refactor nodes into standalone file

2026-03-26 19:50:03 -07:00
parent 711d7995b3
commit de0b49acc5
54 changed files with 3615 additions and 3710 deletions
--- a/backend/nodes/histogram.py
+++ b/backend/nodes/histogram.py
@@ -0,0 +1,100 @@
+from __future__ import annotations
+import numpy as np
+from backend.node_registry import register_node
+from backend.data_types import DataField, MeasureTable
+
+
+@register_node(display_name="Histogram")
+class Histogram:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "field": ("DATA_FIELD",),
+                "n_bins": ("INT", {"default": 256, "min": 10, "max": 1000, "step": 1}),
+                "y_scale": (["linear", "log"],),
+                "x1": ("FLOAT", {"default": 0.25, "min": 0.0, "max": 1.0, "step": 0.01, "hidden": True}),
+                "y1": ("FLOAT", {"default": 0.5,  "min": 0.0, "max": 1.0, "step": 0.01, "hidden": True}),
+                "x2": ("FLOAT", {"default": 0.75, "min": 0.0, "max": 1.0, "step": 0.01, "hidden": True}),
+                "y2": ("FLOAT", {"default": 0.5,  "min": 0.0, "max": 1.0, "step": 0.01, "hidden": True}),
+            }
+        }
+
+    RETURN_TYPES = ("MEASURE_TABLE", "COORDPAIR",)
+    RETURN_NAMES = ("measurements", "marker pair",)
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Compute the height distribution histogram (DH). "
+        "Use log scale to reveal small peaks next to a dominant background. "
+        "Outputs marker measurements while showing the histogram interactively in-node. "
+        "Equivalent to gwy_data_field_dh."
+    )
+
+    _broadcast_overlay_fn = None
+    _current_node_id: str = ""
+
+    def process(
+        self,
+        field: DataField,
+        n_bins: int,
+        y_scale: str = "linear",
+        x1: float = 0.25,
+        y1: float = 0.5,
+        x2: float = 0.75,
+        y2: float = 0.5,
+    ) -> tuple:
+        raw_counts, bin_edges = np.histogram(field.data.ravel(), bins=int(n_bins))
+        bin_centers = 0.5 * (bin_edges[:-1] + bin_edges[1:])
+        counts = raw_counts.astype(np.float64)
+        if y_scale == "log":
+            counts = np.log10(1.0 + counts)
+
+        x1 = float(np.clip(x1, 0.0, 1.0))
+        x2 = float(np.clip(x2, 0.0, 0.0 + 1.0))
+
+        xmin = float(np.min(bin_centers)) if len(bin_centers) else 0.0
+        xmax = float(np.max(bin_centers)) if len(bin_centers) else 1.0
+
+        def x_frac_to_idx(frac):
+            if len(bin_centers) <= 1:
+                return 0
+            if xmax == xmin:
+                return 0
+            target_x = xmin + frac * (xmax - xmin)
+            return int(np.argmin(np.abs(bin_centers - target_x)))
+
+        idx_a = x_frac_to_idx(x1)
+        idx_b = x_frac_to_idx(x2)
+        xa = float(bin_centers[idx_a]) if len(bin_centers) else 0.0
+        xb = float(bin_centers[idx_b]) if len(bin_centers) else 0.0
+        ya = float(counts[idx_a]) if len(counts) else 0.0
+        yb = float(counts[idx_b]) if len(counts) else 0.0
+        count_unit = "count" if y_scale == "linear" else "log10(1+count)"
+
+        if Histogram._broadcast_overlay_fn is not None:
+            Histogram._broadcast_overlay_fn(
+                Histogram._current_node_id,
+                {
+                    "kind": "line_plot",
+                    "section_title": "Histogram",
+                    "line": counts.tolist(),
+                    "x_axis": bin_centers.astype(np.float64).tolist(),
+                    "x1": float(np.clip(x1, 0.0, 1.0)),
+                    "x2": float(np.clip(x2, 0.0, 1.0)),
+                    "y1": float(y1),
+                    "y2": float(y2),
+                    "a_locked": False,
+                    "b_locked": False,
+                },
+            )
+
+        table = MeasureTable([
+            {"quantity": "A position", "value": xa, "unit": field.si_unit_z},
+            {"quantity": "A count",    "value": ya, "unit": count_unit},
+            {"quantity": "B position", "value": xb, "unit": field.si_unit_z},
+            {"quantity": "B count",    "value": yb, "unit": count_unit},
+            {"quantity": "delta X",    "value": xb - xa, "unit": field.si_unit_z},
+            {"quantity": "delta Y",    "value": yb - ya, "unit": count_unit},
+        ])
+        return (table, ((x1, y1), (x2, y2)))