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# bigplotfix.R
# 28 Nov 2016

# This file defines a wrapper for plot.xy which checks if the input
# data is longer than a certain maximum limit. If it is, it is
# downsampled before plotting. For 3 million input points, I got
# speed-ups of 10-100x. Note that if you want the output to look the
# same as the "uncompressed" version, you should be drawing lines,
# because the compression involves taking maximum and minimum values
# of blocks of points (try running test_bigplotfix() for a visual
# explanation). Also, no sorting is done on the input points, so
# things could get weird if they are out of order.
test_bigplotfix = function() {
  oldpar=par();
  par(mfrow=c(2,2))
  n=1e5;
  r=runif(n)
  bigplotfix_verbose<<-T
  mytitle=function(t,m) { title(main=sprintf("%s; elapsed=%0.4f s",m,t["elapsed"])) }
  mytime=function(m,e) { t=system.time(e); mytitle(t,m); }

  oldbigplotfix_maxlen = bigplotfix_maxlen
  bigplotfix_maxlen <<- 1e3;

  mytime("Compressed, points",plot(r));
  mytime("Compressed, lines",plot(r,type="l"));
  bigplotfix_maxlen <<- n
  mytime("Uncompressed, points",plot(r));
  mytime("Uncompressed, lines",plot(r,type="l"));
  par(oldpar);
  bigplotfix_maxlen <<- oldbigplotfix_maxlen
  bigplotfix_verbose <<- F
}

bigplotfix_verbose=F

downsample_xy = function(xy, n, xlog=F) {
  msg=if(bigplotfix_verbose) { message } else { function(...) { NULL } }
  msg("Finding range");
  r=range(xy$x);
  msg("Finding breaks");
  if(xlog) {
    breaks=exp(seq(from=log(r[1]),to=log(r[2]),length.out=n))
  } else {
    breaks=seq(from=r[1],to=r[2],length.out=n)
  }
  msg("Calling findInterval");
  ## cuts=cut(xy$x,breaks);
  # findInterval is much faster than cuts!
  cuts = findInterval(xy$x,breaks);
  if(0) {
    msg("In aggregate 1");
    dmax = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), max)
    dmax$cuts = NULL;
    msg("In aggregate 2");
    dmin = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), min)
    dmin$cuts = NULL;
  } else { # use data.table for MUCH faster aggregates
    # (see http://stackoverflow.com/questions/7722493/how-does-one-aggregate-and-summarize-data-quickly)
    suppressMessages(library(data.table))
    msg("In data.table");
    dt = data.table(x=xy$x,y=xy$y,cuts=cuts)
    msg("In data.table aggregate 1");
    dmax = dt[,list(x=max(x),y=max(y)),keyby="cuts"]
    dmax$cuts=NULL;
    msg("In data.table aggregate 2");
    dmin = dt[,list(x=min(x),y=min(y)),keyby="cuts"]
    dmin$cuts=NULL;
    #  ans = data_t[,list(A = sum(count), B = mean(count)), by = 'PID,Time,Site']
  }
  msg("In rep, rbind");
  # interleave rows (copied from a SO answer)
  s <- rep(1:n, each = 2) + (0:1) * n
  xy = rbind(dmin,dmax)[s,];
  xy
}

library(graphics);
# make sure we don't create infinite recursion if someone sources
# this file twice
if(!exists("old_plot.xy")) {
  old_plot.xy = graphics::plot.xy
}

bigplotfix_maxlen = 1e4

# formals copied from graphics::plot.xy
my_plot.xy = function(xy, type, pch = par("pch"), lty = par("lty"),
  col = par("col"), bg = NA, cex = 1, lwd = par("lwd"),
  ...) {

  if(bigplotfix_verbose) {
    message("In bigplotfix's plot.xy\n");
  }

  mycall=match.call();
  len=length(xy$x)
  if(len>bigplotfix_maxlen) {
    warning("bigplotfix.R (plot.xy): too many points (",len,"), compressing to ",bigplotfix_maxlen,"\n");
    xy = downsample_xy(xy, bigplotfix_maxlen, xlog=par("xlog"));
    mycall$xy=xy
  }
  mycall[[1]]=as.symbol("old_plot.xy");

  eval(mycall,envir=parent.frame());
}

# new binding solution adapted from Henrik Bengtsson
# https://stat.ethz.ch/pipermail/r-help/2008-August/171217.html
rebindPackageVar = function(pkg, name, new) {
  # assignInNamespace() no longer works here, thanks nannies
  ns=asNamespace(pkg)
  unlockBinding(name,ns)
  assign(name,new,envir=asNamespace(pkg),inherits=F)
  lockBinding(name,ns)
}
rebindPackageVar("graphics", "plot.xy", my_plot.xy);

