diff --git a/pyerrors/npr.py b/pyerrors/npr.py
index 3be5b4df..d33f8eee 100644
--- a/pyerrors/npr.py
+++ b/pyerrors/npr.py
@@ -1,23 +1,23 @@
 import numpy as np
 
 
-gamma = [0, 0, 0, 0]
-gamma[0] = np.array(
+gammaX = np.array(
     [[0, 0, 0, 1j], [0, 0, 1j, 0], [0, -1j, 0, 0], [-1j, 0, 0, 0]],
     dtype=complex)
-gamma[1] = np.array(
+gammaY = np.array(
     [[0, 0, 0, -1], [0, 0, 1, 0], [0, 1, 0, 0], [-1, 0, 0, 0]],
     dtype=complex)
-gamma[2] = np.array(
+gammaZ = np.array(
     [[0, 0, 1j, 0], [0, 0, 0, -1j], [-1j, 0, 0, 0], [0, 1j, 0, 0]],
     dtype=complex)
-gamma[3] = np.array(
+gammaT = np.array(
     [[0, 0, 1, 0], [0, 0, 0, 1], [1, 0, 0, 0], [0, 1, 0, 0]],
     dtype=complex)
+gamma = np.array([gammaX, gammaY, gammaZ, gammaT])
 gamma5 = np.array(
     [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, -1, 0], [0, 0, 0, -1]],
     dtype=complex)
-imat = np.array(
+identity = np.array(
     [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]],
     dtype=complex)
 
@@ -25,7 +25,7 @@ imat = np.array(
 def Grid_gamma(gamma_tag):
     """Returns gamma matrix in Grid labeling."""
     if gamma_tag == 'Identity':
-        g = imat
+        g = identity
     elif gamma_tag == 'Gamma5':
         g = gamma5
     elif gamma_tag == 'GammaX':
@@ -87,7 +87,7 @@ class Npr_matrix(np.ndarray):
     def _propagate_mom(self, other, name):
         s_mom = getattr(self, name, None)
         o_mom = getattr(other, name, None)
-        if s_mom and o_mom:
+        if s_mom is not None and o_mom is not None:
             if not np.allclose(s_mom, o_mom):
                 raise Exception(name + ' does not match.')
         return o_mom if o_mom else s_mom
diff --git a/pyerrors/pyerrors.py b/pyerrors/pyerrors.py
index 644983ac..acb704c2 100644
--- a/pyerrors/pyerrors.py
+++ b/pyerrors/pyerrors.py
@@ -337,8 +337,12 @@ class Obs:
                 for e_name in self.e_names:
                     print(e_name, ':', self.e_content[e_name])
 
-    def is_zero_within_error(self):
-        return np.abs(self.value) <= self.dvalue
+    def is_zero_within_error(self, sigma=1):
+        """ Checks whether the observable is zero within 'sigma' standard errors.
+
+        Works only properly when the gamma method was run.
+        """
+        return np.abs(self.value) <= sigma * self.dvalue
 
     def is_zero(self):
         return np.isclose(0.0, self.value) and all(np.allclose(0.0, delta) for delta in self.deltas.values())