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