使用grid和ggplot2使用R创建连接图
我想知道如何修复一块地块。这些图以数组排列，因此一行中的所有图都具有相同的Y轴变量，并且列中的所有图都具有相同的X轴变量。
在网格中连接在一起时，会创建一个多重绘图。我禁用大多数图表上的标签，除了外部标签，因为内部标签具有相同的变量和比例。但是，由于外部图表具有标签和轴值，因此它们会产生与其他图案不同的大小。
我正在考虑向网格添加2个列和行，用于变量名称和轴范围值...然后仅绘制相应网格空间上的变量名称和另一个网格空间上的轴值，因此只绘制剩余空间中的点并获得相同的大小。
编辑1：
感谢rcs指点我align.plot
编辑align.plot以接受空值（当不需要轴中的标题/文本时）
现在我更接近目标了，但由于标签，第一个columun图的宽度仍然比其他图块小。
示例代码：
grid_test <- function ()
{
dsmall <- diamonds[sample(nrow(diamonds), 100), ]
#-----/align function-----
align.plots <- function(gl, ...){
# Obtained from http://groups.google.com/group/ggplot2/browse_thread/thread/1b859d6b4b441c90
# Adopted from http://ggextra.googlecode.com/svn/trunk/R/align.r
# BUGBUG: Does not align horizontally when one has a title.
# There seems to be a spacer used when a title is present. Include the
# size of the spacer. Not sure how to do this yet.
stats.row <- vector( "list", gl$nrow )
stats.col <- vector( "list", gl$ncol )
lstAll <- list(...)
dots <- lapply(lstAll, function(.g) ggplotGrob(.g[[1]]))
#ytitles <- lapply(dots, function(.g) editGrob(getGrob(.g,"axis.title.y.text",grep=TRUE), vp=NULL))
#ylabels <- lapply(dots, function(.g) editGrob(getGrob(.g,"axis.text.y.text",grep=TRUE), vp=NULL))
#xtitles <- lapply(dots, function(.g) editGrob(getGrob(.g,"axis.title.x.text",grep=TRUE), vp=NULL))
#xlabels <- lapply(dots, function(.g) editGrob(getGrob(.g,"axis.text.x.text",grep=TRUE), vp=NULL))
plottitles <- lapply(dots, function(.g) editGrob(getGrob(.g,"plot.title.text",grep=TRUE), vp=NULL))
xtitles <- lapply(dots, function(.g) if(!is.null(getGrob(.g,"axis.title.x.text",grep=TRUE)))
editGrob(getGrob(.g,"axis.title.x.text",grep=TRUE), vp=NULL) else ggplot2:::.zeroGrob)
xlabels <- lapply(dots, function(.g) if(!is.null(getGrob(.g,"axis.text.x.text",grep=TRUE)))
editGrob(getGrob(.g,"axis.text.x.text",grep=TRUE), vp=NULL) else ggplot2:::.zeroGrob)
ytitles <- lapply(dots, function(.g) if(!is.null(getGrob(.g,"axis.title.y.text",grep=TRUE)))
editGrob(getGrob(.g,"axis.title.y.text",grep=TRUE), vp=NULL) else ggplot2:::.zeroGrob)
ylabels <- lapply(dots, function(.g) if(!is.null(getGrob(.g,"axis.text.y.text",grep=TRUE)))
editGrob(getGrob(.g,"axis.text.y.text",grep=TRUE), vp=NULL) else ggplot2:::.zeroGrob)
legends <- lapply(dots, function(.g) if(!is.null(.g$children$legends))
editGrob(.g$children$legends, vp=NULL) else ggplot2:::.zeroGrob)
widths.left <- mapply(`+`, e1=lapply(ytitles, grobWidth),
e2= lapply(ylabels, grobWidth), SIMPLIFY=FALSE)
widths.right <- lapply(legends, grobWidth)
# heights.top <- lapply(plottitles, grobHeight)
heights.top <- lapply( plottitles, function(x) unit(0,"cm") )
heights.bottom <- mapply(`+`, e1=lapply(xtitles, grobHeight), e2= lapply(xlabels, grobHeight), SIMPLIFY=FALSE)
for ( i in seq_along( lstAll ) ) {
lstCur <- lstAll[[i]]
# Left
valNew <- widths.left[[ i ]]
valOld <- stats.col[[ min(lstCur[[3]]) ]]$widths.left.max
if ( is.null( valOld ) ) valOld <- unit( 0, "cm" )
stats.col[[ min(lstCur[[3]]) ]]$widths.left.max <- max( do.call( unit.c, list(valOld, valNew) ) )
# Right
valNew <- widths.right[[ i ]]
valOld <- stats.col[[ max(lstCur[[3]]) ]]$widths.right.max
if ( is.null( valOld ) ) valOld <- unit( 0, "cm" )
stats.col[[ max(lstCur[[3]]) ]]$widths.right.max <- max( do.call( unit.c, list(valOld, valNew) ) )
# Top
valNew <- heights.top[[ i ]]
valOld <- stats.row[[ min(lstCur[[2]]) ]]$heights.top.max
if ( is.null( valOld ) ) valOld <- unit( 0, "cm" )
stats.row[[ min(lstCur[[2]]) ]]$heights.top.max <- max( do.call( unit.c, list(valOld, valNew) ) )
# Bottom
valNew <- heights.bottom[[ i ]]
valOld <- stats.row[[ max(lstCur[[2]]) ]]$heights.bottom.max
if ( is.null( valOld ) ) valOld <- unit( 0, "cm" )
stats.row[[ max(lstCur[[2]]) ]]$heights.bottom.max <- max( do.call( unit.c, list(valOld, valNew) ) )
}
for(i in seq_along(dots)){
lstCur <- lstAll[[i]]
nWidthLeftMax <- stats.col[[ min( lstCur[[ 3 ]] ) ]]$widths.left.max
nWidthRightMax <- stats.col[[ max( lstCur[[ 3 ]] ) ]]$widths.right.max
nHeightTopMax <- stats.row[[ min( lstCur[[ 2 ]] ) ]]$heights.top.max
nHeightBottomMax <- stats.row[[ max( lstCur[[ 2 ]] ) ]]$heights.bottom.max
pushViewport( viewport( layout.pos.row=lstCur[[2]],
layout.pos.col=lstCur[[3]], just=c("left","top") ) )
pushViewport(viewport(
x=unit(0, "npc") + nWidthLeftMax - widths.left[[i]],
y=unit(0, "npc") + nHeightBottomMax - heights.bottom[[i]],
width=unit(1, "npc") - nWidthLeftMax + widths.left[[i]] -
nWidthRightMax + widths.right[[i]],
