Corr.correlate implemented

pyerrors/correlators.py

@@ -3,7 +3,7 @@ import numpy as np
 import autograd.numpy as anp
 import matplotlib.pyplot as plt
 import scipy.linalg
-from .pyerrors import Obs, dump_object, reweight
+from .pyerrors import Obs, dump_object, reweight, correlate
 from .fits import least_squares
 from .linalg import eigh, inv, cholesky
 from .roots import find_root
@@ -237,6 +237,22 @@ class Corr:
         """Reverse the time ordering of the Corr"""
         return Corr(self.content[::-1])
 
+    def correlate(self, partner):
+        """Correlate the correlator with another correlator or Obs"""
+        new_content = []
+        for x0, t_slice in enumerate(self.content):
+            if t_slice is None:
+                new_content.append(None)
+            else:
+                if isinstance(partner, Corr):
+                    new_content.append(np.array([correlate(o, partner.content[x0][0]) for o in t_slice]))
+                elif isinstance(partner, Obs):
+                    new_content.append(np.array([correlate(o, partner) for o in t_slice]))
+                else:
+                    raise Exception("Can only correlate with an Obs or a Corr.")
+
+        return Corr(new_content)
+
     def reweight(self, weight, **kwargs):
         """Reweight the correlator.
 

pyerrors/pyerrors.py

@@ -1145,6 +1145,13 @@ def reweight(weight, obs, **kwargs):
 def correlate(obs_a, obs_b):
     """Correlate two observables.
 
+    Attributes:
+    -----------
+    obs_a : Obs
+        First observable
+    obs_b : Obs
+        Second observable
+
     Keep in mind to only correlate primary observables which have not been reweighted
     yet. The reweighting has to be applied after correlating the observables.
     Currently only works if ensembles are identical. This is not really necessary.

tests/pyerrors_test.py

@@ -290,6 +290,14 @@ def test_merge_obs():
     assert diff == -(my_obs1.value + my_obs2.value) / 2
 
 
+def test_correlate():
+    my_obs1 = pe.Obs([np.random.rand(100)], ['t'])
+    my_obs2 = pe.Obs([np.random.rand(100)], ['t'])
+    corr1 = pe.correlate(my_obs1, my_obs2)
+    corr2 = pe.correlate(my_obs2, my_obs1)
+    assert corr1 == corr2
+
+
 def test_irregular_error_propagation():
     obs_list = [pe.Obs([np.random.rand(100)], ['t']),
                 pe.Obs([np.random.rand(50)], ['t'], idl=[range(1, 100, 2)]),