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Diff of /pkg/R/Matrix.R

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revision 1290, Thu Jun 8 09:30:21 2006 UTC revision 1551, Tue Sep 12 16:39:13 2006 UTC
# Line 1  Line 1 
1  #### Toplevel ``virtual'' class "Matrix"  #### Toplevel ``virtual'' class "Matrix"
2    
3    
4    ### Virtual coercions -- via smart "helpers" (-> ./Auxiliaries.R)
5    
6    setAs("Matrix", "sparseMatrix", function(from) as_Csparse(from))
7    setAs("Matrix", "denseMatrix",  function(from) as_dense(from))
8    
9    setAs(from = "Matrix", to = "matrix", # do *not* call base::as.matrix() here:
10          function(from) .bail.out.2("coerce", class(from), class(to)))
11    
12  ## ## probably not needed eventually:  ## ## probably not needed eventually:
13  ## setAs(from = "ddenseMatrix", to = "matrix",  ## setAs(from = "ddenseMatrix", to = "matrix",
14  ##       function(from) {  ##       function(from) {
# Line 12  Line 21 
21  ## for 'Matrix' objects, as.array() should be equivalent:  ## for 'Matrix' objects, as.array() should be equivalent:
22  setMethod("as.array",  signature(x = "Matrix"), function(x) as(x, "matrix"))  setMethod("as.array",  signature(x = "Matrix"), function(x) as(x, "matrix"))
23    
24    ## head and tail apply to all Matrix objects for which subscripting is allowed:
25    setMethod("head", signature(x = "Matrix"), utils::head.matrix)
26    setMethod("tail", signature(x = "Matrix"), utils::tail.matrix)
27    
28  ## slow "fall back" method {subclasses should have faster ones}:  ## slow "fall back" method {subclasses should have faster ones}:
29  setMethod("as.vector", signature(x = "Matrix", mode = "missing"),  setMethod("as.vector", signature(x = "Matrix", mode = "missing"),
30            function(x) as.vector(as(x, "matrix")))            function(x) as.vector(as(x, "matrix")))
31    
32    ## mainly need these for "dMatrix" or "lMatrix" respectively, but why not general:
33    setMethod("as.numeric", signature(x = "Matrix"),
34              function(x, ...) as.numeric(as.vector(x)))
35    setMethod("as.logical", signature(x = "Matrix"),
36              function(x, ...) as.logical(as.vector(x)))
37    
38    
39  ## Note that isSymmetric is *not* exported  ## "base" has an isSymmetric() S3-generic since R 2.3.0
 ## but that "base" has an isSymmetric() S3-generic since R 2.3.0  
40  setMethod("isSymmetric", signature(object = "symmetricMatrix"),  setMethod("isSymmetric", signature(object = "symmetricMatrix"),
41            function(object,tol) TRUE)            function(object,tol) TRUE)
42  setMethod("isSymmetric", signature(object = "triangularMatrix"),  setMethod("isSymmetric", signature(object = "triangularMatrix"),
43            ## TRUE iff diagonal:            ## TRUE iff diagonal:
44            function(object,tol) isDiagonal(object))            function(object,tol) isDiagonal(object))
45    
 if(paste(R.version$major, R.version$minor, sep=".") < "2.3")  
     ## need a "matrix" method as in R 2.3 and later  
     setMethod("isSymmetric", signature(object = "matrix"),  
               function(object, tol = 100*.Machine$double.eps, ...)  
           {  
               ## pretest: is it square?  
               d <- dim(object)  
               if(d[1] != d[2]) return(FALSE)  
               ## for `broken' all.equal in R <= 2.2.x:  
               dn <- dimnames(object)  
               if(!identical(dn[1], dn[2])) return(FALSE)  
               test <-  
                   if(is.complex(object))  
                       all.equal.numeric(object, Conj(t(object)), tol = tol, ...)  
                   else              # numeric, character, ..  
                       all.equal(object, t(object), tol = tol, ...)  
