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2012-03-02T20:09:32.330
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Update With the release of ggplot2 0.9.0, much of this functionality is covered by the new additions of <code>stat_summary2d</code> and <code>stat_summary_bin</code>. here is a gist for this answer: <a href="https://gist.github.com/1341218">https://gist.github.com/1341218</a> here is a slight modification of stat_bin2d so as to accept arbitrary function: <pre><code>StatAggr2d <- proto(Stat, { objname <- "aggr2d" default_aes <- function(.) aes(fill = ..value..) required_aes <- c("x", "y", "z") default_geom <- function(.) GeomRect calculate <- function(., data, scales, binwidth = NULL, bins = 30, breaks = NULL, origin = NULL, drop = TRUE, fun = mean, ...) { range <- list( x = scales$x$output_set(), y = scales$y$output_set() ) # Determine binwidth, if omitted if (is.null(binwidth)) { binwidth <- c(NA, NA) if (is.integer(data$x)) { binwidth[1] <- 1 } else { binwidth[1] <- diff(range$x) / bins } if (is.integer(data$y)) { binwidth[2] <- 1 } else { binwidth[2] <- diff(range$y) / bins } } stopifnot(is.numeric(binwidth)) stopifnot(length(binwidth) == 2) # Determine breaks, if omitted if (is.null(breaks)) { if (is.null(origin)) { breaks <- list( fullseq(range$x, binwidth[1]), fullseq(range$y, binwidth[2]) ) } else { breaks <- list( seq(origin[1], max(range$x) + binwidth[1], binwidth[1]), seq(origin[2], max(range$y) + binwidth[2], binwidth[2]) ) } } stopifnot(is.list(breaks)) stopifnot(length(breaks) == 2) stopifnot(all(sapply(breaks, is.numeric))) names(breaks) <- c("x", "y") xbin <- cut(data$x, sort(breaks$x), include.lowest=TRUE) ybin <- cut(data$y, sort(breaks$y), include.lowest=TRUE) if (is.null(data$weight)) data$weight <- 1 ans <- ddply(data.frame(data, xbin, ybin), .(xbin, ybin), function(d) data.frame(value = fun(d$z))) within(ans,{ xint <- as.numeric(xbin) xmin <- breaks$x[xint] xmax <- breaks$x[xint + 1] yint <- as.numeric(ybin) ymin <- breaks$y[yint] ymax <- breaks$y[yint + 1] }) } }) stat_aggr2d <- StatAggr2d$build_accessor() </code></pre> and usage: <pre><code>ggplot(data = testDF,aes(x=x,y=y, z=rts))+stat_aggr2d(bins=3) ggplot(data = testDF,aes(x=x,y=y, z=rts))+ stat_aggr2d(bins=3, fun = function(x) sum(x^2)) </code></pre> <img src="https://i.stack.imgur.com/8V3Z0.png" alt="enter image description here"> As well, here is a slight modification of stat_binhex: <pre><code>StatAggrhex <- proto(Stat, { objname <- "aggrhex" default_aes <- function(.) aes(fill = ..value..) required_aes <- c("x", "y", "z") default_geom <- function(.) GeomHex calculate <- function(., data, scales, binwidth = NULL, bins = 30, na.rm = FALSE, fun = mean, ...) { try_require("hexbin") data <- remove_missing(data, na.rm, c("x", "y"), name="stat_hexbin") if (is.null(binwidth)) { binwidth <- c( diff(scales$x$input_set()) / bins, diff(scales$y$input_set() ) / bins ) } try_require("hexbin") x <- data$x y <- data$y # Convert binwidths into bounds + nbins xbnds <- c( round_any(min(x), binwidth[1], floor) - 1e-6, round_any(max(x), binwidth[1], ceiling) + 1e-6 ) xbins <- diff(xbnds) / binwidth[1] ybnds <- c( round_any(min(y), binwidth[1], floor) - 1e-6, round_any(max(y), binwidth[2], ceiling) + 1e-6 ) ybins <- diff(ybnds) / binwidth[2] # Call hexbin hb <- hexbin( x, xbnds = xbnds, xbins = xbins, y, ybnds = ybnds, shape = ybins / xbins, IDs = TRUE ) value <- tapply(data$z, hb@cID, fun) # Convert to data frame data.frame(hcell2xy(hb), value) } }) stat_aggrhex <- StatAggrhex$build_accessor() </code></pre> and usage: <pre><code>ggplot(data = testDF,aes(x=x,y=y, z=rts))+stat_aggrhex(bins=3) ggplot(data = testDF,aes(x=x,y=y, z=rts))+ stat_aggrhex(bins=3, fun = function(x) sum(x^2)) </code></pre> <img src="https://i.stack.imgur.com/vYgc3.png" alt="enter image description here">
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