[Vegan-commits] r2950 - in pkg/vegan: . R inst man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Mon May 25 08:52:06 CEST 2015


Author: jarioksa
Date: 2015-05-25 08:52:06 +0200 (Mon, 25 May 2015)
New Revision: 2950

Modified:
   pkg/vegan/DESCRIPTION
   pkg/vegan/R/CCorA.R
   pkg/vegan/R/MDSrotate.R
   pkg/vegan/R/adipart.default.R
   pkg/vegan/R/anova.ccabyterm.R
   pkg/vegan/R/betadiver.R
   pkg/vegan/R/cca.default.R
   pkg/vegan/R/estimateR.default.R
   pkg/vegan/R/factorfit.R
   pkg/vegan/R/make.commsim.R
   pkg/vegan/R/multipart.default.R
   pkg/vegan/R/nesteddisc.R
   pkg/vegan/R/nestedtemp.R
   pkg/vegan/R/permustats.R
   pkg/vegan/R/plot.cca.R
   pkg/vegan/R/plot.meandist.R
   pkg/vegan/R/plot.radfit.frame.R
   pkg/vegan/R/print.varpart.R
   pkg/vegan/R/print.varpart234.R
   pkg/vegan/R/rankindex.R
   pkg/vegan/R/rarecurve.R
   pkg/vegan/R/rda.default.R
   pkg/vegan/R/read.cep.R
   pkg/vegan/R/scores.cca.R
   pkg/vegan/R/scores.ordihull.R
   pkg/vegan/R/scores.rda.R
   pkg/vegan/R/summary.anosim.R
   pkg/vegan/R/summary.bioenv.R
   pkg/vegan/R/summary.cca.R
   pkg/vegan/R/summary.radfit.frame.R
   pkg/vegan/R/varpart.R
   pkg/vegan/R/vegemite.R
   pkg/vegan/README.md
   pkg/vegan/inst/NEWS.Rd
   pkg/vegan/man/permustats.Rd
Log:
Merge branch 'cran-2.3' into r-forge-svn-local

Modified: pkg/vegan/DESCRIPTION
===================================================================
--- pkg/vegan/DESCRIPTION	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/DESCRIPTION	2015-05-25 06:52:06 UTC (rev 2950)
@@ -1,7 +1,7 @@
 Package: vegan
 Title: Community Ecology Package
-Version: 2.2-2
-Date: 2015-01-12
+Version: 2.3-0
+Date: 2015-05-21
 Author: Jari Oksanen, F. Guillaume Blanchet, Roeland Kindt, Pierre Legendre, 
    Peter R. Minchin, R. B. O'Hara, Gavin L. Simpson, Peter Solymos, 
    M. Henry H. Stevens, Helene Wagner  

Modified: pkg/vegan/R/CCorA.R
===================================================================
--- pkg/vegan/R/CCorA.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/CCorA.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -98,7 +98,7 @@
     qq <- temp$m
     rownames(X) <- rownoms
     ## Correction PL, 26dec10
-    if(max(pp,qq) >= (n-1)) 
+    if(max(pp,qq) >= (n-1))
     	stop("Not enough degrees of freedom: max(pp,qq) >= (n-1)")
     ## Covariance matrices, etc. from the PCA scores
     S11 <- cov(Y)
@@ -120,7 +120,7 @@
     if((p == q) & (var(K.svd$d) < epsilon))
     	cat("Warning: [nearly] circular covariance matrix. The solution may be meaningless.",'\n')
     ## K.svd$u %*% diag(K.svd$d) %*% t(K.svd$v)   # To check that K = U D V'
-    axenames <- paste("CanAxis",1:length(K.svd$d),sep="")
+    axenames <- paste("CanAxis",seq_along(K.svd$d),sep="")
     U <- K.svd$u
     V <- K.svd$v
     A <- S11.chol.inv %*% U
@@ -134,7 +134,7 @@
     corr.X.Cx <- cor(X.c, Cx)  # To plot X in biplot in space X
     ## Add row and column names
     rownames(Cy) <- rownames(Cx) <- rownoms
-	colnames(Cy) <- colnames(Cx) <- axenames    
+	colnames(Cy) <- colnames(Cx) <- axenames
     rownames(corr.Y.Cy) <- rownames(corr.Y.Cx) <- Ynoms
     rownames(corr.X.Cy) <- rownames(corr.X.Cx) <- Xnoms
     colnames(corr.Y.Cy) <- colnames(corr.Y.Cx) <- axenames
@@ -163,20 +163,20 @@
                       ncol(permat), n))
 