               isTRUE(test)  
           })  
   
   
46  setMethod("isTriangular", signature(object = "triangularMatrix"),  setMethod("isTriangular", signature(object = "triangularMatrix"),
47            function(object, ...) TRUE)            function(object, ...) TRUE)
48    
# Line 77  Line 75 
75    
76  Matrix <-  Matrix <-
77      function (data = NA, nrow = 1, ncol = 1, byrow = FALSE, dimnames = NULL,      function (data = NA, nrow = 1, ncol = 1, byrow = FALSE, dimnames = NULL,
78                sparse = NULL)                sparse = NULL, forceCheck = FALSE)
79  {  {
80      sparseDefault <- function(m)      sparseDefault <- function(m)
81          prod(dim(m)) > 2*sum(as(m, "matrix") != 0)          prod(dim(m)) > 2*sum(is.na(m <- as(m, "matrix")) | m != 0)
82    
83      i.M <- is(data, "Matrix")      i.M <- is(data, "Matrix")
84      if(is.null(sparse) && (i.M || is(data, "matrix")))      if(is.null(sparse) && (i.M || is(data, "matrix")))
85          sparse <- sparseDefault(data)          sparse <- sparseDefault(data)
86    
87        doDN <- TRUE
88      if (i.M) {      if (i.M) {
89          sM <- is(data,"sparseMatrix")          sM <- is(data,"sparseMatrix")
90          if((sparse && sM) || (!sparse && !sM))          if(!forceCheck && ((sparse && sM) || (!sparse && !sM)))
91              return(data)              return(data)
92          ## else : convert  dense <-> sparse -> at end          ## else : convert  dense <-> sparse -> at end
93      }      }
# Line 97  Line 96 
96              nrow <- ceiling(length(data)/ncol)              nrow <- ceiling(length(data)/ncol)
97          else if (missing(ncol))          else if (missing(ncol))
98              ncol <- ceiling(length(data)/nrow)              ncol <- ceiling(length(data)/nrow)
99            if(length(data) == 1 && !is.na(data) && data == 0 &&
100               !identical(sparse, FALSE)) {
101    
102                if(is.null(sparse)) sparse <- TRUE
103                ## will be sparse: do NOT construct full matrix!
104                data <- new(if(is.numeric(data)) "dgTMatrix" else
105                            if(is.logical(data)) "lgTMatrix" else
106                            stop("invalid 'data'"),
107                            Dim = as.integer(c(nrow,ncol)),
108                            Dimnames = if(is.null(dimnames)) list(NULL,NULL)
109                            else dimnames)
110            } else { ## normal case
111          data <- .Internal(matrix(data, nrow, ncol, byrow))          data <- .Internal(matrix(data, nrow, ncol, byrow))
112          if(is.null(sparse))          if(is.null(sparse))
113              sparse <- sparseDefault(data)              sparse <- sparseDefault(data)
114          dimnames(data) <- dimnames          dimnames(data) <- dimnames
115      } else if (!is.null(dimnames))          }
116          dimnames(data) <- dimnames          doDN <- FALSE
117        }
118      ## 'data' is now a "matrix" or "Matrix"      ## 'data' is now a "matrix" or "Matrix"
119        if (doDN && !is.null(dimnames))
120            dimnames(data) <- dimnames
121    
122      ## check for symmetric / triangular / diagonal :      ## check for symmetric / triangular / diagonal :
123      isSym <- isSymmetric(data)      isSym <- isSymmetric(data)
# Line 163  Line 176 
176    
177  setMethod("crossprod", signature(x = "Matrix", y = "numeric"),  setMethod("crossprod", signature(x = "Matrix", y = "numeric"),
178            function(x, y = NULL) callGeneric(x, as.matrix(y)))            function(x, y = NULL) callGeneric(x, as.matrix(y)))
   
179  setMethod("crossprod", signature(x = "numeric", y = "Matrix"),  setMethod("crossprod", signature(x = "numeric", y = "Matrix"),
180            function(x, y = NULL)  callGeneric(rbind(x), y))            function(x, y = NULL)  callGeneric(as.matrix(x), y))
181    
182    ## The as.matrix() promotion seems illogical to MM,
183    ## but is according to help(tcrossprod, package = "base") :
184    setMethod("tcrossprod", signature(x = "Matrix", y = "numeric"),
185              function(x, y = NULL) callGeneric(x, as.matrix(y)))
186    setMethod("tcrossprod", signature(x = "numeric", y = "Matrix"),
187              function(x, y = NULL)  callGeneric(as.matrix(x), y))
