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Merge branch 'develop' into feat/typehints

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Fabian Joswig 2025-05-05 19:11:51 +02:00
commit 6d80efd388
15 changed files with 156 additions and 93 deletions
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32
tests/obs_test.py
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@ -333,7 +333,7 @@ def test_derived_observables():
def test_multi_ens():
names = ['A0', 'A1|r001', 'A1|r002']
test_obs = pe.Obs([np.random.rand(50), np.random.rand(50), np.random.rand(50)], names)
test_obs = pe.Obs([np.random.rand(50)], names[:1]) + pe.Obs([np.random.rand(50), np.random.rand(50)], names[1:])
assert test_obs.e_names == ['A0', 'A1']
assert test_obs.e_content['A0'] == ['A0']
assert test_obs.e_content['A1'] == ['A1|r001', 'A1|r002']
@ -345,6 +345,9 @@ def test_multi_ens():
ensembles.append(str(i))
assert my_sum.e_names == sorted(ensembles)
with pytest.raises(ValueError):
test_obs = pe.Obs([np.random.rand(50), np.random.rand(50), np.random.rand(50)], names)
def test_multi_ens2():
names = ['ens', 'e', 'en', 'e|r010', 'E|er', 'ens|', 'Ens|34', 'ens|r548984654ez4e3t34terh']
@ -499,18 +502,25 @@ def test_reweighting():
with pytest.raises(ValueError):
pe.reweight(my_irregular_obs, [my_obs])
my_merged_obs = my_obs + pe.Obs([np.random.rand(1000)], ['q'])
with pytest.raises(ValueError):
pe.reweight(my_merged_obs, [my_merged_obs])
def test_merge_obs():
my_obs1 = pe.Obs([np.random.rand(100)], ['t'])
my_obs2 = pe.Obs([np.random.rand(100)], ['q'], idl=[range(1, 200, 2)])
my_obs1 = pe.Obs([np.random.normal(1, .1, 100)], ['t|1'])
my_obs2 = pe.Obs([np.random.normal(1, .1, 100)], ['t|2'], idl=[range(1, 200, 2)])
merged = pe.merge_obs([my_obs1, my_obs2])
diff = merged - my_obs2 - my_obs1
assert diff == -(my_obs1.value + my_obs2.value) / 2
diff = merged - (my_obs2 + my_obs1) / 2
assert np.isclose(0, diff.value, atol=1e-16)
with pytest.raises(ValueError):
pe.merge_obs([my_obs1, my_obs1])
my_covobs = pe.cov_Obs(1.0, 0.003, 'cov')
with pytest.raises(ValueError):
pe.merge_obs([my_obs1, my_covobs])
my_obs3 = pe.Obs([np.random.rand(100)], ['q|2'], idl=[range(1, 200, 2)])
with pytest.raises(ValueError):
pe.merge_obs([my_obs1, my_obs3])
@ -543,6 +553,9 @@ def test_correlate():
my_obs6 = pe.Obs([np.random.rand(100)], ['t'], idl=[range(5, 505, 5)])
corr3 = pe.correlate(my_obs5, my_obs6)
assert my_obs5.idl == corr3.idl
my_obs7 = pe.Obs([np.random.rand(99)], ['q'])
with pytest.raises(ValueError):
pe.correlate(my_obs1, my_obs7)
my_new_obs = pe.Obs([np.random.rand(100)], ['q3'])
with pytest.raises(ValueError):
@ -682,14 +695,14 @@ def test_gamma_method_irregular():
assert (a.dvalue - 5 * a.ddvalue < expe and expe < a.dvalue + 5 * a.ddvalue)
arr2 = np.random.normal(1, .2, size=N)
afull = pe.Obs([arr, arr2], ['a1', 'a2'])
afull = pe.Obs([arr], ['a1']) + pe.Obs([arr2], ['a2'])
configs = np.ones_like(arr2)
for i in np.random.uniform(0, len(arr2), size=int(.8*N)):
configs[int(i)] = 0
zero_arr2 = [arr2[i] for i in range(len(arr2)) if not configs[i] == 0]
idx2 = [i + 1 for i in range(len(configs)) if configs[i] == 1]
a = pe.Obs([zero_arr, zero_arr2], ['a1', 'a2'], idl=[idx, idx2])
a = pe.Obs([zero_arr], ['a1'], idl=[idx]) + pe.Obs([zero_arr2], ['a2'], idl=[idx2])
afull.gamma_method()
a.gamma_method()
@ -1023,7 +1036,7 @@ def test_correlation_intersection_of_idls():
def test_covariance_non_identical_objects():
obs1 = pe.Obs([np.random.normal(1.0, 0.1, 1000), np.random.normal(1.0, 0.1, 1000), np.random.normal(1.0, 0.1, 732)], ["ens|r1", "ens|r2", "ens2"])
obs1 = pe.Obs([np.random.normal(1.0, 0.1, 1000), np.random.normal(1.0, 0.1, 1000)], ["ens|r1", "ens|r2"]) + pe.Obs([np.random.normal(1.0, 0.1, 732)], ['ens2'])
obs1.gamma_method()
obs2 = obs1 + 1e-18
obs2.gamma_method()
@ -1107,6 +1120,9 @@ def test_reweight_method():
obs1 = pe.pseudo_Obs(0.2, 0.01, 'test')
rw = pe.pseudo_Obs(0.999, 0.001, 'test')
assert obs1.reweight(rw) == pe.reweight(rw, [obs1])[0]
rw2 = pe.pseudo_Obs(0.999, 0.001, 'test2')
with pytest.raises(ValueError):
obs1.reweight(rw2)
def test_jackknife():