Check for DimNames propagation in coercion and other operations.
------
- rcond methods for sparseMatrix classes

- Report the problem in the Linux ldexp manual page.  The second and
  third calls in the Synopsis should be to ldexpf and ldexpl.

- [,] indexing: for sparse "works", but not yet for negative indices!

- consider moving alloc3Darray from ./src/Mutils.c to
  $(RSRC)/src/base/array.c
------
- provide methods for "dspMatrix" and "dppMatrix"!

- implement (more) methods for supporting "packed" (symmetric / triangular)
  matrices; particularly something like pack() and unpack()  [to/from our
  classes from/to "numeric"] --- have already man/unpack.Rd but no method yet!

  (have some dtr* <-> dtp*)

-----

- combine the C functions for multiplication by special forms and
  solution wrt special forms by using a 'right' argument and a
  'classed' argument.
   [done with dgeMatrix_matrix_mm();  not yet for other classes;
    and for _crossprod()]

- add more comprehensive examples / tests for Schur decomposition

- arithmetic for sparse matrices:
	     <sparseMatrix>  o  <same-dim-sparseMatrix>
  should return a sparse matrix  for at least "+" and "*" , also %%,
  and "/" and "%/%" at least when the RHS is non-zero a scalar.
  Challenge: nice implementation (``common non-0''; but Tsparse* is not uniq).

-----

- "Math2" , "Math", "Arith":
   keep triangular and symmetric Matrices when appropriate:
   particularly desirable for  "Math2": round(), signif()

- "d" <-> "l" coercion for all "[TCR]" sparse matrices is really trivial:
  "d" -> "l" : drops the 'x' slot
  "l" -> "d" : construct an 'x' slot of all '1'
  We currently have many of these conversions explicitly, e.g.
   setAs("dsTMatrix", "lsTMatrix",
      function(from) new("lsTMatrix", i = from@i, j = from@j, uplo = from@uplo,
                         Dim = from@Dim, Dimnames = from@Dimnames))
  but I would rather want to automatically construct all these coercion
  methods at once by a ``method constructor'', i.e.,
  for all  "dsparse*" -> "lsparse*" and vice versa.
  How can one do this {in a documented way} ?

- tcrossprod(x, y) : do provide methods for y != NULL
  calling Lapack's DGEMM for "dense"
  [2005-12-xx: done for dgeMatrix at least]

- BUGlet:  Shouldn't lose factorization here:
  h6 <- Hilbert(6); chol(h6) ; str(h6) # has factor
  str(H6 <- as(h6, "dspMatrix"))       # has lost factor
  ## and the same in a similar situation involving  "dpo", "dpp"

- Things like  M[upper.tri(M)] are not really most useful for  sparse
  matrices.  --> provide generic functions
  upperTriMatrix(), lowerTriMatrix()  both with argument  'diag = TRUE'
  (which can be set to FALSE of course) which are used to extract a
  triangle from an arbitrary sparse matrix and  return a  "dtCMatrix".

- Factorizations: LU done; also Schur()  for  *sparse*  Matrices.

- band(), triu(), tril() for *all* including "matrix", not just sparse matrices

- is.na() method for all our matrices [ ==> which(*, arr.ind=TRUE) might work ]

- When we have a packed matrix, it's a waste to go through "full" to "sparse":
  ==> implement
	setAs("dspMatrix", "sparseMatrix")
	setAs("dppMatrix", "sparseMatrix")
	setAs("dtpMatrix", "sparseMatrix")
  and the same for "lsp" , "ltp"  and  "nsp" , "ntp" !

- use  .Call(Csparse_drop, M, tol) in more places,
  both with 'tol = 0.' to drop "values that happen to be 0" and for
  zapsmall() methods for Csparse*

- implement .Call(Csparse_scale, ....) interfacing to cholmod_scale()
  in src/CHOLMOD/Include/cholmod_matrixops.h : for another function
  specifically for multiplying a cholmod_sparse object by a diagonal matrix.
  Use it in %*% and [t]crossprod methods.

- chol() and determinant() should ``work'': proper result or "good" error
  message.

- Think of constructing  setAs(...) calls automatically in order to
  basically enable all ``sensible'' as(fromMatrix, toMatrix)  calls,
  possibly using canCoerce(.)

- make sure *all* group methods have (maybe "bail-out") setMethod for "Matrix".
  e.g. zapsmall(<pMatrix>) fails "badly"

- speedup: pass class definition to non0ind() [check all calls ..]

- sum(): implement methods which work for *all* our matrices.

- Implement  expand(.) for the Cholesky() results
  "dCHMsimpl" and  "dCHMsuper"  -- currently have no *decent* way to get at
  the matrix factors of the corresponding matrix factorization !!

- rbind(<sparse>, <dense>) does not work  (e.g. <dgC>, <dge>)