离散调色板我们使用带平滑曲线的散点图和条形图来演示ggsci中的离散调色板。 原始配色 library('ggplot2')library('gridExtra')library('ggsci')p1 <- ggplot( subset(diamonds, carat >= 2.2), aes(x = table, y = price, colour = cut)) + geom_point(alpha = 0.7) + geom_smooth(method = "loess", alpha = 0.05, size = 1, span = 1) + theme_bw()p2 <- ggplot( subset(diamonds, carat > 2.2 & depth > 55 & depth < 70), aes(x = depth, fill = cut)) + geom_histogram(colour = "black", binwidth = 1, position = "dodge") + theme_bw()grid.arrange(p1, p2, ncol = 2)NPG配色 NPG调色板的灵感来自于自然出版集团出版的期刊中的图表 p1_npg <- p1 + scale_color_npg()p2_npg <- p2 + scale_fill_npg()grid.arrange(p1_npg, p2_npg, ncol = 2)AAAS配色p1_aaas <- p1 + scale_color_aaas()p2_aaas <- p2 + scale_fill_aaas()grid.arrange(p1_aaas, p2_aaas, ncol = 2)NEJMp1_nejm <- p1 + scale_color_nejm()p2_nejm <- p2 + scale_fill_nejm()grid.arrange(p1_nejm, p2_nejm, ncol = 2)Lancetp1_lancet <- p1 + scale_color_lancet()p2_lancet <- p2 + scale_fill_lancet()grid.arrange(p1_lancet, p2_lancet, ncol = 2)JAMAp1_jama <- p1 + scale_color_jama()p2_jama <- p2 + scale_fill_jama()grid.arrange(p1_jama, p2_jama, ncol = 2)JCOp1_jco <- p1 + scale_color_jco()p2_jco <- p2 + scale_fill_jco()grid.arrange(p1_jco, p2_jco, ncol = 2)UCSCGBp1_ucscgb <- p1 + scale_color_ucscgb()p2_ucscgb <- p2 + scale_fill_ucscgb()grid.arrange(p1_ucscgb, p2_ucscgb, ncol = 2)D3p1_d3 <- p1 + scale_color_d3()p2_d3 <- p2 + scale_fill_d3()grid.arrange(p1_d3, p2_d3, ncol = 2)LocusZoomp1_locuszoom <- p1 + scale_color_locuszoom()p2_locuszoom <- p2 + scale_fill_locuszoom()grid.arrange(p1_locuszoom, p2_locuszoom, ncol = 2)
IGVp1_igv_default <- p1 + scale_color_igv()p2_igv_default <- p2 + scale_fill_igv()grid.arrange(p1_igv_default, p2_igv_default, ncol = 2)
COSMICp1_cosmic_hallmarks_light <- p1 + scale_color_cosmic("hallmarks_light")p2_cosmic_hallmarks_light <- p2 + scale_fill_cosmic("hallmarks_light")grid.arrange(p1_cosmic_hallmarks_light, p2_cosmic_hallmarks_light, ncol = 2)
p1_cosmic_hallmarks_dark <- p1 + scale_color_cosmic("hallmarks_dark")p2_cosmic_hallmarks_dark <- p2 + scale_fill_cosmic("hallmarks_dark")grid.arrange(p1_cosmic_hallmarks_dark, p2_cosmic_hallmarks_dark, ncol = 2)
p1_cosmic_signature <- p1 + scale_color_cosmic("signature_substitutions")p2_cosmic_signature <- p2 + scale_fill_cosmic("signature_substitutions")grid.arrange(p1_cosmic_signature, p2_cosmic_signature, ncol = 2)
UChicagop1_uchicago <- p1 + scale_color_uchicago()p2_uchicago <- p2 + scale_fill_uchicago()grid.arrange(p1_uchicago, p2_uchicago, ncol = 2)
Star Trekp1_startrek <- p1 + scale_color_startrek()p2_startrek <- p2 + scale_fill_startrek()grid.arrange(p1_startrek, p2_startrek, ncol = 2)
Tron Legacyp1_tron <- p1 + theme_dark() + theme( panel.background = element_rect(fill = "#2D2D2D"), legend.key = element_rect(fill = "#2D2D2D")) + scale_color_tron()p2_tron <- p2 + theme_dark() + theme( panel.background = element_rect(fill = "#2D2D2D")) + scale_fill_tron()grid.arrange(p1_tron, p2_tron, ncol = 2)
