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Apply lag effect to float values for smoothing transitions in data processing, enhancing fluidity and coherence.
The AK_LagChop node is designed to apply a lag effect to a sequence of float values, which can be particularly useful in audio processing or any scenario where smoothing or gradual transitions are desired. This node takes an input list of float values and processes them to create an output list where each value is influenced by its predecessor, creating a lagging effect. The primary benefit of using this node is its ability to smooth out abrupt changes in data, making transitions appear more natural and less jarring. This is achieved by adjusting each value in the list based on a specified lag factor, which determines the degree to which the output lags behind the input. The AK_LagChop node is an essential tool for artists and developers looking to introduce subtle, controlled variations in their data streams, enhancing the overall fluidity and coherence of their projects.
The float_list
parameter is a list of float values that serves as the input data for the node. This list represents the sequence of values to which the lag effect will be applied. The function of this parameter is to provide the raw data that will be processed by the node. The impact of this parameter on the node's execution is direct, as it determines the initial values that will be transformed into a lagged sequence. There are no specific minimum, maximum, or default values for this parameter, as it is entirely dependent on the user's input data.
The lag_factor
parameter is a float value that controls the degree of lag applied to the input list. It determines how much the output values will lag behind the input values, with a range between 0.0 and 1.0. The minimum value is just above 0.0, and the maximum value is 1.0, with a default value of 0.5. A higher lag factor results in a more pronounced lag effect, meaning the output values will change more slowly in response to changes in the input values. Conversely, a lower lag factor will result in a quicker response to input changes. This parameter is crucial for fine-tuning the smoothness and responsiveness of the output data.
The output_list
is the primary output of the AK_LagChop node, consisting of a list of float values that have been processed to include the lag effect. Each value in this list is calculated based on the previous output value and the current input value, adjusted by the lag factor. The importance of this output lies in its ability to provide a smoothed version of the input data, which can be used in various applications where gradual transitions are preferred. The interpretation of the output values is straightforward: they represent the lagged version of the input list, with each value reflecting the influence of its predecessor and the specified lag factor.
lag_factor
parameter is set to a value outside the allowed range of greater than 0 and less than or equal to 1.lag_factor
is set to a value within the specified range. Adjust the value to be greater than 0 and less than or equal to 1 to resolve this error.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.