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作者：李誉辉

四川大学在读研究生

前言

这篇是plot3D包绘图系列之四，前一篇请戳：

R_3D图(三)

，后续还有两篇连载，大家一起加油！做教程狠费精力的，别忘了点赞和转发。谢谢。4 scatter2D()与scatter3D() 及text2D()与text3D()

point3D()是scatter3D()的特殊形式，参数typ【我爱线报网】e = “p”。lines3D()是scatter3D()的特殊形式，参数type = “l”。point2D()是scatter2D()的特殊形式，参数type = “p”。lines2D()是scatter2D()的特殊形式，参数type = “l”。text2D() 是另一种不可替代的函数text3D() 是另一种不可替代的函数

语法：

scatter3D (x, y, z, …, colvar = z, phi = 40, theta = 40, col = NULL, NAcol = “white”, breaks = NULL, colkey = N【我爱线报网】ULL, panel.first = NULL, clim = NULL, clab = NULL, bty = “b”, CI = NULL, surf = NULL, add = FALSE, plot = TRUE) text3D (x, y, z, labels, …, colvar = NULL, phi = 40, theta = 40, col = NULL, NAcol = “white”, breaks = NULL, colkey = NULL, panel.first = 【我爱线报网】NULL, clim = NULL, clab = NULL, bty = “b”, add = FALSE, plot = TRUE) points3D (x, y, z, …) lines3D (x, y, z, …) scatter2D (x, y, …, colvar = NULL, col = NULL, NAcol = “white”, breaks = NULL, colkey = NULL, clim = NULL, clab = NULL, 【我爱线报网】 CI = NULL, add = FALSE, plot = TRUE) lines2D(x, y, …) points2D(x, y, …) text2D (x, y, labels, …, colvar = NULL, col = NULL, NAcol = “white”, breaks = NULL, colkey = NULL, clim = NULL, clab = NULL, add = FALSE, plot = TRUE)

参数解释：

x, y, z,表示点的坐标，为数字向量，他们应该【我爱线报网】等长度，length(x) = length(y) = length(z) 。colvar,表示指定要着色的变量，默认NULL，如果指定，则长度应等于(x, y, z)。theta, phi, 表示指定观察方向。与persp()中一样。col, 表示指定色板， xxx.col(), 默认NULL，如colvar指定了，则默认红黄蓝的jet.col()颜色。如果col = NULL，且colvar未指定，则col默认为黑色。NAcol, 表示指定colvar中NA的颜色。breaks, 表示指定colvar的断点，为数字向量，长度应该比col参数大1个。需要增序排列，默认自动增序排列。colke【我爱线报网】y, 为逻辑值或NULL(默认), 也可以用列表传递colkey参数。当colkey = NULL时，若col参数是一个向量，才会自动添加图例，col参数是一个字符串则不添加图例。设定colkey = list(plot = FALSE)则为图例留下空间，但不显示图例。colkey = FALSE则不绘制图例。CI，为NULL(默认)或列表(包含参数和置信区间数字向量),如果为列表，则至少应包含x, y, z(z仅仅用于scatter3D()中), 这些参数应该是2列的矩阵，表示左/右间隔。 其它参数应该是：alen = 0.01, lty = par(“lty”), lwd = par(“l【我爱线报网】wd”), col = NULL,这几个参数设置箭头的长度，线型，宽度和颜色。 如果col = NULL,则使用colvar指定的颜色。panel.first, 表示指定一种变换函数，常常用于绘制背景网格和三维散点图的平滑处理。 该函数的其中一个参数应该是pmat矩阵变换。见persp3D()中的例子。clab, 表示指定图例标题内容，当colkey = NULL或colkey = FALSE时失效。默认位置于主标题同一高度，降低高度，使用向量指定，第一个元素为空字符串。clim, 表示指定colvar显示范围，如果colvar参数被指定了，则超出clim范围的colvar将以NA显示。bty【我爱线报网】, 表示指定box的类型，默认仅仅画背景panels,只有当persp()中的box = TRUE时才有效。其它与perspbox()函数中一致，bty = c(“b”, “b2”, “f”, “g”, “bl”, “bl2”, “u”, “n”)其中之一。labels, 表示指定每个散点的的文本标签内容。其长度应等于(x, y, z)。surf, NULL(默认)或列表传参, 表示增加散点图拟合的曲面，拟合曲面参数包括: 必要参数(x, y, z指定曲面),可选参数(colvar, col, NAcol, border, facets, lwd, resfac, clim, ltheta, 【我爱线报网】lphi, shade, lighting, fit)参数用法与persp()中一样。 默认参数中未指定colvar, 表示默认colvar = z，z的排列应该与scatter3D()中的z一致。add, 表示是否将该绘图对象加入到已存在的绘图对象中，TRUE相当于增加图层，默认FALSE则新建。plot, 表示是否立即绘图，默认TRUE则立即绘图，FALSE则往下传递绘图参数，直到最后一个图层一起绘制。…, 表示其它参数，包括公共参数, persp()中的参数，perspbox()中的一些参数。 persp()中的一些参数：xlim, ylim, zlim, xlab, ylab, zla【我爱线报网】b, main, sub,r, d, scale, expand, box, axes, nticks, ticktype。同样xlim,ylim, zlim也只限制坐标轴范围，超出该范围的图形仍然会绘制出来，使用plotdev()设定图形范围。 perspbox()中的一些参数： col.axis, col.panel, lwd.panel, col.grid, lwd.grid。公共参数：alpha透明度，从0(全透明)到1(不透明)。 lty线型，lwd线宽，shade和lighting没有任何作用。type, 表示指定点或线等绘图几何类型。只有text3D不可取代。如type = “p【我爱线报网】“或”b”，指定type后，pch, cex, bg等参数就可以使用了。

