32 lines
1.6 KiB
Markdown
32 lines
1.6 KiB
Markdown
# Terrace Fit
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Segment a surface into flat terraces separated by atomic steps, fit a polynomial to each terrace, and extract step heights. Set n_terraces=0 for automatic detection via histogram clustering. Equivalent to Gwyddion's terracefit.c module.
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## Inputs
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| Name | Type | Required | Description |
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|------|------|----------|-------------|
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| field | DATA_FIELD | Yes | Input surface with step/terrace features |
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## Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| result | DATA_FIELD | Residual, fitted surface, or label map |
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| step_heights | RECORD_TABLE | Per-terrace heights and step height differences |
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## Controls
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| Name | Type | Default | Description |
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|------|------|---------|-------------|
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| n_terraces | INT | 0 | Number of terraces to fit; 0 = auto-detect from histogram peaks (0–50) |
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| broadening | FLOAT | 1.0 | Smoothing factor for terrace detection; larger values merge noisy pixels (0.1–20.0) |
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| poly_degree | INT | 0 | Polynomial degree per terrace: 0 = constant (flat), 1 = linear, 2 = quadratic, 3 = cubic (0–3) |
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| output | dropdown | residual | Output mode: residual (original minus fit), fitted (fit surface), or labels (terrace assignment map) |
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## Notes
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- Use poly_degree=0 for ideal crystalline surfaces with perfectly flat terraces. Higher degrees compensate for sample curvature within each terrace.
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- Auto-detection works best when terraces are well-separated in height. For noisy surfaces, increase broadening to improve terrace segmentation.
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- The labels output assigns integer IDs (0, 1, 2, ...) to each terrace, ordered by height.
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