test_jackknife added

This commit is contained in:
Fabian Joswig 2021-11-15 14:18:26 +00:00
parent 69d786c155
commit 331d7cb471
2 changed files with 16 additions and 1 deletions

View file

@ -562,7 +562,7 @@ class Obs:
Returns
-------
np.ndarray
numpy.ndarray
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
the mean value of the Obs, entries 1 to N contain the N jackknife samples

View file

@ -504,3 +504,18 @@ def test_covariance2_symmetry():
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) < 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())