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revision 510, Fri Feb 4 23:36:17 2005 UTC revision 2115, Sat Feb 23 09:23:17 2008 UTC
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1    - Check for DimNames propagation in coercion and other operations.
2    
3  - Report the problem in the Linux ldexp manual page.  The second and  - Report the problem in the Linux ldexp manual page.  The second and
4    third calls in the Synopsis should be to ldexpf and ldexpl.    third calls in the Synopsis should be to ldexpf and ldexpl.
5    
6  - [,] indexing  - provide methods for "dspMatrix" and "dppMatrix"!
7    
8    - implement (more) methods for supporting "packed" (symmetric / triangular)
9      matrices; particularly something like pack() and unpack()  [to/from our
10      classes from/to "numeric"] --- have already man/unpack.Rd but no method yet!
11    
12      (have some dtr* <-> dtp*)
13    
14    - combine the C functions for multiplication by special forms and
15      solution wrt special forms by using a 'right' argument and a
16      'classed' argument.
17       [done with dgeMatrix_matrix_mm();  not yet for other classes;
18        and for _crossprod()]
19    
20    -----
21    
22    - "Math2" , "Math", "Arith":
23       keep triangular and symmetric Matrices when appropriate:
24       particularly desirable for  "Math2": round(), signif()
25    
26    - "d" <-> "l" coercion for all "[TCR]" sparse matrices is really trivial:
27      "d" -> "l" : drops the 'x' slot
28      "l" -> "d" : construct an 'x' slot of all '1'
29      We currently have many of these conversions explicitly, e.g.
30       setAs("dsTMatrix", "lsTMatrix",
31          function(from) new("lsTMatrix", i = from@i, j = from@j, uplo = from@uplo,
32                             Dim = from@Dim, Dimnames = from@Dimnames))
33      but I would rather want to automatically construct all these coercion
34      methods at once by a ``method constructor'', i.e.,
35      for all  "dsparse*" -> "lsparse*" and vice versa.
36      How can one do this {in a documented way} ?
37    
38    - Think of constructing  setAs(...) calls automatically in order to
39      basically enable all ``sensible'' as(fromMatrix, toMatrix)  calls,
40      possibly using canCoerce(.)
41    
42    - setAs(<Mcl>,  "[dln]Matrix") for <Mcl> in {Matrix or denseMatrix + sparseMatrix}
43    
44    - When we have a packed matrix, it's a waste to go through "full" to "sparse":
45      ==> implement
46            setAs("dspMatrix", "sparseMatrix")
47            setAs("dppMatrix", "sparseMatrix")
48            setAs("dtpMatrix", "sparseMatrix")
49      and the same for "lsp" , "ltp"  and  "nsp" , "ntp" !
50    
51    - tcrossprod(x, y) : do provide methods for y != NULL
52      calling Lapack's DGEMM for "dense"
53      [2005-12-xx: done for dgeMatrix at least]
54    
55    - BUGlet:  Shouldn't lose factorization here:
56      h6 <- Hilbert(6); chol(h6) ; str(h6) # has factor
57      str(H6 <- as(h6, "dspMatrix"))       # has lost factor
58      ## and the same in a similar situation involving  "dpo", "dpp"
59    
60    - Factorizations: LU done; also Schur()  for  *sparse*  Matrices.
61    
62    - is.na() method for all our matrices [ ==> which(*, arr.ind=TRUE) might work ]
63    
64    - use  .Call(Csparse_drop, M, tol) in more places,
65      both with 'tol = 0.' to drop "values that happen to be 0" and for
66      zapsmall() methods for Csparse*
67    
68    - implement .Call(Csparse_scale, ....) interfacing to cholmod_scale()
69      in src/CHOLMOD/Include/cholmod_matrixops.h : for another function
70      specifically for multiplying a cholmod_sparse object by a diagonal matrix.
71      Use it in %*% and [t]crossprod methods.
72    
73    - chol() and determinant() should ``work'': proper result or "good" error
74      message.
75    
76    - make sure *all* group methods have (maybe "bail-out") setMethod for "Matrix".
77      e.g. zapsmall(<pMatrix>) fails "badly"
78    
79    - sum(): implement methods which work for *all* our matrices.
80    
81    - Implement  expand(.) for the Cholesky() results
82      "dCHMsimpl" and  "dCHMsuper"  -- currently have no *decent* way to get at
83      the matrix factors of the corresponding matrix factorization !!
84    
85    - rbind2(<sparse>, <dense>) does not work  (e.g. <dgC>, <dge>)
86    
87    - <sparse> %*% <dense>  {also in crossprod/tcrossprod}  currently always
88      returns <dense>, since --> Csparse_dense_prod --> cholmod_sdmult
89      and that does only return dense.
90      When the sparse matrix is very sparse, i.e. has many rows with only zero
91      entries, it would make much sense to return sparse.
92    
93    - sparse-symmetric + diagonal should stay sparse-symmetric
94      (only stays sparse): Matrix(0, 4, 4) + Diagonal(4, 1:4)
95      --> R/diagMatrix.R ('FIXME')
96      but also R/Ops.R  to ensure  sp-sym. + sp-sym. |-> sp-sym.  etc
97    
98    - Diagonal(n) %*% A ---  too slow!! --> ~/R/MM/Pkg-ex/Matrix/diag-Tamas-ex.R
99    
100    - ! <symmetricMatrix>  loses symmetry, both for dense and sparse matrices.
101      !M  where M is "sparseMatrix", currently always gives dense. This only
102      makes sense when M is ``really sparse''.
103    
104    - msy <- as(matrix(c(2:1,1:2),2), "dsyMatrix"); str(msy)
105    
106      shows that the Cholesky factorization is computed ``too quickly''.
107      Can be a big pain for largish matrices, when it is unneeded.
108    
109    - example(Cholesky, echo=FALSE) ; cm <- chol(mtm); str(cm); str(mtm)
110    
111      shows that chol() does not seems to make use of an already
112      present factorization and rather uses one with more '0' in x slot.
113    
114    - diag(m) <- val    currently automatically works via  m[cbind(i,i)] <- val
115      This (`[<-` method) is now "smart" for diagonalMatrix, but needs also to
116      be for triangularMatrix, and probably also "dense*general*Matrix" since the
117      above currently goes via "matrix" and back instead of using the 'x' slot
118      directly; in particular, the triangular* "class property" is lost!
119    
120    - image(M, ..): Think about an optional smart option which keeps
121       "0 |-> transparent" and allows colors to differentiate negative and
122       positive entries.
123    
124    - examples for solve( Cholesky(.), b, system = c("A", "LDLt"....))
125      probably rather in man/CHMfactor-class.Rd than man/Cholesky.Rd
126    
127    - tr(A %*% B) {and even  tr(A %*% B %*% C) ...} are also needed
128      frequently in some computations {conditional normal distr. ...}.
129      Since this can be done faster than by
130        sum(diag(A %*% B))  even for traditional matrices, e.g.
131                   sum(A * t(B)) or {even faster for "full" mat}
132                   crossprod(as.vector(A), as.vector(B))
133      and even more so for, e.g.  <sparse> %*% <dense>
134      {used in Soeren's 'gR' computations},
135      we should also provide a generic and methods.
136    
137    - qr.R(qr(x)) may differ for the "same" matrix, depending on it being
138      sparse or dense:
139        "qr.R(<sparse>) may differ from qr.R(<dense>) because of permutations"
140    
141  - group generics: "Arith", but also "Ops" and "Math";  see    This is not really acceptable and currently influences  rcond() as well.
   ?Math.data.frame  and the examples in  
   ?SetGeneric  
142    
143  - check to see if the .onLoad function to require the methods package  - chol() and qr() generic:  currently have *two* arguments, and give the msg
   (in the AllClass.R file) is needed  
144    
145  - Should the uplo and diag slots continue to be stored as character?    >  New generic for "chol" does not agree with implicit generic from package
146    An alternative is to use a factor as in the enum values for the    >  "base"; a new generic will be assigned with package "Matrix"
   cblas.  
147    
148  - Organization of the source code files - right now they are organized    (and ditto for "qr")
   according to class (e.g. dgeMatrix.R, dgeMatrix.h, dgeMatrix.c).  Is  
   there a better way?  
149    
150  - Fix the calculation of the Dim slot for the crossprod method for    It was mentioned by an R-core member that he thought it did not make
151    dgCMatrix objects (too tired to do that now).    sense to also dispatch on 'tol' or 'pivot' ...  --> maybe change that..
152    
153  - bCrosstab(): do we really want the diagonal "V:V" crosstabs?  - eigen() should become generic, and get a method at least for diagonal,
154      but also for symmetric -> dsyMatrix  [LAPACK dsyev() uses UPLO !],
155      but also simply for dgeMatrix (without going via tradition matrices).
156      What about Sparse?  There's fill-in, but it may still be sensible, e.g.
157      mlist <- list(1, 2:3, diag(x=5:3), 27, cbind(1,3:6), 100:101)
158      ee <- eigen(tcrossprod(bdiag(lapply(mlist, as.matrix))))
159      Matrix( signif(ee$vectors, 3) )
160    
161  - src/Metis/ : some Makefile needs fixing, as changing src/Metis/*.c  - facmul() has no single method defined;  it looks like a good idea though
162               does not lead to recompilation.    (instead of the infamous qr.qy, qr.qty,.... functions)
163    
164  - man/Matrix.Rd :  has example with dimnames, but we just drop them!  - symmpart() and skewpart()  for *sparse* matrices still use (x +/- t(x))/2
165                  MM thinks dimnames should be supported (but then ...)    and could be made more efficient.
166      Consider going via  asTuniq() or something very close to
167      .Arith.Csparse() in R/Ops.R
168    
169  - data/ : names 'mm' and even more 'y' are  ``too short''.  - many setAs(*, "[dl]..Matrix") are still needed, as long as e.g.
170          If we really want to keep them, don't use "LazyData"    replCmat() uses as_CspClass() and drop0(.) which itself call
171          (such that one needs  data(*) explicitly);    as_CspClass() quite a bit.  --> try to replace these by
172          But MM would rather want something like  ex.mm and ex.y    as(*, "CsparseMatrix"); forceSymmetric, etc.

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