Merge branch 'develop' into documentation

pyerrors/dirac.py

@@ -22,6 +22,30 @@ identity = np.array(
     dtype=complex)
 
 
+def epsilon_tensor(i, j, k):
+    """Rank-3 epsilon tensor
+
+    Based on https://codegolf.stackexchange.com/a/160375
+    """
+    test_set = set((i, j, k))
+    if not (test_set <= set((1, 2, 3)) or test_set <= set((0, 1, 2))):
+        raise Exception("Unexpected input", i, j, k)
+
+    return (i - j) * (j - k) * (k - i) / 2
+
+
+def epsilon_tensor_rank4(i, j, k, o):
+    """Rank-4 epsilon tensor
+
+    Extension of https://codegolf.stackexchange.com/a/160375
+    """
+    test_set = set((i, j, k, o))
+    if not (test_set <= set((1, 2, 3, 4)) or test_set <= set((0, 1, 2, 3))):
+        raise Exception("Unexpected input", i, j, k, o)
+
+    return (i - j) * (j - k) * (k - i) * (i - o) * (j - o) * (o - k) / 12
+
+
 def Grid_gamma(gamma_tag):
     """Returns gamma matrix in Grid labeling."""
     if gamma_tag == 'Identity':

pyerrors/input/hadrons.py

@@ -298,18 +298,6 @@ def read_Fourquark_hd5(path, filestem, ens_id, idl=None, vertices=["VA", "AV"]):
     return result_dict
 
 
-def _epsilon_tensor(i, j, k, o):
-    """Rank-4 epsilon tensor
-
-    Extension of https://codegolf.stackexchange.com/a/160375
-    """
-    test_set = set((i, j, k, o))
-    if not (test_set <= set((1, 2, 3, 4)) or test_set <= set((0, 1, 2, 3))):
-        raise Exception("Unexpected input", i, j, k, o)
-
-    return (i - j) * (j - k) * (k - i) * (i - o) * (j - o) * (o - k) / 12
-
-
 def _get_lorentz_names(name):
     assert len(name) == 2
 

pyerrors/obs.py

@@ -434,10 +434,6 @@ class Obs:
                 my_string_list.append(my_string)
             print('\n'.join(my_string_list))
 
-    def print(self, level=1):
-        warnings.warn("Method 'print' renamed to 'details'", DeprecationWarning)
-        self.details(level > 1)
-
     def is_zero_within_error(self, sigma=1):
         """Checks whether the observable is zero within 'sigma' standard errors.
 
@@ -799,9 +795,6 @@ class Obs:
     def arctanh(self):
         return derived_observable(lambda x: anp.arctanh(x[0]), [self])
 
-    def sinc(self):
-        return derived_observable(lambda x: anp.sinc(x[0]), [self])
-
 
 class CObs:
     """Class for a complex valued observable."""

tests/dirac_test.py

@@ -32,3 +32,32 @@ def test_grid_dirac():
         pe.dirac.Grid_gamma(gamma)
     with pytest.raises(Exception):
         pe.dirac.Grid_gamma('Not a gamma matrix')
+
+
+def test_epsilon_tensor():
+    check = {(1, 2, 3) : 1.0,
+             (3, 1, 2) : 1.0,
+             (2, 3, 1) : 1.0,
+             (1, 1, 1) : 0.0,
+             (3, 2, 1) : -1.0,
+             (1, 3, 2) : -1.0,
+             (1, 1, 3) : 0.0}
+    for key, value in check.items():
+        assert pe.dirac.epsilon_tensor(*key) == value
+    with pytest.raises(Exception):
+        pe.dirac.epsilon_tensor(0, 1, 3)
+
+
+def test_epsilon_tensor_rank4():
+    check = {(1, 4, 3, 2) : -1.0,
+             (1, 2, 3, 4) : 1.0,
+             (2, 1, 3, 4) : -1.0,
+             (4, 3, 2, 1) : 1.0,
+             (3, 2, 4, 3) : 0.0,
+             (0, 1, 2, 3) : 1.0,
+             (1, 1, 1, 1) : 0.0,
+             (1, 2, 3, 1) : 0.0}
+    for key, value in check.items():
+        assert pe.dirac.epsilon_tensor_rank4(*key) == value
+    with pytest.raises(Exception):
+        pe.dirac.epsilon_tensor_rank4(0, 1, 3, 4)

tests/obs_test.py

@@ -57,6 +57,7 @@ def test_dump():
     value = np.random.normal(5, 10)
     dvalue = np.abs(np.random.normal(0, 1))
     test_obs = pe.pseudo_Obs(value, dvalue, 't')
+    test_obs.dump('test_dump', path=".")
     test_obs.dump('test_dump')
     new_obs = pe.load_object('test_dump.p')
     os.remove('test_dump.p')
@@ -105,6 +106,12 @@ def test_function_overloading():
     assert np.sqrt(b ** 2) == b
     assert np.sqrt(b) ** 2 == b
 
+    np.arcsin(1 / b)
+    np.arccos(1 / b)
+    np.arctan(1 / b)
+    np.arctanh(1 / b)
+    np.sinc(1 / b)
+
 
 def test_overloading_vectorization():
     a = np.random.randint(1, 100, 10)
@@ -428,6 +435,14 @@ def test_reweighting():
     assert r_obs[0].reweighted
     r_obs2 = r_obs[0] * my_obs
     assert r_obs2.reweighted
+    my_covobs = pe.cov_Obs(1.0, 0.003, 'cov')
+    with pytest.raises(Exception):
+        pe.reweight(my_obs, [my_covobs])
+    my_obs2 = pe.Obs([np.random.rand(1000)], ['t2'])
+    with pytest.raises(Exception):
+        pe.reweight(my_obs, [my_obs + my_obs2])
+    with pytest.raises(Exception):
+        pe.reweight(my_irregular_obs, [my_obs])
 
 
 def test_merge_obs():
@@ -436,6 +451,12 @@ def test_merge_obs():
     merged = pe.merge_obs([my_obs1, my_obs2])
     diff = merged - my_obs2 - my_obs1
     assert diff == -(my_obs1.value + my_obs2.value) / 2
+    with pytest.raises(Exception):
+        pe.merge_obs([my_obs1, my_obs1])
+    my_covobs = pe.cov_Obs(1.0, 0.003, 'cov')
+    with pytest.raises(Exception):
+        pe.merge_obs([my_obs1, my_covobs])
+
 
 
 def test_merge_obs_r_values():
@@ -468,6 +489,17 @@ def test_correlate():
     corr3 = pe.correlate(my_obs5, my_obs6)
     assert my_obs5.idl == corr3.idl
 
+    my_new_obs = pe.Obs([np.random.rand(100)], ['q3'])
+    with pytest.raises(Exception):
+        pe.correlate(my_obs1, my_new_obs)
+    my_covobs = pe.cov_Obs(1.0, 0.003, 'cov')
+    with pytest.raises(Exception):
+        pe.correlate(my_covobs, my_covobs)
+    r_obs = pe.reweight(my_obs1, [my_obs1])[0]
+    with pytest.warns(RuntimeWarning):
+        pe.correlate(r_obs, r_obs)
+
+
 
 def test_irregular_error_propagation():
     obs_list = [pe.Obs([np.random.rand(100)], ['t']),