     if (nperm > 0) {
-        p.perm <- sapply(1:nperm, function(indx, ...) 
+        p.perm <- sapply(seq_len(nperm), function(indx, ...)
                          probPillai(Y[permat[indx,],] , X, n, S11.inv, S22.inv, s,
                                     df1, df2, epsilon, Fval, nperm, ...))
         p.perm <- (sum(p.perm) +1)/(nperm + 1)
     } else {
         p.perm <- NA
     }
-    
+
     out <- list(Pillai=PillaiTrace, Eigenvalues=Eigenvalues, CanCorr=K.svd$d,
-                Mat.ranks=c(RsquareX.Y$m, RsquareY.X$m), 
+                Mat.ranks=c(RsquareX.Y$m, RsquareY.X$m),
                 RDA.Rsquares=c(RsquareY.X$Rsquare, RsquareX.Y$Rsquare),
                 RDA.adj.Rsq=c(Rsquare.adj.Y.X, Rsquare.adj.X.Y),
-                nperm=nperm, p.Pillai=p.Pillai, p.perm=p.perm, Cy=Cy, Cx=Cx, 
-                corr.Y.Cy=corr.Y.Cy, corr.X.Cx=corr.X.Cx, corr.Y.Cx=corr.Y.Cx, 
+                nperm=nperm, p.Pillai=p.Pillai, p.perm=p.perm, Cy=Cy, Cx=Cx,
+                corr.Y.Cy=corr.Y.Cy, corr.X.Cx=corr.X.Cx, corr.Y.Cx=corr.Y.Cx,
                 corr.X.Cy=corr.X.Cy, control = attr(permat, "control"),
                 call = match.call())
     class(out) <- "CCorA"

Modified: pkg/vegan/R/MDSrotate.R
===================================================================
--- pkg/vegan/R/MDSrotate.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/MDSrotate.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -3,7 +3,7 @@
 `MDSrotate` <-
     function(object, vec, na.rm = FALSE, ...) 
 {
-    workswith <- c("metaMDS", "monoMDS")
+    workswith <- c("metaMDS", "monoMDS", "GO")
     if (!inherits(object, workswith))
         stop(gettextf("function works only with the results of: %s",
                       paste(workswith, collapse = ", ")))

Modified: pkg/vegan/R/adipart.default.R
===================================================================
--- pkg/vegan/R/adipart.default.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/adipart.default.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -32,7 +32,7 @@
         rval[[i]] <- interaction(rhs[,nCol], rval[[(i-1)]], drop=TRUE)
         nCol <- nCol - 1
     }
-    rval <- as.data.frame(rval[rev(1:length(rval))])
+    rval <- as.data.frame(rval[rev(seq_along(rval))])
     l2 <- sapply(rval, function(z) length(unique(z)))
     if (any(l1 != l2))
         stop("levels are not perfectly nested")
@@ -41,7 +41,7 @@
     fullgamma <-if (nlevels(rhs[,nlevs]) == 1)
         TRUE else FALSE
     ftmp <- vector("list", nlevs)
-    for (i in 1:nlevs) {
+    for (i in seq_len(nlevs)) {
         ftmp[[i]] <- as.formula(paste("~", tlab[i], "- 1"))
     }
 
@@ -71,16 +71,16 @@
         ## matrix sum *can* change in oecosimu (but default is constant sumMatr)
         sumMatr <- sum(x)
         if (fullgamma) {
-            tmp <- lapply(1:(nlevs-1), function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
+            tmp <- lapply(seq_len(nlevs-1), function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
             tmp[[nlevs]] <- matrix(colSums(x), nrow = 1, ncol = ncol(x))
         } else {
-            tmp <- lapply(1:nlevs, function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
+            tmp <- lapply(seq_len(nlevs), function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
         }
         ## weights will change in oecosimu thus need to be recalculated
         if (weights == "prop")
-            wt <- lapply(1:nlevs, function(i) apply(tmp[[i]], 1, function(z) sum(z) / sumMatr))
-        else wt <- lapply(1:nlevs, function(i) rep(1 / NROW(tmp[[i]]), NROW(tmp[[i]])))
-        a <- sapply(1:nlevs, function(i) sum(divfun(tmp[[i]]) * wt[[i]]))
+            wt <- lapply(seq_len(nlevs), function(i) apply(tmp[[i]], 1, function(z) sum(z) / sumMatr))
+        else wt <- lapply(seq_len(nlevs), function(i) rep(1 / NROW(tmp[[i]]), NROW(tmp[[i]])))
+        a <- sapply(seq_len(nlevs), function(i) sum(divfun(tmp[[i]]) * wt[[i]]))
         if (relative)
             a <- a / a[length(a)]
         b <- sapply(2:nlevs, function(i) a[i] - a[(i-1)])
@@ -95,8 +95,8 @@
         sim <- list(statistic = sim,
                     oecosimu = list(z = tmp, pval = tmp, method = NA, statistic = sim))
     }
-    nam <- c(paste("alpha", 1:(nlevs-1), sep="."), "gamma",
-             paste("beta", 1:(nlevs-1), sep="."))
+    nam <- c(paste("alpha", seq_len(nlevs-1), sep="."), "gamma",
+             paste("beta", seq_len(nlevs-1), sep="."))
     names(sim$statistic) <- attr(sim$oecosimu$statistic, "names") <- nam
     call <- match.call()
     call[[1]] <- as.name("adipart")

Modified: pkg/vegan/R/anova.ccabyterm.R
===================================================================
--- pkg/vegan/R/anova.ccabyterm.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/anova.ccabyterm.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -137,7 +137,7 @@
     fla <- reformulate(names(LC))
     Pvals <- rep(NA, length(eig))
     environment(object$terms) <- environment()
-    for (i in 1:length(eig)) {
+    for (i in seq_along(eig)) {
         part <- paste("~ . +Condition(",
                       paste(names(LC)[-i], collapse = "+"), ")")
         upfla <- update(fla, part)

Modified: pkg/vegan/R/betadiver.R
===================================================================
--- pkg/vegan/R/betadiver.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/betadiver.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -27,7 +27,7 @@
                  "z"="(log(2)-log(2*a+b+c)+log(a+b+c))/log(2)"
                  )
     if (help) {
-        for (i in 1:length(beta)) 
+        for (i in seq_along(beta)) 
             writeLines(strwrap(paste(i, " \"", names(beta[i]),
                                      "\" = ", beta[[i]], "\n", sep="")))
         return(invisible(NULL))

Modified: pkg/vegan/R/cca.default.R
===================================================================
--- pkg/vegan/R/cca.default.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/cca.default.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -1,5 +1,5 @@
 `cca.default` <-
-    function (X, Y, Z, ...) 
+    function (X, Y, Z, ...)
 {
     ZERO <- 1e-04
     CCA <- NULL
@@ -18,7 +18,7 @@
         isTRUE(all.equal(X, t(X))))
         stop("function cannot be used with (dis)similarities")
     X <- as.matrix(X)
-    if (any(rowSums(X) <= 0)) 
+    if (any(rowSums(X) <= 0))
         stop("All row sums must be >0 in the community data matrix")
     if (any(tmp <- colSums(X) <= 0)) {
         exclude.spec <- seq(along=tmp)[tmp]
@@ -40,7 +40,7 @@
         Z <- qr.fitted(Q, Xbar)
         tmp <- sum(svd(Z, nu = 0, nv = 0)$d^2)
         if (Q$rank) {
-            pCCA <- list(rank = Q$rank, tot.chi = tmp, QR = Q, 
+            pCCA <- list(rank = Q$rank, tot.chi = tmp, QR = Q,
                          Fit = Z, envcentre = attr(Z.r, "centre"))
             Xbar <- qr.resid(Q, Xbar)
         }
@@ -52,7 +52,7 @@
         Y <- as.matrix(Y)
         Y.r <- weight.centre(Y, rowsum)
         Q <- qr(cbind(Z.r, Y.r), tol = ZERO)
-        if (is.null(pCCA)) 
+        if (is.null(pCCA))
             rank <- Q$rank
         else rank <- Q$rank - pCCA$rank
         ## save rank of constraints
@@ -61,7 +61,7 @@
         sol <- svd(Y)
         ## rank of svd can be < qrank
         rank <- min(rank, sum(sol$d > ZERO))
-        ax.names <- paste("CCA", 1:length(sol$d), sep = "")
+        ax.names <- paste("CCA", seq_along(sol$d), sep = "")
         colnames(sol$u) <- ax.names
         colnames(sol$v) <- ax.names
         names(sol$d) <- ax.names
@@ -69,20 +69,20 @@
         rownames(sol$v) <- colnames(X)
         if (rank) {
             CCA <- list(eig = sol$d[1:rank]^2)
-            CCA$u <- sweep(as.matrix(sol$u[, 1:rank, drop = FALSE]), 
+            CCA$u <- sweep(as.matrix(sol$u[, 1:rank, drop = FALSE]),
                            1, 1/sqrt(rowsum), "*")
-            CCA$v <- sweep(as.matrix(sol$v[, 1:rank, drop = FALSE]), 
+            CCA$v <- sweep(as.matrix(sol$v[, 1:rank, drop = FALSE]),
                            1, 1/sqrt(colsum), "*")
-            wa.eig <- sweep(Xbar %*% sol$v[, 1:rank, drop = FALSE], 
+            wa.eig <- sweep(Xbar %*% sol$v[, 1:rank, drop = FALSE],
                             1, 1/sqrt(rowsum), "*")
             CCA$wa <- sweep(wa.eig, 2, 1/sol$d[1:rank], "*")
             oo <- Q$pivot
-            if (!is.null(pCCA$rank)) 
+            if (!is.null(pCCA$rank))
                 oo <- oo[-(1:pCCA$rank)] - ncol(Z.r)
             oo <- oo[1:qrank]
-            if (length(oo) < ncol(Y.r)) 
+            if (length(oo) < ncol(Y.r))
                 CCA$alias <- colnames(Y.r)[-oo]
-            CCA$biplot <- cor(Y.r[, oo, drop = FALSE], sol$u[, 
+            CCA$biplot <- cor(Y.r[, oo, drop = FALSE], sol$u[,
                                         1:rank, drop = FALSE])
             CCA$rank <- rank
             CCA$qrank <- qrank
@@ -104,11 +104,11 @@
         if (exists("exclude.spec")) {
             attr(CCA$v, "na.action") <- exclude.spec
         }
-        
+
     }
     Q <- qr(Xbar)
     sol <- svd(Xbar)
-    ax.names <- paste("CA", 1:length(sol$d), sep = "")
+    ax.names <- paste("CA", seq_along(sol$d), sep = "")
     colnames(sol$u) <- ax.names
     colnames(sol$v) <- ax.names
     names(sol$d) <- ax.names
@@ -116,15 +116,15 @@
     rownames(sol$v) <- colnames(X)
     rank <- min(Q$rank, sum(sol$d > ZERO))
     if (rank) {
-        CA <- list(eig = sol$d[1:rank]^2)
-        CA$u <- sweep(as.matrix(sol$u[, 1:rank, drop = FALSE]), 
+        CA <- list(eig = sol$d[seq_len(rank)]^2)
+        CA$u <- sweep(as.matrix(sol$u[, seq_len(rank), drop = FALSE]),
                       1, 1/sqrt(rowsum), "*")
-        CA$v <- sweep(as.matrix(sol$v[, 1:rank, drop = FALSE]), 
+        CA$v <- sweep(as.matrix(sol$v[, seq_len(rank), drop = FALSE]),
                       1, 1/sqrt(colsum), "*")
         CA$rank <- rank
         CA$tot.chi <- sum(CA$eig)
         CA$Xbar <- Xbar
-        
+
     } else {   # zero rank: no residual component
         CA <- list(eig = 0, rank = rank, tot.chi = 0,
                    Xbar = Xbar)
@@ -139,8 +139,8 @@
     ## computed pCCA$rank was needed before, but zero it here
     if (!is.null(pCCA) && pCCA$tot.chi == 0)
         pCCA$rank <- 0
-    sol <- list(call = call, grand.total = gran.tot, rowsum = rowsum, 
-                colsum = colsum, tot.chi = tot.chi, pCCA = pCCA, CCA = CCA, 
+    sol <- list(call = call, grand.total = gran.tot, rowsum = rowsum,
+                colsum = colsum, tot.chi = tot.chi, pCCA = pCCA, CCA = CCA,
                 CA = CA)
     sol$method <- "cca"
     sol$inertia <- "mean squared contingency coefficient"

