[Vegan-commits] r2892 - in pkg/vegan: R man tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Fri Oct 3 15:15:29 CEST 2014
Author: jarioksa
Date: 2014-10-03 15:15:29 +0200 (Fri, 03 Oct 2014)
New Revision: 2892
Removed:
pkg/vegan/man/scores.hclust.Rd
Modified:
pkg/vegan/R/permutest.betadisper.R
pkg/vegan/man/reorder.hclust.Rd
pkg/vegan/tests/Examples/vegan-Ex.Rout.save
Log:
Squashed commit of the following:
commit fba9b24cc98f984254544db5cd87cdb224098588
Author: Gavin Simpson <ucfagls at gmail.com>
Date: Thu Oct 2 23:16:46 2014 -0600
Update test example output
commit 8d70932789980c484b108c14f7166f0bac24f3ff
Merge: 8086446 a439b75
Author: Gavin Simpson <ucfagls at gmail.com>
Date: Thu Oct 2 22:43:57 2014 -0600
Merge pull request #45 from jarioksa/fix-no-of-permutations-in-permutest.beadisper
@jarioksa has convinced me of the benefits of treating permutations following Phipson, B. & Smyth, G. K. Permutation P-values should never be zero: calculating exact P-values when permutations are randomly drawn. Stat. Appl. Genet. Mol. Biol. 9, Article39 (2010). permutest.betadisper: no. of permutations counted without observed stat
commit 8086446245adb253f6cf8bbd749c21195dff2dc8
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date: Thu Oct 2 16:34:17 2014 +0300
update tests/Examples
commit a439b751ed64b32c1234a6993c726153f8f8f6cf
Author: Jari Oksanen <jari.oksanen at oulu.fi>
Date: Fri Sep 26 12:00:39 2014 +0300
permutest.betadisper: no. of permutations counted without observed stat
Although we put the observed value among permutations, the number
of permutations should be given without that observed statistic
(like done in all other vegan functions).
Modified: pkg/vegan/R/permutest.betadisper.R
===================================================================
--- pkg/vegan/R/permutest.betadisper.R 2014-10-02 05:24:17 UTC (rev 2891)
+++ pkg/vegan/R/permutest.betadisper.R 2014-10-03 13:15:29 UTC (rev 2892)
@@ -131,7 +131,7 @@
pairwise <- NULL
}
- retval <- cbind(mod.aov[, 1:4], c(nperm + 1, NA), c(pval, NA))
+ retval <- cbind(mod.aov[, 1:4], c(nperm, NA), c(pval, NA))
dimnames(retval) <- list(c("Groups", "Residuals"),
c("Df", "Sum Sq", "Mean Sq", "F", "N.Perm",
"Pr(>F)"))
Modified: pkg/vegan/man/reorder.hclust.Rd
===================================================================
--- pkg/vegan/man/reorder.hclust.Rd 2014-10-02 05:24:17 UTC (rev 2891)
+++ pkg/vegan/man/reorder.hclust.Rd 2014-10-03 13:15:29 UTC (rev 2892)
@@ -1,6 +1,7 @@
\name{reorder.hclust}
\alias{reorder.hclust}
\alias{rev.hclust}
+\alias{scores.hclust}
\title{
Reorder a Hierarchical Clustering Tree
@@ -21,6 +22,7 @@
\method{reorder}{hclust}(x, wts,
agglo.FUN = c("mean", "min", "max", "sum", "uwmean"), ...)
\method{rev}{hclust}(x)
+\method{scores}{hclust}(x, display = "internal", ...)
}
\arguments{
@@ -33,6 +35,10 @@
\item{agglo.FUN}{
a function for weights agglomeration, see below.
}
+ \item{display}{
+ return \code{"internal"} nodes or \code{"terminal"} nodes (also
+ called \code{"leaves"}).
+}
\item{\dots}{
additional arguments (ignored).
}
@@ -55,8 +61,13 @@
The function accepts only a limited list of \code{agglo.FUN}
functions for assessing the value of \code{wts} for groups. The
ordering is always ascending, but the order of leaves can be
- reversed with \code{rev}.
+ reversed with \code{rev}.
+ Function \code{scores} finds the coordinates of nodes as a two-column
+ matrix. For terminal nodes (leaves) this the value at which the item
+ is merged to the tree, and the labels can still \code{hang} below this
+ level (see \code{\link{plot.hclust}}).
+
}
\value{
@@ -81,11 +92,18 @@
alternative implementation.
