synthetic surface and spm specific features

backend/nodes/lateral_force_sim.py

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+"""Lateral Force Simulation — topography artifacts in friction channels."""
+
+from __future__ import annotations
+
+import numpy as np
+
+from backend.node_registry import register_node
+from backend.data_types import DataField
+
+
+@register_node(display_name="Lateral Force Simulation")
+class LateralForceSim:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "field": ("DATA_FIELD",),
+                "direction": (["forward", "reverse", "both"],),
+                "friction_coefficient": ("FLOAT", {
+                    "default": 0.3, "min": 0.0, "max": 10.0, "step": 0.01,
+                }),
+                "adhesion": ("FLOAT", {
+                    "default": 1e-9, "min": 0.0, "max": 1e-6, "step": 1e-12,
+                }),
+                "load": ("FLOAT", {
+                    "default": 10e-9, "min": 1e-12, "max": 1e-6, "step": 1e-12,
+                }),
+            }
+        }
+
+    OUTPUTS = (
+        ('DATA_FIELD', 'forward'),
+        ('DATA_FIELD', 'reverse'),
+    )
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Simulates topography-induced artifacts in lateral force (friction) "
+        "microscopy channels. Computes the lateral force signal from surface "
+        "slope, friction coefficient, adhesion, and normal load for forward "
+        "and/or reverse scan directions. Based on a contact-mechanics model "
+        "where the measured lateral force depends on the local tilt angle of "
+        "the sample surface."
+    )
+
+    def process(
+        self,
+        field: DataField,
+        direction: str,
+        friction_coefficient: float,
+        adhesion: float,
+        load: float,
+    ) -> tuple:
+        data = np.asarray(field.data, dtype=np.float64)
+
+        # Surface slope angle from x-gradient of topography
+        dz_dx = np.gradient(data, axis=1)
+        theta = np.arctan2(dz_dx, field.dx)
+
+        sin_theta = np.sin(theta)
+        cos_theta = np.cos(theta)
+
+        va = load * sin_theta
+        vc = cos_theta
+        vb = friction_coefficient * (load * vc + adhesion)
+        vd = friction_coefficient * sin_theta
+
+        # Forward scan (tip moves in +x)
+        denom_fwd = vc - vd
+        safe_fwd = np.abs(denom_fwd) >= 1e-30
+        lateral_forward = np.where(safe_fwd, (va + vb) / np.where(safe_fwd, denom_fwd, 1.0), 0.0)
+
+        # Reverse scan (tip moves in -x)
+        denom_rev = vc + vd
+        safe_rev = np.abs(denom_rev) >= 1e-30
+        lateral_reverse = np.where(safe_rev, -(va - vb) / np.where(safe_rev, denom_rev, 1.0), 0.0)
+
+        if direction == "forward":
+            lateral_reverse = lateral_forward.copy()
+        elif direction == "reverse":
+            lateral_forward = lateral_reverse.copy()
+
+        out_fwd = field.replace(data=lateral_forward, si_unit_z="N")
+        out_rev = field.replace(data=lateral_reverse, si_unit_z="N")
+
+        return (out_fwd, out_rev)