Faheem Mitha | 18 May 2013 17:39

ggplot2 0.9.3.1 tests failing on Debian squeeze with R 2.15.3


Hi,

ggplot2 tests are failing for me. I'm running the tests with

faheem <at> orwell:/usr/local/src/ggplot2/r-cran-ggplot2-0.9.3.1/tests$ Rscript test-all.R

Is this correct? If so, would someone be willing to look at the output? If 
so, where should I post it? To this mailing list, inline or as an 
attachment, or elsewhere? Obviously, the output is quite large. Please CC 
me on any reply. Thanks.

                                                           Regards, Faheem

> sessionInfo()
R version 2.15.3 (2013-03-01)
Platform: i486-pc-linux-gnu (32-bit)

locale:
  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
  [7] LC_PAPER=C                 LC_NAME=C
  [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

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

--

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(Continue reading)

Miao | 18 May 2013 16:53
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Is there any way to see the range of the graph created by ggplot?

 

p<-ggplot(…….)

 

If xlim and ylim are not set with the ggplot function, then the range of the graph is determined automatically by ggplot. Is there any way to see the range of the graph?

 

Range <- somefunction(p)

Or

Range <-p$.....  ?

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Ryan Hope | 18 May 2013 14:56
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Combining geoms & scales

I am working on a R package for eyetracking reasearch and in it I provide some functions to visual data with ggplot2. Some of the visualizations are stand alone plots but others work well as layers that could be combined with other plots. I've created some "custom" geoms by simply wrapping pre-existing geoms in a function so that I can transform in input into ggplot friendly arguments. This works fine for most cases but I have run into a few situations where I would like to combine 2 geoms into one. For example, I would like to do something like this:

geom_grid <- function() {
 geom_hline() + geom_vline()
}

which obviously throws a "non-numeric argument to binary operator" error. The same thing goes for creating a function to set both x and y scales with one function. Is there an easy way to do this?

--
Ryan Hope, M.S.
CogWorks Lab
Cognitive Science Department
Rensselaer Polytechnic Institute

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G Land | 18 May 2013 09:50
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Re: scale & breaks & minor_breaks

I tried your code. But I don't see any minor breaks. Am I missing something? My plot attached.
Thanks.
G






On Friday, April 30, 2010 3:43:07 PM UTC-7, fgtaboada wrote:
Don't know if you are looking to something like this (also note my absolute
ignorance on rpy2), but hope this helps

library(ggplot2)
df <- data.frame(x = c(2:6), y = 10^c(2:6))
mbreaks_y <- round(range(log10(df$y)))
qplot(x, y, data = df) +
        scale_y_log10(breaks = 10^c(mbreaks_y[1]:mbreaks_y[2]),
                minor_breaks = rep(10^c(mbreaks_y[1]: (mbreaks_y[2] - 1) ),
each = 9) *
                rep(1:9, mbreaks_y[2] - mbreaks_y[1]))


-----Mensaje original-----
De: ggp...-/JYPxA39Uh5TLH3MbocFFw@public.gmane.org [mailto:ggp... <at> googlegroups.com] En nombre de
John Owens
Enviado el: viernes, 30 de abril de 2010 17:54
Para: ggplot2
Asunto: scale & breaks & minor_breaks

I'd like to wrangle scale_y_log10 into putting major and minor lines
where I want them. (The current graph I'm drawing puts 2 major lines
and 2 minor lines per decade by default. I'd like instead 1 major line
per decade, at 10^x, and 9 minor lines.)

What is working is if I call (I'm using rpy2, so the syntax might be
off as I'm translating to R):

      scale_y_log10(breaks="10**(0:10)",
minor_breaks=([1,2,3,4,5,6,7,8,9,10,20,30,40,50,60,70,80,90,100,200,300,400,
500,600,700,800,900,1000,2000,3000,4000,5000,6000,7000,8000,9000,10000]))
+ \

but then I'm just putting them in manually.

I'd much rather be able to say "draw one break every decade and 9
evenly spaced minor breaks every decade" rather than have to type them
in manually. Any way to do this?

JDO

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Yasutaka Hirasawa | 17 May 2013 22:10
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color line segment with ggplot?

wonder if we can generate the same chart using ggplot2?

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adam.loveland | 17 May 2013 20:42
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faceting distr in terms of percents (nominal values)

Hi,

A couple of weeks ago Dennis answered my question as to how to bin (and facet) an interval variable so that its distribution is in terms of the percent of total.

It involved multiplying the density by the binwidth. However, this solution  not surprisingly does not work when the x axis is a nominal variable and binning is not required.

Does anyone know a solution to this problem?

Below is an example in which I would like the y axis to be the % of total instead of the frequency. Thanks for your help.

ggplot(diamonds,aes(cut))+geom_histogram()+facet_grid(clarity~color)


Adam Loveland


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afkoeppel | 17 May 2013 18:35
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ggplot2 with both stat_binhex and scale_x_log10

Hello everyone.  

I'm trying to make a scatter plot with ggplot2, but I'm running into an issue.

I want to use scale_x_log10 and scale_y_log10 to make both the axes logarithmic.  I also want to use stat_binhex to show the density of points.  My code works when I use either one without the other, but when I use both together, I get the following error:

Error in if (!missing(xbnds) && any(sign(xbnds - range(x)) == c(1, -1))) stop("'xbnds' must encompass range(x)") : 
  missing value where TRUE/FALSE needed

My code is below.  I'm running R version 2.15.2.  

library(ggplot2)
g <- ggplot(unfilttable, aes(x=matchlist, y=mismatchlist))
#g <- g + geom_point(shape=1)
g <- g + stat_binhex(bins=20)
g <- g + scale_x_log10()
g <- g + scale_y_log10()
g

Is it possible (or reasonable?) to do the binhex thing on a log scale?

Thanks,

Alex

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Miao | 17 May 2013 09:47
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Create a plot with many lines and points by loops

Hi, 


   I would like to create a plot with 40 lines and 40 sets of points. The sizes of the datasets are unequal. I wonder how I could do it in ggplot2. This is a toy example I try, but I just see 2 lines and the corresponding point sets in the first graph "p_test" and see 1 lines and  the corresponding point sets in the first graph "p_test2". How could it be modified in order to see all the three lines and the corresponding point sets ? Thanks,

Miao


rm(list=ls())

library(ggplot2)

 

 

x1<-1:4

y1<-6:9

x2<-seq(1.5, 4.5, 1)

y2<-seq(5.5, 8.5, 1)

x3<-seq(4,10,2)

y3<-seq(5,-1,-2)

 

dft<-data.frame(x1,y1,x2,y2,x3,y3)

p_test<-ggplot(dft, aes(dft[,1], dft[,2]))+ geom_point()+

  geom_line(data=dft, aes(dft[,1], dft[,2]))

for(i1 in 2:3)

{

  p_test<-p_test+geom_point(data = dft, aes(dft[,i1*2-1],dft[,i1*2]))+

    geom_line(data=dft, aes(dft[,i1*2-1],dft[,i1*2]))

}

 


p_test2<-ggplot(NULL)+geom_point()

for(i2 in 1:3)

{

  p_test2<-p_test2+geom_point(data =dft, aes(dft[,i1*2-1],dft[,i1*2]))+

    geom_line(data=dft, aes(dft[,i1*2-1],dft[,i1*2]))

}

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catherine.planey | 16 May 2013 20:40
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forest plots in ggplot2: uneven scaling causing skewed/misplaced error bars

Hi ggplot group,


I've been trying to fix a bug in my forest plots for a few weeks now (officially driving me crazy). 


The problem is that the axes do not pop out uniformly scaled. Seems like multiple things are going on here, even though the plot only needs 1 line of code from the R-bloggers tutorial: http://www.r-bloggers.com/forest-plots-using-r-and-ggplot2/  


The bars are oftentimes placed with flipped signs so that they don't fall on the mean value. Even the zero hline() isn't on the right scale.  I've tried using geom_errorbar() instead and scaling options, but I'm throwing in the towel. Does anyone have any suggestions? I think something's up with my data frame. Code is below.


Best,

Katie

___

Katie Planey

Stanford Biomedical Informatics

Butte Lab | http://buttelab.stanford.edu/




  p <-ggplot(data, aes(x=study_names,y=g,ymin=gMin,ymax=gMax)) +geom_pointrange() + geom_hline(aes(x=0), lty=2) + coord_flip()

 

plot(p)



#My dataset is below - it's effect sizes (g) and max/min (g+ standard deviation) for a meta-analysis of microarray data from different studies. 

#I just created a data frame with the relevant statistics:

data <- structure(list(study_names = structure(1:9, .Names = c("GSE19615_GPL570_g", 

"GSE19697_GPL570_g", "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", 

"GSE25065_GPL96_LBJ_g", "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", 

"GSE25065_GPL96_PERU_g", "GSE25065_GPL96_USO_g"), .Label = c("GSE19615_GPL570_g", 

"GSE19697_GPL570_g", "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", 

"GSE25065_GPL96_LBJ_g", "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", 

"GSE25065_GPL96_PERU_g", "GSE25065_GPL96_USO_g"), class = "factor"), 

    g = structure(c(1L, 8L, 6L, 3L, 2L, 4L, 9L, 7L, 5L), .Names = c("GSE19615_GPL570_g", 

    "GSE19697_GPL570_g", "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", 

    "GSE25065_GPL96_LBJ_g", "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", 

    "GSE25065_GPL96_PERU_g", "GSE25065_GPL96_USO_g"), .Label = c("-0.0880224564200254", 

    "-0.293760093370228", "-0.297381677328331", "-0.303845191315", 

    "-0.307510645327556", "-0.426248689072173", "-0.590197752144345", 

    "-0.60072930481096", "-1.13419569672925"), class = "factor"), 

    gMax = structure(c(9L, 6L, 3L, 4L, 8L, 2L, 7L, 5L, 1L), .Names = c("GSE19615_GPL570_g", 

