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Specialized node for generating natural, fractal-like noise patterns with organic appearance for AI artists.
Power-Law Noise (PPF Noise) is a specialized node designed to generate noise patterns based on the power-law distribution, which is often used in various fields such as physics, biology, and economics to model phenomena with heavy-tailed distributions. This node is particularly useful for AI artists looking to create textures and patterns that exhibit natural, fractal-like characteristics. By leveraging the power-law distribution, the node can produce noise that has a more organic and less uniform appearance compared to traditional noise functions. This can be beneficial for creating more realistic and visually appealing textures in digital art and procedural content generation.
The width parameter specifies the width of the generated noise pattern. It determines how many pixels wide the noise texture will be. This parameter is crucial for defining the resolution of the noise and can impact the level of detail in the generated pattern. The value should be a positive integer, with higher values resulting in more detailed noise textures.
The height parameter specifies the height of the generated noise pattern. Similar to the width parameter, it determines how many pixels tall the noise texture will be. This parameter is essential for defining the resolution of the noise and can impact the level of detail in the generated pattern. The value should be a positive integer, with higher values resulting in more detailed noise textures.
The noise_type parameter defines the type of noise to be generated. Different noise types can produce varying visual effects, and selecting the appropriate type can significantly influence the final appearance of the noise pattern. Common options include "white noise," "pink noise," and "brown noise," each with distinct characteristics.
The alpha_exp parameter controls the exponent of the power-law distribution. This parameter affects the distribution of noise values, with higher values resulting in a more pronounced heavy-tailed distribution. Adjusting this parameter can help fine-tune the visual characteristics of the noise pattern, making it more or less uniform.
The range_scale parameter determines the scaling factor for the noise values. This parameter can be used to adjust the overall intensity and contrast of the noise pattern. Higher values will amplify the noise, making it more prominent, while lower values will produce a subtler effect.
The modulator parameter allows for additional modulation of the noise pattern. This can be used to introduce variations and complexity into the noise, creating more intricate and interesting textures. The specific function of the modulator can vary depending on the implementation.
The seed parameter sets the random seed for noise generation. By specifying a seed value, you can ensure that the same noise pattern is generated consistently across different runs. This is useful for reproducibility and for creating specific, repeatable noise effects.
The noise output parameter contains the generated noise pattern as a tensor. This tensor can be used directly in various applications, such as texture generation, procedural content creation, or as an input to other nodes in a processing pipeline. The noise tensor's dimensions will match the specified width and height parameters, and its values will be influenced by the other input parameters.
alpha_exp
values to achieve the desired level of detail and distribution in your noise patterns.seed
parameter to generate consistent noise patterns for reproducible results.range_scale
parameter to control the intensity and contrast of the noise, making it suitable for various artistic applications.© Copyright 2024 RunComfy. All Rights Reserved.