4.1 scatter2D()与scatter3D()

4.1.1 全矩阵数据源

library(plot3D) par(bg = “#b3ff99”)# par设定背景颜色 M <- mesh(seq(0, 2*pi, length.out = 100), seq(0, pi, length.out = 100)) u <- M$x ; v <- M$y x <- cos(u)*sin(v) # 矩阵Hadamard积，对应元素相乘 【我爱线报网】 y <- sin(u)*sin(v) z <- cos(v) # scatter3D(x, y, z, pch = “.”, col = “magenta”, # pch点型可以为字符 cex = 2, colkey = FALSE, # cex设定点的大小 bty = “u”, col.panel = NA) # 手动设定背景, col.panel = NA设定透明背景

4.1.2 type类型

library(plot3D) # 编一个数据 z <- seq(0, 10, 0.2【我爱线报网】) x <- cos(z) y <- sin(z)*z # 三维点图与三维文本 scatter3D(x, y, z, phi = 0, # col = ramp.col(col = c(“cyan”, “magenta”), n = length(z)), # 指定颜色色板 pch = 20, cex = 2, ticktype = “detailed”, bty = “u”, col.panel = “#ffffcc”, col.grid = “white”) ##【我爱线报网】 添加图层, 添加一个点在三维空间 scatter3D(x = 0, y = 0, z = 0, add = TRUE, col = “blue”, # 指定颜色色板 colkey = FALSE, pch = 10, cex = 3, lwd = 3) # pch点型，cex点尺寸，lwd点中线宽 ## 添加图层， 添加10个大写字母在三维空间 text3D(x = cos(1:10), y = (sin(1:10)*(1:10) – 1), z = 1:10, colkey = 【我爱线报网】FALSE, add = TRUE, labels = LETTERS[1:10], col = ramp.col(col = c(“blue”, “red”), n = 10))# 三维线图， scatter3D(x, y, z, phi = 0, type = “l”, # type = “l”连线 col = ramp.col(col = c(“cyan”, “magenta”), n = length(z)), # 指定颜色色板 ticktype = “detailed”, lwd = 4, bty = “【我爱线报网】u”, col.panel = “#ffffcc”, col.grid = “white”)# 三维点图与三维线图 scatter3D(x, y, z, phi = 0, type = “b”,# type = “b”表示both，即点连线 col = ramp.col(col = c(“cyan”, “magenta”), n = length(z)), # 指定颜色色板 bty = “u”, col.panel = “#ffffcc”, col.grid = “white”, ticktype = “detailed”, pc【我爱线报网】h = 20, cex = c(0.5, 1, 1.5))# 竖线条 scatter3D(x, y, z, phi = 0, type = “h”, # type = “h” 点与竖线条 col = ramp.col(col = c(“cyan”, “magenta”), n = length(z)), # 指定颜色色板 bty = “u”, col.panel = “#ffffcc”, col.grid = “white”, ticktype = “detailed”)

