46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
from __future__ import annotations
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import numpy as np
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from scipy.ndimage import grey_erosion
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from backend.node_registry import register_node
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from backend.data_types import DataField
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@register_node(display_name="Tip Deconvolution")
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class TipDeconvolution:
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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": ("DATA_FIELD",),
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"tip": ("DATA_FIELD",),
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}
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}
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OUTPUTS = (
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('DATA_FIELD', 'surface'),
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)
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FUNCTION = "process"
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DESCRIPTION = (
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"Reconstruct the true surface from a tip-broadened measured image. "
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"Uses morphological grey erosion (Villarrubia algorithm): "
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" mytip = flip(tip) - max(flip(tip)) [max shifted to 0] "
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" surface[y,x] = min_{dy,dx}[image[y+dy, x+dx] - mytip[dy,dx]] "
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"Connect the tip output from a TipModel node. "
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"The tip pixel size must match the image pixel size. "
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)
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KEYWORDS = ("erosion", "morphology", "villarrubia", "surface reconstruction", "apex", "deblur")
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def process(self, field: DataField, tip: DataField) -> tuple:
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# Gwyddion gwy_tip_erosion:
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# mytip = flip(tip) - max(flip(tip)) (values ≤ 0, apex = 0)
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# result[y,x] = min_{ty,tx}[surface[y+ty, x+tx] - mytip[ty,tx]]
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tip_flipped = np.flipud(np.fliplr(tip.data))
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mytip = tip_flipped - tip_flipped.max() # shift so max = 0
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result = grey_erosion(field.data, structure=mytip)
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return (field.replace(data=result),)
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