}
\examples{
+## reorder by water content of soil
data(mite, mite.env)
hc <- hclust(vegdist(wisconsin(sqrt(mite))))
ohc <- with(mite.env, reorder(hc, WatrCont))
plot(hc)
plot(ohc)
+
+## label leaves by the observed value, and each branching point
+## (internal node) by the cluster mean
+with(mite.env, plot(ohc, labels=round(WatrCont), cex=0.7))
+ordilabel(scores(ohc), label=round(ohc$value), cex=0.7)
+
## Slightly different from reordered 'dendrogram' which ignores group
## sizes in assessing means.
den <- as.dendrogram(hc)
Deleted: pkg/vegan/man/scores.hclust.Rd
===================================================================
--- pkg/vegan/man/scores.hclust.Rd 2014-10-02 05:24:17 UTC (rev 2891)
+++ pkg/vegan/man/scores.hclust.Rd 2014-10-03 13:15:29 UTC (rev 2892)
@@ -1,70 +0,0 @@
-\name{scores.hclust}
-\alias{scores.hclust}
-
-\title{
- Coordinates of Leaves and Internal Nodes in a hclust Tree
-}
-
-\description{ The function finds the coordinates that will be used for
- internal nodes and leaves when an \code{\link{hclust}} object is
- plotted. These help in annotating the plotted dendrogram. }
-
-\usage{
-\method{scores}{hclust}(x, display = "internal", ...)
-}
-
-\arguments{
- \item{x}{
- An \code{\link{hclust}} result object.
-}
- \item{display}{
- Return \code{"internal"} nodes or \code{"terminal"} nodes (also
- called \code{"leaves"}.
-}
- \item{\dots}{
- Other arguments passed to the function (ignored).
-}
-}
-
-\details{
-
- The function returns the coordinates of nodes in an
- \code{\link{hclust}} plot as two-column matrix. First column called
- \code{x} gives the horizontal coordinates which for \eqn{n} terminal
- nodes (leaves) is an integer sequence \eqn{1..n}. The second column
- called \code{height} gives the merge value. For terminal nodes
- (leaves) this the value at which the item is merged to the tree, and
- in plots the labels can still hang below this level, as defined by
- the argument \code{hang} in \code{\link{plot.hclust}}.
-
- The function only works with \code{\link{hclust}} objects; it does
- not work with \code{\link{dendrogram}}.
-
-}
-
-\value{
- A two-column matrix of coordinates.
-}
-
-\author{
- Jari Oksanen.
-}
-
-\note{
- This function may be removed as useless.
-}
-
-
-\seealso{
- \code{\link{hclust}}, \code{\link{plot.hclust}}.
-}
-\examples{
-## Show values that were used in reordering a tree
-data(mite, mite.env)
-hc <- hclust(vegdist(mite))
-hc <- with(mite.env, reorder(hc, WatrCont))
-with(mite.env, plot(hc, labels=round(WatrCont), cex=0.7))
-ordilabel(scores(hc), label=round(hc$value), cex=0.7)
-}
-\keyword{ multivariate }
-
Modified: pkg/vegan/tests/Examples/vegan-Ex.Rout.save
===================================================================
--- pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2014-10-02 05:24:17 UTC (rev 2891)
+++ pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2014-10-03 13:15:29 UTC (rev 2892)
@@ -1,5 +1,5 @@
-R Under development (unstable) (2014-09-30 r66697) -- "Unsuffered Consequences"
+R version 3.1.1 Patched (2014-09-17 r66626) -- "Sock it to Me"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: x86_64-unknown-linux-gnu (64-bit)
@@ -160,7 +160,7 @@
Formula:
y ~ poly(x1, 1) + poly(x2, 1)
-<environment: 0x640f490>
+<environment: 0x7448210>
Total model degrees of freedom 3
REML score: -3.185099
@@ -1098,7 +1098,7 @@
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
-Groups 1 0.07931 0.079306 4.6156 100 0.04 *
+Groups 1 0.07931 0.079306 4.6156 99 0.04 *
Residuals 22 0.37801 0.017182
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
@@ -1255,7 +1255,7 @@
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
-Groups 1 0.039979 0.039979 2.4237 100 0.19
+Groups 1 0.039979 0.039979 2.4237 99 0.19
Residuals 18 0.296910 0.016495
> anova(mod2)
Analysis of Variance Table
