// cargo-deps: hsl, image, csv = "1.0.0-beta.4", serde, serde_derive

extern crate csv;
extern crate hsl;
extern crate image;
extern crate serde;
#[macro_use]
extern crate serde_derive;

use std::collections::BTreeSet;
use std::io;

#[derive(Debug, Deserialize)]
#[serde(rename_all = "camelCase")]
struct Tile {
    tile_x: usize,
    tile_y: usize,
    create_time: u64,
    modify_count: u64,
    modify_time: u64,
    access_count: u64,
    access_time: u64,
}

// Torus size (in tiles).
const TORUS_SZ: u32 = 512;

// Tile width/height (in pixels).
const TILE_W: u32 = 8;
const TILE_H: u32 = 5;

fn main() {
    // Read the `torus.csv` into a 2D array of `(access, modify)`.
    // Also track the values we see in `BTreeSet` (for ordering).
    let mut tiles = [[(0, 0); TORUS_SZ as usize]; TORUS_SZ as usize];
    let mut ord_a = BTreeSet::new();
    let mut ord_m = BTreeSet::new();
    for result in csv::Reader::from_reader(io::stdin()).deserialize() {
        let Tile {
            access_count: a,
            modify_count: m,
            tile_x: x,
            tile_y: y,
            ..
        } = result.unwrap();

        // Ignore 0,0, the values are too large.
        if (x, y) != (0, 0) {
            ord_a.insert(a);
            ord_m.insert(m);
        }

        // Handle old migrated values.
        if a == 0 && m > 0 {
            tiles[y][x] = (1, 0);
        } else {
            tiles[y][x] = (a, m);
        }
    }

    // Chunk the values by splitting them at the largest gaps.
    #[derive(PartialEq, Eq, PartialOrd, Ord)]
    struct Chunk {
        start: u64,
    }
    fn chunks(ord: BTreeSet<u64>, chunks: usize) -> Vec<Chunk> {
        let mut gaps = BTreeSet::new();
        let mut prev = 0;
        let mut run = 0;
        for &x in &ord {
            let gap = x - prev;
            if gap > 100 {
                // Favor gaps with longer runs before them.
                gaps.insert((gap + run * 2, x));
                run = 0;
            } else {
                run += 1;
            }
            prev = x;
        }
        let mut chunks: Vec<_> = gaps.iter()
            .rev()
            .take(chunks)
            .map(|&(_, start)| Chunk { start })
            .collect();
        chunks.sort();
        chunks
    }
    let chunks_a = chunks(ord_a, 15);
    let chunks_m = chunks(ord_m, 15);

    // Compose the heatmap image in-memory from the 2D array.
    let mut heatmap = image::ImageBuffer::new(TORUS_SZ * TILE_W, TORUS_SZ * TILE_H);
    let red = hsl::HSL::from_rgb(&[255, 0, 0]).h;
    // let green = hsl::HSL::from_rgb(&[0, 255, 0]).h;
    // let blue = hsl::HSL::from_rgb(&[0, 0, 255]).h;
    let yellow = hsl::HSL::from_rgb(&[255, 255, 0]).h;
    for y in 0..TORUS_SZ {
        for x in 0..TORUS_SZ {
            // Normalize a value to the [0, 1] interval based on chunks.
            fn chunk_normalize(chunks: &[Chunk], x: u64) -> f64 {
                if x == 0 {
                    0.0
                } else {
                    // Find the chunk x is in.
                    let i = chunks.iter().position(|c| c.start > x);
                    let mut v = i.unwrap_or(chunks.len()) as f64;

                    // Add the intra-chunk linear offset.
                    if let Some(i) = i {
                        let start = if i > 1 {
                            chunks[i - 1].start
                        } else {
                            0
                        };
                        v += (x - start) as f64 / (chunks[i].start - start) as f64;
                    }

                    // Normalize so all the chunks fit in [0, 1].
                    (v / chunks.len() as f64).min(1.0)
                }
            }
            // Get and normalize the values.
            let (a, m) = tiles[y as usize][x as usize];
            let a = chunk_normalize(&chunks_a, a).powf(0.2);
            let m = chunk_normalize(&chunks_m, m).powf(0.2);

            // access => luminosity
            let l = (a + m).min(1.0) * 0.7;
            // modify => saturation + hue (grey -> red -> yellow)
            let h = red * (1.0 - m) + yellow * m;
            let s = m;

            let (r, g, b) = hsl::HSL { h, s, l }.to_rgb();
            let rgb = image::Rgb([r, g, b]);

            let coord = |x, dx, px| ((x * 2 + TORUS_SZ + 1) * px / 2 + dx) % (TORUS_SZ * px);
            for dy in 0..TILE_H {
                let y = coord(y, dy, TILE_H);
                for dx in 0..TILE_W {
                    let x = coord(x, dx, TILE_W);
                    heatmap.put_pixel(x, y, rgb);
                }
            }
        }
    }

    // Save the heatmap image.
    heatmap.save("heatmap.png").unwrap();
}