]> gitweb.michael.orlitzky.com - sage.d.git/blobdiff - mjo/eja/eja_algebra.py
eja: demonstration for https://trac.sagemath.org/ticket/31421.
[sage.d.git] / mjo / eja / eja_algebra.py
index 7da2207e9bce1fdf306d06586f7f8bd0ca63e648..e6a60929055fccb28fd86765e7743a028b1904a1 100644 (file)
@@ -2690,7 +2690,8 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
 
     SETUP::
 
-        sage: from mjo.eja.eja_algebra import (CartesianProductEJA,
+        sage: from mjo.eja.eja_algebra import (random_eja,
+        ....:                                  CartesianProductEJA,
         ....:                                  HadamardEJA,
         ....:                                  JordanSpinEJA,
         ....:                                  RealSymmetricEJA)
@@ -2740,37 +2741,57 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
         ...
         ValueError: all factors must share the same base field
 
+    The "cached" Jordan and inner products are the componentwise
+    ones::
+
+        sage: set_random_seed()
+        sage: J1 = random_eja()
+        sage: J2 = random_eja()
+        sage: J = cartesian_product([J1,J2])
+        sage: x,y = J.random_elements(2)
+        sage: x*y == J.cartesian_jordan_product(x,y)
+        True
+        sage: x.inner_product(y) == J.cartesian_inner_product(x,y)
+        True
+
     """
     def __init__(self, modules, **kwargs):
-        CombinatorialFreeModule_CartesianProduct.__init__(self, modules, **kwargs)
+        CombinatorialFreeModule_CartesianProduct.__init__(self,
+                                                          modules,
+                                                          **kwargs)
         field = modules[0].base_ring()
         if not all( J.base_ring() == field for J in modules ):
             raise ValueError("all factors must share the same base field")
 
-        M = cartesian_product( [J.matrix_space() for J in modules] )
+        basis = tuple( b.to_vector().column() for b in self.basis() )
 
-        m = len(modules)
-        W = VectorSpace(field,m)
-        self._matrix_basis = []
-        for k in range(m):
-            for a in modules[k].matrix_basis():
-                v = W.zero().list()
-                v[k] = a
-                self._matrix_basis.append(M(v))
+        # Define jordan/inner products that operate on the basis.
+        def jordan_product(x_mat,y_mat):
+            x = self.from_vector(_mat2vec(x_mat))
+            y = self.from_vector(_mat2vec(y_mat))
+            return self.cartesian_jordan_product(x,y).to_vector().column()
 
-        self._matrix_basis = tuple(self._matrix_basis)
+        def inner_product(x_mat, y_mat):
+            x = self.from_vector(_mat2vec(x_mat))
+            y = self.from_vector(_mat2vec(y_mat))
+            return self.cartesian_inner_product(x,y)
 
-        n = len(self._matrix_basis)
-        # TODO:
-        #
-        # Initialize the FDEJA class, too. Does this override the
-        # initialization that we did for the
-        # CombinatorialFreeModule_CartesianProduct class? If not, we
-        # will probably have to duplicate some of the work (i.e. one
-        # of the constructors).  Since the CartesianProduct one is
-        # smaller, that makes the most sense to copy/paste if it comes
-        # down to that.
+        # Use whatever category the superclass came up with. Usually
+        # some join of the EJA and Cartesian product
+        # categories. There's no need to check the field since it
+        # already came from an EJA.
         #
+        # If you want the basis to be orthonormalized, orthonormalize
+        # the factors.
+        FiniteDimensionalEJA.__init__(self,
+                                      basis,
+                                      jordan_product,
+                                      inner_product,
+                                      field=field,
+                                      orthonormalize=False,
+                                      check_field=False,
+                                      check_axioms=False,
+                                      category=self.category())
 
         self.rank.set_cache(sum(J.rank() for J in modules))
 
@@ -2780,10 +2801,15 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
         SETUP::
 
             sage: from mjo.eja.eja_algebra import (random_eja,
+            ....:                                  JordanSpinEJA,
             ....:                                  HadamardEJA,
-            ....:                                  RealSymmetricEJA)
+            ....:                                  RealSymmetricEJA,
+            ....:                                  ComplexHermitianEJA)
 
-        EXAMPLES::
+        EXAMPLES:
+
+        The projection morphisms are Euclidean Jordan algebra
+        operators::
 
             sage: J1 = HadamardEJA(2)
             sage: J2 = RealSymmetricEJA(2)
@@ -2810,6 +2836,21 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
             Codomain: Euclidean Jordan algebra of dimension 3 over Algebraic
             Real Field
 
