From emillfilipov at gmail.com  Tue Jun 14 20:34:31 2016
From: emillfilipov at gmail.com (phdmonster)
Date: Tue, 14 Jun 2016 11:34:31 -0700 (PDT)
Subject: [datatable-help] Table function deletes non NA values in R
Message-ID: <1465929271856-4721792.post@n4.nabble.com>

This here bugger worked perfectly until i changed the data set:

    for (k in m) {
    mos_sub <- subset(work_table_ansfreq, !is.na(work_table_ansfreq[,r]) &      
work_table_ansfreq$MOS_GROUP==k & !is.na(work_table_ansfreq$MOS_GROUP))
    freq_mos<- table(mos_sub[,r])
    qa[,k] <- freq_mos
    }
For some reason it removes both NA values (which is normal) and one column
that actually has values. I will demonstrate. Output of the above code is:

    I provide care for someone who suffers from                             
Not applicable                        Prefer not to answer 
                                          4                                        
631                                          14 
       Someone in my household suffers from 
                                          1 
And when i include **exclude = NULL** in the table brackets i get this:

    I provide care for someone who suffers from                              
I suffer from                              Not applicable 
                                             22                                          
6                                        5258 
                           Prefer not to answer        Someone in my
household suffers from                                        <NA> 
                                             94                                         
13                                           0 

How do i fix this? Meaning how do i exclude only the NA which should be the
only one excluded from the table anyway.
Thanks!




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From fperickson at wisc.edu  Tue Jun 14 21:16:15 2016
From: fperickson at wisc.edu (Frank Erickson)
Date: Tue, 14 Jun 2016 15:16:15 -0400
Subject: [datatable-help] Table function deletes non NA values in R
In-Reply-To: <1465929271856-4721792.post@n4.nabble.com>
References: <1465929271856-4721792.post@n4.nabble.com>
Message-ID: <CAJd-hdmoXxyzv=wphmw5cR8F-W1V5YPh9e-mZDrUOJvhJV+y7w@mail.gmail.com>

Hi Emil,

This mailing list is only for the data.table package. Find out about other
lists here: https://www.r-project.org/mail.html

For reference, you probably want to link your SO post
http://stackoverflow.com/q/37819796/1191259

--Frank

On Tue, Jun 14, 2016 at 2:34 PM, phdmonster <emillfilipov at gmail.com> wrote:

> This here bugger worked perfectly until i changed the data set:
>
>     for (k in m) {
>     mos_sub <- subset(work_table_ansfreq, !is.na(work_table_ansfreq[,r]) &
> work_table_ansfreq$MOS_GROUP==k & !is.na(work_table_ansfreq$MOS_GROUP))
>     freq_mos<- table(mos_sub[,r])
>     qa[,k] <- freq_mos
>     }
> For some reason it removes both NA values (which is normal) and one column
> that actually has values. I will demonstrate. Output of the above code is:
>
>     I provide care for someone who suffers from
> Not applicable                        Prefer not to answer
>                                           4
> 631                                          14
>        Someone in my household suffers from
>                                           1
> And when i include **exclude = NULL** in the table brackets i get this:
>
>     I provide care for someone who suffers from
> I suffer from                              Not applicable
>                                              22
> 6                                        5258
>                            Prefer not to answer        Someone in my
> household suffers from                                        <NA>
>                                              94
> 13                                           0
>
> How do i fix this? Meaning how do i exclude only the NA which should be the
> only one excluded from the table anyway.
> Thanks!
>
>
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Table-function-deletes-non-NA-values-in-R-tp4721792.html
> Sent from the datatable-help mailing list archive at Nabble.com.
> _______________________________________________
> datatable-help mailing list
> datatable-help at lists.r-forge.r-project.org
> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
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From vedahung1116 at gmail.com  Thu Jun 16 14:30:17 2016
From: vedahung1116 at gmail.com (Veda)
Date: Thu, 16 Jun 2016 05:30:17 -0700 (PDT)
Subject: [datatable-help] recode variable regardless of its order
Message-ID: <1466080217763-4721864.post@n4.nabble.com>

Hello experts,

I have two variables in a data frame, say "varA" and "varB".
varA: a, a, a, b, b, b, c, c, c
varB: a, b, c, a, b, c, a, b, c

What I want to do is to create two new variables like bellow
varA: a, a, a, *a*, b, b, *a*, *b*, c
varB: a, b, c, *b*, b, c, *c*, *c*, c

The point is to ignore whether the element is in varA or varB in the
recoding. I really appreciate any suggestion to achieve this. Thanks!

