C# 有没有更有效的方法来计算和使用柏林噪声?
我几天前才开始使用柏林噪音,效果看起来相当不错。但是,计算并绘制所述噪声的1024x1024位图需要3秒钟以上。我使用1024x1024数组来存储范围从-1到1的int32 创建柏林噪波阵列的代码:C# 有没有更有效的方法来计算和使用柏林噪声?,c#,noise,perlin-noise,C#,Noise,Perlin Noise,我几天前才开始使用柏林噪音,效果看起来相当不错。但是,计算并绘制所述噪声的1024x1024位图需要3秒钟以上。我使用1024x1024数组来存储范围从-1到1的int32 创建柏林噪波阵列的代码: private void button1_Click(object sender, EventArgs e) { sw.Start(); LibNoise.Perlin perlinMap = new LibNoise.Perlin(); p
private void button1_Click(object sender, EventArgs e)
{
sw.Start();
LibNoise.Perlin perlinMap = new LibNoise.Perlin();
perlinMap.Lacunarity = lacunarity + 0.01d;
perlinMap.NoiseQuality = LibNoise.NoiseQuality.High;
perlinMap.OctaveCount = octaveCount;
perlinMap.Persistence = persistence;
perlinMap.Frequency = frequency;
perlinMap.Seed = 1024;
if (radioButton1.Checked)
perlinMap.NoiseQuality = LibNoise.NoiseQuality.Low;
else if (radioButton2.Checked)
perlinMap.NoiseQuality = LibNoise.NoiseQuality.Standard;
else if (radioButton3.Checked)
perlinMap.NoiseQuality = LibNoise.NoiseQuality.High;
double sample = trackBar6.Value * 10;
double[,] perlinArray = new double[resolutieX, resolutieY];
for (int x = 0; x < resolutieX; x++)
{
for (int y = 0; y < resolutieY; y++)
{
perlinArray[x, y] = perlinMap.GetValue(x / sample, y / sample, 1d);
}
}
draw(perlinArray);
textBox12.Text = sw.ElapsedMilliseconds.ToString() + "ms";
sw.Reset();
}
public void draw(double[,] array)
{
Bitmap afbeelding = new Bitmap(1024, 1024);
Color color;
int tileSize = 1024 / resolutieY;
for (int y = 1; y < resolutieY; y++)
{
for (int x = 1; x < resolutieX; x++)
{
if (array[x, y] <= -0.2)
color = Color.DarkBlue;
if (array[x, y] <= 0)
color = Color.DarkBlue;
else if (array[x, y] <= 0.1)
color = Color.Blue;
else if (array[x, y] <= 0.2)
color = Color.Beige;
else if (array[x, y] <= 0.22)
color = Color.LightGreen;
else if (array[x, y] <= 0.40)
color = Color.Green;
else if (array[x, y] <= 0.75)
color = Color.DarkGreen;
else if (array[x, y] <= 0.8)
color = Color.LightSlateGray;
else if (array[x, y] <= 0.9)
color = Color.Gray;
else if (array[x, y] <= 1)
color = Color.DarkSlateGray;
else
color = Color.DarkSlateGray;
// color = Color.FromArgb(255);
for (int i = 0; i < tileSize; i++)
{
for (int j = 0; j < tileSize; j++)
{
afbeelding.SetPixel(((x - 1) * tileSize) + i, ((y - 1) * tileSize) + j, color);
}
}
}
}
pictureBox1.Image = afbeelding;
}
private void按钮1\u单击(对象发送者,事件参数e)
{
sw.Start();
LibNoise.Perlin perlinMap=新LibNoise.Perlin();
perlinMap.空隙率=空隙率+0.01d;
perlinMap.noiseequality=LibNoise.noiseequality.High;
perlinMap.OctaveCount=OctaveCount;
perlinMap.Persistence=Persistence;
perlinMap.频率=频率;
perlinMap.Seed=1024;
如果(radioButton1.选中)
perlinMap.noiseequality=LibNoise.noiseequality.Low;
