Come ridurre le dimensioni di un video con VLC

Mi è accaduto più di una volta di dover ridurre le dimensioni di  video molto pesanti (per consentire poi una facile condivisione o rimaneggiamento).

Nonostante io non sia un esperto dell’argomento, me la sono sempre cavata egregiamente con l’uso di VLC. Immagino che tutti conosciate questo software gratuito per la visualizzazione di video (e molto altro). Altrimenti, vi consiglio di provarlo. Potete scaricarlo da qui.

Riportoqui la semplice procedura, un po’ come promemoria, un po’ con la speranza che possa essere utile a qualcuno.

Vi mostrerò la procedura su sistema operativo Ubuntu, ma i passi sono gli stessi anche su sistemi operativi Windows. L’esempio è riferito al solo compito di ridurre la dimensione di un video mp4 (senza conversione di formato). Comunque, il salvataggio in altro formato è molto semplice.

1) Aprite VLC
2) Dal menu “Media”, selezionate “Convert/Save”
3) Comparirà il pop-up “Open Media” (Figura 1). Dal Tab “File”, cliccate su “Add” per scegliere il file che volete ridurre.

4) Una volta aggiunto il file, il bottone “Convert/Save” diventerà attivo. Cliccateci sopra  (Figura 2)

5) A questo punto, vi sarà possibile settare alcuni parametri relativi alla conversione. Per farlo dovete cliccare sull’icona che ho evidenziato con un contorno rosso in Figura 3.

6) Si aprirà una nuova finestra. Selezionate il tab “Video Codec” e assicuratevi che i valori che compaiono nel tab “Encoding parameters” (parametri di encoding) siano settati sugli stessi valori mostrati in Figura 4. Giocare un po’ con Bitrate e Frame Rate potrebbe essere utile, ma fatelo a vostro rischio: molto spesso il risultato è che ci si trova con un video di qualità molto bassa!

7) A questo punto, cliccate sul tab “Resolution”. Per utenti non esperti (come me) questo è il metodo più facile e sicuro di ridurre la dimensione del video a livelli accettabili senza causare orrende diminuzioni di qualità. Nella mia esperienza, settare il parametro “Scale” a 0.75 dà in  genere buoni risultati, consentendo di ridurre decisamente la dimensione del file senza causare eccessive perdite nella qualità. In genere utilizzo questo valore. Settare “Scale”  più bassi consente di ridurre ulteriormente la dimensione del file, a spese della qualità. La scelta finale dipende dal livello di qualità e riduzione di dimensione che si desidera. In generale, non c’è bisogno di agire su altri settaggi. Potete cliccare sul bottone “Save” in basso a destra (Figura 5).

8) Adesso, selezionate il percorso e il nome del file che volete creare, premete “Start” e attendete; in alcuni minuti (a seconda della dimensione del file), il vostro file ridotto sarà pronto. .

Nota: Nel caso queste istruzioni non siano state utili, non demordete. Online ci sono decine di tutorial che offrono soluzioni lievemente diverse. Per utenti linux, ad esempio, ci sono varie soluzioni sul sempre valido AskUbuntu

Videos

compress, VLC

April 15, 2018

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How to downsample a video with VLC

I often find in a situation in which I receive very large videos that need to be compressed for being transferred or somehow managed.

I am not expert in the issue, so I found it very useful the use of VLC.

Here is the procedure, which is more a note to self, but will hopefully help people facing the same problem.

Let’s face the easy steps. These are valid both for Windows and Ubuntu, and are focused on the task of reducing the size of an mp4 video (no format conversion). Hoewever, extension to other tasks is simple and I might treat it in future posts.

1) Open VLC
2) From the Media menu, select “Convert/Save”
3) From the the “Convert” popup window click on Add, to select the file you want to downsample (Figure 1)

4) Once you have added the file, the Convert/Save button will become active. Click on it (Figure 2)

5) At this point, you will have the opportunity to check/edit the conversion settings, by clicking on the icon highlighted in red in Figure 3.

6) Click on the Video Codec tab and make sure that the Encoding parameters are as shown in Figure 4. Playing with Bitrate and Frame Rate parameters might be an option, but if you are not expert you might end up with a very low quality video.

7) Click on the Resolution tab. For non-experst (like me) this is the safest way to downsample the size of video. Setting a scale of 0.75 will generally end up in a significant reduction in file size without causing great loss of quality. I use this value often. Lower values will result in smaller files and lower quality. The final choice is up to you. You don’t need to act on other settings. You can click save on the bottom right corner of the window (Figure 5)

8) Now, just select the output file, click start and wait a little bit.

