--- pkg/TODO 2005/02/04 23:36:17 510
+++ pkg/TODO 2008/03/17 22:21:24 2137
@@ -1,35 +1,184 @@
+- Check for DimNames propagation in coercion and other operations.
+
- Report the problem in the Linux ldexp manual page. The second and
third calls in the Synopsis should be to ldexpf and ldexpl.
-- [,] indexing
+- 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()]
+
+-----
+
+- "Math2" , "Math", "Arith":
+ keep triangular and symmetric Matrices when appropriate:
+ particularly desirable for "Math2": round(), signif()
+
+ For triangular matrices, more specifically make sure the four rules of
+ "triangular matrix algebra" (Golub+Van Loan 1996, 3.1.8, p.93) are
+ fulfilled; now(2008-03-06) ok for Csparse; not yet for %*%
+
+- "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} ?
+
+- Think of constructing setAs(...) calls automatically in order to
+ basically enable all ``sensible'' as(fromMatrix, toMatrix) calls,
+ possibly using canCoerce(.)
+
+- setAs(, "[dln]Matrix") for in {Matrix or denseMatrix + sparseMatrix}
+
+- 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" !
+
+- 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"
+
+- Factorizations: LU done; also Schur() for *sparse* Matrices.
+
+- is.na() method for all our matrices [ ==> which(*, arr.ind=TRUE) might work ]
+
+- 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.
+
+- make sure *all* group methods have (maybe "bail-out") setMethod for "Matrix".
+ e.g. zapsmall() fails "badly"
+
+- 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 !!
+
+- rbind2(, ) does not work (e.g. , )
+
+- %*% {also in crossprod/tcrossprod} currently always
+ returns , since --> Csparse_dense_prod --> cholmod_sdmult
+ and that does only return dense.
+ When the sparse matrix is very sparse, i.e. has many rows with only zero
+ entries, it would make much sense to return sparse.
+
+- sparse-symmetric + diagonal should stay sparse-symmetric
+ (only stays sparse): Matrix(0, 4, 4) + Diagonal(4, 1:4)
+ --> R/diagMatrix.R ('FIXME')
+ but also R/Ops.R to ensure sp-sym. + sp-sym. |-> sp-sym. etc
+
+- Diagonal(n) %*% A --- too slow!! --> ~/R/MM/Pkg-ex/Matrix/diag-Tamas-ex.R
+
+- ! loses symmetry, both for dense and sparse matrices.
+ !M where M is "sparseMatrix", currently always gives dense. This only
+ makes sense when M is ``really sparse''.
+
+- msy <- as(matrix(c(2:1,1:2),2), "dsyMatrix"); str(msy)
+
+ shows that the Cholesky factorization is computed ``too quickly''.
+ Can be a big pain for largish matrices, when it is unneeded.
+
+- example(Cholesky, echo=FALSE) ; cm <- chol(mtm); str(cm); str(mtm)
+
+ shows that chol() does not seems to make use of an already
+ present factorization and rather uses one with more '0' in x slot.
+
+- diag(m) <- val currently automatically works via m[cbind(i,i)] <- val
+ This (`[<-` method) is now "smart" for diagonalMatrix, but needs also to
+ be for triangularMatrix, and probably also "dense*general*Matrix" since the
+ above currently goes via "matrix" and back instead of using the 'x' slot
+ directly; in particular, the triangular* "class property" is lost!
+
+- image(M, ..): Think about an optional smart option which keeps
+ "0 |-> transparent" and allows colors to differentiate negative and
+ positive entries.
+
+- examples for solve( Cholesky(.), b, system = c("A", "LDLt"....))
+ probably rather in man/CHMfactor-class.Rd than man/Cholesky.Rd
+
+- LDL() looks relatively easy; via "tCsparse_diag()"
+ {diagonal entries of *triangular* Csparse}
+ --> see comment in determinant() in R/dsCMatrix.R, will give
+ faster determinant
+
+- Cholesky() generalized: provide R interface cholmod_factorize_p()
+ which factorizes |A + beta*I| ==> R interface to fast det|A + b*I|
+
+- tr(A %*% B) {and even tr(A %*% B %*% C) ...} are also needed
+ frequently in some computations {conditional normal distr. ...}.
+ Since this can be done faster than by
+ sum(diag(A %*% B)) even for traditional matrices, e.g.
+ sum(A * t(B)) or {even faster for "full" mat}
+ crossprod(as.vector(A), as.vector(B))
+ and even more so for, e.g. %*%
+ {used in Soeren's 'gR' computations},
+ we should also provide a generic and methods.
+
+- qr.R(qr(x)) may differ for the "same" matrix, depending on it being
+ sparse or dense:
+ "qr.R() may differ from qr.R() because of permutations"
-- group generics: "Arith", but also "Ops" and "Math"; see
- ?Math.data.frame and the examples in
- ?SetGeneric
+ This is not really acceptable and currently influences rcond() as well.
-- check to see if the .onLoad function to require the methods package
- (in the AllClass.R file) is needed
+- chol() and qr() generic: currently have *two* arguments, and give the msg
-- Should the uplo and diag slots continue to be stored as character?
- An alternative is to use a factor as in the enum values for the
- cblas.
+ > New generic for "chol" does not agree with implicit generic from package
+ > "base"; a new generic will be assigned with package "Matrix"
-- Organization of the source code files - right now they are organized
- according to class (e.g. dgeMatrix.R, dgeMatrix.h, dgeMatrix.c). Is
- there a better way?
+ (and ditto for "qr")
-- Fix the calculation of the Dim slot for the crossprod method for
- dgCMatrix objects (too tired to do that now).
+ It was mentioned by an R-core member that he thought it did not make
+ sense to also dispatch on 'tol' or 'pivot' ... --> maybe change that..
-- bCrosstab(): do we really want the diagonal "V:V" crosstabs?
+- eigen() should become generic, and get a method at least for diagonal,
+ but also for symmetric -> dsyMatrix [LAPACK dsyev() uses UPLO !],
+ but also simply for dgeMatrix (without going via tradition matrices).
+ What about Sparse? There's fill-in, but it may still be sensible, e.g.
+ mlist <- list(1, 2:3, diag(x=5:3), 27, cbind(1,3:6), 100:101)
+ ee <- eigen(tcrossprod(bdiag(lapply(mlist, as.matrix))))
+ Matrix( signif(ee$vectors, 3) )
-- src/Metis/ : some Makefile needs fixing, as changing src/Metis/*.c
- does not lead to recompilation.
+- facmul() has no single method defined; it looks like a good idea though
+ (instead of the infamous qr.qy, qr.qty,.... functions)
-- man/Matrix.Rd : has example with dimnames, but we just drop them!
- MM thinks dimnames should be supported (but then ...)
+- symmpart() and skewpart() for *sparse* matrices still use (x +/- t(x))/2
+ and could be made more efficient.
+ Consider going via asTuniq() or something very close to
+ .Arith.Csparse() in R/Ops.R
-- data/ : names 'mm' and even more 'y' are ``too short''.
- If we really want to keep them, don't use "LazyData"
- (such that one needs data(*) explicitly);
- But MM would rather want something like ex.mm and ex.y
+- many setAs(*, "[dl]..Matrix") are still needed, as long as e.g.
+ replCmat() uses as_CspClass() and drop0(.) which itself call
+ as_CspClass() quite a bit. --> try to replace these by
+ as(*, "CsparseMatrix"); forceSymmetric, etc.