['dt']) + \
'{0:10} {1:.4e} \n'.format('tsigma:', res['dtsig'])
print(txt)
# plot model
curves_obs.set_tshift(res['dt'])
# curves_mdl.set_tshift(0.)
ax = lcp.curves_plot(curves_mdl)
lt = {lc.Band.Name: 'o' for lc in curves_obs}
lcp.curves_plot(curves_obs, ax, lt=lt, xlim=(-10, 300), is_line=False)
plt.show()
def test_FitMPF_best_curves_SN1999em(self):
from pystella.rf import light_curve_func as lcf
from pystella.rf import light_curve_plot as lcp
# Get observations
D = 11.5e6 # pc
ebv_sn = 0.
# ebv_sn = 0.1
# dm = -5. * np.log10(D) + 5
# dm = -30.4 # D = 12.e6 pc
curves_obs = sn1999em.read_curves()
# Get model
name = 'cat_R500_M15_Ni006_E12'
path = join(dirname(dirname(abspath(__file__))), 'data', 'stella')
curves_mdl = ps.Stella(name, path=path).curves(curves_obs.BandNames,
distance=D,
ebv=ebv_sn)
# fit
fitter = ps.FitMPFit()
fitter.is_info = True
fitter.is_debug = True
fitter.is_quiet = True
fit_result, res, dum = fitter.best_curves(
curves_mdl,
curves_obs,
dt0=0.,
)
# fit_result, res, dum = fitter.best_curves(curves_mdl, curves_obs, dt0=0., dm0=0.)
dt, dtsig = res['dt'], res['dtsig']
dm, dmsig = res['dm'], res['dmsig']
# plot model
curves_mdl.set_tshift(dt)
ax = lcp.curves_plot(curves_mdl)
lt = {lc.Band.Name: 'o' for lc in curves_obs}
lcp.curves_plot(curves_obs, ax, lt=lt, xlim=(-10, 300), is_line=False)
# print
txt = '{:10} {:.2f} +- {:.4f}'.format('dt:', res['dt'], res['dtsig'])
txt += '\n{:10} {:.2f} +- {:.4f}'.format('dm:', res['dm'],
res['dmsig'])
print(txt)
title_font = {
'size': '12',
'color': 'black',
'weight': 'normal',
'verticalalignment': 'bottom'
}
ax.text(0.03,
0.95,
txt,
transform=ax.transAxes,
bbox={
'facecolor': 'none',
'alpha': 0.2,
'edgecolor': 'none'
},
**title_font)
plt.show()