"""
P = self.parent()
r = P.rank()
- p = P._charpoly_coeff(0)
- # The _charpoly_coeff function already adds the factor of
- # -1 to ensure that _charpoly_coeff(0) is really what
- # appears in front of t^{0} in the charpoly. However,
- # we want (-1)^r times THAT for the determinant.
+ p = P._charpoly_coefficients()[0]
+ # The _charpoly_coeff function already adds the factor of -1
+ # to ensure that _charpoly_coefficients()[0] is really what
+ # appears in front of t^{0} in the charpoly. However, we want
+ # (-1)^r times THAT for the determinant.
return ((-1)**r)*p(*self.to_vector())
sage: l0*c0 + l1*c1 == x
True
+ The spectral decomposition should work in subalgebras, too::
+
+ sage: J = RealSymmetricEJA(4)
+ sage: (e0, e1, e2, e3, e4, e5, e6, e7, e8, e9) = J.gens()
+ sage: A = 2*e5 - 2*e8
+ sage: (lambda1, c1) = A.spectral_decomposition()[1]
+ sage: (J0, J5, J1) = J.peirce_decomposition(c1)
+ sage: (f0, f1, f2) = J1.gens()
+ sage: f0.spectral_decomposition()
+ [(0, 1.000000000000000?*f2), (1, 1.000000000000000?*f0)]
+
"""
- P = self.parent()
A = self.subalgebra_generated_by(orthonormalize_basis=True)
result = []
for (evalue, proj) in A(self).operator().spectral_decomposition():
# the trace is an empty sum.
return P.base_ring().zero()
- p = P._charpoly_coeff(r-1)
+ p = P._charpoly_coefficients()[r-1]
# The _charpoly_coeff function already adds the factor of
# -1 to ensure that _charpoly_coeff(r-1) is really what
# appears in front of t^{r-1} in the charpoly. However,