ComfyUI Node: 🧪 Laboratory

Laboratory [Dream]:

The Laboratory [Dream] node is a versatile utility designed to generate and manage random values within specified ranges and policies, making it an essential tool for AI artists looking to introduce controlled randomness into their projects. This node allows you to define a key, seed, and various parameters to produce values that can be used in different creative processes. The node's primary function is to generate a new value based on the given parameters or reuse a previously generated value depending on the specified renewal policy. This capability is particularly useful for creating dynamic and varied outputs in generative art, ensuring that each frame or iteration can have unique characteristics while still adhering to defined constraints.

Laboratory [Dream] Input Parameters:

key

This parameter is a string that serves as an identifier for the generated value. It allows you to reference and reuse the value in subsequent operations. The default value is a randomly generated string.

seed

The seed is an integer used to initialize the random number generator, ensuring reproducibility of the generated values. The default value is 0, and it can range from 0 to 0xffffffffffffffff.

renew_policy

This parameter determines when a new value should be generated. It can be set to every frame to generate a new value for each frame or first frame to generate a value only for the first frame and reuse it for subsequent frames.

min_value

This is the minimum value for the generated random number. It is a floating-point number with a default value of 0.0.

max_value

This is the maximum value for the generated random number. It is a floating-point number with a default value of 1.0.

mode

The mode parameter defines the distribution or pattern of the generated values. It can be set to random uniform, random bell, ladder, or random walk, each providing a different method of value generation.

step_size (optional)

This optional parameter specifies the step size for the ladder and random walk modes. It is a floating-point number with a default value of 0.1.

Laboratory [Dream] Output Parameters:

FLOAT

This output is the generated floating-point value based on the specified parameters. It represents the main result of the node's operation.

INT

This output is the integer representation of the generated floating-point value, providing a rounded version of the FLOAT output.

log_entry

This output is a log entry that records the details of the generated value, including the key and the generated FLOAT and INT values. It is useful for tracking and debugging purposes.

Laboratory [Dream] Usage Tips:

• Use the seed parameter to ensure reproducibility of your random values, which is particularly useful when you need consistent results across different runs.
• Experiment with different renew_policy settings to see how generating new values every frame versus only on the first frame affects your project.
• Adjust the min_value and max_value parameters to control the range of your random values, tailoring them to fit the specific needs of your project.
• Try different mode settings to explore various patterns of randomness, such as uniform distribution or random walks, to add unique characteristics to your generative art.

Laboratory [Dream] Common Errors and Solutions:

min_value is greater than max_value

• Explanation: This error occurs when the minimum value is set higher than the maximum value, which is not logically valid for generating random numbers.
• Solution: Ensure that the min_value is always less than or equal to the max_value. If necessary, swap the values to correct the order.

Invalid renew_policy setting

• Explanation: This error happens when an unsupported value is provided for the renew_policy parameter.
• Solution: Use only the supported values every frame or first frame for the renew_policy parameter.

Missing key parameter

• Explanation: This error occurs when the key parameter is not provided, which is required to identify the generated value.
• Solution: Always provide a unique string for the key parameter to ensure proper identification and reuse of the generated value.