height=unit(1, "npc") - nHeightBottomMax + heights.bottom[[i]] -
nHeightTopMax + heights.top[[i]],
just=c("left","bottom")))
grid.draw(dots[[i]])
upViewport(2)
}
}
#-----\align function-----
# edge margins
margin1 = 0.1
margin2 = -0.9
margin3 = 0.5
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = x, y = depth, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.text.x = theme_blank(), axis.ticks = theme_blank(), axis.title.x = theme_blank())
plot1 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin2,"lines"), unit(margin3,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = y, y = depth, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.text.x = theme_blank(), axis.ticks = theme_blank(), axis.title.x = theme_blank(), axis.text.y = theme_blank(), axis.title.y = theme_blank())
plot2 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin2,"lines"), unit(margin2,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = z, y = depth, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.text.x = theme_blank(), axis.ticks = theme_blank(), axis.title.x = theme_blank(), axis.text.y = theme_blank(), axis.title.y = theme_blank())
plot3 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin2,"lines"), unit(margin2,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = x, y = price, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.text.x = theme_blank(), axis.ticks = theme_blank(), axis.title.x = theme_blank())
plot4 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin2,"lines"), unit(margin3,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = y, y = price, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.text.x = theme_blank(), axis.ticks = theme_blank(), axis.title.x = theme_blank(), axis.text.y = theme_blank(), axis.title.y = theme_blank())
plot5 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin2,"lines"), unit(margin2,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = z, y = price, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.text.x = theme_blank(), axis.ticks = theme_blank(), axis.title.x = theme_blank(), axis.text.y = theme_blank(), axis.title.y = theme_blank())
plot6 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin2,"lines"), unit(margin2,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = x, y = carat, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.ticks = theme_blank())
plot7 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin3,"lines"), unit(margin3,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = y, y = carat, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.ticks = theme_blank(), axis.text.y = theme_blank(), axis.title.y = theme_blank())
plot8 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin3,"lines"), unit(margin2,"lines")))
plot <- ggplot(data = dsmall) + geom_point(mapping = aes(x = z, y = carat, colour = cut)) + opts(legend.position="none")
plot <- plot + opts(axis.ticks = theme_blank(), axis.text.y = theme_blank(), axis.title.y = theme_blank())
plot9 <- plot + opts(plot.margin=unit.c(unit(margin1, "lines"), unit(margin1,"lines"), unit(margin3,"lines"), unit(margin2,"lines")))
grid_layout <- grid.layout( nrow=3, ncol=3, widths=c(2,2,2), heights=c(2,2,2) )
grid.newpage()
pushViewport( viewport( layout=grid_layout ) )
align.plots( grid_layout,
list( plot1, 1, 1 ),
list( plot2, 1, 2 ),
list( plot3, 1, 3 ),
list( plot4, 2, 1 ),
list( plot5, 2, 2 ),
list( plot6, 2, 3 ),
list( plot7, 3, 1 ),
list( plot8, 3, 2 ),
list( plot9, 3, 3 ) )
}
原始图片：
当前进度图片：
2 个答案:
答案 0 :(得分：3)
align.plots包中有一个函数ggExtra。
从ggplot2邮件列表中检查这个帖子：
Aligning time series plots
aligned plots http://img138.imageshack.us/img138/6786/aligngrid.png
答案 1 :(得分：3)
这是ggplot2和melt的简单方法：
diamonds_sample <- diamonds[sample(nrow(diamonds), 100), ]
melted_diamonds <- melt(diamonds_sample, measure.vars=c('x','y','z'),
variable_name='letter')
# rename the melt results to avoid confusion with next melt
# (bug in melt means you can't rename the value during melt)
names(melted_diamonds)[9] <- 'letter.value'
melted_diamonds <- melt(melted_diamonds,
measure.vars=c('depth', 'price', 'carat'), variable_name='variables')
ggplot(melted_diamonds, aes(x=letter.value, y=value, colour=cut)) +
geom_point() + facet_grid(variables~letter, scale='free')
<强>结果：
您可以使用所有ggplot2选项进行操作，以使标签显示在适当的位置，然后删除图例。
注意：对于这样的图，您想要成对地比较大量变量，请查看the GGally package。这里有一些文档：http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=GGally:ggpairs。
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