feat!: merged the parameters padding_front and padding_back of Corr into

one parameter padding

pyerrors/__init__.py

@@ -206,7 +206,7 @@ print(my_corr)
 ```
 In case the correlation functions are not defined on the outermost timeslices, for example because of fixed boundary conditions, a padding can be introduced.
 ```python
-my_corr = pe.Corr([obs_0, obs_1, obs_2, obs_3], padding_front=1, padding_back=1)
+my_corr = pe.Corr([obs_0, obs_1, obs_2, obs_3], padding=[1, 1])
 print(my_corr)
 > x0/a	Corr(x0/a)
 > ------------------

pyerrors/correlators.py

@@ -23,7 +23,7 @@ class Corr:
 
     """
 
-    def __init__(self, data_input, padding_front=0, padding_back=0, prange=None):
+    def __init__(self, data_input, padding=[0, 0], prange=None):
         # All data_input should be a list of things at different timeslices. This needs to be verified
 
         if not isinstance(data_input, list):
@@ -53,7 +53,7 @@ class Corr:
 
         # We now apply some padding to our list. In case that our list represents a correlator of length T but is not defined at every value.
         # An undefined timeslice is represented by the None object
-        self.content = [None] * padding_front + self.content + [None] * padding_back
+        self.content = [None] * padding[0] + self.content + [None] * padding[1]
         self.T = len(self.content)  # for convenience: will be used a lot
 
         # The attribute "range" [start,end] marks a range of two timeslices.
@@ -331,7 +331,7 @@ class Corr:
                     newcontent.append(self.content[t + 1] - self.content[t])
             if(all([x is None for x in newcontent])):
                 raise Exception("Derivative is undefined at all timeslices")
-            return Corr(newcontent, padding_back=1)
+            return Corr(newcontent, padding=[0, 1])
         if symmetric:
             newcontent = []
             for t in range(1, self.T - 1):
@@ -341,7 +341,7 @@ class Corr:
                     newcontent.append(0.5 * (self.content[t + 1] - self.content[t - 1]))
             if(all([x is None for x in newcontent])):
                 raise Exception('Derivative is undefined at all timeslices')
-            return Corr(newcontent, padding_back=1, padding_front=1)
+            return Corr(newcontent, padding=[1, 1])
 
     def second_deriv(self):
         """Return the second derivative of the correlator with respect to x0."""
@@ -353,7 +353,7 @@ class Corr:
                 newcontent.append((self.content[t + 1] - 2 * self.content[t] + self.content[t - 1]))
         if(all([x is None for x in newcontent])):
             raise Exception("Derivative is undefined at all timeslices")
-        return Corr(newcontent, padding_back=1, padding_front=1)
+        return Corr(newcontent, padding=[1, 1])
 
     def m_eff(self, variant='log', guess=1.0):
         """Returns the effective mass of the correlator as correlator object
@@ -381,7 +381,7 @@ class Corr:
             if(all([x is None for x in newcontent])):
                 raise Exception('m_eff is undefined at all timeslices')
 
-            return np.log(Corr(newcontent, padding_back=1))
+            return np.log(Corr(newcontent, padding=[0, 1]))
 
         elif variant in ['periodic', 'cosh', 'sinh']:
             if variant in ['periodic', 'cosh']:
@@ -404,7 +404,7 @@ class Corr:
             if(all([x is None for x in newcontent])):
                 raise Exception('m_eff is undefined at all timeslices')
 
-            return Corr(newcontent, padding_back=1)
+            return Corr(newcontent, padding=[0, 1])
 
         elif variant == 'arccosh':
             newcontent = []
@@ -415,7 +415,7 @@ class Corr:
                     newcontent.append((self.content[t + 1] + self.content[t - 1]) / (2 * self.content[t]))
             if(all([x is None for x in newcontent])):
                 raise Exception("m_eff is undefined at all timeslices")
-            return np.arccosh(Corr(newcontent, padding_back=1, padding_front=1))
+            return np.arccosh(Corr(newcontent, padding=[1, 1]))
 
         else:
             raise Exception('Unknown variant.')

pyerrors/input/json.py

@@ -402,7 +402,7 @@ def import_json_string(json_string, verbose=True, full_output=False):
         if len(tmp_o['tag']) == 0:
             del tmp_o['tag']
         dat = get_Array_from_dict(tmp_o)
-        my_corr = Corr(list(dat), padding_front=padding_front, padding_back=padding_back)
+        my_corr = Corr(list(dat), padding=[padding_front, padding_back])
         if corr_tag != 'None':
             my_corr.tag = corr_tag
         return my_corr

tests/correlators_test.py

@@ -115,7 +115,7 @@ def test_plateau():
 
 def test_padded_correlator():
     my_list = [pe.Obs([np.random.normal(1.0, 0.1, 100)], ['ens1']) for o in range(8)]
-    my_corr = pe.Corr(my_list, padding_front=7, padding_back=3)
+    my_corr = pe.Corr(my_list, padding=[7, 3])
     my_corr.reweighted
     [o for o in my_corr]
 

tests/io_test.py

@@ -101,7 +101,7 @@ def test_json_corr_io():
             for fp in [0, 2]:
                 for bp in [0, 7]:
                     for corr_tag in [None, 'my_Corr_tag']:
-                        my_corr = pe.Corr(obs_list, padding_front=fp, padding_back=bp)
+                        my_corr = pe.Corr(obs_list, padding=[fp, bp])
                         my_corr.tag = corr_tag
                         pe.input.json.dump_to_json(my_corr, 'corr')
                         recover = pe.input.json.load_json('corr')
@@ -116,7 +116,7 @@ def test_json_corr_2d_io():
     for tag in [None, "test"]:
         obs_list[3][0, 1].tag = tag
         for padding in [0, 1]:
-            my_corr = pe.Corr(obs_list, padding_front=padding, padding_back=padding)
+            my_corr = pe.Corr(obs_list, padding=[padding, padding])
             my_corr.tag = tag
             pe.input.json.dump_to_json(my_corr, 'corr')
             recover = pe.input.json.load_json('corr')