2012-10-02 311 views
5

我有一個主要是整容問題。我使用ggplot2庫創建了四個圖,然後我將它安排在一列中(使用)。圖表顯示相同的數據,但對於四組,x軸是時間,這就是爲什麼我想將圖保存在單個列中的原因。R使用ggplot2(圖例和軸更改大小)一致的圖形大小

因此,我將圖例添加到頂部圖形,並將x軸的標籤添加到底部圖形。這兩個動作改變了圖形的大小;添加圖例會導致圖形增長,添加x軸標籤會使其縮小以適應這些情況。

有沒有辦法指定一個固定的圖形大小,這將使我的佈局一致?

我的情節: plot

代碼重複的結果:

library(ggplot2) 
library(reshape) 

raw_data <- structure(list(Sample = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
23L, 24L, 25L, 26L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 
24L, 25L, 26L), Month = structure(c(12L, 12L, 11L, 11L, 10L, 
10L, 3L, 3L, 5L, 5L, 4L, 4L, 8L, 8L, 1L, 1L, 9L, 9L, 7L, 7L, 
6L, 6L, 2L, 2L, 12L, 12L, 12L, 12L, 11L, 11L, 10L, 10L, 3L, 3L, 
5L, 5L, 4L, 4L, 8L, 8L, 1L, 1L, 9L, 9L, 7L, 7L, 6L, 6L, 2L, 2L, 
12L, 12L), .Label = c("April", "Aug", "Dec", "Feb", "Jan", "July", 
"June", "March", "May", "Nov", "Oct", "Sep"), class = "factor"), 
    Channel = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", 
    "B"), class = "factor"), Amplitude = c(5000L, 
    5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 
    5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 
    5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 
    5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L, 5000L)), .Names = c("Sample", 
"Month", "Channel", "Amplitude"), row.names = c(NA, 52L), class = "data.frame") 



multiplot <- function(..., plotlist=NULL, cols) { 
    require(grid) 

    # Make a list from the ... arguments and plotlist 
    plots <- c(list(...), plotlist) 

    numPlots = length(plots) 

    # Make the panel 
    plotCols = cols       # Number of columns of plots 
    plotRows = ceiling(numPlots/plotCols) # Number of rows needed, calculated from # of cols 

    # Set up the page 
    grid.newpage() 
    pushViewport(viewport(layout = grid.layout(plotRows, plotCols))) 
    vplayout <- function(x, y) { 
      viewport(layout.pos.row = x, layout.pos.col = y) 
    } 

    # Make each plot, in the correct location 
    for (i in 1:numPlots) { 
     curRow = ceiling(i/plotCols) 
     curCol = (i-1) %% plotCols + 1 
     print(plots[[i]], vp = vplayout(curRow, curCol)) 
    } 

} 


mybarplot <- function(first=0, last=0) { 
    # Create the barplot 
    p <- ggplot(raw_data, aes(x=Sample, y=Amplitude, fill=Channel)) 

    # Make it a grouped barplot with already summarised values 
    p <- p + geom_bar(position="dodge", stat="identity") 


    # Apply a log10 transformation to the y-axis, and create appropriate axis ticks 
    p <- p + scale_y_log10(breaks = c(5,10,50,100,500,1000,5000,10000)) 

    # Zoom in (barplots will not show when axis change to remove 0, so have to zoom) 
    p <- p + coord_cartesian(ylim=c(1,15000), xlim=c(1,26)) 

    # Make it greyscale 
    p <- p + scale_fill_grey() 


    # Hide X label 
    p <- p + opts(axis.text.x=theme_blank(), axis.title.x=theme_blank(), axis.title.y=theme_blank()) 
    # Change X label size 
    p <- p + opts(axis.text.y=theme_text(size=7)) 



    # Change the Legend 
    p <- p + scale_fill_manual(values=c("black", "grey75", "grey25"), name="Channel", breaks=c("A", "B")) 

