def antipode_ck(tree):
"""Return the antipode in the Butcher, Connes, Kreimer Hopf-algebra."""
# TODO: Should be memoized, but linearCOmbination is mutable.
# Make LinComb clonable??
result = LinearCombination()
if tree == empty_tree:
result[empty_tree] = 1
return result
elif isinstance(tree, Forest):
result[empty_tree] = 1
for tree1, multiplicity in tree.items():
for i in range(multiplicity):
tmp = LinearCombination()
for forest1, multiplicity1 in antipode_ck(tree1).items():
for forest2, multiplicity2 in result.items():
tmp[forest1 * forest2] += multiplicity1 * multiplicity2
result = tmp
return result
# TODO: implement multiplication of LinComb.
result[Forest((tree, ))] -= 1
for (forest,
subtree), multiplicity in _subtrees_for_antipode(tree).items():
for forest2, coefficient in antipode_ck(forest).items():
result[forest2.add(subtree)] -= coefficient * multiplicity
return result
def differentiate(thing):
"""performs grafting corresponding to
derivate once more with respect to *t*."""
if isinstance(thing, LinearCombination):
result = LinearCombination()
for tree, factor in thing.items():
result += treeD(tree) * factor
elif isinstance(thing, UnorderedTree):
result = treeD(thing)
elif thing == empty_tree:
result = LinearCombination()
result += leaf
return result
def test_last(self):
t1 = UnorderedTree([self.t3_2, self.t3_2])
result = symp_split(t1)
t2 = UnorderedTree([self.t3_2, self.t2_1])
expected = LinearCombination()
expected[t2] = 4
self.assertEqual(expected, result)
def test_second(self):
result = subtrees(self.t2_1)
expected = LinearCombination()
expected[(self.et, self.t2_1)] = 1
expected[(Forest((self.t1_1, )), self.t1_1)] = 1
expected[(Forest((self.t2_1, )), self.et)] = 1
self.assertEqual(expected, result)
def linCombCommutator(op1, op2, max_order=None):
"""Tree commutator for linear combinations of trees."""
if isinstance(op1, UnorderedTree) or op1 == empty_tree:
tmp = LinearCombination()
tmp += op1
op1 = tmp
if isinstance(op2, UnorderedTree) or op2 == empty_tree:
tmp = LinearCombination()
tmp += op2
op2 = tmp
result = LinearCombination()
for tree1, factor1 in op1.items():
for tree2, factor2 in op2.items():
if (not max_order) or tree1.order() + tree2.order() <= max_order:
result += (factor1 * factor2) * tree_commutator(tree1, tree2)
return result
def test_fourth(self):
result = antipode_ck(self.t3_2)
expected = LinearCombination()
expected[Forest((self.t3_2, ))] = -1
expected[Forest((self.t2_1, self.t1_1))] = 2
expected[Forest((self.t1_1, self.t1_1, self.t1_1))] = -1
self.assertEqual(expected, result)
def _subtrees_for_antipode(tree):
r"""Slightly modified edition of ``subtrees`` used by ``antipode_ck``
Does not include
:math:`\tau \otimes \emptyset` and
:math:`\emptyset \otimes \tau`.
"""
result = LinearCombination()
tmp = [subtrees(child_tree)
for child_tree in tree.elements()] # TODO: more efficient looping.
if tmp:
tmp = [elem.items() for elem in tmp] # TODO: Try using iterators.
for item in product(*tmp): # iterator over all combinations.
tensorproducts, factors = zip(*item)
multiplicity = 1
for factor in factors:
multiplicity *= factor
cuttings, to_be_grafted = zip(*tensorproducts)
with Forest().clone() as forest_of_cuttings:
for forest in cuttings:
forest_of_cuttings.inplace_multiset_sum(forest)
result[(forest_of_cuttings,
UnorderedTree(to_be_grafted))] += multiplicity
result[(empty_tree, tree)] = 0 # TODO: FIND NICER WAY.
return result
def test_eighth(self):
result = _subtrees_for_antipode(self.t4_4)
expected = LinearCombination()
expected[(Forest((self.t1_1, self.t1_1, self.t1_1)), self.t1_1)] = 1
expected[(Forest((self.t1_1, self.t1_1)), self.t2_1)] = 3
expected[(Forest((self.t1_1, )), self.t3_2)] = 3
self.assertEqual(expected, result)
def series_commutator(a, b):
"""Corresponds to tree commutator, just for series."""
