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r - ggpairs 图与相关值的热图,具有重要的星星和自定义主题

转载 作者:行者123 更新时间:2023-12-03 23:06:38 30 4
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我想用 ggPairs() 创建一个相关图,它应该包含

  • 相关值的热图 ( as in this SO question )
  • 相关性的重要星 ( as in this SO question )
  • 字体类型和字体大小根据自定义主题。

  • 基于@user20650 为上述 SO 问题提供的出色解决方案,我成功构建了一个函数来生成具有重要星的相关值的热图。

    不幸的是,当添加(自定义)主题时,彩色的 panel.backgrounds 被删除(下面提供了 MWE)。

    enter image description here

    移动电源
    library(ggplot2)
    library(GGally)
    # fct. to create heatmap of correlation values with significance stars for upper triangle of ggpairs plot
    cor_fun <- function(data, mapping, method="pearson", use="pairwise", ndp=2, sz=5, stars=TRUE, ...){

    # grab data
    x <- eval_data_col(data, mapping$x)
    y <- eval_data_col(data, mapping$y)

    # calculate correlation: for significance stars
    corr <- cor.test(x, y, method=method)
    est <- corr$estimate
    lb.size <- sz* abs(est)

    # get significance stars
    if(stars){
    stars <- c("***", "**", "*", "")[findInterval(corr$p.value, c(0, 0.001, 0.01, 0.05, 1))]
    lbl <- paste0(round(est, ndp), stars)
    }else{
    lbl <- round(est, ndp)
    }

    # calculate correlation: for colored tiles
    corr <- cor(x, y, method=method, use=use)

    # calculate color based on correlation value
    # corr = -1 => blue,
    # corr = 0 => white,
    # corr = +1 => red,
    colFn <- colorRampPalette(c("blue", "white", "red"), interpolate ='spline')
    fill <- colFn(100)[findInterval(corr, seq(-1, 1, length=100))]

    ggplot(data = data, mapping = mapping, ...) +
    theme_void() +
    annotate("text",
    x=mean(x, na.rm=TRUE),
    y=mean(y, na.rm=TRUE),
    label=lbl,
    size=lb.size,
    ...) +
    theme(panel.background = element_rect(fill=fill, # to fill background of panel with color
    colour=NA), # to remove border of panel
    panel.grid.major = element_blank())
    }

    sample_df <- iris[,1:3]
    ggpairs(sample_df,
    # LOWER TRIANGLE ELEMENTS: add line with smoothing; make points transparent and smaller
    lower=list(continuous=wrap("smooth", colour="darkgreen", alpha = 0.3, size=0.8)),
    # DIAGONAL ELEMENTS: histograms instead of smooothed density
    diag=list(continuous=wrap("barDiag", fill="grey")),
    # UPPER TRIANGLE ELEMENTS: use new fct. to create heatmap of correlation values with significance stars
    upper=list(continuous=cor_fun)
    ) + theme_minimal(base_size=12, base_family="Lato Light")

    最佳答案

    基于@user20650 的评论,我找到了一个解决方案,我想与遇到类似困难的其他人分享:

    library(ggplot2)
    library(GGally)
    theme_lato <- theme_minimal(base_size=10, base_family="Lato Light")

    ggpairs(sample_df,
    # LOWER TRIANGLE ELEMENTS: add line with smoothing; make points transparent and smaller
    lower = list(continuous = function(...)
    ggally_smooth(..., colour="darkgreen", alpha = 0.3, size=0.8) + theme_lato),
    # DIAGONAL ELEMENTS: histograms
    diag = list(continuous = function(...)
    ggally_barDiag(..., fill="grey") + theme_lato),
    # to plot smooth densities instead: use ggally_densityDiag() or better my_dens(), see comment below
    # UPPER TRIANGLE ELEMENTS: use new fct. to create heatmap of correlation values with significance stars
    upper = list(continuous = cor_fun)
    ) +
    theme(# adjust strip texts
    strip.background = element_blank(), # remove color
    strip.text = element_text(size=12, family="Lato Light"), # change font and font size
    axis.line = element_line(colour = "grey"),
    # remove grid
    panel.grid.minor = element_blank(), # remove smaller gridlines
    # panel.grid.major = element_blank() # remove larger gridlines
    )

    enter image description here

    如果有兴趣在对角线上绘制密度而不是直方图: ggally_densityDiag()可能导致密度大于 1。
    以下 fct。可以代替使用:
    my_dens <- function(data, mapping, ...) {
    ggplot(data = data, mapping=mapping) +
    geom_density(..., aes(x=..., y=..scaled..), alpha = 0.7, color = NA)
    }

    session 信息:
    MacOs 10.13.6、R 3.6.3、ggplot2_3.3.1、GGally_1.5.0

    关于r - ggpairs 图与相关值的热图,具有重要的星星和自定义主题,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/62196950/

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