X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feuclidean_jordan_algebra.py;h=0b6b15da68fd4404f69ce094f4f96d07ad2c6adc;hb=4b1bdeb8c097e6c162cb0a32c07ba2740d89b1e5;hp=a0c072bb13bfdac56a3389b4463ed37e7793fafd;hpb=94eadcdcc061b299f5be5bce1450b94bbd7bfa39;p=sage.d.git

diff --git a/mjo/eja/euclidean_jordan_algebra.py b/mjo/eja/euclidean_jordan_algebra.py
index a0c072b..0b6b15d 100644
--- a/mjo/eja/euclidean_jordan_algebra.py
+++ b/mjo/eja/euclidean_jordan_algebra.py
@@ -5,13 +5,104 @@ are used in optimization, and have some additional nice methods beyond
 what can be supported in a general Jordan Algebra.
 """
 
-from sage.all import *
-
-def eja_minimal_polynomial(x):
-    """
-    Return the minimal polynomial of ``x`` in its parent EJA
-    """
-    return x._x.matrix().minimal_polynomial()
+from sage.algebras.finite_dimensional_algebras.finite_dimensional_algebra import FiniteDimensionalAlgebra
+from sage.algebras.finite_dimensional_algebras.finite_dimensional_algebra_element import FiniteDimensionalAlgebraElement
+
+class FiniteDimensionalEuclideanJordanAlgebra(FiniteDimensionalAlgebra):
+    @staticmethod
+    def __classcall__(cls, field, mult_table, names='e', category=None):
+        fda = super(FiniteDimensionalEuclideanJordanAlgebra, cls)
+        return fda.__classcall_private__(cls,
+                                         field,
+                                         mult_table,
+                                         names,
+                                         category)
+
+    def __init__(self, field, mult_table, names='e', category=None):
+        fda = super(FiniteDimensionalEuclideanJordanAlgebra, self)
+        fda.__init__(field, mult_table, names, category)
+
+
+    def _repr_(self):
+        """
+        Return a string representation of ``self``.
+        """
+        return "Euclidean Jordan algebra of degree {} over {}".format(self.degree(), self.base_ring())
+
+    def rank(self):
+        """
+        Return the rank of this EJA.
+        """
+        raise NotImplementedError
+
+
+    class Element(FiniteDimensionalAlgebraElement):
+        """
+        An element of a Euclidean Jordan algebra.
+
+        Since EJAs are commutative, the "right multiplication" matrix is
+        also the left multiplication matrix and must be symmetric::
+
+            sage: set_random_seed()
+            sage: J = eja_ln(5)
+            sage: J.random_element().matrix().is_symmetric()
+            True
+
+        """
+
+        def __pow__(self, n):
+            """
+            Return ``self`` raised to the power ``n``.
+
+            Jordan algebras are always power-associative; see for
+            example Faraut and Koranyi, Proposition II.1.2 (ii).
+            """
+            A = self.parent()
+            if n == 0:
+                return A.one()
+            elif n == 1:
+                return self
+            else:
+                return A.element_class(A, self.vector()*(self.matrix()**(n-1)))
+
+
+        def span_of_powers(self):
+            """
+            Return the vector space spanned by successive powers of
+            this element.
+            """
+            # The dimension of the subalgebra can't be greater than
+            # the big algebra, so just put everything into a list
+            # and let span() get rid of the excess.
+            V = self.vector().parent()
+            return V.span( (self**d).vector() for d in xrange(V.dimension()) )
+
+
+        def degree(self):
+            """
+            Compute the degree of this element the straightforward way
+            according to the definition; by appending powers to a list
+            and figuring out its dimension (that is, whether or not
+            they're linearly dependent).
+
+            EXAMPLES::
+
+                sage: J = eja_ln(4)
+                sage: J.one().degree()
+                1
+                sage: e0,e1,e2,e3 = J.gens()
+                sage: (e0 - e1).degree()
+                2
+
+            """
+            return self.span_of_powers().dimension()
+
+
+        def minimal_polynomial(self):
+            return self.matrix().minimal_polynomial()
+
+        def characteristic_polynomial(self):
+            return self.matrix().characteristic_polynomial()
 
 
 def eja_rn(dimension, field=QQ):
@@ -47,16 +138,12 @@ def eja_rn(dimension, field=QQ):
     Qs = [ matrix(field, dimension, dimension, lambda k,j: 1*(k == j == i))
            for i in xrange(dimension) ]
 
-    # Assuming associativity is wrong here, but it works to
-    # temporarily trick the Jordan algebra constructor into using the
-    # multiplication table.
-    A = FiniteDimensionalAlgebra(field,Qs,assume_associative=True)
-    return JordanAlgebra(A)
+    return FiniteDimensionalEuclideanJordanAlgebra(field,Qs)
 
 
 def eja_ln(dimension, field=QQ):
     """
-    Return the Jordan algebra corresponding to the Lorenzt "ice cream"
+    Return the Jordan algebra corresponding to the Lorentz "ice cream"
     cone of the given ``dimension``.
 
     EXAMPLES:
@@ -101,8 +188,4 @@ def eja_ln(dimension, field=QQ):
         Qi[0,0] = Qi[0,0] * ~field(2)
         Qs.append(Qi)
 
-    # Assuming associativity is wrong here, but it works to
-    # temporarily trick the Jordan algebra constructor into using the
-    # multiplication table.
-    A = FiniteDimensionalAlgebra(field,Qs,assume_associative=True)
-    return JordanAlgebra(A)
+    return FiniteDimensionalEuclideanJordanAlgebra(field,Qs)