"""Multiple profiles — extract and compare profiles from multiple images.""" from __future__ import annotations import numpy as np from backend.node_registry import register_node from backend.data_types import DataField, LineData @register_node(display_name="Multiple Profiles") class MultipleProfiles: @classmethod def INPUT_TYPES(cls): return { "required": { "field_a": ("DATA_FIELD",), "field_b": ("DATA_FIELD",), "row": ("INT", {"default": -1, "min": -1, "max": 10000, "step": 1}), "direction": (["horizontal", "vertical"], {"default": "horizontal"}), "mode": (["overlay", "mean", "difference"], {"default": "overlay"}), } } OUTPUTS = ( ('LINE_DATA', 'profile'), ) FUNCTION = "process" DESCRIPTION = ( "Extract and compare line profiles from two fields. " "Row=-1 uses the center row/column. Modes: overlay returns field_a's " "profile, mean averages both, difference subtracts b from a. " ) def process(self, field_a: DataField, field_b: DataField, row: int, direction: str, mode: str) -> tuple: a = np.asarray(field_a.data, dtype=np.float64) b = np.asarray(field_b.data, dtype=np.float64) if direction == "horizontal": if row < 0: row = a.shape[0] // 2 row = min(row, a.shape[0] - 1, b.shape[0] - 1) pa = a[row, :] pb = b[row, :min(a.shape[1], b.shape[1])] pa = pa[:len(pb)] dx = field_a.dx x_unit = field_a.si_unit_xy else: if row < 0: row = a.shape[1] // 2 row = min(row, a.shape[1] - 1, b.shape[1] - 1) pa = a[:, row] pb = b[:min(a.shape[0], b.shape[0]), row] pa = pa[:len(pb)] dx = field_a.dy x_unit = field_a.si_unit_xy x_axis = np.arange(len(pa)) * dx if mode == "overlay": result = pa elif mode == "mean": result = 0.5 * (pa + pb) elif mode == "difference": result = pa - pb else: result = pa return (LineData(data=result, x_axis=x_axis, x_unit=x_unit, y_unit=field_a.si_unit_z),)