X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=mjo%2Feja%2Feja_utils.py;h=8f2d8f32b0dd2e2cf6e693166688d6be1f3ea999;hb=f72c84ce3d46f2611a65417c72e9017754ec156f;hp=b6b0a0327c19842ce654023b00bf6e0b9af539a1;hpb=a0fea53fa276670d9a4c6a44ae9023df58592b88;p=sage.d.git diff --git a/mjo/eja/eja_utils.py b/mjo/eja/eja_utils.py index b6b0a03..8f2d8f3 100644 --- a/mjo/eja/eja_utils.py +++ b/mjo/eja/eja_utils.py @@ -1,4 +1,95 @@ from sage.modules.free_module_element import vector +from sage.rings.number_field.number_field import NumberField +from sage.rings.polynomial.polynomial_ring_constructor import PolynomialRing +from sage.rings.real_lazy import RLF def _mat2vec(m): return vector(m.base_ring(), m.list()) + +def gram_schmidt(v): + """ + Perform Gram-Schmidt on the list ``v`` which are assumed to be + vectors over the same base ring. Returns a list of orthonormalized + vectors over the smallest extention ring containing the necessary + roots. + + SETUP:: + + sage: from mjo.eja.eja_utils import gram_schmidt + + EXAMPLES:: + + sage: v1 = vector(QQ,(1,2,3)) + sage: v2 = vector(QQ,(1,-1,6)) + sage: v3 = vector(QQ,(2,1,-1)) + sage: v = [v1,v2,v3] + sage: u = gram_schmidt(v) + sage: [ u_i.inner_product(u_i).sqrt() == 1 for u_i in u ] + True + sage: u[0].inner_product(u[1]) == 0 + True + sage: u[0].inner_product(u[2]) == 0 + True + sage: u[1].inner_product(u[2]) == 0 + True + + TESTS: + + Ensure that zero vectors don't get in the way:: + + sage: v1 = vector(QQ,(1,2,3)) + sage: v2 = vector(QQ,(1,-1,6)) + sage: v3 = vector(QQ,(0,0,0)) + sage: v = [v1,v2,v3] + sage: len(gram_schmidt(v)) == 2 + True + + """ + def proj(x,y): + return (y.inner_product(x)/x.inner_product(x))*x + + v = list(v) # make a copy, don't clobber the input + + # Drop all zero vectors before we start. + v = [ v_i for v_i in v if not v_i.is_zero() ] + + if len(v) == 0: + # cool + return v + + R = v[0].base_ring() + + # First orthogonalize... + for i in xrange(1,len(v)): + # Earlier vectors can be made into zero so we have to ignore them. + v[i] -= sum( proj(v[j],v[i]) for j in range(i) if not v[j].is_zero() ) + + # And now drop all zero vectors again if they were "orthogonalized out." + v = [ v_i for v_i in v if not v_i.is_zero() ] + + # Now pretend to normalize, building a new ring R that contains + # all of the necessary square roots. + norms_squared = [0]*len(v) + + for i in xrange(len(v)): + norms_squared[i] = v[i].inner_product(v[i]) + ns = [norms_squared[i].numerator(), norms_squared[i].denominator()] + + # Do the numerator and denominator separately so that we + # adjoin e.g. sqrt(2) and sqrt(3) instead of sqrt(2/3). + for j in xrange(len(ns)): + PR = PolynomialRing(R, 'z') + z = PR.gen() + p = z**2 - ns[j] + if p.is_irreducible(): + R = NumberField(p, + 'sqrt' + str(ns[j]), + embedding=RLF(ns[j]).sqrt()) + + # When we're done, we have to change every element's ring to the + # extension that we wound up with, and then normalize it (which + # should work, since "R" contains its norm now). + for i in xrange(len(v)): + v[i] = v[i].change_ring(R) / R(norms_squared[i]).sqrt() + + return v