    #margins 
    # c(top,,bottom,) 
    top_margin <- unit(c( 1, 1, -0.25, 1), "lines") 
    middle_margin <- unit(c(-0.25, 1, -0.25, 1), "lines") 
    bottom_margin <- unit(c(-0.25, 1,  2, 1), "lines") 


    if (first) { 
     # Anchor legend box to top right corner 
     p <- p + opts(legend.justification=c(1,1), legend.position=c(1,1)) 
     # Put a white box around it 
     p <- p + opts(legend.background = theme_rect(fill="white")) 
     # Top margin 
     p <- p + opts(plot.margin = top_margin) 
     p <- p + scale_x_discrete(breaks = 1:26) 
    } else { 
     p <- p + opts(legend.position="none") 
     if (last) { 
      # Bottom margin 
      p <- p + opts(plot.margin = bottom_margin) 
       # label X-axis 
      p <- p + scale_x_discrete(breaks = 1:26, labels=c("Sep", "", "Oct", "", "Nov", "", "Dec", "", "Jan", "", "Feb", "", "March", "", "April", "", "May", "", "June", "", "July", "", "Aug", "", "Sep", "")) 

      p <- p + ylab("Amplitude") 
      p <- p + xlab("Sampling time") 
      # Angle x labels 
      #p <- p + opts(axis.text.x=theme_text(angle=-45, hjust=0.5)) 
      p <- p + opts(axis.text.x=theme_text(hjust=0.5)) 

      # Move X title 
      p <- p + opts(axis.title.x=theme_text(vjust=-0.5)) 
     } else { 
      p <- p + opts(plot.margin = middle_margin) 
      p <- p + scale_x_discrete(breaks = 1:26) 
     } 
    } 



} 


plot1 <- mybarplot(first=1) 
plot2 <- mybarplot() 
plot3 <- mybarplot() 
plot4 <- mybarplot(last=1) 

multiplot(plot1, plot2, plot3, plot4, cols=1) 

會議信息:

> sessionInfo() 
R version 2.15.1 (2012-06-22) 
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) 

locale: 
[1] C 

attached base packages: 
[1] grid  stats  graphics grDevices utils  datasets methods base  

other attached packages: 
[1] reshape_0.8.4 plyr_1.7.1 ggplot2_0.9.1 

loaded via a namespace (and not attached): 
[1] MASS_7.3-18  RColorBrewer_1.0-5 colorspace_1.1-1 dichromat_1.2-4 digest_0.5.2  labeling_0.1  memoise_0.1  munsell_0.3  proto_0.3-9.2  reshape2_1.2.1  
[11] scales_0.2.1  stringr_0.6.1  
+0

你可以顯示你用來製作劇情的代碼,以便你的問題是[reproducible](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example )。 – Justin

+0

對不起。增加了代碼來重現它。 – NFA

回答

5

在您的例子中,每個情節都是相同的,但是我認爲是不最終產品的計劃。我認爲最簡單的方法就是分面,而不是單獨佈置每個區域。

dat <- data.frame(facetvar=letters[1:5], yvar=rep(1:10, each=5), xvar=rep(letters[6:10], each=5)) 
ggplot(dat, aes(x=xvar, y=yvar, group=facetvar)) + 
    geom_bar(stat='identity') + 
    facet_grid(facetvar~.) 

如果需要,可以先將數據子集並使用任意分面變量。

ggplot(dat[sample(1:50, 40),], aes(x=xvar, y=yvar, group=facetvar)) + 
    geom_bar(stat='identity') + 
    facet_grid(facetvar~.) 

如果需要,您還可以提供scales.y='free'facet_grid()

+0

是的,我的例子中的數據是相同的,但它不會在最終的圖表中。那只是因爲它是重現它的最快方法。尺寸差異仍然存在。 爲了使用方面,我需要我所有的數據在1幀,對不對?就像現在我從4個獨立的文件中獲取數據一樣,我需要先轉換並融合數據。我會考慮在明天工作,但我擔心把它們合併成一個單一的數據框會很棘手。 – NFA

+0

你說得對,你需要一個'data.frame'。然而,在你融化之後,你通常可以添加一個任意的「facet」列,並使用類似'rbind()'的東西把它們混合在一起。 – Justin

+1

它不應該是棘手的。將四個數據集中的響應和預測值列重命名爲相同的值,爲每個給出方面ID的列添加一個列(通過'rep(ID,length(data))',綁定它們,然後使用facet語句重新繪製 – Chris