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feat: removed attribute is_merged.
This commit is contained in:
Fabian Joswig
parent
b708411830
commit
a53fb18821
6 changed files with 2 additions and 28 deletions
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@ -41,8 +41,6 @@ def create_json_string(ol, description='', indent=1):
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for r_name in ol[0].e_content[name]:
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rd = {}
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rd['name'] = r_name
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if ol[0].is_merged.get(r_name, False):
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rd['is_merged'] = True
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rd['deltas'] = []
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offsets = [o.r_values[r_name] - o.value for o in ol]
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deltas = np.column_stack([ol[oi].deltas[r_name] + offsets[oi] for oi in range(No)])
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@ -138,7 +136,6 @@ def create_json_string(ol, description='', indent=1):
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for name in obs._covobs:
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my_obs.names.append(name)
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my_obs.reweighted = obs.reweighted
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my_obs.is_merged = obs.is_merged
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return my_obs
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def write_Corr_to_dict(my_corr):
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@ -258,7 +255,6 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
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retd['names'] = []
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retd['idl'] = []
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retd['deltas'] = []
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retd['is_merged'] = {}
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for ens in d:
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for rep in ens['replica']:
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rep_name = rep['name']
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@ -270,7 +266,6 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
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retd['names'].append(rep_name)
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retd['idl'].append([di[0] for di in rep['deltas']])
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retd['deltas'].append(np.array([di[1:] for di in rep['deltas']]))
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retd['is_merged'][rep_name] = rep.get('is_merged', False)
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return retd
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def _gen_covobsd_from_cdatad(d):
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@ -300,7 +295,6 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
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if od:
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ret = Obs([[ddi[0] + values[0] for ddi in di] for di in od['deltas']], od['names'], idl=od['idl'])
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ret._value = values[0]
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ret.is_merged = od['is_merged']
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else:
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ret = Obs([], [], means=[])
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ret._value = values[0]
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@ -326,7 +320,6 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
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if od:
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ret.append(Obs([list(di[:, i] + values[i]) for di in od['deltas']], od['names'], idl=od['idl']))
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ret[-1]._value = values[i]
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ret[-1].is_merged = od['is_merged']
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else:
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ret.append(Obs([], [], means=[]))
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ret[-1]._value = values[i]
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@ -354,7 +347,6 @@ def _parse_json_dict(json_dict, verbose=True, full_output=False):
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if od:
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ret.append(Obs([di[:, i] + values[i] for di in od['deltas']], od['names'], idl=od['idl']))
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ret[-1]._value = values[i]
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ret[-1].is_merged = od['is_merged']
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else:
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ret.append(Obs([], [], means=[]))
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ret[-1]._value = values[i]
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@ -932,7 +932,6 @@ def qtop_projection(qtop, target=0):
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proj_qtop.append(np.array([1 if round(qtop.r_values[n] + q) == target else 0 for q in qtop.deltas[n]]))
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reto = Obs(proj_qtop, qtop.names, idl=[qtop.idl[name] for name in qtop.names])
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reto.is_merged = qtop.is_merged
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return reto
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@ -109,7 +109,7 @@ def _assert_equal_properties(ol, otype=Obs):
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for o in ol[1:]:
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if not isinstance(o, otype):
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raise Exception("Wrong data type in list.")
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for attr in ["is_merged", "reweighted", "e_content", "idl"]:
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for attr in ["reweighted", "e_content", "idl"]:
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if hasattr(ol[0], attr):
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if not getattr(ol[0], attr) == getattr(o, attr):
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raise Exception(f"All Obs in list have to have the same state '{attr}'.")