4.1.3 CI置信区间

CI参数为列表，内有【我爱线报网】1到3个元素，每个元素都是矩阵，其行数和列数length(x)。

表示在各个坐标轴方向上的置信区间，

library(plot3D) x <- runif(20) # 20个随机数 y <- runif(20) z <- runif(20) ## 设定置信区间参数，1个方向的置信区间 CI <- list(z = matrix(nrow = length(x), data = rep(0.05, 2 * length(x)))) # 矩阵行数和列数都是length(x),值均为0.05 # 设定box类【我爱线报网】型，bty=g灰色背景，白色grid scatter3D(x, y, z, theta = 45, phi = 0, bty = “g”, CI = CI, col = ramp.col(col = c(“cyan”, “magenta”), n = 100, alpha = 0.8), pch = 19, cex = 2, ticktype = “detailed”, xlim = c(0, 1), ylim = c(0, 1), zlim = c(0, 1)) # 增加一些散点 点坐标参数 x <- runif【我爱线报网】(20) y <- runif(20) z <- runif(20) ## 设定置信区间参数， 2个方向的置信区间 CI2 <- list(x = matrix(nrow = length(x), data = rep(0.05, 2 * length(x))), z = matrix(nrow = length(x), data = rep(0.05, 2 * length(x)))) scatter3D(x, y, z, CI = CI2, add = TRUE, col = “orange”,【我爱线报网】 pch = 2)

4.1.4 surf添加曲面

surf参数中，可以使用列表传递曲面参数，与persp()中的参数一样。

当传递坐标参数与scatter3D()中无关则相当于添加曲面。

library(plot3D) M <- mesh(1:nrow(volcano), 1:ncol(volcano)) # 绘制100个点，编坐标参数 N <- 100 xs <- runif(N) * 87 ys <- runif(N) * 61 zs <- runif(N)*50 + 154 # 绘图,【我爱线报网】 scatter3D(xs, ys, zs, theta = 45, ticktype = “detailed”, pch = 16, bty = “f”, xlim = c(1, 87), ylim = c(1,61), zlim = c(94, 215), # bty = “f”,所有panels透明 surf = list(x = M$x, y = M$y, z = volcano, NAcol = “grey”, shade = 0.1))library(plot3D) # 构建曲面网格坐标 【我爱线报网】 M <- mesh(seq(0, 2*pi, length = 30), (1:30)/100) z <- with (M, sin(x) + y) # # 散点图坐标 N <- 30 xs <- runif(N) * 2*pi ys <- runif(N) * 0.3 zs <- sin(xs) + ys + rnorm(N)*0.3 CI <- list(z = matrix(nrow = length(xs), data = rep(0.3, 2*length【我爱线报网】(xs))), lwd = 3) # CI列表传参还能传递其它参数 # facets = NA,网格面透明，网格线border为黑色 scatter3D(xs, ys, zs, ticktype = “detailed”, pch = 16, col = ramp.col(col = c(“cyan”, “magenta”), n = 30, alpha = 0.8), xlim = c(0, 2*pi), ylim = c(0, 0.3), zlim = c(-1.5, 1.5), # 指定坐标轴显示范围 【我爱线报网】 CI = CI, theta = 20, phi = 30, cex = 2, surf = list(x = M$x, y = M$y, z = z, border = “orange”, facets = NA) )

4.1.5 坐标数据来自预测值

在with()内绘图

library(plot3D) par(bg = “#ffffcc”) with (mtcars, { # with内处理数据并绘图 # 线性回归，多元回归 fit <- lm(mpg ~ wt + disp) 【我爱线报网】 # 构建预测数据 wt.pred <- seq(1.5, 5.5, length.out = 30) disp.pred <- seq(71, 472, length.out = 30) xy <- expand.grid(wt = wt.pred, disp = disp.pred) # expand.grid向量构建数据框 ## 预测mag值，然后转换成矩阵 mpg.pred <- matrix (nrow = 30, ncol = 30, data = predict(fit, newda【我爱线报网】ta = data.frame(xy), interval = “prediction”) ) # olddata预测 fitpoints <- predict(fit) scatter3D(z = mpg, x = wt, y = disp, pch = 18, cex = 2, theta = 20, phi = 20, ticktype = “detailed”, col = ramp.col(col = c(“cyan”, “magenta”), n = 30, alpha 【我爱线报网】= 0.8), xlab = “wt”, ylab = “disp”, zlab = “mpg”, # 修改坐标轴标题 surf = list(x = wt.pred, y = disp.pred, z = mpg.pred, facets = NA, fit = fitpoints), # fit参数增加预测值与真实值之间的连线 main = “mtcars”, bty = “u”, col.panel = NA) # col.panel = NA则panel透明 })