 

Note: Further details on how to downsample a video in Ubuntu can be found on the always helpful AskUbuntu

Videos

compress, VLC

April 14, 2018

1 Comment

How to remove GRUB from Ubuntu-Vista dual boot

Preface: when it comes to installing operating systems I am a script kiddie. Every time I find a solution to some problem I am so happy I want everyone to know. This is why I am publishing this post, although, as you will see, all of the merit goes to a “mysterious” user of askubuntu, anwar.
I was in a situation in which I had an old laptop with a small partition reserved for Linux Ubuntu and a large one for windows.
I decided to give the PC to my mum, who will never use Ubuntu, and she likely would have troubles in managing dual boot.
Thus, I set out to remove grub.

Note: I do not have any install disk, nor recovery disk. Maybe I had them, once, not sure. In case you have a recovery disk, then things are easier.

Luckily enough, I found the answers here on askubuntu (answer by Anwar):

I repost it (with minor modification), in case somenone else may need it.

1) First download bootsect.exe from here into the Download directory (Warning the download will bring you through some redirection, but at the end you will get the program).
2) Rename the file to bootsect.exe (the name should be _Getintopc.com_bootsect.exe)
3) press the windows key, type cmd.exe and on the result (The command prompt) start it as an “Administrator” by right clicking on the cmd icon, and select Run as Administrator.
4) In the new cmd.exe window, cd to your download directory. for example cd C:\Users\Lalu Patel\Downloads. _assuming your user name is “Lalu Patel”.
5) Then enter this command. bootsect.exe /nt60 ALL /force /mbr.
6) Restart your system to see that, Windows is automatically loading without grub.

At this point, if you need to resize your partition, just go to askubuntu and follow the instructions

linux, Uncategorized

dual-boot, grub, Ubuntu, vista

February 25, 2018

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Visualize KEGG pathway and fold enrichment

As a useful note to self, I paste here an easy example on the use of the pathview package by Weijun Luo to plot the log fold change of gene expression across a given KEGG pathway. This example is on Vitis vinifera (as the prefix vvi can suggest), but the approach is general.
Basically, you just need to feed pathview the pathway argument and a gene.data argument. In this case, gene.data is a named vector, with names being the (entrez) gene names, and the value is the log Fold Change.
I selected a pathway for which KEGG has a nice representation, you might not be so lucky!

library(pathview)
mypathway<-"vvi03060"
genes<-c("100241050","100243802","100244217","100244265","100247624","100247887","100248517","
100248990","100250268","100250385","100250458","100251379","100252350","100252527","100252725","
100252902","100253826","100254350","100254429","100254996","100255515","100256046","100256113","
100256412","100256941","100257568","100257730","100258179","100258854","100259285","100259443","
100260422","100260431","100261219","100262919","100263033","100264739","100265371","100266802","
100267343","100267692","100852861","100853033","100854110","100854416","100854647","100855182","
104879783","109122671")
logFC<-rnorm(length(genes),-0.5,1)
names(logFC)<-genes
pathview(gene.data=logFC,species="vvi",pathway=mypathway)

The result should be something like this:

R, Uncategorized

KEGG, pathview

November 14, 2017

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Perform pairwise Wilcoxon test, classify groups by significance and plot results

This post is the result of work performed in collaboration with my colleague Eleonora Paparelli (who actually did most of the work!). We wanted to compare several distributions using Wilcoxon test and summarize results (i.e. indicate the comparisons showing significant differences).
R base includes pairwise.wilcox.test to perform Wilcoxon rank sum test between all pairs of samples in a study.
A common way to represent significance in pairwise comparisons is the use of letters. Samples sharing a letter are not different from each other. Samples not sharing letters are different.
Library multcompView in R can take a square matrix of p-values and return letters for all samples.
Sadly enough, pairwise.wilcox.test returns a triangular matrix, so I had to write a small function – named tri.to.squ – to take the output of pairwise.wilcox.test and convert it in a suitable input for the multcompLetters function of multcompView.
Now we can easily plot the distributions as box plot and add the letters as text.

