Question

我使用vis.gam()绘制模型的结果。代码如下：

    vis.gam(model,view=c("CHLA","SST"),xlim=c(0,15),ylim=c(10,30),xlab="CHL-a (mg.m-3)",ylab="SST (°C)",plot.type="contour",type="response",color="terrain",n.grid=200)

我想从我自己的调色板中设置新颜色，如下面的代码所示：

    # colors palette definition
    jet.colors <-colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan",
                            "#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000"))

    vis.gam(model,view=c("CHLA","SST"),xlim=c(0,15),ylim=c(10,30),xlab="CHL-a (mg.m-3)",ylab="SST (°C)",plot.type="contour",type="response",color=jet.colors(10),n.grid=200)

不幸的是，我有这个错误：

vis.gam中的错误（模型，视图= c（“CHLA”，“SST”），xlim = c（0,15），ylim = c（10，：配色方案未被识别

我不知道如何将jet.colors调色板用于函数vis.gam ......

感谢您的帮助！

Answer 1

您可以自定义vis.gam功能以使用jet.colors渐变：

这是一个黑客版本（请参阅我的内联评论）：

jet.colors <-colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan",
                                "#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000"))

myvis.gam <- function (x, view = NULL, cond = list(), n.grid = 30, too.far = 0, 
          col = NA, color = "heat", contour.col = NULL, se = -1, type = "link", 
          plot.type = "persp", zlim = NULL, nCol = 50, ...) 
{
  fac.seq <- function(fac, n.grid) {
    fn <- length(levels(fac))
    gn <- n.grid
    if (fn > gn) 
      mf <- factor(levels(fac))[1:gn]
    else {
      ln <- floor(gn/fn)
      mf <- rep(levels(fac)[fn], gn)
      mf[1:(ln * fn)] <- rep(levels(fac), rep(ln, fn))
      mf <- factor(mf, levels = levels(fac))
    }
    mf
  }
  dnm <- names(list(...))
  v.names <- names(x$var.summary)
  if (is.null(view)) {
    k <- 0
    view <- rep("", 2)
    for (i in 1:length(v.names)) {
      ok <- TRUE
      if (is.matrix(x$var.summary[[i]])) 
        ok <- FALSE
      else if (is.factor(x$var.summary[[i]])) {
        if (length(levels(x$var.summary[[i]])) <= 1) 
          ok <- FALSE
      }
      else {
        if (length(unique(x$var.summary[[i]])) == 1) 
          ok <- FALSE
      }
      if (ok) {
        k <- k + 1
        view[k] <- v.names[i]
      }
      if (k == 2) 
        break
    }
    if (k < 2) 
      stop("Model does not seem to have enough terms to do anything useful")
  }
  else {
    if (sum(view %in% v.names) != 2) 
      stop(paste(c("view variables must be one of", v.names), 
                 collapse = ", "))
    for (i in 1:2) if (!inherits(x$var.summary[[view[i]]], 
                                 c("numeric", "factor"))) 
      stop("Don't know what to do with parametric terms that are not simple numeric or factor variables")
  }
  ok <- TRUE
  for (i in 1:2) if (is.factor(x$var.summary[[view[i]]])) {
    if (length(levels(x$var.summary[[view[i]]])) <= 1) 
      ok <- FALSE
  }
  else {
    if (length(unique(x$var.summary[[view[i]]])) <= 1) 
      ok <- FALSE
  }
  if (!ok) 
    stop(paste("View variables must contain more than one value. view = c(", 
               view[1], ",", view[2], ").", sep = ""))
  if (is.factor(x$var.summary[[view[1]]])) 
    m1 <- fac.seq(x$var.summary[[view[1]]], n.grid)
  else {
    r1 <- range(x$var.summary[[view[1]]])
    m1 <- seq(r1[1], r1[2], length = n.grid)
  }
  if (is.factor(x$var.summary[[view[2]]])) 
    m2 <- fac.seq(x$var.summary[[view[2]]], n.grid)
  else {
    r2 <- range(x$var.summary[[view[2]]])
    m2 <- seq(r2[1], r2[2], length = n.grid)
