我如何使用 colnames 作为chart.Correlation 的标签，如 corrplot

Question

I love the correlation plot from chart.Correlation but for multiple columns the names aren't readable and the values from the single correlation plots aren't that important anymore. So is there a way to define the labels in chart.Correlation to how they are in corrplot?

library(corrplot)
library(xts)
library(PerformanceAnalytics)

dat <- xts(matrix(rnorm(1000), ncol = 4), order.by = as.Date(1:250))
colnames(dat) <- c("Name1", "Name2", "Name3", "Name4")

cor <- cor(dat)
corrplot(cor, method = "number")
chart.Correlation(dat)

Update:

I got the solution for some of it but i am stuck with the alignment of mtext()

custom.chart.Correlation <- function (R, histogram = TRUE, method = c("pearson", "kendall", 
                                          "spearman"), ...) 
{
  x = checkData(R, method = "matrix")
  if (missing(method)) 
    method = method[1]
  panel.cor <- function(x, y, digits = 2, prefix = "", 
                        use = "pairwise.complete.obs", method = "pearson", 
                        cex.cor = 1, ...) {
    usr <- par("usr")
    on.exit(par(usr))
    par(usr = c(0, 1, 0, 1))
    r <- cor(x, y, use = use, method = method)
    txt <- format(c(round(r,2), 0.123456789), digits = digits)[1]
    txt <- paste(prefix, txt, sep = "")
    if (missing(cex.cor)) 
      cex.cor <- 0.8/strwidth(txt)
    test <- cor.test(as.numeric(x), as.numeric(y), method = method)
    # Signif <- symnum(test$p.value, corr = FALSE, na = FALSE, 
    #                  cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1), symbols = c("***", 
    #                                                                           "**", "*", ".", " "))
    #Create a function to generate a continuous color palette
    rbPal <- colorRampPalette(c('red','blue'))
    text(0.5, 0.5, txt, cex = cex.cor, col = rbPal(100)[as.numeric(abs(r)*100)])
    # text(0.8, 0.8, Signif, cex = cex, col = 2)
  }
  f <- function(t) {
    dnorm(t, mean = mean(x), sd = sd.xts(x))
  }
  dotargs <- list(...)
  dotargs$method <- NULL
  rm(method)
  hist.panel = function(x, ... = NULL) {
    par(new = TRUE)
    hist(x, col = "light gray", probability = TRUE, 
         axes = FALSE, main = "", breaks = "FD")
    lines(density(x, na.rm = TRUE), col = "red", lwd = 1)
    rug(x)
  }
  if (histogram) 
    pairs(x, gap = 0, lower.panel = panel.smooth, upper.panel = panel.cor, 
          diag.panel = hist.panel, ...)
  else pairs(x, gap = 0, lower.panel = panel.smooth, upper.panel = panel.cor, ...)
  size = (par("usr")[2] - par("usr")[1])/1.08
  start <- par("usr")[1] + 0.04*size
  end <- par("usr")[2] - 0.04*size
  at <- seq(0.04, 1-0.04, length.out = ncol(R)+2)
  mtext(colnames(R), side = 3, at[2:ncol(R)+1] = at, cex = 0.5, las = 2)
}

custom.chart.Correlation(dat, pch = ".", cex.cor = 1, yaxt = 'n', xaxt = 'n', labels = "")

The real world example:

Answer 1

It is doable with a different package to create the plot. GGally uses lots of ggplot features.

library(GGally)
lowerFn <- function(data, mapping, method = "lm", ...) {
  p <- ggplot(data = data, mapping = mapping) +
    geom_point(colour = "black") +
    geom_smooth(method = method, color = "red", ...)
  p
}


ggpairs(dat, lower=list(continuous = wrap(lowerFn, method = "lm")),
        upper = list(continuous = "cor"),
        diag=list(discrete= "barDiag"), 
        axisLabels='none') +
  theme_bw() +
  theme(strip.text = element_text(angle=90, hjust=1),
        strip.background = element_rect(fill = NA),
        strip.text.y = element_blank(),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank())

Results in your prefered corrolationmatrix with the labels as in the corrplot. For a nice example also see this question