[R] Exporting objects plotted with plot3d() - rgl package

Alejandro González jano at rjb.csic.es
Wed Apr 22 18:18:52 CEST 2009


Dear all,
Can anybody tell me how to export a 3d figure made with the plot3d 
function? I'm careless about whether it's still interactive or not in 
another format, as long I can get it out of R.
Thanks!

Alejandro González
Departamento de Biodiversidad y Conservación
Real Jardín Botánico
Consejo Superior de Investigaciones Científicas

Claudio Moyano, 1
28014 Madrid, Spain

Tel +0034 914203017



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> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 21 Apr 2009 11:03:52 +0100
> From: William Simpson <william.a.simpson at gmail.com>
> Subject: [R] line wrap in R console under windows
> To: r-help at r-project.org
> Message-ID:
> 	<21ce39b20904210303h34a95282q122dc554cb7ca0de at mail.gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1
>
> I would like the R console to wrap lines at 80 cols.
> It does not do so, even though I have used the Rgui Configuration
> Editor to set the Console cols at 80 and the Pager cols at 80.
>
> Please tell me how to set it up so I have word wrap.
>
> Just to be clear: in older/other R versions, console input is wrapped
> at 80 cols and so you have something that looks like
>   
>> blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah
>>     
>  blah blah blah blah blah blah blah blah blah blah blah blah blah blah
> blah blah blah blah
> Instead of what I see, which is
>   
>> blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah$
>>     
> and I need to scroll sideways to see the rest of the stuff past $
>
> I checked the archives and saw no postings on this.
>
> Thanks very much for any help.
>
> Bill
>
>
>
> ------------------------------
>
> Message: 2
> Date: Tue, 21 Apr 2009 11:10:10 +0100
> From: William Simpson <william.a.simpson at gmail.com>
> Subject: [R] lme for between-within anova
> To: r-help at r-project.org
> Message-ID:
> 	<21ce39b20904210310i139a53berd38642cddd13038a at mail.gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1
>
> I have the following between-within anova:
> aovn1 <- aov(amplitude ~ stereo*site*stimulus +
> Error(subject/(site*stimulus)), stereon1)
>
> This works fine. BUT I need to do Tukey HSD multiple comparisons, and
> the aov() approach won't work. So I am trying the method posted on
> r-help:
> lmen1 <- lme(amplitude ~ stereo*site*stimulus, random =
> ~1|subject/(site*stimulus), stereon1)
>
> This doesn't work:
>   
>> lmen1 <- lme(amplitude ~ stereo*site*stimulus, random = ~1|subject/(site*stimulus), stereon1)
>>     
> Error in getGroups.data.frame(dataMix, groups) :
>         Invalid formula for groups
>
> Please tell me what to do to get the lme() fit to work.
>
> After I get lmen1, I will do:
> anova(lmen1)
>
> summary(lmen1)
> summary(glht(lmen1, linfct=mcp(V="Tukey")))
>
> Please tell me if that sounds right.
>
> Thanks very much for any help!
>
> Bill
>
> ============= This is the example I am following (with modifications
> for my expt design)
> You want to use lme() in package nlme, then glht() in the multcomp
> package.  This will give you multiplicity adjusted p-values and
> confidence intervals.
>
> ## Example
> require(MASS)         ## for oats data set
> require(nlme)         ## for lme()
> require(multcomp)  ## for multiple comparison stuff
>
> Aov.mod <- aov(Y ~ N + V + Error(B/V), data = oats)
> Lme.mod <- lme(Y ~ N + V, random = ~1 | B/V, data = oats)
>
> summary(Aov.mod)
> anova(Lme.mod)
>
> summary(Lme.mod)
> summary(glht(Lme.mod, linfct=mcp(V="Tukey")))
>
>
>
> ------------------------------
>
> Message: 3
> Date: Tue, 21 Apr 2009 12:12:34 +0200
> From: Liviu Andronic <landronimirc at gmail.com>
> Subject: Re: [R] joined R-today
> To: Bala subramanian <bala.biophysics at gmail.com>
> Cc: r-help at r-project.org
> Message-ID:
> 	<68b1e2610904210312g651337b6v3c4d0d29d0bd41df at mail.gmail.com>
> Content-Type: text/plain; charset=UTF-8
>
> On Tue, Apr 21, 2009 at 11:57 AM, Bala subramanian
> <bala.biophysics at gmail.com> wrote:
>   
>> Dear Simon,
>> I installed the ncdf package in the way you suggested but still i got the
