R: Best way to preserve plot parameters between plots?

I'm trying to overlay plots of the price action between the bid and the ask on intraday. I have a piece of data that's normalized to micro-returns [i.e., the bounce back from the bid and the ask during the day.]

How do i get the plot to keep the same x and y dimensions from the previous plot automatically, without precalculating an xlim and ylim variable?

Here's plot 1, from running this:

> plot( log( rets$V4[2:l] / rets$V4[1l-1)] )[1:100], type="l" )

<img src="http://media.chartvibe.com/etimg/retv4_1.jpg">

Here's plot 2:

> plot( log( rets$V5[2:l] / rets$V5[1l-1)] )[1:100], type="l", col="blue" )

<img src="http://media.chartvibe.com/etimg/retv5_1.jpg">


Now, if I try something like this:

plot( log( rets$V4[2:l] / rets$V4[1l-1)] )[1:100], type="l" )
plotparams <- par( no.readonly = TRUE )
plotparams$new=T
par( plotparams )
plot( log( rets$V5[2:l] / rets$V5[1l-1)] )[1:100], type="l", col="blue" )

I'll get something like this:

<img src="http://media.chartvibe.com/etimg/combined.jpg">

But what I want, is this (even though I manually compute this stuff), is something that gets created by this code:

# slice off 1:100 for the ET post
l <- length( rets$V4 )
logret4 <- log( rets$V4[2: l] / rets$V4[1l-1)] )[1:100]
logret5 <- log( rets$V5[2: l] / rets$V5[1l-1)] )[1:100]
ydm <- c( min( logret4, logret5 ), max( logret4, logret5 ) )
xdm <- c( 0, 100 )
plot( logret4 , type="l", col="red", ylab="y", xlab="x", ylim=ydm, xlim=xdm )
par( new=T )
plot( logret5, type="l", col="blue", ylab="y", xlab="x", ylim=ydm, xlim=xdm )

<img src="http://media.chartvibe.com/etimg/combined_smooth.jpg">

How do I get R to cleanly carry over the underlying plot parameters and have plot() actually work with it? This drives me nuts every time, but I end up re-coding it every time. It's driving me bat5hi7 crazy. There should be a slick way to overlay the plot and preserve the dimensions as is.

 

Ivanovich, please fix the federal reserve and my R problem.

 

Table is huge, man. Two files of intraday data from two dow components ~ 80MB. I'm just plotting a tiny slice to let me zoom in on local areas where the math looks odd. The data is semi-worthless for real analysis because a lot of the retail data-feeds strip out the exchange time-stamps and lop off the accuracy at 1s.

Oh, here are the two slices -- doubt it will help.

> logret4
[1] 0.000000e+00 0.000000e+00 5.018821e-04 0.000000e+00 5.016303e-04 5.013788e-04 0.000000e+00 0.000000e+00 0.000000e+00
[10] 5.011275e-04 5.008765e-04 -5.008765e-04 0.000000e+00 0.000000e+00 5.008765e-04 0.000000e+00 0.000000e+00 0.000000e+00
[19] 5.006258e-04 1.501389e-04 -1.501389e-04 0.000000e+00 -1.001502e-03 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[28] 0.000000e+00 0.000000e+00 -5.011275e-04 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[37] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 -5.013788e-04 0.000000e+00
[46] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 -5.016303e-04 0.000000e+00 0.000000e+00 0.000000e+00
[55] 0.000000e+00 -5.018821e-04 0.000000e+00 0.000000e+00 5.018821e-04 5.016303e-04 0.000000e+00 0.000000e+00 0.000000e+00
[64] 5.013788e-04 0.000000e+00 -5.013788e-04 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 5.013788e-04
[73] -5.013788e-04 0.000000e+00 -1.003512e-03 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 -5.021341e-04
[82] 0.000000e+00 5.021341e-04 0.000000e+00 0.000000e+00 0.000000e+00 5.019954e-05 3.513263e-04 1.003563e-04 -5.018821e-04
[91] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 5.018821e-04 -5.018821e-04 5.018821e-04
[100] 0.000000e+00
> logret5
[1] 0.0000000000 0.0006495616 -0.0006495616 -0.0006499838 0.0006499838 0.0006495616 0.0000000000 0.0000000000 0.0006491399
[10] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0006487188 0.0006482982 0.0000000000
[19] 0.0006478782 -0.0006478782 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
[28] 0.0000000000 -0.0006482982 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
[37] 0.0000000000 0.0000000000 0.0006482982 0.0000000000 -0.0006482982 0.0000000000 0.0000000000 0.0000000000 0.0000000000
[46] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 -0.0006487188 0.0000000000 0.0000000000 -0.0006491399 0.0000000000
[55] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 -0.0006495616 0.0000000000 0.0005196830 0.0000000000
[64] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 -0.0001948495 0.0003247280 0.0000000000 0.0000000000
[73] 0.0000000000 0.0000000000 -0.0006495616 0.0000000000 -0.0006499838 0.0000000000 0.0000000000 0.0000000000 -0.0006504065
[82] 0.0000000000 0.0000000000 0.0006504065 0.0000000000 0.0000000000 0.0000000000 0.0000000000 -0.0006504065 0.0000000000
[91] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0006504065 -0.0004552401 -0.0001951664 0.0000000000 0.0000000000
[100] 0.0000000000

 

try this:
set one of the variables you want to
vector b.
The other to vector a.

i.e. b<-1st set of data
a<-2nd set

then try
require(graphics)
ts.plot(ts(b),ts(a),col=c("red","blue"))

 

comparison of your 1st method vs. the 2nd I showed:

require(graphics)
ts.plot(ts(b),ts(a),col=c("red","blue"))


P.S. next time attach or print the file with the sample vectors as complete columns. Easier to process.

 

Thanks!!