X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_subalgebra.py;h=9326793f9dfd1a1619241c3dcd2e5bb8dcda1351;hb=37b994d59056fc4adb9d42f3a0d2dcc5ca6d6d56;hp=c82bd1a485c5eb6b82e92134fc30658be4d6d669;hpb=16dfa403c6eb709d3a5188a0f19919652b6a225d;p=sage.d.git diff --git a/mjo/eja/eja_subalgebra.py b/mjo/eja/eja_subalgebra.py index c82bd1a..9326793 100644 --- a/mjo/eja/eja_subalgebra.py +++ b/mjo/eja/eja_subalgebra.py @@ -2,7 +2,7 @@ from sage.matrix.constructor import matrix from mjo.eja.eja_algebra import FiniteDimensionalEuclideanJordanAlgebra from mjo.eja.eja_element import FiniteDimensionalEuclideanJordanAlgebraElement - +from mjo.eja.eja_utils import gram_schmidt class FiniteDimensionalEuclideanJordanElementSubalgebraElement(FiniteDimensionalEuclideanJordanAlgebraElement): """ @@ -99,7 +99,7 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide 1 """ - def __init__(self, elt): + def __init__(self, elt, orthonormalize_basis): self._superalgebra = elt.parent() category = self._superalgebra.category().Associative() V = self._superalgebra.vector_space() @@ -135,31 +135,36 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide natural_basis=natural_basis) - # First compute the vector subspace spanned by the powers of - # the given element. - superalgebra_basis = [self._superalgebra.one()] - # If our superalgebra is a subalgebra of something else, then - # superalgebra.one().to_vector() won't have the right - # coordinates unless we use V.from_vector() below. - basis_vectors = [V.from_vector(self._superalgebra.one().to_vector())] - W = V.span_of_basis(basis_vectors) - for exponent in range(1, V.dimension()): - new_power = elt**exponent - basis_vectors.append( V.from_vector(new_power.to_vector()) ) - try: - W = V.span_of_basis(basis_vectors) - superalgebra_basis.append( new_power ) - except ValueError: - # Vectors weren't independent; bail and keep the - # last subspace that worked. - break - - # Make the basis hashable for UniqueRepresentation. - superalgebra_basis = tuple(superalgebra_basis) - - # Now figure out the entries of the right-multiplication - # matrix for the successive basis elements b0, b1,... of - # that subspace. + # This list is guaranteed to contain all independent powers, + # because it's the maximal set of powers that could possibly + # be independent (by a dimension argument). + powers = [ elt**k for k in range(V.dimension()) ] + + if orthonormalize_basis == False: + # In this case, we just need to figure out which elements + # of the "powers" list are redundant... First compute the + # vector subspace spanned by the powers of the given + # element. + power_vectors = [ p.to_vector() for p in powers ] + + # Figure out which powers form a linearly-independent set. + ind_rows = matrix(field, power_vectors).pivot_rows() + + # Pick those out of the list of all powers. + superalgebra_basis = tuple(map(powers.__getitem__, ind_rows)) + + # If our superalgebra is a subalgebra of something else, then + # these vectors won't have the right coordinates for + # V.span_of_basis() unless we use V.from_vector() on them. + basis_vectors = map(power_vectors.__getitem__, ind_rows) + else: + # If we're going to orthonormalize the basis anyway, we + # might as well just do Gram-Schmidt on the whole list of + # powers. The redundant ones will get zero'd out. + superalgebra_basis = gram_schmidt(powers) + basis_vectors = [ b.to_vector() for b in superalgebra_basis ] + + W = V.span_of_basis( V.from_vector(v) for v in basis_vectors ) n = len(superalgebra_basis) mult_table = [[W.zero() for i in range(n)] for j in range(n)] for i in range(n): @@ -197,6 +202,30 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide natural_basis=natural_basis) + def _a_regular_element(self): + """ + Override the superalgebra method to return the one + regular element that is sure to exist in this + subalgebra, namely the element that generated it. + + SETUP:: + + sage: from mjo.eja.eja_algebra import random_eja + + TESTS:: + + sage: set_random_seed() + sage: J = random_eja().random_element().subalgebra_generated_by() + sage: J._a_regular_element().is_regular() + True + + """ + if self.dimension() == 0: + return self.zero() + else: + return self.monomial(1) + + def _element_constructor_(self, elt): """ Construct an element of this subalgebra from the given one. @@ -212,7 +241,7 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide sage: J = RealSymmetricEJA(3) sage: x = sum( i*J.gens()[i] for i in range(6) ) - sage: K = FiniteDimensionalEuclideanJordanElementSubalgebra(x) + sage: K = FiniteDimensionalEuclideanJordanElementSubalgebra(x,False) sage: [ K(x^k) for k in range(J.rank()) ] [f0, f1, f2] @@ -289,6 +318,18 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide return self.monomial(self.one_basis()) + def natural_basis_space(self): + """ + Return the natural basis space of this algebra, which is identical + to that of its superalgebra. + + This is correct "by definition," and avoids a mismatch when the + subalgebra is trivial (with no natural basis to infer anything + from) and the parent is not. + """ + return self.superalgebra().natural_basis_space() + + def superalgebra(self): """ Return the superalgebra that this algebra was generated from. @@ -306,20 +347,20 @@ class FiniteDimensionalEuclideanJordanElementSubalgebra(FiniteDimensionalEuclide EXAMPLES:: sage: J = RealSymmetricEJA(3) - sage: x = sum( i*J.gens()[i] for i in range(6) ) - sage: K = FiniteDimensionalEuclideanJordanElementSubalgebra(x) + sage: x = J.monomial(0) + 2*J.monomial(2) + 5*J.monomial(5) + sage: K = FiniteDimensionalEuclideanJordanElementSubalgebra(x,False) sage: K.vector_space() - Vector space of degree 6 and dimension 3 over Rational Field + Vector space of degree 6 and dimension 3 over... User basis matrix: [ 1 0 1 0 0 1] - [ 0 1 2 3 4 5] - [10 14 21 19 31 50] + [ 1 0 2 0 0 5] + [ 1 0 4 0 0 25] sage: (x^0).to_vector() (1, 0, 1, 0, 0, 1) sage: (x^1).to_vector() - (0, 1, 2, 3, 4, 5) + (1, 0, 2, 0, 0, 5) sage: (x^2).to_vector() - (10, 14, 21, 19, 31, 50) + (1, 0, 4, 0, 0, 25) """ return self._vector_space