>> same error i got before. I haves pasted below the installation log and
>> errors.
>>
>>     
> Does ncdf depend on netcdf [1]? If so, perhaps it is missing, or is
> not up-to-date. Also, it's a good habit to install.packages('ncdf',
> dep=TRUE).
> Regards,
> Liviu
>
> [1] http://www.unidata.ucar.edu/software/netcdf/
>
>
>
> ------------------------------
>
> Message: 4
> Date: Tue, 21 Apr 2009 06:12:32 -0400
> From: "John Sorkin" <jsorkin at grecc.umaryland.edu>
> Subject: [R] Package or packages for randomization in a clinical trial
> To: <r-help at r-project.org>
> Message-ID: <49ED63CE.91DF.00CB.0 at grecc.umaryland.edu>
> Content-Type: text/plain; charset=US-ASCII
>
> Can anyone recommend a package that can be used to randomize subjects? I am looking for a generalized package, or several packages that can accomplish 
> unrestricted randomization (i.e. simple random assignment)
> restricted randomization including stratified randomization, blocked randomization, and adaptive randomization.
> Thanks,
> John
>
> John David Sorkin M.D., Ph.D.
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology
> Baltimore VA Medical Center
> 10 North Greene Street
> GRECC (BT/18/GR)
> Baltimore, MD 21201-1524
> (Phone) 410-605-7119
> (Fax) 410-605-7913 (Please call phone number above prior to faxing)
>
> Confidentiality Statement:
> This email message, including any attachments, is for th...{{dropped:6}}
>
>
>
> ------------------------------
>
> Message: 5
> Date: Tue, 21 Apr 2009 12:21:09 +0200
> From: Bala subramanian <bala.biophysics at gmail.com>
> Subject: Re: [R] joined R-today
> To: Liviu Andronic <landronimirc at gmail.com>
> Cc: r-help at r-project.org
> Message-ID:
> 	<288df32a0904210321l64d25470yea9aef47c5859221 at mail.gmail.com>
> Content-Type: text/plain
>
> Hi,
> Yes ncdf needs netcdf, netcdf is already installed in my fedora10. I
> reinstalled ncdf with the following option
>   
>> install.packages('ncdf',dep=TRUE)
>> library(ncdf)> library(ncdf)
>>     
> Error in dyn.load(file, DLLpath = DLLpath, ...) :
>   unable to load shared library '/usr/lib/R/library/ncdf/libs/ncdf.so':
>   /usr/lib/R/library/ncdf/libs/ncdf.so: cannot restore segment prot after
> reloc: Permission denied
> Error in library(ncdf) : .First.lib failed for 'ncdf'
>
> Again the same error,
> Bala
>
>
> On Tue, Apr 21, 2009 at 12:12 PM, Liviu Andronic <landronimirc at gmail.com>wrote:
>
>   
>> On Tue, Apr 21, 2009 at 11:57 AM, Bala subramanian
>> <bala.biophysics at gmail.com> wrote:
>>     
>>> Dear Simon,
>>> I installed the ncdf package in the way you suggested but still i got the
>>> same error i got before. I haves pasted below the installation log and
>>> errors.
>>>
>>>       
>> Does ncdf depend on netcdf [1]? If so, perhaps it is missing, or is
>> not up-to-date. Also, it's a good habit to install.packages('ncdf',
>> dep=TRUE).
>> Regards,
>> Liviu
>>
>> [1] http://www.unidata.ucar.edu/software/netcdf/
>>
>>     
>
> 	[[alternative HTML version deleted]]
>
>
>
> ------------------------------
>
> Message: 6
> Date: Tue, 21 Apr 2009 22:25:01 +1200
> From: Seyit Ali Kayis <s_a_kayis at hotmail.com>
> Subject: [R] Sampling in R
> To: <r-help at r-project.org>
> Message-ID: <BAY105-W34886F283B2E531D6C5844B4770 at phx.gbl>
> Content-Type: text/plain
>
>
> Dear R users, 
>
> I need to do sampling without replacement (bootstraps). I have two variables (Xvar, Yvar). 
> I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am doing 50000 sampling, 
> and in each sampling  calculating correlations, saving, sorting and  getting 95% cutt off point (0.1351877). 
> I am getting maximum value as 0.3507219 (much smaller than correlation of my original data). 
> I repeated the sampling a  couple of time and none of them produced a correlation 
> coefficient higher than my original data set. However, if I sort out my Xvar and Yvar and 
> obtain correlation it is 0.9657125 which is much higher than correlation for my original data. 
> I am doing sampling in another program and getting at least 1% higher correlation than mine. 
> Now I am getting confused with sampling(random data) in R. My data and codes for the scenario above are below