  }
  v1 <- rep(m1, n.grid)
  v2 <- rep(m2, rep(n.grid, n.grid))
  newd <- data.frame(matrix(0, n.grid * n.grid, 0))
  for (i in 1:length(x$var.summary)) {
    ma <- cond[[v.names[i]]]
    if (is.null(ma)) {
      ma <- x$var.summary[[i]]
      if (is.numeric(ma)) 
        ma <- ma[2]
    }
    if (is.matrix(x$var.summary[[i]])) 
      newd[[i]] <- matrix(ma, n.grid * n.grid, ncol(x$var.summary[[i]]), 
                          byrow = TRUE)
    else newd[[i]] <- rep(ma, n.grid * n.grid)
  }
  names(newd) <- v.names
  newd[[view[1]]] <- v1
  newd[[view[2]]] <- v2
  if (type == "link") 
    zlab <- paste("linear predictor")
  else if (type == "response") 
    zlab <- type
  else stop("type must be \"link\" or \"response\"")
  fv <- predict.gam(x, newdata = newd, se.fit = TRUE, type = type)
  z <- fv$fit
  if (too.far > 0) {
    ex.tf <- exclude.too.far(v1, v2, x$model[, view[1]], 
                             x$model[, view[2]], dist = too.far)
    fv$se.fit[ex.tf] <- fv$fit[ex.tf] <- NA
  }
  if (is.factor(m1)) {
    m1 <- as.numeric(m1)
    m1 <- seq(min(m1) - 0.5, max(m1) + 0.5, length = n.grid)
  }
  if (is.factor(m2)) {
    m2 <- as.numeric(m2)
    m2 <- seq(min(m1) - 0.5, max(m2) + 0.5, length = n.grid)
  }
  if (se <= 0) {
    old.warn <- options(warn = -1)
    av <- matrix(c(0.5, 0.5, rep(0, n.grid - 1)), n.grid, 
                 n.grid - 1)
    options(old.warn)
    max.z <- max(z, na.rm = TRUE)
    z[is.na(z)] <- max.z * 10000
    z <- matrix(z, n.grid, n.grid)
    surf.col <- t(av) %*% z %*% av
    surf.col[surf.col > max.z * 2] <- NA
    if (!is.null(zlim)) {
      if (length(zlim) != 2 || zlim[1] >= zlim[2]) 
        stop("Something wrong with zlim")
      min.z <- zlim[1]
      max.z <- zlim[2]
    }
    else {
      min.z <- min(fv$fit, na.rm = TRUE)
      max.z <- max(fv$fit, na.rm = TRUE)
    }
    surf.col <- surf.col - min.z
    surf.col <- surf.col/(max.z - min.z)
    surf.col <- round(surf.col * nCol)
    con.col <- 1
    if (color == "heat") {
      pal <- heat.colors(nCol)
      con.col <- 3
    }
    else if (color == "topo") {
      pal <- topo.colors(nCol)
      con.col <- 2
    }
    else if (color == "cm") {
      pal <- cm.colors(nCol)
      con.col <- 1
    }
    else if (color == "terrain") {
      pal <- terrain.colors(nCol)
      con.col <- 2
    }
    else if (color == "gray" || color == "bw") {
      pal <- gray(seq(0.1, 0.9, length = nCol))
      con.col <- 1
    }
    ### customized here
    else if (color == 'jet') {
      pal <- jet.colors(nCol)
      con.col = 1
    }
    ####
    else stop("color scheme not recognised")
    if (is.null(contour.col)) 
      contour.col <- con.col
    surf.col[surf.col < 1] <- 1
    surf.col[surf.col > nCol] <- nCol
    if (is.na(col)) 
      col <- pal[as.array(surf.col)]
    z <- matrix(fv$fit, n.grid, n.grid)
    if (plot.type == "contour") {
      stub <- paste(ifelse("xlab" %in% dnm, "", ",xlab=view[1]"), 
                    ifelse("ylab" %in% dnm, "", ",ylab=view[2]"), 
                    ifelse("main" %in% dnm, "", ",main=zlab"), ",...)", 
                    sep = "")
      if (color != "bw") {
        txt <- paste("image(m1,m2,z,col=pal,zlim=c(min.z,max.z)", 
                     stub, sep = "")
        eval(parse(text = txt))
