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feat: new_cov_names and new_sample_names added to derived_array

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Fabian Joswig 2021-12-02 16:54:51 +00:00
parent 15dd10f19a
commit 5789c0cef6
1 changed files with 8 additions and 5 deletions
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13
pyerrors/obs.py
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@ -1048,6 +1048,7 @@ def derived_observable(func, data, array_mode=False, **kwargs):
raveled_data = data.ravel()
# Workaround for matrix operations containing non Obs data
# TODO: Find more elegant solution here.
for i_data in raveled_data:
if isinstance(i_data, Obs):
first_name = i_data.names[0]
@ -1070,11 +1071,13 @@ def derived_observable(func, data, array_mode=False, **kwargs):
n_obs = len(raveled_data)
new_names = sorted(set([y for x in [o.names for o in raveled_data] for y in x]))
new_cov_names = sorted(set([y for x in [o.cov_names for o in raveled_data] for y in x]))
new_sample_names = sorted(set(new_names) - set(new_cov_names))
is_merged = {name: (len(list(filter(lambda o: o.is_merged.get(name, False) is True, raveled_data))) > 0) for name in new_names}
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}
reweighted = len(list(filter(lambda o: o.reweighted is True, raveled_data))) > 0
new_idl_d = {}
for name in new_names:
for name in new_sample_names:
idl = []
for i_data in raveled_data:
tmp = i_data.idl.get(name)
@ -1096,7 +1099,7 @@ def derived_observable(func, data, array_mode=False, **kwargs):
multi = 1
new_r_values = {}
for name in new_names:
for name in new_sample_names:
tmp_values = np.zeros(n_obs)
for i, item in enumerate(raveled_data):
tmp = item.r_values.get(name)
@ -1140,7 +1143,7 @@ def derived_observable(func, data, array_mode=False, **kwargs):
if array_mode is True:
d_extracted = {}
for name in new_names:
for name in new_sample_names:
d_extracted[name] = []
for i_dat, dat in enumerate(data):
ens_length = len(new_idl_d[name])
@ -1150,7 +1153,7 @@ def derived_observable(func, data, array_mode=False, **kwargs):
new_deltas = {}
new_grad = {}
if array_mode is True:
for name in new_names:
for name in new_sample_names:
ens_length = d_extracted[name][0].shape[-1]
new_deltas[name] = np.zeros(ens_length)
for i_dat, dat in enumerate(d_extracted[name]):