package main

import (
	"image"
	"image/color"
	"image/draw"
	"math"
	"math/rand"

	"github.com/aquilax/go-perlin"
	"github.com/disintegration/imaging"
	"github.com/ojrac/opensimplex-go"
)

const (
	alpha = 2.
	beta  = 2.
	n     = 3
)

func GenerateHeightmap(width, height, octaves int, scale float64, seed int64) image.Image {
	p := perlin.NewPerlin(alpha, beta, n, seed)
	img := image.NewGray(image.Rect(0, 0, width, height))

	if scale == 0 {
		scale = 100.0
	}

	for x := range width {
		for y := range height {
			var noise float64
			frequency := 1.0
			amplitude := 1.0
			maxAmplitude := 0.0

			for range octaves {
				noise += p.Noise2D(float64(x)*frequency/scale, float64(y)*frequency/scale) * amplitude
				maxAmplitude += amplitude
				amplitude /= 2.0
				frequency *= 2.0
			}

			noise /= maxAmplitude
			grayColor := uint8((noise + 1) * 127.5)
			img.SetGray(x, y, color.Gray{Y: grayColor})
		}
	}

	return img
}

func ApplyRoughness(heightmap image.Image, roughness float64) image.Image {
	bounds := heightmap.Bounds()
	composite := image.NewRGBA(bounds)
	draw.Draw(composite, bounds, heightmap, image.Point{}, draw.Src)

	alphaValue := 255 - uint8(roughness*2.55)
	overlay := image.NewUniform(color.RGBA{R: 128, G: 128, B: 128, A: alphaValue})
	draw.Draw(composite, bounds, overlay, image.Point{}, draw.Over)

	return composite
}

// DarkenLakeAreas applies a visual darkening effect to the heightmap where lakes exist.
func DarkenLakeAreas(heightmap image.Image, lakePixels []image.Point) image.Image {
	bounds := heightmap.Bounds()
	width := bounds.Dx()

	// Create a new black image to draw the lakes on
	lakeMask := image.NewRGBA(bounds)
	black := color.RGBA{0, 0, 0, 255}
	for _, p := range lakePixels {
		lakeMask.Set(p.X, p.Y, black)
	}

	// Apply a Gaussian blur to the lake mask
	blurRadius := float64(width) * 0.05
	blurredLakeMask := imaging.Blur(lakeMask, blurRadius)

	// Composite the blurred lake mask onto the heightmap with 50% opacity
	composite := image.NewRGBA(bounds)
	draw.Draw(composite, bounds, heightmap, image.Point{}, draw.Src)
	draw.DrawMask(composite, bounds, blurredLakeMask, image.Point{}, image.NewUniform(color.Alpha{192}), image.Point{}, draw.Over)

	return composite
}

func GenerateTrees(img *image.RGBA, lakePixels []image.Point, minTreeSize, maxTreeSize, treeCoverage, treeClumpiness float64, seed int64) {
	width := img.Bounds().Dx()
	height := img.Bounds().Dy()

	// 1. Calculate number of trees to place from coverage %.
	avgTreeSize := (minTreeSize + maxTreeSize) / 2
	if avgTreeSize <= 0 {
		return
	}
	avgRadius := avgTreeSize / 2
	avgTreeArea := math.Pi * avgRadius * avgRadius
	if avgTreeArea == 0 {
		return
	}
	totalArea := float64(width * height)
	targetTreePixels := totalArea * (treeCoverage / 100.0)
	numTreesToPlace := int(targetTreePixels / avgTreeArea)
	if numTreesToPlace == 0 {
		return
	}

	// 2. Generate a simplex noise map for tree placement.
	noise := opensimplex.New(seed)
	treeNoiseMap := image.NewGray(image.Rect(0, 0, width, height))
	treeNoiseZoom := 0.05
	for y := range height {
		for x := range width {
			val := noise.Eval2(float64(x)*treeNoiseZoom, float64(y)*treeNoiseZoom)
			val = (val + 1) / 2 // Normalize to 0-1
			treeNoiseMap.SetGray(x, y, color.Gray{Y: uint8(val * 255)})
		}
	}
	threshold := uint8(255 * (1 - (treeCoverage / 100.0)))

	isLake := make(map[image.Point]bool)
	for _, p := range lakePixels {
		isLake[p] = true
	}

	randSrc := rand.New(rand.NewSource(seed))

	// 3. Determine initial clump trees
	numClumpTrees := min(int(treeClumpiness), numTreesToPlace)

	initialPoints := make([]image.Point, 0, numClumpTrees)
	for range numClumpTrees {
		for range 100 { // try 100 times to find a valid spot
			p := image.Point{X: randSrc.Intn(width), Y: randSrc.Intn(height)}
			if treeNoiseMap.GrayAt(p.X, p.Y).Y >= threshold && !isLake[p] {
				initialPoints = append(initialPoints, p)
				break
			}
		}
	}

	// 4. Place remaining trees using Bridson's Algorithm
	minRadius := minTreeSize
	allPoints := poissonDiscSampling(width, height, minRadius, 30, initialPoints, func(p image.Point) bool {
		return treeNoiseMap.GrayAt(p.X, p.Y).Y >= threshold && !isLake[p]
	}, seed)