# bigplotfix.R
# 28 Nov 2016

# This file defines a wrapper for plot.xy which checks if the input
# data is longer than a certain maximum limit. If it is, it is
# downsampled before plotting. For 3 million input points, I got
# speed-ups of 10-100x. Note that if you want the output to look the
# same as the "uncompressed" version, you should be drawing lines,
# because the compression involves taking maximum and minimum values
# of blocks of points (try running test_bigplotfix() for a visual
# explanation). Also, no sorting is done on the input points, so
# things could get weird if they are out of order.
test_bigplotfix = function() {
  oldpar=par();
  par(mfrow=c(2,2))
  n=1e5;
  r=runif(n)
  bigplotfix_verbose<<-T
  mytitle=function(t,m) { title(main=sprintf("%s; elapsed=%0.4f s",m,t["elapsed"])) }
  mytime=function(m,e) { t=system.time(e); mytitle(t,m); }

  oldbigplotfix_maxlen = bigplotfix_maxlen
  bigplotfix_maxlen <<- 1e3;

  mytime("Compressed, points",plot(r));
  mytime("Compressed, lines",plot(r,type="l"));
  bigplotfix_maxlen <<- n
  mytime("Uncompressed, points",plot(r));
  mytime("Uncompressed, lines",plot(r,type="l"));
  par(oldpar);
  bigplotfix_maxlen <<- oldbigplotfix_maxlen
  bigplotfix_verbose <<- F
}

bigplotfix_verbose=F

downsample_xy = function(xy, n, xlog=F) {
  msg=if(bigplotfix_verbose) { message } else { function(...) { NULL } }
  msg("Finding range");
  r=range(xy$x);
  msg("Finding breaks");
  if(xlog) {
    breaks=exp(seq(from=log(r[1]),to=log(r[2]),length.out=n))
  } else {
    breaks=seq(from=r[1],to=r[2],length.out=n)
  }
  msg("Calling findInterval");
  ## cuts=cut(xy$x,breaks);
  # findInterval is much faster than cuts!
  cuts = findInterval(xy$x,breaks);
  if(0) {
    msg("In aggregate 1");
    dmax = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), max)
    dmax$cuts = NULL;
    msg("In aggregate 2");
    dmin = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), min)
    dmin$cuts = NULL;
  } else { # use data.table for MUCH faster aggregates
    # (see http://stackoverflow.com/questions/7722493/how-does-one-aggregate-and-summarize-data-quickly)
    suppressMessages(library(data.table))
    msg("In data.table");
    dt = data.table(x=xy$x,y=xy$y,cuts=cuts)
    msg("In data.table aggregate 1");
    dmax = dt[,list(x=max(x),y=max(y)),keyby="cuts"]
    dmax$cuts=NULL;
    msg("In data.table aggregate 2");
    dmin = dt[,list(x=min(x),y=min(y)),keyby="cuts"]
    dmin$cuts=NULL;
    #  ans = data_t[,list(A = sum(count), B = mean(count)), by = 'PID,Time,Site']
  }
  msg("In rep, rbind");
  # interleave rows (copied from a SO answer)
  s <- rep(1:n, each = 2) + (0:1) * n
  xy = rbind(dmin,dmax)[s,];
  xy
}

library(graphics);
# make sure we don't create infinite recursion if someone sources
# this file twice
if(!exists("old_plot.xy")) {
  old_plot.xy = graphics::plot.xy
}

bigplotfix_maxlen = 1e4

# formals copied from graphics::plot.xy
my_plot.xy = function(xy, type, pch = par("pch"), lty = par("lty"),
  col = par("col"), bg = NA, cex = 1, lwd = par("lwd"),
  ...) {

