Matrix Constraints in R Optim

Sent from my phone. Please excuse my brevity.

On June 17, 2016 3:10:41 PM PDT, Narendra Modi <bjpmodi2016 at gmail.com> wrote:
>how to do that Jeff? I am newbie to R.
>
>I am posting the whole message again here and I made sure it is in
>plain-text format.
>
>
>
>
>
>
>my.data.matrix.inj <- as.matrix(my.data)  #convert DATA FRAME to MATRIX
>my.data.matrix.inj
>
>
>my.data.2 <- readWorksheetFromFile(file,sheet=2,startRow=1)
>str(my.data.2)  # DATA FRAME
>my.data.matrix.time <- as.matrix(my.data.2)  #convert DATA FRAME to
>MATRIX
>my.data.matrix.time
>
>my.data <- readWorksheetFromFile(file,sheet=3,startRow=1)
>str(my.data)  # DATA FRAME
>my.data.matrix.prod <- as.matrix(my.data)  #convert DATA FRAME to
>MATRIX
>my.data.matrix.prod
>
>
> # my.data.var <- vector("numeric",length = 24)
> # my.data.var
>
>my.data.var <- c(10,0.25,0.25,0.25,0.25,0.25,
>                 10,0.25,0.25,0.25,0.25,0.25,
>                 10,0.25,0.25,0.25,0.25,0.25,
>                 10,0.25,0.25,0.25,0.25,0.25)
>my.data.var
>
>my.data.qo <- c(5990,150,199,996)   #Pre-Waterflood Production
>my.data.timet0 <- 0 # starting condition for time
>
>#FUNCTION
>Qjk.Cal.func <- function(my.data.timet0,my.data.qo,my.data.matrix.time,
>                         my.data.matrix.inj,
>my.data.matrix.prod,my.data.var,my.data.var.mat)
>{
>
>  qjk.cal.matrix <- matrix(,nrow = nrow(my.data.matrix.prod),
>ncol=ncol(my.data.matrix.prod))
>
>  count <- 1
>  number <- 1
>  for(colnum in 1:ncol(my.data.matrix.prod))   # loop through all PROD
>wells columns
>  {
>    sum <-0
>    for(row in 1:nrow(my.data.matrix.prod)) #loop through all the rows
>    {
>      sum <-0
>      deltaT <-0
>      expo <-0
>
>
>        for(column in 1:ncol(my.data.matrix.inj)) #loop through all
>the injector columns to get the PRODUCT SUM
>         {
>            sum = sum +
>my.data.matrix.inj[row,column]*my.data.var.mat[colnum,number+column]
>         }
>
>      if(count<2)
>      {
>        deltaT<- my.data.matrix.time[row]
>      }
>      else
>      {deltaT <- my.data.matrix.time[row]-my.data.matrix.time[row-1]}
>
>
>      expo <- exp(-deltaT/my.data.var.mat[colnum,1])
># change here too
>
>      if(count<2)
>      {
>    qjk.cal.matrix[row,colnum] = my.data.qo[colnum]*expo + (1-expo)*sum
>      }
>      else
>      {
>        qjk.cal.matrix[row,colnum]=qjk.cal.matrix[row-1,colnum]*expo +
>(1-expo)*sum
>      }
>      count <- count+1
>    }
>
>    count <-1
>  }
>
>  qjk.cal.matrix      # RETURN CALCULATED MATRIX TO THE ERROR FUNCTION
>
>}
>
>
># ERROR FUNCTION - FINDS DIFFERENCE BETWEEN CAL. MATRIX AND ORIGINAL
>MATRIX. Miminize the Error by changing my.data.var
>
>Error.func <- function(my.data.var)
>{
>  #First convert vector(my.data.var) to MATRIX aand send it to
>calculate new MATRIX
>  my.data.var.mat <- matrix(my.data.var,nrow =
>ncol(my.data.matrix.prod),ncol = ncol(my.data.matrix.inj)+1,byrow =
>TRUE)
>
>Calc.Qjk.Value <-
>Qjk.Cal.func(my.data.timet0,my.data.qo,my.data.matrix.time,
>                                 my.data.matrix.inj,
>my.data.matrix.prod,my.data.var,my.data.var.mat)
>
>
>  diff.values <- my.data.matrix.prod-Calc.Qjk.Value    #FIND
>DIFFERENCE BETWEEN CAL. MATRIX AND ORIGINAL MATRIX
>
>
>  Error <- ((colSums ((diff.values^2), na.rm = FALSE, dims =
>1))/nrow(my.data.matrix.inj))^0.5    #sum of square root of the diff
>  print(paste(Error))
>
>  Error_total <- sum(Error,na.rm=FALSE)/ncol(my.data.matrix.prod)   #
>total avg error
>
>
>  Error_total
>}
>
># OPTIMIZE
>
>sols<-optim(my.data.var,Error.func,method="L-BFGS-B",upper=c(Inf,1,1,1,1,1,Inf,1,1,1,1,1,Inf,1,1,1,1,1,Inf,1,1,1,1,1),
>lower=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),control=list(maxit
>=1000))
>sols
>
>
>
>
>
>
>On Fri, Jun 17, 2016 at 4:55 PM, Jeff Newmiller
><jdnewmil at dcn.davis.ca.us> wrote:
>>
>> Your code is corrupt because you failed to send your email in plain
>text format.
