add nodes, fft acf 1d

backend/nodes/acf_1d.py

@@ -0,0 +1,61 @@
+from __future__ import annotations
+
+import numpy as np
+
+from backend.node_registry import register_node
+from backend.data_types import LineData, MeasureTable
+from backend.nodes.spectral_common import acf_line_from_data
+
+
+def _first_positive_peak(acf: np.ndarray, lag_axis: np.ndarray) -> float | None:
+    """Return the lag of the first local maximum in the positive-lag half of the ACF."""
+    center = len(acf) // 2
+    pos_acf = acf[center + 1:]
+    pos_lags = lag_axis[center + 1:]
+    for i in range(1, len(pos_acf) - 1):
+        if pos_acf[i] >= pos_acf[i - 1] and pos_acf[i] > pos_acf[i + 1]:
+            return float(pos_lags[i])
+    return None
+
+
+@register_node(display_name="ACF 1D")
+class ACF1D:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "profile": ("LINE", {
+                    "label": "input",
+                    "accepted_types": ["LINE"],
+                }),
+                "level": (["mean", "none"], {"default": "mean"}),
+            }
+        }
+
+    OUTPUTS = (
+        ('LINE', 'acf'),
+        ('MEASURE_TABLE', 'measurement'),
+    )
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Compute the one-dimensional autocorrelation function of a line profile. "
+        "The output is symmetric about zero lag with the lag on the x-axis. "
+        "The measurement table reports the dominant period from the first positive peak."
+    )
+
+    def process(self, profile: LineData, level: str) -> tuple:
+        z = np.asarray(profile, dtype=np.float64)
+        if level == "mean":
+            z = z - z.mean()
+
+        acf_line = acf_line_from_data(profile, z)
+
+        x_unit = profile.x_unit if isinstance(profile, LineData) else ""
+        peak_lag = _first_positive_peak(acf_line.data, acf_line.x_axis)
+
+        rows = []
+        if peak_lag is not None:
+            rows.append({"quantity": "Peak period", "value": peak_lag, "unit": x_unit})
+
+        return (acf_line, MeasureTable(rows))