Modified: pkg/vegan/R/estimateR.default.R
===================================================================
--- pkg/vegan/R/estimateR.default.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/estimateR.default.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -76,7 +76,7 @@
     sd.Chao1 <- sqrt(sd.Chao1)
 
     C.ace <- 1 - a[1]/N.rare
-    i <- 1:length(a)
+    i <- seq_along(a)
     thing <- i * (i - 1) * a
     Gam <- sum(thing) * S.rare/(C.ace * N.rare * (N.rare - 1)) - 
         1

Modified: pkg/vegan/R/factorfit.R
===================================================================
--- pkg/vegan/R/factorfit.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/factorfit.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -1,5 +1,5 @@
 `factorfit` <-
-    function (X, P, permutations = 0, strata = NULL, w,  ...) 
+    function (X, P, permutations = 0, strata = NULL, w,  ...)
 {
     P <- as.data.frame(P)
     ## Check that all variables are factors, and coerce if necessary
@@ -7,7 +7,7 @@
         P <- data.frame(lapply(P, function(x)
                         if (is.factor(x)) x else factor(x)))
     P <- droplevels(P) ## make sure only the used levels are present
-    if (any(!sapply(P, is.factor))) 
+    if (any(!sapply(P, is.factor)))
         stop("All non-numeric variables must be factors")
     NR <- nrow(X)
     NC <- ncol(X)
@@ -19,7 +19,7 @@
     r <- NULL
     pval <- NULL
     totvar <- .C("goffactor", as.double(X), as.integer(rep(0, NR)),
-                 as.double(w), as.integer(NR), as.integer(NC), as.integer(1), 
+                 as.double(w), as.integer(NR), as.integer(NC), as.integer(1),
                  double(1), double(1), double(1), var = double(1), PACKAGE = "vegan")$var
     sol <- centroids.cca(X, P, w)
     var.id <- rep(names(P), sapply(P, nlevels))
@@ -27,12 +27,12 @@
     permat <- getPermuteMatrix(permutations, NR, strata = strata)
     permutations <- nrow(permat)
 
