英文:
Chunks not connected
问题
这是我的代码：
def generate(octaves):全局变量 world, xpix, chunkSize # 设置全局变量（用于脚本的其余部分中的其他引用等）chunkSize = (12, 12)xpix, ypix = chunkSize[0], chunkSize[1]world = []noise1 = PerlinNoise(octaves=octaves, seed=seed) # 生成噪声for i in range(xpix): # 生成用于绘制的列表行 = []for j in range(ypix):noise_val = noise1([(i / xpix) + chunkCoordX * xpix, (j / ypix) + chunkCoordY * ypix])if noise_val <= .05:tiletoplace = tileclassdata.waterelif noise_val <= .13:tiletoplace = tileclassdata.sandelse:tiletoplace = tileclassdata.grassplaced_tile = classes.tile(tiletoplace, i, j)行.append(placed_tile)world.append(行)
我正在尝试使我生成的区块连接起来。例如：
我可以在1,-4处有一个区块，在0,-4处有一个区块。但它们会是这个样子的：
我希望它们连接起来，这样我就可以获得诸如岛屿之类的东西，而不仅仅是在我的游戏地图中随机散布的斑点。
我尝试重构求解柏林噪声地图中区块位置的总和，但我还没有能够设计出一个能解决这个问题的总和。
英文:
Here is my code:
def generate(octaves):global world, xpix, chunkSize #set globals (for other references in the rest of the script etc)chunkSize = (12, 12)xpix, ypix = chunkSize[0], chunkSize[1]world = []noise1 = PerlinNoise(octaves=octaves, seed=seed) #make noisefor i in range(xpix): # make list for drawer to userow = []for j in range(ypix):noise_val = noise1([(i / xpix) + chunkCoordX * xpix, (j / ypix) + chunkCoordY * ypix])if noise_val <= .05:tiletoplace = tileclassdata.waterelif noise_val <= .13:tiletoplace = tileclassdata.sandelse:tiletoplace = tileclassdata.grassplaced_tile = classes.tile(tiletoplace, i, j)row.append(placed_tile)world.append(row)
I am trying to make the chunks I generate connect. For example:
I could have a chunk at 1,-4 and one at 0,-4. But this is what they'd look like:
I would like them to connect so that I can get things like islands generating across chunks instead of just have random blobs scattered around my game's map.
I have tried refactoring the sum for working out the chunks position in the perlin-noise map but I have not been able to devise a sum that figures it out.
答案1
得分: 0
以下是代码部分的翻译：
import numpy as npfrom scipy import ndimageimport seaborn as snsdef generate_landscape(field_size: int, flatness: int, magnitude=255):""" 生成一个类似岛屿的地形，给定参数:Args:field_size: 结果numpy数组的大小flatness: 很大的数字将导致完全平坦的地形；1将导致每个点都随机绘制"""field = np.random.binomial(1, 1 / flatness, size=(field_size, field_size)) \* np.random.randint(low=0, high=magnitude, size=(field_size, field_size))mask_size = max(int(flatness ** 0.5), 1)return ndimage.gaussian_filter(field, mask_size)sns.heatmap(generate_landscape(32, 10))
请注意，代码部分中的 HTML 实体 """ 已被保留，以确保代码的完整性。
英文:
Quick and dirty example of the idea in the comments:
import numpy as npfrom scipy import ndimageimport seaborn as snsdef generate_landscape(field_size: int, flatness: int, magnitude=255):""" Generates an islandish landscape, given:Args:field_size: size of the resulting numpy arrayflatness: very large number will result in a completely flat terrain;1 will result in every spot being drawn at random"""field = np.random.binomial(1, 1 / flatness, size=(field_size, field_size)) \* np.random.randint(low=0, high=magnitude, size=(field_size, field_size))mask_size = max(int(flatness ** 0.5), 1)return ndimage.gaussian_filter(field, mask_size)sns.heatmap(generate_landscape(32, 10))
Example output:
After that, I'd take a desired water/sand %%, calculate quantiles and apply the threshold.
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