kcrisman wrote: > Dear support, > > sage: M = matrix(RDF,[[1.,2.],[3.,4.]]) > sage: M.LU() > > ([0.0 1.0] > [1.0 0.0], > [ 1.0 0.0] > [0.333333333333 1.0], > [ 3.0 4.0] > [ 0.0 0.666666666667]) > sage: N = matrix([[1.,2.],[3.,4.]]) # N.L[tab] does nothing > sage: O = matrix([[1,2],[3,4]]) # O.L[tab] only gives lattice stuff > > Is there a mathematical reason LU decomposition isn't available for > these, or was it simply never implemented? It seems it is only > available for > sage.matrix.matrix_real_double_dense.Matrix_real_double_dense, not for > sage.matrix.matrix_generic_dense.Matrix_generic_dense (floats, RR).
RDF LU calls scipy. Here is a trac ticket with a patch for a generic LU decomposition: http://trac.sagemath.org/sage_trac/ticket/3048 > > And would it be mathematically correct to place that code in place if > all entries could be RDFed, or not? Any equivalent for symbolic > matrices (even if slow)? > > (On a related note, > > sage: O = matrix([[1,2],[3,4]]) > sage: O.echelon_form() > > [1 0] > [0 2] > > so apparently we have yet to implement the (agreed on sage-devel?) > decision that echelon_form should be over the most sensible quotient > field...) > Not yet. I have a partial patch waiting for me to get back to it. Jason -- Jason Grout -- To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/sage-support URL: http://www.sagemath.org
