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revision 834, Mon Aug 8 08:36:34 2005 UTC revision 1887, Thu Jun 7 09:04:34 2007 UTC
# Line 1  Line 1 
1    Check for DimNames propagation in coercion and other operations.
2    ------
3    - rcond methods for sparseMatrix classes
4    
5  - Report the problem in the Linux ldexp manual page.  The second and  - Report the problem in the Linux ldexp manual page.  The second and
6    third calls in the Synopsis should be to ldexpf and ldexpl.    third calls in the Synopsis should be to ldexpf and ldexpl.
7    
8  - [,] indexing  - [,] indexing: for sparse "works", but not yet for negative indices!
   
 - group generics: "Arith" (partly done),  
   but also "Compare", "Math" etc;  
   see ?Math  and the examples in ?SetGeneric  
   
 - methods for rbind and cbind where they make sense  
   (Kurt is particularly interested in dgCMatrix ones, for pkg 'arules')  
   ****> UNFEASIBLE as long cbind is function(..., *) !!!! <*******  
     --> follow John's proposition  cbind(x, ...) via Generic cbind2(x,y)?  
9    
10  - consider moving alloc3Darray from ./src/Mutils.c to  - consider moving alloc3Darray from ./src/Mutils.c to
11    $(RSRC)/src/base/array.c    $(RSRC)/src/base/array.c
12    ------
 - 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  
   
 -  slot "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}  
   
 ---  
   
13  - provide methods for "dspMatrix" and "dppMatrix"!  - provide methods for "dspMatrix" and "dppMatrix"!
14    
15  - implement (more) methods for supporting "packed" (symmetric / triangular)  - implement (more) methods for supporting "packed" (symmetric / triangular)
# Line 50  Line 18 
18    
19    (have some dtr* <-> dtp*)    (have some dtr* <-> dtp*)
20    
21  - implement diagonal Matrix class  "ddiMatrix" etc  -----
   using constructor function Diagonal() or Diag().  
   
 - FIXME: dtpMatrix(... diag = "U") (i.e., unit-diagonal packed triangular)  
   -----  *does* need 'x' entries for the diagonal but these are never looked at.  
     -> change doc {or code ? - depends on what Lapack expects !}  
   
 BUG: rcond() of a singular dpoMatrix gives a LaPack error instead of just 0:  
   MM <- crossprod(M <- Matrix(c(1:4,9:6), 2,4)) ; rcond(MM)  
   ##> Error in rcond(MM) : Lapack routine dpotrf returned error code 4  
   
