X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_algebra.py;h=02ed966540132c07af408a1a9fb4e6eebc220c31;hb=b05705ab04692f738a57a6ef387662ba5ea46ceb;hp=1ae3286cea5a26eda3d82f7161aab639bc9d724c;hpb=a2dabad45525791c258a91e2134abbf5f5591dbe;p=sage.d.git diff --git a/mjo/eja/eja_algebra.py b/mjo/eja/eja_algebra.py index 1ae3286..02ed966 100644 --- a/mjo/eja/eja_algebra.py +++ b/mjo/eja/eja_algebra.py @@ -5,7 +5,7 @@ are used in optimization, and have some additional nice methods beyond what can be supported in a general Jordan Algebra. """ -from itertools import repeat +from itertools import izip, repeat from sage.algebras.quatalg.quaternion_algebra import QuaternionAlgebra from sage.categories.magmatic_algebras import MagmaticAlgebras @@ -61,9 +61,6 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): self._rank = rank self._natural_basis = natural_basis - # TODO: HACK for the charpoly.. needs redesign badly. - self._basis_normalizers = None - if category is None: category = MagmaticAlgebras(field).FiniteDimensional() category = category.WithBasis().Unital() @@ -156,26 +153,6 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): return self.from_vector(coords) - @staticmethod - def _max_test_case_size(): - """ - Return an integer "size" that is an upper bound on the size of - this algebra when it is used in a random test - case. Unfortunately, the term "size" is quite vague -- when - dealing with `R^n` under either the Hadamard or Jordan spin - product, the "size" refers to the dimension `n`. When dealing - with a matrix algebra (real symmetric or complex/quaternion - Hermitian), it refers to the size of the matrix, which is - far less than the dimension of the underlying vector space. - - We default to five in this class, which is safe in `R^n`. The - matrix algebra subclasses (or any class where the "size" is - interpreted to be far less than the dimension) should override - with a smaller number. - """ - return 5 - - def _repr_(self): """ Return a string representation of ``self``. @@ -259,19 +236,6 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): store the trace/determinant (a_{r-1} and a_{0} respectively) separate from the entire characteristic polynomial. """ - if self._basis_normalizers is not None: - # Must be a matrix class? - # WARNING/TODO: this whole mess is mis-designed. - n = self.natural_basis_space().nrows() - field = self.base_ring().base_ring() # yeeeeaaaahhh - J = self.__class__(n, field, False) - (_,x,_,_) = J._charpoly_matrix_system() - p = J._charpoly_coeff(i) - # p might be missing some vars, have to substitute "optionally" - pairs = zip(x.base_ring().gens(), self._basis_normalizers) - substitutions = { v: v*c for (v,c) in pairs } - return p.subs(substitutions) - (A_of_x, x, xr, detA) = self._charpoly_matrix_system() R = A_of_x.base_ring() if i >= self.rank(): @@ -425,7 +389,7 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): # assign a[r] goes out-of-bounds. a.append(1) # corresponds to x^r - return sum( a[k]*(t**k) for k in range(len(a)) ) + return sum( a[k]*(t**k) for k in xrange(len(a)) ) def inner_product(self, x, y): @@ -442,8 +406,8 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): EXAMPLES: - Our inner product satisfies the Jordan axiom, which is also - referred to as "associativity" for a symmetric bilinear form:: + Our inner product is "associative," which means the following for + a symmetric bilinear form:: sage: set_random_seed() sage: J = random_eja() @@ -507,7 +471,7 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): """ M = list(self._multiplication_table) # copy - for i in range(len(M)): + for i in xrange(len(M)): # M had better be "square" M[i] = [self.monomial(i)] + M[i] M = [["*"] + list(self.gens())] + M @@ -676,27 +640,6 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): """ return tuple( self.random_element() for idx in xrange(count) ) - @classmethod - def random_instance(cls, field=QQ, **kwargs): - """ - Return a random instance of this type of algebra. - - In subclasses for algebras that we know how to construct, this - is a shortcut for constructing test cases and examples. - """ - if cls is FiniteDimensionalEuclideanJordanAlgebra: - # Red flag! But in theory we could do this I guess. The - # only finite-dimensional exceptional EJA is the - # octononions. So, we could just create an EJA from an - # associative matrix algebra (generated by a subset of - # elements) with the symmetric product. Or, we could punt - # to random_eja() here, override it in our subclasses, and - # not worry about it. - raise NotImplementedError - - n = ZZ.random_element(1, cls._max_test_case_size()) - return cls(n, field, **kwargs) - def rank(self): """ @@ -731,18 +674,12 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): The rank of the `n`-by-`n` Hermitian real, complex, or quaternion matrices is `n`:: - sage: RealSymmetricEJA(2).rank() - 2 - sage: ComplexHermitianEJA(2).rank() - 2 + sage: RealSymmetricEJA(4).rank() + 4 + sage: ComplexHermitianEJA(3).rank() + 3 sage: QuaternionHermitianEJA(2).rank() 2 - sage: RealSymmetricEJA(5).rank() - 5 - sage: ComplexHermitianEJA(5).rank() - 5 - sage: QuaternionHermitianEJA(5).rank() - 5 TESTS: @@ -779,7 +716,57 @@ class FiniteDimensionalEuclideanJordanAlgebra(CombinatorialFreeModule): Element = FiniteDimensionalEuclideanJordanAlgebraElement -class RealCartesianProductEJA(FiniteDimensionalEuclideanJordanAlgebra): +class KnownRankEJA(object): + """ + A class for algebras that we actually know we can construct. The + main issue is that, for most of our methods to make sense, we need + to know the rank of our algebra. Thus we can't simply generate a + "random" algebra, or even check that a given basis and product + satisfy the axioms; because even if everything looks OK, we wouldn't + know the rank we need to actuallty build the thing. + + Not really a subclass of FDEJA because doing that causes method + resolution errors, e.g. + + TypeError: Error when calling the metaclass bases + Cannot create a consistent method resolution + order (MRO) for bases FiniteDimensionalEuclideanJordanAlgebra, + KnownRankEJA + + """ + @staticmethod + def _max_test_case_size(): + """ + Return an integer "size" that is an upper bound on the size of + this algebra when it is used in a random test + case. Unfortunately, the term "size" is quite vague -- when + dealing with `R^n` under either the Hadamard or Jordan spin + product, the "size" refers to the dimension `n`. When dealing + with a matrix algebra (real symmetric or complex/quaternion + Hermitian), it refers to the size of the matrix, which is + far less than the dimension of the underlying vector space. + + We default to five in this class, which is safe in `R^n`. The + matrix algebra subclasses (or any class where the "size" is + interpreted to be far less than the dimension) should override + with a smaller number. + """ + return 5 + + @classmethod + def random_instance(cls, field=QQ, **kwargs): + """ + Return a random instance of this type of algebra. + + Beware, this will crash for "most instances" because the + constructor below looks wrong. + """ + n = ZZ.random_element(cls._max_test_case_size()) + 1 + return cls(n, field, **kwargs) + + +class RealCartesianProductEJA(FiniteDimensionalEuclideanJordanAlgebra, + KnownRankEJA): """ Return the Euclidean Jordan Algebra corresponding to the set `R^n` under the Hadamard product. @@ -821,8 +808,8 @@ class RealCartesianProductEJA(FiniteDimensionalEuclideanJordanAlgebra): """ def __init__(self, n, field=QQ, **kwargs): V = VectorSpace(field, n) - mult_table = [ [ V.gen(i)*(i == j) for j in range(n) ] - for i in range(n) ] + mult_table = [ [ V.gen(i)*(i == j) for j in xrange(n) ] + for i in xrange(n) ] fdeja = super(RealCartesianProductEJA, self) return fdeja.__init__(field, mult_table, rank=n, **kwargs) @@ -888,11 +875,7 @@ def random_eja(): Euclidean Jordan algebra of dimension... """ - classname = choice([RealCartesianProductEJA, - JordanSpinEJA, - RealSymmetricEJA, - ComplexHermitianEJA, - QuaternionHermitianEJA]) + classname = choice(KnownRankEJA.__subclasses__()) return classname.random_instance() @@ -905,16 +888,22 @@ class MatrixEuclideanJordanAlgebra(FiniteDimensionalEuclideanJordanAlgebra): def _max_test_case_size(): # Play it safe, since this will be squared and the underlying # field can have dimension 4 (quaternions) too. - return 3 + return 2 - @classmethod - def _denormalized_basis(cls, n, field): - raise NotImplementedError + def __init__(self, field, basis, rank, normalize_basis=True, **kwargs): + """ + Compared to the superclass constructor, we take a basis instead of + a multiplication table because the latter can be computed in terms + of the former when the product is known (like it is here). + """ + # Used in this class's fast _charpoly_coeff() override. + self._basis_normalizers = None - def __init__(self, n, field=QQ, normalize_basis=True, **kwargs): - S = self._denormalized_basis(n, field) + # We're going to loop through this a few times, so now's a good + # time to ensure that it isn't a generator expression. + basis = tuple(basis) - if n > 1 and normalize_basis: + if rank > 1 and normalize_basis: # We'll need sqrt(2) to normalize the basis, and this # winds up in the multiplication table, so the whole # algebra needs to be over the field extension. @@ -923,21 +912,47 @@ class MatrixEuclideanJordanAlgebra(FiniteDimensionalEuclideanJordanAlgebra): p = z**2 - 2 if p.is_irreducible(): field = NumberField(p, 'sqrt2', embedding=RLF(2).sqrt()) - S = [ s.change_ring(field) for s in S ] + basis = tuple( s.change_ring(field) for s in basis ) self._basis_normalizers = tuple( - ~(self.natural_inner_product(s,s).sqrt()) for s in S ) - S = tuple( s*c for (s,c) in zip(S,self._basis_normalizers) ) + ~(self.natural_inner_product(s,s).sqrt()) for s in basis ) + basis = tuple(s*c for (s,c) in izip(basis,self._basis_normalizers)) - Qs = self.multiplication_table_from_matrix_basis(S) + Qs = self.multiplication_table_from_matrix_basis(basis) fdeja = super(MatrixEuclideanJordanAlgebra, self) return fdeja.__init__(field, Qs, - rank=n, - natural_basis=S, + rank=rank, + natural_basis=basis, **kwargs) + @cached_method + def _charpoly_coeff(self, i): + """ + Override the parent method with something that tries to compute + over a faster (non-extension) field. + """ + if self._basis_normalizers is None: + # We didn't normalize, so assume that the basis we started + # with had entries in a nice field. + return super(MatrixEuclideanJordanAlgebra, self)._charpoly_coeff(i) + else: + basis = ( (b/n) for (b,n) in izip(self.natural_basis(), + self._basis_normalizers) ) + field = self.base_ring().base_ring() # yeeeaahhhhhhh + J = MatrixEuclideanJordanAlgebra(field, + basis, + self.rank(), + normalize_basis=False) + (_,x,_,_) = J._charpoly_matrix_system() + p = J._charpoly_coeff(i) + # p might be missing some vars, have to substitute "optionally" + pairs = izip(x.base_ring().gens(), self._basis_normalizers) + substitutions = { v: v*c for (v,c) in pairs } + return p.subs(substitutions) + + @staticmethod def multiplication_table_from_matrix_basis(basis): """ @@ -959,9 +974,9 @@ class MatrixEuclideanJordanAlgebra(FiniteDimensionalEuclideanJordanAlgebra): V = VectorSpace(field, dimension**2) W = V.span_of_basis( _mat2vec(s) for s in basis ) n = len(basis) - mult_table = [[W.zero() for j in range(n)] for i in range(n)] - for i in range(n): - for j in range(n): + mult_table = [[W.zero() for j in xrange(n)] for i in xrange(n)] + for i in xrange(n): + for j in xrange(n): mat_entry = (basis[i]*basis[j] + basis[j]*basis[i])/2 mult_table[i][j] = W.coordinate_vector(_mat2vec(mat_entry)) @@ -1013,7 +1028,25 @@ class MatrixEuclideanJordanAlgebra(FiniteDimensionalEuclideanJordanAlgebra): return tr.coefficient_tuple()[0] -class RealSymmetricEJA(MatrixEuclideanJordanAlgebra): +class RealMatrixEuclideanJordanAlgebra(MatrixEuclideanJordanAlgebra): + @staticmethod + def real_embed(M): + """ + The identity function, for embedding real matrices into real + matrices. + """ + return M + + @staticmethod + def real_unembed(M): + """ + The identity function, for unembedding real matrices from real + matrices. + """ + return M + + +class RealSymmetricEJA(RealMatrixEuclideanJordanAlgebra, KnownRankEJA): """ The rank-n simple EJA consisting of real symmetric n-by-n matrices, the usual symmetric Jordan product, and the trace inner @@ -1113,37 +1146,17 @@ class RealSymmetricEJA(MatrixEuclideanJordanAlgebra): else: Sij = Eij + Eij.transpose() S.append(Sij) - return tuple(S) + return S @staticmethod def _max_test_case_size(): - return 5 # Dimension 10 - - @staticmethod - def real_embed(M): - """ - Embed the matrix ``M`` into a space of real matrices. - - The matrix ``M`` can have entries in any field at the moment: - the real numbers, complex numbers, or quaternions. And although - they are not a field, we can probably support octonions at some - point, too. This function returns a real matrix that "acts like" - the original with respect to matrix multiplication; i.e. - - real_embed(M*N) = real_embed(M)*real_embed(N) - - """ - return M - + return 4 # Dimension 10 - @staticmethod - def real_unembed(M): - """ - The inverse of :meth:`real_embed`. - """ - return M + def __init__(self, n, field=QQ, **kwargs): + basis = self._denormalized_basis(n, field) + super(RealSymmetricEJA, self).__init__(field, basis, n, **kwargs) class ComplexMatrixEuclideanJordanAlgebra(MatrixEuclideanJordanAlgebra): @@ -1265,7 +1278,38 @@ class ComplexMatrixEuclideanJordanAlgebra(MatrixEuclideanJordanAlgebra): return matrix(F, n/2, elements) -class ComplexHermitianEJA(ComplexMatrixEuclideanJordanAlgebra): + @classmethod + def natural_inner_product(cls,X,Y): + """ + Compute a natural inner product in this algebra directly from + its real embedding. + + SETUP:: + + sage: from mjo.eja.eja_algebra import ComplexHermitianEJA + + TESTS: + + This gives the same answer as the slow, default method implemented + in :class:`MatrixEuclideanJordanAlgebra`:: + + sage: set_random_seed() + sage: J = ComplexHermitianEJA.random_instance() + sage: x,y = J.random_elements(2) + sage: Xe = x.natural_representation() + sage: Ye = y.natural_representation() + sage: X = ComplexHermitianEJA.real_unembed(Xe) + sage: Y = ComplexHermitianEJA.real_unembed(Ye) + sage: expected = (X*Y).trace().vector()[0] + sage: actual = ComplexHermitianEJA.natural_inner_product(Xe,Ye) + sage: actual == expected + True + + """ + return RealMatrixEuclideanJordanAlgebra.natural_inner_product(X,Y)/2 + + +class ComplexHermitianEJA(ComplexMatrixEuclideanJordanAlgebra, KnownRankEJA): """ The rank-n simple EJA consisting of complex Hermitian n-by-n matrices over the real numbers, the usual symmetric Jordan product, @@ -1326,6 +1370,7 @@ class ComplexHermitianEJA(ComplexMatrixEuclideanJordanAlgebra): True """ + @classmethod def _denormalized_basis(cls, n, field): """ @@ -1377,9 +1422,13 @@ class ComplexHermitianEJA(ComplexMatrixEuclideanJordanAlgebra): # Since we embedded these, we can drop back to the "field" that we # started with instead of the complex extension "F". - return tuple( s.change_ring(field) for s in S ) + return ( s.change_ring(field) for s in S ) + def __init__(self, n, field=QQ, **kwargs): + basis = self._denormalized_basis(n,field) + super(ComplexHermitianEJA,self).__init__(field, basis, n, **kwargs) + class QuaternionMatrixEuclideanJordanAlgebra(MatrixEuclideanJordanAlgebra): @staticmethod @@ -1513,8 +1562,39 @@ class QuaternionMatrixEuclideanJordanAlgebra(MatrixEuclideanJordanAlgebra): return matrix(Q, n/4, elements) + @classmethod + def natural_inner_product(cls,X,Y): + """ + Compute a natural inner product in this algebra directly from + its real embedding. + + SETUP:: + + sage: from mjo.eja.eja_algebra import QuaternionHermitianEJA + + TESTS: + + This gives the same answer as the slow, default method implemented + in :class:`MatrixEuclideanJordanAlgebra`:: + + sage: set_random_seed() + sage: J = QuaternionHermitianEJA.random_instance() + sage: x,y = J.random_elements(2) + sage: Xe = x.natural_representation() + sage: Ye = y.natural_representation() + sage: X = QuaternionHermitianEJA.real_unembed(Xe) + sage: Y = QuaternionHermitianEJA.real_unembed(Ye) + sage: expected = (X*Y).trace().coefficient_tuple()[0] + sage: actual = QuaternionHermitianEJA.natural_inner_product(Xe,Ye) + sage: actual == expected + True + + """ + return RealMatrixEuclideanJordanAlgebra.natural_inner_product(X,Y)/4 + -class QuaternionHermitianEJA(QuaternionMatrixEuclideanJordanAlgebra): +class QuaternionHermitianEJA(QuaternionMatrixEuclideanJordanAlgebra, + KnownRankEJA): """ The rank-n simple EJA consisting of self-adjoint n-by-n quaternion matrices, the usual symmetric Jordan product, and the @@ -1625,11 +1705,15 @@ class QuaternionHermitianEJA(QuaternionMatrixEuclideanJordanAlgebra): S.append(Sij_J) Sij_K = cls.real_embed(K*Eij - K*Eij.transpose()) S.append(Sij_K) - return tuple(S) + return S + def __init__(self, n, field=QQ, **kwargs): + basis = self._denormalized_basis(n,field) + super(QuaternionHermitianEJA,self).__init__(field, basis, n, **kwargs) -class JordanSpinEJA(FiniteDimensionalEuclideanJordanAlgebra): + +class JordanSpinEJA(FiniteDimensionalEuclideanJordanAlgebra, KnownRankEJA): """ The rank-2 simple EJA consisting of real vectors ``x=(x0, x_bar)`` with the usual inner product and jordan product ``x*y = @@ -1669,9 +1753,9 @@ class JordanSpinEJA(FiniteDimensionalEuclideanJordanAlgebra): """ def __init__(self, n, field=QQ, **kwargs): V = VectorSpace(field, n) - mult_table = [[V.zero() for j in range(n)] for i in range(n)] - for i in range(n): - for j in range(n): + mult_table = [[V.zero() for j in xrange(n)] for i in xrange(n)] + for i in xrange(n): + for j in xrange(n): x = V.gen(i) y = V.gen(j) x0 = x[0]