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Fix/merge idx (#172)
* Fix: Corrected merging of idls * Fix: Computation of drho in cases where tau_int is large compared to the chain length * Removed unnecessary imports * Refactor list comparisons in obs.py
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s-kuberski
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2 changed files with 77 additions and 46 deletions
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@ -1,8 +1,6 @@
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import warnings
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import hashlib
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import pickle
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from math import gcd
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from functools import reduce
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import numpy as np
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import autograd.numpy as anp # Thinly-wrapped numpy
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from autograd import jacobian
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@ -280,7 +278,7 @@ class Obs:
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def _compute_drho(i):
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tmp = (self.e_rho[e_name][i + 1:w_max]
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+ np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 < 0 else 2 * (i - w_max // 2):-1],
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+ np.concatenate([self.e_rho[e_name][i - 1:None if i - w_max // 2 <= 0 else 2 * (i - w_max // 2):-1],
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self.e_rho[e_name][1:max(1, w_max - 2 * i)]])
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- 2 * self.e_rho[e_name][i] * self.e_rho[e_name][1:w_max - i])
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self.e_drho[e_name][i] = np.sqrt(np.sum(tmp ** 2) / e_N)
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@ -1022,7 +1020,7 @@ def _expand_deltas(deltas, idx, shape, gapsize):
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def _merge_idx(idl):
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"""Returns the union of all lists in idl as sorted list
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"""Returns the union of all lists in idl as range or sorted list
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Parameters
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----------
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@ -1030,26 +1028,22 @@ def _merge_idx(idl):
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List of lists or ranges.
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"""
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# Use groupby to efficiently check whether all elements of idl are identical
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try:
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g = groupby(idl)
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if next(g, True) and not next(g, False):
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return idl[0]
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except Exception:
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pass
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if _check_lists_equal(idl):
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return idl[0]
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if np.all([type(idx) is range for idx in idl]):
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if len(set([idx[0] for idx in idl])) == 1:
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idstart = min([idx.start for idx in idl])
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idstop = max([idx.stop for idx in idl])
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idstep = min([idx.step for idx in idl])
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return range(idstart, idstop, idstep)
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idunion = sorted(set().union(*idl))
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return sorted(set().union(*idl))
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# Check whether idunion can be expressed as range
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idrange = range(idunion[0], idunion[-1] + 1, idunion[1] - idunion[0])
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idtest = [list(idrange), idunion]
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if _check_lists_equal(idtest):
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return idrange
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return idunion
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def _intersection_idx(idl):
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"""Returns the intersection of all lists in idl as sorted list
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"""Returns the intersection of all lists in idl as range or sorted list
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Parameters
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----------
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@ -1057,28 +1051,21 @@ def _intersection_idx(idl):
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List of lists or ranges.
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"""
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def _lcm(*args):
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"""Returns the lowest common multiple of args.
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if _check_lists_equal(idl):
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return idl[0]
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From python 3.9 onwards the math library contains an lcm function."""
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return reduce(lambda a, b: a * b // gcd(a, b), args)
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idinter = sorted(set.intersection(*[set(o) for o in idl]))
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# Use groupby to efficiently check whether all elements of idl are identical
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# Check whether idinter can be expressed as range
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try:
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g = groupby(idl)
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if next(g, True) and not next(g, False):
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return idl[0]
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except Exception:
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idrange = range(idinter[0], idinter[-1] + 1, idinter[1] - idinter[0])
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idtest = [list(idrange), idinter]
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if _check_lists_equal(idtest):
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return idrange
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except IndexError:
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pass
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if np.all([type(idx) is range for idx in idl]):
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if len(set([idx[0] for idx in idl])) == 1:
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idstart = max([idx.start for idx in idl])
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idstop = min([idx.stop for idx in idl])
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idstep = _lcm(*[idx.step for idx in idl])
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return range(idstart, idstop, idstep)
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return sorted(set.intersection(*[set(o) for o in idl]))
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return idinter
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def _expand_deltas_for_merge(deltas, idx, shape, new_idx):
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@ -1299,13 +1286,8 @@ def _reduce_deltas(deltas, idx_old, idx_new):
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if type(idx_old) is range and type(idx_new) is range:
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if idx_old == idx_new:
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return deltas
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# Use groupby to efficiently check whether all elements of idx_old and idx_new are identical
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try:
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g = groupby([idx_old, idx_new])
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if next(g, True) and not next(g, False):
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return deltas
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except Exception:
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pass
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if _check_lists_equal([idx_old, idx_new]):
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return deltas
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indices = np.intersect1d(idx_old, idx_new, assume_unique=True, return_indices=True)[1]
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if len(indices) < len(idx_new):
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raise Exception('Error in _reduce_deltas: Config of idx_new not in idx_old')
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@ -1650,3 +1632,18 @@ def _determine_gap(o, e_content, e_name):
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raise Exception(f"Replica for ensemble {e_name} do not have a common spacing.", gaps)
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return gap
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def _check_lists_equal(idl):
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'''
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Use groupby to efficiently check whether all elements of idl are identical.
