minor bug fixes

README.rst

@@ -2,7 +2,7 @@
 anesthetic: nested sampling post-processing
 ===========================================
 :Authors: Will Handley and Lukas Hergt
-:Version: 2.0.0
+:Version: 2.0.1
 :Homepage: https://github.com/handley-lab/anesthetic
 :Documentation: http://anesthetic.readthedocs.io/
 

anesthetic/_version.py

@@ -1 +1 @@
-__version__ = '2.0.0'
+__version__ = '2.0.1'

anesthetic/samples.py

@@ -247,6 +247,7 @@ def plot_1d(self, axes=None, *args, **kwargs):
                 self[x].plot(ax=ax, xlabel=xlabel,
                              *args, **kwargs)
                 ax.set_xlabel(xlabel)
+                ax.set_ylabel("")
             else:
                 ax.plot([], [])
 

anesthetic/weighted_pandas.py

@@ -10,7 +10,7 @@
 from pandas.util._exceptions import find_stack_level
 from pandas.util import hash_pandas_object
 from numpy.ma import masked_array
-from anesthetic.utils import (compress_weights, neff as neff_, quantile,
+from anesthetic.utils import (compress_weights, neff, quantile,
                               temporary_seed, adjust_docstrings)
 from pandas.core.dtypes.missing import notna
 
@@ -222,10 +222,10 @@ def reset_index(self, level=None, drop=False, inplace=False,
         else:
             return answer.__finalize__(self, "reset_index")
 
-    def neff(self, axis=0):
+    def neff(self, axis=0, beta=1):
         """Effective number of samples."""
         if self.isweighted(axis):
-            return neff_(self.get_weights(axis))
+            return neff(self.get_weights(axis), beta=beta)
         else:
             return self.shape[axis]
 

tests/test_weighted_pandas.py

@@ -379,14 +379,18 @@ def test_WeightedDataFrame_sample(frame):
 
 
 def test_WeightedDataFrame_neff(frame):
-    neff = frame.neff()
-    assert isinstance(neff, float)
-    assert neff < len(frame)
-    assert neff > len(frame) * np.exp(-0.25)
-
-    neff = frame.neff(1)
-    assert isinstance(neff, int)
-    assert neff == len(frame.T)
+    N_eff = frame.neff()
+    assert isinstance(N_eff, float)
+    assert N_eff < len(frame)
+    assert N_eff > len(frame) * np.exp(-0.25)
+
+    N_eff = frame.neff(1)
+    assert isinstance(N_eff, int)
+    assert N_eff == len(frame.T)
+
+    # beta kwarg
+    for beta in [0.5, 1, 2, np.inf, '0.5', 'equal', 'entropy', 'kish']:
+        assert frame.neff(beta=beta) == neff(frame.get_weights(), beta=beta)
 
 
 def test_WeightedDataFrame_compress(frame):