processing time too long

Dear Jim,

Thanks for ur suggesion. Earlier problem is solved with ur advise. My code
is taking too long to
execute, more than 30 hours. there are 40309 rows and 26952 columns. file
size is 110 MB.Please guide
me what is wrong.

Shashi
On Thu, 09 Jun 2016 14:27:17 +0530 Jim Lemon wrote

Hi Shashi,

Without trying to go through all that code, your error is something

simple. When you read in "matrixdata" right in the beginning, you are

getting a data frame, not a vector or a matrix (which in some cases

can be treated like a vector). That will cause trouble at some point.

Another thing is that when you call this:



if((sum > 0 && sums1 > 0 && sums2 > 0) != NA)



you seem to be asking for the union of three multi-valued vectors (?)

which will probably cause at least a warning, but the error suggests

that at least one of these objects has an NA value somewhere. This

might be because "dtm_500_1.CSV" (whatever that is) has NA values in

it. The code is fairly obscure and I can only say that your best bet

is probably to check the initial data frame for NA values and then

print out the results of each step, or least



cat(sum(is.na(x)),"\n")



where x is the object you have just created. That should allow you to

find where in the tangle of code the NAs are appearing.



Jim







On Thu, Jun 9, 2016 at 4:49 PM, SHASHI SETH wrote:

Hi Jim,

I am getting the following error:

Error in if ((sum > 0 && sums1 > 0 && sums2 > 0) != NA) { :

missing value where TRUE/FALSE needed

I have including my code below for your review:

fitness_1_data <- c();

src="dtm_500_1.CSV"

matrixdata <- read.csv(src)

#get no vector/column from file/matrix

noofvec <- length(matrixdata)

#set no of records/rows/document

noofrecords <- length(matrixdata[,1])

#set row index

rindex<-1;

#preapare header

colindex<-1;

colList <- colnames(matrixdata)

combine<-"";

vec_fitness_data<- c();

while(colindex <= length(colList))

{

fitness_1_data <- append(fitness_1_data,colList[colindex])

colindex<- colindex+1

}

#add two additional vector for percentage and cluster

fitness_1_data <- append(fitness_1_data,"percentage")

fitness_1_data <- append(fitness_1_data,"Cluster")

write.table(as.list(fitness_1_data), file ="Result_500_cycle1.csv",append
=

TRUE,

row.names=FALSE, col.names=FALSE, sep=",")

#end header record

nestedloopindex <- 2

while( nestedloopindex <= noofrecords )

{

#init of temperory variables

sums1 <- 0;

sums2 <- 0;

sum <- 0;

#set initial index of column 2 ,coloumn one hold document no not

actual data

colindex <- 2;

# combine <-"";

vec1 <- c();

vec2 <- c();

#add document number in vector

vec1 <- append(vec1,matrixdata[rindex,1]);

vec2 <- append(vec2,matrixdata[nestedloopindex,1]);

#declaration of temp -out variable for calculation

#out <- 0;

while(colindex <= noofvec )

{

vec1 <- append(vec1,matrixdata[rindex,colindex]);

vec2 <- append(vec2,matrixdata[nestedloopindex,colindex]);

sum = sum +

matrixdata[rindex,colindex]*matrixdata[nestedloopindex,colindex]

sums1 <- sums1 + matrixdata[rindex,colindex]^2;

sums2 <- sums2 + matrixdata[nestedloopindex,colindex]^2;

colindex <- colindex+1

}

if((sum > 0 && sums1 > 0 && sums2 > 0) != NA)

{

out <- sum / ((sqrt(sums1) * sqrt(sums2)))

}else

{

out <-0

}

vec1 <- append(vec1,out);

vec1 <-append(vec1, "1")

vec2 <- append(vec2, out);

if(nestedloopindex==2)

{

write.table(as.list(vec1), file ="Result_500_cycle1.csv",append =

TRUE, row.names=FALSE, col.names=FALSE, sep=",")

write.table(as.list(vec2), file ="Result_500_cycle1.csv",append =

TRUE, row.names=FALSE, col.names=FALSE, sep=",")

nestedloopindex<- nestedloopindex+1

} else

{

write.table(as.list(vec2), file ="Result_500_cycle1.csv",append =

TRUE, row.names=FALSE, col.names=FALSE, sep=",")

nestedloopindex<- nestedloopindex+1

}

}

With Best Regards,

Shashi

On Thu, 09 Jun 2016 04:45:09 +0530 Jim Lemon wrote

Hi John,

With due respect to the other respondents, here is something that might

help:

# get a vector of values

foo<-rnorm(100)

# get a vector of increasing indices (aka your "recent" values)

bar<-sort(sample(1:100,40))

# write a function to "clump" the adjacent index values

clump_adj_int<-function(x) {

index_list<-list(x[1])

list_index<-1

for(i in 2:length(x)) {

if(x[i]==x[i-1]+1)

index_list[[list_index]]<-c(index_list[[list_index]],x[i])

else {

list_index<-list_index+1

index_list[[list_index]]<-x[i]

}

}

return(index_list)

}

index_clumps<-clump_adj_int(bar)

# write another function to sum the values

sum_subsets<-function(indices,vector)

return(sum(vector[indices],na.rm=TRUE))

# now "apply" the function to the list of indices

lapply(index_clumps,sum_subsets,foo)

Jim

On Thu, Jun 9, 2016 at 2:41 AM, John Logsdon

wrote:

Folks

Is there any way to get the row index into apply as a variable?

I want a function to do some sums on a small subset of some very long

vectors, rolling through the whole vectors.

apply(X,1,function {do something}, other arguments)

seems to be the way to do it.

The subset I want is the most recent set of measurements only - perhaps a

couple of hundred out of millions - but I can't see how to index each

value. The ultimate output should be a matrix of results the length of

the input vector. But to do the sum I need to access the current row

number.

It is easy in a loop but that will take ages. Is there any vectorised

apply-like solution to this?

Or does apply etc only operate on each row at a time, independently of

other rows?

Best wishes

John

John Logsdon

Quantex Research Ltd

+44 161 445 4951/+44 7717758675