  if(bigplotfix_verbose) {
    message("In bigplotfix's plot.xy\n");
  }

  mycall=match.call();
  len=length(xy$x)
  if(len>bigplotfix_maxlen) {
    warning("bigplotfix.R (plot.xy): too many points (",len,"), compressing to ",bigplotfix_maxlen,"\n");
    xy = downsample_xy(xy, bigplotfix_maxlen, xlog=par("xlog"));
    mycall$xy=xy
  }
  mycall[[1]]=as.symbol("old_plot.xy");

  eval(mycall,envir=parent.frame());
}

# new binding solution adapted from Henrik Bengtsson
# https://stat.ethz.ch/pipermail/r-help/2008-August/171217.html
rebindPackageVar = function(pkg, name, new) {
  # assignInNamespace() no longer works here, thanks nannies
  ns=asNamespace(pkg)
  unlockBinding(name,ns)
  assign(name,new,envir=asNamespace(pkg),inherits=F)
  assign(name,new,envir=globalenv())
  lockBinding(name,ns)
}
rebindPackageVar("graphics", "plot.xy", my_plot.xy);

Here's a file I call bigplotfix.R. If you source it, it will define a wrapper for plot.xy. It also changes the environment of plot(), lines(), and points() so that these functions use the new wrapper (plot.xy is the "workhorse" function for these standard plotting methods). Thus you can continue to use the functions plot(), lines(), and points() with no modification. The wrapper does nothing if the input is small, but if the input is large then it breaks it into chunks and just plots the maximum and minimum x and y value for each chunk.

# bigplotfix.R
# 28 Nov 2016

# This file defines a wrapper for plot.xy which checks if the input
# data is longer than a certain maximum limit. If it is, it is
# downsampled before plotting. For 3 million input points, I got
# speed-ups of 10-100x. Note that if you want the output to look the
# same as the "uncompressed" version, you should be drawing lines,
# because the compression involves taking maximum and minimum values
# of blocks of points (try running test_bigplotfix() for a visual
# explanation). Also, no sorting is done on the input points, so
# things could get weird if they are out of order.
test_bigplotfix = function() {
  oldpar=par();
  par(mfrow=c(2,2))
  n=1e5;
  r=runif(n)
  bigplotfix_verbose<<-T
  mytitle=function(t,m) { title(main=sprintf("%s; elapsed=%0.4f s",m,t["elapsed"])) }
  mytime=function(m,e) { t=system.time(e); mytitle(t,m); }

  oldbigplotfix_maxlen = bigplotfix_maxlen
  bigplotfix_maxlen <<- 1e3;

  mytime("Compressed, points",plot(r));
  mytime("Compressed, lines",plot(r,type="l"));
  bigplotfix_maxlen <<- n
  mytime("Uncompressed, points",plot(r));
  mytime("Uncompressed, lines",plot(r,type="l"));
  par(oldpar);
  bigplotfix_maxlen <<- oldbigplotfix_maxlen
  bigplotfix_verbose <<- F
}

bigplotfix_verbose=F

downsample_xy = function(xy, n, xlog=F) {
  msg=if(bigplotfix_verbose) { message } else { function(...) { NULL } }
  msg("Finding range");
  r=range(xy$x);
  msg("Finding breaks");
  if(xlog) {
    breaks=exp(seq(from=log(r[1]),to=log(r[2]),length.out=n))
  } else {
    breaks=seq(from=r[1],to=r[2],length.out=n)
  }
  msg("Calling findInterval");
  ## cuts=cut(xy$x,breaks);
  # findInterval is much faster than cuts!
  cuts = findInterval(xy$x,breaks);
  if(0) {
    msg("In aggregate 1");
    dmax = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), max)
    dmax$cuts = NULL;
    msg("In aggregate 2");
    dmin = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), min)
    dmin$cuts = NULL;
  } else { # use data.table for MUCH faster aggregates
    # (see http://stackoverflow.com/questions/7722493/how-does-one-aggregate-and-summarize-data-quickly)
    suppressMessages(library(data.table))
    msg("In data.table");
    dt = data.table(x=xy$x,y=xy$y,cuts=cuts)
    msg("In data.table aggregate 1");
    dmax = dt[,list(x=max(x),y=max(y)),keyby="cuts"]
    dmax$cuts=NULL;
    msg("In data.table aggregate 2");
    dmin = dt[,list(x=min(x),y=min(y)),keyby="cuts"]
    dmin$cuts=NULL;
    #  ans = data_t[,list(A = sum(count), B = mean(count)), by = 'PID,Time,Site']
  }
  msg("In rep, rbind");
  # interleave rows (copied from a SO answer)
  s <- rep(1:n, each = 2) + (0:1) * n
  xy = rbind(dmin,dmax)[s,];
  xy
}

