def test_pi1_pi1adjoint():
lc_1 = parse_concatenation('12-21')
assert pi1(lc_1, 2) == lc_1
lc_1 = parse_concatenation('12')
assert pi1(lc_1, 2) == pi1(pi1(lc_1, 2), 2)
lc_1 = parse_concatenation('123')
lc.assert_almost_equal(pi1(lc_1, 3), pi1(pi1(lc_1, 3), 3))
dim = 2
n = 3
for w in itertools.product(range(1, dim + 1), repeat=n):
left = lc.lift(ShuffleWord(w))
for v in itertools.product(range(1, dim + 1), repeat=n):
right = lc.lift(ConcatenationWord(v))
assert inner_product_sw_cw(left,
pi1(right, n)) == inner_product_sw_cw(
pi1adjoint(left, n), right)
# pi1adjoint does _not_ depend on the realization of an element in the dual of Lie inside of T(\R^d).
assert pi1adjoint(parse_shuffle('12'),
2) == pi1adjoint(parse_shuffle('[0.5] 12 - [0.5] 21'), 2)
# For everything orthogonal on Lie, the result should be zero.
zero = lc.LinearCombination()
assert pi1adjoint(parse_shuffle('11'), 2) == zero
assert pi1adjoint(parse_shuffle('22'), 2) == zero
lc.assert_almost_equal(
pi1adjoint(parse_shuffle('12') * parse_shuffle('21'), 4), zero)
def exp(x, upto_level):
xell = lc.lift(CompositionConcatenation())
ret = xell
for ell in range(upto_level + 1):
xell = project_smaller_equal(xell * x, upto_level)
ret += 1 / sympy.factorial(ell) * xell
return ret
def _lie_bracket_of_expression2(expression):
"""Lie bracket of an expression like [[1],[[1],[2]]]."""
if len(expression) == 1:
return lc.lift(ConcatenationWord((expression[0], )))
else:
return lie_bracket(_lie_bracket_of_expression2(expression[0]),
_lie_bracket_of_expression2(expression[1]))
def lbpt(x):
def wrap(ell):
def q(z):
if isinstance(z, int):
return (z, )
else:
return wrap(z)
return tuple(q(x) for x in ell)
return lc.lift(LabeledBinaryPlanarTree(wrap(x)))
def finer_monomial(dp_mon):
yield dp_mon
lc_dp_mon = lc.lift( dp_mon )\
.coproduct()\
.apply_linear_function( lc.Tensor.fn_otimes_linear( id_, id_ ) )
for x in lc_dp_mon.apply_linear_function(lc.Tensor.m):
yield x
for i in range(1, dp_mon.deg()):
lc_dp_mon = lc_dp_mon\
.apply_linear_function( lc.Tensor.fn_otimes_linear( *( [CompositionConcatenation.coproduct] + [id_]*i ) ) )\
.apply_linear_function( lc.Tensor.fn_otimes_linear( * [id_] * (i+2) ) )
for x in lc_dp_mon.apply_linear_function(lc.Tensor.m):
yield x
def test_shuffle_word():
t = lambda x, y: lc.Tensor((x, y))
def sw(*args):
return ShuffleWord(args)
lc_1 = lc.lift(sw(1, 2))
lc_2 = lc.lift(sw(3, ))
assert lc.LinearCombination( {sw( 1,2,3 ):1, sw( 1,3,2 ):1, sw( 3,1,2 ):1} ) \
== lc_1 * lc_2
assert lc.LinearCombination( {t( sw(), sw(1,2) ):1, t(sw(1),sw(2)):1, t( sw(1,2), sw() ):1} ) \
== lc_1.apply_linear_function( ShuffleWord.coproduct )
# Condition on product vs coproduct: \Delta( \tau \tau' ) = \Delta(\tau) \Delta(\tau').
lc_1 = lc.lift(sw(1, 2))
lc_2 = lc.lift(sw())
assert (lc_1 * lc_2).apply_linear_function( ShuffleWord.coproduct ) \
== lc_1.apply_linear_function( ShuffleWord.coproduct ) \
* lc_2.apply_linear_function( ShuffleWord.coproduct )
lc_1 = lc.lift(sw(1, 2))
lc_2 = lc.lift(sw(3, ))
assert (lc_1 * lc_2).apply_linear_function( ShuffleWord.coproduct ) \
== lc_1.apply_linear_function( ShuffleWord.coproduct ) \
* lc_2.apply_linear_function( ShuffleWord.coproduct )
# Condition on antipode: \Nabla (A \otimes id) \Delta = \eta \vareps.
assert lc.LinearCombination() \
== lc_1.apply_linear_function(ShuffleWord.coproduct)\
.apply_linear_function( lc.Tensor.fn_otimes_linear(lc.id,ShuffleWord.antipode) )\
.apply_linear_function( lc.Tensor.m12 )
assert lc.lift(sw()) \
== lc.lift(sw())\
.apply_linear_function(ShuffleWord.coproduct)\
.apply_linear_function( lc.Tensor.fn_otimes_linear(lc.id,ShuffleWord.antipode) )\
.apply_linear_function( lc.Tensor.m12 )
# Unit.
assert lc_1 == ShuffleWord.unit() * lc_1
# Counit.
assert lc_1 == lc_1\
.apply_linear_function( ShuffleWord.coproduct )\
.apply_linear_function( lc.Tensor.id_otimes_fn( ShuffleWord.counit) )
def _LOG_dual_monomial(m):
_ret = lc.LinearCombination()
for C in finer(CompositionConcatenation((m, ))):
_ret += sympy.Rational((-1)**(len(C) - 1), len(C)) * lc.lift(C)
return _ret
def _EXP_dual_monomial(m):
_ret = lc.LinearCombination()
for C in finer(CompositionConcatenation((m, ))):
_ret += sympy.Rational(1, sympy.factorial(len(C))) * lc.lift(C)
return _ret
def is_primitive(_x):
e = lc.lift(CompositionConcatenation())
return _x.apply_linear_function( CompositionConcatenation.coproduct )\
== lc.LinearCombination.otimes(_x,e) + lc.LinearCombination.otimes(e, _x)
def test_pi1():
x = lc.lift(CompositionConcatenation((Monomial({'a': 2}), )))
assert is_primitive(pi1(x, 2))
assert pi1(x, 2) == pi1(pi1(x, 2), 2)
def M_concat(*args):
return reduce(operator.mul,\
map( lambda d: lc.lift(CompositionConcatenation((Monomial(d),))), args),\
lc.lift(CompositionConcatenation()))
def lcw(*args):
return lc.lift(ConcatenationWord(args))
def test_concatentation_word():
def lcw(*args):
return lc.lift(ConcatenationWord(args))
assert lcw(1, 2, 3) + 77 * lcw(1, 9) == lc.LinearCombination.from_str(
"123 + [77] 19", ConcatenationWord)
t = lambda x, y: lc.Tensor((x, y))
def cw(*args):
return ConcatenationWord(args)
lc_1 = lc.lift(cw(1, 2))
lc_2 = lc.lift(cw(3))
assert lc.LinearCombination({ConcatenationWord((1, 2, 3)):
1}) == lc_1 * lc_2
o = lc.LinearCombination.otimes(lc_1, lc_1 + 7 * lc_2)
assert lc.LinearCombination( { t(cw(1,2,1,2), cw(1,2,1,2)):1, t(cw(1,2,1,2),cw(1,2,3)):7, t(cw(1,2,1,2),cw(3,1,2)):7, t(cw(1,2,1,2),cw(3,3)):49} )\
== o * o
lc_1 = lc.lift(cw(1, 2))
lc_2 = lc.lift(cw(3, 4, 5))
def id_otimes_coproduct(t):
for x, c in ConcatenationWord.coproduct(t[1]):
yield (lc.Tensor((t[0], x[0], x[1])), c)
def coproduct_otimes_id(t):
for x, c in ConcatenationWord.coproduct(t[0]):
yield (lc.Tensor((x[0], x[1], t[1])), c)
# Coassociativity.
assert lc_1.apply_linear_function( ConcatenationWord.coproduct ).apply_linear_function( lc.Tensor.fn_otimes_linear( lc.id, ConcatenationWord.coproduct ) ) \
== lc_1.apply_linear_function( ConcatenationWord.coproduct ).apply_linear_function( lc.Tensor.fn_otimes_linear( ConcatenationWord.coproduct, lc.id ) )
assert lc_2.apply_linear_function( ConcatenationWord.coproduct ).apply_linear_function( lc.Tensor.fn_otimes_linear( lc.id, ConcatenationWord.coproduct ) ) \
== lc_2.apply_linear_function( ConcatenationWord.coproduct ).apply_linear_function( lc.Tensor.fn_otimes_linear( ConcatenationWord.coproduct, lc.id ) )
# Condition on product vs coproduct: \Delta( \tau \tau' ) = \Delta(\tau) \Delta(\tau').
assert (lc_1 * lc_2).apply_linear_function( ConcatenationWord.coproduct ) \
== lc_1.apply_linear_function( ConcatenationWord.coproduct ) \
* lc_2.apply_linear_function( ConcatenationWord.coproduct )
# Condition on antipode: \Nabla (A \otimes id) \Delta = \eta \vareps.
assert lc.LinearCombination() \
== lc_1.apply_linear_function(ConcatenationWord.coproduct)\
.apply_linear_function( lc.Tensor.fn_otimes_linear(lc.id,ConcatenationWord.antipode) )\
.apply_linear_function( lc.Tensor.m12 )
assert lc.lift(cw()) \
== lc.lift(cw())\
.apply_linear_function(ConcatenationWord.coproduct)\
.apply_linear_function( lc.Tensor.fn_otimes_linear(lc.id,ConcatenationWord.antipode) )\
.apply_linear_function( lc.Tensor.m12 )
# Unit.
assert lc_1 == ConcatenationWord.unit() * lc_1
# Counit.
#assert lc_1 == lc_1.apply_linear_function( ConcatenationWord.coproduct )\
# .apply_linear_function( lc.Tensor.fn_otimes_linear( lc.id, ConcatenationWord.counit ) )\
# .apply_linear_function( lc.Tensor.projection(0) )
assert lc_1 == lc_1.apply_linear_function( ConcatenationWord.coproduct )\
.apply_linear_function( lc.Tensor.id_otimes_fn( ConcatenationWord.counit ) )
# The inner product is a bit awkward:
# The natural dual of the concatenation algebra is the shuffle algebra.
# But the method LinearCombination.inner_product only works with vectors of the exact same type.
# Hence we need to transform one of them into the other.
assert 1 == lc.LinearCombination.inner_product(lc_1, lc_1)
lc_sw_1 = lc.lift(ShuffleWord((1, 2)))
assert 0 == lc.LinearCombination.inner_product(lc_sw_1, lc_1)
assert 1 == lc.LinearCombination.inner_product(
lc_sw_1.apply_linear_function(shuffle_word_to_concatenation_word),
lc_1)
def lsw(*args):
return lc.lift(ShuffleWord(args))