@@ -1298,7 +1298,7 @@
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
-Groups 1 0.033468 0.033468 3.1749 100 0.1
+Groups 1 0.033468 0.033468 3.1749 99 0.1
Residuals 18 0.189749 0.010542
> anova(mod3)
Analysis of Variance Table
@@ -1556,8 +1556,6 @@
> ## Avoid negative eigenvalues with additive constant
> capscale(varespec ~ N + P + K + Condition(Al), varechem,
+ dist="bray", add =TRUE)
-Warning in cmdscale(X, k = k, eig = TRUE, add = add) :
- only 22 of the first 23 eigenvalues are > 0
Call: capscale(formula = varespec ~ N + P + K + Condition(Al), data =
varechem, distance = "bray", add = TRUE)
@@ -3667,7 +3665,7 @@
Run 6 stress 0.107471
Run 7 stress 0.1067169
... New best solution
-... procrustes: rmse 4.525314e-06 max resid 1.281822e-05
+... procrustes: rmse 4.525315e-06 max resid 1.281822e-05
*** Solution reached
> sol
@@ -4833,38 +4831,20 @@
Call: mite.hel ~ WatrCont + Shrub + Substrate + Topo
R2.adjusted
-<All variables> 0.4367038
+ SubsDens 0.4367038
+<All variables> 0.4367038
<none> 0.4004249
- Topo 0.3653551
- Shrub 0.3591790
- Substrate 0.3525851
- WatrCont 0.3145444
- Df AIC F Pr(>F)
-+ SubsDens 1 -94.489 4.7999 0.002 **
----
-Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-
-Step: R2.adj= 0.4367038
-Call: mite.hel ~ WatrCont + Shrub + Substrate + Topo + SubsDens
-
- R2.adjusted
-<All variables> 0.4367038
-<none> 0.4367038
-- Shrub 0.4079297
-- SubsDens 0.4004249
-- Substrate 0.3951235
-- Topo 0.3901844
-- WatrCont 0.3357858
-
> step.res$anova # Summary table
R2.adj Df AIC F Pr(>F)
+ WatrCont 0.26085 1 -84.336 25.3499 0.002 **
+ Shrub 0.31775 2 -88.034 3.8360 0.002 **
+ Substrate 0.36536 6 -87.768 1.8251 0.002 **
+ Topo 0.40042 1 -90.924 4.5095 0.004 **
-+ SubsDens 0.43670 1 -94.489 4.7999 0.002 **
<All variables> 0.43670
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
@@ -4902,7 +4882,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "tp", fx = FALSE)
-<environment: 0xa8e2d20>
+<environment: 0x975bfa8>
Estimated degrees of freedom:
5.63 total = 6.63
@@ -4919,7 +4899,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "tp", fx = FALSE)
-<environment: 0xa0f4ee0>
+<environment: 0x89d2290>
Estimated degrees of freedom:
6.45 total = 7.45
@@ -4950,7 +4930,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "tp", fx = FALSE)
-<environment: 0x9fe1070>
+<environment: 0x8fb08f0>
Estimated degrees of freedom:
5.63 total = 6.63
@@ -4965,7 +4945,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "ts", fx = FALSE)
-<environment: 0x9c8d8d0>
+<environment: 0x78c4998>
Estimated degrees of freedom:
4.43 total = 5.43
@@ -4981,7 +4961,7 @@
> ## or via plot.gam directly
> library(mgcv)
Loading required package: nlme
-This is mgcv 1.8-2. For overview type 'help("mgcv-package")'.
+This is mgcv 1.8-3. For overview type 'help("mgcv-package")'.
> plot.gam(fit, cex = 2, pch = 1, col = "blue")
> ## 'col' effects all objects drawn...
>
@@ -4994,7 +4974,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "ds", fx = FALSE)
-<environment: 0x9eb7d88>
+<environment: 0x9fe91d8>
Estimated degrees of freedom:
5.63 total = 6.63
@@ -5010,7 +4990,7 @@
Formula:
y ~ s(x1, x2, k = 4, bs = "tp", fx = TRUE)
-<environment: 0xaac1348>
+<environment: 0x90fa158>
Estimated degrees of freedom:
3 total = 4
@@ -5027,7 +5007,7 @@
Formula:
y ~ te(x1, x2, k = c(4, 4), bs = c("cr", "cr"), fx = c(FALSE,
FALSE))
-<environment: 0xaa638d0>
+<environment: 0x89ebcd0>
Estimated degrees of freedom:
2.99 total = 3.99
@@ -5046,7 +5026,7 @@
Formula:
y ~ te(x1, x2, k = c(3, 4), bs = c("cs", "cs"), fx = c(TRUE,
TRUE))
-<environment: 0xa8be370>
+<environment: 0x99a2720>
Estimated degrees of freedom:
11 total = 12
@@ -5187,7 +5167,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "tp", fx = FALSE)
-<environment: 0x8b3ea98>
+<environment: 0xa7534d8>
Estimated degrees of freedom:
8.71 total = 9.71
