diff --git a/docs/pyerrors/obs.html b/docs/pyerrors/obs.html
index 809eac44..d38d1d51 100644
--- a/docs/pyerrors/obs.html
+++ b/docs/pyerrors/obs.html
@@ -280,21 +280,21 @@
73
74 if kwargs.get("means") is None and len(samples):
75 if len(samples) != len(names):
- 76 raise Exception('Length of samples and names incompatible.')
+ 76 raise ValueError('Length of samples and names incompatible.')
77 if idl is not None:
78 if len(idl) != len(names):
- 79 raise Exception('Length of idl incompatible with samples and names.')
+ 79 raise ValueError('Length of idl incompatible with samples and names.')
80 name_length = len(names)
81 if name_length > 1:
82 if name_length != len(set(names)):
- 83 raise Exception('names are not unique.')
+ 83 raise ValueError('Names are not unique.')
84 if not all(isinstance(x, str) for x in names):
85 raise TypeError('All names have to be strings.')
86 else:
87 if not isinstance(names[0], str):
88 raise TypeError('All names have to be strings.')
89 if min(len(x) for x in samples) <= 4:
- 90 raise Exception('Samples have to have at least 5 entries.')
+ 90 raise ValueError('Samples have to have at least 5 entries.')
91
92 self.names = sorted(names)
93 self.shape = {}
@@ -312,13 +312,13 @@
105 elif isinstance(idx, (list, np.ndarray)):
106 dc = np.unique(np.diff(idx))
107 if np.any(dc < 0):
- 108 raise Exception("Unsorted idx for idl[%s]" % (name))
+ 108 raise ValueError("Unsorted idx for idl[%s]" % (name))
109 if len(dc) == 1:
110 self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
111 else:
112 self.idl[name] = list(idx)
113 else:
- 114 raise Exception('incompatible type for idl[%s].' % (name))
+ 114 raise TypeError('incompatible type for idl[%s].' % (name))
115 else:
116 for name, sample in sorted(zip(names, samples)):
117 self.idl[name] = range(1, len(sample) + 1)
@@ -334,7 +334,7 @@
127 self.shape[name] = len(self.idl[name])
128 self.N += self.shape[name]
129 if len(sample) != self.shape[name]:
- 130 raise Exception('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
+ 130 raise ValueError('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
131 self.r_values[name] = np.mean(sample)
132 self.deltas[name] = sample - self.r_values[name]
133 self._value += self.shape[name] * self.r_values[name]
@@ -1908,21 +1908,21 @@
74
75 if kwargs.get("means") is None and len(samples):
76 if len(samples) != len(names):
- 77 raise Exception('Length of samples and names incompatible.')
+ 77 raise ValueError('Length of samples and names incompatible.')
78 if idl is not None:
79 if len(idl) != len(names):
- 80 raise Exception('Length of idl incompatible with samples and names.')
+ 80 raise ValueError('Length of idl incompatible with samples and names.')
81 name_length = len(names)
82 if name_length > 1:
83 if name_length != len(set(names)):
- 84 raise Exception('names are not unique.')
+ 84 raise ValueError('Names are not unique.')
85 if not all(isinstance(x, str) for x in names):
86 raise TypeError('All names have to be strings.')
87 else:
88 if not isinstance(names[0], str):
89 raise TypeError('All names have to be strings.')
90 if min(len(x) for x in samples) <= 4:
- 91 raise Exception('Samples have to have at least 5 entries.')
+ 91 raise ValueError('Samples have to have at least 5 entries.')
92
93 self.names = sorted(names)
94 self.shape = {}
@@ -1940,13 +1940,13 @@
106 elif isinstance(idx, (list, np.ndarray)):
107 dc = np.unique(np.diff(idx))
108 if np.any(dc < 0):
-109 raise Exception("Unsorted idx for idl[%s]" % (name))
+109 raise ValueError("Unsorted idx for idl[%s]" % (name))
110 if len(dc) == 1:
111 self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
112 else:
113 self.idl[name] = list(idx)
114 else:
-115 raise Exception('incompatible type for idl[%s].' % (name))
+115 raise TypeError('incompatible type for idl[%s].' % (name))
116 else:
117 for name, sample in sorted(zip(names, samples)):
118 self.idl[name] = range(1, len(sample) + 1)
@@ -1962,7 +1962,7 @@
128 self.shape[name] = len(self.idl[name])
129 self.N += self.shape[name]
130 if len(sample) != self.shape[name]:
-131 raise Exception('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
+131 raise ValueError('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
132 self.r_values[name] = np.mean(sample)
133 self.deltas[name] = sample - self.r_values[name]
134 self._value += self.shape[name] * self.r_values[name]
@@ -2762,21 +2762,21 @@ this overwrites the standard value for that ensemble.
74
75 if kwargs.get("means") is None and len(samples):
76 if len(samples) != len(names):
- 77 raise Exception('Length of samples and names incompatible.')
+ 77 raise ValueError('Length of samples and names incompatible.')
78 if idl is not None:
79 if len(idl) != len(names):
- 80 raise Exception('Length of idl incompatible with samples and names.')
+ 80 raise ValueError('Length of idl incompatible with samples and names.')
81 name_length = len(names)
82 if name_length > 1:
83 if name_length != len(set(names)):
- 84 raise Exception('names are not unique.')
+ 84 raise ValueError('Names are not unique.')
85 if not all(isinstance(x, str) for x in names):
86 raise TypeError('All names have to be strings.')
87 else:
88 if not isinstance(names[0], str):
89 raise TypeError('All names have to be strings.')
90 if min(len(x) for x in samples) <= 4:
- 91 raise Exception('Samples have to have at least 5 entries.')
+ 91 raise ValueError('Samples have to have at least 5 entries.')
92
93 self.names = sorted(names)
94 self.shape = {}
@@ -2794,13 +2794,13 @@ this overwrites the standard value for that ensemble.
106 elif isinstance(idx, (list, np.ndarray)):
107 dc = np.unique(np.diff(idx))
108 if np.any(dc < 0):
-109 raise Exception("Unsorted idx for idl[%s]" % (name))
+109 raise ValueError("Unsorted idx for idl[%s]" % (name))
110 if len(dc) == 1:
111 self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
112 else:
113 self.idl[name] = list(idx)
114 else:
-115 raise Exception('incompatible type for idl[%s].' % (name))
+115 raise TypeError('incompatible type for idl[%s].' % (name))
116 else:
117 for name, sample in sorted(zip(names, samples)):
118 self.idl[name] = range(1, len(sample) + 1)
@@ -2816,7 +2816,7 @@ this overwrites the standard value for that ensemble.
128 self.shape[name] = len(self.idl[name])
129 self.N += self.shape[name]
130 if len(sample) != self.shape[name]:
-131 raise Exception('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
+131 raise ValueError('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
132 self.r_values[name] = np.mean(sample)
133 self.deltas[name] = sample - self.r_values[name]
134 self._value += self.shape[name] * self.r_values[name]