 

library(multcompView)

tri.to.squ<-function(x)
{
rn<-row.names(x)
cn<-colnames(x)
an<-unique(c(cn,rn))
myval<-x[!is.na(x)]
mymat<-matrix(1,nrow=length(an),ncol=length(an),dimnames=list(an,an))
for(ext in 1:length(cn))
{
 for(int in 1:length(rn))
 {
 if(is.na(x[row.names(x)==rn[int],colnames(x)==cn[ext]])) next
 mymat[row.names(mymat)==rn[int],colnames(mymat)==cn[ext]]<-x[row.names(x)==rn[int],colnames(x)==cn[ext]]
 mymat[row.names(mymat)==cn[ext],colnames(mymat)==rn[int]]<-x[row.names(x)==rn[int],colnames(x)==cn[ext]]
 }
 
}
return(mymat)
}
first.set<-cbind(rnorm(100,mean=1.8),1)
second.set<-cbind(rnorm(100,mean=0.9),2)
third.set<-cbind(rnorm(100,mean=1),3)

full<-rbind(first.set,second.set,third.set)

pp<-pairwise.wilcox.test(full[,1], full[,2], p.adjust.method = "none", paired = FALSE)
mymat<-tri.to.squ(pp$p.value)
myletters<-multcompLetters(mymat,compare="<=",threshold=0.05,Letters=letters)

boxplot(full[,1] ~ full[,2],ylab="Something nice",names=c("Set 1","Set 2","Set 3"),ylim=c(min(full[,1]),0.3+max(full[,1])))
text(c(1,2,3),0.2+max(full[,1]),c(myletters$Letters[1],myletters$Letters[2],myletters$Letters[3]))

R

March 25, 2017

10 Comments

Reading large data tables in R

Ok, I confess.

Until yesterday I was one of those still trying to read large data tables using read.table.

Then, I came across this thread in stackoverflow and I saw the light.

Since I noticed that a lot of people still struggle with read.table I decided to write this very brief post.

Imagine that you have your large file named “mylargefile.txt”. Then all you have to do is the following.

library(data.table)
mydata<-fread("mylargefile.txt")

I promise I’ll never go back to read.table again!

R

data.table, fread, large files, read.table

May 2, 2014

6 Comments

Summarize content of a vector or data.frame every n entries

I imagine that the same result can be achieved by a proper use of quantile, but I like to have an easy way to obtain summary statistics every n entries of my dataset be it a vector or data.frame.

The function takes three parameters: the R object on which we need to obtain statistics (x), how many entries should each summary contain (step, defaulting to 1000), and the function we want to apply (fun, defaulting to “mean”).

Then, it’s all about using aggregate.

The present version incorporates useful comments by pat and ap53!

summarize.by <- function(x,step=1000,fun="mean")
{
n <- NROW(x)
group<-sort(rep(seq(1,ceiling(n/step)),step)[1:n])
x <- data.frame(group,x)
x <- aggregate(x,by=list(x$group),FUN=fun)
x <- x[,-c(1,2)]
return(x)
}

Example application and result for a data.frame:

dummy<-data.frame(matrix(runif(100000,0,1),ncol=10))
summarize.by(dummy)
          X1        X2        X3        X4        X5        X6        X7
1  0.5081756 0.5206011 0.4972622 0.5060707 0.4907807 0.5063138 0.4982252
2  0.5014300 0.5093051 0.5015310 0.4718058 0.4931249 0.4882382 0.5084970
3  0.4994759 0.4979546 0.4964157 0.5138695 0.5018427 0.5228862 0.4980824
4  0.4970300 0.4953163 0.4954068 0.5157935 0.4770471 0.5000562 0.4960250
5  0.5118221 0.4967686 0.5114420 0.4945936 0.5016019 0.5003544 0.5016693
6  0.5026323 0.4995367 0.5003587 0.4970245 0.4992188 0.4993896 0.4873300
7  0.4911944 0.5081578 0.4858666 0.4974576 0.4864710 0.5022401 0.5058064
8  0.5050684 0.5021456 0.4970707 0.4829222 0.4980984 0.4901941 0.5053296
9  0.4910359 0.4883865 0.4915000 0.4984415 0.4941274 0.4933778 0.4964306
10 0.4832396 0.4986647 0.5017873 0.5008766 0.4952849 0.5036030 0.5084799
          X8        X9       X10
1  0.5052379 0.4906292 0.4916262
2  0.5074966 0.5117570 0.5183119
3  0.4988349 0.5029704 0.5077726
4  0.4889516 0.5066026 0.5078195
5  0.5068717 0.4988389 0.5018225
6  0.5010366 0.4870614 0.4827767
7  0.5148197 0.5083662 0.5037901
8  0.4979452 0.5273463 0.4944513
9  0.5130718 0.5061075 0.5058208
10 0.4896030 0.4911127 0.4956848

And for a vector

dummy<-runif(10000,0,1)
summarize.by(dummy)
 [1] 0.4914789 0.4908839 0.4951939 0.4928015 0.4911908 0.4994735 0.4947729
 [8] 0.5058204 0.5026956 0.5018375

R

aggregate, data.frame, R, summarize, vector

August 8, 2013

5 Comments

A biologist’s guide to linux “screen”

I write here a very concise guide to linux screen (ok, I assume you know something about linux, even if you are a biologist…).
It takes five minutes to learn and you can live with it for all of your life. Trust me, I’m a biologist!

Why screen?
If you work on a remote server and there is an interruption of your internet/LAN connection, all you were doing is gone. Screen prevents you against these data losses.
How does it work?
Simple. To create a screen or resume an existing screen you can use the ever useful command
screen -dR

Then, when you are in screen you can do all your work ignoring you are in screen except that you have a series of screen commands that help you create several screens inside the same terminal and also move around them.
Any screen command starts pressing at the same time ctrl-a (yes, even in mac).
AFTER pressing ctrl-a you can press one of the following letters:
c: create an additional screen
n: move to next screen (if existing)
p: move to previous screen (if existing)
d: detach screen

The only command that needs not be preceded by ctrl-a is exit. If you type exit inside screen you will quite screen and erase it from memory (so do not type exit if you have unsaved work).

linux, Uncategorized

biologist, linux, screen, shell

April 4, 2013

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Restituire dignità alla wi-fi fastweb

Ammettiamolo, ultimamente la rete fastweb non è il massimo.
So di svariate persone che si riducono ad usare la chiavetta per navigare… da casa.
Anche la mitologica “riqualifica della linea”, la prima opzione che immancabilmente fastweb propone, ultimamente non dava risultati.
Stavo veramente meditando a quale nuovo operatore affidarmi quando ho avuto un lampo di genio (ebbene sì, io non ho culo, ho lampi di genio) e mi sono imbattuto in una serie di post che suggerivano di cambiare il canale del wireless.
Nonostante io sappia a malapena cambiare il canale della TV (strumento che da decenni non possiedo più) ho deciso di cimentarmi in questa impresa.
Con un po’ di colpi di c… ehm di genio, sono riuscito a farlo. Scrivo qui la mia avventura a imperitura memoria e affinché gli altri poveri sfigati come me vittime della lentezza del wi-fi fastweb vi trovino consolazione e – magari – la salvezza, come è capitato a me.

Allora, un po’ rocambolescamente ho trovato questa pagina di fastweb in cui si accede alla configurazione del wifi di fastweb (ovviamente bisogna effettuare il login):
http://www.fastweb.it/myfastpage/assistenza/guide/assistenza-tecnica/internet/non-funziona-internet-wireless/

Si presenta una pagina, nelle cui prime righe c’è un link un po’ mimetizzato che io però ho evidenziato con una freccia rossa

Una volta cliccato, si aprirà un pop-up nel quale ci sono vari settaggi. Basta cercare “Modifica canale wi-fi” e cambiare il numero.

Io, dall’alto delle mie competenze informatiche, ho cambiato a caso.
Ha funzionato.
Auguro anche a voi la stessa fortuna.

Uncategorized

canale, fastweb, internet, wi-fi

March 24, 2013

5 Comments

R and theater

You might ask what R has to do with theater.
I assure you it has. I act in the theater group ‘ndescenze. We will soon present (actually, we just performed) a show based on the Marx Brothers Radio Shows. We shuffle actors and characters during the show (we like it complicated!) and we needed to find at least one sequence of scenes which allowed people to change dress and be ready quickly to be back on stage.
I manually described a number of rules based on the roles of the actors.
For example, “Teatro”, in which I act as Ravelli and I am on stage until the end of the scene, cannot be followed by “Autobus”, in which I act as Miss Dimple and I am on stage in the beginning of the scene…
After doing that, I just needed to find the combination of six scenes (named “affitto”,”autobus”,”eredita”,”ristorante”,”tassista” and “teatro”) which didn’t break any of the imposed rules.
No need to say that I used R! It worked, I found a good answer, but with a really ugly piece of code… Let’s see if you can find the right answer(s) and with a better piece of code (ok, the latter is not so difficult)