-    for (i in 1:length(P)) {
+    for (i in seq_along(P)) {
         A <- as.integer(P[[i]])
         NL <- nlevels(P[[i]])
         invar <- .C("goffactor", as.double(X), as.integer(A - 1), as.double(w),
-                    as.integer(NR), as.integer(NC), 
-                    as.integer(NL), double(NL), double(NL), double(NL), 
+                    as.integer(NR), as.integer(NC),
+                    as.integer(NL), double(NL), double(NL), double(NL),
                     var = double(1), PACKAGE = "vegan")$var
         r.this <- 1 - invar/totvar
         r <- c(r, r.this)
@@ -43,24 +43,24 @@
                 take <- A[indx]
                 invar <- .C("goffactor", as.double(X),
                             as.integer(take -  1), as.double(w),
-                            as.integer(NR), as.integer(NC), 
-                            as.integer(NL), double(NL), double(NL), double(NL), 
+                            as.integer(NR), as.integer(NC),
+                            as.integer(NL), double(NL), double(NL), double(NL),
                             var = double(1), PACKAGE = "vegan")$var
                 1 - invar/totvar
             }
-            tmp <- sapply(1:permutations,
+            tmp <- sapply(seq_len(permutations),
                           function(indx,...) ptest(permat[indx,], ...))
             pval.this <- (sum(tmp >= r.this) + 1)/(permutations + 1)
             pval <- c(pval, pval.this)
         }
     }
-    if (is.null(colnames(X))) 
+    if (is.null(colnames(X)))
         colnames(sol) <- paste("Dim", 1:ncol(sol), sep = "")
     else colnames(sol) <- colnames(X)
     names(r) <- names(P)
-    if (!is.null(pval)) 
+    if (!is.null(pval))
         names(pval) <- names(P)
-    out <- list(centroids = sol, r = r, permutations = permutations, 
+    out <- list(centroids = sol, r = r, permutations = permutations,
                 pvals = pval, var.id = var.id)
     out$control <- attr(permat, "control")
     class(out) <- "factorfit"

