EasyUse¶

Documentation¶

Class name: easy XYInputs: PositiveCond
Category: EasyUse/XY Inputs
Output node: False

This node is designed to process positive conditioning inputs for XY plotting, allowing users to specify conditions that influence the plotting axis and values based on positive scenarios. It abstracts the complexity of handling conditional logic for positive inputs, facilitating the creation of customized plots that reflect specific positive conditions.

Input types¶

Optional¶

positive_i
- Represents a positive condition to be applied, where 'i' can range from 1 to 4. Each condition incrementally modifies the plot's axis and values, enhancing the plot's specificity and allowing for a layered approach to customizing the plot's appearance based on positive scenarios.
- Comfy dtype: CONDITIONING
- Python dtype: Optional[str]

Output types¶

X or Y
- Comfy dtype: X_Y
- Outputs the configured axis and values for the plot, reflecting the applied positive conditions. This output demonstrates the flexibility in choosing either the X or Y axis based on the conditions applied, providing a tailored plotting experience.
- Python dtype: Tuple[Dict[str, Any]]

Usage tips¶

Infra type: CPU
Common nodes: unknown

Source code¶

class XYplot_Positive_Cond:

    @classmethod
    def INPUT_TYPES(cls):
        inputs = {
            "optional": {
                "positive_1": ("CONDITIONING",),
                "positive_2": ("CONDITIONING",),
                "positive_3": ("CONDITIONING",),
                "positive_4": ("CONDITIONING",),
            }
        }

        return inputs

    RETURN_TYPES = ("X_Y",)
    RETURN_NAMES = ("X or Y",)
    FUNCTION = "xy_value"
    CATEGORY = "EasyUse/XY Inputs"

    def xy_value(self, positive_1=None, positive_2=None, positive_3=None, positive_4=None):
        axis = "advanced: Pos Condition"
        values = []
        cond = []
        # Create base entry
        if positive_1 is not None:
            values.append("0")
            cond.append(positive_1)
        if positive_2 is not None:
            values.append("1")
            cond.append(positive_2)
        if positive_3 is not None:
            values.append("2")
            cond.append(positive_3)
        if positive_4 is not None:
            values.append("3")
            cond.append(positive_4)

        return ({"axis": axis, "values": values, "cond": cond},) if values is not None else (None,)