# TODO: TEST ME!
def new_rule(tree):
order = tree.order()
if order in new_rule.orders:
return new_rule.storage[tree] * tree.symmetry()
# TODO: Move the correction by symmetry to initialisation.
else:
result = LinearCombination()
for tree1, tree2 in tree_tuples_of_order(order):
result += \
Fraction(a(tree1) * b(tree2),
tree1.symmetry() * tree2.symmetry()) * \
tree_commutator(tree1, tree2)
new_rule.orders.add(order)
new_rule.storage += result
return new_rule.storage[tree] * tree.symmetry()
new_rule.storage = LinearCombination()
new_rule.orders = set(
(0, )) # the coefficient of the empty tree is always 0.
return BseriesRule(new_rule)
def test_fourth(self):
result = subtrees(self.t3_2)
expected = LinearCombination()
expected[(Forest((self.t3_2, )), self.et)] = 1
expected[(Forest((self.t1_1, self.t1_1)), self.t1_1)] = 1
expected[(Forest((self.t1_1, )), self.t2_1)] = 2
expected[(self.et, self.t3_2)] = 1
self.assertEqual(expected, result)
def test_first_second(self):
tree1 = leaf
tree2 = list(D(tree1).keys())[0]
expected = LinearCombination()
forest1 = Forest([tree1, tree1])
tree3 = UnorderedTree(forest1)
expected -= tree3
result = tree_commutator(tree2, tree1)
self.assertEqual(result, expected)
def test_sixth(self):
result = _subtrees_for_antipode(self.t4_2)
expected = LinearCombination()
expected[(Forest((self.t3_2, )), self.t1_1)] = 1
expected[(Forest((self.t1_1, self.t1_1)), self.t2_1)] = 1
expected[(Forest((self.t1_1, )), self.t3_1)] = 2
print(expected)
print(result)
self.assertEqual(expected, result)
def subtrees(tree):
"""Return the HCK coproduct.
This is function does the heavy lifting when composing B-series.
The return value is a :class:`LinearCombination` of 2 tuples.
The 0th element in the tuples are the forests of cutting,
while the 1st element is the subtree.
"""
result = LinearCombination()
if tree == empty_tree:
result += (empty_tree, empty_tree)
return result
elif isinstance(tree, Forest):
if tree.number_of_trees() == 1:
for elem in tree:
return subtrees(elem)
else: # several trees.
for elem in tree:
amputated_forest = tree.sub(elem)
break
for pair1, multiplicity1 in subtrees(elem).items():
for pair2, multiplicity2 in subtrees(amputated_forest).items():
if isinstance(pair1[1], UnorderedTree):
pair1_1 = Forest((pair1[1], ))
else:
pair1_1 = pair1[1]
if isinstance(pair2[1], UnorderedTree):
pair2_1 = Forest((pair2[1], ))
else:
pair2_1 = pair2[1] # TODO: Nasty workaround.
pair = (pair1[0] * pair2[0], pair1_1 * pair2_1)
result[pair] += multiplicity1 * multiplicity2
return result
result[(Forest((tree, )), empty_tree)] = 1
if tree == leaf:
result[(empty_tree, tree)] = 1
return result
tmp = [subtrees(child_tree) for child_tree in tree.elements()]
# TODO: more efficient looping.
# TODO: The multiplicities in "tree" are accounted for by "elements()".
tmp = [elem.items() for elem in tmp] # TODO: Try using iterators.
for item in product(*tmp): # iterator over all combinations.
tensorproducts, factors = zip(*item)
multiplicity = 1
for factor in factors:
multiplicity *= factor
cuttings, to_be_grafted = zip(*tensorproducts)
with Forest().clone() as forest_of_cuttings:
for forest in cuttings:
forest_of_cuttings.inplace_multiset_sum(forest)
result[(forest_of_cuttings, UnorderedTree(to_be_grafted))] += \
multiplicity
return result
def _split(tree):
"""Return the splitting of tree except for :math:`tree \otimes \emptyset`.
Used by `split()`.
