#### Toplevel ``virtual'' class "Matrix" ### Virtual coercions -- via smart "helpers" (-> ./Auxiliaries.R) setAs("Matrix", "sparseMatrix", function(from) as_Csparse(from)) setAs("Matrix", "denseMatrix", function(from) as_dense(from)) ## ## probably not needed eventually: ## setAs(from = "ddenseMatrix", to = "matrix", ## function(from) { ## if(length(d <- dim(from)) != 2) stop("dim(.) has not length 2") ## array(from@x, dim = d, dimnames = dimnames(from)) ## }) ## should propagate to all subclasses: setMethod("as.matrix", signature(x = "Matrix"), function(x) as(x, "matrix")) ## for 'Matrix' objects, as.array() should be equivalent: setMethod("as.array", signature(x = "Matrix"), function(x) as(x, "matrix")) ## head and tail apply to all Matrix objects for which subscripting is allowed: ## if(paste(R.version$major, R.version$minor, sep=".") < "2.4") { setMethod("head", signature(x = "Matrix"), utils:::head.matrix) setMethod("tail", signature(x = "Matrix"), utils:::tail.matrix) ## } else { # R 2.4.0 and newer ## setMethod("head", signature(x = "Matrix"), utils::head.matrix) ## setMethod("tail", signature(x = "Matrix"), utils::tail.matrix) ## } ## slow "fall back" method {subclasses should have faster ones}: setMethod("as.vector", signature(x = "Matrix", mode = "missing"), function(x) as.vector(as(x, "matrix"))) ## mainly need these for "dMatrix" or "lMatrix" respectively, but why not general: setMethod("as.numeric", signature(x = "Matrix"), function(x, ...) as.numeric(as.vector(x))) setMethod("as.logical", signature(x = "Matrix"), function(x, ...) as.logical(as.vector(x))) ## "base" has an isSymmetric() S3-generic since R 2.3.0 setMethod("isSymmetric", signature(object = "symmetricMatrix"), function(object,tol) TRUE) setMethod("isSymmetric", signature(object = "triangularMatrix"), ## TRUE iff diagonal: function(object,tol) isDiagonal(object)) setMethod("isTriangular", signature(object = "triangularMatrix"), function(object, ...) TRUE) setMethod("isTriangular", signature(object = "matrix"), isTriMat) setMethod("isDiagonal", signature(object = "matrix"), .is.diagonal) setMethod("dim", signature(x = "Matrix"), function(x) x@Dim, valueClass = "integer") setMethod("dimnames", signature(x = "Matrix"), function(x) x@Dimnames) ## not exported but used more than once for "dimnames<-" method : ## -- or do only once for all "Matrix" classes ?? dimnamesGets <- function (x, value) { d <- dim(x) if (!is.list(value) || length(value) != 2 || !(is.null(v1 <- value[[1]]) || length(v1) == d[1]) || !(is.null(v2 <- value[[2]]) || length(v2) == d[2])) stop(sprintf("invalid dimnames given for '%s' object", class(x))) x@Dimnames <- list(if(!is.null(v1)) as.character(v1), if(!is.null(v2)) as.character(v2)) x } setMethod("dimnames<-", signature(x = "Matrix", value = "list"), dimnamesGets) setMethod("unname", signature("Matrix", force="missing"), function(obj) { obj@Dimnames <- list(NULL,NULL); obj}) Matrix <- function (data = NA, nrow = 1, ncol = 1, byrow = FALSE, dimnames = NULL, sparse = NULL, forceCheck = FALSE) { sparseDefault <- function(m) prod(dim(m)) > 2*sum(is.na(m <- as(m, "matrix")) | m != 0) i.M <- is(data, "Matrix") if(is.null(sparse) && (i.M || is(data, "matrix"))) sparse <- sparseDefault(data) doDN <- TRUE if (i.M && !forceCheck) { sM <- is(data,"sparseMatrix") if((sparse && sM) || (!sparse && !sM)) return(data) ## else : convert dense <-> sparse -> at end } else if (!is.matrix(data)) { ## cut & paste from "base::matrix" : if (missing(nrow)) nrow <- ceiling(length(data)/ncol) else if (missing(ncol)) ncol <- ceiling(length(data)/nrow) if(length(data) == 1 && !is.na(data) && data == 0 && !identical(sparse, FALSE)) { if(is.null(sparse)) sparse <- TRUE ## will be sparse: do NOT construct full matrix! data <- new(if(is.numeric(data)) "dgTMatrix" else if(is.logical(data)) "lgTMatrix" else stop("invalid 'data'"), Dim = as.integer(c(nrow,ncol)), Dimnames = if(is.null(dimnames)) list(NULL,NULL) else dimnames) } else { ## normal case