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revision 510, Fri Feb 4 23:36:17 2005 UTC revision 2120, Tue Mar 4 21:44:41 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      For triangular matrices, more specifically make sure the four rules of
27      "triangular matrix algebra" (Golub+Van Loan 1996, 3.1.8, p.93) are
28      fulfilled;  currently  <dtC> %*% <dtC> --> <dgC>
29    
30    - "d" <-> "l" coercion for all "[TCR]" sparse matrices is really trivial:
31      "d" -> "l" : drops the 'x' slot
32      "l" -> "d" : construct an 'x' slot of all '1'
33      We currently have many of these conversions explicitly, e.g.
34       setAs("dsTMatrix", "lsTMatrix",
35          function(from) new("lsTMatrix", i = from@i, j = from@j, uplo = from@uplo,
36                             Dim = from@Dim, Dimnames = from@Dimnames))
37      but I would rather want to automatically construct all these coercion
38      methods at once by a ``method constructor'', i.e.,
39      for all  "dsparse*" -> "lsparse*" and vice versa.
40      How can one do this {in a documented way} ?
41    
42    - Think of constructing  setAs(...) calls automatically in order to
43      basically enable all ``sensible'' as(fromMatrix, toMatrix)  calls,
44      possibly using canCoerce(.)
45    
46    - setAs(<Mcl>,  "[dln]Matrix") for <Mcl> in {Matrix or denseMatrix + sparseMatrix}
47    
48    - When we have a packed matrix, it's a waste to go through "full" to "sparse":
49      ==> implement
50            setAs("dspMatrix", "sparseMatrix")
51            setAs("dppMatrix", "sparseMatrix")
52            setAs("dtpMatrix", "sparseMatrix")
53      and the same for "lsp" , "ltp"  and  "nsp" , "ntp" !
54    
55    - tcrossprod(x, y) : do provide methods for y != NULL
56      calling Lapack's DGEMM for "dense"
57      [2005-12-xx: done for dgeMatrix at least]
58    
59    - BUGlet:  Shouldn't lose factorization here:
60      h6 <- Hilbert(6); chol(h6) ; str(h6) # has factor
61      str(H6 <- as(h6, "dspMatrix"))       # has lost factor
62      ## and the same in a similar situation involving  "dpo", "dpp"
63    
64    - Factorizations: LU done; also Schur()  for  *sparse*  Matrices.
65    
66    - is.na() method for all our matrices [ ==> which(*, arr.ind=TRUE) might work ]
67    
68    - use  .Call(Csparse_drop, M, tol) in more places,
69      both with 'tol = 0.' to drop "values that happen to be 0" and for
70      zapsmall() methods for Csparse*
71    
72    - implement .Call(Csparse_scale, ....) interfacing to cholmod_scale()
73      in src/CHOLMOD/Include/cholmod_matrixops.h : for another function
74      specifically for multiplying a cholmod_sparse object by a diagonal matrix.
75      Use it in %*% and [t]crossprod methods.
76    
77    - chol() and determinant() should ``work'': proper result or "good" error
78      message.
79    
80    - make sure *all* group methods have (maybe "bail-out") setMethod for "Matrix".
81      e.g. zapsmall(<pMatrix>) fails "badly"
82    
83    - sum(): implement methods which work for *all* our matrices.
84    
85    - Implement  expand(.) for the Cholesky() results
86      "dCHMsimpl" and  "dCHMsuper"  -- currently have no *decent* way to get at
87      the matrix factors of the corresponding matrix factorization !!
88    
89    - rbind2(<sparse>, <dense>) does not work  (e.g. <dgC>, <dge>)
90    
91    - <sparse> %*% <dense>  {also in crossprod/tcrossprod}  currently always
92      returns <dense>, since --> Csparse_dense_prod --> cholmod_sdmult
93      and that does only return dense.
94      When the sparse matrix is very sparse, i.e. has many rows with only zero
95      entries, it would make much sense to return sparse.
96    
97    - sparse-symmetric + diagonal should stay sparse-symmetric
98      (only stays sparse): Matrix(0, 4, 4) + Diagonal(4, 1:4)
99      --> R/diagMatrix.R ('FIXME')
100      but also R/Ops.R  to ensure  sp-sym. + sp-sym. |-> sp-sym.  etc
101    
102    - Diagonal(n) %*% A ---  too slow!! --> ~/R/MM/Pkg-ex/Matrix/diag-Tamas-ex.R
103    
104    - ! <symmetricMatrix>  loses symmetry, both for dense and sparse matrices.
105      !M  where M is "sparseMatrix", currently always gives dense. This only
106      makes sense when M is ``really sparse''.
107    
108    - msy <- as(matrix(c(2:1,1:2),2), "dsyMatrix"); str(msy)
109    
110      shows that the Cholesky factorization is computed ``too quickly''.
111      Can be a big pain for largish matrices, when it is unneeded.
112    
113    - example(Cholesky, echo=FALSE) ; cm <- chol(mtm); str(cm); str(mtm)
114    
115      shows that chol() does not seems to make use of an already
116      present factorization and rather uses one with more '0' in x slot.
117    
118    - diag(m) <- val    currently automatically works via  m[cbind(i,i)] <- val
119      This (`[<-` method) is now "smart" for diagonalMatrix, but needs also to
120      be for triangularMatrix, and probably also "dense*general*Matrix" since the
121      above currently goes via "matrix" and back instead of using the 'x' slot
122      directly; in particular, the triangular* "class property" is lost!
123    
124    - image(M, ..): Think about an optional smart option which keeps
125       "0 |-> transparent" and allows colors to differentiate negative and
126       positive entries.
127    
128    - examples for solve( Cholesky(.), b, system = c("A", "LDLt"....))
129      probably rather in man/CHMfactor-class.Rd than man/Cholesky.Rd
130    
131    - tr(A %*% B) {and even  tr(A %*% B %*% C) ...} are also needed
132      frequently in some computations {conditional normal distr. ...}.
133      Since this can be done faster than by
134        sum(diag(A %*% B))  even for traditional matrices, e.g.
135                   sum(A * t(B)) or {even faster for "full" mat}
136                   crossprod(as.vector(A), as.vector(B))
137      and even more so for, e.g.  <sparse> %*% <dense>
138      {used in Soeren's 'gR' computations},
139      we should also provide a generic and methods.
140    
141    - qr.R(qr(x)) may differ for the "same" matrix, depending on it being
142      sparse or dense:
143        "qr.R(<sparse>) may differ from qr.R(<dense>) because of permutations"
144    
145  - 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  
146    
147  - 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  
148    
149  - Should the uplo and diag slots continue to be stored as character?    >  New generic for "chol" does not agree with implicit generic from package
150    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.  
151    
152  - 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?  
153    
154  - 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
155    dgCMatrix objects (too tired to do that now).    sense to also dispatch on 'tol' or 'pivot' ...  --> maybe change that..
156    
157  - bCrosstab(): do we really want the diagonal "V:V" crosstabs?  - eigen() should become generic, and get a method at least for diagonal,
158      but also for symmetric -> dsyMatrix  [LAPACK dsyev() uses UPLO !],
159      but also simply for dgeMatrix (without going via tradition matrices).
160      What about Sparse?  There's fill-in, but it may still be sensible, e.g.
161      mlist <- list(1, 2:3, diag(x=5:3), 27, cbind(1,3:6), 100:101)
162      ee <- eigen(tcrossprod(bdiag(lapply(mlist, as.matrix))))
163      Matrix( signif(ee$vectors, 3) )
164    
165  - src/Metis/ : some Makefile needs fixing, as changing src/Metis/*.c  - facmul() has no single method defined;  it looks like a good idea though
166               does not lead to recompilation.    (instead of the infamous qr.qy, qr.qty,.... functions)
167    
168  - man/Matrix.Rd :  has example with dimnames, but we just drop them!  - symmpart() and skewpart()  for *sparse* matrices still use (x +/- t(x))/2
169                  MM thinks dimnames should be supported (but then ...)    and could be made more efficient.
170      Consider going via  asTuniq() or something very close to
171      .Arith.Csparse() in R/Ops.R
172    
173  - data/ : names 'mm' and even more 'y' are  ``too short''.  - many setAs(*, "[dl]..Matrix") are still needed, as long as e.g.
174          If we really want to keep them, don't use "LazyData"    replCmat() uses as_CspClass() and drop0(.) which itself call
175          (such that one needs  data(*) explicitly);    as_CspClass() quite a bit.  --> try to replace these by
176          But MM would rather want something like  ex.mm and ex.y    as(*, "CsparseMatrix"); forceSymmetric, etc.

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