Veda





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From Cedric.Duprez at ign.fr  Thu Jun 16 15:36:47 2016
From: Cedric.Duprez at ign.fr (Cedric Duprez)
Date: Thu, 16 Jun 2016 13:36:47 +0000
Subject: [datatable-help] recode variable regardless of its order
In-Reply-To: <1466080217763-4721864.post@n4.nabble.com>
References: <1466080217763-4721864.post@n4.nabble.com>
Message-ID: <5762AB7A.8060208@ign.fr>

Hi,

Perhaps something like this :

 > test <- data.table(varA=c("a", "a", "a", "b", "b", "b", "c", "c", 
"c"), varB=c("a", "b", "c", "a", "b", "c", "a", "b", "c"))
 > test
    varA varB
1:    a    a
2:    a    b
3:    a    c
4:    b    a
5:    b    b
6:    b    c
7:    c    a
8:    c    b
9:    c    c
 > test[, `:=`(varA2 = pmin(varA, varB), varB2 = pmax(varA, varB))]
 > test
    varA varB varA2 varB2
1:    a    a     a     a
2:    a    b     a     b
3:    a    c     a     c
4:    b    a     a     b
5:    b    b     b     b
6:    b    c     b     c
7:    c    a     a     c
8:    c    b     b     c
9:    c    c     c     c

The two new variables (varA2 and varB2) look like what you're waiting 
for. Isn't it?

Regards,
Cedric

From fperickson at wisc.edu  Thu Jun 16 15:49:32 2016
From: fperickson at wisc.edu (Frank Erickson)
Date: Thu, 16 Jun 2016 09:49:32 -0400
Subject: [datatable-help] recode variable regardless of its order
In-Reply-To: <5762AB7A.8060208@ign.fr>
References: <1466080217763-4721864.post@n4.nabble.com>
 <5762AB7A.8060208@ign.fr>
Message-ID: <CAJd-hdmu3o9uG6FroE41D_MLezZ7ExKj660X8MxDnhn-qR8aKQ@mail.gmail.com>

Another way of doing what Cedric did, if you're willing to overwrite the
original vars:

test[varA > varB, `:=`(VarA = VarB, VarB = VarA)]

On Thu, Jun 16, 2016 at 9:36 AM, Cedric Duprez <Cedric.Duprez at ign.fr> wrote:

> Hi,
>
> Perhaps something like this :
>
>  > test <- data.table(varA=c("a", "a", "a", "b", "b", "b", "c", "c",
> "c"), varB=c("a", "b", "c", "a", "b", "c", "a", "b", "c"))
>  > test
>     varA varB
> 1:    a    a
> 2:    a    b
> 3:    a    c
> 4:    b    a
> 5:    b    b
> 6:    b    c
> 7:    c    a
> 8:    c    b
> 9:    c    c
>  > test[, `:=`(varA2 = pmin(varA, varB), varB2 = pmax(varA, varB))]
>  > test
>     varA varB varA2 varB2
> 1:    a    a     a     a
> 2:    a    b     a     b
> 3:    a    c     a     c
> 4:    b    a     a     b
> 5:    b    b     b     b
> 6:    b    c     b     c
> 7:    c    a     a     c
> 8:    c    b     b     c
> 9:    c    c     c     c
>
> The two new variables (varA2 and varB2) look like what you're waiting
> for. Isn't it?
>
> Regards,
> Cedric
> _______________________________________________
> datatable-help mailing list
> datatable-help at lists.r-forge.r-project.org
> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
>
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From vedahung1116 at gmail.com  Thu Jun 16 15:52:05 2016
From: vedahung1116 at gmail.com (Veda)
Date: Thu, 16 Jun 2016 06:52:05 -0700 (PDT)
Subject: [datatable-help] recode variable regardless of its order
In-Reply-To: <CAJd-hdmu3o9uG6FroE41D_MLezZ7ExKj660X8MxDnhn-qR8aKQ@mail.gmail.com>
References: <1466080217763-4721864.post@n4.nabble.com>
 <5762AB7A.8060208@ign.fr>
 <CAJd-hdmu3o9uG6FroE41D_MLezZ7ExKj660X8MxDnhn-qR8aKQ@mail.gmail.com>
Message-ID: <1466085125991-4721870.post@n4.nabble.com>

Thanks to Cedric and Frank for the great suggestions.
The thing is that I cannot use `:=` 
What package does this function require?
Thanks!



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From fperickson at wisc.edu  Thu Jun 16 17:54:23 2016
From: fperickson at wisc.edu (Frank Erickson)
Date: Thu, 16 Jun 2016 11:54:23 -0400
Subject: [datatable-help] recode variable regardless of its order
In-Reply-To: <1466085125991-4721870.post@n4.nabble.com>
References: <1466080217763-4721864.post@n4.nabble.com>
 <5762AB7A.8060208@ign.fr>
 <CAJd-hdmu3o9uG6FroE41D_MLezZ7ExKj660X8MxDnhn-qR8aKQ@mail.gmail.com>
 <1466085125991-4721870.post@n4.nabble.com>
Message-ID: <CAJd-hd=5n5+H0ahUz9O-vLYwq7zVXJfJJMTcJKWZxnJ-x89Ovw@mail.gmail.com>

You posted on the mailing list for the data.table package, where that
function comes from. Next time, look for a general R mailing list.