Modified: pkg/vegan/R/make.commsim.R
===================================================================
--- pkg/vegan/R/make.commsim.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/make.commsim.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -4,9 +4,9 @@
 ## so it can be used instead of match.arg(method) in other functions
 ## NOTE: very very long -- but it can be a central repository of algos
 ## NOTE 2: storage mode coercions are avoided here
-## (with no apparent effect on speed), it should be 
+## (with no apparent effect on speed), it should be
 ## handled by nullmodel and commsim characteristics
-make.commsim <- 
+make.commsim <-
 function(method)
 {
     algos <- list(
@@ -78,19 +78,19 @@
             out <- array(unlist(r2dtable(n, rs, cs)), c(nr, nc, n))
             storage.mode(out) <- "integer"
             for (k in seq_len(n))
-                out[,,k] <- .C("quasiswap", 
+                out[,,k] <- .C("quasiswap",
                     m = out[,,k], nr, nc, PACKAGE = "vegan")$m
             out
         }),
-        "swap" = commsim(method="swap", binary=TRUE, isSeq=TRUE, 
+        "swap" = commsim(method="swap", binary=TRUE, isSeq=TRUE,
         mode="integer",
         fun=function(x, n, nr, nc, rs, cs, rf, cf, s, fill, thin) {
             out <- array(0L, c(nr, nc, n))
-            out[,,1] <- .C("swap", 
+            out[,,1] <- .C("swap",
                 m = x, nr, nc, thin, PACKAGE = "vegan")$m
             for (k in seq_len(n-1))
-                out[,,k+1] <- .C("swap", 
-                    m = out[,,k], nr, nc, thin, 
+                out[,,k+1] <- .C("swap",
+                    m = out[,,k], nr, nc, thin,
                     PACKAGE = "vegan")$m
             out
         }),
@@ -98,10 +98,10 @@
         mode="integer",
         fun=function(x, n, nr, nc, rs, cs, rf, cf, s, fill, thin) {
             out <- array(0L, c(nr, nc, n))
-            out[,,1] <- .C("trialswap", 
+            out[,,1] <- .C("trialswap",
                 m = x, nr, nc, thin, PACKAGE = "vegan")$m
             for (k in seq_len(n-1))
-                out[,,k+1] <- .C("trialswap", 
+                out[,,k+1] <- .C("trialswap",
                     m = out[,,k], nr, nc, thin, PACKAGE = "vegan")$m
             out
         }),
@@ -118,7 +118,7 @@
                 ij <- sample(free, prob = prob)
                 i <- (ij - 1)%%nr + 1
                 j <- (ij - 1)%/%nr + 1
-                for (k in 1:length(ij)) {
+                for (k in seq_along(ij)) {
                     if (icount[i[k]] < rs[i[k]] && jcount[j[k]] < cs[j[k]]) {
                         out[ij[k]] <- 1L
                         icount[i[k]] <- icount[i[k]] + 1L
@@ -126,25 +126,25 @@
                     }
                 }
                 ndrop <- 1
-                for (i in 1:10000) {
+                for (i in seq_len(10000)) {
                     oldout <- out
                     oldn <- sum(out)
                     drop <- sample(all[out == 1L], ndrop)
                     out[drop] <- 0L
                     candi <- outer(rowSums(out) < rs, colSums(out) < cs, "&") & out == 0L
                     while (sum(candi) > 0) {
-                        if (sum(candi) > 1) 
+                        if (sum(candi) > 1)
                           ij <- sample(all[candi], 1)
                         else ij <- all[candi]
                         out[ij] <- 1L
                         candi <- outer(rowSums(out) < rs, colSums(out) < cs, "&") & out == 0
                     }
-                    if (sum(out) >= fill) 
+                    if (sum(out) >= fill)
                         break
-                    if (oldn >= sum(out)) 
+                    if (oldn >= sum(out))
                         ndrop <- min(ndrop + 1, 4)
                     else ndrop <- 1
-                    if (oldn > sum(out)) 
+                    if (oldn > sum(out))
                         out <- oldout
                 }
                 out
@@ -165,10 +165,10 @@
         mode="integer",
         fun=function(x, n, nr, nc, cs, rs, rf, cf, s, fill, thin) {
             out <- array(0L, c(nr, nc, n))
-            out[,,1] <- .C("swapcount", 
+            out[,,1] <- .C("swapcount",
                 m = x, nr, nc, thin, PACKAGE = "vegan")$m
             for (k in seq_len(n-1))
-                out[,,k+1] <- .C("swapcount", 
+                out[,,k+1] <- .C("swapcount",
                     m = out[,,k], nr, nc, thin, PACKAGE = "vegan")$m
             out
         }),
@@ -178,7 +178,7 @@
             out <- array(unlist(r2dtable(n, rs, cs)), c(nr, nc, n))
             storage.mode(out) <- "integer"
             for (k in seq_len(n))
-                out[,,k] <- .C("rswapcount", 
+                out[,,k] <- .C("rswapcount",
                     m = out[,,k], nr, nc, fill, PACKAGE = "vegan")$m
             out
         }),
@@ -189,7 +189,7 @@
             out <- array(unlist(r2dtable(fill, rf, cf)), c(nr, nc, n))
             storage.mode(out) <- "double"
             for (k in seq_len(n)) {
-                out[,,k] <- .C("quasiswap", 
+                out[,,k] <- .C("quasiswap",
                     m = as.integer(out[,,k]), nr, nc, PACKAGE = "vegan")$m
                 out[,,k][out[,,k] > 0] <- sample(nz) # we assume that length(nz)>1
             }
@@ -205,7 +205,7 @@
             out <- array(unlist(r2dtable(fill, rf, cf)), c(nr, nc, n))
             storage.mode(out) <- "integer"
             for (k in seq_len(n)) {
-                out[,,k] <- .C("quasiswap", 
+                out[,,k] <- .C("quasiswap",
                     m = out[,,k], nr, nc, PACKAGE = "vegan")$m
                 out[,,k][out[,,k] > 0] <- indshuffle(nz - 1L) + 1L  # we assume that length(nz)>1
             }
@@ -218,7 +218,7 @@
             storage.mode(out) <- "double"
             I <- seq_len(nr)
             for (k in seq_len(n)) {
-                out[,,k] <- .C("quasiswap", 
+                out[,,k] <- .C("quasiswap",
                     m = as.integer(out[,,k]), nr, nc, PACKAGE = "vegan")$m
                 for (i in I) {
                     nz <- x[i,][x[i,] > 0]
@@ -237,7 +237,7 @@
             storage.mode(out) <- "double"
             J <- seq_len(nc)
             for (k in seq_len(n)) {
-                out[,,k] <- .C("quasiswap", 
+                out[,,k] <- .C("quasiswap",
                     m = as.integer(out[,,k]), nr, nc, PACKAGE = "vegan")$m
                 for (j in J) {
                     nz <- x[,j][x[,j] > 0]
@@ -259,7 +259,7 @@
             out <- array(unlist(r2dtable(fill, rf, cf)), c(nr, nc, n))
             storage.mode(out) <- "integer"
             for (k in seq_len(n)) {
-                out[,,k] <- .C("quasiswap", 
+                out[,,k] <- .C("quasiswap",
                     m = out[,,k], nr, nc, PACKAGE = "vegan")$m
                 for (i in I) {
                     nz <- as.integer(x[i,][x[i,] > 0])
@@ -281,7 +281,7 @@
             out <- array(unlist(r2dtable(fill, rf, cf)), c(nr, nc, n))
             storage.mode(out) <- "integer"
             for (k in seq_len(n)) {
-                out[,,k] <- .C("quasiswap", 
+                out[,,k] <- .C("quasiswap",
                     m = out[,,k], nr, nc,  PACKAGE = "vegan")$m
                 for (j in J) {
                     nz <- as.integer(x[,j][x[,j] > 0])
@@ -297,10 +297,10 @@
         mode="double",
         fun=function(x, n, nr, nc, cs, rs, rf, cf, s, fill, thin) {
             out <- array(0, c(nr, nc, n))
-            out[,,1] <- .C("abuswap", 
+            out[,,1] <- .C("abuswap",
                 m = x, nr, nc, thin, 1L, PACKAGE = "vegan")$m
             for (k in seq_len(n-1))
-                out[,,k+1] <- .C("abuswap", 
+                out[,,k+1] <- .C("abuswap",
                     m = out[,,k], nr, nc, thin, 1L, PACKAGE = "vegan")$m
             out
         }),
@@ -308,10 +308,10 @@
         mode="double",
         fun=function(x, n, nr, nc, cs, rs, rf, cf, s, fill, thin) {
             out <- array(0, c(nr, nc, n))
-            out[,,1] <- .C("abuswap", 
+            out[,,1] <- .C("abuswap",
                 m = x, nr, nc, thin, 0L, PACKAGE = "vegan")$m
             for (k in seq_len(n-1))
-                out[,,k+1] <- .C("abuswap", 
+                out[,,k+1] <- .C("abuswap",
                     m = out[,,k], nr, nc, thin, 0L, PACKAGE = "vegan")$m
             out
         }),

