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RPG_City_Maker_Reborn/terrain.go
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package main
import (
"image"
"image/color"
"image/draw"
"math"
"math/rand"
"runtime"
"sync"
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"github.com/aquilax/go-perlin"
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"github.com/disintegration/imaging"
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"github.com/ojrac/opensimplex-go"
)
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const (
alpha = 2.
beta = 2.
n = 3
)
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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))
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if scale == 0 {
scale = 100.0
}
numGoroutines := runtime.NumCPU()
var wg sync.WaitGroup
rowsPerGoroutine := height / numGoroutines
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for i := 0; i < numGoroutines; i++ {
startY := i * rowsPerGoroutine
endY := startY + rowsPerGoroutine
if i == numGoroutines-1 {
endY = height
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}
wg.Add(1)
go func(startY, endY int) {
defer wg.Done()
for y := startY; y < endY; y++ {
for x := 0; x < width; x++ {
var noise float64
frequency := 1.0
amplitude := 1.0
maxAmplitude := 0.0
for j := 0; j < octaves; j++ {
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})
}
}
}(startY, endY)
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}
wg.Wait()
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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
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}
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// 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()
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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)
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draw.DrawMask(composite, bounds, blurredLakeMask, image.Point{}, image.NewUniform(color.Alpha{192}), image.Point{}, draw.Over)
return composite
}
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func FlattenRoadAreas(heightmap image.Image, roadPixels []image.Point) image.Image {
bounds := heightmap.Bounds()
width := bounds.Dx()
// Create a new image with the road pixels drawn on it.
roadMask := image.NewGray(bounds)
for _, p := range roadPixels {
roadMask.SetGray(p.X, p.Y, color.Gray{Y: 255})
}
// Blur the road mask.
blurRadius := float64(width) * 0.01
blurredRoadMask := imaging.Blur(roadMask, blurRadius)
// Create a new image to store the blurred heightmap.
blurredHeightmap := imaging.Blur(heightmap, blurRadius)
// Create a new composite image.
composite := image.NewRGBA(bounds)
for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
for x := bounds.Min.X; x < bounds.Max.X; x++ {
maskAlpha, _, _, _ := blurredRoadMask.At(x, y).RGBA()
if maskAlpha > 0 {
// Linearly interpolate between the original and blurred heightmap based on the mask alpha.
originalColor := heightmap.At(x, y)
blurredColor := blurredHeightmap.At(x, y)
r1, g1, b1, a1 := originalColor.RGBA()
r2, g2, b2, a2 := blurredColor.RGBA()
alpha := float64(maskAlpha) / 65535.0
r := uint16(float64(r1)*(1-alpha) + float64(r2)*alpha)
g := uint16(float64(g1)*(1-alpha) + float64(g2)*alpha)
b := uint16(float64(b1)*(1-alpha) + float64(b2)*alpha)
a := uint16(float64(a1)*(1-alpha) + float64(a2)*alpha)
composite.Set(x, y, color.RGBA64{R: r, G: g, B: b, A: a})
} else {
composite.Set(x, y, heightmap.At(x, y))
}
}
}
return composite
}
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func GenerateTrees(img *image.RGBA, lakePixels, roadPixels []image.Point, minTreeSize, maxTreeSize, treeCoverage, treeClumpiness float64, seed int64) []image.Point {
width := img.Bounds().Dx()
height := img.Bounds().Dy()
// 1. Calculate number of trees to place from coverage %.
avgTreeSize := (minTreeSize + maxTreeSize) / 2
if avgTreeSize <= 0 {
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return nil
}
avgRadius := avgTreeSize / 2
avgTreeArea := math.Pi * avgRadius * avgRadius
if avgTreeArea == 0 {
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return nil
}
totalArea := float64(width * height)
targetTreePixels := totalArea * (treeCoverage / 100.0)
numTreesToPlace := int(targetTreePixels / avgTreeArea)
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if numTreesToPlace == 0 {
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return nil
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}
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// 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
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for y := range height {
for x := range width {
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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)})
}
}
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threshold := uint8(255 * (1 - (treeCoverage / 100.0)))
isLake := make(map[image.Point]bool)
for _, p := range lakePixels {
isLake[p] = true
}
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isRoad := make(map[image.Point]bool)
for _, p := range roadPixels {
isRoad[p] = true
}
randSrc := rand.New(rand.NewSource(seed))
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// 3. Determine initial clump trees
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numClumpTrees := min(int(treeClumpiness), numTreesToPlace)
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initialPoints := make([]image.Point, 0, numClumpTrees)
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for range numClumpTrees {
for range 100 { // try 100 times to find a valid spot
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p := image.Point{X: randSrc.Intn(width), Y: randSrc.Intn(height)}
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if treeNoiseMap.GrayAt(p.X, p.Y).Y >= threshold && !isLake[p] && !isRoad[p] {
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initialPoints = append(initialPoints, p)
break
}
}
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}
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// 4. Place remaining trees using Bridson's Algorithm
minRadius := minTreeSize
allPoints := poissonDiscSampling(width, height, minRadius, 30, initialPoints, func(p image.Point) bool {
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return treeNoiseMap.GrayAt(p.X, p.Y).Y >= threshold && !isLake[p] && !isRoad[p]
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}, seed)
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var treePixels []image.Point
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// 5. Draw the trees.
numGoroutines := runtime.NumCPU()
if len(allPoints) < numGoroutines {
numGoroutines = len(allPoints)
}
if numGoroutines == 0 {
return nil
}
var wg sync.WaitGroup
results := make(chan []image.Point, numGoroutines)
pointsPerGoroutine := (len(allPoints) + numGoroutines - 1) / numGoroutines
for i := 0; i < numGoroutines; i++ {
start := i * pointsPerGoroutine
end := start + pointsPerGoroutine
if end > len(allPoints) {
end = len(allPoints)
}
wg.Add(1)
go func(points []image.Point, seed int64) {
defer wg.Done()
localRand := rand.New(rand.NewSource(seed))
localTreePixels := make([]image.Point, 0)
for _, p := range points {
size := minTreeSize + localRand.Float64()*(maxTreeSize-minTreeSize)
if size <= 0 {
continue
}
r := size / 2
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] || isRoad[pt] {
continue
}
if (math.Pow(float64(x-p.X), 2) + math.Pow(float64(y-p.Y), 2)) <= r*r {
img.Set(x, y, color.RGBA{R: 0, G: 100, B: 0, A: 255})
localTreePixels = append(localTreePixels, pt)
}
}
}
}
results <- localTreePixels
}(allPoints[start:end], seed+int64(i))
}
wg.Wait()
close(results)
for res := range results {
treePixels = append(treePixels, res...)
}
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return treePixels
}
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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
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for range k {
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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
}