plotting large time series

A simple way may be not to plot all data points. But it will depend on
your data if that is a good idea.

Regards,
Enrico

## EXAMPLE

require("zoo")

## random data
dates <- seq(from = as.Date("2000-01-01"),
             to   = as.Date("2011-10-31"), by = "1 day")
x <- cumsum(rnorm(length(dates)))

## plot all
plot(zoo(x, dates), col = "blue")

## plot every 100th point
subs <- seq(1, length(x), by = 10)
lines(zoo(x[subs], dates[subs]), lwd = 2)

Am 28.10.2011 02:46, schrieb jim holtman:

Try another format (tiff, jpg, etc) to see how they look, what the
sizes are for different resolutions.  If you have a lot of single
points, PDF files get very large because of the commands used to print
each point.  If you want to keep PDF, then find some way of
aggregating the data points so that you plot an "average" of several
of them.  Depending on what you are trying to show, I have used the
hexbin package to plot large numbers of points.

Why do you need PDFs?  Will something else do?

On Thu, Oct 27, 2011 at 11:39 AM, Agnes
Richard<agnes.richard at fhnw.ch>  wrote:

hello,

I got a problem with plotting large time series, since I want to
store the
results in a .PDF file (I want to store several pages of plots). The
PDF
files get too large to be handled (>  10MB, one was even 200MB big).

So I wonder, if there would be a possibilty to either
- reduce the file size of the PDF
- change the way the plot is generated to reduce the plot size?

I use:
plot(myDate,myFile[,1],type="l",xlab="Date")

using
myts = as.ts(start=myDate[1],end=myDate[length(myDate)],x=myFile[,1])
plot.ts(myts,xlab="Date")

produces the same file size.

for storing the PDF I use:
pdf(file=paste(outpath,"myPDF.pdf",sep=''),paper="a4r").

I would be very grateful for an answer!!!!