[R] Fwd: Matrix Constraints in R Optim

Priyank Dwivedi
Sun, 19 Jun 2016 23:17:27 -0000

All,
Here are the dput files of the input data to the code.

Thanks for any advice.

I am adding the entire code below too just in case.


file <- file.path("Learning R","CRM_R_Ver4.xlsx")
file
my.data <- readWorksheetFromFile(file,sheet=1,startRow=1)
str(my.data)  # DATA FRAME
my.data.matrix.inj <- as.matrix(my.data)  #convert DATA FRAME to MATRIX
my.data.matrix.inj

dput(my.data.matrix.inj,"my.data.matrix.inj.txt")


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

dput(my.data.matrix.time,"my.data.matrix.time.txt")

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

dput(my.data.matrix.prod,"my.data.matrix.prod.txt")

 # 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

dput(my.data.var,"my.data.var.txt")


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))

sols

On 17 June 2016 at 16:55, 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,
Priyank Dwivedi
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-------------- next part --------------
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-------------- next part --------------
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-------------- next part --------------
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