__author__ = "Andrea Tramacere"
from .model_parameters import ModelParameterArray, ModelParameter
import numpy as np
from astropy import constants as const
from .spectral_shapes import SED
from .base_model import Model
__all__=['AnalyticalParameter','Disk']
[docs]
class AnalyticalParameter(ModelParameter):
"""
This class is a subclass of the :class:`.ModelParameter` class,
extending the base class to analytical parameters.
"""
def __init__(self,polymodel,**keywords):
self.polymodel=polymodel
self.allowed_par_types=['Temperature','peak freq','peak flux']
super(AnalyticalParameter,self).__init__( **keywords)
if 'val' in keywords.keys():
val=keywords['val']
self.assign_val(self.name,val)
[docs]
def set(self,**keywords):
super(AnalyticalParameter,self).set(**keywords )
"""
sets a parameter value checking for physical boundaries
"""
if 'val' in keywords.keys():
self.assign_val(self.name,keywords['val'])
[docs]
def assign_val(self,name,val):
"""
assigns the paramter valut to the :class:`Template` object
"""
setattr(self.polymodel,name,val)
[docs]
class Disk(Model):
def __init__(self,cosmo,z,nu_size=100,name='disk',**keywords):
"""
"""
super(Disk,self).__init__( **keywords)
self.z=z
self.name=name
self.model_type='analytical'
self.SED = SED(name=self.model_type)
self.parameters = ModelParameterArray()
self.T_Disk=10000
self.parameters.add_par(AnalyticalParameter(self,name='T_Disk',par_type='Temperature',val=10000,val_min=0.,val_max=None,units=''))
self.nuFnu_p_D=1E-10
self.parameters.add_par(AnalyticalParameter(self,name='nuFnu_p',par_type='peak flux',val=1E-10,val_min=0.,val_max=1E-3,units='erg cm^-2 s^-1',log=True))
self.HPLANCK=const.h.cgs.value
self.SIGSB=const.sigma_sb.cgs.value
self.vluce_cm=const.c.cgs.value
self.K_boltz=const.k_B.cgs.value
self.cosmo=cosmo
self.DL=self.cosmo.get_DL_cm(self.z)
self.L_D=self.get_L_D()
self.nu_p_Disk=self.get_nu_p()
[docs]
def set_disk_pars(self,fit_model,model_name):
self.L_Disk=self.get_L_D()
self.L_Disk_err=self.L_Disk*(fit_model.parameters.get(model_name,'nuFnu_p','best_fit_err')/
fit_model.parameters.get(model_name,'nuFnu_p','best_fit_val'))
self.T_Disk=fit_model.parameters.get(model_name,'T_Disk','best_fit_val')
self.T_Disk_err=fit_model.parameters.get(model_name,'T_Disk','best_fit_err')
self.nu_p_Disk=self.get_nu_p()
self.nu_p_Disk_err=self.nu_p_Disk*(self.T_Disk_err/self.T_Disk)
[docs]
def get_nu_p(self):
return self.T_Disk*(1.39*5.879e10)
[docs]
def get_L_D(self):
return 4*np.pi*self.DL*self.DL*self.nuFnu_p
#def log_func(self,log_nu):
# return np.log10(self.lin_func(np.power(10,log_nu)))
[docs]
def lin_func(self,nu):
nu=nu*(1+self.z)
a = 2 * self.HPLANCK * nu*nu*nu*nu / (self.vluce_cm* self.vluce_cm)
a *= 1.0 / (np.exp((self.HPLANCK * nu) / (self.K_boltz * self.T_Disk)) - 1)
return a/(self.SIGSB*self.T_Disk*self.T_Disk*self.T_Disk*self.T_Disk/np.pi)*self.nuFnu_p
[docs]
def log_func(self,log_nu):
return np.log10(self.lin_func(np.power(10,log_nu)))
