### Define Methods that can be inherited for all subclasses ### Idea: Coercion between *VIRTUAL* classes -- as() chooses "closest" classes ### ---- should also work e.g. for dense-triangular --> sparse-triangular ! ##-> see als ./dMatrix.R, ./ddenseMatrix.R and ./lMatrix.R setAs("ANY", "sparseMatrix", function(from) as(from, "CsparseMatrix")) setAs(from = "sparseMatrix", to = "generalMatrix", as_gCsimpl) ## "graph" coercions -- this needs the graph package which is currently ## ----- *not* required on purpose ## Note: 'undirected' graph <==> 'symmetric' matrix ## Add some utils that may no longer be needed in future versions of the 'graph' package graph.has.weights <- function(g) "weight" %in% names(edgeDataDefaults(g)) graph.wgtMatrix <- function(g) { ## Purpose: work around "graph" package's as(g, "matrix") bug ## ---------------------------------------------------------------------- ## Arguments: g: an object inheriting from (S4) class "graph" ## ---------------------------------------------------------------------- ## Author: Martin Maechler, based on Seth Falcon's code; Date: 12 May 2006 ## MM: another buglet for the case of "no edges": if(numEdges(g) == 0) { p <- length(nd <- nodes(g)) return( matrix(0, p,p, dimnames = list(nd, nd)) ) } ## Usual case, when there are edges: has.w <- "weight" %in% names(edgeDataDefaults(g)) if(has.w) { w <- unlist(edgeData(g, attr = "weight")) has.w <- any(w != 1) } ## now 'has.w' is TRUE iff there are weights != 1 m <- as(g, "matrix") ## now is a 0/1 - matrix (instead of 0/wgts) with the 'graph' bug if(has.w) { ## fix it if needed tm <- t(m) tm[tm != 0] <- w t(tm) } else m } setAs("graphAM", "sparseMatrix", function(from) { symm <- edgemode(from) == "undirected" && isSymmetric(from@adjMat) ## This is only ok if there are no weights... if(graph.has.weights(from)) { as(graph.wgtMatrix(from), if(symm) "dsTMatrix" else "dgTMatrix") } else { ## no weights: 0/1 matrix -> logical as(as(from, "matrix"), if(symm) "nsTMatrix" else "ngTMatrix") } }) setAs("graph", "CsparseMatrix", function(from) as(as(from, "graphNEL"), "CsparseMatrix")) setAs("graphNEL", "CsparseMatrix", function(from) as(as(from, "TsparseMatrix"), "CsparseMatrix")) setAs("graphNEL", "TsparseMatrix", function(from) { nd <- nodes(from) dm <- rep.int(length(nd), 2) symm <- edgemode(from) == "undirected" if(graph.has.weights(from)) { eWts <- edgeWeights(from) lens <- unlist(lapply(eWts, length)) i <- rep.int(0:(dm[1]-1), lens) # column indices (0-based) To <- unlist(lapply(eWts, names)) j <- as.integer(match(To,nd) - 1:1) # row indices (0-based) ## symm <- symm && : improbable ## if(symm) new("dsTMatrix", .....) else new("dgTMatrix", i = i, j = j, x = unlist(eWts), Dim = dm, Dimnames = list(nd, nd)) } else { ## no weights: 0/1 matrix -> logical edges <- lapply(from@edgeL[nd], "[[", "edges") lens <- unlist(lapply(edges, length)) ## nnz <- sum(unlist(lens)) # number of non-zeros i <- rep.int(0:(dm[1]-1), lens) # column indices (0-based) j <- as.integer(unlist(edges) - 1) # row indices (0-based) if(symm) { # symmetric: ensure upper triangle tmp <- i flip <- i > j i[flip] <- j[flip] j[flip] <- tmp[flip] new("nsTMatrix", i = i, j = j, Dim = dm, Dimnames = list(nd, nd), uplo = "U") } else { new("ngTMatrix", i = i, j = j, Dim = dm, Dimnames = list(nd, nd)) } } }) setAs("sparseMatrix", "graph", function(from) as(from, "graphNEL")) setAs("sparseMatrix", "graphNEL", function(from) as(as(from, "TsparseMatrix"), "graphNEL")) Tsp2grNEL <- function(from) { d <- dim(from) if(d[1] != d[2]) stop("only square matrices can be used as incidence matrices for graphs") n <- d[1] if(n == 0) return(new("graphNEL")) if(is.null(rn <- dimnames(from)[[1]])) rn <- as.character(1:n) from <- uniq(from) ## Need to 'uniquify' the triplets! if(isSymmetric(from)) { # either "symmetricMatrix" or otherwise ##-> undirected graph: every