我正在关注这个示例R，了解如何使用带有's 的树状图创建集群热图plotly。这是示例：
library(ggplot2)
library(ggdendro)
library(plotly)
#dendogram data
x <- as.matrix(scale(mtcars))
dd.col <- as.dendrogram(hclust(dist(x)))
dd.row <- as.dendrogram(hclust(dist(t(x))))
dx <- dendro_data(dd.row)
dy <- dendro_data(dd.col)
# helper function for creating dendograms
ggdend <- function(df) {
ggplot() +
geom_segment(data = df, aes(x=x, y=y, xend=xend, yend=yend)) +
labs(x = "", y = "") + theme_minimal() +
theme(axis.text = element_blank(), axis.ticks = element_blank(),
panel.grid = element_blank())
}
# x/y dendograms
px <- ggdend(dx$segments)
py <- ggdend(dy$segments) + coord_flip()
# heatmap
col.ord <- order.dendrogram(dd.col)
row.ord <- order.dendrogram(dd.row)
xx <- scale(mtcars)[col.ord, row.ord]
xx_names <- attr(xx, "dimnames")
df <- as.data.frame(xx)
colnames(df) <- xx_names[[2]]
df$car <- xx_names[[1]]
df$car <- with(df, factor(car, levels=car, ordered=TRUE))
mdf <- reshape2::melt(df, id.vars="car")
p <- ggplot(mdf, aes(x = variable, y = car)) + geom_tile(aes(fill = value))
mat <- matrix(unlist(dplyr::select(df,-car)),nrow=nrow(df))
colnames(mat) <- colnames(df)[1:ncol(df)-1]
rownames(mat) <- rownames(df)
# hide axis ticks and grid lines
eaxis <- list(
showticklabels = FALSE,
showgrid = FALSE,
zeroline = FALSE
)
p_empty <- plot_ly(filename="r-docs/dendrogram") %>%
# note that margin applies to entire plot, so we can
# add it here to make tick labels more readable
layout(margin = list(l = 200),
xaxis = eaxis,
yaxis = eaxis)
subplot(px, p_empty, p, py, nrows = 2, margin = 0.01)
这使：
我稍微更改了代码，以便在我的情况下生成热图，plotly而不是ggplot因为它在我的真实大数据上运行得更快，因此我这样做：
heatmap.plotly <- plot_ly() %>% add_heatmap(z=~mat,x=factor(colnames(mat),lev=colnames(mat)),y=factor(rownames(mat),lev=rownames(mat)))
接着：
subplot(px, p_empty, heatmap.plotly, py, nrows = 2, margin = 0.01)
这使：
我的问题是：
如何让热图的行和列标签不会像在两个图中那样被截断？
在第二个图中，着色器的标签更改为“mat”。知道如何防止这种情况吗？
如何更改热图和树状图之间的边距？