"""
result = LinearCombination()
for childtree, multiplicity in tree.items():
amputated_tree = tree.sub(childtree)
result[(childtree, amputated_tree)] = multiplicity
childSplits = _split(childtree)
for pair, multiplicity2 in childSplits.items():
new_tree = amputated_tree.add(pair[1])
new_pair = (pair[0], new_tree)
result[new_pair] = multiplicity * multiplicity2
return result
def new_rule(tree):
order = tree.order()
if order in new_rule.orders:
return new_rule.storage[tree] * tree.symmetry()
# TODO: Move the correction by symmetry to initialisation.
else:
result = LinearCombination()
for tree1, tree2 in tree_tuples_of_order(order):
result += \
Fraction(a(tree1) * b(tree2),
tree1.symmetry() * tree2.symmetry()) * \
tree_commutator(tree1, tree2)
new_rule.orders.add(order)
new_rule.storage += result
return new_rule.storage[tree] * tree.symmetry()
def graft(other, base):
r"""Grafting *other* :math:`\curvearrowright` *base*."""
result = LinearCombination()
if base == empty_tree:
result += other
elif other == empty_tree:
result += base
else:
result += base.butcher_product(other)
for subtree, multiplicity1 in base.items():
amputated_tree = base.sub(subtree)
replacements = graft(other, subtree)
for replacement, multiplicity2 in replacements.items():
new_tree = amputated_tree.add(replacement)
result[new_tree] += multiplicity1 * multiplicity2
return result
def symp_split(tree):
"""Perform the split needed for symplecticity checks.
It differs from the ``split``-function
by only splitting off leaves."""
result = LinearCombination()
for childtree, multiplicity in tree.items():
amputated_tree = tree.sub(childtree)
if childtree == leaf:
result[amputated_tree] += multiplicity
else:
child_splits = symp_split(childtree)
for tree2, multiplicity2 in child_splits.items():
new_tree = amputated_tree.add(tree2)
result[new_tree] += multiplicity * multiplicity2
return result
def test_thirteenth(self):
result = symp_split(self.t5_5)
expected = LinearCombination()
expected[self.t4_1] = 1
expected[self.t4_3] = 1
self.assertEqual(expected, result)
def test_first(self):
result = antipode_ck(self.t1_1)
expected = LinearCombination()
expected[Forest((leaf, ))] = -1
self.assertEqual(expected, result)
def test_first(self):
result = symp_split(self.t1_1)
expected = LinearCombination() # TODO: right way to do it?
self.assertEqual(expected, result)
def test_second(self):
result = antipode_ck(self.t2_1)
expected = LinearCombination()
expected[Forest((self.t2_1, ))] = -1
expected[Forest((self.t1_1, self.t1_1))] = 1
self.assertEqual(expected, result)
def test_fourth(self):
result = symp_split(self.t3_2)
expected = LinearCombination()
expected[self.t2_1] = 2
self.assertEqual(expected, result)
def test_second(self):
result = symp_split(self.t2_1)
expected = LinearCombination()
expected += self.t1_1
self.assertEqual(expected, result)
def test_tenth(self):
result = symp_split(self.t5_2)
expected = LinearCombination()
expected[self.t4_1] = 2
self.assertEqual(expected, result)
def test_fifth(self):
result = symp_split(self.t4_1)
expected = LinearCombination()
expected[self.t3_1] = 1
self.assertEqual(expected, result)
def test_eleventh(self):
result = symp_split(self.t5_3)
expected = LinearCombination()
expected[self.t4_1] = 1
expected[self.t4_2] = 1
self.assertEqual(expected, result)
def test_empty(self):
result = subtrees(self.et)
expected = LinearCombination()
expected[(self.et, self.et)] = 1
self.assertEqual(expected, result)
def test_twelfth(self):
result = symp_split(self.t5_4)
expected = LinearCombination()
expected[self.t4_2] = 3
self.assertEqual(expected, result)
def test_seventeenth(self):
result = symp_split(self.t5_9)
expected = LinearCombination()
expected[self.t4_4] = 4
self.assertEqual(expected, result)
def test_sixthteenth(self):
result = symp_split(self.t5_8)
expected = LinearCombination()
expected[self.t4_4] = 1
expected[self.t4_3] = 2
self.assertEqual(expected, result)
