Merge pull request #34 from fjosw/feature/json_corr_Nd

Feature/json corr nd
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Fabian Joswig 2022-01-18 12:59:37 +00:00 committed by GitHub
commit bf20274b67
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3 changed files with 71 additions and 1 deletions

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@ -8,6 +8,7 @@ import platform
import warnings
from ..obs import Obs
from ..covobs import Covobs
from ..correlators import Corr
from .. import version as pyerrorsversion
@ -173,6 +174,18 @@ def create_json_string(ol, description='', indent=1):
d['cdata'] = cdata
return d
def write_Corr_to_dict(my_corr):
front_padding = next(i for i, j in enumerate(my_corr.content) if np.all(j))
back_padding_start = front_padding + next((i for i, j in enumerate(my_corr.content[front_padding:]) if not np.all(j)), my_corr.T)
dat = write_Array_to_dict(np.array(my_corr.content[front_padding:back_padding_start]))
dat['type'] = 'Corr'
corr_meta_data = str(front_padding) + '|' + str(my_corr.T - back_padding_start) + '|' + str(my_corr.tag)
if 'tag' in dat.keys():
dat['tag'].append(corr_meta_data)
else:
dat['tag'] = [corr_meta_data]
return dat
if not isinstance(ol, list):
ol = [ol]
@ -193,6 +206,10 @@ def create_json_string(ol, description='', indent=1):
d['obsdata'].append(write_List_to_dict(io))
elif isinstance(io, np.ndarray):
d['obsdata'].append(write_Array_to_dict(io))
elif isinstance(io, Corr):
d['obsdata'].append(write_Corr_to_dict(io))
else:
raise Exception("Unkown datatype.")
jsonstring = json.dumps(d, indent=indent, cls=my_encoder, ensure_ascii=False)
@ -374,6 +391,22 @@ def import_json_string(json_string, verbose=True, full_output=False):
ret[-1].tag = taglist[i]
return np.reshape(ret, layout)
def get_Corr_from_dict(o):
taglist = o.get('tag')
corr_meta_data = taglist[-1].split('|')
padding_front = int(corr_meta_data[0])
padding_back = int(corr_meta_data[1])
corr_tag = corr_meta_data[2]
tmp_o = o
tmp_o['tag'] = taglist[:-1]
if len(tmp_o['tag']) == 0:
del tmp_o['tag']
dat = get_Array_from_dict(tmp_o)
my_corr = Corr(list(dat), padding_front=padding_front, padding_back=padding_back)
if corr_tag != 'None':
my_corr.tag = corr_tag
return my_corr
json_dict = json.loads(json_string)
prog = json_dict.get('program', '')
@ -400,6 +433,10 @@ def import_json_string(json_string, verbose=True, full_output=False):
ol.append(get_List_from_dict(io))
elif io['type'] == 'Array':
ol.append(get_Array_from_dict(io))
elif io['type'] == 'Corr':
ol.append(get_Corr_from_dict(io))
else:
raise Exception("Unkown datatype.")
if full_output:
retd = {}

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@ -89,3 +89,36 @@ def test_json_string_reconstruction():
assert reconstructed_string == json_string
assert my_obs == reconstructed_obs2
def test_json_corr_io():
my_list = [pe.Obs([np.random.normal(1.0, 0.1, 100)], ['ens1']) for o in range(8)]
rw_list = pe.reweight(pe.Obs([np.random.normal(1.0, 0.1, 100)], ['ens1']), my_list)
for obs_list in [my_list, rw_list]:
for tag in [None, "test"]:
obs_list[3].tag = tag
for fp in [0, 2]:
for bp in [0, 7]:
for corr_tag in [None, 'my_Corr_tag']:
my_corr = pe.Corr(obs_list, padding_front=fp, padding_back=bp)
my_corr.tag = corr_tag
pe.input.json.dump_to_json(my_corr, 'corr')
recover = pe.input.json.load_json('corr')
assert np.all([o.is_zero() for o in [x for x in (my_corr - recover) if x is not None]])
assert my_corr.tag == recover.tag
assert my_corr.reweighted == recover.reweighted
def test_json_corr_2d_io():
obs_list = [np.array([[pe.pseudo_Obs(1.0 + i, 0.1 * i, 'test'), pe.pseudo_Obs(0.0, 0.1 * i, 'test')], [pe.pseudo_Obs(0.0, 0.1 * i, 'test'), pe.pseudo_Obs(1.0 + i, 0.1 * i, 'test')]]) for i in range(8)]
for tag in [None, "test"]:
obs_list[3][0, 1].tag = tag
for padding in [0, 1]:
my_corr = pe.Corr(obs_list, padding_front=padding, padding_back=padding)
my_corr.tag = tag
pe.input.json.dump_to_json(my_corr, 'corr')
recover = pe.input.json.load_json('corr')
assert np.all([np.all([o.is_zero() for o in q]) for q in [x.ravel() for x in (my_corr - recover) if x is not None]])
assert my_corr.tag == recover.tag

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@ -615,7 +615,7 @@ def test_covariance_symmetry():
cov_ab = pe.covariance(test_obs1, a)
cov_ba = pe.covariance(a, test_obs1)
assert np.abs(cov_ab - cov_ba) <= 10 * np.finfo(np.float64).eps
assert np.abs(cov_ab) < test_obs1.dvalue * test_obs2.dvalue * (1 + 10 * np.finfo(np.float64).eps)
assert np.abs(cov_ab) < test_obs1.dvalue * a.dvalue * (1 + 10 * np.finfo(np.float64).eps)
def test_empty_obs():