data <- .Internal(matrix(data, nrow, ncol, byrow)) if(is.null(sparse)) sparse <- sparseDefault(data) dimnames(data) <- dimnames } doDN <- FALSE } ## 'data' is now a "matrix" or "Matrix" if (doDN && !is.null(dimnames)) dimnames(data) <- dimnames ## check for symmetric / triangular / diagonal : isSym <- isSymmetric(data) if((isTri <- !isSym)) isTri <- isTriangular(data) isDiag <- isSym # cannot be diagonal if it isn't symmetric if(isDiag) isDiag <- isDiagonal(data) ### TODO: Compare with as.Matrix() and its tests in ./dgeMatrix.R ## Find proper matrix class 'cl' cl <- if(isDiag) "diagonalMatrix" # -> will automatically check for type else { ## consider it's type ctype <- if(is(data,"Matrix")) class(data) else { if("complex" == (ctype <- typeof(data))) "z" else ctype } ctype <- substr(ctype, 1,1) # "d", "l", "i" or "z" if(ctype == "z") stop("complex matrices not yet implemented in Matrix package") if(ctype == "i") { warning("integer matrices not yet implemented in 'Matrix'; ", "using 'double' ones'") ctype <- "d" } paste(ctype, if(sparse) { if(isSym) "sCMatrix" else if(isTri) "tCMatrix" else "gCMatrix" } else { ## dense if(isSym) "syMatrix" else if(isTri) "trMatrix" else "geMatrix" }, sep="") } ## Now coerce and return as(data, cl) } ## Methods for operations where one argument is numeric ## Using as.matrix() and rbind() ## in order to get dimnames from names {at least potentially}: setMethod("%*%", signature(x = "Matrix", y = "numeric"), function(x, y) callGeneric(x, as.matrix(y))) setMethod("%*%", signature(x = "numeric", y = "Matrix"), function(x, y) callGeneric(rbind(x), y)) setMethod("crossprod", signature(x = "Matrix", y = "numeric"), function(x, y = NULL) callGeneric(x, as.matrix(y))) setMethod("crossprod", signature(x = "numeric", y = "Matrix"), function(x, y = NULL) callGeneric(as.matrix(x), y)) ## The as.matrix() promotion seems illogical to MM, ## but is according to help(tcrossprod, package = "base") : setMethod("tcrossprod", signature(x = "Matrix", y = "numeric"), function(x, y = NULL) callGeneric(x, as.matrix(y))) setMethod("tcrossprod", signature(x = "numeric", y = "Matrix"), function(x, y = NULL) callGeneric(as.matrix(x), y)) setMethod("solve", signature(a = "Matrix", b = "numeric"), function(a, b, ...) callGeneric(a, as.matrix(b))) ## bail-out methods in order to get better error messages setMethod("%*%", signature(x = "Matrix", y = "Matrix"), function (x, y) stop(gettextf('not-yet-implemented method for <%s> %%*%% <%s>', class(x), class(y)))) setMethod("crossprod", signature(x = "Matrix", y = "ANY"), function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y))) setMethod("crossprod", signature(x = "ANY", y = "Matrix"), function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y))) setMethod("tcrossprod", signature(x = "Matrix", y = "ANY"), function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y))) setMethod("tcrossprod", signature(x = "ANY", y = "Matrix"), function (x, y = NULL) .bail.out.2(.Generic, class(x), class(y))) ## cheap fallbacks setMethod("crossprod", signature(x = "Matrix", y = "Matrix"), function(x, y = NULL) t(x) %*% y) setMethod("tcrossprod", signature(x = "Matrix", y = "Matrix"), function(x, y = NULL) x %*% t(y)) ## There are special sparse methods; this is a "fall back": setMethod("kronecker", signature(X = "Matrix", Y = "ANY", FUN = "ANY", make.dimnames = "ANY"), function(X, Y, FUN, make.dimnames, ...) { X <- as(X, "matrix") ; Matrix(callGeneric()) }) setMethod("kronecker", signature(X = "ANY", Y = "Matrix", FUN = "ANY", make.dimnames = "ANY"), function(X, Y, FUN, make.dimnames, ...) { Y <- as(Y, "matrix") ; Matrix(callGeneric()) }) setMethod("diag", signature(x = "Matrix"), function(x, nrow, ncol) .bail.out.1(.Generic, class(x))) setMethod("t", signature(x = "Matrix"), function(x) .bail.out.1(.Generic, class(x))) ## Group Methods setMethod("+", signature(e1 = "Matrix", e2 = "missing"), function(e1) e1) ## "fallback": setMethod("-", signature(e1 = "Matrix", e2 = "missing"), function(e1) { warning("inefficient method used for \"- e1\"") 0-e1 }) ## bail-outs: setMethod("Compare", signature(e1 = "Matrix", e2 = "Matrix"), function(e1, e2) { d <- dimCheck(e1,e2) .bail.out.2(.Generic, class(e1), class(e2)) }) setMethod("Compare", signature(e1 = "Matrix", e2 = "ANY"), function(e1, e2) .bail.out.2(.Generic, class(e1), class(e2))) setMethod("Compare", signature(e1 = "ANY", e2 = "Matrix"), function(e1, e2) .bail.out.2(.Generic, class(e1), class(e2))) ### -------------------------------------------------------------------------- ### ### Subsetting "[" and ### SubAssign "[<-" : The "missing" cases can be dealt with here, "at the top": ## Using "index" for indices should allow ## integer (numeric), logical, or character (names!) indices : ## "x[]": setMethod("[", signature(x = "Matrix", i = "missing", j = "missing", drop = "ANY"), function (x, i, j, drop) x) ## missing 'drop' --> 'drop = TRUE' ## ----------- ## select rows setMethod("[", signature(x = "Matrix", i = "index", j = "missing", drop = "missing"), function(x,i,j, drop) callGeneric(x, i=i, drop= TRUE)) ## select columns setMethod("[", signature(x = "Matrix", i = "missing", j = "index", drop = "missing"), function(x,i,j, drop) callGeneric(x, j=j, drop= TRUE)) setMethod("[", signature(x = "Matrix", i = "index", j = "index", drop = "missing"), function(x,i,j, drop) callGeneric(x, i=i, j=j, drop= TRUE)) ## bail out if any of (i,j,drop) is "non-sense" setMethod("[", signature(x = "Matrix", i = "ANY", j = "ANY", drop = "ANY"), function(x,i,j, drop) stop("invalid or not-yet-implemented 'Matrix' subsetting")) ## logical indexing, such as M[ M >= 7 ] *BUT* also M[ M[,1] >= 3,], ## The following is *both* for M [ ] ## and also for M [ , ] .M.sub.i.logical <- function (x, i, j, drop) { nA <- nargs() if(nA == 2) { ## M [ M >= 7 ] as(x, geClass(x))@x[as.vector(i)] ## -> error when lengths don't match } else if(nA == 3) { ## M [ M[,1, drop=FALSE] >= 7, ] stop("not-yet-implemented 'Matrix' subsetting") ## FIXME } else stop("nargs() = ", nA, " should never happen; please report.") } setMethod("[", signature(x = "Matrix", i = "lMatrix", j = "missing", drop = "ANY"), .M.sub.i.logical) setMethod("[", signature(x = "Matrix", i = "logical", j = "missing", drop = "ANY"), .M.sub.i.logical) ## "FIXME:" ## ------ get at A[ ij ] where ij is (i,j) 2-column matrix? ### "[<-" : ----------------- ## x[] <- value : setReplaceMethod("[", signature(x = "Matrix", i = "missing", j = "missing", value = "ANY"),## double/logical/... function (x, value) { x@x <- value validObject(x)# check if type and lengths above match x }) ## Method for all 'Matrix' kinds (rather than incomprehensible error messages); ## (ANY,ANY,ANY) is used when no `real method' is implemented : setReplaceMethod("[", signature(x = "Matrix", i = "ANY", j = "ANY", value = "ANY"), function (x, i, j, value) { if(!is.atomic(value)) stop("RHS 'value' must match matrix class ", class(x)) else stop("not-yet-implemented 'Matrix[<-' method") }) ## The trivial methods : setMethod("cbind2", signature(x = "Matrix", y = "NULL"), function(x, y) x) setMethod("cbind2", signature(x = "Matrix", y = "missing"), function(x, y) x) setMethod("cbind2", signature(x = "NULL", y="Matrix"), function(x, y) x) setMethod("rbind2", signature(x = "Matrix", y = "NULL"), function(x, y) x) setMethod("rbind2", signature(x = "Matrix", y = "missing"), function(x, y) x) setMethod("rbind2", signature(x = "NULL", y="Matrix"), function(x, y) x) ## Makes sure one gets x decent error message for the unimplemented cases: setMethod("cbind2", signature(x = "Matrix", y = "Matrix"), function(x, y) { rowCheck(x,y) stop(gettextf("cbind2() method for (%s,%s) not-yet defined", class(x), class(y))) }) ## Use a working fall back {particularly useful for sparse}: ## FIXME: implement rbind2 via "cholmod" for C* and Tsparse ones setMethod("rbind2", signature(x = "Matrix", y = "Matrix"), function(x, y) { colCheck(x,y) t(cbind2(t(x), t(y))) })