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Merge pull request #81 from s-kuberski/bugfix/idl

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_merge_idx now returns sorted lists
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Fabian Joswig 2022-02-23 17:00:59 +00:00 • committed by GitHub
commit b960ce0e3d
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2 changed files with 19 additions and 5 deletions
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10
pyerrors/obs.py
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@ -934,7 +934,7 @@ def _expand_deltas(deltas, idx, shape):
deltas : list deltas : list
List of fluctuations List of fluctuations
idx : list idx : list
List or range of configs on which the deltas are defined. List or range of configs on which the deltas are defined, has to be sorted in ascending order.
shape : int shape : int
Number of configs in idx. Number of configs in idx.
""" """
@ -948,7 +948,7 @@ def _expand_deltas(deltas, idx, shape):
def _merge_idx(idl): def _merge_idx(idl):
"""Returns the union of all lists in idl """Returns the union of all lists in idl as sorted list
Parameters Parameters
---------- ----------
@ -971,7 +971,7 @@ def _merge_idx(idl):
idstep = min([idx.step for idx in idl]) idstep = min([idx.step for idx in idl])
return range(idstart, idstop, idstep) return range(idstart, idstop, idstep)
return list(set().union(*idl)) return sorted(set().union(*idl))
def _expand_deltas_for_merge(deltas, idx, shape, new_idx): def _expand_deltas_for_merge(deltas, idx, shape, new_idx):
@ -985,11 +985,11 @@ def _expand_deltas_for_merge(deltas, idx, shape, new_idx):
List of fluctuations List of fluctuations
idx : list idx : list
List or range of configs on which the deltas are defined. List or range of configs on which the deltas are defined.
Has to be a subset of new_idx. Has to be a subset of new_idx and has to be sorted in ascending order.
shape : list shape : list
Number of configs in idx. Number of configs in idx.
new_idx : list new_idx : list
List of configs that defines the new range. List of configs that defines the new range, has to be sorted in ascending order.
""" """
if type(idx) is range and type(new_idx) is range: if type(idx) is range and type(new_idx) is range:

14
tests/obs_test.py
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@ -613,6 +613,12 @@ def test_gamma_method_irregular():
assert((ae.e_tauint['a'] - 4 * ae.e_dtauint['a'] < ao.e_tauint['a'])) assert((ae.e_tauint['a'] - 4 * ae.e_dtauint['a'] < ao.e_tauint['a']))
assert((ae.e_tauint['a'] + 4 * ae.e_dtauint['a'] > ao.e_tauint['a'])) assert((ae.e_tauint['a'] + 4 * ae.e_dtauint['a'] > ao.e_tauint['a']))
a = pe.pseudo_Obs(1, .1, 'a', samples=10)
a.idl['a'] = range(4, 15)
b = pe.pseudo_Obs(1, .1, 'a', samples=151)
b.idl['a'] = range(4, 608, 4)
ol = [a, b]
o = (ol[0] - ol[1]) / (ol[1])
def test_covariance_symmetry(): def test_covariance_symmetry():
value1 = np.random.normal(5, 10) value1 = np.random.normal(5, 10)
@ -691,3 +697,11 @@ def test_reduce_deltas():
new = pe.obs._reduce_deltas(deltas, idx_old, idx_new) new = pe.obs._reduce_deltas(deltas, idx_old, idx_new)
print(new) print(new)
assert(np.alltrue([float(i) for i in idx_new] == new)) assert(np.alltrue([float(i) for i in idx_new] == new))
def test_merge_idx():
idl = [list(np.arange(1, 14)) + list(range(16, 100, 4)), range(4, 604, 4), [2, 4, 5, 6, 8, 9, 12, 24], range(1, 20, 1), range(50, 789, 7)]
new_idx = pe.obs._merge_idx(idl)
assert(new_idx[-1] > new_idx[0])
for i in range(1, len(new_idx)):
assert(new_idx[i - 1] < new_idx[i])