Added an alternative version of the power2 model with a parametrisati…

…on introduced by P.F.L. Maxted (2018).

ldtk/ldmodel.py

@@ -18,7 +18,8 @@
 """
 
 import numpy as np
-from numpy import asarray, sqrt
+from numpy import asarray, sqrt, log2
+
 
 class LDModel(object):
  npar = None
@@ -127,11 +128,27 @@ def evaluate(cl, mu, pv):
  mu = asarray(mu)
  return 1. - pv[0]*(1.-(mu**pv[1]))
 
+class Power2MPModel(LDModel):
+ """Power-2 limb darkening model with an alternative parametrisation (Maxted, P.F.L., 2018)."""
+ npar = 2
+ name = 'power2mp'
+ abbr = 'p2mp'
+
+ @classmethod
+ def evaluate(cl, mu, pv):
+ assert len(pv) == cl.npar
+ mu = asarray(mu)
+ c = 1 - pv[0] + pv[1]
+ a = log2(c/pv[1])
+ return 1. - c*(1.-(mu**a))
+
 
 models = {'linear': LinearModel,
  'quadratic': QuadraticModel,
  'triquadratic': TriangularQuadraticModel,
  'sqrt': SquareRootModel,
  'nonlinear': NonlinearModel,
  'general': GeneralModel,
- 'power2': Power2Model}
+ 'power2': Power2Model,
+ 'power2mp': Power2MPModel}
+

ldtk/ldtk.py

@@ -23,7 +23,7 @@
 from scipy.optimize import fmin
 
 from .ldmodel import (LinearModel, QuadraticModel, TriangularQuadraticModel, SquareRootModel, NonlinearModel,
- GeneralModel, Power2Model, models)
+ GeneralModel, Power2Model, Power2MPModel, models)
 from .client import Client
 from .core import *
 
@@ -78,6 +78,8 @@ def __init__(self, filters, mu, ldp_samples):
  self.lnlike_nl = partial(self._lnlike, ldmodel=NonlinearModel)
  self.lnlike_ge = partial(self._lnlike, ldmodel=GeneralModel)
  self.lnlike_p2 = partial(self._lnlike, ldmodel=Power2Model)
+ self.lnlike_p2mp = partial(self._lnlike, ldmodel=Power2MPModel)
+
 
  self.coeffs_ln = partial(self._coeffs, ldmodel=LinearModel)
  self.coeffs_qd = partial(self._coeffs, ldmodel=QuadraticModel)
@@ -86,6 +88,7 @@ def __init__(self, filters, mu, ldp_samples):
  self.coeffs_nl = partial(self._coeffs, ldmodel=NonlinearModel)
  self.coeffs_ge = partial(self._coeffs, ldmodel=GeneralModel)
  self.coeffs_p2 = partial(self._coeffs, ldmodel=Power2Model)
+ self.coeffs_p2mp = partial(self._coeffs, ldmodel=Power2MPModel)
 
  self.lnlike_ln.__doc__ = "Linear limb darkening model\n(coeffs, join=True, flt=None)"
  self.lnlike_qd.__doc__ = "Quadratic limb darkening model\n(coeffs, join=True, flt=None)"
@@ -94,6 +97,7 @@ def __init__(self, filters, mu, ldp_samples):
  self.lnlike_nl.__doc__ = "Nonlinear limb darkening model\n(coeffs, join=True, flt=None)"
  self.lnlike_ge.__doc__ = "General limb darkening model\n(coeffs, join=True, flt=None)"
  self.lnlike_p2.__doc__ = "Power-2 limb darkening model\n(coeffs, join=True, flt=None)"
+ self.lnlike_p2mp.__doc__ = "Power-2 limb darkening model with an alternative parametrisation\n(coeffs, join=True, flt=None)"
 
  self.coeffs_ln.__doc__ = "Estimate the linear limb darkening model coefficients, see LPDSet._coeffs for details."
  self.coeffs_qd.__doc__ = "Estimate the quadratic limb darkening model coefficients, see LPDSet._coeffs for details."
@@ -102,6 +106,7 @@ def __init__(self, filters, mu, ldp_samples):
  self.coeffs_nl.__doc__ = "Estimate the nonlinear limb darkening model coefficients, see LPDSet._coeffs for details."
  self.coeffs_ge.__doc__ = "Estimate the general limb darkening model coefficients, see LPDSet._coeffs for details."
  self.coeffs_p2.__doc__ = "Estimate the power-2 limb darkening model coefficients, see LPDSet._coeffs for details."
+ self.coeffs_p2mp.__doc__ = "Estimate the power-2 MP limb darkening model coefficients, see LPDSet._coeffs for details."
 
 
  def save(self, filename):