+        The projections work the way you'd expect on the vector
+        representation of an element::
+
+            sage: J1 = JordanSpinEJA(2)
+            sage: J2 = ComplexHermitianEJA(2)
+            sage: J = cartesian_product([J1,J2])
+            sage: pi_left = J.cartesian_projection(0)
+            sage: pi_right = J.cartesian_projection(1)
+            sage: pi_left(J.one()).to_vector()
+            (1, 0)
+            sage: pi_right(J.one()).to_vector()
+            (1, 0, 0, 1)
+            sage: J.one().to_vector()
+            (1, 0, 1, 0, 0, 1)
+
         TESTS:
 
         The answer never changes::
@@ -2825,12 +2866,11 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
 
         """
         Ji = self.cartesian_factors()[i]
-        # We reimplement the CombinatorialFreeModule superclass method
-        # because if we don't, something gets messed up with the caching
-        # and the answer changes the second time you run it. See the TESTS.
-        Pi = self._module_morphism(lambda j_t: Ji.monomial(j_t[1])
-                                   if i == j_t[0] else Ji.zero(),
-                                   codomain=Ji)
+
+        # Required until https://trac.sagemath.org/ticket/31421 is fixed.
+        Pi = self.module_morphism(lambda j_t: Ji.monomial(j_t[1])
+                                  if i == j_t[0] else Ji.zero(),
+                                  codomain=Ji)
         return FiniteDimensionalEJAOperator(self,Ji,Pi.matrix())
 
     @cached_method
@@ -2839,10 +2879,14 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
         SETUP::
 
             sage: from mjo.eja.eja_algebra import (random_eja,
+            ....:                                  JordanSpinEJA,
             ....:                                  HadamardEJA,
             ....:                                  RealSymmetricEJA)
 
-        EXAMPLES::
+        EXAMPLES:
+
+        The embedding morphisms are Euclidean Jordan algebra
+        operators::
 
             sage: J1 = HadamardEJA(2)
             sage: J2 = RealSymmetricEJA(2)
@@ -2874,6 +2918,29 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
             Algebraic Real Field (+) Euclidean Jordan algebra of
             dimension 3 over Algebraic Real Field
 
+        The embeddings work the way you'd expect on the vector
+        representation of an element::
+
+            sage: J1 = JordanSpinEJA(3)
+            sage: J2 = RealSymmetricEJA(2)
+            sage: J = cartesian_product([J1,J2])
+            sage: iota_left = J.cartesian_embedding(0)
+            sage: iota_right = J.cartesian_embedding(1)
+            sage: iota_left(J1.zero()) == J.zero()
+            True
+            sage: iota_right(J2.zero()) == J.zero()
+            True
+            sage: J1.one().to_vector()
+            (1, 0, 0)
+            sage: iota_left(J1.one()).to_vector()
+            (1, 0, 0, 0, 0, 0)
+            sage: J2.one().to_vector()
+            (1, 0, 1)
+            sage: iota_right(J2.one()).to_vector()
+            (0, 0, 0, 1, 0, 1)
+            sage: J.one().to_vector()
+            (1, 0, 0, 1, 0, 1)
+
         TESTS:
 
         The answer never changes::
@@ -2887,12 +2954,32 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
             sage: E0 == E1
             True
 
+        Composing a projection with the corresponding inclusion should
+        produce the identity map, and mismatching them should produce
+        the zero map::
+
+            sage: set_random_seed()
+            sage: J1 = random_eja()
+            sage: J2 = random_eja()
+            sage: J = cartesian_product([J1,J2])
+            sage: iota_left = J.cartesian_embedding(0)
+            sage: iota_right = J.cartesian_embedding(1)
+            sage: pi_left = J.cartesian_projection(0)
+            sage: pi_right = J.cartesian_projection(1)
+            sage: pi_left*iota_left == J1.one().operator()
+            True
+            sage: pi_right*iota_right == J2.one().operator()
+            True
+            sage: (pi_left*iota_right).is_zero()
+            True
+            sage: (pi_right*iota_left).is_zero()
+            True
+
         """
         Ji = self.cartesian_factors()[i]
-        # We reimplement the CombinatorialFreeModule superclass method
-        # because if we don't, something gets messed up with the caching
-        # and the answer changes the second time you run it. See the TESTS.
-        Ei = Ji._module_morphism(lambda t: self.monomial((i, t)), codomain=self)
+        # Required until https://trac.sagemath.org/ticket/31421 is fixed.
+        Ei = Ji.module_morphism(lambda t: self.monomial((i, t)),
+                                codomain=self)
         return FiniteDimensionalEJAOperator(Ji,self,Ei.matrix())
 
 
@@ -2972,114 +3059,8 @@ class CartesianProductEJA(CombinatorialFreeModule_CartesianProduct,
         return sum( P(x).inner_product(P(y)) for P in projections )
 
