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Merge branch 'develop' into documentation

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fjosw 2021-11-15 14:18:54 +00:00
commit 3c4b7fa9bf
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pyerrors/obs.py
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@ -562,7 +562,7 @@ class Obs:
Returns Returns
------- -------
np.ndarray numpy.ndarray
Returns a numpy array of length N + 1 where N is the number of samples Returns a numpy array of length N + 1 where N is the number of samples
for the given ensemble and replicum. The zeroth entry of the array contains for the given ensemble and replicum. The zeroth entry of the array contains
the mean value of the Obs, entries 1 to N contain the N jackknife samples the mean value of the Obs, entries 1 to N contain the N jackknife samples

15
tests/obs_test.py
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@ -504,3 +504,18 @@ def test_covariance2_symmetry():
cov_ba = pe.covariance2(a, test_obs1) cov_ba = pe.covariance2(a, test_obs1)
assert np.abs(cov_ab - cov_ba) <= 10 * np.finfo(np.float64).eps 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 * test_obs2.dvalue * (1 + 10 * np.finfo(np.float64).eps)
def test_jackknife():
full_data = np.random.normal(1.1, 0.87, 5487)
my_obs = pe.Obs([full_data], ['test'])
n = full_data.size
mean = np.mean(full_data)
tmp_jacks = np.zeros(n + 1)
tmp_jacks[0] = mean
for i in range(n):
tmp_jacks[i + 1] = (n * mean - full_data[i]) / (n - 1)
assert np.allclose(tmp_jacks, my_obs.export_jackknife())