edge only once! if(!is(from, "symmetricMatrix")) { ## a general matrix which happens to be symmetric ## ==> remove the double indices from <- tril(from) } eMode <- "undirected" } else { eMode <- "directed" } ## every edge is there only once, either upper or lower triangle ft1 <- cbind(rn[from@i + 1:1], rn[from@j + 1:1]) ## not yet: graph::ftM2graphNEL(.........) ftM2graphNEL(ft1, W = from@x, V= rn, edgemode= eMode) } setAs("TsparseMatrix", "graphNEL", Tsp2grNEL) ### Subsetting -- basic things (drop = "missing") are done in ./Matrix.R ### FIXME : we defer to the "*gT" -- conveniently, but not efficient for gC ! ## [dl]sparse -> [dl]gT -- treat both in one via superclass ## -- more useful when have "z" (complex) and even more setMethod("[", signature(x = "sparseMatrix", i = "index", j = "missing", drop = "logical"), function (x, i, j, drop) { cld <- getClassDef(class(x)) if(!extends(cld, "generalMatrix")) x <- as(x, "generalMatrix") viaCl <- paste(.M.kind(x, cld), "gTMatrix", sep='') x <- callGeneric(x = as(x, viaCl), i=i, drop=drop) ## try_as(x, c(cl, sub("T","C", viaCl))) if(is(x, "Matrix") && extends(cld, "CsparseMatrix")) as(x, "CsparseMatrix") else x }) setMethod("[", signature(x = "sparseMatrix", i = "missing", j = "index", drop = "logical"), function (x, i, j, drop) { cld <- getClassDef(class(x)) if(!extends(cld, "generalMatrix")) x <- as(x, "generalMatrix") viaCl <- paste(.M.kind(x, cld), "gTMatrix", sep='') x <- callGeneric(x = as(x, viaCl), j=j, drop=drop) if(is(x, "Matrix") && extends(cld, "CsparseMatrix")) as(x, "CsparseMatrix") else x }) setMethod("[", signature(x = "sparseMatrix", i = "index", j = "index", drop = "logical"), function (x, i, j, drop) { cld <- getClassDef(class(x)) ## be smart to keep symmetric indexing of symmetric: doSym <- (extends(cld, "symmetricMatrix") && length(i) == length(j) && all(i == j)) if(!doSym && !extends(cld, "generalMatrix")) x <- as(x, "generalMatrix") viaCl <- paste(.M.kind(x, cld), if(doSym) "sTMatrix" else "gTMatrix", sep='') x <- callGeneric(x = as(x, viaCl), i=i, j=j, drop=drop) if(is(x, "Matrix") && extends(cld, "CsparseMatrix")) as(x, "CsparseMatrix") else x }) ## setReplaceMethod("[", .........) ## -> ./Tsparse.R ## & ./Csparse.R ## FIXME: also for RsparseMatrix ## Group Methods setMethod("Math", signature(x = "sparseMatrix"), function(x) callGeneric(as(x, "CsparseMatrix"))) ## further group methods -> see ./Ops.R ### --- show() method --- ## FIXME(?) -- ``merge this'' (at least ``synchronize'') with ## - - - prMatrix() from ./Auxiliaries.R prSpMatrix <- function(object, digits = getOption("digits"), maxp = getOption("max.print"), zero.print = ".", row.trailer = '', align = c("fancy", "right")) ## FIXME: prTriang() in ./Auxiliaries.R should also get align = "fancy" { cl <- getClassDef(class(object)) stopifnot(extends(cl, "sparseMatrix")) d <- dim(object) if(prod(d) > maxp) { # "Large" => will be "cut" ## only coerce to dense that part which won't be cut : nr <- maxp %/% d[2] m <- as(object[1:max(1, nr), ,drop=FALSE], "Matrix") } else { m <- as(object, "matrix") } logi <- extends(cl,"lsparseMatrix") || extends(cl,"nsparseMatrix") if(logi) x <- array("N", # or as.character(NA), dim(m), dimnames=dimnames(m)) else { ## numeric (or --not yet-- complex): x <- apply(m, 2, format) if(is.null(dim(x))) {# e.g. in 1 x 1 case dim(x) <- dim(m) dimnames(x) <- dimnames(m) } } x <- emptyColnames(x) if(is.logical(zero.print)) zero.print <- if(zero.print) "0" else " " if(logi) { x[!m] <- zero.print x[m] <- "|" } else { # non logical ## show only "structural" zeros as 'zero.print', not all of them.. ## -> cannot use 'm' d <- dim(x) ne <- length(iN0 <- 1:1 + encodeInd(non0ind(object, cl), nr = d[1])) if(0 < ne && ne < prod(d)) { align <- match.arg(align) if(align == "fancy") { fi <- apply(m, 2, format.info) ## fi[3,] == 0 <==> not expo. ## now 'format' the zero.print by padding it with ' ' on the right: ## case 1: non-exponent: fi[2,] + as.logical(fi[2,] > 0) ## the column numbers of all 'zero' entries -- (*large*) cols <- 1:1 + (0:(prod(d)-1:1))[-iN0] %/% d[1] pad <- ifelse(fi[3,] == 0, fi[2,] + as.logical(fi[2,] > 0), ## exponential: fi[2,] + fi[3,] + 4) ## now be efficient ; sprintf() is relatively slow ## and pad is much smaller than 'cols'; instead of "simply" ## zero.print <- sprintf("%-*s", pad[cols] + 1, zero.print) if(any(doP <- pad > 0)) {# ## only pad those that need padding - *before* expanding z.p.pad <- rep.int(zero.print, length(pad)) z.p.pad[doP] <- sprintf("%-*s", pad[doP] + 1, zero.print) zero.print <- z.p.pad[cols] } else zero.print <- rep.int(zero.print, length(cols)) } ## else "right" : nothing to do x[-iN0] <- zero.print } else if (ne == 0)# all zeroes x[] <- zero.print } if(row.trailer != '') x <- cbind(x, row.trailer, deparse.level = 0) ## right = TRUE : cheap attempt to get better "." alignment print(x, quote = FALSE, right = TRUE, max = maxp) invisible(object) } setMethod("show", signature(object = "sparseMatrix"), function(object) { d <- dim(object) cl <- class(object) cat(sprintf('%d x %d sparse Matrix of class "%s"\n', d[1], d[2], cl)) maxp <- getOption("max.print") if(prod(d) <= maxp) prSpMatrix(object, maxp = maxp) else { ## d[1] > maxp / d[2] >= nr : -- this needs [,] working: nR <- d[1] # nrow useW <- getOption("width") - (format.info(nR)[1] + 3+1) ## space for "[,] " suppCols <- (d[2] * 2 > useW) nc <- if(suppCols) (useW - (1 + 6)) %/% 2 else d[2] ## sp+ row.trailer row.trailer <- if(suppCols) "......" else "" nr <- maxp %/% nc suppRows <- (nr < nR) if(suppRows) { if(suppCols) object <- object[ , 1:nc, drop = FALSE] n2 <- ceiling(nr / 2) prSpMatrix(object[seq_len(min(nR, max(1, n2))), , drop=FALSE], row.trailer = row.trailer) cat("\n ..............................", "\n ..........suppressing rows in show(); maybe adjust 'options(max.print= *)'", "\n ..............................\n\n", sep='') ## tail() automagically uses "[..,]" rownames: prSpMatrix(tail(object, max(1, nr-n2)), row.trailer = row.trailer) } else if(suppCols) { prSpMatrix(object[ , 1:nc , drop = FALSE], row.trailer = row.trailer) cat("\n .....suppressing columns in show(); maybe adjust 'options(max.print= *)'", "\n ..............................\n", sep='') } else stop("logic programming error in prSpMatrix(), please report") invisible(object) } }) setMethod("isSymmetric", signature(object = "sparseMatrix"), function(object, tol = 100*.Machine$double.eps) { ## pretest: is it square? d <- dim(object) if(d[1] != d[2]) return(FALSE) ## else slower test if (is(object, "dMatrix")) ## use gC; "T" (triplet) is *not* unique! isTRUE(all.equal(.as.dgC.0.factors( object), .as.dgC.0.factors(t(object)), tol = tol)) else if (is(object, "lMatrix")) ## test for exact equality; FIXME(?): identical() too strict? identical(as(object, "lgCMatrix"), as(t(object), "lgCMatrix")) else if (is(object, "nMatrix")) ## test for exact equality; FIXME(?): identical() too strict? identical(as(object, "ngCMatrix"), as(t(object), "ngCMatrix")) else stop("not yet implemented") }) ## These two are not (yet?) exported: setMethod("isTriangular", signature(object = "sparseMatrix"), function(object, upper = NA) isTriC(as(object, "CsparseMatrix"), upper)) setMethod("isDiagonal", signature(object = "sparseMatrix"), function(object) { gT <- as(object, "TsparseMatrix") all(gT@i == gT@j) }) setMethod("diag", signature(x = "sparseMatrix"), function(x, nrow, ncol = n) diag(as(x, "CsparseMatrix"))) ## .as.dgT.Fun setMethod("colSums", signature(x = "sparseMatrix"), .as.dgT.Fun) setMethod("colMeans", signature(x = "sparseMatrix"), .as.dgT.Fun) ## .as.dgC.Fun setMethod("rowSums", signature(x = "sparseMatrix"), .as.dgC.Fun) setMethod("rowMeans", signature(x = "sparseMatrix"),.as.dgC.Fun)