Futuramap1_futurama <- p1 + scale_color_futurama()p2_futurama <- p2 + scale_fill_futurama()grid.arrange(p1_futurama, p2_futurama, ncol = 2)
Rick and Mortyp1_rickandmorty <- p1 + scale_color_rickandmorty()p2_rickandmorty <- p2 + scale_fill_rickandmorty()grid.arrange(p1_rickandmorty, p2_rickandmorty, ncol = 2)
The Simpsonsp1_simpsons <- p1 + scale_color_simpsons()p2_simpsons <- p2 + scale_fill_simpsons()grid.arrange(p1_simpsons, p2_simpsons, ncol = 2)
连续调色板我们将使用相关矩阵可视化来演示ggsci中的连续调色板。 library("reshape2")data("mtcars")cor <- cor(unname(cbind(mtcars, mtcars, mtcars, mtcars)))cor_melt <- melt(cor)p3 <- ggplot( cor_melt, aes(x = Var1, y = Var2, fill = value)) + geom_tile(colour = "black", size = 0.3) + theme_bw() + theme( axis.title.x = element_blank(), axis.title.y = element_blank() )p3
GSEAp3_gsea <- p3 + scale_fill_gsea()p3_gsea_inv <- p3 + scale_fill_gsea(reverse = TRUE)grid.arrange(p3_gsea, p3_gsea_inv, ncol = 2)
Material Design材料设计调色板来自材料设计颜色指南。我们首先生成一个随机矩阵： library("reshape2")set.seed(121)k <- 9x <- diag(k)x[upper.tri(x)] <- runif(sum(1:(k - 1)), 0, 1)x_melt <- melt(x)p4 <- ggplot(x_melt, aes(x = Var1, y = Var2, fill = value)) + geom_tile(colour = "black", size = 0.3) + scale_x_continuous(expand = c(0, 0)) + scale_y_continuous(expand = c(0, 0)) + theme_bw() + theme( legend.position = "none", plot.background = element_blank(), axis.line = element_blank(), axis.ticks = element_blank(), axis.text.x = element_blank(), axis.text.y = element_blank(), axis.title.x = element_blank(), axis.title.y = element_blank(), panel.background = element_blank(), panel.border = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank() )p4
使用19个材质设计调色板绘制矩阵： grid.arrange( p4 + scale_fill_material("red"), p4 + scale_fill_material("pink"), p4 + scale_fill_material("purple"), p4 + scale_fill_material("deep-purple"), p4 + scale_fill_material("indigo"), p4 + scale_fill_material("blue"), p4 + scale_fill_material("light-blue"), p4 + scale_fill_material("cyan"), p4 + scale_fill_material("teal"), p4 + scale_fill_material("green"), p4 + scale_fill_material("light-green"), p4 + scale_fill_material("lime"), p4 + scale_fill_material("yellow"), p4 + scale_fill_material("amber"), p4 + scale_fill_material("orange"), p4 + scale_fill_material("deep-orange"), p4 + scale_fill_material("brown"), p4 + scale_fill_material("grey"), p4 + scale_fill_material("blue-grey"), ncol = 6)
从上图中我们可以看到，尽管所有的图都显示了一个相同的矩阵，但是一些调色板比其他调色板更舒服，因为我们的眼睛对饱和度的变化更敏感 Non-ggplot2 Graphics要将ggsci中的调色板应用于其他图形系统（如基础图形和晶格图形），只需使用上表中的调色板生成器函数。例如： mypal <- pal_npg("nrc", alpha = 0.7)(9)mypal## [1] "#E64B35B2" "#4DBBD5B2" "#00A087B2" "#3C5488B2" "#F39B7FB2" "#8491B4B2"## [7] "#91D1C2B2" "#DC0000B2" "#7E6148B2"library("scales")show_col(mypal)
您将能够使用生成的十六进制颜色代码为这样的图形系统相应。整个调色板的透明级别很容易通过每个生成器或scale函数中的参数“alpha”进行调整。 好了，今天的分享就到这里 福利专用贴：福利专用贴 目前有 1. 火山图，热图示例文件及完整代码 2. R语言学习基础知识代码 3. R语言实战(中文完整版) 4. R数据科学(中文完整版） 5. ggplot2：数据分析与图形艺术 6. 30分钟学会ggplot2 7. TCGA数据整理8. ggplot2速查表pdf（可复制） |
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