# save the original plot.xy
library(graphics);
old_plot.xy = graphics::plot.xy

bigplotfix_maxlen = 1e4

# formals copied from graphics::plot.xy
plot.xy = function(xy, type, pch = par("pch"), lty = par("lty"),
  col = par("col"), bg = NA, cex = 1, lwd = par("lwd"),
  ...) {

  if(bigplotfix_verbose) {
    message("In bigplotfix's plot.xy\n");
  }

  mycall=match.call();
  len=length(xy$x)
  if(len>bigplotfix_maxlen) {
    warning("bigplotfix.R (plot.xy): too many points (",len,"), compressing to ",bigplotfix_maxlen,"\n");
    xy = downsample_xy(xy, bigplotfix_maxlen, xlog=par("xlog"));
    mycall$xy=xy
  }
  mycall[[1]]=as.symbol("old_plot.xy");

  eval(mycall,envir=parent.frame());
}

# Are these the only callers of plot.xy?
environment(plot.default)=globalenv();
environment(lines.default)=globalenv();
environment(points.default)=globalenv();
# The above reassignment of function environments is a bit hacky. We
# could also just reassign plot.xy in the graphics package, but there
# is an annoying problem with "locked bindings" and "locked
# namespaces" which makes this difficult, see
# http://stackoverflow.com/questions/3094232/add-objects-to-package-namespace
# Anyway... better solutions welcome...

Here's a file I call bigplotfix.R. If you source it, it will define a wrapper for plot.xy which "compresses" the plot data when it is very large. The wrapper does nothing if the input is small, but if the input is large then it breaks it into chunks and just plots the maximum and minimum x and y value for each chunk. Sourcing bigplotfix.R also rebinds graphics::plot.xy to point to the wrapper (sourcing multiple times is OK).

Note that plot.xy is the "workhorse" function for the standard plotting methods like plot(), lines(), and points(). Thus you can continue to use these functions in your code with no modification, and your large plots will be automatically compressed.

# bigplotfix.R
# 28 Nov 2016

# This file defines a wrapper for plot.xy which checks if the input
# data is longer than a certain maximum limit. If it is, it is
# downsampled before plotting. For 3 million input points, I got
# speed-ups of 10-100x. Note that if you want the output to look the
# same as the "uncompressed" version, you should be drawing lines,
# because the compression involves taking maximum and minimum values
# of blocks of points (try running test_bigplotfix() for a visual
# explanation). Also, no sorting is done on the input points, so
# things could get weird if they are out of order.
test_bigplotfix = function() {
  oldpar=par();
  par(mfrow=c(2,2))
  n=1e5;
  r=runif(n)
  bigplotfix_verbose<<-T
  mytitle=function(t,m) { title(main=sprintf("%s; elapsed=%0.4f s",m,t["elapsed"])) }
  mytime=function(m,e) { t=system.time(e); mytitle(t,m); }

  oldbigplotfix_maxlen = bigplotfix_maxlen
  bigplotfix_maxlen <<- 1e3;

  mytime("Compressed, points",plot(r));
  mytime("Compressed, lines",plot(r,type="l"));
  bigplotfix_maxlen <<- n
  mytime("Uncompressed, points",plot(r));
  mytime("Uncompressed, lines",plot(r,type="l"));
  par(oldpar);
  bigplotfix_maxlen <<- oldbigplotfix_maxlen
  bigplotfix_verbose <<- F
}

