work on straighten path

backend/nodes/straighten_path.py

@@ -3,10 +3,12 @@
 from __future__ import annotations
 
 import numpy as np
+from scipy.interpolate import CubicSpline
 from scipy.ndimage import map_coordinates
 
 from backend.node_registry import register_node
-from backend.data_types import DataField
+from backend.data_types import DataField, LineData, datafield_to_uint8, encode_preview
+from backend.execution_context import emit_overlay
 
 
 @register_node(display_name="Straighten Path")
@@ -16,8 +18,8 @@ class StraightenPath:
         return {
             "required": {
                 "field": ("DATA_FIELD",),
-                "points_x": ("STRING", {"default": "0.25, 0.5, 0.75"}),
-                "points_y": ("STRING", {"default": "0.5, 0.3, 0.5"}),
+                "points_x": ("STRING", {"default": "0.25, 0.5, 0.75", "hidden": True}),
+                "points_y": ("STRING", {"default": "0.5, 0.3, 0.5", "hidden": True}),
                 "thickness": ("INT", {"default": 1, "min": 1, "max": 100, "step": 1}),
                 "n_samples": ("INT", {"default": 256, "min": 10, "max": 2048, "step": 1}),
             }
@@ -25,14 +27,15 @@ class StraightenPath:
 
     OUTPUTS = (
         ('DATA_FIELD', 'straightened'),
+        ('LINE', 'profile'),
     )
     FUNCTION = "process"
 
     DESCRIPTION = (
         "Extract a cross-section along an arbitrary curved path defined by "
-        "control points. Points are given as fractional coordinates (0-1). "
-        "The path is interpolated with cubic splines, and data is sampled "
-        "along it with configurable thickness. "
+        "control points. The path is a natural cubic spline through the "
+        "points. Drag the points on the preview to reshape the path; the "
+        "shaded band shows the sampling thickness. "
     )
 
     KEYWORDS = ("unbend", "unroll", "spline", "curved profile", "extract path")
@@ -42,36 +45,46 @@ class StraightenPath:
         data = np.asarray(field.data, dtype=np.float64)
         yres, xres = data.shape
 
-        # Parse control points
-        px = [float(v.strip()) * (xres - 1) for v in points_x.split(",") if v.strip()]
-        py = [float(v.strip()) * (yres - 1) for v in points_y.split(",") if v.strip()]
+        fx = [float(v.strip()) for v in points_x.split(",") if v.strip()]
+        fy = [float(v.strip()) for v in points_y.split(",") if v.strip()]
+        n_pts = min(len(fx), len(fy))
+        fx, fy = fx[:n_pts], fy[:n_pts]
 
-        if len(px) < 2 or len(py) < 2:
-            # Need at least 2 points
-            return (field,)
+        emit_overlay({
+            "kind": "straighten_path",
+            "section_title": "Path",
+            "image": encode_preview(datafield_to_uint8(field, field.colormap)),
+            "points": [{"x": float(fx[i]), "y": float(fy[i])} for i in range(n_pts)],
+            "thickness": int(thickness),
+            "xres": int(xres),
+            "yres": int(yres),
+        })
 
-        n_pts = min(len(px), len(py))
-        px, py = px[:n_pts], py[:n_pts]
+        if n_pts < 2:
+            empty_line = LineData(
+                data=np.zeros(0, dtype=np.float64),
+                x_axis=np.zeros(0, dtype=np.float64),
+                x_unit=field.si_unit_xy,
+                y_unit=field.si_unit_z,
+            )
+            return (field, empty_line)
+
+        px = [f * (xres - 1) for f in fx]
+        py = [f * (yres - 1) for f in fy]
 
-        # Parameterize path and interpolate
         t_ctrl = np.linspace(0, 1, n_pts)
         t_sample = np.linspace(0, 1, n_samples)
-
-        # Simple cubic interpolation via numpy
-        if n_pts >= 4:
-            from numpy.polynomial.polynomial import Polynomial
-            cx = np.interp(t_sample, t_ctrl, px)
-            cy = np.interp(t_sample, t_ctrl, py)
+        if n_pts >= 3:
+            cx = CubicSpline(t_ctrl, px, bc_type="natural")(t_sample)
+            cy = CubicSpline(t_ctrl, py, bc_type="natural")(t_sample)
         else:
             cx = np.interp(t_sample, t_ctrl, px)
             cy = np.interp(t_sample, t_ctrl, py)
 
-        # Sample along path with thickness
         if thickness <= 1:
             values = map_coordinates(data, [cy, cx], order=1, mode='nearest')
             result = values.reshape(1, -1)
         else:
-            # Compute normals
             dcx = np.gradient(cx)
             dcy = np.gradient(cy)
             length = np.sqrt(dcx**2 + dcy**2)
@@ -86,12 +99,22 @@ class StraightenPath:
                 sy = cy + off * ny
                 result[i] = map_coordinates(data, [sy, sx], order=1, mode='nearest')
 
-        # Physical dimensions
         total_length = 0.0
         for i in range(1, len(cx)):
             dx_phys = (cx[i] - cx[i - 1]) * field.dx
             dy_phys = (cy[i] - cy[i - 1]) * field.dy
             total_length += np.sqrt(dx_phys**2 + dy_phys**2)
 
-        return (field.replace(data=result, xreal=total_length,
-                              yreal=thickness * max(field.dx, field.dy)),)
+        center_values = map_coordinates(data, [cy, cx], order=1, mode='nearest')
+        profile = LineData(
+            data=center_values,
+            x_axis=np.linspace(0.0, total_length, n_samples),
+            x_unit=field.si_unit_xy,
+            y_unit=field.si_unit_z,
+        )
+
+        straightened = field.replace(
+            data=result, xreal=total_length,
+            yreal=thickness * max(field.dx, field.dy),
+        )
+        return (straightened, profile)