4.1.6 panel.first参数在pa【我爱线报网】nel中增加图形

panel.first可以指定绘图对象，也就可以在panels中增加图形。

library(plot3D) par(bg = “#ffffcc”) # 第一种方法，type = “h”增加垂线条 with(quakes, scatter3D(x = long, y = lat, z = -depth, colvar = mag, pch = 16, cex = 1.5, xlab = “longitude”, ylab = “latitude”, col = ramp.col(col = c(“cya【我爱线报网】n”, “magenta”), n = length(mag), alpha = 0.5), zlab = “depth, km”, clab = c(“Richter”,”Magnitude”), main = “Earthquakes off Fiji”, ticktype = “detailed”, bty = “u”, col.panel = NA, # 透明面板 type = “h”, theta = 10, d = 2, colkey = list(length = 0.5, width = 0.5, cex.clab【我爱线报网】 = 0.75)) # 图例列表传参 ) # 第2中方法，使用trans3D构建转换空间 # 然后使用转换空间绘制二维散点图，再使用panel.first参数将该图add到scatter3D基图中 # 绘制panel.first图 lens <- length(quakes$mag) panelfirst <- function(pmat) { ## 绘制x-y平面的panel zmin <- min(-quakes$depth) ### trans3【我爱线报网】D构建转换空间，x,y坐标与第1种方法中一样，z轴仅仅计数，以免重复 XY <- trans3D(quakes$long, quakes$lat, z = rep(zmin, nrow(quakes)), pmat = pmat) ### 使用转换空间绘制散点图，必须使用add = TRUE才能将图形以panel.first参数传入基图中 scatter2D(XY$x, XY$y, colvar = quakes$mag, pch = “.”, # colvar着色变量与基图相同 col = ramp.col(co【我爱线报网】l = c(“cyan”, “magenta”), n = lens, alpha = 0.5), cex = 2, add = TRUE, colkey = FALSE) # ## 绘制y-z平面的panel xmin <- min(quakes$long) # x轴仅仅计数 ### trans3D构建转换空间，y,z坐标与第1种方法相同，x轴仅仅计数避免重复 XY <- trans3D(x = rep(xmin, nrow(quakes)), y = quakes$lat, z = -quake【我爱线报网】s$depth, pmat = pmat) ### 使用转换空间绘制散点图，必须使用add = TRUE才能将图形以panel.first参数传入基图中 scatter2D(XY$x, XY$y, colvar = quakes$mag, pch = “.”, # colvar着色变量与基图相同 col = ramp.col(col = c(“cyan”, “magenta”), n = lens, alpha = 0.5), cex = 2, add = TRUE, colkey = FALSE) } 【我爱线报网】 # 将panel.first图添加到scatter3D基图中 with(quakes, scatter3D(x = long, y = lat, z = -depth, colvar = mag, pch = 16, cex = 1.5, xlab = “longitude”, ylab = “latitude”, col = ramp.col(col = c(“cyan”, “magenta”), n = length(mag), alpha = 0.5), zlab = “depth, km”, clab = c(“Ri【我爱线报网】chter”,”Magnitude”), main = “Earthquakes off Fiji”, ticktype = “detailed”, bty = “u”, col.panel = NA, # 透明面板 panel.first = panelfirst, theta = 10, d = 2, # panel.first传递panels绘图对象 colkey = list(length = 0.5, width = 0.5, cex.clab = 0.75)) )

4.2 text2D()与text3D()

