add aligned spin prior

CHANGELOG.md

@@ -21,6 +21,7 @@ Changes currently on master, but not under a tag.
 - Hyperparameter estimation now enables the user to provide the single event evidences
 - Add nested samples to nestle output
 - Prior and child classes now implement the \_\_eq\_\_ magic method for comparisons
+- Add AlignedSpin gw prior
 
 ### Changes
 - Fix construct_cbc_derived_parameters

test/prior_test.py

@@ -7,7 +7,6 @@ import os
 import shutil
 from collections import OrderedDict
 
-
 class TestPriorInstantiationWithoutOptionalPriors(unittest.TestCase):
 
     def setUp(self):
@@ -152,7 +151,8 @@ class TestPriorClasses(unittest.TestCase):
             tupak.core.prior.Cauchy(name='test', unit='unit', alpha=0, beta=1),
             tupak.core.prior.Lorentzian(name='test', unit='unit', alpha=0, beta=1),
             tupak.core.prior.Gamma(name='test', unit='unit', k=1, theta=1),
-            tupak.core.prior.ChiSquared(name='test', unit='unit', nu=2)
+            tupak.core.prior.ChiSquared(name='test', unit='unit', nu=2),
+            tupak.gw.prior.AlignedSpin(name='test', unit='unit')
         ]
 
     def test_minimum_rescaling(self):

tupak/gw/prior.py

 import os
-from ..core.prior import PriorSet, FromFile, Prior, DeltaFunction, Gaussian
+from ..core.prior import (PriorSet, Uniform, FromFile, Prior, DeltaFunction,
+                          Gaussian, Interped)
 from ..core.utils import logger
 import numpy as np
 from scipy.interpolate import UnivariateSpline
@@ -26,6 +27,43 @@ class UniformComovingVolume(FromFile):
                           latex_label=latex_label, unit='Mpc')
 
 
+class AlignedSpin(Interped):
+
+    def __init__(self, a_prior=Uniform(0, 1), z_prior=Uniform(-1, 1),
+                 name=None, latex_label=None, unit=None):
+        """
+        Prior distribution for the aligned (z) component of the spin.
+
+        This takes prior distributions for the magnitude and cosine of the tilt
+        and forms a compound prior.
+
+        This is useful when using aligned-spin only waveform approximants.
+
+        This is an extension of e.g., (A7) of https://arxiv.org/abs/1805.10457.
+
+        Parameters
+        ----------
+        a_prior: Prior
+            Prior distribution for spin magnitude
+        z_prior: Prior
+            Prior distribution for cosine spin tilt
+        name: see superclass
+        latex_label: see superclass
+        unit: see superclass
+        """
+        self.a_prior = a_prior
+        self.z_prior = z_prior
+        chi_min = min(a_prior.maximum * z_prior.minimum,
+                      a_prior.minimum * z_prior.maximum)
+        chi_max = a_prior.maximum * z_prior.maximum
+        xx = np.linspace(chi_min, chi_max, 800)
+        aas = np.linspace(a_prior.minimum, a_prior.maximum, 1000)
+        yy = [np.trapz(np.nan_to_num(a_prior.prob(aas) / aas *
+                                     z_prior.prob(x / aas)), aas) for x in xx]
+        Interped.__init__(self, xx=xx, yy=yy, name=name,
+                          latex_label=latex_label, unit=unit)
+
+
 class BBHPriorSet(PriorSet):
     def __init__(self, dictionary=None, filename=None):
         """ Initialises a Prior set for Binary Black holes