   
 ---  
22    
23  - combine the C functions for multiplication by special forms and  - combine the C functions for multiplication by special forms and
24    solution wrt special forms by using a 'right' argument and a    solution wrt special forms by using a 'right' argument and a
# Line 73  Line 29 
29  - add more comprehensive examples / tests for Schur decomposition  - add more comprehensive examples / tests for Schur decomposition
30    
31  - arithmetic for sparse matrices:  - arithmetic for sparse matrices:
32               <sparseMatrix>  o  { <scalar> | <same-dim-sparseMatrix> }               <sparseMatrix>  o  <same-dim-sparseMatrix>
33    should return a sparse matrix  for at least "+" and "*" , also %%,    should return a sparse matrix  for at least "+" and "*" , also %%,
34    and "/" and "%/%" at least when the RHS is non-zero a scalar.    and "/" and "%/%" at least when the RHS is non-zero a scalar.
35      Challenge: nice implementation (``common non-0''; but Tsparse* is not uniq).
36    
37    -----
38    
39    - "Math2" , "Math", "Arith":
40       keep triangular and symmetric Matrices when appropriate:
41       particularly desirable for  "Math2": round(), signif()
42    
43    - "d" <-> "l" coercion for all "[TCR]" sparse matrices is really trivial:
44      "d" -> "l" : drops the 'x' slot
45      "l" -> "d" : construct an 'x' slot of all '1'
46      We currently have many of these conversions explicitly, e.g.
47       setAs("dsTMatrix", "lsTMatrix",
48          function(from) new("lsTMatrix", i = from@i, j = from@j, uplo = from@uplo,
49                             Dim = from@Dim, Dimnames = from@Dimnames))
50      but I would rather want to automatically construct all these coercion
51      methods at once by a ``method constructor'', i.e.,
52      for all  "dsparse*" -> "lsparse*" and vice versa.
53      How can one do this {in a documented way} ?
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    - Things like  M[upper.tri(M)] are not really most useful for  sparse
65      matrices.  --> provide generic functions
66      upperTriMatrix(), lowerTriMatrix()  both with argument  'diag = TRUE'
67      (which can be set to FALSE of course) which are used to extract a
68      triangle from an arbitrary sparse matrix and  return a  "dtCMatrix".
69    
70    - Factorizations: LU done; also Schur()  for  *sparse*  Matrices.
71    
72    - band(), triu(), tril() for *all* including "matrix", not just sparse matrices
73    
74    - is.na() method for all our matrices [ ==> which(*, arr.ind=TRUE) might work ]
75    
76    - When we have a packed matrix, it's a waste to go through "full" to "sparse":
77      ==> implement
78            setAs("dspMatrix", "sparseMatrix")
79            setAs("dppMatrix", "sparseMatrix")
80            setAs("dtpMatrix", "sparseMatrix")
81      and the same for "lsp" , "ltp"  and  "nsp" , "ntp" !
82    
83    - use  .Call(Csparse_drop, M, tol) in more places,
84      both with 'tol = 0.' to drop "values that happen to be 0" and for
85      zapsmall() methods for Csparse*
86    
87    - implement .Call(Csparse_scale, ....) interfacing to cholmod_scale()
88      in src/CHOLMOD/Include/cholmod_matrixops.h : for another function
89      specifically for multiplying a cholmod_sparse object by a diagonal matrix.
90      Use it in %*% and [t]crossprod methods.
91    
92    - chol() and determinant() should ``work'': proper result or "good" error
93      message.
94    
95    - Think of constructing  setAs(...) calls automatically in order to
96      basically enable all ``sensible'' as(fromMatrix, toMatrix)  calls,
97      possibly using canCoerce(.)
98    
99    - make sure *all* group methods have (maybe "bail-out") setMethod for "Matrix".
100      e.g. zapsmall(<pMatrix>) fails "badly"
101    
102    - speedup: pass class definition to non0ind() [check all calls ..]
103    
104    - sum(): implement methods which work for *all* our matrices.
105    
106    - Implement  expand(.) for the Cholesky() results
107      "dCHMsimpl" and  "dCHMsuper"  -- currently have no *decent* way to get at
108      the matrix factors of the corresponding matrix factorization !!
109    
110    - rbind(<sparse>, <dense>) does not work  (e.g. <dgC>, <dge>)
111    
112    - setAs(<Mcl>,  "[dln]Matrix" )  for <Mcl> in {Matrix or denseMatrix + sparseMatrix}
113    
114    - Tell users about the possibility to disable the "S4-generic but somewhat slow"
115      cbind/rbind, e.g. via
116    
117      setHook(packageEvent("Matrix", "onLoad"),
118              function(...) methods:::bind_activation(FALSE))
119    
120    - ensure that  M[0], M[FALSE], M[1:2]  works as for traditional Matrices
121    
122    - make sure  M[FALSE, FALSE]  works for all Matrices
123      {e.g. fails for M <- Diagonal(4)}
124    
125    - <sparse> %*% <dense>  {also in crossprod/tcrossprod}  currently always
126      returns <dense>, since --> Csparse_dense_prod --> cholmod_sdmult
127      and that does only return dense.
128      When the sparse matrix is very sparse, i.e. has many rows with only zero
129      entries, it would make much sense to return sparse.
130    
131    - sparse-symmetric + diagonal should stay sparse-symmetric
132      (only stays sparse): Matrix(0, 4, 4) + Diagonal(4, 1:4)
133      --> R/diagMatrix.R ('FIXME')
134      but also R/Ops.R  to ensure  sp-sym. + sp-sym. |-> sp-sym.  etc
135    
136    - For a square sparse matrix 'b' {typically dgCMatrix or dgTMatrix},
137      we'd want a function  "Mat_plus_t_Mat" <- function(b) {....}
138      which computes the symmetric sparse matrix   b + t(b)
139      in way that never works with size-doubled vectors from  b@i etc..
140    
141    - ! <symmetricMatrix>  loses symmetry, both for dense and sparse matrices.
142      !M  where M is "sparseMatrix", currently always gives dense. This only
143      makes sense when M is ``really sparse''.
144    
145  ---  - column names of sparse matrices are not printed;
146      we now "mention" them (if they are non-empty).
147      Option:
148            build show( <sparseMatrix>) on a function, possibly
149            print.sparseMatrix(), which gets an argument such as
150            'col.names.show  = FALSE' which is documented and can be set to TRUE
151    
152  - in lmer.c check all instances of the use of ZtX and XtX and change  - 'arules' needs fast colSums() and rowSums() - for ngCMatrix;
153    them so that having a negative last element of nc means use the    do it for "nMatrix" and "lMatrix" and return *integer*
   response only (but look for it in the right place).  

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