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Merge branch 'develop' into documentation

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fjosw 2022-01-19 11:04:37 +00:00
commit 2d72c1ef6a
5 changed files with 38 additions and 18 deletions
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6
pyerrors/correlators.py
View file

@ -4,7 +4,7 @@ import autograd.numpy as anp
import matplotlib.pyplot as plt
import scipy.linalg
from .obs import Obs, reweight, correlate, CObs
from .misc import dump_object
from .misc import dump_object, _assert_equal_properties
from .fits import least_squares
from .linalg import eigh, inv, cholesky
from .roots import find_root
@ -42,10 +42,8 @@ class Corr:
if not isinstance(data_input, list):
raise TypeError('Corr__init__ expects a list of timeslices.')
# data_input can have multiple shapes. The simplest one is a list of Obs.
# We check, if this is the case
if all([(isinstance(item, Obs) or isinstance(item, CObs)) for item in data_input]):
_assert_equal_properties(data_input)
self.content = [np.asarray([item]) for item in data_input]
self.N = 1

15
pyerrors/input/json.py
View file

@ -9,6 +9,7 @@ import warnings
from ..obs import Obs
from ..covobs import Covobs
from ..correlators import Corr
from ..misc import _assert_equal_properties
from .. import version as pyerrorsversion
@ -104,20 +105,6 @@ def create_json_string(ol, description='', indent=1):
dl.append(ed)
return dl
def _assert_equal_properties(ol, otype=Obs):
for o in ol:
if not isinstance(o, otype):
raise Exception("Wrong data type in list.")
for o in ol[1:]:
if not ol[0].is_merged == o.is_merged:
raise Exception("All Obs in list have to be defined on the same set of configs.")
if not ol[0].reweighted == o.reweighted:
raise Exception("All Obs in list have to have the same property 'reweighted'.")
if not ol[0].e_content == o.e_content:
raise Exception("All Obs in list have to be defined on the same set of configs.")
if not ol[0].idl == o.idl:
raise Exception("All Obs in list have to be defined on the same set of configurations.")
def write_Obs_to_dict(o):
d = {}
d['type'] = 'Obs'

15
pyerrors/misc.py
View file

@ -70,3 +70,18 @@ def gen_correlated_data(means, cov, name, tau=0.5, samples=1000):
data.append(np.sqrt(1 - a ** 2) * rand[i] + a * data[-1])
corr_data = np.array(data) - np.mean(data, axis=0) + means
return [Obs([dat], [name]) for dat in corr_data.T]
def _assert_equal_properties(ol, otype=Obs):
for o in ol:
if not isinstance(o, otype):
raise Exception("Wrong data type in list.")
for o in ol[1:]:
if not ol[0].is_merged == o.is_merged:
raise Exception("All Obs in list have to be defined on the same set of configs.")
if not ol[0].reweighted == o.reweighted:
raise Exception("All Obs in list have to have the same property 'reweighted'.")
if not ol[0].e_content == o.e_content:
raise Exception("All Obs in list have to be defined on the same set of configs.")
if not ol[0].idl == o.idl:
raise Exception("All Obs in list have to be defined on the same set of configurations.")

18
tests/correlators_test.py
View file

@ -120,6 +120,24 @@ def test_padded_correlator():
[o for o in my_corr]
def test_corr_exceptions():
obs_a = pe.Obs([np.random.normal(0.1, 0.1, 100)], ['test'])
obs_b= pe.Obs([np.random.normal(0.1, 0.1, 99)], ['test'])
with pytest.raises(Exception):
pe.Corr([obs_a, obs_b])
obs_a = pe.Obs([np.random.normal(0.1, 0.1, 100)], ['test'])
obs_b= pe.Obs([np.random.normal(0.1, 0.1, 100)], ['test'], idl=[range(1, 200, 2)])
with pytest.raises(Exception):
pe.Corr([obs_a, obs_b])
obs_a = pe.Obs([np.random.normal(0.1, 0.1, 100)], ['test'])
obs_b= pe.Obs([np.random.normal(0.1, 0.1, 100)], ['test2'])
with pytest.raises(Exception):
pe.Corr([obs_a, obs_b])
def test_utility():
corr_content = []
for t in range(8):

2
tests/io_test.py
View file

@ -105,6 +105,7 @@ def test_json_corr_io():
my_corr.tag = corr_tag
pe.input.json.dump_to_json(my_corr, 'corr')
recover = pe.input.json.load_json('corr')
os.remove('corr.json.gz')
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
@ -120,5 +121,6 @@ def test_json_corr_2d_io():
my_corr.tag = tag
pe.input.json.dump_to_json(my_corr, 'corr')
recover = pe.input.json.load_json('corr')
os.remove('corr.json.gz')
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