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tests: test covariance vs numpy added.

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This commit is contained in:
Fabian Joswig 2022-05-19 14:09:05 +01:00
parent 9011adb0de
commit bb0236a556
1 changed files with 20 additions and 0 deletions
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20
tests/obs_test.py
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@ -648,6 +648,26 @@ def test_covariance_is_variance():
assert np.isclose(test_obs.dvalue ** 2, pe.covariance([test_obs, test_obs])[0, 1])
def test_covariance_vs_numpy():
N = 1078
data1 = np.random.normal(2.5, 0.2, N)
data2 = np.random.normal(0.5, 0.08, N)
data3 = np.random.normal(-178, 5, N)
uncorr = np.row_stack([data1, data2, data3])
corr = np.random.multivariate_normal([0.0, 17, -0.0487], [[1.0, 0.6, -0.22], [0.6, 0.8, 0.01], [-0.22, 0.01, 1.9]], N).T
for X in [uncorr, corr]:
obs1 = pe.Obs([X[0]], ["ens1"])
obs2 = pe.Obs([X[1]], ["ens1"])
obs3 = pe.Obs([X[2]], ["ens1"])
obs1.gamma_method(S=0.0)
obs2.gamma_method(S=0.0)
obs3.gamma_method(S=0.0)
pe_cov = pe.covariance([obs1, obs2, obs3])
np_cov = np.cov(X) / N
assert np.allclose(pe_cov, np_cov, atol=1e-14)
def test_covariance_symmetry():
value1 = np.random.normal(5, 10)
dvalue1 = np.abs(np.random.normal(0, 1))