Here I list the rules:
“teatro” must take place after “affitto”, because in “affitto” we explain some things that will be needed for “teatro”.
They don’t need to be consecutive, though.
Then a list of consecutive combinations that are forbidden
“affitto” cannot be followed by “tassista” nor by “teatro”
“autobus” cannot be followed by “ristorante”
“eredita” cannot be followed by “tassista” nor by “autobus”
“ristorante” cannot be followed by “affitto”, “tassista”, “teatro” nor by “autobus”
“tassista” cannot be followed by “affitto”, “teatro” nor by “eredita”
“teatro” cannot be followed by “autobus”, “affitto”, nor by “ristorante”

Here’s the code:

scenes<-c("affitto","autobus","eredita","ristorante","tassista","teatro")
choose.me<-expand.grid(list(scenes,scenes,scenes,scenes,scenes,scenes),
                       stringsAsFactors=FALSE)
for (bbb in 1: nrow(choose.me))
	{
	if(length(unique(as.character(choose.me[bbb,])))<6) 
    {choose.me[bbb,]<-rep(NA,6);next} 
    if(which(choose.me[bbb,]=="affitto") > which(choose.me[bbb,]=="teatro")) 
    {choose.me[bbb,]<-rep(NA,6);next}	
	if(which(choose.me[bbb,]=="affitto")+1==which(choose.me[bbb,]=="tassista")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="affitto")+1==which(choose.me[bbb,]=="teatro")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="autobus")+1==which(choose.me[bbb,]=="ristorante")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="eredita")+1==which(choose.me[bbb,]=="tassista")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="eredita")+1==which(choose.me[bbb,]=="autobus")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="ristorante")+1==which(choose.me[bbb,]=="affitto")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="ristorante")+1==which(choose.me[bbb,]=="tassista")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="ristorante")+1==which(choose.me[bbb,]=="teatro")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="ristorante")+1==which(choose.me[bbb,]=="autobus")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="tassista")+1==which(choose.me[bbb,]=="affitto")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="tassista")+1==which(choose.me[bbb,]=="teatro")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="tassista")+1==which(choose.me[bbb,]=="eredita")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="teatro")+1==which(choose.me[bbb,]=="autobus")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="teatro")+1==which(choose.me[bbb,]=="affitto")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	if(which(choose.me[bbb,]=="teatro")+1==which(choose.me[bbb,]=="ristorante")) 
    {choose.me[bbb,]<-rep(NA,6);next}
	} 
choose.me<-na.omit(choose.me)

Using this code, I was able to find 10 combinations of scenes that were technically feasible. Among them we chose the one likely to have the best impact on the audience…
The list of all the technically possible scenes and the chosen one will be out soon… Obviously, if you attended our show you already know!
Waiting for comments on how to improve the code and your guesses for the right answer!

Improved code by Paul Fruin
Following Paul’s comment I paste below the complete code for solving the same problem. I tested it and it provides the right answer. In addition, Paul’s code avoids the loop and thus saves a considerable amount of time! I am always happy when I learn a way to avid a loop, so thanks Paul!

BTW: stay tuned, I will soon add alternative versions suggested by comments… I just need some time to test them and comment them!!

Here’s Paul’s code:

scenes<-c("affitto","autobus","eredita","ristorante","tassista","teatro")
choose.me<-expand.grid(list(scenes,scenes,scenes,scenes,scenes,scenes),
		stringsAsFactors=FALSE)
##now knock out rows step by step, using apply() to index the bad rows
choose.me[ apply(choose.me,1,function(x) 
					! length(unique(as.character(x)))<6),] -> choose.me

#remove rows based on next criteria
choose.me[ apply(choose.me,1,function(x)
					! which(x=="affitto") > which(x=="teatro") ) , ] -> choose.me

#remove al the other rows...
choose.me[ apply(choose.me,1,function(x)
					! which(x=="affitto")+1 == which(x=="tassista") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="affitto")+1 == which(x=="teatro") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="autobus")+1 == which(x=="ristorante") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="eredita")+1 == which(x=="tassista") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="eredita")+1 == which(x=="autobus") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="ristorante")+1 == which(x=="affitto") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="ristorante")+1 == which(x=="tassista") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="ristorante")+1 == which(x=="teatro") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="ristorante")+1 == which(x=="autobus") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="tassista")+1 == which(x=="affitto") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="tassista")+1 == which(x=="teatro") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="tassista")+1 == which(x=="eredita") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="teatro")+1 == which(x=="autobus") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="teatro")+1 == which(x=="affitto") ) , ] -> choose.me
choose.me[ apply(choose.me,1,function(x)
					! which(x=="teatro")+1 == which(x=="ristorante") ) , ] -> choose.me