On Thu, Jun 16, 2016 at 9:52 AM, Veda <vedahung1116 at gmail.com> wrote:

> Thanks to Cedric and Frank for the great suggestions.
> The thing is that I cannot use `:=`
> What package does this function require?
> Thanks!
>
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/recode-variable-regardless-of-its-order-tp4721864p4721870.html
> Sent from the datatable-help mailing list archive at Nabble.com.
> _______________________________________________
> datatable-help mailing list
> datatable-help at lists.r-forge.r-project.org
> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
>
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From slam-norilsk at mail.ru  Tue Jun 21 20:33:05 2016
From: slam-norilsk at mail.ru (sermal)
Date: Tue, 21 Jun 2016 11:33:05 -0700 (PDT)
Subject: [datatable-help] Predict the next state via RHmm package
Message-ID: <1466533985672-4722029.post@n4.nabble.com>

Hi. 
How can I predict next state of HMM with discrete distribution? I'm using
RHmm package for this.



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From rana_dandis at yahoo.com  Tue Jun 28 12:24:08 2016
From: rana_dandis at yahoo.com (Dandis)
Date: Tue, 28 Jun 2016 03:24:08 -0700 (PDT)
Subject: [datatable-help] Forward Recursive method
Message-ID: <1467109448799-4722233.post@n4.nabble.com>

Hello guys,

I am trying to compute the likelihood for a hidden Markov chain problem
using the forward recursive process, described in the attached pdf,

LikelihoodComputation.pdf
<http://r.789695.n4.nabble.com/file/n4722233/LikelihoodComputation.pdf>  

My goal is to find the parameters beta and mu that will maximize the above
likelihood using R software and the following transition and emission
matrices 


n=3
h=0.1
x=matrix(data=NA, nrow=n+1, ncol=n+1)      # x is the transition matrix
for(i in 0:n){
  for(j in 0:n){
    if(i==j){ x[i+1,j+1] = 1-beta*j*(n-j)*h-mu*j*h}
    else{
      if(j==i+1){x[i+1,j+1] = beta*j*(n-j)*h}
      else{
        if(j==i-1){ x[i+1,j+1] = j*mu*h}
        else{x[i+1,j+1] =0}
      }}}}
x

E=matrix(data=NA, nrow=n+1, ncol=n+1) # the emission matrix 
for(i in 0:n){
  for(j in 0:n){
    E[i+1,j+1]=dbinom(j, size=i, prob=0.59) }}
E

Can you please help me to program this using R , or just give me a hint how
to start!


Thanks in advance,

Dandis






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From swright7 at uga.edu  Wed Jun 29 15:18:02 2016
From: swright7 at uga.edu (swright71234)
Date: Wed, 29 Jun 2016 06:18:02 -0700 (PDT)
Subject: [datatable-help] Create a new window
Message-ID: <1467206282642-4722299.post@n4.nabble.com>

Hello all, 

I am trying to perform image analysis with the following code. The code
works fine and is not the issue here. I would like for the completed images
to pop-up in a new and bigger when each image goes through the analysis.
Does anyone have any suggestions? 


par(mfrow=c(2,1))
for (i in 1: length(my_files))
{
  img <- brick(my_files[i])
  #crop the photo using previously defined parameters
  #my_img2 <- crop(img, my_extent)
  my_img2<-img
  #change band names(to make it easier to code)
  names(my_img2) <- c("b1", "b2", "b3")
  #remove the trend from the flash for each band ----------------------
  #define coordinates from the image
  x <- coordinates(my_img2)[,1]
  y <- coordinates(my_img2)[,2]
  #Regression for each layer, removing the polynomial trend
  #band1
  reg <- lm(my_img2$b1[] ~ x+ y+I(x^2)+I(y^2) )
  b <- coefficients(reg)
  my_img2$pred <- b[1] + b[2] *  x+ b[3]* y+ b[4]*x^2+b[5]*y^2
  my_img2$b1   <- my_img2$b1[] - my_img2$pred[]
  #band2
  reg <- lm(my_img2$b2[] ~ x+ y+I(x^2)+I(y^2) )
  b <- coefficients(reg)
  my_img2$pred <- b[1] + b[2] *  x+ b[3]* y+ b[4]*x^2+b[5]*y^2
  my_img2$b2   <- my_img2$b2[] - my_img2$pred[]
  #band3
  reg <- lm(my_img2$b3[] ~ x+ y+I(x^2)+I(y^2) )
  b <- coefficients(reg)
  my_img2$pred <- b[1] + b[2] *  x+ b[3]* y+ b[4]*x^2+b[5]*y^2
  my_img2$b3   <- my_img2$b3[] - my_img2$pred[]
  #
  my_img2 <-dropLayer(my_img2, "pred")
  my_img2 <- improve_contrast(my_img2)
  #
  #Plot 2 images so user can see the original plus the added
  #The aspect is changed to make it easier to click on the knots
  par(mfrow=c(2,1))
  plotRGB(my_img2,asp=3)
  plotRGB(my_img2,asp=3)
  
