Finish rv_names -> rv_mode for dit.other.

dit/other/extropy.py

@@ -2,11 +2,12 @@
 The extropy
 """
 
-from ..math.ops import LogOperations
+from ..helpers import RV_MODES
+from ..math.ops import get_ops
 
 import numpy as np
 
-def extropy(dist, rvs=None, rv_names=None):
+def extropy(dist, rvs=None, rv_mode=None):
     """
     Returns the extropy J[X] over the random variables in `rvs`.
 
@@ -22,11 +23,12 @@ def extropy(dist, rvs=None, rv_names=None):
         The indexes of the random variable used to calculate the extropy.
         If None, then the extropy is calculated over all random variables.
         This should remain `None` for ScalarDistributions.
-    rv_names : bool
-        If `True`, then the elements of `rvs` are treated as random variable
-        names. If `False`, then the elements of `rvs` are treated as random
-        variable indexes.  If `None`, then the value `True` is used if the
-        distribution has specified names for its random variables.
+    rv_mode : str, None
+        Specifies how to interpret the elements of `rvs`. Valid options are:
+        {'indices', 'names'}. If equal to 'indices', then the elements of
+        `rvs` are interpreted as random variable indices. If equal to 'names',
+        the the elements are interpreted as random variable names. If `None`,
+        then the value of `dist._rv_mode` is consulted.
 
     Returns
     -------
@@ -44,15 +46,15 @@ def extropy(dist, rvs=None, rv_names=None):
         import dit
         dist = dit.ScalarDistribution([dist, 1-dist])
         rvs = None
-        rv_names = False
+        rv_mode = RV_MODES.INDICES
 
     if dist.is_joint():
         if rvs is None:
             # Set to entropy of entire distribution
             rvs = list(range(dist.outcome_length()))
-            rv_names = False
+            rv_mode = RV_MODES.INDICES
 
-        d = dist.marginal(rvs, rv_names=rv_names)
+        d = dist.marginal(rvs, rv_mode=rv_mode)
     else:
         d = dist
 
@@ -63,7 +65,7 @@ def extropy(dist, rvs=None, rv_names=None):
         terms = -base**npmf * npmf
     else:
         # Calculate entropy in bits.
-        log = LogOperations(2).log
+        log = get_ops(2).log
         npmf = 1 - pmf
         terms = -npmf * log(npmf)