@@ -5200,7 +5180,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "tp", fx = FALSE)
-<environment: 0xa93f6e8>
+<environment: 0x8b20660>
Estimated degrees of freedom:
7.18 total = 8.18
@@ -5213,7 +5193,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "tp", fx = FALSE)
-<environment: 0x9785868>
+<environment: 0xb43c2c8>
Estimated degrees of freedom:
8.32 total = 9.32
@@ -5543,7 +5523,7 @@
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
-Groups 1 0.07931 0.079306 4.6156 100 0.04 *
+Groups 1 0.07931 0.079306 4.6156 99 0.04 *
Residuals 22 0.37801 0.017182
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
@@ -6003,8 +5983,8 @@
[2,] 0.1154641 0.9933117
Translation of averages:
- [,1] [,2]
-[1,] 3.038945e-17 1.218602e-17
+ [,1] [,2]
+[1,] -3.278601e-18 9.393617e-18
Scaling of target:
[1] 0.6727804
@@ -6218,16 +6198,23 @@
>
> ### Name: reorder.hclust
> ### Title: Reorder a Hierarchical Clustering Tree
-> ### Aliases: reorder.hclust rev.hclust
+> ### Aliases: reorder.hclust rev.hclust scores.hclust
> ### Keywords: multivariate
>
> ### ** Examples
>
+> ## reorder by water content of soil
> data(mite, mite.env)
> hc <- hclust(vegdist(wisconsin(sqrt(mite))))
> ohc <- with(mite.env, reorder(hc, WatrCont))
> plot(hc)
> plot(ohc)
+>
+> ## label leaves by the observed value, and each branching point
+> ## (internal node) by the cluster mean
+> with(mite.env, plot(ohc, labels=round(WatrCont), cex=0.7))
+> ordilabel(scores(ohc), label=round(ohc$value), cex=0.7)
+>
> ## Slightly different from reordered 'dendrogram' which ignores group
> ## sizes in assessing means.
> den <- as.dendrogram(hc)
@@ -6281,28 +6268,6 @@
>
>
> cleanEx()
-> nameEx("scores.hclust")
-> ### * scores.hclust
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: scores.hclust
-> ### Title: Coordinates of Leaves and Internal Nodes in a hclust Tree
-> ### Aliases: scores.hclust
-> ### Keywords: multivariate
->
-> ### ** Examples
->
-> ## Show values that were used in reordering a tree
-> data(mite, mite.env)
-> hc <- hclust(vegdist(mite))
-> hc <- with(mite.env, reorder(hc, WatrCont))
-> with(mite.env, plot(hc, labels=round(WatrCont), cex=0.7))
-> ordilabel(scores(hc), label=round(hc$value), cex=0.7)
->
->
->
-> cleanEx()
> nameEx("screeplot.cca")
> ### * screeplot.cca
>
@@ -7146,7 +7111,7 @@
Anthodor 1.0199113 7.575379e-01
Bellpere 1.1104145 9.067794e-01
Bromhord 1.0381512 5.515502e-01
-Chenalbu 0.6033850 6.883383e-15
+Chenalbu 0.6033850 3.996803e-15
Cirsarve 1.3186022 1.010898e-09
Comapalu 2.1945688 5.677653e-01
Eleopalu 1.7007903 8.292822e-01
@@ -7859,7 +7824,7 @@
Formula:
y ~ s(x1, x2, k = 10, bs = "tp", fx = FALSE)
-<environment: 0x926b0a0>
+<environment: 0xb0f94a8>
Estimated degrees of freedom:
1.28 total = 2.28
@@ -8381,13 +8346,13 @@
> ## Eigevalues are numerically similar
> ca$CA$eig - ord$eig
CA1 CA2 CA3 CA4 CA5
- 2.220446e-16 -1.276756e-15 -1.054712e-15 1.942890e-16 1.387779e-16
+ 1.110223e-16 -6.106227e-16 2.775558e-16 -1.110223e-16 2.775558e-16
CA6 CA7 CA8 CA9 CA10
- 1.387779e-16 -1.387779e-17 -1.387779e-16 2.359224e-16 2.775558e-17
+-2.775558e-17 -1.387779e-16 -2.636780e-16 1.942890e-16 -6.938894e-18
CA11 CA12 CA13 CA14 CA15
- 1.387779e-16 0.000000e+00 3.469447e-17 2.775558e-17 1.561251e-17
+ 1.387779e-16 4.857226e-17 7.632783e-17 3.469447e-18 1.734723e-17
CA16 CA17 CA18 CA19
- 0.000000e+00 1.734723e-18 1.127570e-17 1.196959e-16
+ 0.000000e+00 -1.734723e-18 -2.602085e-17 4.336809e-18
> ## Configurations are similar when site scores are scaled by
> ## eigenvalues in CA
> procrustes(ord, ca, choices=1:19, scaling = 1)
@@ -8415,7 +8380,7 @@
> ###
> options(digits = 7L)
> base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed: 34.698 8.183 40.373 0 0
+Time elapsed: 104.001 1.198 105.469 0 0
> grDevices::dev.off()
null device
1
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