library(ggplot2)
library(grid)
library(readr)
train <- data.frame(read_csv("../input/train.csv"))

labels   <- train[,1]
features <- train[,-1]

rowsToPlot <- sample(1:nrow(train), 49)

rowToMatrix <- function(row) {
    intensity <- as.numeric(row)/max(as.numeric(row))
    return(t(matrix((rgb(intensity, intensity, intensity)), 28, 28)))
}

geom_digit <- function(digits) 
{
  layer(geom = GeomRasterDigit, stat = "identity", position = "identity", data = NULL, 
        params = list(digits=digits))  
}


GeomRasterDigit <- ggproto("GeomRasterDigit", 
                           ggplot2::GeomRaster, 
                           draw_panel = function(data, panel_scales, coordinates, digits = digits) {
                             if (!inherits(coordinates, "CoordCartesian")) {
                               stop("geom_digit only works with Cartesian coordinates",
                                    call. = FALSE)
                             }
                             corners <- data.frame(x = c(-Inf, Inf), y = c(-Inf, Inf))
                             bounds <- coordinates$transform(corners, panel_scales)
                             x_rng <- range(bounds$x, na.rm = TRUE)
                             y_rng <- range(bounds$y, na.rm = TRUE)
                             rasterGrob(as.raster(rowToMatrix(digits[data$rows,])), 
                                        x = mean(x_rng), y = mean(y_rng), 
                                        default.units = "native", just = c("center","center"), 
                                        interpolate = FALSE)
                           }) 

p <- ggplot(data.frame(rows=rowsToPlot, labels=labels[rowsToPlot]), 
  aes(x=.1, y=.9, rows=rows, label=labels)) +
  facet_wrap(~ rows, ncol=7) +
  geom_digit(features) 
  
ggsave("example_digits.png", p, width=10, height=10)