From 763c759ae0aeeb83331e0e24eb380e99fdfcad02 Mon Sep 17 00:00:00 2001
From: Fabian Joswig <fabian.joswig@ed.ac.uk>
Date: Tue, 28 Jun 2022 14:40:49 +0100
Subject: [PATCH] fix: Corr.m_eff can now returns None entries if the
 correlator has a sign flip. Before that the logarithm of a negative number
 was computed and a warning was thrown.

---
 pyerrors/correlators.py   | 4 ++++
 tests/correlators_test.py | 9 +++++++++
 2 files changed, 13 insertions(+)

diff --git a/pyerrors/correlators.py b/pyerrors/correlators.py
index 0ebb6115..e0cccec8 100644
--- a/pyerrors/correlators.py
+++ b/pyerrors/correlators.py
@@ -604,6 +604,8 @@ class Corr:
             for t in range(self.T - 1):
                 if ((self.content[t] is None) or (self.content[t + 1] is None)) or (self.content[t + 1][0].value == 0):
                     newcontent.append(None)
+                elif self.content[t][0].value / self.content[t + 1][0].value < 0:
+                    newcontent.append(None)
                 else:
                     newcontent.append(self.content[t] / self.content[t + 1])
             if(all([x is None for x in newcontent])):
@@ -627,6 +629,8 @@ class Corr:
                 # Fill the two timeslices in the middle of the lattice with their predecessors
                 elif variant == 'sinh' and t in [self.T / 2, self.T / 2 - 1]:
                     newcontent.append(newcontent[-1])
+                elif self.content[t][0].value / self.content[t + 1][0].value < 0:
+                    newcontent.append(None)
                 else:
                     newcontent.append(np.abs(find_root(self.content[t][0] / self.content[t + 1][0], root_function, guess=guess)))
             if(all([x is None for x in newcontent])):
diff --git a/tests/correlators_test.py b/tests/correlators_test.py
index c1c79975..ee2c3eb7 100644
--- a/tests/correlators_test.py
+++ b/tests/correlators_test.py
@@ -105,6 +105,15 @@ def test_m_eff():
         my_corr.m_eff('unkown_variant')
 
 
+def test_m_eff_negative_values():
+    for padding in [0, 4]:
+        my_corr = pe.correlators.Corr([1.0 * pe.pseudo_Obs(10, 0.1, 't'), 1.0 * pe.pseudo_Obs(9, 0.05, 't'), -pe.pseudo_Obs(9, 0.1, 't')], padding=[padding, padding])
+        m_eff_log = my_corr.m_eff('log')
+        assert m_eff_log[padding + 1] is None
+        m_eff_cosh = my_corr.m_eff('cosh')
+        assert m_eff_cosh[padding + 1] is None
+
+
 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