bigplotfix_verbose=F

downsample_xy = function(xy, n, xlog=F) {
  msg=if(bigplotfix_verbose) { message } else { function(...) { NULL } }
  msg("Finding range");
  r=range(xy$x);
  msg("Finding breaks");
  if(xlog) {
    breaks=exp(seq(from=log(r[1]),to=log(r[2]),length.out=n))
  } else {
    breaks=seq(from=r[1],to=r[2],length.out=n)
  }
  msg("Calling findInterval");
  ## cuts=cut(xy$x,breaks);
  # findInterval is much faster than cuts!
  cuts = findInterval(xy$x,breaks);
  if(0) {
    msg("In aggregate 1");
    dmax = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), max)
    dmax$cuts = NULL;
    msg("In aggregate 2");
    dmin = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), min)
    dmin$cuts = NULL;
  } else { # use data.table for MUCH faster aggregates
    # (see http://stackoverflow.com/questions/7722493/how-does-one-aggregate-and-summarize-data-quickly)
    suppressMessages(library(data.table))
    msg("In data.table");
    dt = data.table(x=xy$x,y=xy$y,cuts=cuts)
    msg("In data.table aggregate 1");
    dmax = dt[,list(x=max(x),y=max(y)),keyby="cuts"]
    dmax$cuts=NULL;
    msg("In data.table aggregate 2");
    dmin = dt[,list(x=min(x),y=min(y)),keyby="cuts"]
    dmin$cuts=NULL;
    #  ans = data_t[,list(A = sum(count), B = mean(count)), by = 'PID,Time,Site']
  }
  msg("In rep, rbind");
  # interleave rows (copied from a SO answer)
  s <- rep(1:n, each = 2) + (0:1) * n
  xy = rbind(dmin,dmax)[s,];
  xy
} 

library(graphics);
# make sure we don't create infinite recursion if someone sources
# this file twice
if(!exists("old_plot.xy")) {
  old_plot.xy = graphics::plot.xy
}

bigplotfix_maxlen = 1e4

# formals copied from graphics::plot.xy
my_plot.xy = function(xy, type, pch = par("pch"), lty = par("lty"),
  col = par("col"), bg = NA, cex = 1, lwd = par("lwd"),
  ...) {

  if(bigplotfix_verbose) {
    message("In bigplotfix's plot.xy\n");
  }

  mycall=match.call();
  len=length(xy$x)
  if(len>bigplotfix_maxlen) {
    warning("bigplotfix.R (plot.xy): too many points (",len,"), compressing to ",bigplotfix_maxlen,"\n");
    xy = downsample_xy(xy, bigplotfix_maxlen, xlog=par("xlog"));
    mycall$xy=xy
  }
  mycall[[1]]=as.symbol("old_plot.xy");

  eval(mycall,envir=parent.frame());
}

# new binding solution adapted from Henrik Bengtsson
# https://stat.ethz.ch/pipermail/r-help/2008-August/171217.html
rebindPackageVar = function(pkg, name, new) {
  # assignInNamespace() no longer works here, thanks nannies
  ns=asNamespace(pkg)
  unlockBinding(name,ns)
  assign(name,new,envir=asNamespace(pkg),inherits=F)
  lockBinding(name,ns)
}
rebindPackageVar("graphics", "plot.xy", my_plot.xy);

# bigplotfix.R
# 28 Nov 2016

# This file defines a wrapper for plot.xy which checks if the input
# data is longer than a certain maximum limit. If it is, it is
# downsampled before plotting. For 3 million input points, I got
# speed-ups of 10-100x. Note that if you want the output to look the
# same as the "uncompressed" version, you should be drawing lines,
# because the compression involves taking maximum and minimum values
# of blocks of points (try running test_bigplotfix() for a visual
# explanation). Also, no sorting is done on the input points, so
# things could get weird if they are out of order.
test_bigplotfix = function() {
  oldpar=par();
  par(mfrow=c(2,2))
  n=1e5;
  r=runif(n)
  bigplotfix_verbose<<-T
  mytitle=function(t,m) { title(main=sprintf("%s; elapsed=%0.4f s",m,t["elapsed"])) }
  mytime=function(m,e) { t=system.time(e); mytitle(t,m); }

  oldbigplotfix_maxlen = bigplotfix_maxlen
  bigplotfix_maxlen <<- 1e3;

