Description Usage Arguments Value Examples

`dendsort`

sorts a dendrogram object which is
typically a result of hierarchical clustering (hclust). The
subtrees in the resulting dendrogram are sorted based on the
average distance of subtrees at every merging point. The
tighter cluster, in other words the cluster with smaller
average distance, is placed on the left side of branch.
When a leaf merge with a cluster, the leaf is placed on the
right side.

1 |

`d` |
a dendrogram or hclust object. |

`isReverse` |
logical indicating if the order should be reversed.Defaults to FALSE |

`type` |
character indicating the type of sorting. Default to "min" |

output A sorted dendrogram or hclust.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ```
#generate sample data
set.seed(1234); par(mar=c(0,0,0,0))
x <- rnorm(10, mean=rep(1:5, each=2), sd=0.4)
y <- rnorm(10, mean=rep(c(1,2), each=5), sd=0.4)
dataFrame <- data.frame(x=x, y=y, row.names=c(1:10))
#calculate Euclidian distance
distxy <- dist(dataFrame)
#hierachical clustering "complete" linkage by default
hc <- hclust(distxy)
#sort dendrogram
dd <- dendsort(as.dendrogram(hc))
hc_sorted <- as.hclust(dd)
#sort in reverse, you can also pass hclust object
plot(dendsort(hc, isReverse=TRUE))
#sort by average distance
plot(dendsort(hc, type="average"))
#plot the result
par(mfrow = c(1, 3), mai=c(0.8,0.8,2,0.8))
plot(x, y, col="gray", pch=19, cex=2)
text(x, y, labels=as.character(1:10), cex=0.9)
plot(hc,main="before sorting", xlab="", sub="")
plot(hc_sorted, main="after sorting", xlab="", sub="")
``` |

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