Noise generator based on Open Simplex. This resource allows you to configure and sample a fractal noise space. Here is a brief usage example that configures an OpenSimplexNoise and gets samples at various positions and dimensions: [codeblock] var noise = OpenSimplexNoise.new() # Configure noise.seed = randi() noise.octaves = 4 noise.period = 20.0 noise.persistence = 0.8 # Sample print("Values:") print(noise.get_noise_2d(1.0, 1.0)) print(noise.get_noise_3d(0.5, 3.0, 15.0)) print(noise.get_noise_4d(0.5, 1.9, 4.7, 0.0)) [/codeblock] Generate a noise image with the requested [code]width[/code] and [code]height[/code], based on the current noise parameters. Returns the 1D noise value [code][-1,1][/code] at the given x-coordinate. [b]Note:[/b] This method actually returns the 2D noise value [code][-1,1][/code] with fixed y-coordinate value 0.0. Returns the 2D noise value [code][-1,1][/code] at the given position. Returns the 2D noise value [code][-1,1][/code] at the given position. Returns the 3D noise value [code][-1,1][/code] at the given position. Returns the 3D noise value [code][-1,1][/code] at the given position. Returns the 4D noise value [code][-1,1][/code] at the given position. Generate a tileable noise image, based on the current noise parameters. Generated seamless images are always square ([code]size[/code] × [code]size[/code]). Difference in period between [member octaves]. Number of OpenSimplex noise layers that are sampled to get the fractal noise. Period of the base octave. A lower period results in a higher-frequency noise (more value changes across the same distance). Contribution factor of the different octaves. A [code]persistence[/code] value of 1 means all the octaves have the same contribution, a value of 0.5 means each octave contributes half as much as the previous one. Seed used to generate random values, different seeds will generate different noise maps.