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Refine sigma values by removing those below a specified threshold for data cleaning and integrity maintenance.
The Sigmas DeleteBelowFloor node is designed to refine a sequence of sigma values by removing any values that fall below a specified threshold, known as the "floor." This node is particularly useful in scenarios where you need to ensure that all sigma values meet a minimum requirement, which can be crucial for maintaining the integrity of certain processes or calculations. By filtering out values that do not meet the minimum threshold, the node helps in cleaning up the data, ensuring that only relevant and significant sigma values are retained for further processing. This can be especially beneficial in applications where sigma values represent certain statistical or probabilistic measures, and maintaining a certain level of these values is necessary for accurate results.
The sigmas
parameter represents the sequence of sigma values that you want to process. This input is mandatory, as the node needs these values to perform the filtering operation. The sigmas
are typically a series of numerical values that may represent statistical measures or other relevant data points in your workflow. The node will evaluate each of these values against the specified floor to determine which values should be retained.
The floor
parameter is a floating-point number that sets the minimum threshold for the sigma values. Any sigma value below this threshold will be removed from the sequence. The default value for the floor is 0.0291675, but you can adjust it to any value between -10000 and 10000, with a step size of 0.01. This flexibility allows you to tailor the filtering process to your specific needs, ensuring that only sigma values above a certain level are considered in your analysis or processing.
The output parameter, SIGMAS
, is the filtered sequence of sigma values. After processing, this output will contain only those sigma values that are equal to or greater than the specified floor. This refined sequence can then be used in subsequent nodes or processes, ensuring that only the most relevant and significant sigma values are included. This output is crucial for maintaining the quality and accuracy of your data analysis or processing tasks.
floor
parameter to match the minimum significance level required for your specific application. This ensures that only meaningful sigma values are retained.sigmas
input is not supplied to the node.floor
parameter is set outside the allowed range of -10000 to 10000.floor
parameter to fall within the specified range, ensuring it is a valid floating-point number.RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Playground, enabling artists to harness the latest AI tools to create incredible art.