        txt <- paste("contour(m1,m2,z,col=contour.col,zlim=c(min.z,max.z)", 
                     ifelse("add" %in% dnm, "", ",add=TRUE"), ",...)", 
                     sep = "")
        eval(parse(text = txt))
      }
      else {
        txt <- paste("contour(m1,m2,z,col=1,zlim=c(min.z,max.z)", 
                     stub, sep = "")
        eval(parse(text = txt))
      }
    }
    else {
      stub <- paste(ifelse("xlab" %in% dnm, "", ",xlab=view[1]"), 
                    ifelse("ylab" %in% dnm, "", ",ylab=view[2]"), 
                    ifelse("main" %in% dnm, "", ",zlab=zlab"), ",...)", 
                    sep = "")
      if (color == "bw") {
        op <- par(bg = "white")
        txt <- paste("persp(m1,m2,z,col=\"white\",zlim=c(min.z,max.z) ", 
                     stub, sep = "")
        eval(parse(text = txt))
        par(op)
      }
      else {
        txt <- paste("persp(m1,m2,z,col=col,zlim=c(min.z,max.z)", 
                     stub, sep = "")
        eval(parse(text = txt))
      }
    }
  }
  else {
    if (color == "bw" || color == "gray") {
      subs <- paste("grey are +/-", se, "s.e.")
      lo.col <- "gray"
      hi.col <- "gray"
    }
    else {
      subs <- paste("red/green are +/-", se, "s.e.")
      lo.col <- "green"
      hi.col <- "red"
    }
    if (!is.null(zlim)) {
      if (length(zlim) != 2 || zlim[1] >= zlim[2]) 
        stop("Something wrong with zlim")
      min.z <- zlim[1]
      max.z <- zlim[2]
    }
    else {
      z.max <- max(fv$fit + fv$se.fit * se, na.rm = TRUE)
      z.min <- min(fv$fit - fv$se.fit * se, na.rm = TRUE)
    }
    zlim <- c(z.min, z.max)
    z <- fv$fit - fv$se.fit * se
    z <- matrix(z, n.grid, n.grid)
    if (plot.type == "contour") 
      warning("sorry no option for contouring with errors: try plot.gam")
    stub <- paste(ifelse("xlab" %in% dnm, "", ",xlab=view[1]"), 
                  ifelse("ylab" %in% dnm, "", ",ylab=view[2]"), ifelse("zlab" %in% 
                                                                         dnm, "", ",zlab=zlab"), ifelse("sub" %in% dnm, 
                                                                                                        "", ",sub=subs"), ",...)", sep = "")
    txt <- paste("persp(m1,m2,z,col=col,zlim=zlim", ifelse("border" %in% 
                                                             dnm, "", ",border=lo.col"), stub, sep = "")
    eval(parse(text = txt))
    par(new = TRUE)
    z <- fv$fit
    z <- matrix(z, n.grid, n.grid)
    txt <- paste("persp(m1,m2,z,col=col,zlim=zlim", ifelse("border" %in% 
                                                             dnm, "", ",border=\"black\""), stub, sep = "")
    eval(parse(text = txt))
    par(new = TRUE)
    z <- fv$fit + se * fv$se.fit
    z <- matrix(z, n.grid, n.grid)
    txt <- paste("persp(m1,m2,z,col=col,zlim=zlim", ifelse("border" %in% 
                                                             dnm, "", ",border=hi.col"), stub, sep = "")
    eval(parse(text = txt))
  }
}

如需使用，只需使用color = 'jet'：

library(mgcv)
set.seed(0)
n<-200;sig2<-4
x0 <- runif(n, 0, 1);x1 <- runif(n, 0, 1)
x2 <- runif(n, 0, 1)
y<-x0^2+x1*x2 +runif(n,-0.3,0.3)
g<-gam(y~s(x0,x1,x2))
myvis.gam(g,ticktype="detailed",color='heat',theta=-35) 
myvis.gam(g,ticktype="detailed",color='jet',theta=-35)

enter image description here

从mg.gv中的vis.gam改变等高线图中的颜色

1 个答案: