def tensor_product(self, other):
r"""
Return the graded tensor product.
INPUT:
- ``other`` -- a filtered vector space.
OUTPUT:
The graded tensor product, that is, the tensor product of a
generator of degree `d_1` with a generator in degree `d_2` has
degree `d_1 + d_2`.
EXAMPLES::
sage: F1 = FilteredVectorSpace(1, 1)
sage: F2 = FilteredVectorSpace(1, 2)
sage: F1.tensor_product(F2)
QQ^1 >= 0
sage: F1 * F2
QQ^1 >= 0
sage: F1.min_degree()
1
sage: F2.min_degree()
2
sage: (F1*F2).min_degree()
3
A suitable base ring is chosen if they do not match::
sage: v = [(1,0), (0,1)]
sage: F1 = FilteredVectorSpace(v, {0:[0], 1:[1]}, base_ring=QQ)
sage: F2 = FilteredVectorSpace(v, {0:[0], 1:[1]}, base_ring=RDF)
sage: F1 * F2
RDF^4 >= RDF^3 >= RDF^1 >= 0
"""
V = self
W = other
from sage.structure.element import get_coercion_model
base_ring = get_coercion_model().common_parent(V.base_ring(), W.base_ring())
from sage.modules.tensor_operations import VectorCollection, TensorOperation
V_generators, V_indices = V.presentation()
W_generators, W_indices = W.presentation()
V_coll = VectorCollection(V_generators, base_ring, V.dimension())
W_coll = VectorCollection(W_generators, base_ring, W.dimension())
T = TensorOperation([V_coll, W_coll], 'product')
filtration = dict()
for V_deg in V.support():
for W_deg in W.support():
deg = V_deg + W_deg
indices = filtration.get(deg, set())
for i in V_indices[V_deg]:
for j in W_indices[W_deg]:
i_tensor_j = T.index_map(i, j)
indices.add(i_tensor_j)
filtration[deg] = indices
return FilteredVectorSpace(T.vectors(), filtration, base_ring=base_ring)
def tensor_product(self, other):
r"""
Return the graded tensor product.
INPUT:
- ``other`` -- a filtered vector space.
OUTPUT:
The graded tensor product, that is, the tensor product of a
generator of degree `d_1` with a generator in degree `d_2` has
degree `d_1 + d_2`.
EXAMPLES::
sage: F1 = FilteredVectorSpace(1, 1)
sage: F2 = FilteredVectorSpace(1, 2)
sage: F1.tensor_product(F2)
QQ^1 >= 0
sage: F1 * F2
QQ^1 >= 0
sage: F1.min_degree()
1
sage: F2.min_degree()
2
sage: (F1*F2).min_degree()
3
A suitable base ring is chosen if they do not match::
sage: v = [(1,0), (0,1)]
sage: F1 = FilteredVectorSpace(v, {0:[0], 1:[1]}, base_ring=QQ)
sage: F2 = FilteredVectorSpace(v, {0:[0], 1:[1]}, base_ring=RDF)
sage: F1 * F2
RDF^4 >= RDF^3 >= RDF^1 >= 0
"""
V = self
W = other
from sage.structure.element import get_coercion_model
base_ring = get_coercion_model().common_parent(V.base_ring(), W.base_ring())
from sage.modules.tensor_operations import VectorCollection, TensorOperation
V_generators, V_indices = V.presentation()
W_generators, W_indices = W.presentation()
V_coll = VectorCollection(V_generators, base_ring, V.dimension())
W_coll = VectorCollection(W_generators, base_ring, W.dimension())
T = TensorOperation([V_coll, W_coll], 'product')
filtration = dict()
for V_deg in V.support():
for W_deg in W.support():
deg = V_deg + W_deg
indices = filtration.get(deg, set())
for i in V_indices[V_deg]:
for j in W_indices[W_deg]:
i_tensor_j = T.index_map(i, j)
indices.add(i_tensor_j)
filtration[deg] = indices
return FilteredVectorSpace(T.vectors(), filtration, base_ring=base_ring)
def _power_operation(self, n, operation):
"""
Return tensor power operation.
INPUT:
- ``n`` -- integer. the number of factors of ``self``.
- ``operation`` -- string. See
:class:`~sage.modules.tensor_operations.TensorOperation` for
details.
EXAMPLES::
sage: F = FilteredVectorSpace(1, 1) + FilteredVectorSpace(1, 2); F
QQ^2 >= QQ^1 >= 0
sage: F._power_operation(2, 'symmetric')
QQ^3 >= QQ^2 >= QQ^1 >= 0
sage: F._power_operation(2, 'antisymmetric')
QQ^1 >= 0
"""
from sage.modules.tensor_operations import VectorCollection, TensorOperation
generators, indices = self.presentation()
V = VectorCollection(generators, self.base_ring(), self.dimension())
T = TensorOperation([V] * n, operation)
iters = [self.support()] * n
filtration = dict()
from sage.categories.cartesian_product import cartesian_product
for degrees in cartesian_product(iters):
deg = sum(degrees)
filt_deg = filtration.get(deg, set())
for i in cartesian_product([indices.get(d) for d in degrees]):
pow_i = T.index_map(*i)
if pow_i is not None:
filt_deg.add(pow_i)
filtration[deg] = filt_deg
return FilteredVectorSpace(T.vectors(),
filtration,
base_ring=self.base_ring())
def _power_operation(self, n, operation):
"""
Return tensor power operation.
INPUT:
- ``n`` -- integer. the number of factors of ``self``.
- ``operation`` -- string. See
:class:`~sage.modules.tensor_operations.TensorOperation` for
details.
EXAMPLES::
sage: F = FilteredVectorSpace(1, 1) + FilteredVectorSpace(1, 2); F
QQ^2 >= QQ^1 >= 0
sage: F._power_operation(2, 'symmetric')
QQ^3 >= QQ^2 >= QQ^1 >= 0
sage: F._power_operation(2, 'antisymmetric')
QQ^1 >= 0
"""
from sage.modules.tensor_operations import VectorCollection, TensorOperation
generators, indices = self.presentation()
V = VectorCollection(generators, self.base_ring(), self.dimension())
T = TensorOperation([V] * n, operation)
iters = [self.support()] * n
filtration = dict()
from sage.categories.cartesian_product import cartesian_product
for degrees in cartesian_product(iters):
deg = sum(degrees)
filt_deg = filtration.get(deg, set())
for i in cartesian_product([indices.get(d) for d in degrees]):
pow_i = T.index_map(*i)
if pow_i is not None:
filt_deg.add(pow_i)
filtration[deg] = filt_deg
return FilteredVectorSpace(T.vectors(), filtration, base_ring=self.base_ring())
