Files
tono/backend/nodes/level_plane.py

72 lines
2.1 KiB
Python

from __future__ import annotations
import numpy as np
from backend.node_registry import register_node
from backend.data_types import DataField
from backend.nodes.helpers import normalize_mask, apply_masking
def _fit_plane(
data: np.ndarray,
mask: np.ndarray | None,
masking: str,
) -> tuple[float, float, float, np.ndarray, np.ndarray]:
yres, xres = data.shape
x = np.linspace(0.0, 1.0, xres)
y = np.linspace(0.0, 1.0, yres)
xx, yy = np.meshgrid(x, y)
valid = apply_masking(data, mask, masking)
if np.count_nonzero(valid) < 3:
raise ValueError("Plane Level requires at least three usable pixels for fitting.")
A = np.column_stack([
np.ones(int(np.count_nonzero(valid)), dtype=np.float64),
xx[valid].ravel(),
yy[valid].ravel(),
])
z = data[valid].ravel()
coeffs, _, _, _ = np.linalg.lstsq(A, z, rcond=None)
pa, pbx, pby = coeffs
return float(pa), float(pbx), float(pby), xx, yy
@register_node(display_name="Plane Level")
class PlaneLevelField:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"field": ("DATA_FIELD",),
"masking": (["ignore", "include", "exclude"], {"default": "ignore"}),
},
"optional": {
"mask": ("IMAGE",),
},
}
OUTPUTS = (
('DATA_FIELD', 'leveled'),
)
FUNCTION = "process"
DESCRIPTION = (
"Fit and subtract a least-squares plane from the data. Supports include/exclude mask fitting "
"for flattening around features, similar to masked plane fitting workflows in Gwyddion."
)
KEYWORDS = ("flatten", "tilt", "background")
def process(
self,
field: DataField,
masking: str = "ignore",
mask: np.ndarray | None = None,
) -> tuple:
data = field.data.copy()
mask_array = normalize_mask(mask, data.shape)
pa, pbx, pby, xx, yy = _fit_plane(data, mask_array, masking)
plane = (pa + pbx * xx + pby * yy)
return (field.replace(data=data - plane),)