79 lines
3.0 KiB
R
79 lines
3.0 KiB
R
## ---- message=FALSE-----------------------------------------------------------
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library(gapmap)
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## -----------------------------------------------------------------------------
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set.seed(1234)
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x <- rnorm(10, mean=rep(1:5, each=2), sd=0.4)
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y <- rnorm(10, mean=rep(c(1,2), each=5), sd=0.4)
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dataFrame <- data.frame(x=x, y=y, row.names=c(1:10))
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#calculate distance matrix. default is Euclidean distance
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distxy <- dist(dataFrame)
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#perform hierarchical clustering. default is complete linkage.
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hc <- hclust(distxy)
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dend <- as.dendrogram(hc)
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## ---- fig.width= 6.5, fig.height=6--------------------------------------------
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grey_scale =c("#333333", "#5C5C5C", "#757575", "#8A8A8A", "#9B9B9B", "#AAAAAA", "#B8B8B8", "#C5C5C5", "#D0D0D0", "#DBDBDB", "#E6E6E6")
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gapmap(m = as.matrix(distxy), d_row= rev(dend), d_col=dend, col = grey_scale)
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## ---- fig.width= 6.5, fig.height=6--------------------------------------------
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gapmap(m = as.matrix(distxy), d_row= rev(dend), d_col=dend, mode = "quantitative", mapping="linear", col = grey_scale)
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## ---- echo=FALSE, fig.width= 6.5, fig.height=6--------------------------------
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distances <-seq(0, 5, 0.1)
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data <- data.frame(distance=distances)
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s <- 0.5
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l <- data
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e <- data
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for(i in 1:nrow(data)){
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dist <- data$distance[i]
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linear <- map(dist, 0, 5, 0, 1)
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exp <- map.exp(dist, 0, 5, 0, 1, scale = s)
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#print(paste0("dist =", dist," linear=",linear, " exp=", exp))
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l$gap[i] = linear
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e$gap[i] = exp
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l$type[i] = "linear"
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e$type[i] = "exponential"
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}
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gaps <- rbind(l, e)
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ggplot(gaps, aes(x=gap, y=distance, group=type)) + geom_line(aes(color=type))+theme_bw()+ theme(legend.position= c(0.9,0.1))
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## ---- echo=FALSE, fig.width= 6.5, fig.height=6--------------------------------
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scales <- seq(0.1, 3, 0.3)
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distances <-seq(0, 5, 0.1)
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D = data.frame()
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for(j in 1:length(scales)){
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s <- scales[j]
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data <- data.frame(distance=distances)
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for(i in 1:nrow(data)){
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dist <- data$distance[i]
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exp <- map.exp(dist, 0, 5, 0, 1, scale = s)
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data$gap[i] = exp
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data$scale[i] = s
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}
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D <- rbind(D, data)
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}
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labels = data.frame()
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for(j in 1:length(scales)){
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a = 0
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b = 5
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c = 0
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d = 1
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y = 0.4 # x position
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x = scales[j]
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v = a + ((y/(d-c))^x) *(b-a)
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labels <- rbind(labels, data.frame(scale=x, distance =v, gap=y))
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}
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ggplot() + geom_line(data=D, aes(x=gap, y=distance, group=scale), color="#56B1F7")+ scale_y_continuous(limits = c(0,5))+
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geom_text(data= labels, aes(x=gap,y=distance, label=scale), hjust=-0.2, vjust=0) +
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geom_point(data= labels, aes(x=gap,y=distance)) +
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theme_bw() + theme(legend.position="none")
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## ---- fig.width= 6.5, fig.height=6--------------------------------------------
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gapmap(m = as.matrix(distxy), d_row= rev(dend), d_col=dend, mode = "threshold", row_threshold = 2, col_threshold = 2, col = grey_scale)
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## ---- fig.width= 6.5, fig.height=6--------------------------------------------
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library(dendsort);
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gapmap(m = as.matrix(distxy), d_row= rev(dendsort(dend)), d_col=dendsort(dend), mode = "quantitative", col = grey_scale)
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