X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_element.py;h=a832185502c7fafb16879ab3a08084499d3582ab;hb=d00138c6bd4e7082c0ac0c92528a1692226232ac;hp=2c425ca320a5c04e6defee044bd0deb01e76dda4;hpb=99952b3ef2ad157d820f1dbd946d329987383464;p=sage.d.git diff --git a/mjo/eja/eja_element.py b/mjo/eja/eja_element.py index 2c425ca..a832185 100644 --- a/mjo/eja/eja_element.py +++ b/mjo/eja/eja_element.py @@ -375,7 +375,8 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): Ensure that the determinant is multiplicative on an associative subalgebra as in Faraut and Korányi's Proposition II.2.2:: - sage: J = random_eja().random_element().subalgebra_generated_by() + sage: x0 = random_eja().random_element() + sage: J = x0.subalgebra_generated_by(orthonormalize=False) sage: x,y = J.random_elements(2) sage: (x*y).det() == x.det()*y.det() True @@ -484,10 +485,12 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): of an element is the inverse of its left-multiplication operator applied to the algebra's identity, when that inverse exists:: - sage: J = random_eja() - sage: x = J.random_element() - sage: (not x.operator().is_invertible()) or ( - ....: x.operator().inverse()(J.one()) == x.inverse() ) + sage: J = random_eja() # long time + sage: x = J.random_element() # long time + sage: (not x.operator().is_invertible()) or ( # long time + ....: x.operator().inverse()(J.one()) # long time + ....: == # long time + ....: x.inverse() ) # long time True Check that the fast (cached) and slow algorithms give the same @@ -504,15 +507,18 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): True """ not_invertible_msg = "element is not invertible" - if self.parent()._charpoly_coefficients.is_in_cache(): + + algebra = self.parent() + if algebra._charpoly_coefficients.is_in_cache(): # We can invert using our charpoly if it will be fast to # compute. If the coefficients are cached, our rank had # better be too! if self.det().is_zero(): raise ZeroDivisionError(not_invertible_msg) - r = self.parent().rank() + r = algebra.rank() a = self.characteristic_polynomial().coefficients(sparse=False) - return (-1)**(r+1)*sum(a[i+1]*self**i for i in range(r))/self.det() + return (-1)**(r+1)*algebra.sum(a[i+1]*self**i + for i in range(r))/self.det() try: inv = (~self.quadratic_representation())(self) @@ -976,9 +982,9 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): The minimal polynomial should always kill its element:: - sage: x = random_eja().random_element() - sage: p = x.minimal_polynomial() - sage: x.apply_univariate_polynomial(p) + sage: x = random_eja().random_element() # long time + sage: p = x.minimal_polynomial() # long time + sage: x.apply_univariate_polynomial(p) # long time 0 The minimal polynomial is invariant under a change of basis, @@ -1371,7 +1377,7 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): This subalgebra, being composed of only powers, is associative:: sage: x0 = random_eja().random_element() - sage: A = x0.subalgebra_generated_by() + sage: A = x0.subalgebra_generated_by(orthonormalize=False) sage: x,y,z = A.random_elements(3) sage: (x*y)*z == x*(y*z) True @@ -1380,7 +1386,7 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): the superalgebra:: sage: x = random_eja().random_element() - sage: A = x.subalgebra_generated_by() + sage: A = x.subalgebra_generated_by(orthonormalize=False) sage: A(x^2) == A(x)*A(x) True @@ -1419,7 +1425,7 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): where there are non-nilpotent elements, or that we get the dumb solution in the trivial algebra:: - sage: J = random_eja() + sage: J = random_eja(field=QQ, orthonormalize=False) sage: x = J.random_element() sage: while x.is_nilpotent() and not J.is_trivial(): ....: x = J.random_element() @@ -1555,7 +1561,7 @@ class FiniteDimensionalEJAElement(IndexedFreeModuleElement): sage: x.trace_inner_product(y) == y.trace_inner_product(x) True sage: # bilinear - sage: a = J.base_ring().random_element(); + sage: a = J.base_ring().random_element() sage: actual = (a*(x+z)).trace_inner_product(y) sage: expected = ( a*x.trace_inner_product(y) + ....: a*z.trace_inner_product(y) )