[Analogue-commits] r290 - in pkg: . inst man tests/Examples

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Wed Jan 2 15:10:44 CET 2013


Author: gsimpson
Date: 2013-01-02 15:10:44 +0100 (Wed, 02 Jan 2013)
New Revision: 290

Modified:
   pkg/DESCRIPTION
   pkg/NAMESPACE
   pkg/inst/ChangeLog
   pkg/man/mat.Rd
   pkg/tests/Examples/analogue-Ex.Rout.save
Log:
set up 0.10-0 release for CRAN

Modified: pkg/DESCRIPTION
===================================================================
--- pkg/DESCRIPTION	2012-12-23 19:12:15 UTC (rev 289)
+++ pkg/DESCRIPTION	2013-01-02 14:10:44 UTC (rev 290)
@@ -1,7 +1,7 @@
 Package: analogue
 Type: Package
 Title: Analogue and weighted averaging methods for palaeoecology
-Version: 0.9-11
+Version: 0.10-0
 Date: $Date$
 Depends: R (>= 2.15.0), stats, graphics, vegan (>= 1.17-12), lattice, grid, 
          MASS, princurve, mgcv

Modified: pkg/NAMESPACE
===================================================================
--- pkg/NAMESPACE	2012-12-23 19:12:15 UTC (rev 289)
+++ pkg/NAMESPACE	2013-01-02 14:10:44 UTC (rev 290)
@@ -29,6 +29,7 @@
        dissim,
        dissimilarities,
        distance,
+       distance3,
        fuse,
        getK,
        gradientDist,
@@ -79,6 +80,7 @@
 S3method(dissimilarities, mat)
 S3method(distance, default)
 S3method(distance, join)
+S3method(distance3, default)
 S3method(eigenvals, pcr)
 S3method(fuse, dist)
 S3method(fuse, matrix)

Modified: pkg/inst/ChangeLog
===================================================================
--- pkg/inst/ChangeLog	2012-12-23 19:12:15 UTC (rev 289)
+++ pkg/inst/ChangeLog	2013-01-02 14:10:44 UTC (rev 290)
@@ -1,5 +1,10 @@
 analogue Change Log
 
+Version 0.10-0
+
+	* Release: Version 0.9-11 plus a minor documentation fix
+	was released to CRAN 2 Jan 2013.
+
 Version 0.9-11
 
 	* Was loading compiled code both via the package namespace

Modified: pkg/man/mat.Rd
===================================================================
--- pkg/man/mat.Rd	2012-12-23 19:12:15 UTC (rev 289)
+++ pkg/man/mat.Rd	2013-01-02 14:10:44 UTC (rev 290)
@@ -279,7 +279,7 @@
 plot(ik.mat2)
 par(mfrow = c(1,1))
 
-## reconstruct for the RLGH core data
+## reconstruct for the V12.122 core data
 coreV12.mat2 <- predict(ik.mat, V12.122, k = 3)
 coreV12.mat2
 summary(coreV12.mat2)

Modified: pkg/tests/Examples/analogue-Ex.Rout.save
===================================================================
--- pkg/tests/Examples/analogue-Ex.Rout.save	2012-12-23 19:12:15 UTC (rev 289)
+++ pkg/tests/Examples/analogue-Ex.Rout.save	2013-01-02 14:10:44 UTC (rev 290)
@@ -1,5 +1,5 @@
 
