rename grains to particle, add colormap adjust, table math

backend/nodes/particle.py

@@ -0,0 +1,76 @@
+"""
+Particle detection nodes.
+
+Gwyddion equivalents:
+  ParticleAnalysis → gwy_data_field_particles_get_values (particles-values.c)
+"""
+
+from __future__ import annotations
+import numpy as np
+from backend.node_registry import register_node
+from backend.data_types import DataField
+
+
+# ---------------------------------------------------------------------------
+# ParticleAnalysis
+# ---------------------------------------------------------------------------
+
+@register_node(display_name="Particle Analysis")
+class ParticleAnalysis:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "field": ("DATA_FIELD",),
+                "mask": ("IMAGE",),
+                "min_size": ("INT", {"default": 10, "min": 1, "max": 100000, "step": 1}),
+            }
+        }
+
+    RETURN_TYPES = ("TABLE",)
+    RETURN_NAMES = ("particle_stats",)
+    FUNCTION = "process"
+    CATEGORY = "particles"
+    DESCRIPTION = (
+        "Label connected particle regions in a binary mask and compute per-particle "
+        "statistics: area, equivalent diameter, mean/max height, bounding box. "
+        "Equivalent to gwy_data_field_particles_get_values."
+    )
+
+    def process(self, field: DataField, mask: np.ndarray, min_size: int) -> tuple:
+        from scipy.ndimage import label
+
+        binary = (mask > 127).astype(np.int32)
+        labeled, n_particles = label(binary)
+
+        pixel_area = field.dx * field.dy  # m^2 per pixel
+
+        rows = []
+        for pid in range(1, n_particles + 1):
+            particle_pixels = labeled == pid
+            area_px = int(particle_pixels.sum())
+            if area_px < min_size:
+                continue
+
+            area_m2 = area_px * pixel_area
+            equiv_diam = float(2.0 * np.sqrt(area_m2 / np.pi))
+
+            heights = field.data[particle_pixels]
+            mean_h = float(heights.mean())
+            max_h = float(heights.max())
+
+            # Bounding box
+            ys, xs = np.where(particle_pixels)
+            bbox = f"({int(xs.min())},{int(ys.min())})-({int(xs.max())},{int(ys.max())})"
+
+            rows.append({
+                "particle_id":  pid,
+                "area_px":      area_px,
+                "area_m2":      area_m2,
+                "equiv_diam_m": equiv_diam,
+                "mean_height":  mean_h,
+                "max_height":   max_h,
+                "bbox":         bbox,
+            })
+
+        return (rows,)