  mytime("Compressed, points",plot(r));
  mytime("Compressed, lines",plot(r,type="l"));
  bigplotfix_maxlen <<- n
  mytime("Uncompressed, points",plot(r));
  mytime("Uncompressed, lines",plot(r,type="l"));
  par(oldpar);
  bigplotfix_maxlen <<- oldbigplotfix_maxlen
  bigplotfix_verbose <<- F
}

bigplotfix_verbose=F

downsample_xy = function(xy, n, xlog=F) {
  msg=if(bigplotfix_verbose) { cat } else { function(...) { NULL } }
  msg("Finding range\n");
  r=range(xy$x);
  msg("Finding breaks\n");
  if(xlog) {
    breaks=exp(seq(from=log(r[1]),to=log(r[2]),length.out=n))
  } else {
    breaks=seq(from=r[1],to=r[2],length.out=n)
  }
  msg("Calling findInterval\n");
  ## cuts=cut(xy$x,breaks);
  # findInterval is much faster than cuts!
  cuts = findInterval(xy$x,breaks);
  if(0) {
    msg("In aggregate 1\n");
    dmax = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), max)
    dmax$cuts = NULL;
    msg("In aggregate 2\n");
    dmin = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), min)
    dmin$cuts = NULL;
  } else { # use data.table for MUCH faster aggregates
    # (see http://stackoverflow.com/questions/7722493/how-does-one-aggregate-and-summarize-data-quickly)
    suppressMessages(library(data.table))
    msg("In data.table\n");
    dt = data.table(x=xy$x,y=xy$y,cuts=cuts)
    msg("In data.table aggregate 1\n");
    dmax = dt[,list(x=max(x),y=max(y)),keyby="cuts"]
    dmax$cuts=NULL;
    msg("In data.table aggregate 2\n");
    dmin = dt[,list(x=min(x),y=min(y)),keyby="cuts"]
    dmin$cuts=NULL;
    #  ans = data_t[,list(A = sum(count), B = mean(count)), by = 'PID,Time,Site']
  }
  msg("In rep, rbind\n");
  # interleave rows (copied from a SO answer)
  s <- rep(1:n, each = 2) + (0:1) * n
  xy = rbind(dmin,dmax)[s,];
  xy
}

# save the original plot.xy
library(graphics);
old_plot.xy = graphics::plot.xy

bigplotfix_maxlen = 1e4

# formals copied from graphics::plot.xy
plot.xy = function(xy, type, pch = par("pch"), lty = par("lty"),
  col = par("col"), bg = NA, cex = 1, lwd = par("lwd"),
  ...) {

  if(bigplotfix_verbose) {
    cat("In bigplotfix's plot.xy\n");
  }

  mycall=match.call();
  len=length(xy$x)
  if(len>bigplotfix_maxlen) {
    cat("bigplotfix.R (plot.xy): too many points (",len,"), compressing to ",bigplotfix_maxlen,"\n");
    xy = downsample_xy(xy, bigplotfix_maxlen, xlog=par("xlog"));
    mycall$xy=xy
  }
  mycall[[1]]=as.symbol("old_plot.xy");

  eval(mycall);
}

# Are these the only callers of plot.xy?
environment(plot.default)=globalenv();
environment(lines.default)=globalenv();
environment(points.default)=globalenv();
# The above reassignment of function environments is a bit hacky. We
# could also just reassign plot.xy in the graphics package, but there
# is an annoying problem with "locked bindings" and "locked
# namespaces" which makes this difficult, see
# http://stackoverflow.com/questions/3094232/add-objects-to-package-namespace
# Anyway... better solutions welcome...

