SCM

SCM Repository

[matrix] Diff of /pkg/TODO
ViewVC logotype

Diff of /pkg/TODO

Parent Directory Parent Directory | Revision Log Revision Log | View Patch Patch

revision 540, Thu Feb 10 14:32:59 2005 UTC revision 2175, Wed Apr 23 11:23:50 2008 UTC
# Line 1  Line 1 
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"!
   
 - group generics: "Arith", but also "Ops" and "Math";  see  
   ?Math.data.frame  and the examples in  
   ?SetGeneric  
   
 - methods for rbind and cbind where they make sense  
   
 - bCrosstab(): do we really want the diagonal "V:V" crosstabs?  
                (if so or in any case: add to  man/bCrosstab.Rd )  
   
 - consider moving alloc3Darray from ./src/Mutils.c to  
   $(RSRC)/src/base/array.c  
   
 - 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  
   
 - "factors" maybe should move up to "Matrix"  
   
 -------  
   
 We have a (at least one) basic problem :  
    Currently the show() method fail sometime after coercion:  
    e.g. 'sy' show()s wrongly, even though it "str()" fine :  
   
       (po <- crossprod(Matrix(0:3, 2))) # ok  
       (ge <- as(po, "dgeMatrix")) # ok  
       (sy <- as(po, "dsyMatrix")) # BAD  
       str(sy) # looks fine  
   
   or  
       example(expand) # -> ex$L and ex$U look bad, however  
       as(ex$L, "dgeMatrix") # `works'  
   
   {Of course, we don't need a workaround but must understand  
    and solve the problem}  
   
 ---  
7    
8  - implement (more) methods for supporting "packed" (symmetric / triangular)  - implement (more) methods for supporting "packed" (symmetric / triangular)
9    matrices; particularly something like pack() and unpack().    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  - implement diagonal Matrix class  "ddiMatrix" etc  - combine the C functions for multiplication by special forms and
15    using constructor function Diagonal() or Diag().    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; now(2008-03-06) ok for Csparse; not yet for <dtr> %*% <dtr>
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    - examples for solve( Cholesky(.), b, system = c("A", "LDLt"....))
125      probably rather in man/CHMfactor-class.Rd than man/Cholesky.Rd
126    
127    - LDL(<CHMsimpl>) looks relatively easy; via  "tCsparse_diag()"
128       {diagonal entries of *triangular* Csparse}
129      --> see comment in determinant(<dsC>) in R/dsCMatrix.R, will give
130      faster determinant
131    
132    - tr(A %*% B) {and even  tr(A %*% B %*% C) ...} are also needed
133      frequently in some computations {conditional normal distr. ...}.
134      Since this can be done faster than by
135        sum(diag(A %*% B))  even for traditional matrices, e.g.
136                   sum(A * t(B)) or {even faster for "full" mat}
137                   crossprod(as.vector(A), as.vector(B))
138      and even more so for, e.g.  <sparse> %*% <dense>
139      {used in Soeren's 'gR' computations},
140      we should also provide a generic and methods.
141    
142    - qr.R(qr(x)) may differ for the "same" matrix, depending on it being
143      sparse or dense:
144        "qr.R(<sparse>) may differ from qr.R(<dense>) because of permutations"
145    
146      This is not really acceptable and currently influences  rcond() as well.
147    
148    - eigen() should become generic, and get a method at least for diagonal,
149      but also for symmetric -> dsyMatrix  [LAPACK dsyev() uses UPLO !],
150      but also simply for dgeMatrix (without going via tradition matrices).
151      What about Sparse?  There's fill-in, but it may still be sensible, e.g.
152      mlist <- list(1, 2:3, diag(x=5:3), 27, cbind(1,3:6), 100:101)
153      ee <- eigen(tcrossprod(bdiag(lapply(mlist, as.matrix))))
154      Matrix( signif(ee$vectors, 3) )
155    
156    - facmul() has no single method defined;  it looks like a good idea though
157      (instead of the infamous qr.qy, qr.qty,.... functions)
158    
159    - symmpart() and skewpart()  for *sparse* matrices still use (x +/- t(x))/2
160      and could be made more efficient.
161      Consider going via  asTuniq() or something very close to
162      .Arith.Csparse() in R/Ops.R
163    
164    - many setAs(*, "[dl]..Matrix") are still needed, as long as e.g.
165      replCmat() uses as_CspClass() and drop0(.) which itself call
166      as_CspClass() quite a bit.  --> try to replace these by
167      as(*, "CsparseMatrix"); forceSymmetric, etc.
168    
169    - implement fast diag(<triangularCsparse>) via calling new
170      src/Csparse.c's diag_tC_ptr()
171    
172    - add examples (and tests!) for update(<CHMfactor>, ..) and
173      Cholesky(......, Imult), also tests for hidden {hence no examples}
174      ldetL2up() { R/CHMfactor.R }
175    
176    - chol(<nsCMatrix>)  gives "temporarily disabled"
177      but should give the *symbolic* factorization;
178      similarly Cholesky(.) is not enabled
179    
180    - writeMM(obj, file=stdout()) creates file "1" since file is silently
181      assumed to be a string, i.e. cannot be a connection.
182      An R (instead of C) version should be pretty simple, and would work with
183      connections automatically ["lsparse" become either "real" or
184      "pattern", "depending if they have NAs or not].

Legend:
Removed from v.540  
changed lines
  Added in v.2175

root@r-forge.r-project.org
ViewVC Help
Powered by ViewVC 1.0.0  
Thanks to:
Vienna University of Economics and Business Powered By FusionForge