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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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6
pyerrors/input/json.py
View file

@ -358,7 +358,7 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
ret = Obs([[ddi[0] + values[0] for ddi in di] for di in od['deltas']], od['names'], idl=od['idl']) ret = Obs([[ddi[0] + values[0] for ddi in di] for di in od['deltas']], od['names'], idl=od['idl'])
ret.is_merged = od['is_merged'] ret.is_merged = od['is_merged']
else: else:
ret = Obs([], []) ret = Obs([], [], means=[])
ret._value = values[0] ret._value = values[0]
for name in cd: for name in cd:
co = cd[name][0] co = cd[name][0]
@ -383,7 +383,7 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
ret.append(Obs([list(di[:, i] + values[i]) for di in od['deltas']], od['names'], idl=od['idl'])) ret.append(Obs([list(di[:, i] + values[i]) for di in od['deltas']], od['names'], idl=od['idl']))
ret[-1].is_merged = od['is_merged'] ret[-1].is_merged = od['is_merged']
else: else:
ret.append(Obs([], [])) ret.append(Obs([], [], means=[]))
ret[-1]._value = values[i] ret[-1]._value = values[i]
print('Created Obs with means= ', values[i]) print('Created Obs with means= ', values[i])
for name in cd: for name in cd:
@ -410,7 +410,7 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
ret.append(Obs([di[:, i] + values[i] for di in od['deltas']], od['names'], idl=od['idl'])) ret.append(Obs([di[:, i] + values[i] for di in od['deltas']], od['names'], idl=od['idl']))
ret[-1].is_merged = od['is_merged'] ret[-1].is_merged = od['is_merged']
else: else:
ret.append(Obs([], [])) ret.append(Obs([], [], means=[]))
ret[-1]._value = values[i] ret[-1]._value = values[i]
for name in cd: for name in cd:
co = cd[name][i] co = cd[name][i]

67
pyerrors/obs.py
View file

@ -94,41 +94,40 @@ class Obs:
self.N = 0 self.N = 0
self.is_merged = {} self.is_merged = {}
self.idl = {} self.idl = {}
if len(samples): if idl is not None:
if idl is not None: for name, idx in sorted(zip(names, idl)):
for name, idx in sorted(zip(names, idl)): if isinstance(idx, range):
if isinstance(idx, range): self.idl[name] = idx
self.idl[name] = idx elif isinstance(idx, (list, np.ndarray)):
elif isinstance(idx, (list, np.ndarray)): dc = np.unique(np.diff(idx))
dc = np.unique(np.diff(idx)) if np.any(dc < 0):
if np.any(dc < 0): raise Exception("Unsorted idx for idl[%s]" % (name))
raise Exception("Unsorted idx for idl[%s]" % (name)) if len(dc) == 1:
if len(dc) == 1: self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
else:
self.idl[name] = list(idx)
else: else:
raise Exception('incompatible type for idl[%s].' % (name)) self.idl[name] = list(idx)
else: else:
for name, sample in sorted(zip(names, samples)): raise Exception('incompatible type for idl[%s].' % (name))
self.idl[name] = range(1, len(sample) + 1) else:
for name, sample in sorted(zip(names, samples)):
self.idl[name] = range(1, len(sample) + 1)
if kwargs.get("means") is not None: if kwargs.get("means") is not None:
for name, sample, mean in sorted(zip(names, samples, kwargs.get("means"))): for name, sample, mean in sorted(zip(names, samples, kwargs.get("means"))):
self.shape[name] = len(self.idl[name]) self.shape[name] = len(self.idl[name])
self.N += self.shape[name] self.N += self.shape[name]
self.r_values[name] = mean self.r_values[name] = mean
self.deltas[name] = sample self.deltas[name] = sample
else: else:
for name, sample in sorted(zip(names, samples)): for name, sample in sorted(zip(names, samples)):
self.shape[name] = len(self.idl[name]) self.shape[name] = len(self.idl[name])
self.N += self.shape[name] self.N += self.shape[name]
if len(sample) != 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])) 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.r_values[name] = np.mean(sample)
self.deltas[name] = sample - self.r_values[name] self.deltas[name] = sample - self.r_values[name]
self._value += self.shape[name] * self.r_values[name] self._value += self.shape[name] * self.r_values[name]
self._value /= self.N self._value /= self.N
self._dvalue = 0.0 self._dvalue = 0.0
self.ddvalue = 0.0 self.ddvalue = 0.0
@ -1522,7 +1521,7 @@ def cov_Obs(means, cov, name, grad=None):
co : Covobs co : Covobs
Covobs to be embedded into the Obs Covobs to be embedded into the Obs
""" """
o = Obs([], []) o = Obs([], [], means=[])
o._value = co.value o._value = co.value
o.names.append(co.name) o.names.append(co.name)
o._covobs[co.name] = co o._covobs[co.name] = co

2
tests/obs_test.py
View file

@ -653,7 +653,7 @@ def test_covariance_symmetry():
def test_empty_obs(): def test_empty_obs():
o = pe.Obs([np.random.rand(100)], ['test']) o = pe.Obs([np.random.rand(100)], ['test'])
q = o + pe.Obs([], []) q = o + pe.Obs([], [], means=[])
assert q == o assert q == o