CHANGELOG updated, style improvements

CHANGELOG.md

@@ -2,6 +2,13 @@
 
 All notable changes to this project will be documented in this file.
 
+## [1.1.0] - 2021-09-29
+### Added
+- Corr class added
+- roots module added which can find the roots of a function that depends on Monte Carlo data via pyerrors Obs
+- input/hadrons module added which can read hdf5 files written by [Hadrons](https://github.com/aportelli/Hadrons)
+- read_rwms can now read reweighting factors in the format used by openQCD-2.0 
+
 ## [1.0.1] - 2020-11-03
 ### Fixed
 - Bug in pyerrors.covariance fixed that appeared when working with several

pyerrors/input/input.py

@@ -125,7 +125,7 @@ def read_sfcf_c(path, prefix, name, quarks='.*', noffset=0, wf=0, wf2=0, **kwarg
     b2b -- if True, read a time-dependent boundary-to-boundary correlation function
     names -- Alternative labeling for replicas/ensembles. Has to have the appropriate length
     """
-    
+
     if kwargs.get('im'):
         im = 1
         part = 'imaginary'

pyerrors/pyerrors.py

@@ -501,8 +501,8 @@ class Obs:
         else:
             if isinstance(y, np.ndarray):
                 return np.array([self + o for o in y])
-            elif(y.__class__.__name__=="Corr"):
-                return NotImplemented 
+            elif y.__class__.__name__ == 'Corr':
+                return NotImplemented
             else:
                 return derived_observable(lambda x, **kwargs: x[0] + y, [self], man_grad=[1])
     def __radd__(self, y):
@@ -515,9 +515,9 @@ class Obs:
         else:
             if isinstance(y, np.ndarray):
                 return np.array([self * o for o in y])
-            elif(y.__class__.__name__=="Corr"):
-                return NotImplemented 
-                
+            elif y.__class__.__name__ == 'Corr':
+                return NotImplemented
+
             else:
                 return derived_observable(lambda x, **kwargs: x[0] * y, [self], man_grad=[y])
 
@@ -531,9 +531,9 @@ class Obs:
         else:
             if isinstance(y, np.ndarray):
                 return np.array([self - o for o in y])
-            
-            elif(y.__class__.__name__=="Corr"):
-                return NotImplemented 
+
+            elif y.__class__.__name__ == 'Corr':
+                return NotImplemented
 
             else:
                 return derived_observable(lambda x, **kwargs: x[0] - y, [self], man_grad=[1])
@@ -554,7 +554,7 @@ class Obs:
             if isinstance(y, np.ndarray):
                 return np.array([self / o for o in y])
 
-            elif(y.__class__.__name__=="Corr"):
+            elif y.__class__.__name__ == 'Corr':
                 return NotImplemented
 
             else: