package radarfetch

import (
	"fmt"
	"image"
	"image/color"
	"image/png"
	"os"
	"path/filepath"
)

// AttachClusterPNGs renders a tiny PNG for each cluster by flood-filling
// from its centroid on the thresholded mask, cropping to the cluster bbox.
// It writes files to outDir/clusters/cluster-<id>.png and returns updated clusters
// with PNG field filled.
func AttachClusterPNGs(grid [][]*float64, thr float64, clusters []Cluster, outDir string) ([]Cluster, error) {
	const W, H = 256, 256
	if len(grid) != H || (len(grid) > 0 && len(grid[0]) != W) {
		return clusters, nil
	}
	// precompute threshold mask
	mask := make([][]bool, H)
	for r := 0; r < H; r++ {
		mask[r] = make([]bool, W)
		for c := 0; c < W; c++ {
			if grid[r][c] == nil {
				continue
			}
			if *grid[r][c] >= thr {
				mask[r][c] = true
			}
		}
	}
	outDir = filepath.Join(outDir, "clusters")
	_ = os.MkdirAll(outDir, 0o755)
	for i := range clusters {
		cl := &clusters[i]
		// BFS from (Row,Col) within mask to reconstruct membership
		r0, c0 := cl.Row, cl.Col
		if r0 < 0 || r0 >= H || c0 < 0 || c0 >= W || !mask[r0][c0] {
			// skip if centroid not on mask
			continue
		}
		minR, minC := cl.MinRow, cl.MinCol
		maxR, maxC := cl.MaxRow, cl.MaxCol
		w := maxC - minC + 1
		h := maxR - minR + 1
		if w <= 0 || h <= 0 || w > W || h > H {
			continue
		}
		img := image.NewRGBA(image.Rect(0, 0, w, h))
		// init transparent
		for y := 0; y < h; y++ {
			for x := 0; x < w; x++ {
				img.SetRGBA(x, y, color.RGBA{0, 0, 0, 0})
			}
		}
		// flood fill within bbox
		vis := make([][]bool, H)
		for r := 0; r < H; r++ {
			vis[r] = make([]bool, W)
		}
		stack := [][2]int{{r0, c0}}
		vis[r0][c0] = true
		dirs := [][2]int{{-1, 0}, {1, 0}, {0, -1}, {0, 1}, {-1, -1}, {-1, 1}, {1, -1}, {1, 1}}
		for len(stack) > 0 {
			cur := stack[len(stack)-1]
			stack = stack[:len(stack)-1]
			rr, cc := cur[0], cur[1]
			if rr < minR || rr > maxR || cc < minC || cc > maxC {
				continue
			}
			// paint
			dbz := grid[rr][cc]
			if dbz != nil {
				col := colorForDBZ(*dbz)
				img.SetRGBA(cc-minC, rr-minR, col)
			}
			for _, d := range dirs {
				nr, nc := rr+d[0], cc+d[1]
				if nr < 0 || nr >= H || nc < 0 || nc >= W {
					continue
				}
				if vis[nr][nc] || !mask[nr][nc] {
					continue
				}
				vis[nr][nc] = true
				stack = append(stack, [2]int{nr, nc})
			}
		}
		// write file
		name := fmt.Sprintf("cluster-%d.png", cl.ID)
		p := filepath.Join(outDir, name)
		f, err := os.Create(p)
		if err != nil {
			continue
		}
		_ = png.Encode(f, img)
		_ = f.Close()
		cl.PNG = filepath.Join(filepath.Base(outDir), name)
	}
	return clusters, nil
}