-R version 2.15.1 Patched (2012-07-27 r60002) -- "Roasted Marshmallows"
+R version 2.15.2 Patched (2012-12-05 r61228) -- "Trick or Treat"
 Copyright (C) 2012 The R Foundation for Statistical Computing
 ISBN 3-900051-07-0
 Platform: x86_64-unknown-linux-gnu (64-bit)
@@ -24,14 +24,14 @@
 > library('analogue')
 Loading required package: vegan
 Loading required package: permute
-This is vegan 2.0-4
+This is vegan 2.0-5
 Loading required package: lattice
 Loading required package: grid
 Loading required package: MASS
 Loading required package: princurve
 Loading required package: mgcv
-This is mgcv 1.7-6. For overview type 'help("mgcv-package")'.
-This is analogue 0.9-10
+This is mgcv 1.7-22. For overview type 'help("mgcv-package")'.
+This is analogue 0.10-0
 > 
 > assign(".oldSearch", search(), pos = 'CheckExEnv')
 > cleanEx()
@@ -2330,6 +2330,79 @@
 > 
 > 
 > cleanEx()
+> nameEx("distance3")
+> ### * distance3
+> 
+> flush(stderr()); flush(stdout())
+> 
+> ### Name: distance3
+> ### Title: Flexibly calculate dissimilarity or distance measures
+> ### Aliases: distance3 distance3.default
+> ### Keywords: multivariate methods
+> 
+> ### ** Examples
+> 
+> ## simple example using dummy data
+> train <- data.frame(matrix(abs(runif(200)), ncol = 10))
+> rownames(train) <- LETTERS[1:20]
+> colnames(train) <- as.character(1:10)
+> fossil <- data.frame(matrix(abs(runif(100)), ncol = 10))
+> colnames(fossil) <- as.character(1:10)
+> rownames(fossil) <- letters[1:10]
+> 
+> ## calculate distances/dissimilarities between train and fossil
+> ## samples
+> test <- distance3(train, fossil)
+> test.o <- distance(train, fossil)
+> stopifnot(isTRUE(all.equal(test.o, test)))
+> 
+> ## using a different coefficient, chi-square distance
+> test <- distance3(train, fossil, method = "chi.distance")
+> test.o <- distance(train, fossil, method = "chi.distance")
+> stopifnot(isTRUE(all.equal(test.o, test)))
+> 
+> ## calculate pairwise distances/dissimilarities for training
+> ## set samples
+> ##test2 <- distance3(train)
+> 
+> ## Using distance on an object of class join
+> #dists <- distance3(join(train, fossil))
+> #str(dists)
+> 
+> ## calculate Gower's general coefficient for mixed data
+> ## first, make a couple of variables factors
+> fossil[,4] <- factor(sample(rep(1:4, length = 10), 10))
+> train[,4] <- factor(sample(rep(1:4, length = 20), 20))
+> ## now fit the mixed coefficient
+> test3 <- distance3(train, fossil, "mixed")
+> 
+> ## Example from page 260 of Legendre & Legendre (1998)
+> x1 <- t(c(2,2,NA,2,2,4,2,6))
+> x2 <- t(c(1,3,3,1,2,2,2,5))
+> Rj <- c(1,4,2,4,1,3,2,5) # supplied ranges
+> 
+> distance3(x1, x2, method = "mixed", R = Rj)
+          [,1]
+[1,] 0.3380952
+attr(,"method")
+[1] "mixed"
+attr(,"class")
+[1] "distance" "matrix"  
+> distance(x1, x2, method = "mixed", R = Rj)
+[1] 0.3380952
+attr(,"method")
+[1] "mixed"
+attr(,"class")
+[1] "distance" "matrix"  
+> 
+> ## note this gives 1 - 0.66 (not 0.66 as the answer in
+> ## Legendre & Legendre) as this is expressed as a
+> ## distance whereas Legendre & Legendre describe the
+> ## coefficient as similarity coefficient
+> 
+> 
+> 
+> cleanEx()
 > nameEx("fuse")
 > ### * fuse
 > 
@@ -4075,7 +4148,7 @@
 > plot(ik.mat2)
 > par(mfrow = c(1,1))
 > 
-> ## reconstruct for the RLGH core data
+> ## reconstruct for the V12.122 core data
 > coreV12.mat2 <- predict(ik.mat, V12.122, k = 3)
 > coreV12.mat2
 
