multiple plots, each with there own scale_gradient()

scale_gradient.r

library(ggplot2)
library(grid)

make_normal_cont <- function(Ea, n=100, steps=11){
    Ut <- 0.2/Ea
    x <- rma_normal(n, Ea, Ea/10, 1e-4, Ut)
    effect_sizes <- seq(1e-4, Ea * 2, length.out=steps)
    mus <- seq(Ut - Ut/1.2, Ut *3, length.out=steps)
    res <- expand.grid(mean_effect = effect_sizes, Ut=mus)
    res$Lik <- apply(res, 1, function(r) dma_normal(x, a=r[1], Va =r[1]/50,
                                                    1e-4, r[2], log=TRUE))
#    res$Lik <- exp(res$Lik)
    p <- ggplot(res, aes(Ut, mean_effect, fill=Lik, z=Lik))
    p + geom_raster() + scale_fill_gradient() + geom_contour(colour='white') +
        geom_point(x=Ut, y=Ea, colour="white", size=2)
}

grid_layout <- list( c(1,1),
                     c(1,2),
                     c(2,1),
                     c(2,2))


Ea <- c(0.01, 0.02, 0.04, 0.1)

set.seed(321123)
grid.newpage()
pushViewport(viewport(layout=grid.layout(2,2)))
for(i in 1:4){
    p <- make_normal_cont(Ea[i], 1000, 31)
    print(p, vp=viewport(layout.pos.row=grid_layout[[i]][1], 
                         layout.pos.col=grid_layout[[i]][2]))
}