4.2.1 t【我爱线报网】ext3D()添加文字

library(plot3D) par(bg = “#ffffcc”)# par设定背景颜色 data(“USArrests”) # 绘制散点图与垂线条 scatter3D(USArrests$Murder, USArrests$Assault, USArrests$Rape – 1, colvar = USArrests$UrbanPop, col = ramp.col(col = c(“cyan”, “magenta”), n = length(USArrests$Urba【我爱线报网】nPop), alpha = 0.5), colkey = list( length = 0.5, col.clab = “blue”, dist = -0.1), # 列表传参,设定图例 type = “h”, pch = “.”,bty = “u”, col.panel = NA) # 添加文字 text3D(USArrests$Murder, USArrests$Assault, USArrests$Rape, add = TRUE, colvar = USArrests$UrbanPop, theta = 【我爱线报网】60, phi = 20, col = ramp.col(col = c(“cyan”, “magenta”), n = length(USArrests$UrbanPop), alpha = 0.5), xlab = “Murder”, ylab = “Assault”, zlab = “Rape”, main = “USA arrests”, colkey = FALSE, labels = rownames(USArrests), cex = 0.6, bty = “u”, ticktype = “detai【我爱线报网】led”, d = 2, clab = c(“Urban”,”Pop”), adj = 0.5, font = 2, col.panel = NA)

4.2.2 坐标轴刻度文本text

library(plot3D) data(VADeaths) hist3D(x = 1:5, y = 1:4, z = VADeaths, expand = 0.5, phi = 20, theta = -72, shade = 0.2, itheta = 72, iphi = 60, d = 2, xlab = “”, ylab = “”, zlab【我爱线报网】 = “”, main = “VADeaths”, col = ramp.col(col = c(“cyan”, “green”), n = 3, alpha = 0.5)[2], border = “magenta”, alpha = 0.15, opaque.top = TRUE, bty = “g”, space = 0.3, ticktype = “detailed”, cex.axis = 1e-09) text3D(x = 1:5, y = rep(0.5, 5), z = rep(3, 5), labels = ro【我爱线报网】wnames(VADeaths), add = TRUE, adj = 0, col = “magenta”, bty = “g”) text3D(x = rep(1, 4), y = 1:4, z = rep(0, 4), labels = colnames(VADeaths), add = TRUE, adj = 1, col = “magenta”, bty = “g”)

4.3 scatter2D()

4.3.1 type参数

library(plot3D) par(mfrow = c(2, 2), bg = “#ffffcc”【我爱线报网】) # 多图排版，2*2矩阵排列 x <- seq(0, 2*pi, length.out = 30) # 默认type为点 scatter2D(x, sin(x), colvar = cos(x), pch = 16, col = ramp.col(col = c(“cyan”, “magenta”), n = 30, alpha = 0.5), colkey = list(col.axis = “blue”, col.ticks = “green”, col.clab = “purple”), # 设定图例参数【我爱线报网】 ylab = “sin”, clab = “cos”, cex = 1.5) # type = “l”连线 scatter2D(x, sin(x), colvar = cos(x), col = ramp.col(col = c(“cyan”, “magenta”), n = 30, alpha = 0.5), colkey = list(col.axis = “blue”, col.ticks = “green”, col.clab = “purple”), # 设定图例参数 type = “l【我爱线报网】“, lwd = 4, bty = “g”) # type = “b”点和联系 scatter2D(x, sin(x), colvar = cos(x), col = ramp.col(col = c(“cyan”, “magenta”), n = 30, alpha = 0.5), colkey = list(col.axis = “blue”, col.ticks = “green”, col.clab = “purple”), # 设定图例参数 type = “b”, lwd = 2, bty = “g”) 【我爱线报网】 # type = “h”竖线 scatter2D(x, sin(x), colvar = cos(x), col = ramp.col(col = c(“cyan”, “magenta”), n = 30, alpha = 0.5), colkey = list(col.axis = “blue”, col.ticks = “green”, col.clab = “purple”), # 设定图例参数 type = “h”, lwd = 4, alpha = 0.5) # 指定透明的和线宽

4.3.2 text2D(【我爱线报网】)添加文本

library(plot3D) data(“USArrests”) par(bg = “#ffffcc”) text2D(x = USArrests$Murder, y = USArrests$Assault + 5, colvar = USArrests$Rape, col = ramp.col(col = c(“cyan”, “magenta”), n = length(USArrests$Rape), alpha = 0.5), xlab = “Murder”, ylab = “Assault”, 【我爱线报网】clab = “Rape”, main = “USA arrests”, labels = rownames(USArrests), cex = 0.6, adj = 0.5, font = 2, colkey = list(plot = FALSE)) scatter2D(x = USArrests$Murder, y = USArrests$Assault, colvar = USArrests$Rape, col = ramp.col(col = c(“cyan”, “magenta”), n = length(USArrests$Rape【我爱线报网】), alpha = 0.8), pch = 16, add = TRUE)

4.3.3 mesh数据源

library(plot3D) par(mfrow = c(1, 2), bg = “#ffffcc”) x <- seq(-1, 1, by = 0.1) y <- seq(-2, 2, by = 0.2) grid <- mesh(x, y) z <- with(grid, cos(x) * sin(y)) # 第一张图 image2D(x = x, y = y,【我爱线报网】 z = z, col = ramp.col(col = c(“cyan”, “magenta”), n = length(x), alpha = 0.5)) points(grid, col = “blue”) # 使用R自带函数添加图层,设定变量颜色为蓝色 # 第2张图 scatter2D(grid$x, grid$y, colvar = z, pch = 20, cex = 2, col = ramp.col(col = c(“cyan”, “magenta”), n = length(x), alpha =【我爱线报网】 0.5))

4.3.4 CI置信区间

library(plot3D) par(bg = “#ffffcc”) x <- sort(rnorm(10)) y <- runif(10) cv <- sqrt(x^2 + y^2) # 创建置信区间列表 CI <- list(lwd = 2) # 置信区间线宽 CI$x <- matrix(nrow = length(x), data = c(rep(0.25, 2 * length(x)))) # 给列表增加元素，x方向的置信区间 【我爱线报网】 CI2 <- CI CI2$y <- matrix(nrow = length(y), data = c(rep(0.25, 2 * length(y)))) # 给列表增加元素，y方向的置信区间 scatter2D(x, y, colvar = cv, col = ramp.col(col = c(“cyan”, “magenta”), n = length(x), alpha = 0.5), pch = 16, cex = 2, CI = CI) # 更改type = b点连线 scatter2D(x,【我爱线报网】 y, colvar = cv, col = ramp.col(col = c(“cyan”, “magenta”), n = length(x), alpha = 0.5), pch = 16, cex = 2, CI = CI, type = “b”) # 增加y方向的置信区间 scatter2D(x, y, colvar = cv, col = ramp.col(col = c(“cyan”, “magenta”), n = length(x), alpha = 0.5), pch = 16, cex = 2, CI = C【我爱线报网】I2, type = “b”)

4.3.5 添加绘图对象到地图中

library(plot3D) data(Oxsat) # image2D绘制地图 oxlim <- range(Oxsat$val[, , 1], na.rm = TRUE) image2D(z = Oxsat$val[, , 1], x = Oxsat$lon, y = Oxsat$lat, contour = TRUE, xlab = “longitude”, ylab = “latitude”, main = “Oxygen saturation【我爱线报网】“, clim = oxlim, clab = “%”) # 数据点坐标创建 lon <- c(11.2, 6, 0.9, -4, -8.8) lat <- c(-19.7, -14.45, -9.1, -3.8, -1.5) O2sat <- c(90, 95, 92, 85, 100) # 数据点着色变量 # add to image; use same zrange; avoid adding a color key scatter2D(x = lon, y = lat, co【我爱线报网】lvar = O2sat, clim = oxlim, pch = 16, add = TRUE, cex = 2, colkey = FALSE)

4.4 line2D()

与scatter2D()中type = “l”结果一样

library(plot3D) data(“sunspot.month”) par(bg = “#ffffcc”) # 筛选数据 sunspot <- data.frame(year = time(sunspot.month), anom = sunspot.month – m【我爱线报网】ean(sunspot.month)) ff <- 100 sunspot$ma <- filter(sunspot$anom, rep(1/ff, ff), sides = 2) # type = “h”绘制垂线条 lines2D(sunspot$year, sunspot$anom, colvar = sunspot$anom > 0, col = ramp.col(col = c(“pink”, “lightblue”), n = 2, alpha = 0.1), # 正数一种颜色，负数一种颜色 【我爱线报网】 main = “sunspot anomaly”, type = “h”, colkey = FALSE, las = 1, xlab = “year”, ylab = “”) # tyep = “l”绘制连线,注意着色变量不一样 lines2D(sunspot$year, sunspot$ma, add = TRUE, col = ramp.col(col = c(“green”, “magenta”), n = length(sunspot$ma), alpha = 0.9))

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往期精彩：

R_插值_拟合_回归_样条R【我爱线报网】_circlize包_和弦图（一）R_circlize包_和弦图（二）R_ggplot2基础（一）R_ggplot2基础（二）R_ggplot2基础（三）R_ggplot2基础（四）R_3D图(一)R_3D图(二)

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