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Returns True if all elements are equal, otherwise False.
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Parameters
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----------
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idl : list of lists, ranges or np.ndarrays
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'''
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g = groupby([np.nditer(el) if isinstance(el, np.ndarray) else el for el in idl])
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if next(g, True) and not next(g, False):
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return True
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return False
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@ -537,7 +537,21 @@ def test_correlate():
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def test_merge_idx():
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assert pe.obs._merge_idx([range(10, 1010, 10), range(10, 1010, 50)]) == range(10, 1010, 10)
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assert pe.obs._merge_idx([range(500, 6050, 50), range(500, 6250, 250)]) == range(500, 6250, 50)
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assert isinstance(pe.obs._merge_idx([range(10, 1010, 10), range(10, 1010, 50)]), range)
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assert pe.obs._merge_idx([range(500, 6050, 50), range(500, 6250, 250)]) == range(500, 6001, 50)
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assert isinstance(pe.obs._merge_idx([range(500, 6050, 50), range(500, 6250, 250)]), range)
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assert pe.obs._merge_idx([range(1, 1011, 2), range(1, 1010, 1)]) == range(1, 1010, 1)
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assert isinstance(pe.obs._merge_idx([range(1, 1011, 2), range(1, 1010, 1)]), range)
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assert pe.obs._merge_idx([range(1, 100, 2), range(2, 100, 2)]) == range(1, 100, 1)
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assert isinstance(pe.obs._merge_idx([range(1, 100, 2), range(2, 100, 2)]), range)
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for j in range(5):
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idll = [range(1, int(round(np.random.uniform(300, 700))), int(round(np.random.uniform(1, 14)))) for i in range(10)]
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assert pe.obs._merge_idx(idll) == sorted(set().union(*idll))
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for j in range(5):
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idll = [range(int(round(np.random.uniform(1, 28))), int(round(np.random.uniform(300, 700))), int(round(np.random.uniform(1, 14)))) for i in range(10)]
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assert pe.obs._merge_idx(idll) == sorted(set().union(*idll))
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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)]
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new_idx = pe.obs._merge_idx(idl)
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@ -550,10 +564,21 @@ def test_intersection_idx():
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assert pe.obs._intersection_idx([range(1, 100), range(1, 100), range(1, 100)]) == range(1, 100)
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assert pe.obs._intersection_idx([range(1, 100, 10), range(1, 100, 2)]) == range(1, 100, 10)
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assert pe.obs._intersection_idx([range(10, 1010, 10), range(10, 1010, 50)]) == range(10, 1010, 50)
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assert pe.obs._intersection_idx([range(500, 6050, 50), range(500, 6250, 250)]) == range(500, 6050, 250)
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assert pe.obs._intersection_idx([range(500, 6050, 50), range(500, 6250, 250)]) == range(500, 6001, 250)
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assert pe.obs._intersection_idx([range(1, 1011, 2), range(1, 1010, 1)]) == range(1, 1010, 2)
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idll = [range(1, 100, 2), range(5, 105, 1)]
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assert pe.obs._intersection_idx(idll) == range(5, 100, 2)
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assert isinstance(pe.obs._intersection_idx(idll), range)
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idll = [range(1, 100, 2), list(range(5, 105, 1))]
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assert pe.obs._intersection_idx(idll) == range(5, 100, 2)
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assert isinstance(pe.obs._intersection_idx(idll), range)
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for ids in [[list(range(1, 80, 3)), list(range(1, 100, 2))], [range(1, 80, 3), range(1, 100, 2), range(1, 100, 7)]]:
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assert list(pe.obs._intersection_idx(ids)) == pe.obs._intersection_idx([list(o) for o in ids])
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interlist = pe.obs._intersection_idx([list(o) for o in ids])
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listinter = list(pe.obs._intersection_idx(ids))
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assert len(interlist) == len(listinter)
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assert all([o in listinter for o in interlist])
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assert all([o in interlist for o in listinter])
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def test_merge_intersection():
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@ -733,6 +758,15 @@ def test_gamma_method_irregular():
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with pytest.raises(Exception):
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my_obs.gm()
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# check cases where tau is large compared to the chain length
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N = 15
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for i in range(10):
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arr = np.random.normal(1, .2, size=N)
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for rho in .1 * np.arange(20):
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carr = gen_autocorrelated_array(arr, rho)
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a = pe.Obs([carr], ['a'])
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a.gm()
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def test_irregular_gapped_dtauint():
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my_idl = list(range(0, 5010, 10))
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