  print("Input 0 and hit Enter for no knots or Enter if knots")
  numberknots <- readline(paste("Knots for ", my_files[i],": ", sep=' '))
  #If knotsforeachpiece = 0 we can skip labeling the knots
  if(numberknots==0){
    #Add to dataframe that the piece didn't have any knots
    lknots   <- data.frame(board = my_files[i], x = NA, y = NA,area=NA)
    lknots      <- as.data.frame(lknots)
    my_knots <- rbind(my_knots, lknots)
    name<-my_files[i]
    name<-gsub(".tif","",name)
    
    #Write the images
    #image(my_img2)
    #my_img2
    #png(paste(name,"_Knots", ".png", sep=''))
    #par(mfrow=c(1,1))
    #plotRGB(my_img2)
    #plot(my_img2.poly, add = TRUE, col = "red", border ="red")
    #dev.off()
    
    
    #Copy file when done
    #file.copy(my_files[i], "Complete")
  }
  else   {
    #Identify clusters
    my_img2.mtrx <- as.matrix(my_img2)
    clusters <- kmeans(my_img2.mtrx, centers=7)
    my_img2$cl2 <- fitted(clusters)[,1]
    my_img2$cl  <- clusters$cluster
    mV <- minValue(my_img2$cl2)
    #pknots will be identified when cluster is equal to minimum value,
otherwise not a knot
    my_img2$pknots <- ifelse(my_img2$cl2[] == mV,1,NA)
    my_img2.poly <- rasterToPolygons(my_img2$pknots, dissolve = TRUE)
    my_img2.poly <- disaggregate(my_img2.poly)
    my_img2.poly$area <- sapply(slot(my_img2.poly, "polygons"), slot,
"area")
    plot(my_img2.poly, add = TRUE, col = "red", border ="red")
    #Joe Add
    #Did Algorithm correctly identify all the knots?
    #The identification of other stuff is not important since user will
identify the correct ones
    print("Input 0 & Enter if not all knots were identified")
    print("It does not matter if other stuff was identified but all knots
must be identified")
    print("Hit enter if all knots were identified")
    knotscorrect <- readline(paste("Knots Correct for ", my_files[i],": ",
sep=' '))
    #If knotsforeachpiece = 0 we can skip labeling the knots
    if(knotscorrect==0){
      #Copy file when done
      file.copy(my_files[i], "Incomplete")
    }
    else   {
      #Start locator for knots
      print("Select knots with mouse and when finished hit esc")
      my_points   <- locator(type ="p", pch ="x")
      my_pointsXY <- rasterToPoints(my_img2$pknots)
      #The following code line doesn't work but was included in the code you
sent me
      #my_points2  <- identify.map(my_pointsXY[,1], my_pointsXY[,2])
      
     
      lknots   <- data.frame(board = my_files[i], x = my_points$x, y =
my_points$y)
      #This isn't used for anything ???
      coordinates(lknots) <- ~x+y
      
      #problem when more points than identified (either algorithm doesn't
identify
      #Or user clicks outside knot (easy to do on small knots)
      my_img2.poly$isKnot <- as.vector(over(my_img2.poly, lknots)[,1])
      my_img2.poly <- subset(my_img2.poly, !is.na(my_img2.poly$isKnot))
      lknots      <- as.data.frame(lknots)
      lknots$area <- my_img2.poly$area
      #I would like to save the image with the ID'ed knots but this doesn't
work well due to the white space
      name<-my_files[i]
      name<-gsub(".tif","",name)
      #Save raster picture with knots identified
      png(paste(name,"_Knots", ".png", sep=''),width = 6000, height = 6000)
      par(mfrow=c(1,1))
      plotRGB(my_img2)
      plot(my_img2.poly, add = TRUE, col = "red", border ="red")
      dev.off()
      #rbind dataframe
      my_knots <- rbind(my_knots, lknots)
      #Copy file when done
      #file.copy(my_files[i], "Complete")
    }
  }
}


I would really appreciate any help!



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