否则如果(radioButton2.选中)
perlinMap.noiseequality=LibNoise.noiseequality.Standard;
否则如果(radioButton3.选中)
perlinMap.noiseequality=LibNoise.noiseequality.High;
双样本=trackBar6.值*10;
double[,]perlinArray=新的double[Resolutionex,Resolutiony];
对于(int x=0;x
绘制柏林噪波的代码:
private void button1_Click(object sender, EventArgs e)
{
sw.Start();
LibNoise.Perlin perlinMap = new LibNoise.Perlin();
perlinMap.Lacunarity = lacunarity + 0.01d;
perlinMap.NoiseQuality = LibNoise.NoiseQuality.High;
perlinMap.OctaveCount = octaveCount;
perlinMap.Persistence = persistence;
perlinMap.Frequency = frequency;
perlinMap.Seed = 1024;
if (radioButton1.Checked)
perlinMap.NoiseQuality = LibNoise.NoiseQuality.Low;
else if (radioButton2.Checked)
perlinMap.NoiseQuality = LibNoise.NoiseQuality.Standard;
else if (radioButton3.Checked)
perlinMap.NoiseQuality = LibNoise.NoiseQuality.High;
double sample = trackBar6.Value * 10;
double[,] perlinArray = new double[resolutieX, resolutieY];
for (int x = 0; x < resolutieX; x++)
{
for (int y = 0; y < resolutieY; y++)
{
perlinArray[x, y] = perlinMap.GetValue(x / sample, y / sample, 1d);
}
}
draw(perlinArray);
textBox12.Text = sw.ElapsedMilliseconds.ToString() + "ms";
sw.Reset();
}
public void draw(double[,] array)
{
Bitmap afbeelding = new Bitmap(1024, 1024);
Color color;
int tileSize = 1024 / resolutieY;
for (int y = 1; y < resolutieY; y++)
{
for (int x = 1; x < resolutieX; x++)
{
if (array[x, y] <= -0.2)
color = Color.DarkBlue;
if (array[x, y] <= 0)
color = Color.DarkBlue;
else if (array[x, y] <= 0.1)
color = Color.Blue;
else if (array[x, y] <= 0.2)
color = Color.Beige;
else if (array[x, y] <= 0.22)
color = Color.LightGreen;
else if (array[x, y] <= 0.40)
color = Color.Green;
else if (array[x, y] <= 0.75)
color = Color.DarkGreen;
else if (array[x, y] <= 0.8)
color = Color.LightSlateGray;
else if (array[x, y] <= 0.9)
color = Color.Gray;
else if (array[x, y] <= 1)
color = Color.DarkSlateGray;
else
color = Color.DarkSlateGray;
// color = Color.FromArgb(255);
for (int i = 0; i < tileSize; i++)
{
for (int j = 0; j < tileSize; j++)
{
afbeelding.SetPixel(((x - 1) * tileSize) + i, ((y - 1) * tileSize) + j, color);
}
}
}
}
pictureBox1.Image = afbeelding;
}
public void draw(双[,]数组)
{
位图afbeelding=新位图(10241024);
颜色;
int tileSize=1024/分辨率;
对于(int y=1;y
并确保在没有附加调试器的情况下以发布模式运行代码。这两种情况都会显著影响性能
单纯形噪声在这里没有帮助,因为它在更高的维度上获得了性能。二维噪声可能没有任何性能增益
计算和使用
这是两种截然不同的野兽,每一种都有许多不同的方法。
通过在数据结构中存储柏林噪声或任何昂贵的隐式计算的结果,可以节省大量时间。
如果您想在应用程序中保持适当的帧速率,即使在现代硬件上实时评估噪声也不是一个好主意,因为它会消耗大量的处理资源。一旦存储在数据结构中,您可以将处理过程简化为对该结构的简单访问,而该结构的访问成本要低得多,并且通常可以为您提供b确认大部分处理预算。最有可能的是SetPixel
是您的瓶颈。查看c#中不安全的位图编辑。这个问题似乎离题了,因为它是关于提高工作代码的性能。请改为询问您的问题。您的代码与柏林噪声无关。@Ephoric添加了柏林噪声它一定是柏林噪声吗?因为你可以用单纯形噪声得到类似的结果,但它更容易计算