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@ -49,7 +49,7 @@ class Obs:
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'ddvalue', 'reweighted', 'S', 'tau_exp', 'N_sigma',
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'e_dvalue', 'e_ddvalue', 'e_tauint', 'e_dtauint',
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'e_windowsize', 'e_rho', 'e_drho', 'e_n_tauint', 'e_n_dtauint',
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'idl', 'is_merged', 'tag', '_covobs', '__dict__']
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'idl', 'tag', '_covobs', '__dict__']
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S_global = 2.0
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S_dict = {}
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@ -97,7 +97,6 @@ class Obs:
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self._value = 0
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self.N = 0
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self.is_merged = {}
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self.idl = {}
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if idl is not None:
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for name, idx in sorted(zip(names, idl)):
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@ -1153,7 +1152,6 @@ def derived_observable(func, data, array_mode=False, **kwargs):
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new_cov_names = sorted(set([y for x in [o.cov_names for o in raveled_data] for y in x]))
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new_sample_names = sorted(set(new_names) - set(new_cov_names))
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is_merged = {name: (len(list(filter(lambda o: o.is_merged.get(name, False) is True, raveled_data))) > 0) for name in new_sample_names}
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reweighted = len(list(filter(lambda o: o.reweighted is True, raveled_data))) > 0
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if data.ndim == 1:
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@ -1179,8 +1177,6 @@ def derived_observable(func, data, array_mode=False, **kwargs):
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tmp_values = np.array(tmp_values).reshape(data.shape)
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new_r_values[name] = func(tmp_values, **kwargs)
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new_idl_d[name] = _merge_idx(idl)
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if not is_merged[name]:
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is_merged[name] = (1 != len(set([len(idx) for idx in [*idl, new_idl_d[name]]])))
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if 'man_grad' in kwargs:
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deriv = np.asarray(kwargs.get('man_grad'))
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@ -1266,7 +1262,6 @@ def derived_observable(func, data, array_mode=False, **kwargs):
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final_result[i_val].names.append(name)
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final_result[i_val]._covobs = new_covobs
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final_result[i_val]._value = new_val
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final_result[i_val].is_merged = is_merged
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final_result[i_val].reweighted = reweighted
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if multi == 0:
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@ -1347,7 +1342,6 @@ def reweight(weight, obs, **kwargs):
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result.append(tmp_obs / new_weight)
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result[-1].reweighted = True
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result[-1].is_merged = obs[i].is_merged
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return result
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@ -1391,7 +1385,6 @@ def correlate(obs_a, obs_b):
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new_idl.append(obs_a.idl[name])
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o = Obs(new_samples, sorted(obs_a.names), idl=new_idl)
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o.is_merged = {name: (obs_a.is_merged.get(name, False) or obs_b.is_merged.get(name, False)) for name in o.names}
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o.reweighted = obs_a.reweighted or obs_b.reweighted
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return o
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@ -1589,7 +1582,6 @@ def merge_obs(list_of_obs):
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names = sorted(new_dict.keys())
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o = Obs([new_dict[name] for name in names], names, idl=[idl_dict[name] for name in names])
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o.is_merged = {name: np.any([oi.is_merged.get(name, False) for oi in list_of_obs]) for name in o.names}
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o.reweighted = np.max([oi.reweighted for oi in list_of_obs])
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return o
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@ -404,11 +404,4 @@ def assert_equal_Obs(to, ro):
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if not np.allclose(v, v2, atol=1e-14):
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print(kw, "does not match.")
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return False
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m_to = getattr(to, "is_merged")
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m_ro = getattr(ro, "is_merged")
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if not m_to == m_ro:
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if not (all(value is False for value in m_ro.values()) and all(value is False for value in m_to.values())):
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print("is_merged", "does not match.")
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return False
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return True
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@ -201,8 +201,6 @@ def test_matmul_irregular_histories():
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t2 = pe.linalg.matmul(standard_matrix, irregular_matrix)
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assert np.all([o.is_zero() for o in (t1 - t2).ravel()])
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assert np.all([o.is_merged for o in t1.ravel()])
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assert np.all([o.is_merged for o in t2.ravel()])
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def test_irregular_matrix_inverse():
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