188    
189  setMethod("solve", signature(a = "Matrix", b = "numeric"),  setMethod("solve", signature(a = "Matrix", b = "numeric"),
190            function(a, b, ...) callGeneric(a, as.matrix(b)))            function(a, b, ...) callGeneric(a, as.matrix(b)))
# Line 180  Line 199 
199            function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y)))            function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y)))
200  setMethod("crossprod", signature(x = "ANY", y = "Matrix"),  setMethod("crossprod", signature(x = "ANY", y = "Matrix"),
201            function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y)))            function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y)))
202    setMethod("tcrossprod", signature(x = "Matrix", y = "ANY"),
203              function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y)))
204    setMethod("tcrossprod", signature(x = "ANY", y = "Matrix"),
205              function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y)))
206    
207    ## cheap fallbacks
208    setMethod("crossprod", signature(x = "Matrix", y = "Matrix"),
209              function(x, y = NULL) t(x) %*% y)
210    setMethod("tcrossprod", signature(x = "Matrix", y = "Matrix"),
211              function(x, y = NULL) x %*% t(y))
212    
213  ## There are special sparse methods; this is a "fall back":  ## There are special sparse methods; this is a "fall back":
214  setMethod("kronecker", signature(X = "Matrix", Y = "ANY",  setMethod("kronecker", signature(X = "Matrix", Y = "ANY",
# Line 192  Line 221 
221                Y <- as(Y, "matrix") ; Matrix(callGeneric()) })                Y <- as(Y, "matrix") ; Matrix(callGeneric()) })
222    
223    
224    setMethod("diag", signature(x = "Matrix"),
225              function(x, nrow, ncol) .bail.out.1(.Generic, class(x)))
226  setMethod("t", signature(x = "Matrix"),  setMethod("t", signature(x = "Matrix"),
227            function(x) .bail.out.1(.Generic, class(x)))            function(x) .bail.out.1(.Generic, class(x)))
228    
# Line 249  Line 280 
280            function(x,i,j, drop)            function(x,i,j, drop)
281            stop("invalid or not-yet-implemented 'Matrix' subsetting"))            stop("invalid or not-yet-implemented 'Matrix' subsetting"))
282    
283  ##  "logical *vector* indexing, such as  M [ M >= 10 ] :  ## logical indexing, such as M[ M >= 7 ] *BUT* also M[ M[,1] >= 3,],
284  setMethod("[", signature(x = "Matrix", i = "lMatrix", j = "missing",  ## The following is *both* for    M [ <logical>   ]
285                           drop = "ANY"),  ##                 and also for   M [ <logical> , ]
286            function (x, i, j, drop) {  .M.sub.i.logical <- function (x, i, j, drop)
287    {
288        nA <- nargs()
289        if(nA == 2) { ##  M [ M >= 7 ]
290                as(x, geClass(x))@x[as.vector(i)]                as(x, geClass(x))@x[as.vector(i)]
291                                          # -> error when lengths don't match          ## -> error when lengths don't match
292            })      } else if(nA == 3) { ##  M [ M[,1, drop=FALSE] >= 7, ]
293            stop("not-yet-implemented 'Matrix' subsetting") ## FIXME
294    
295        } else stop("nargs() = ", nA,
296                    " should never happen; please report.")
297    }
298    setMethod("[", signature(x = "Matrix", i = "lMatrix", j = "missing",
299                             drop = "ANY"),
300              .M.sub.i.logical)
301  setMethod("[", signature(x = "Matrix", i = "logical", j = "missing",  setMethod("[", signature(x = "Matrix", i = "logical", j = "missing",
302                           drop = "ANY"),                           drop = "ANY"),
303            function (x, i, j, drop) as(x, geClass(x))@x[i])            .M.sub.i.logical)
304    
305    
306  ## "FIXME:"  ## "FIXME:"
307  ## How can we get at   A[ ij ]  where ij is (i,j) 2-column matrix?  ## ------ get at  A[ ij ]  where ij is (i,j) 2-column matrix?
308  ##  and                A[ LL ]  where LL is a logical *vector*  
 ## -> [.data.frame uses nargs() - can we do this in the *generic* ?  
309    
310    
311  ### "[<-" : -----------------  ### "[<-" : -----------------

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