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Merge pull request #94 from fjosw/feature/covariance_idl_first_fix

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Feature/covariance idl first fix
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Fabian Joswig 2022-04-19 17:29:31 +01:00 • committed by GitHub
commit d96c5cab75
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2 changed files with 18 additions and 25 deletions
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28
pyerrors/obs.py
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@ -974,7 +974,7 @@ def _merge_idx(idl):
def _expand_deltas_for_merge(deltas, idx, shape, new_idx):
"""Expand deltas defined on idx to the list of configs that is defined by new_idx.
New, empy entries are filled by 0. If idx and new_idx are of type range, the smallest
New, empty entries are filled by 0. If idx and new_idx are of type range, the smallest
common divisor of the step sizes is used as new step size.
Parameters
@ -1416,31 +1416,9 @@ def _smooth_eigenvalues(corr, E):
def _covariance_element(obs1, obs2):
"""Estimates the covariance of two Obs objects, neglecting autocorrelations."""
def expand_deltas(deltas, idx, shape, new_idx):
"""Expand deltas defined on idx to a contiguous range [new_idx[0], new_idx[-1]].
New, empy entries are filled by 0. If idx and new_idx are of type range, the smallest
common divisor of the step sizes is used as new step size.
Parameters
----------
deltas -- List of fluctuations
idx -- List or range of configs on which the deltas are defined.
Has to be a subset of new_idx.
shape -- Number of configs in idx.
new_idx -- List of configs that defines the new range.
"""
if type(idx) is range and type(new_idx) is range:
if idx == new_idx:
return deltas
ret = np.zeros(new_idx[-1] - new_idx[0] + 1)
for i in range(shape):
ret[idx[i] - new_idx[0]] = deltas[i]
return ret
def calc_gamma(deltas1, deltas2, idx1, idx2, new_idx):
deltas1 = expand_deltas(deltas1, idx1, len(idx1), new_idx)
deltas2 = expand_deltas(deltas2, idx2, len(idx2), new_idx)
deltas1 = _expand_deltas_for_merge(deltas1, idx1, len(idx1), new_idx)
deltas2 = _expand_deltas_for_merge(deltas2, idx2, len(idx2), new_idx)
return np.sum(deltas1 * deltas2)
if set(obs1.names).isdisjoint(set(obs2.names)):

15
tests/obs_test.py
View file

@ -510,6 +510,10 @@ def test_correlate():
pe.correlate(r_obs, r_obs)
def test_merge_idx():
assert pe.obs._merge_idx([range(10, 1010, 10), range(10, 1010, 50)]) == range(10, 1010, 10)
assert pe.obs._merge_idx([range(500, 6050, 50), range(500, 6250, 250)]) == range(500, 6250, 50)
def test_irregular_error_propagation():
obs_list = [pe.Obs([np.random.rand(100)], ['t']),
@ -713,6 +717,17 @@ def test_covariance_rank_deficient():
with pytest.warns(RuntimeWarning):
pe.covariance(obs)
def test_covariance_idl():
range1 = range(10, 1010, 10)
range2 = range(10, 1010, 50)
obs1 = pe.Obs([np.random.normal(1.0, 0.1, len(range1))], ["ens"], idl=[range1])
obs2 = pe.Obs([np.random.normal(1.0, 0.1, len(range2))], ["ens"], idl=[range2])
obs1.gamma_method()
obs2.gamma_method()
pe.covariance([obs1, obs2])
def test_empty_obs():
o = pe.Obs([np.random.rand(100)], ['test'])