def __init__(self, name, kt_array=None): if kt_array is None: kt_array = DEFAULT_KT_ARRAY else: kt_array = np.atleast_1d(np.asfarray(kt_array)) self.gfac = Parameter(name, 'gfac', 0.5, 1e-4, 1e4, 1e-6, 1e6) self.Abundanc = Parameter(name, 'Abundanc', 1., 0., 5., 0.0, hugeval, frozen=True) self.redshift = Parameter(name, 'redshift', 0., -0.999, 10., -0.999, hugeval, frozen=True) self.norm = Parameter(name, 'norm', 1.0, 0.0, 1e24, 0.0, hugeval) self._kt_array = kt_array self._cur_cache_key = None self._cached_vals = None XSAdditiveModel.__init__( self, name, (self.gfac, self.Abundanc, self.redshift, self.norm))
def __init__(self, name='zkerrbb'): self.eta = Parameter(name, 'eta', 0, 0, 1.0, 0, 1.0, frozen=True) self.a = Parameter(name, 'a', 0.5, -0.99, 0.999, -0.99, 0.9999) self.i = Parameter(name, 'i', 30, 0, 85, 0, 85, units='degree', frozen=True) self.Mbh = Parameter(name, 'Mbh', 1e7, 3, 1e10, 3, 1e10, units='M_sun', frozen=True) self.Mdd = Parameter(name, 'Mdd', 1, 1e-5, 1e4, 1e-5, 1e5, units='M0yr') self.z = Parameter(name, 'z', 0.01, 0, 10, 0, 10, frozen=True) self.fcol = Parameter(name, 'fcol', 2, -100, 100, -100, 100, frozen=True) self.rflag = Parameter(name, 'rflag', 1, alwaysfrozen=True) self.lflag = Parameter(name, 'lflag', 1, alwaysfrozen=True) self.norm = Parameter(name, 'norm', 1.0, 0, 1e24, 0, hugeval) pars = (self.eta, self.a, self.i, self.Mbh, self.Mdd, self.z, self.fcol, self.rflag, self.lflag, self.norm) XSAdditiveModel.__init__(self, name, pars)
def __init__(self, name='foo'): self.kT = Parameter(name, 'kT', 1.0) XSAdditiveModel.__init__(self, name, (self.kT))
def __init__(self, name='powerlaw'): self.PhoIndex = Parameter(name, 'PhoIndex', 1., 0.95, 1.05, 0.95, 1.05) self.norm = Parameter(name, 'norm', 9.2, 8.8, 9.7, 8.8, 9.7) XSAdditiveModel.__init__(self, name, (self.PhoIndex, self.norm))
def __init__(self, name='agnslim'): self.mass = Parameter(name, 'mass', 1e7, 1, 1e10, 1, 1e10, units='solar', frozen=True) self.dist = Parameter(name, 'dist', 100, 0.01, 1e9, 0.01, 1e9, units='Mpc', frozen=True) self.logmdot = Parameter(name, 'logmdot', 1, -10, 3, -10, 3) self.astar = Parameter(name, 'astar', 0, 0, 0.998, 0, 0.998, frozen=True) self.cosi = Parameter(name, 'cosi', 0.5, 0.05, 1, 0.05, 1, frozen=True) self.kTe_hot = Parameter(name, 'kTe_hot', 100, 10, 300, 10, 300, units='KeV(-pl)', frozen=True) self.kTe_warm = Parameter(name, 'kTe_warm', 0.2, 0.1, 0.5, 0.1, 0.5, units='KeV(-sc)') self.Gamma_hot = Parameter(name, 'Gamma_hot', 2.4, 1.3, 3, 1.3, 3) self.Gamma_warm = Parameter(name, 'Gamma_warm', 3.0, 2, 5, 2, 10, units='(-disk)') self.R_hot = Parameter(name, 'R_hot', 10, 2, 500, 2, 500, units='Rg') self.R_warm = Parameter(name, 'R_warm', 20, 2, 500, 2, 500, units='Rg') self.logrout = Parameter(name, 'logrout', -1.0, -3, 7, -3, 7, units='(-selfg)', frozen=True) self.rin = Parameter(name, 'rin', -1, -1, 100, -1, 100, frozen=True) self.redshift = Parameter(name, 'redshift', 0, 0, 5, 0, 5, frozen=True) self.norm = Parameter(name, 'norm', 1.0, alwaysfrozen=True) pars = (self.mass, self.dist, self.logmdot, self.astar, self.cosi, self.kTe_hot, self.kTe_warm, self.Gamma_hot, self.Gamma_warm, self.R_hot, self.R_warm, self.logrout, self.rin, self.redshift, self.norm) XSAdditiveModel.__init__(self, name, pars)