# bigplotfix.R
# 28 Nov 2016

# This file defines a wrapper for plot.xy which checks if the input
# data is longer than a certain maximum limit. If it is, it is
# downsampled before plotting. For 3 million input points, I got
# speed-ups of 10-100x. Note that if you want the output to look the
# same as the "uncompressed" version, you should be drawing lines,
# because the compression involves taking maximum and minimum values
# of blocks of points (try running test_bigplotfix() for a visual
# explanation). Also, no sorting is done on the input points, so
# things could get weird if they are out of order.
test_bigplotfix = function() {
  oldpar=par();
  par(mfrow=c(2,2))
  n=1e5;
  r=runif(n)
  bigplotfix_verbose<<-T
  mytitle=function(t,m) { title(main=sprintf("%s; elapsed=%0.4f s",m,t["elapsed"])) }
  mytime=function(m,e) { t=system.time(e); mytitle(t,m); }

  oldbigplotfix_maxlen = bigplotfix_maxlen
  bigplotfix_maxlen <<- 1e3;

  mytime("Compressed, points",plot(r));
  mytime("Compressed, lines",plot(r,type="l"));
  bigplotfix_maxlen <<- n
  mytime("Uncompressed, points",plot(r));
  mytime("Uncompressed, lines",plot(r,type="l"));
  par(oldpar);
  bigplotfix_maxlen <<- oldbigplotfix_maxlen
  bigplotfix_verbose <<- F
}

bigplotfix_verbose=F

downsample_xy = function(xy, n, xlog=F) {
  msg=if(bigplotfix_verbose) { message } else { function(...) { NULL } }
  msg("Finding range");
  r=range(xy$x);
  msg("Finding breaks");
  if(xlog) {
    breaks=exp(seq(from=log(r[1]),to=log(r[2]),length.out=n))
  } else {
    breaks=seq(from=r[1],to=r[2],length.out=n)
  }
  msg("Calling findInterval");
  ## cuts=cut(xy$x,breaks);
  # findInterval is much faster than cuts!
  cuts = findInterval(xy$x,breaks);
  if(0) {
    msg("In aggregate 1");
    dmax = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), max)
    dmax$cuts = NULL;
    msg("In aggregate 2");
    dmin = aggregate(list(x=xy$x, y=xy$y), by=list(cuts=cuts), min)
    dmin$cuts = NULL;
  } else { # use data.table for MUCH faster aggregates
    # (see http://stackoverflow.com/questions/7722493/how-does-one-aggregate-and-summarize-data-quickly)
    suppressMessages(library(data.table))
    msg("In data.table");
    dt = data.table(x=xy$x,y=xy$y,cuts=cuts)
    msg("In data.table aggregate 1");
    dmax = dt[,list(x=max(x),y=max(y)),keyby="cuts"]
    dmax$cuts=NULL;
    msg("In data.table aggregate 2");
    dmin = dt[,list(x=min(x),y=min(y)),keyby="cuts"]
    dmin$cuts=NULL;
    #  ans = data_t[,list(A = sum(count), B = mean(count)), by = 'PID,Time,Site']
  }
  msg("In rep, rbind");
  # interleave rows (copied from a SO answer)
  s <- rep(1:n, each = 2) + (0:1) * n
  xy = rbind(dmin,dmax)[s,];
  xy
}

# save the original plot.xy
library(graphics);
old_plot.xy = graphics::plot.xy

bigplotfix_maxlen = 1e4

# formals copied from graphics::plot.xy
plot.xy = function(xy, type, pch = par("pch"), lty = par("lty"),
  col = par("col"), bg = NA, cex = 1, lwd = par("lwd"),
  ...) {

  if(bigplotfix_verbose) {
    message("In bigplotfix's plot.xy\n");
  }

  mycall=match.call();
  len=length(xy$x)
  if(len>bigplotfix_maxlen) {
    warning("bigplotfix.R (plot.xy): too many points (",len,"), compressing to ",bigplotfix_maxlen,"\n");
    xy = downsample_xy(xy, bigplotfix_maxlen, xlog=par("xlog"));
    mycall$xy=xy
  }
  mycall[[1]]=as.symbol("old_plot.xy");

  eval(mycall,envir=parent.frame());
}

# Are these the only callers of plot.xy?
environment(plot.default)=globalenv();
environment(lines.default)=globalenv();
environment(points.default)=globalenv();
# The above reassignment of function environments is a bit hacky. We
# could also just reassign plot.xy in the graphics package, but there
# is an annoying problem with "locked bindings" and "locked
# namespaces" which makes this difficult, see
# http://stackoverflow.com/questions/3094232/add-objects-to-package-namespace
# Anyway... better solutions welcome...