Resolve "parameterized eos sampling"

Merge request to include the spectral decomposition parameterized equation of state (EOS) simulation code and ability to sample in EOS model parameters.

bilby/gw/eos/eos.py

@@ -295,9 +295,17 @@ class TabularEOS(EOS):
         plt.show()
 
 
+def spectral_adiabatic_index(gammas, x):
+    arg = 0
+    for i in range(len(gammas)):
+        arg += gammas[i] * x ** i
+
+    return np.exp(arg)
+
+
 class SpectralDecompositionEOS(TabularEOS):
 
-    def __init__(self, gammas, p0, e0, xmax, npts=100):
+    def __init__(self, gammas, p0=3.01e33, e0=2.03e14, xmax=8, npts=100):
         """
         Parameterized EOS using a spectral
         decomposition per Lindblom
@@ -311,7 +319,7 @@ class SpectralDecompositionEOS(TabularEOS):
             spaces.
         priors: See superclass.
         p0: float
-            lowest pressure value in EoS in cgs units.
+            lowest pressure value in EoS in cgs units. Default is p0 for SLy from Lindblom paper
         e0: float
             lowest energy density value in EoS. FIXME: the input param is actually e0/c**2
         xmax: float
@@ -332,16 +340,9 @@ class SpectralDecompositionEOS(TabularEOS):
         self.e_of_p = self.__construct_e_of_p_table()
         super().__init__(self.e_of_p, from_array=True)
 
-    def adiabatic_index(self, x):
-        arg = 0
-        for i in range(len(self.gammas)):
-            arg += self.gammas[i] * x ** i
-
-        return np.exp(arg)
-
     def __mu_integrand(self, x):
 
-        return 1. / self.adiabatic_index(x)
+        return 1. / spectral_adiabatic_index(self.gammas, x)
 
     def mu(self, x):
 
@@ -349,7 +350,7 @@ class SpectralDecompositionEOS(TabularEOS):
 
     def __eps_integrand(self, x):
 
-        return np.exp(x) * self.mu(x) / self.adiabatic_index(x)
+        return np.exp(x) * self.mu(x) / spectral_adiabatic_index(self.gammas, x)
 
     def energy_density(self, x, eps0):