 
-FiniteDimensionalEJA.CartesianProduct = CartesianProductEJA
-
-
-#     def projections(self):
-#         r"""
-#         Return a pair of projections onto this algebra's factors.
-
-#         SETUP::
-
-#             sage: from mjo.eja.eja_algebra import (JordanSpinEJA,
-#             ....:                                  ComplexHermitianEJA,
-#             ....:                                  DirectSumEJA)
-
-#         EXAMPLES::
-
-#             sage: J1 = JordanSpinEJA(2)
-#             sage: J2 = ComplexHermitianEJA(2)
-#             sage: J = DirectSumEJA(J1,J2)
-#             sage: (pi_left, pi_right) = J.projections()
-#             sage: J.one().to_vector()
-#             (1, 0, 1, 0, 0, 1)
-#             sage: pi_left(J.one()).to_vector()
-#             (1, 0)
-#             sage: pi_right(J.one()).to_vector()
-#             (1, 0, 0, 1)
-
-#         """
-#         (J1,J2) = self.factors()
-#         m = J1.dimension()
-#         n = J2.dimension()
-#         V_basis = self.vector_space().basis()
-#         # Need to specify the dimensions explicitly so that we don't
-#         # wind up with a zero-by-zero matrix when we want e.g. a
-#         # zero-by-two matrix (important for composing things).
-#         P1 = matrix(self.base_ring(), m, m+n, V_basis[:m])
-#         P2 = matrix(self.base_ring(), n, m+n, V_basis[m:])
-#         pi_left = FiniteDimensionalEJAOperator(self,J1,P1)
-#         pi_right = FiniteDimensionalEJAOperator(self,J2,P2)
-#         return (pi_left, pi_right)
-
-#     def inclusions(self):
-#         r"""
-#         Return the pair of inclusion maps from our factors into us.
-
-#         SETUP::
-
-#             sage: from mjo.eja.eja_algebra import (random_eja,
-#             ....:                                  JordanSpinEJA,
-#             ....:                                  RealSymmetricEJA,
-#             ....:                                  DirectSumEJA)
-
-#         EXAMPLES::
-
-#             sage: J1 = JordanSpinEJA(3)
-#             sage: J2 = RealSymmetricEJA(2)
-#             sage: J = DirectSumEJA(J1,J2)
-#             sage: (iota_left, iota_right) = J.inclusions()
-#             sage: iota_left(J1.zero()) == J.zero()
-#             True
-#             sage: iota_right(J2.zero()) == J.zero()
-#             True
-#             sage: J1.one().to_vector()
-#             (1, 0, 0)
-#             sage: iota_left(J1.one()).to_vector()
-#             (1, 0, 0, 0, 0, 0)
-#             sage: J2.one().to_vector()
-#             (1, 0, 1)
-#             sage: iota_right(J2.one()).to_vector()
-#             (0, 0, 0, 1, 0, 1)
-#             sage: J.one().to_vector()
-#             (1, 0, 0, 1, 0, 1)
-
-#         TESTS:
-
-#         Composing a projection with the corresponding inclusion should
-#         produce the identity map, and mismatching them should produce
-#         the zero map::
-
-#             sage: set_random_seed()
-#             sage: J1 = random_eja()
-#             sage: J2 = random_eja()
-#             sage: J = DirectSumEJA(J1,J2)
-#             sage: (iota_left, iota_right) = J.inclusions()
-#             sage: (pi_left, pi_right) = J.projections()
-#             sage: pi_left*iota_left == J1.one().operator()
-#             True
-#             sage: pi_right*iota_right == J2.one().operator()
-#             True
-#             sage: (pi_left*iota_right).is_zero()
-#             True
-#             sage: (pi_right*iota_left).is_zero()
-#             True
-
-#         """
-#         (J1,J2) = self.factors()
-#         m = J1.dimension()
-#         n = J2.dimension()
-#         V_basis = self.vector_space().basis()
-#         # Need to specify the dimensions explicitly so that we don't
-#         # wind up with a zero-by-zero matrix when we want e.g. a
-#         # two-by-zero matrix (important for composing things).
-#         I1 = matrix.column(self.base_ring(), m, m+n, V_basis[:m])
-#         I2 = matrix.column(self.base_ring(), n, m+n, V_basis[m:])
-#         iota_left = FiniteDimensionalEJAOperator(J1,self,I1)
-#         iota_right = FiniteDimensionalEJAOperator(J2,self,I2)
-#         return (iota_left, iota_right)
-
-
+    Element = FiniteDimensionalEJAElement
 
 
+FiniteDimensionalEJA.CartesianProduct = CartesianProductEJA
 random_eja = ConcreteEJA.random_instance