Remove polarization_samples deprecationwarning and actually deprecate it

pycbc/inference/models/marginalized_gaussian_noise.py

@@ -374,19 +374,19 @@ class MarginalizedPolarization(DistMarg, BaseGaussianNoise):
     marginalization over polarization angle. This is accomplished using
     a fixed set of integration points distribution uniformation between
     0 and 2pi. By default, 1000 integration points are used.
-    The 'polarization_samples' argument can be passed to set an alternate
+    The 'marginalize_vector_samples' argument can be passed to set an alternate
     number of integration points.
     """
     name = 'marginalized_polarization'
 
     def __init__(self, variable_params, data, low_frequency_cutoff, psds=None,
                  high_frequency_cutoff=None, normalize=False,
-                 polarization_samples=1000,
+                 marginalize_vector_samples=1000,
                  **kwargs):
 
         variable_params, kwargs = self.setup_marginalization(
                                variable_params,
-                               polarization_samples=polarization_samples,
+                               marginalize_vector_samples=marginalize_vector_samples,
                                **kwargs)
 
         # set up the boiler-plate attributes

pycbc/inference/models/tools.py

@@ -2,7 +2,6 @@
 """
 
 import logging
-import warnings
 from distutils.util import strtobool
 
 import numpy
@@ -63,6 +62,8 @@ def setup_marginalization(self,
                               marginalize_vector_params=None,
                               marginalize_vector_samples=1e3,
                               marginalize_sky_initial_samples=1e6,
+                              marginalize_polarization=True,
+                              marginalize_polarization_samples=1e3,
                               **kwargs):
         """ Setup the model for use with distance marginalization
 
@@ -96,7 +97,7 @@ def setup_marginalization(self,
         -------
         variable_params: list of strings
             Set of variable params (missing distance-related parameter).
-        kwags: dict
+        kwargs: dict
             The keyword arguments to the model initialization, may be modified
             from the original set by this function.
         """
@@ -126,20 +127,15 @@ def pop_prior(param):
         self.marginalize_sky_initial_samples = \
             int(float(marginalize_sky_initial_samples))
 
+        if marginalize_polarization:
+            pol_uniform = numpy.linspace(0, numpy.pi * 2.0, self.vsamples)
+            self.marginalize_vector_params['polarization'] = pol_uniform
+
         for param in str_to_tuple(marginalize_vector_params, str):
             logging.info('Marginalizing over %s, %s points from prior',
                          param, self.vsamples)
             self.marginalized_vector_priors[param] = pop_prior(param)
 
-        # Remove in the future, backwards compatibility
-        if 'polarization_samples' in kwargs:
-            warnings.warn("use marginalize_vector_samples rather "
-                          "than 'polarization_samples'", DeprecationWarning)
-            pol_uniform = numpy.linspace(0, numpy.pi * 2.0, self.vsamples)
-            self.marginalize_vector_params['polarization'] = pol_uniform
-            self.vsamples = int(kwargs['polarization_samples'])
-            kwargs.pop('polarization_samples')
-
         self.reset_vector_params()
 
         self.marginalize_phase = str_to_bool(marginalize_phase)