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refactor!: if clause in Obs.__init__ eliminated, empty observables need

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to be initialized with means=[] from now on.
This commit is contained in:
Fabian Joswig 2022-02-28 13:43:49 +00:00
parent 42df254288
commit 498a251072
3 changed files with 38 additions and 39 deletions
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67
pyerrors/obs.py
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@ -94,41 +94,40 @@ class Obs:
self.N = 0
self.is_merged = {}
self.idl = {}
if len(samples):
if idl is not None:
for name, idx in sorted(zip(names, idl)):
if isinstance(idx, range):
self.idl[name] = idx
elif isinstance(idx, (list, np.ndarray)):
dc = np.unique(np.diff(idx))
if np.any(dc < 0):
raise Exception("Unsorted idx for idl[%s]" % (name))
if len(dc) == 1:
self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
else:
self.idl[name] = list(idx)
if idl is not None:
for name, idx in sorted(zip(names, idl)):
if isinstance(idx, range):
self.idl[name] = idx
elif isinstance(idx, (list, np.ndarray)):
dc = np.unique(np.diff(idx))
if np.any(dc < 0):
raise Exception("Unsorted idx for idl[%s]" % (name))
if len(dc) == 1:
self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
else:
raise Exception('incompatible type for idl[%s].' % (name))
else:
for name, sample in sorted(zip(names, samples)):
self.idl[name] = range(1, len(sample) + 1)
self.idl[name] = list(idx)
else:
raise Exception('incompatible type for idl[%s].' % (name))
else:
for name, sample in sorted(zip(names, samples)):
self.idl[name] = range(1, len(sample) + 1)
if kwargs.get("means") is not None:
for name, sample, mean in sorted(zip(names, samples, kwargs.get("means"))):
self.shape[name] = len(self.idl[name])
self.N += self.shape[name]
self.r_values[name] = mean
self.deltas[name] = sample
else:
for name, sample in sorted(zip(names, samples)):
self.shape[name] = len(self.idl[name])
self.N += self.shape[name]
if len(sample) != self.shape[name]:
raise Exception('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
self.r_values[name] = np.mean(sample)
self.deltas[name] = sample - self.r_values[name]
self._value += self.shape[name] * self.r_values[name]
self._value /= self.N
if kwargs.get("means") is not None:
for name, sample, mean in sorted(zip(names, samples, kwargs.get("means"))):
self.shape[name] = len(self.idl[name])
self.N += self.shape[name]
self.r_values[name] = mean
self.deltas[name] = sample
else:
for name, sample in sorted(zip(names, samples)):
self.shape[name] = len(self.idl[name])
self.N += self.shape[name]
if len(sample) != self.shape[name]:
raise Exception('Incompatible samples and idx for %s: %d vs. %d' % (name, len(sample), self.shape[name]))
self.r_values[name] = np.mean(sample)
self.deltas[name] = sample - self.r_values[name]
self._value += self.shape[name] * self.r_values[name]
self._value /= self.N
self._dvalue = 0.0
self.ddvalue = 0.0
@ -1522,7 +1521,7 @@ def cov_Obs(means, cov, name, grad=None):
co : Covobs
Covobs to be embedded into the Obs
"""
o = Obs([], [])
o = Obs([], [], means=[])
o._value = co.value
o.names.append(co.name)
o._covobs[co.name] = co