>>
>> You also don't appear to have all data needed to reproduce the
>problem. Use the dput function to generate R code form of a sample of
>your data.
>> --
>> Sent from my phone. Please excuse my brevity.
>>
>> On June 17, 2016 1:07:21 PM PDT, Priyank Dwivedi
><dpriyank23 at gmail.com> wrote:
>> >By mistake, I sent it earlier to the wrong address.
>> >
>> >---------- Forwarded message ----------
>> >From: Priyank Dwivedi <dpriyank23 at gmail.com>
>> >Date: 17 June 2016 at 14:50
>> >Subject: Matrix Constraints in R Optim
>> >To: r-help-owner at r-project.org
>> >
>> >
>> >Hi,
>> >
>> >Below is the code snippet I wrote in R:
>> >
>> >The basic idea is to minimize error by optimizing set of values (in
>> >this
>> >scenario 12) in the form of a matrix. I defined the matrix elements
>as
>> >vector "*my.data.var" * and then stacked it into a matrix called
>> >"*my.data.var.mat"
>> >in the error function. *
>> >
>> >The only part that I can't figure out is "what if the column sum in
>> >the *my.data.var.mat
>> >needs to be <=1"; that's the constraint/s.. Where do I introduce it
>in
>> >the
>> >OPTIM solver or elsewhere?*
>> >
>> >
>> >
>> >
>> >
>> >
>> >*my.data.matrix.inj* <- as.matrix(my.data)  #convert DATA FRAME to
>> >MATRIX
>> >my.data.matrix.inj
>> >
>> >
>> >*my.data.matrix.time* <- as.matrix(my.data.2)  #convert DATA FRAME
>to
>> >MATRIX
>> >my.data.matrix.time
>> >
>> >
>> >*my.data.matrix.prod* <- as.matrix(my.data)  #convert DATA FRAME to
>> >MATRIX
>> >my.data.matrix.prod
>> >
>> >
>> >*my.data.var* <-
>>
>>c(2,0.8,0.5,0.2,0.2,0.1,10,0.01,0.02,0.2,0.1,0.01,2,0.8,0.5,0.2,0.2,0.1,10,0.01,0.02,0.2,0.1,0.01,2,0.8,0.5,0.2,0.2,0.1,10,0.01,0.02,0.2,0.1,0.01)
>> >my.data.var
>> >
>> >*my.data.qo* <- c(5990,150,199,996)   #Pre-Waterflood Production
>> >
>> >*my.data.timet0* <- 0 # starting condition for time
>> >
>> >
>> >*#FUNCTIONQjk.Cal.func* <-
>> >function(my.data.timet0,my.data.qo,my.data.matrix.time,
>> >                         my.data.matrix.inj,
>> >my.data.matrix.prod,my.data.var,my.data.var.mat)
>> >{
>> >
>> >  qjk.cal.matrix <- matrix(,nrow = nrow(my.data.matrix.prod),
>> >ncol=ncol(my.data.matrix.prod))
>> >
>> >  count <- 1
>> >  number <- 1
>> >  for(colnum in 1:ncol(my.data.matrix.prod))   # loop through all
>PROD
>> >wells columns
>> >  {
>> >    sum <-0
>> >    for(row in 1:nrow(my.data.matrix.prod)) #loop through all the
>rows
>> >    {
>> >      sum <-0
>> >      deltaT <-0
>> >      expo <-0
>> >
>> >
>> >        for(column in 1:ncol(my.data.matrix.inj)) #loop through all
>the
>> >injector columns to get the PRODUCT SUM
>> >         {
>> >            sum = sum +
