def compute_the_microlensing_model(self, telescope, pyLIMA_parameters):
""" Compute the microlens model according the injected parameters. This is modified by child submodel sublclass,
if not the default microlensing model is returned.
:param object telescope: a telescope object. More details in telescope module.
:param object pyLIMA_parameters: a namedtuple which contain the parameters
:returns: the microlensing model
:rtype: array_like
"""
lightcurve = telescope.lightcurve_flux
time = lightcurve[:, 0] - 2456425
amplification, u = self.model_magnification(telescope, pyLIMA_parameters)
period = getattr(pyLIMA_parameters, 'period')
pulsations = 0.0
# factor = 0.0
# pulsations = getattr(pyLIMA_parameters, 'AO'+'_' + telescope.filter)
for i in xrange(self.number_of_harmonics):
# mplitude = getattr(pyLIMA_parameters, 'A_' + str(i))
# factor = getattr(pyLIMA_parameters, 'q_' + telescope.filter)
# factor2 = getattr(pyLIMA_parameters, 'phi_' + telescope.filter)
amplitude = getattr(pyLIMA_parameters, 'A' + str(i + 1) + '_' + telescope.filter)
# phase = getattr(pyLIMA_parameters, 'phi_' + str(i) + '1')
phase = getattr(pyLIMA_parameters, 'phi' + str(i + 1) + '_' + telescope.filter)
# if telescope.filter != 'I':
# amplitude *= getattr(pyLIMA_parameters, 'A'+str(i+1)+'_'+'I')
# phase *= getattr(pyLIMA_parameters, 'phia'+str(i+1)+'_' +'I')
# phase += getattr(pyLIMA_parameters, 'phib' + str(i + 1) + '_' + telescope.filter)
# import pdb;
# pdb.set_trace()
# phase *=(1+factor2)
pulsations += amplitude * np.cos(2 * np.pi * (i + 1) / period * time + phase)
# import pdb;
# pdb.set_trace()
pulsations = 10 ** (-pulsations / 2.5)
f_source, f_blending = self.derive_telescope_flux(telescope, pyLIMA_parameters, amplification, pulsations)
# microlensing_model = f_source * pulsations * amplification + f_blending
microlensing_model = f_source * amplification * pulsations + f_blending
# Prior here.
# print telescope.name,f_source,f_blending
priors = microlpriors.microlensing_flux_priors(len(microlensing_model), f_source, f_blending / f_source)
return microlensing_model, priors, f_source, f_blending
def _default_microlensing_model(self, telescope, pyLIMA_parameters, amplification):
""" Compute the default microlens model according the injected parameters:
flux(t) = f_source*magnification(t)+f_blending
:param object telescope: a telescope object. More details in telescope module.
:param object pyLIMA_parameters: a namedtuple which contain the parameters
:param array_like amplification: the magnification associated to the model
:returns: the microlensing model, the microlensing priors
:rtype: array_like, float
"""
f_source, g_blending = self.derive_telescope_flux(telescope, pyLIMA_parameters, amplification)
microlensing_model = f_source * (amplification + g_blending)
# Prior here
priors = microlpriors.microlensing_flux_priors(len(microlensing_model), f_source, g_blending)
# print 'the microl model', python_time.time() - start_time
return microlensing_model, priors, f_source, g_blending