	// 5. Draw the trees.
	for _, p := range allPoints {
		size := minTreeSize + randSrc.Float64()*(maxTreeSize-minTreeSize)
		if size <= 0 {
			continue
		}
		r := size / 2
		// Use a simple pixel-by-pixel circle drawing method
		for y := p.Y - int(r); y <= p.Y+int(r); y++ {
			for x := p.X - int(r); x <= p.X+int(r); x++ {
				pt := image.Point{X: x, Y: y}
				if !pt.In(img.Bounds()) || isLake[pt] {
					continue
				}

				if (math.Pow(float64(x-p.X), 2) + math.Pow(float64(y-p.Y), 2)) <= r*r {
					// Blend the tree color with the background
					// For simplicity, we just set a solid color for now.
					img.Set(x, y, color.RGBA{R: 0, G: 100, B: 0, A: 255})
				}
			}
		}
	}
}

func poissonDiscSampling(width, height int, minRadius float64, k int, initialPoints []image.Point, isValid func(image.Point) bool, seed int64) []image.Point {
	randSrc := rand.New(rand.NewSource(seed))
	points := initialPoints
	activeList := append([]image.Point(nil), initialPoints...)

	cellSize := minRadius / math.Sqrt(2)
	gridWidth := int(math.Ceil(float64(width)/cellSize)) + 1
	gridHeight := int(math.Ceil(float64(height)/cellSize)) + 1
	grid := make([][]image.Point, gridWidth)
	for i := range grid {
		grid[i] = make([]image.Point, gridHeight)
	}

	for _, p := range points {
		gridX, gridY := int(float64(p.X)/cellSize), int(float64(p.Y)/cellSize)
		grid[gridX][gridY] = p
	}

	for len(activeList) > 0 {
		listIndex := randSrc.Intn(len(activeList))
		p := activeList[listIndex]
		found := false
		for range k {
			angle := randSrc.Float64() * 2 * math.Pi
			radius := minRadius + randSrc.Float64()*minRadius
			x, y := float64(p.X)+radius*math.Cos(angle), float64(p.Y)+radius*math.Sin(angle)
			newPoint := image.Point{X: int(x), Y: int(y)}

			if newPoint.X < 0 || newPoint.X >= width || newPoint.Y < 0 || newPoint.Y >= height {
				continue
			}

			if !isValid(newPoint) {
				continue
			}

			gridX, gridY := int(x/cellSize), int(y/cellSize)
			valid := true
			for m := -1; m <= 1; m++ {
				for n := -1; n <= 1; n++ {
					checkX, checkY := gridX+m, gridY+n
					if checkX >= 0 && checkX < gridWidth && checkY >= 0 && checkY < gridHeight && grid[checkX][checkY] != (image.Point{}) {
						dist := math.Sqrt(math.Pow(float64(grid[checkX][checkY].X-newPoint.X), 2) + math.Pow(float64(grid[checkX][checkY].Y-newPoint.Y), 2))
						if dist < minRadius {
							valid = false
							break
						}
					}
				}
				if !valid {
					break
				}
			}

			if valid {
				points = append(points, newPoint)
				activeList = append(activeList, newPoint)
				grid[gridX][gridY] = newPoint
				found = true
			}
		}
		if !found {
			activeList = append(activeList[:listIndex], activeList[listIndex+1:]...)
		}
	}
	return points
}
func bresenham(path []image.Point) []image.Point {
	if len(path) < 2 {
		return path
	}

	var fullPath []image.Point
	for i := range len(path) - 1 {
		p1, p2 := path[i], path[i+1]
		dx, dy := p2.X-p1.X, p2.Y-p1.Y
		absDx, absDy := int(math.Abs(float64(dx))), int(math.Abs(float64(dy)))
		sx, sy := 1, 1
		if dx < 0 {
			sx = -1
		}
		if dy < 0 {
			sy = -1
		}
		err := absDx - absDy

		x, y := p1.X, p1.Y
		for {
			fullPath = append(fullPath, image.Point{X: x, Y: y})
			if x == p2.X && y == p2.Y {
				break
			}
			e2 := 2 * err
			if e2 > -absDy {
				err -= absDy
				x += sx
			}
			if e2 < absDx {
				err += absDx
				y += sy
			}
		}
	}
	return fullPath
}
func calculatePath(start, end image.Point, curvyness, avgDim float64, randSrc *rand.Rand, numControlPoints int) []image.Point {

	dx := end.X - start.X

	dy := end.Y - start.Y

	dist := math.Sqrt(float64(dx*dx + dy*dy))

	if dist == 0 {

		return []image.Point{start}

	}

	if curvyness == 0 {

		return bresenham([]image.Point{start, end})

	}

	type wave struct {
		amplitude float64

		numWaves float64

		phase float64
	}

	waves := make([]wave, 3)

	amp := (avgDim / 10.0) * curvyness

	mainWavelength := avgDim / 4.0

	if mainWavelength < 1 {

		mainWavelength = 1

	}

	baseNumWaves := (dist / mainWavelength) * curvyness

	for i := range 3 {

		freqMultiplier := 1.0 + float64(i)

		randomizedNumWaves := baseNumWaves * freqMultiplier * (0.75 + randSrc.Float64()*0.5)

		waves[i] = wave{

			amplitude: amp,

			numWaves: randomizedNumWaves,

			phase: randSrc.Float64() * 2 * math.Pi,
		}

		amp /= 3

	}

	controlPoints := make([]image.Point, numControlPoints+1)

	for i := range numControlPoints + 1 {

		t := float64(i) / float64(numControlPoints)

		x := float64(start.X) + t*float64(dx)

		y := float64(start.Y) + t*float64(dy)

		perpX, perpY := -float64(dy)/dist, float64(dx)/dist

		totalOffset := 0.0

		for _, w := range waves {

			totalOffset += math.Sin(t*w.numWaves*2*math.Pi+w.phase) * w.amplitude

		}

		// Apply an envelope to ensure start/end points are anchored

		totalOffset *= math.Sin(t * math.Pi)

		x += totalOffset * perpX

		y += totalOffset * perpY

		controlPoints[i] = image.Point{X: int(math.Round(x)), Y: int(math.Round(y))}

	}

	return bresenham(controlPoints)

}