feat: _intersection_idx and _collapse_deltas_for_merge together with

tests added.
This commit is contained in:
Fabian Joswig 2022-04-08 11:14:58 +01:00
parent 5e7753a66d
commit 934d091249
2 changed files with 75 additions and 0 deletions

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@ -972,6 +972,33 @@ def _merge_idx(idl):
return sorted(set().union(*idl))
def _intersection_idx(idl):
"""Returns the intersection of all lists in idl as sorted list
Parameters
----------
idl : list
List of lists or ranges.
"""
# Use groupby to efficiently check whether all elements of idl are identical
try:
g = groupby(idl)
if next(g, True) and not next(g, False):
return idl[0]
except Exception:
pass
if np.all([type(idx) is range for idx in idl]):
if len(set([idx[0] for idx in idl])) == 1:
idstart = max([idx.start for idx in idl])
idstop = min([idx.stop for idx in idl])
idstep = max([idx.step for idx in idl])
return range(idstart, idstop, idstep)
return sorted(set().intersection(*idl))
def _expand_deltas_for_merge(deltas, idx, shape, new_idx):
"""Expand deltas defined on idx to the list of configs that is defined by new_idx.
New, empty entries are filled by 0. If idx and new_idx are of type range, the smallest
@ -999,6 +1026,34 @@ def _expand_deltas_for_merge(deltas, idx, shape, new_idx):
return np.array([ret[new_idx[i] - new_idx[0]] for i in range(len(new_idx))])
def _collapse_deltas_for_merge(deltas, idx, shape, new_idx):
"""Collapse deltas defined on idx to the list of configs that is defined by new_idx.
If idx and new_idx are of type range, the smallest
common divisor of the step sizes is used as new step size.
Parameters
----------
deltas : list
List of fluctuations
idx : list
List or range of configs on which the deltas are defined.
Has to be a subset of new_idx and has to be sorted in ascending order.
shape : list
Number of configs in idx.
new_idx : list
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 idx == new_idx:
return deltas
ret = np.zeros(new_idx[-1] - new_idx[0] + 1)
for i in range(shape):
if idx[i] in new_idx:
ret[idx[i] - new_idx[0]] = deltas[i]
return np.array([ret[new_idx[i] - new_idx[0]] for i in range(len(new_idx))])
def _filter_zeroes(deltas, idx, eps=Obs.filter_eps):
"""Filter out all configurations with vanishing fluctuation such that they do not
contribute to the error estimate anymore. Returns the new deltas and

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@ -515,6 +515,26 @@ def test_merge_idx():
assert pe.obs._merge_idx([range(500, 6050, 50), range(500, 6250, 250)]) == range(500, 6250, 50)
def test_intersection_idx():
assert pe.obs._intersection_idx([range(1, 100), range(1, 100), range(1, 100)]) == range(1, 100)
assert pe.obs._intersection_idx([range(1, 100, 10), range(1, 100, 2)]) == range(1, 100, 10)
assert pe.obs._intersection_idx([range(10, 1010, 10), range(10, 1010, 50)]) == range(10, 1010, 50)
assert pe.obs._intersection_idx([range(500, 6050, 50), range(500, 6250, 250)]) == range(500, 6050, 250)
def test_intersection_collapse():
range1 = range(1, 2000, 2)
range2 = range(2, 2001, 8)
obs1 = pe.Obs([np.random.normal(1.0, 0.1, len(range1))], ["ens"], idl=[range1])
obs_merge = obs1 + pe.Obs([np.random.normal(1.0, 0.1, len(range2))], ["ens"], idl=[range2])
intersection = pe.obs._intersection_idx([o.idl["ens"] for o in [obs1, obs_merge]])
coll = pe.obs._collapse_deltas_for_merge(obs_merge.deltas["ens"], obs_merge.idl["ens"], len(obs_merge.idl["ens"]), range1)
assert np.all(coll == obs1.deltas["ens"])
def test_irregular_error_propagation():
obs_list = [pe.Obs([np.random.rand(100)], ['t']),
pe.Obs([np.random.rand(50)], ['t'], idl=[range(1, 100, 2)]),