From c1de17e9396d3ef2ac82e636d7f8db80e56f68bc Mon Sep 17 00:00:00 2001 From: fjosw Date: Thu, 2 Mar 2023 18:55:32 +0000 Subject: [PATCH] Documentation updated --- docs/pyerrors/obs.html | 42 +++++++++++++++++++++--------------------- 1 file changed, 21 insertions(+), 21 deletions(-) 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]