    "GSE19697_GPL570_g", "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", 

    "GSE25065_GPL96_LBJ_g", "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", 

    "GSE25065_GPL96_PERU_g", "GSE25065_GPL96_USO_g"), .Label = c("-0.0644600967202706", 

    "-0.0646476363654359", "-0.10990976467328", "-0.166274833020161", 

    "-0.203680097076338", "-0.321207868946344", "-0.539150356441367", 

    "0.217241161839879", "0.289255627935715"), class = "factor"), 

    gMin = structure(c(2L, 7L, 5L, 1L, 6L, 3L, 9L, 8L, 4L), .Names = c("GSE19615_GPL570_g", 

    "GSE19697_GPL570_g", "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", 

    "GSE25065_GPL96_LBJ_g", "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", 

    "GSE25065_GPL96_PERU_g", "GSE25065_GPL96_USO_g"), .Label = c("-0.428488521636501", 

    "-0.465300540775766", "-0.543042746264564", "-0.550561193934842", 

    "-0.742587613471065", "-0.804761348580336", "-0.880250740675576", 

    "-0.976715407212353", "-1.72924103701714"), class = "factor"), 

    se.g = structure(c(6L, 4L, 5L, 1L, 8L, 2L, 9L, 7L, 3L), .Names = c("GSE19615_GPL570_g", 

    "GSE19697_GPL570_g", "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", 

    "GSE25065_GPL96_LBJ_g", "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", 

    "GSE25065_GPL96_PERU_g", "GSE25065_GPL96_USO_g"), .Label = c("0.13110684430817", 

    "0.239197554949564", "0.243050548607286", "0.279521435864616", 

    "0.316338924398893", "0.377278084355741", "0.386517655068008", 

    "0.511001255210108", "0.595045340287887"), class = "factor"), 

    study_names = c("GSE19615_GPL570_g", "GSE19697_GPL570_g", 

    "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", "GSE25065_GPL96_LBJ_g", 

    "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", "GSE25065_GPL96_PERU_g", 

    "GSE25065_GPL96_USO_g"), study_sizes = c(20, 24, 42, 99, 

    8, 28, 6, 10, 6)), .Names = c("study_names", "g", "gMax", 

"gMin", "se.g", "study_names", "study_sizes"), row.names = c("GSE19615_GPL570_g", 

"GSE19697_GPL570_g", "GSE22226_GPL1708_g", "GSE25055_GPL96_MDACC_M_g", 

"GSE25065_GPL96_LBJ_g", "GSE25065_GPL96_MDACC_g", "GSE25065_GPL96_MDACC_MDA_g", 

"GSE25065_GPL96_PERU_g", "GSE25065_GPL96_USO_g"), class = "data.frame")

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Ross Boylan | 16 May 2013 21:09
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Controlling legends and annotations

I'm having trouble controlling legends and adding annotations to some 
graphs:

  p <- ggplot(NHBS, aes(x=Age, y=Rate, group=Race, colour=Race))
   p1 <- p+geom_line()+labs(title="MSM HIV+ Prevalence by Race x Age, 2004, 2008, 2011 NHBS LA")
   # first graph fine
   plot(p1)
   p2 <- p1+geom_linerange(aes(ymin=Lower, ymax=Upper, size=2, alpha=0.5),
position=position_jitter(h=0, w=0.5))+geom_point(aes(size=Negative+Positive))
   # 2nd graph legends not so good
   plot(p2)
   dev.off()
   # Could not get next one to work well
   p3 <- p2+
     geom_text(aes(x=0.5, y=1, label="Courtesy of TA Bingham.  Not for redistribution.", colour="black"))+
       geom_text(aes(x=0.5,y=0.9, label="Bars are exact 95% profile likilihood CI's.", colour="black"))

The legend for the second graph looks like this
2
<series of increasingly large boxes with numbers next to them>

0.5
<line labeled as 0.5>

Race
<colored lines with race name>

The first 2 groups seem to be labelled with the constants for size in 
the first aes, and alpha.
The boxes under 2 probably reflect the range of sizes in the second aes.
The handling of Race is just what I want.

What I would like to show is a legend for size in the second aes,
with circles as the accompanying graphic. The points do appear as 
circles in the figure.

As for the 3rd plot I'm looking for a way to get a legend in. Optimally, 
it would appear below the graph, and the main graph would not take up 
the entire vertical space. Googling  revealed some methods that involved 
graphics primitives from base R, but a) isn't there a way to do it 
within ggplot2? and b) it's not really sufficient to overlay the plot, 
since I want to shrink it.

Thanks.
Ross Boylan

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Ravi | 16 May 2013 16:21
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text box with background colour

This is my first posting to this group.
I am interested in having a text box in my plot with black text, white background colour and a border with thin lines.
My example :
x=1:10;y=x^2
d1<-data.frame(x=x,y=y)
l1<-"Some text"
p1<-ggplot(data=d1,aes(x=x,y=y))+geom_point()+geom_line()+geom_text(data=NULL,x=2,y=75,label=l1)
How do I access the options for changing the attributes for the text. For the legend, I have noted that there is an option for changing the legend.background colour. Are there any corresponding options for the text?

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