docstring and test added for Corr.reweight

pyerrors/correlators.py

@@ -233,13 +233,28 @@ class Corr:
         """Reverse the time ordering of the Corr"""
         return Corr(self.content[::-1])
 
-    def reweight(self, weight):
+    def reweight(self, weight, **kwargs):
+        """Reweight the correlator.
+
+        Parameters
+        ----------
+        weight : Obs
+            Reweighting factor. An Observable that has to be defined on a superset of the
+            configurations in obs[i].idl for all i.
+
+        Keyword arguments
+        -----------------
+        all_configs : bool
+            if True, the reweighted observables are normalized by the average of
+            the reweighting factor on all configurations in weight.idl and not
+            on the configurations in obs[i].idl.
+        """
         new_content = []
         for t_slice in self:
             if t_slice is None:
                 new_content.append(None)
             else:
-                new_content.append(np.array(reweight(weight, t_slice)))
+                new_content.append(np.array(reweight(weight, t_slice, **kwargs)))
         return Corr(new_content)
 
     def T_symmetry(self, partner, parity=+1):

pyerrors/pyerrors.py

@@ -1105,9 +1105,10 @@ def reweight(weight, obs, **kwargs):
 
     Keyword arguments
     -----------------
-    all_configs -- if True, the reweighted observables are normalized by the average of
-                   the reweighting factor on all configurations in weight.idl and not
-                   on the configurations in obs[i].idl.
+    all_configs : bool
+        if True, the reweighted observables are normalized by the average of
+        the reweighting factor on all configurations in weight.idl and not
+        on the configurations in obs[i].idl.
     """
     result = []
     for i in range(len(obs)):

tests/correlators_test.py

@@ -54,6 +54,12 @@ def test_m_eff():
     my_corr.m_eff('cosh')
     my_corr.m_eff('sinh')
 
+def test_reweighting():
+    my_corr = pe.correlators.Corr([pe.pseudo_Obs(10, 0.1, 't'), pe.pseudo_Obs(0, 0.05, 't')])
+    assert my_corr.reweighted is False
+    r_my_corr = my_corr.reweight(pe.pseudo_Obs(1, 0.1, 't'))
+    assert r_my_corr.reweighted is True
+
 def test_T_symmetry():
     my_corr = pe.correlators.Corr([pe.pseudo_Obs(10, 0.1, 't'), pe.pseudo_Obs(0, 0.05, 't')])
     with pytest.warns(RuntimeWarning):