>
>
> Xvar<-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
>         0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.1333333,0.1818182,0.1702128,
>         0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.4666667,0.4464286,0.362069,0.4285714,0.4561404,
>         0.4736842,0.4545455,0.4166667,0.4181818,0.4590164,0.5166667,0.5423729,0.4833333,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
>         0.5166667,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.4583333,0.3877551,0.4375,0.4117647,0.4313725,0.5333333,0.3962264,
>         0.3548387,0.5272727,0.4137931,0.3928571,0.4666667,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.4333333,0.4,0.4285714,
>         0.4516129,0.5090909,0.4464286,0.4642857,0.4166667,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
>         0.5925926,0.5769231,0.5818182,0.4444444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
>         0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
>         0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
>         0.4576271,0.5471698,0.4745763,0.4821429)
>
> Yvar<-c(0.2553191,0.4107143,0.5660377,0.3888889,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
>         0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.1166667,0.1785714,
>         0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
>         0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
>         0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
>         0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.4722222,0.5,0.3521127,0.4393939,0.3787879,
>         0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.3666667,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
>         0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
>         0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.3666667,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
>         0.4821429,0.5,0.557377,0.4333333,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
>
> my.cor<-cor(Xvar, Yvar)
> print(my.cor)
>  
> nperm<-49999
> Perm.Cor<-NULL
>
> for (iperm in 1:nperm)  {
> XvarNew<-sample(Xvar, size=length(Xvar), replace=FALSE)    
> YvarNew<-sample(Yvar, size=length(Yvar), replace=FALSE)     
> perm.cor<-cor(XvarNew, YvarNew)
> Perm.Cor<-c(Perm.Cor, perm.cor)
>                         }
> print(max(Perm.Cor))
> XvarSorted<-sort(Xvar, decreasing=TRUE)
> YvarSorted<-sort(Yvar, decreasing=TRUE)
> max.cor<-cor(XvarSorted, YvarSorted)
> print(max.cor)
> if(mat.cor>0) Perm.Cor.Sorted<-sort(Perm.Cor, decreasing=TRUE)                        
> if(mat.cor<0) Perm.Cor.Sorted<-sort(Perm.Cor, decreasing=FALSE)                        
> T95<-Perm.Cor.Sorted[(nperm+1)*0.05]    # 95% treshold value
> T99<-Perm.Cor.Sorted[(nperm+1)*0.01]    # 99% treshold value
>
>  
>
> I want to understand where I am making a mistake. Any comment is deeply appreciated.
>
> Kind Regards
>
> Seyit Ali
>
>
> ------------------------------------------------------------------------------------------------------------------ 
> Dr. Seyit Ali KAYIS
> Selcuk University
> Faculty of Agriculture
> Kampus, Konya, TURKEY
>
>             s_a_kayis at yahoo.com,    s_a_kayis at hotmail.com
> Tell: +90 332 223 2830  Mobile: +90 535 587 1139  Fax: +90 332 241 0108
>
>                    Greetings from Konya, TURKEY
>                 http://www.ziraat.selcuk.edu.tr/skayis/
> ---------------------------------------------------------------------------------------------------------------------- 
>
>
>
>
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>
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> ------------------------------
>
> Message: 7
> Date: Tue, 21 Apr 2009 03:52:57 -0700 (PDT)
> From: onyourmark <william108 at gmail.com>
> Subject: [R]  search through a matrix
> To: r-help at r-project.org
> Message-ID: <23153538.post at talk.nabble.com>
> Content-Type: text/plain; charset=us-ascii
>
>
> Hi. I have a 925 by 925 correlation matrix corM. I want to identify all
> variables that have correlation greater than 0.9.  Can anyone suggest an "R
> way" of doing this?
>
> Thank you.
>




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