Carlos Ortega provided an even faster solution. It uses libraries “combinat” and “stringr” and it runs in less than 3 secs even on my old laptop! I tested it and it provides the right answer. I promise that I will try to learn this efficient implementation!
You can find Carlo’s code below:

a<-Sys.time()
library(combinat)
library(stringr)

scenes<-c("affitto","autobus","eredita","ristorante","tassista","teatro")
all.sce<-permn(scenes )

foo<-function(x) {
	str_c(x, collapse="-")
}
sce.god<-lapply(all.sce, foo)

# Working data.frame
sce.end<-as.data.frame(sce.god)
names(sce.end)<-NULL
sce.wrk<-t(sce.end)

###### Forbidden Rules
r01<-c('affitto-tassista')
r02<-c('affitto-teatro')
r03<-c('autobus-ristorante')
r04<-c('eredita-tassista')
r05<-c('eredita-autobus')
r06<-c('ristorante-affitto')
r07<-c('ristorante-tassista')
r08<-c('ristorante-teatro')
r09<-c('ristorante-autobus')
r10<-c('tassista-affitto')
r11<-c('tassista-teatro')
r12<-c('tassista-eredita')
r13<-c('teatro-autobus')
r14<-c('teatro-affitto')
r15<-c('teatro-ristorante')
r16<-c('^teatro')

rul.for<-data.frame(
		r01, r02, r03, r04, r05,
		r06, r07, r08, r09, r10,
		r11, r12, r13, r14, r15, r16
)

############# Process to get the valid scenes
sce.ini<-sce.wrk

for(i in 1:ncol(rul.for)) {
	
	rul.tmp<-as.vector(rul.for[1,i])
	val.tmp<-str_locate(sce.ini, rul.tmp)
	sce.tmp<-sce.ini[is.na(val.tmp[,1])]
	
	sce.ini<-sce.tmp
	
}

### To eliminate first rule Ð teatro after affittoÉ
te.val<-str_locate(sce.ini, "teatro")
af.val<-str_locate(sce.ini, "affitto")
te.af<-data.frame(te=te.val[,1],af=af.val[,1])

no.val<-as.numeric(row.names(te.af[te.af$te < te.af$af,]))

### Valid Scenes
valid.scenes <- sce.ini[-no.val]
valid.scenes

b<-Sys.time()
b-a

Last but not least, Ben Bolker found another elegant solution providing the correct answer.
I paste it below:

scenes<-c("affitto","autobus","eredita","ristorante","tassista","teatro")
choose.me<-expand.grid(list(scenes,scenes,scenes,scenes,scenes,scenes),
stringsAsFactors=FALSE)
##now knock out rows step by step, using apply() to index the bad rows
choose.me[ apply(choose.me,1,function(x) ! length(unique(as.character(x)))<6),] -> choose.me

choose.me[ apply(choose.me,1,function(x)
! which(x=="affitto") > which(x=="teatro") ) , ] -> choose.me

##remove rows based on next criteria
not_adjacent <- function(t1,t2) {
apply(choose.me,1,function(x)
! (which(x==t1)+1 == which(x==t2)))
}
omit_pairs <- matrix(c("affitto","tassista",
"affitto","teatro",
"autobus","ristorante",
"eredita","tassista",
"eredita","autobus",
"ristorante","affitto",
"ristorante","tassista",
"ristorante","teatro",
"ristorante","autobus",
"tassista","affitto",
"tassista","teatro",
"tassista","eredita",
"teatro","autobus",
"teatro","affitto",
"teatro","ristorante"),
ncol=2,byrow=TRUE)
invisible(apply(omit_pairs,1,
function(z) {
choose.me <<- choose.me[not_adjacent(z[1],z[2]),]
}))
nrow(choose.me) ## 10

All the solutions provided so far were correct, fast and elegant. This makes me realize the paucity of my R skills, but at the same time stimulates me to learn more!

R

theater, theatre

June 3, 2012

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