@@ -4950,25 +5023,25 @@
 wa> ## residuals for the training set
 wa> residuals(mod4)
      V14.61     V17.196     V18.110     V16.227      V14.47      V23.22 
--3.89845110 -0.95914237 -0.57577610  0.83646773 -1.12654866  1.85855684 
+-3.89845110 -0.95914236 -0.57577610  0.83646773 -1.12654865  1.85855684 
       V2.12      V23.29      V12.43        R9.7      A157.3      V23.81 
- 4.93907447 -1.56332718  1.02901346 -2.01091600  0.72379238 -2.30397581 
+ 4.93907447 -1.56332718  1.02901346 -2.01091601  0.72379237 -2.30397582 
      V23.82      V12.53      V23.83      V12.56     A152.84      V16.50 
--1.16893885 -1.90464620  0.99721686 -1.39764003  1.29346295 -0.29234573 
+-1.16893886 -1.90464621  0.99721685 -1.39764003  1.29346294 -0.29234573 
     V22.122      V16.41       V4.32      V12.66     V19.245        V4.8 
- 2.13000056 -4.44031822 -0.92783840  0.99172654 -1.49152689  1.88724026 
+ 2.13000055 -4.44031821 -0.92783839  0.99172654 -1.49152688  1.88724027 
     A180.15      V18.34     V20.213     V19.222     A180.39     V16.189 
- 2.78850048 -0.63727536  0.33475037 -0.01275751 -1.65993109 -2.09930701 
+ 2.78850049 -0.63727536  0.33475038 -0.01275751 -1.65993108 -2.09930701 
      V12.18       V7.67     V17.165     V19.310     V16.190    A153.154 
--0.97538682  2.31383514  1.87380535  2.64327583  0.01900071  0.13747169 
+-0.97538682  2.31383515  1.87380536  2.64327583  0.01900072  0.13747169 
     V19.308     V22.172      V10.98     V22.219      V16.33     V22.204 
--0.26612390 -2.21647192  2.40270758  0.25826513 -1.69856608  0.20738893 
+-0.26612390 -2.21647192  2.40270759  0.25826513 -1.69856608  0.20738893 
     V20.167      V10.89      V12.79     V19.216      V14.90     A180.72 
 -0.92731700 -0.84954530 -0.55321548  0.80956624  0.66973330  0.70524398 
      V16.21     A180.76     V15.164     A180.78       V14.5      V3.128 
 -0.23696237 -0.14589252 -0.26826158  0.54819699 -0.32786314  1.64879299 
     A179.13       V9.31     V20.230       V20.7     V20.234      V18.21 
- 1.53212230  0.96958483  0.44047759 -0.17038549 -0.21308146 -0.39014885 
+ 1.53212229  0.96958483  0.44047759 -0.17038549 -0.21308146 -0.39014886 
     V12.122 
  0.72061292 
 > 
@@ -7124,25 +7197,25 @@
 > ## residuals for the training set
 > residuals(mod4)
      V14.61     V17.196     V18.110     V16.227      V14.47      V23.22 
--3.89845110 -0.95914237 -0.57577610  0.83646773 -1.12654866  1.85855684 
+-3.89845110 -0.95914236 -0.57577610  0.83646773 -1.12654865  1.85855684 
       V2.12      V23.29      V12.43        R9.7      A157.3      V23.81 
- 4.93907447 -1.56332718  1.02901346 -2.01091600  0.72379238 -2.30397581 
+ 4.93907447 -1.56332718  1.02901346 -2.01091601  0.72379237 -2.30397582 
      V23.82      V12.53      V23.83      V12.56     A152.84      V16.50 
--1.16893885 -1.90464620  0.99721686 -1.39764003  1.29346295 -0.29234573 
+-1.16893886 -1.90464621  0.99721685 -1.39764003  1.29346294 -0.29234573 
     V22.122      V16.41       V4.32      V12.66     V19.245        V4.8 
- 2.13000056 -4.44031822 -0.92783840  0.99172654 -1.49152689  1.88724026 
+ 2.13000055 -4.44031821 -0.92783839  0.99172654 -1.49152688  1.88724027 
     A180.15      V18.34     V20.213     V19.222     A180.39     V16.189 
- 2.78850048 -0.63727536  0.33475037 -0.01275751 -1.65993109 -2.09930701 
+ 2.78850049 -0.63727536  0.33475038 -0.01275751 -1.65993108 -2.09930701 
      V12.18       V7.67     V17.165     V19.310     V16.190    A153.154 
--0.97538682  2.31383514  1.87380535  2.64327583  0.01900071  0.13747169 
+-0.97538682  2.31383515  1.87380536  2.64327583  0.01900072  0.13747169 
     V19.308     V22.172      V10.98     V22.219      V16.33     V22.204 
--0.26612390 -2.21647192  2.40270758  0.25826513 -1.69856608  0.20738893 
+-0.26612390 -2.21647192  2.40270759  0.25826513 -1.69856608  0.20738893 
     V20.167      V10.89      V12.79     V19.216      V14.90     A180.72 
 -0.92731700 -0.84954530 -0.55321548  0.80956624  0.66973330  0.70524398 
      V16.21     A180.76     V15.164     A180.78       V14.5      V3.128 
 -0.23696237 -0.14589252 -0.26826158  0.54819699 -0.32786314  1.64879299 
     A179.13       V9.31     V20.230       V20.7     V20.234      V18.21 
- 1.53212230  0.96958483  0.44047759 -0.17038549 -0.21308146 -0.39014885 
+ 1.53212229  0.96958483  0.44047759 -0.17038549 -0.21308146 -0.39014886 
     V12.122 
  0.72061292 
 > 
@@ -7292,7 +7365,7 @@
 > ### * <FOOTER>
 > ###
 > cat("Time elapsed: ", proc.time() - get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed:  15.918 0.228 16.336 0 0 
+Time elapsed:  22.741 0.267 23.803 0 0 
 > grDevices::dev.off()
 null device 
           1 



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