Modified: pkg/vegan/R/multipart.default.R
===================================================================
--- pkg/vegan/R/multipart.default.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/multipart.default.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -7,7 +7,7 @@
     ## evaluate formula
     lhs <- as.matrix(y)
     if (missing(x))
-        x <- cbind(level_1=seq_len(nrow(lhs)), 
+        x <- cbind(level_1=seq_len(nrow(lhs)),
             leve_2=rep(1, nrow(lhs)))
     rhs <- data.frame(x)
     rhs[] <- lapply(rhs, as.factor)
@@ -20,7 +20,7 @@
     if (any(lhs < 0))
         stop("data matrix contains negative entries")
     if (is.null(colnames(rhs)))
-        colnames(rhs) <- paste("level", 1:nlevs, sep="_")
+        colnames(rhs) <- paste("level", seq_len(nlevs), sep="_")
     tlab <- colnames(rhs)
 
      ## check proper design of the model frame
@@ -34,7 +34,7 @@
         rval[[i]] <- interaction(rhs[,nCol], rval[[(i-1)]], drop=TRUE)
         nCol <- nCol - 1
     }
-    rval <- as.data.frame(rval[rev(1:length(rval))])
+    rval <- as.data.frame(rval[rev(seq_along(rval))])
     l2 <- sapply(rval, function(z) length(unique(z)))
     if (any(l1 != l2))
         stop("levels are not perfectly nested")
@@ -45,7 +45,7 @@
 #    if (!fullgamma && !global)
 #        warning("gamma diversity value might be meaningless")
     ftmp <- vector("list", nlevs)
-    for (i in 1:nlevs) {
+    for (i in seq_len(nlevs)) {
         ftmp[[i]] <- as.formula(paste("~", tlab[i], "- 1"))
     }
 
@@ -77,37 +77,39 @@
     if (global) {
         wdivfun <- function(x) {
             if (fullgamma) {
-                tmp <- lapply(1:(nlevs-1), function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
+                tmp <- lapply(seq_len(nlevs - 1),
+                              function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
                 tmp[[nlevs]] <- matrix(colSums(x), nrow = 1, ncol = ncol(x))
             } else {
-                tmp <- lapply(1:nlevs, function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
+                tmp <- lapply(seq_len(nlevs),
+                              function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
             }
-            raw <- sapply(1:nlevs, function(i) divfun(tmp[[i]]))
+            raw <- sapply(seq_len(nlevs), function(i) divfun(tmp[[i]]))
             a <- sapply(raw, mean)
             G <- a[nlevs]
-            b <- sapply(1:(nlevs-1), function(i) G / a[i])
+            b <- sapply(seq_len(nlevs - 1), function(i) G / a[i])
             if (relative)
-                b <- b / sapply(raw[1:(nlevs-1)], length)
+                b <- b / sapply(raw[seq_len(nlevs - 1)], length)
             c(a, b)
         }
     } else {
         wdivfun <- function(x) {
             if (fullgamma) {
-                tmp <- lapply(1:(nlevs-1), function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
+                tmp <- lapply(seq_len(nlevs-1), function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
                 tmp[[nlevs]] <- matrix(colSums(x), nrow = 1, ncol = ncol(x))
             } else {
-                tmp <- lapply(1:nlevs, function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
+                tmp <- lapply(seq_len(nlevs), function(i) t(model.matrix(ftmp[[i]], rhs)) %*% x)
             }
-            a <- sapply(1:nlevs, function(i) divfun(tmp[[i]]))
-            am <- lapply(1:(nlevs-1), function(i) {
-                    sapply(1:length(unique(id[[i]])), function(ii) {
+            a <- sapply(seq_len(nlevs), function(i) divfun(tmp[[i]]))
+            am <- lapply(seq_len(nlevs - 1), function(i) {
+                    sapply(seq_along(unique(id[[i]])), function(ii) {
                         mean(a[[i]][id[[i]]==ii])
                     })
                 })
-            b <- lapply(1:(nlevs-1), function(i) a[[(i+1)]] / am[[i]])
+            b <- lapply(seq_len(nlevs - 1), function(i) a[[(i+1)]] / am[[i]])
             bmax <- lapply(id, function(i) table(i))
             if (relative)
-                b <- lapply(1:(nlevs-1), function(i) b[[i]] / bmax[[i]])
+                b <- lapply(seq_len(nlevs - 1), function(i) b[[i]] / bmax[[i]])
             c(sapply(a, mean), sapply(b, mean))
         }
     }
@@ -120,8 +122,8 @@
             sim <- list(statistic = sim,
                 oecosimu = list(z = tmp, pval = tmp, method = NA, statistic = sim))
         }
-    nam <- c(paste("alpha", 1:(nlevs-1), sep="."), "gamma",
-        paste("beta", 1:(nlevs-1), sep="."))
+    nam <- c(paste("alpha", seq_len(nlevs - 1), sep="."), "gamma",
+        paste("beta", seq_len(nlevs - 1), sep="."))
     names(sim$statistic) <- attr(sim$oecosimu$statistic, "names") <- nam
     call <- match.call()
     call[[1]] <- as.name("multipart")

