How to customize lines in ggpairs [GGally]

I have the following plot:

在这里输入图像描述

Generated with this code:

library("GGally")
data(iris)
ggpairs(iris[, 1:4], lower=list(continuous="smooth", params=c(colour="blue")),
  diag=list(continuous="bar", params=c(colour="blue")), 
  upper=list(params=list(corSize=6)), axisLabels='show')

My questions are:

  • How can I change the correlation line to be red , now it's black.
  • And the correlation line is buried under the scatter plot. I want to put it on top. How can I do that?

  • I hope there is an easier way to do this, but this is a sort of brute force approach. It does give you flexibility to easily customize the plots further however. The main point is using putPlot to put a ggplot2 plot into the figure.

    library(ggplot2)
    
    ## First create combinations of variables and extract those for the lower matrix
    cols <- expand.grid(names(iris)[1:4], names(iris)[1:3])    
    cols <- cols[c(2:4, 7:8, 12),]  # indices will be in column major order
    
    ## These parameters are applied to each plot we create
    pars <- list(geom_point(alpha=0.8, color="blue"),              
                 geom_smooth(method="lm", color="red", lwd=1.1))
    
    ## Create the plots (dont need the lower plots in the ggpairs call)
    plots <- apply(cols, 1, function(cols)                    
        ggplot(iris[,cols], aes_string(x=cols[2], y=cols[1])) + pars)
    gg <- ggpairs(iris[, 1:4],
                  diag=list(continuous="bar", params=c(colour="blue")), 
                  upper=list(params=list(corSize=6)), axisLabels='show')
    
    ## Now add the new plots to the figure using putPlot
    colFromRight <- c(2:4, 3:4, 4)                                    
    colFromLeft <- rep(c(1, 2, 3), times=c(3,2,1))
    for (i in seq_along(plots)) 
        gg <- putPlot(gg, plots[[i]], colFromRight[i], colFromLeft[i])
    gg
    

    在这里输入图像描述

    ## If you want the slope of your lines to correspond to the 
    ## correlation, you can scale your variables
    scaled <- as.data.frame(scale(iris[,1:4]))
    fit <- lm(Sepal.Length ~ Sepal.Width, data=scaled)
    coef(fit)[2]
    # Sepal.Length 
    #  -0.1175698 
    
    ## This corresponds to Sepal.Length ~ Sepal.Width upper panel
    

    Edit

    To generalize to a function that takes any column indices and makes the same plot

    ## colInds is indices of columns in data.frame
    .ggpairs <- function(colInds, data=iris) {
        n <- length(colInds)
        cols <- expand.grid(names(data)[colInds], names(data)[colInds])
        cInds <- unlist(mapply(function(a, b, c) a*n+b:c, 0:max(0,n-2), 2:n, rep(n, n-1)))
        cols <- cols[cInds,]  # indices will be in column major order
    
        ## These parameters are applied to each plot we create
        pars <- list(geom_point(alpha=0.8, color="blue"),              
                     geom_smooth(method="lm", color="red", lwd=1.1))
    
        ## Create the plots (dont need the lower plots in the ggpairs call)
        plots <- apply(cols, 1, function(cols)                    
            ggplot(data[,cols], aes_string(x=cols[2], y=cols[1])) + pars)
        gg <- ggpairs(data[, colInds],
                      diag=list(continuous="bar", params=c(colour="blue")), 
                      upper=list(params=list(corSize=6)), axisLabels='show')
    
        rowFromTop <- unlist(mapply(`:`, 2:n, rep(n, n-1)))
        colFromLeft <- rep(1:(n-1), times=(n-1):1)
        for (i in seq_along(plots)) 
            gg <- putPlot(gg, plots[[i]], rowFromTop[i], colFromLeft[i])
        return( gg )
    }
    
    ## Example
    .ggpairs(c(1, 3))
    

    Check your version of GGally by packageVersion("GGally") and upgrade your GGally to version 1.0.1

    library("GGally")
    library("ggplot2")
    data(iris)
    
    lowerFn <- function(data, mapping, method = "lm", ...) {
      p <- ggplot(data = data, mapping = mapping) +
        geom_point(colour = "blue") +
        geom_smooth(method = method, color = "red", ...)
      p
    }
    
    ggpairs(
      iris[, 1:4], lower = list(continuous = wrap(lowerFn, method = "lm")),
      diag = list(continuous = wrap("barDiag", colour = "blue")),
      upper = list(continuous = wrap("cor", size = 10))
    )
    

    在这里输入图像描述

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