>> >my.data.matrix.inj[row,column]*my.data.var.mat[colnum,number+column]
>> >         }
>> >
>> >      if(count<2)
>> >      {
>> >        deltaT<- my.data.matrix.time[row]
>> >      }
>> >      else
>> >      {deltaT <-
>my.data.matrix.time[row]-my.data.matrix.time[row-1]}
>> >
>> >
>> >      expo <- exp(-deltaT/my.data.var.mat[colnum,1])                
> #
>> >change here too
>> >
>> >      if(count<2)
>> >      {
>> >    qjk.cal.matrix[row,colnum] = my.data.qo[colnum]*expo +
>(1-expo)*sum
>> >      }
>> >      else
>> >      {
>> >        qjk.cal.matrix[row,colnum]=qjk.cal.matrix[row-1,colnum]*expo
>+
>> >(1-expo)*sum
>> >      }
>> >      count <- count+1
>> >    }
>> >
>> >    count <-1
>> >  }
>> >
>> >  qjk.cal.matrix      # RETURN CALCULATED MATRIX TO THE ERROR
>FUNCTION
>> >
>> >}
>> >
>> >
>> >*# ERROR FUNCTION* - FINDS DIFFERENCE BETWEEN CAL. MATRIX AND
>ORIGINAL
>> >MATRIX. Miminize the Error by changing my.data.var
>> >
>> >*Error.func* <- function(my.data.var)
>> >{
>> > #First convert vector(my.data.var) to MATRIX aand send it to
>calculate
>> >new MATRIX
>> >  *my.data.var.mat* <- matrix(my.data.var,nrow =
>> >ncol(my.data.matrix.prod),ncol = ncol(my.data.matrix.inj)+1,byrow =
>> >TRUE)
>> >
>> >*  Calc.Qjk.Value* <-
>> >Qjk.Cal.func(my.data.timet0,my.data.qo,my.data.matrix.time,
>> >                                 my.data.matrix.inj,
>> >my.data.matrix.prod,my.data.var,my.data.var.mat)
>> >
>> >
>> >  diff.values <- my.data.matrix.prod-Calc.Qjk.Value    #FIND
>DIFFERENCE
>> >BETWEEN CAL. MATRIX AND ORIGINAL MATRIX
>> >
>> >
>> >  Error <- ((colSums ((diff.values^2), na.rm = FALSE, dims =
>> >1))/nrow(my.data.matrix.inj))^0.5    #sum of square root of the diff
>> >  print(paste(Error))
>> >
>> >Error_total <- sum(Error,na.rm=FALSE)/ncol(my.data.matrix.prod)   #
>> >total
>> >avg error
>> >
>> >
>> > * Error_total*
>> >}
>> >
>> ># OPTIMIZE
>> >
>> >*optim*(*my.data.var*
>>
>>,Error.func,method="L-BFGS-B",upper=c(Inf,1,1,1,1,1,Inf,1,1,1,1,1,Inf,1,1,1,1,1,Inf,1,1,1,1,1))
>> >
>> >
>> >
>> >--
>> >Best Regards,
>> >PD
>> >
>> >
>> >
>> >--
>> >Best Regards,
>> >Priyank Dwivedi
>> >
>> >       [[alternative HTML version deleted]]
>> >
>> >______________________________________________
>> >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> >https://stat.ethz.ch/mailman/listinfo/r-help
>> >PLEASE do read the posting guide
>> >http://www.R-project.org/posting-guide.html
>> >and provide commented, minimal, self-contained, reproducible code.
>>
>>         [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.

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