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reverted idl storage to list, added simple test for irregular error

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propagation
This commit is contained in:
Fabian Joswig 2021-10-29 15:12:34 +01:00
parent 6cf478fb57
commit 8ceee688ec
2 changed files with 14 additions and 9 deletions
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2
pyerrors/pyerrors.py
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@ -78,7 +78,7 @@ class Obs:
if len(dc) == 1:
self.idl[name] = range(idx[0], idx[-1] + dc[0], dc[0])
else:
self.idl[name] = np.array(idx)
self.idl[name] = list(idx)
else:
raise Exception('incompatible type for idl[%s].' % (name))
else:

21
tests/pyerrors_test.py
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@ -276,6 +276,12 @@ def test_cobs():
assert (other / my_cobs * my_cobs - other).is_zero()
def test_irregular_error_propagation():
regular_obs = pe.Obs([np.random.rand(1000)], ['t'])
irregular_obs = pe.Obs([np.random.rand(500)], ['t'], idl=[range(1, 1000, 2)])
assert regular_obs == (regular_obs / irregular_obs) * irregular_obs
def test_gamma_method_irregular():
N = 20000
arr = np.random.normal(1, .2, size=N)
@ -307,7 +313,7 @@ def test_gamma_method_irregular():
expe = (afull.dvalue * np.sqrt(N / np.sum(configs)))
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'])
@ -323,21 +329,21 @@ def test_gamma_method_irregular():
expe = (afull.dvalue * np.sqrt(N / np.sum(configs)))
assert (a.dvalue - 5 * a.ddvalue < expe and expe < a.dvalue + 5 * a.ddvalue)
def gen_autocorrelated_array(inarr, rho):
outarr = np.copy(inarr)
for i in range(1, len(outarr)):
outarr[i] = rho * outarr[i - 1] + np.sqrt(1 - rho**2) * outarr[i]
return outarr
arr = np.random.normal(1, .2, size=N)
carr = gen_autocorrelated_array(arr, .346)
a = pe.Obs([carr], ['a'])
a.gamma_method(e_tag=1)
ae = pe.Obs([[carr[i] for i in range(len(carr)) if i % 2 == 0]], ['a'], idl=[[i for i in range(len(carr)) if i % 2 == 0]])
ae.gamma_method(e_tag=1)
ao = pe.Obs([[carr[i] for i in range(len(carr)) if i % 2 == 1]], ['a'], idl=[[i for i in range(len(carr)) if i % 2 == 1]])
ao.gamma_method(e_tag=1)
@ -359,7 +365,7 @@ def test_covariance2_symmetry():
cov_ba = pe.covariance2(test_obs2, 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)
N = 100
arr = np.random.normal(1, .2, size=N)
configs = np.ones_like(arr)
@ -370,9 +376,8 @@ def test_covariance2_symmetry():
a = pe.Obs([zero_arr], ['t'], idl=[idx])
a.gamma_method()
assert np.isclose(a.dvalue**2, pe.covariance2(a, a), atol=100, rtol=1e-4)
cov_ab = pe.covariance2(test_obs1, a)
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)