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en:hier-agglom_examples_rscript

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+ | <code rsplus> | ||

+ | library (vegan) | ||

+ | data (BCI) # example using Baro Colorado data | ||

+ | BCI.log <- log1p (BCI) # first, log transform species data, which contains numbers of individuals | ||

+ | bc.dist <- vegdist (BCI.log, method = 'bray') | ||

+ | bc.dist | ||

+ | print (bc.dist, diag = TRUE) | ||

+ | #install.packages ('cluster') # install if necessary | ||

+ | library (cluster) | ||

+ | clust <- agnes (sqrt (bc.dist), method = 'ward.D2') # calculate Ward's algorithm | ||

+ | # on square-rooted Bray-Curtis distances | ||

+ | plot (clust, which = 2) | ||

+ | rect.hclust (clust, 5, border = 1:5) | ||

+ | groups <- cutree (clust, k = 5) | ||

+ | groups | ||

+ | BCI.env <- read.delim ('https://raw.githubusercontent.com/zdealveindy/anadat-r/master/data/bci.env.txt') | ||

+ | plot (UTM.NS ~ UTM.EW, data = BCI.env, pch = groups, cex = 3) # this is the simple version, only with symbols differentiating individual groups | ||

+ | plot (UTM.NS ~ UTM.EW, data = BCI.env, pch = groups+20, cex = 3, bg = groups, col = 'white') # this is more "colorful" option. Note that symbols now are 21 to 25, arguments 'bg' and 'col' which | ||

+ | |||

+ | # First, NMDS with Bray-Curtis distances | ||

+ | NMDS <- metaMDS (sqrt (vegdist (BCI.log))) # note that I could use also "NMDS <- metaMDS (sqrt (bc.dist))" here | ||

+ | par (mfrow = c(1,2)) # I want to plot both plots into one figure, with two panels in one row | ||

+ | ordiplot (NMDS, type = 'n') | ||

+ | points (NMDS, pch = groups, col = groups) | ||

+ | legend ('topright', pch = 1:5, col = 1:5, legend = 1:5) | ||

+ | |||

+ | # Second, DCA ordination (implicitly using chi-square distance) | ||

+ | DCA <- decorana (BCI.log) | ||

+ | ordiplot (DCA, type = 'n', display = 'si') | ||

+ | points (DCA, pch = groups, col = groups) | ||

+ | legend ('topright', pch = 1:5, col = 1:5, legend = 1:5,) | ||

+ | </code> |

en/hier-agglom_examples_rscript.txt · Last modified: 2018/04/09 15:23 (external edit)