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Priyank Dwivedi

2016-Jun-17 20:07 UTC

[R] Fwd: Matrix Constraints in R Optim

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]]

Jeff Newmiller

2016-Jun-17 21:55 UTC

head link

[R] Fwd: Matrix Constraints in R Optim

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]]

Jeff Newmiller

2016-Jun-17 22:57 UTC

head link

[R] Fwd: Matrix Constraints in R Optim

Always reply-to-all to keep the mailing list informed... I don't do private
consulting online.

You look like you have plain text worked out, but we still cannot run your code.

Read the Posting Guide and [1]. You cannot attach Excel files here (and many R
users can't or won't do that anyway) so you need to figure out dput. You
will know you have a reproducible example when you don't read from any files
and the code produces the error you are asking about when run in a newly opened
R session.  I think you should (!) only need the dput of my.data.var, definition
of Error.func, and the call to optim if you do it right.

[1]
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
-- 
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.
	[[alternative HTML version deleted]]

Priyank Dwivedi

2016-Jun-19 23:17 UTC

head link

[R] Fwd: Matrix Constraints in R Optim

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
-------------- next part --------------
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-------------- next part --------------
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-------------- next part --------------
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-------------- next part --------------
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R help - Jun 2016 - Fwd: Matrix Constraints in R Optim

[R] Fwd: Matrix Constraints in R Optim

[R] Fwd: Matrix Constraints in R Optim

[R] Fwd: Matrix Constraints in R Optim

[R] Fwd: Matrix Constraints in R Optim