Modified: pkg/vegan/R/nesteddisc.R
===================================================================
--- pkg/vegan/R/nesteddisc.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/nesteddisc.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -26,11 +26,11 @@
     ## Range of row sums: only swaps between these have an effect
     rs <- range(rowSums(comm))
     ## Function to evaluate discrepancy
-    FUN <- function(x) sum(comm[col(comm)[,x] <= rowSums(comm)] == 0) 
+    FUN <- function(x) sum(comm[col(comm)[,x] <= rowSums(comm)] == 0)
     Ad <- FUN(x)
     ## Go through all le-items and permute ties. Functions allPerms
     ## and shuffleSet are in permute package.
-    for (i in 1:length(le)) {
+    for (i in seq_along(le)) {
         if (le[i] > 1) {
             take <- x
             idx <- (1:le[i]) + cle[i]

Modified: pkg/vegan/R/nestedtemp.R
===================================================================
--- pkg/vegan/R/nestedtemp.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/nestedtemp.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -31,7 +31,7 @@
         i <- rowpack(comm, j)
     }
     ## Improve eight times
-    for (k in 1:8) {
+    for (k in seq_len(8)) {
         j <- colpack(comm, i)
         i <- rowpack(comm, j)
     }
@@ -67,8 +67,8 @@
     p <- sol$root
     ## row coordinates of the fill line for all matrix entries
     out <- matrix(0, nrow=length(r), ncol=length(c))
-    for (i in 1:length(r))
-        for (j in 1:length(c)) {
+    for (i in seq_along(r))
+        for (j in seq_along(c)) {
             a <- c[j] - r[i]
             out[i,j] <- uniroot(function(x, ...) fillfun(x, p) - a -x,
                                 c(0,1), p = p)$root

Modified: pkg/vegan/R/permustats.R
===================================================================
--- pkg/vegan/R/permustats.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/permustats.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -55,7 +55,7 @@
 
 `print.summary.permustats` <- function(x, ...) {
     m <- cbind("statistic" = x$statistic,
-               "z" = x$z,
+               "SES" = x$z,
                "mean" = x$means,
                x$quantile)
     cat("\n")

Modified: pkg/vegan/R/plot.cca.R
===================================================================
--- pkg/vegan/R/plot.cca.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/plot.cca.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -9,7 +9,7 @@
     if (!is.list(g))
         g <- list(default = g)
     ## Take care that there are names
-    for (i in seq_len(length(g))) {
+    for (i in seq_along(g)) {
         if (length(dim(g[[i]])) > 1)
             rownames(g[[i]]) <- rownames(g[[i]], do.NULL = FALSE,
                                          prefix = substr(names(g)[i], 1, 3))

Modified: pkg/vegan/R/plot.meandist.R
===================================================================
--- pkg/vegan/R/plot.meandist.R	2015-05-21 10:07:59 UTC (rev 2949)
+++ pkg/vegan/R/plot.meandist.R	2015-05-25 06:52:06 UTC (rev 2950)
@@ -13,24 +13,28 @@
         if (missing(ylim))
             ylim <- range(c(w, tr, root), na.rm = TRUE)
         plot(cl, ylim = ylim, leaflab = "none", axes = axes, ...)
-        for (i in 1:length(w)) segments(i, tr[i], i, w[i])
+        seqw <- seq_along(w)
+        for (i in seqw) {
+            segments(i, tr[i], i, w[i])
+        }
         pos <- ifelse(w < tr, 1, 3)
         pos[is.na(pos)] <- 1
         w[is.na(w)] <- tr[is.na(w)]
-        text(1:length(w), w, labels = labels(cl), pos = pos, srt = 0)
+        text(seqw, w, labels = labels(cl), pos = pos, srt = 0)
     } else {
         w <- diag(x)
+        seqw <- seq_along(w)
         tr <- rep(summary(x)$B, length(w))
         if (missing(ylim))
             ylim <- range(c(w, tr), na.rm = TRUE)
-        plot(1:length(w), tr, ylim = ylim, axes = FALSE, xlab = "", ylab = "",
+        plot(seqw, tr, ylim = ylim, axes = FALSE, xlab = "", ylab = "",
              type = "l", ...)
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/vegan -r 2950


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