noise: add simplex noise (#207)

* noise: add simplex 2d implementation * noise: add simplex 1d/3d implementation * noise: add simplex 4d implementation * noise: fmt and clean * noise: rename `Perlin` struct to `Generator` and add tests for simplex noise * noise: add comments * noise: examples * noise: add fractal noise example * noise: fmt * Update README.md * Update README.md --------- Co-authored-by: Ulises Jeremias <[email protected]>
vlang · Aug 5, 2024 · ebaaf2d · ebaaf2d
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diff --git a/examples/noise_fractal_2d/README.md b/examples/noise_fractal_2d/README.md
@@ -0,0 +1,16 @@
+# Example - noise_fractal_2d 📘
+
+This example demonstrates the usage of the V Scientific Library for generating pink noise.
+
+## Instructions
+
+1. Ensure you have the V compiler installed. You can download it from [here](https://vlang.io).
+2. Ensure you have the VSL installed. You can do it following the [installation guide](https://github.com/vlang/vsl?tab=readme-ov-file#-installation)!
+3. Navigate to this directory.
+4. Run the example using the following command:
+
+```sh
+v run main.v
+```
+
+Enjoy exploring the capabilities of the V Scientific Library! 😊
diff --git a/examples/noise_fractal_2d/main.v b/examples/noise_fractal_2d/main.v
@@ -0,0 +1,54 @@
+module main
+
+import rand
+import vsl.noise
+import vsl.plot
+
+fn main() {
+	// Creation of the noise generator.
+	// Other noise functions and dimensions count are available.
+	rand.seed([u32(3155200429), u32(3208395956)])
+	mut generator := noise.Generator.new()
+	generator.randomize()
+
+	mut x := []f64{}
+	mut y := []f64{}
+	mut z := []f64{}
+
+	// 5 layers of simplex noise
+	octaves := 5
+	persistence := 0.5
+
+	for xx in 0 .. 200 {
+		for yy in 0 .. 200 {
+			mut total := 0.0
+			mut frequency := 1.0
+			mut amplitude := 1.0
+			mut max_value := 0.0
+
+			for _ in 0 .. octaves {
+				total += generator.simplex_2d(0.03 * xx * frequency, 0.03 * yy * frequency) * amplitude
+				max_value += amplitude
+				amplitude *= persistence
+				frequency *= 2.0
+			}
+
+			// Normalize to [-1, 1]
+			total /= max_value
+			x << xx
+			y << yy
+			z << total
+		}
+	}
+
+	mut plt := plot.Plot.new()
+	plt.heatmap(
+		x: x
+		y: y
+		z: z
+	)
+	plt.layout(
+		title: 'Pink `fractal` noise 2d example'
+	)
+	plt.show()!
+}
diff --git a/examples/noise_simplex_2d/README.md b/examples/noise_simplex_2d/README.md
@@ -0,0 +1,16 @@
+# Example - noise_simple_2d 📘
+
+This example demonstrates the usage of the V Scientific Library for generating simplex noise.
+
+## Instructions
+
+1. Ensure you have the V compiler installed. You can download it from [here](https://vlang.io).
+2. Ensure you have the VSL installed. You can do it following the [installation guide](https://github.com/vlang/vsl?tab=readme-ov-file#-installation)!
+3. Navigate to this directory.
+4. Run the example using the following command:
+
+```sh
+v run main.v
+```
+
+Enjoy exploring the capabilities of the V Scientific Library! 😊
diff --git a/examples/noise_simplex_2d/main.v b/examples/noise_simplex_2d/main.v
@@ -0,0 +1,38 @@
+module main
+
+import rand
+import vsl.noise
+import vsl.plot
+
+fn main() {
+	// Creation of the noise generator.
+	// Other noise functions and dimensions count are available.
+	rand.seed([u32(3155200429), u32(3208395956)])
+	mut generator := noise.Generator.new()
+	generator.randomize()
+
+	mut x := []f64{}
+	mut y := []f64{}
+	mut z := []f64{}
+
+	for xx in 0 .. 40 {
+		for yy in 0 .. 40 {
+			// We need to scale the coordinates to control the frequency of the noise.
+			val := generator.simplex_2d(0.03 * xx, 0.03 * yy)
+			x << xx
+			y << yy
+			z << val
+		}
+	}
+
+	mut plt := plot.Plot.new()
+	plt.heatmap(
+		x: x
+		y: y
+		z: z
+	)
+	plt.layout(
+		title: 'Simplex noise 2d example'
+	)
+	plt.show()!
+}
diff --git a/noise/noise.v b/noise/noise.v
@@ -0,0 +1,20 @@
+module noise
+
+import rand
+
+// Generator is a struct holding the permutation table used in perlin and simplex noise
+pub struct Generator {
+mut:
+	perm []int = rand.shuffle_clone(permutations) or { panic(err) }
+}
+
+// new is a function that return a new Generator struct
+pub fn Generator.new() Generator {
+	return Generator{}
+}
+
+// randomize is a function that shuffle the permutation set inside the Generator struct
+// will not shuffle if rand.seed is not changed
+pub fn (mut generator Generator) randomize() {
+	generator.perm = rand.shuffle_clone(permutations) or { panic(err) }
+}
diff --git a/noise/perlin2d.v b/noise/perlin2d.v
@@ -1,26 +1,7 @@
 module noise
 
-import rand
-
-// Perlin is a struct that hold the permutation set for perlin noise
-pub struct Perlin {
-mut:
-	perm []int = rand.shuffle_clone(permutations) or { panic(err) }
-}
-
-// new is a function that return a new Perlin struct
-pub fn Perlin.new() Perlin {
-	return Perlin{}
-}
-
-// randomize is a function that shuffle the permutation set inside the Perlin struct
-// will not shuffle if rand.seed is not changed
-pub fn (mut perlin Perlin) randomize() {
-	perlin.perm = rand.shuffle_clone(permutations) or { panic(err) }
-}
-
 // perlin2d is a function that return a single value of perlin noise for a given 2d position
-pub fn (perlin Perlin) perlin2d(x f64, y f64) f64 {
+pub fn (generator Generator) perlin2d(x f64, y f64) f64 {
 	xi := int(x) & 0xFF
 	yi := int(y) & 0xFF
 
@@ -30,13 +11,13 @@ pub fn (perlin Perlin) perlin2d(x f64, y f64) f64 {
 	u := fade(xf)
 	v := fade(yf)
 
-	pxi := perlin.perm[xi]
-	pxi1 := perlin.perm[xi + 1]
+	pxi := generator.perm[xi]
+	pxi1 := generator.perm[xi + 1]
 
-	aa := perlin.perm[pxi + yi]
-	ab := perlin.perm[pxi + yi + 1]
-	ba := perlin.perm[pxi1 + yi]
-	bb := perlin.perm[pxi1 + yi + 1]
+	aa := generator.perm[pxi + yi]
+	ab := generator.perm[pxi + yi + 1]
+	ba := generator.perm[pxi1 + yi]
+	bb := generator.perm[pxi1 + yi + 1]
 
 	x1 := lerp(grad2d(aa, xf, yf), grad2d(ba, xf - 1, yf), u)
 	x2 := lerp(grad2d(ab, xf, yf - 1), grad2d(bb, xf - 1, yf - 1), u)

diff --git a/noise/perlin2d_test.v b/noise/perlin2d_test.v
@@ -6,7 +6,7 @@ import vsl.float.float64
 fn test_perlin2d() {
 	rand.seed([u32(3155200429), u32(3208395956)])
 
-	mut gen := Perlin.new()
+	mut gen := Generator.new()
 	gen.randomize()
 
 	result := gen.perlin2d(0.125, 0.125)

diff --git a/noise/perlin3d.v b/noise/perlin3d.v
@@ -1,7 +1,7 @@
 module noise
 
 // perlin3d is a function that return a single value of perlin noise for a given 3d position
-pub fn (perlin Perlin) perlin3d(x f64, y f64, z f64) f64 {
+pub fn (generator Generator) perlin3d(x f64, y f64, z f64) f64 {
 	xi := int(x) & 0xFF
 	yi := int(y) & 0xFF
 	zi := int(z) & 0xFF
@@ -12,21 +12,21 @@ pub fn (perlin Perlin) perlin3d(x f64, y f64, z f64) f64 {
 	v := fade(yf)
 	w := fade(zf)
 
-	pxi := perlin.perm[xi]
-	pxi_yi := perlin.perm[pxi + yi]
-	pxi_yi1 := perlin.perm[pxi + yi + 1]
-	pxi1 := perlin.perm[xi + 1]
-	pxi1_yi := perlin.perm[pxi1 + yi]
-	pxi1_yi1 := perlin.perm[pxi1 + yi + 1]
+	pxi := generator.perm[xi]
+	pxi_yi := generator.perm[pxi + yi]
+	pxi_yi1 := generator.perm[pxi + yi + 1]
+	pxi1 := generator.perm[xi + 1]
+	pxi1_yi := generator.perm[pxi1 + yi]
+	pxi1_yi1 := generator.perm[pxi1 + yi + 1]
 
-	aaa := perlin.perm[pxi_yi + zi]
-	aba := perlin.perm[pxi_yi1 + zi]
-	aab := perlin.perm[pxi_yi + zi + 1]
-	abb := perlin.perm[pxi_yi1 + zi + 1]
-	baa := perlin.perm[pxi1_yi + zi]
-	bba := perlin.perm[pxi1_yi1 + zi]
-	bab := perlin.perm[pxi1_yi + zi + 1]
-	bbb := perlin.perm[pxi1_yi1 + zi + 1]
+	aaa := generator.perm[pxi_yi + zi]
+	aba := generator.perm[pxi_yi1 + zi]
+	aab := generator.perm[pxi_yi + zi + 1]
+	abb := generator.perm[pxi_yi1 + zi + 1]
+	baa := generator.perm[pxi1_yi + zi]
+	bba := generator.perm[pxi1_yi1 + zi]
+	bab := generator.perm[pxi1_yi + zi + 1]
+	bbb := generator.perm[pxi1_yi1 + zi + 1]
 
 	mut x1 := lerp(grad3d(aaa, xf, yf, zf), grad3d(baa, xf - 1, yf, zf), u)
 	mut x2 := lerp(grad3d(aba, xf, yf - 1, zf), grad3d(bba, xf - 1, yf - 1, zf), u)

diff --git a/noise/perlin3d_test.v b/noise/perlin3d_test.v
@@ -6,7 +6,7 @@ import vsl.float.float64
 fn test_perlin3d() {
 	rand.seed([u32(3155200429), u32(3208395956)])
 
-	mut gen := Perlin.new()
+	mut gen := Generator.new()
 	gen.randomize()
 
 	result := gen.perlin3d(0.125, 0.125, 0.125)